text:
Orbit determination and time synchronization for BDS-3 satellites with raw inter-satellite link ranging observations
Rengui Ruan ORCID: orcid.org/0000-0001-9704-44881,2,3,
Xiaolin Jia1,2,
Laiping Feng1,2,
Jun Zhu4,5,
Zongbo Huyan4,5,
Jie Li4,5 &
Ziqing Wei1,2
Satellite Navigation volume 1, Article number: 8 (2020) Cite this article
To provide competitive global positioning and timing services under the condition that monitoring stations are confined to Chinese territory, inter-satellite link (ISL) technology is used by the third-generation BeiDou Navigation Satellite System (BDS-3). The ISL, together with the dual one-way links between satellites and anchor stations, may enable autonomous navigation for BDS-3. In this paper, we propose a general observation model for orbit determination (OD) and time synchronization (TS) directly using non-simultaneous observations, such as raw ISL pseudoranges. With the proposed model, satellite orbits, clocks, and hardware delay biases of ISL equipment can be determined simultaneously by jointly processing inter-satellite one-way pseudorange data and observation data from ground monitoring stations. Moreover, autonomous OD and TS are also achievable with one-way pseudorange data from anchor stations and satellites. Data from eight BDS-3 satellites, two anchor stations, and seven monitoring stations located in China were collected to validate the proposed method. It is shown that by jointly processing data from the ISL and seven monitoring stations, the RMS of overlap orbit differences in radial direction is 0.019 m, the overlap clock difference (95%) is 0.185 ns, and the stability of the estimated hardware delay biases for each satellite is greater than 0.5 ns. Compared with the results obtained with the seven stations, the improvements of orbits in radial direction and clocks are 95.7% and 90.5%, respectively. When the hardware delay biases are fixed to predetermined values, the accuracies of orbits and clocks are further improved. By jointly processing pseudoranges from the satellites and the two anchor stations, the RMS of overlap orbit differences is 0.017 m in the radial direction, and the overlap clock difference (95%) is 0.037 ns. It has also been demonstrated that under the condition of one-way ranging links, the accuracies of orbits and clocks obtained by the above two modes are still significantly better than those obtained by using the data from the monitoring stations alone.
To enhance orbit determination (OD) and time synchronization (TS) under the condition of regional monitoring stations, the third-generation BeiDou Navigation Satellite System (BDS-3) employs inter-satellite link (ISL) technology which also enable autonomous navigation. The feasibility and performance of the ISL in BDS-3 have been verified with the in-orbit validation satellites [1,2,3,4,5,6,7]. Recent findings show that with the ISL ranging data, the radial orbit accuracy of 10 cm is achievable [2].
Phased array antennas on BDS-3 satellites receive and transmit ISL signals in Ka-band and control the beam pointing of the signal. The Ka-band signal with frequencies more than 10 times the L-band signal would provide greater communication bandwidth and make the ISL antennas smaller in size, which make it preferred for ISL. The ISL of BDS-3 satellites operates in a time-division multiple access (TDMA) mode, i.e., at any time (slot), one satellite can only communicate and perform ranging measurement with another satellite according to the pre-set link planning. Pseudorange measurements observed at one satellite to others are generated in different time slots.
In existing methods of OD or TS for Global Navigation Satellite System (GNSS) satellites with ISL ranging data, the raw non-simultaneously observed pseudoranges are not directly used. Instead, in a typical approach originally proposed for autonomous OD and TS [8], observations are derived at specified times, and then the derived clock measurement (DCM) and the derived ephemeris measurement (DEM) are formed to separate geometry information and clock information [8,9,10,11]. The DEMs are used for OD alone [2, 5,6,7,8,9, 12,13,14] or together with other data such as the monitoring station data [3] and the inter-satellite orientation observations [15], while the DCMs are used for TS [4]. Therefore, OD and TS are performed independently. In another approach, OD and TS are performed simultaneously by directly processing the one-way derived ISL observations together with the monitoring station data [16,17,18]. An advantage of the latter method is that the hardware delay biases of ISL equipment of each satellite can be estimated together with satellite orbits and clocks. However, the latter has only been used in simulation studies at present, and there have been no reports on the application for BDS-3.
A method to directly process raw one-way ISL pseudoranges for OD and TS of BDS-3 satellites was proposed by Ruan [19, 20]. In this paper, the principal of this method will be presented in detail, and its feasibility will be demonstrated with two typical modes for OD and TS: (1) jointly processing the ISL pseudorange data and the L-band pseudorange and carrier phase data from monitoring stations, and (2) jointly processing the Ka-band ISL pseudorange data between satellites and the Ka-band pseudorange data between satellites and anchor stations. The anchor station refers to a station equipped with ISL equipment and can perform communication and ranging with BDS-3 satellites, just as the satellites do. Besides, it will be demonstrated that the proposed OD and TS method is achievable even under the condition of one-way ranging links between satellites (and between satellites and anchor stations).
Observation equation for ISL pseudoranges
The ISL pseudorange observations of satellite \( j \) observed by satellite \( i \) at time \( t^{i,j} \) are expressed as
$$ P^{i,j} (t^{i,j} )= \left| {\varvec{R}^{i} (t^{i,j} )- \varvec{R}^{j} (t^{i,j} - \tau^{i,j} )} \right| + \delta^{i} (t^{i,j} )- \delta^{j} (t^{i,j} { - }\tau^{i,j} )+ \Delta^{j} + \beta^{i} + \omega , $$
where \( \tau^{i,j} \) is the propagation time of ISL signal from satellite \( j \) to satellite \( i \); \( \varvec{R}^{i} \) and \( \varvec{R}^{j} \) are the instantaneous positions of satellite \( i \) and \( j \) at the receiving and transmitting times, respectively; \( \delta^{i} \) and \( \delta^{j} \) are the clock offsets of satellite \( i \) and \( j \), respectively; \( \Delta^{j} \) and \( \beta^{i} \) are the transmitting and receiving hardware delays of satellite \( j \) and \( i \), respectively, considered to be stable in time, and ω is the measurement noise [2, 17]. Equation (1) omits terms such as relativistic delay of signal propagation and satellite antenna phase center offsets.
Equation (1) can also be used for the pseudorange observations between BDS-3 satellites and anchor stations, when the troposphere delay and ionosphere delay are taken into account. Since the BDS-3 ISL runs in Ka-band, pseudorange observations between satellites or between satellites and anchor stations are uniformly referred to as Ka-pseudoranges.
Observation equation for pseudoranges and phases at monitoring stations
Without losing generality, ionosphere-free carrier phase \( L_{r}^{i} \) and pseudorange \( P_{r}^{i} \) of satellite \( i \) observed by station (receiver) \( r \) at the time \( t_{k} \) can be expressed as
$$ \begin{aligned} L_{r}^{i} (t_{k} ) & = \left| {\varvec{R}_{r} (t_{k} ) - \varvec{R}^{i} (t_{k} - \tau_{r}^{i} )} \right| + \theta_{r,k} - \theta_{k}^{i} + T_{r}^{i} + a_{r}^{i} + \varepsilon \\ P_{r}^{i} (t_{k} ) & = \left| {\varvec{R}_{r} (t_{k} ) - \varvec{R}^{i} (t_{k} - \tau_{r}^{i} )} \right| + \theta_{r,k} - \theta_{k}^{i} + T_{r}^{i} + \xi \\ \end{aligned} , $$
where \( k \) is the observation epoch; \( \tau_{r}^{i} \) is the propagation time of signal from satellite \( i \) to station \( r \); \( \varvec{R}_{r} \) is the instantaneous position of the station at the receiving time; \( \theta_{r,k} = \delta_{r,k} + b_{r} \) and \( \theta_{k}^{i} = \delta_{k}^{i} - b^{i} \) are the estimable clock parameters for the station and the satellite, i.e., superposition of the clock offset (\( \delta_{r,k} \) and \( \delta_{k}^{i} \)) and the ionosphere free combination of hardware group delay (\( b_{r} \) and \( b^{i} \)); \( a_{r}^{i} \) is the ionosphere-free phase ambiguity parameter, including the hardware phase and group delays; \( T_{r}^{i} \) is the troposphere delay; \( \varepsilon \) and \( \xi \) are measuring errors of carrier phase and pseudorange measurements, respectively [21]. Equation (2) omits the correction terms of relativistic delay, phase wind-up effect and antenna phase centre offsets of the satellite and the station.
General observation equation for non-simultaneous observations
Pseudoranges and carrier phases [Eq. (2)] and Ka-pseudoranges [Eq. (1)] are radio measurements that contains clock offsets of the signal transmitting and receiving devices. In order to directly process the non-simultaneous observation data, such as the raw Ka-pseudorange observations of ISL, a general observation model is proposed in this section.
Continuous time is divided into discrete non-overlapping time slots with length of \( w \). In any time slot k, the behavior of clocks on transmitting or receiving devices can be modeled with a polynomial, thus, clock offsets at any time t within time slot k are, according to Ruan [19],
$$ \delta^{i} (t) = \delta_{k}^{i} + \dot{\delta }_{k}^{i} \cdot (t - t_{w,k} ) + \ddot{\delta }_{k}^{i} \cdot (t - t_{w,k} )^{2} + \cdots , $$
where tw,k is the selected reference time for the time slot k and is preferably at the middle point of the time slot. \( \delta_{k}^{i} \) is the zero-order coefficient of the polynomial, i.e., clock bias at tw,k; \( \dot{\delta }_{k}^{i} \) and \( \ddot{\delta }_{k}^{i} \) are first and second order coefficients, i.e., drift and acceleration of the clock, respectively. Terms of higher order are omitted in Eq. (3) (usually terms higher than the second order can be safely ignored). In practice, accurate modeling of long-term changes of clocks using polynomials is challenging. In order to control the error of the clock polynomial models, the length of time slots should not be too long, depending on the frequency instability of an individual clock. For example, in a short time period, such as a few minutes, the clock of a GNSS satellite can usually be modeled using a linear polynomial, with adequate precision.
In this way, a radio measurement \( O^{r,e} \) for a transmitting device \( e \) observed at \( t^{r,e} \) by the receiving device \( r \) can be expressed as, according to Ruan [19],
$$ O^{r,e} (t^{r,e} )= \rho^{r,e} + \left[ {\delta_{k}^{r} { + }\dot{\delta }_{k}^{r} \cdot (\Delta t^{r,e} ) { + } \cdots } \right] - \left[ {\delta_{k}^{e} { + }\dot{\delta }_{k}^{e} \cdot (\Delta t^{r,e} - \tau^{r,e} ) { + } \cdots } \right] + \omega_{o} , $$
where \( t^{r,e} \) is within the time slot k, \( \Delta t_{k}^{r,e} = t^{r,e} - t_{w,k} \) is the difference between observing time and the reference time \( t_{w,k} \), \( \rho^{r,e} \) is the distance from a transmitting antenna to a receiving antenna, and \( \omega_{0} \) is the measuring error. The above formula does not include other factors that may affect the observation.
Specifically, if clock offsets are modeled with linear polynomials, the observation equation, Eq. (1), for Ka-pseudoranges observed at time \( t^{i,j} \), which is within the time slot k, can be rewritten as
$$ \begin{aligned} P^{i,j} (t^{i,j} )& = \left| {\varvec{R}^{i} (t^{i,j} )- \varvec{R}^{j} (t^{i,j} - \tau^{i,j} )} \right| \\ & \quad + \,\left[ {\delta_{k}^{i} + \dot{\delta }_{k}^{i} \cdot (\Delta t_{k}^{i,j} )} \right] - \left[ {\delta_{k}^{j} + \dot{\delta }_{k}^{j} \cdot (\Delta t_{k}^{i,j} - \tau^{i,j} )} \right] + \Delta^{j} + \beta^{i} + \omega \\ \end{aligned} . $$
Thus, for any satellite-pair, all Ka-pseudoranges within the same time slot share the same clock parameters, although they are observed at different times. For example, a satellite's clock parameters are first and second order coefficients in Eq. (5). The non-simultaneously observed Ka-pseudoranges of satellites (and anchor stations) can be directly processed separately or jointly with other tracking data, estimation of orbits, clocks, and even hardware delay biases can be achieved simultaneously.
In practice, the drift of satellite clocks can usually be predicted with a relatively high accuracy; therefore, the first order coefficients of clock models in Eq. (5) can be replaced by predicted values. For example, the uncertainty of predicted clock drift of a BDS satellite is less than \( 1 \times 10^{ - 13} \,{\text{s}}/{\text{s}} \) [2], and if the linear variation of the clock is corrected with the predicted clock drift, the resulting modeling error is less than 2 mm for time slots with length less than 1 min. In extreme cases without predicted clock drift, clock variation during short durations can even be directly ignored. Therefore, with predicted clock drift or by ignoring the clock variation, Eq. (5) is simplified to
$$ P^{i,j} (t^{i,j} ) = \left| {\varvec{R}^{i} (t^{i,j} ) - \varvec{R}^{j} (t^{i,j} - \tau^{i,j} )} \right| + \delta_{k}^{i} - \delta_{k}^{j} + \Delta^{j} + \beta^{i} + \bar{\omega }, $$
where \( \bar{\omega } \) is the sum of measuring error and additional errors caused by predicted clock drift or ignoring the clock drift.
The conventional observation model for pseudorange and phase observations observed at monitoring stations, such as in Eq. (2), can be regarded as a special case of Eq. (4) because each time slot contains only one epoch; thus, the model for the receiver clock is simplified with only the zero-order term. For any satellite, the time difference of signal transmitting corresponding to observations simultaneously observed by different stations at the same epoch is very small (i.e., much less than 1 s), so the variation of satellite clock can also be completely ignored.
Orbit determination and time synchronization of BDS-3 satellites
For OD and TS of the BDS-3 satellites, there are several types of tracking data that can be used, including pseudoranges and carrier phases observed at monitoring stations, mainly located within Chinese territory, Ka-pseudoranges observed at satellites and anchor stations, and two-way satellite time frequency transferring data between stations and satellites. For the proposed general observation model, the orbits and clocks of BDS-3 satellites can theoretically be determined by independently processing any type of tracking data or jointly processing several data types. This paper focuses on two modes for OD and TS:
Mode-1 Jointly processing ISL Ka-pseudoranges observed from satellites and observation data from monitoring stations;
Mode-2 Processing Ka-pseudoranges observed from both satellites and anchor stations.
In Mode-1, satellite orbits, clocks, and the hardware delay biases of each satellite are determined simultaneously [17]. This is a significant mode for BDS-3 and may be the best OD and TS mode, as it is an important and self-consistent method, which can resolve the inconsistency of hardware delays of the ISL equipment and the navigation signal generation equipment. In order to construct the joint observation model with both ISL data and the data from monitoring stations, the simplest method is to adopt the observation epoch time \( t_{k} \) of the monitoring station as the reference time of specific time slots; i.e., \( t_{w,k} = t_{k} \). Thus, the zero-order coefficient of the clock polynomial is exactly the clock offset \( \theta_{k}^{i} \) at the time \( t_{k} \). Omitting detailed derivation, joint observation equation with ISL Ka-pseudoranges and ionosphere-free pseudoranges, and phases at time slot \( k \) centered on its reference time \( t_{k} \) is expressed as follows:
$$ \begin{aligned} L_{r}^{i} (t_{k} ) & = \left| {\varvec{R}_{r} (t_{k} ) - \varvec{R}^{i} (t_{k} - \tau_{r}^{i} )} \right| + \theta_{r,k} - \theta_{k}^{i} + T_{r}^{i} + b_{r}^{i} + \varepsilon \\ P_{r}^{i} (t_{k} ) & = \left| {\varvec{R}_{r} (t_{k} ) - \varvec{R}^{i} (t_{k} - \tau_{r}^{i} )} \right| + \theta_{r,k} - \theta_{k}^{i} + T_{r}^{i} + \xi \\ P^{i,j} (t^{i,j} ) & = \left| {\varvec{R}^{i} (t^{i,j} ) - \varvec{R}^{j} (t^{i,j} - \tau^{i,j} )} \right| \\ & \quad + \,\left[ {\theta_{k}^{i} + \dot{\theta }_{k}^{i} \cdot \Delta t_{k}^{i,j} } \right] - \left[ {\theta_{k}^{j} + \dot{\theta }_{k}^{j} \cdot (\Delta t_{k}^{i,j} - \tau^{i,j} )} \right] + \Delta_{b}^{j} + \beta_{b}^{i} + \bar{\omega } \\ \end{aligned} , $$
where \( - \frac{w}{2} \le t^{i,j} - t_{k} < \frac{w}{2} \), \( \dot{\theta }_{k}^{*} \) is the clock drift; \( \Delta_{b}^{*} = \Delta^{*} - b^{*} \) and \( \beta_{b}^{*} = \beta^{*} + b^{*} \) are the transmitting and receiving hardware delay biases for ISL equipment on satellite \( * \) (\( = i,j \)) [17], referred to as transmitting and receiving Ka-biases, respectively, in this context. The definition of Ka-biases and the estimation method are presented in Ruan et al. [16, 17]. In Eq. (7), the observation time of the Ka-pseudoranges is usually different from the sampling time of the L-band pseudorange and phase data, but they share the same clock parameters. After modeling and linearization, unknown parameters such as satellite orbit, clock parameters, and Ka-biases are solved simultaneously, e.g., with the least square method.
Mode-2 uses Ka-pseudoranges observed from both satellites and anchor stations, and is usually referred to as (centralized) autonomous OD and TS [2, 10]. The observation equations are
$$ \begin{aligned} P^{i,j} (t^{i,j} ) & = \left| {\varvec{R}^{i} (t^{i,j} ) - \varvec{R}^{j} (t^{i,j} - \tau^{i,j} )} \right| \\ & \quad + \,\left[ {\theta_{k}^{i} + \dot{\theta }_{k}^{i} \cdot (\Delta t_{k}^{i,j} )} \right] - \left[ {\theta_{k}^{j} + \dot{\theta }_{k}^{j} \cdot (\Delta t_{k}^{i,j} - \tau^{i,j} )} \right] + \bar{\omega } \\ P^{i,a} (t^{i,a} ) & = \left| {\varvec{R}^{i} (t^{i,a} ) - \varvec{R}^{a} (t^{i,a} - \tau^{i,a} )} \right| \\ & \quad + \,\left[ {\theta_{k}^{i} + \dot{\theta }_{k}^{i} \cdot (\Delta t_{k}^{i,a} )} \right] - \left[ {\theta_{k}^{a} + \dot{\theta }_{k}^{a} \cdot (\Delta t_{k}^{i,a} - \tau^{i,a} )} \right] + T_{a}^{i} + \bar{\omega } \\ \end{aligned} , $$
where \( a \) represents anchor stations and \( T_{a}^{i} \) is the troposphere delay in Ka-pseudoranges between satellites and anchor stations. Ka-biases are not present in Eq. (8) because they are linearly correlated with the clock parameters when Ka-pseudoranges are used alone and must be calibrated with known values, e.g., estimates obtained by Mode-1, to achieve an unbiased clock solution for positioning and timing applications.
Data set and experimental scheme
To validate the proposed approach, the Ka-pseudorange data from eight BDS-3 satellites (B19–B22, B27–B30), two anchor stations (A01 and A02), and the pseudorange and carrier phase data from B1I and B3I frequency from seven monitoring stations of the International GNSS Monitoring and Assessment System (iGMAS) during days 152–163 of 2018 were collected. The distribution of the iGMAS stations used in the experiment is shown in Fig. 1.
The distribution of the iGMAS stations. The X- and Y-axis are longitude and latitude in degrees, respectively. The distance between the furthest stations is approximately 1700 km
Table 1 shows the signal transmission and reception between satellites or between satellites and anchor stations during the data arc. It can be seen that each satellite has a bidirectional inter-satellite measurement link with 5–6 satellites, and each satellite has a bidirectional measurement link with the two anchor stations, except satellite B30.
Table 1 Measurement relationships between satellites or between satellites and anchor stations
With the above data, validation of OD and TS was performed by the following experiments:
EXP1: Only data from the iGMAS stations were used.
EXP2: Data from the iGMAS stations and Ka-pseudoranges between satellites were jointly processed with Ka-biases of each satellite estimated simultaneously.
EXP3: Data from the iGMAS stations and Ka-pseudoranges between satellites were jointly processed with Ka-biases of each satellite calibrated with the mean estimated values obtained in EXP2.
EXP4: Ka-pseudoranges from satellites and anchor stations were processed with Ka-biases of each satellite and anchor station calibrated with the mean estimated values in EXP2 and the estimated values from literature [19], respectively.
Data were processed with the SPODS software [22, 23] on a daily basis with 72-h data started on each day. Time slots of 1 min were assigned every 5 min and centered on the sampling epoch, i.e., for the data from monitoring stations, the sampling interval was 5 min. The coordinates of the iGMAS stations, anchor stations, and the earth rotation parameters were fixed to known values. The following orbital dynamics were carefully modeled: gravity of the earth computed with the EGM2008 up to degree and order 12, with linear variation of low-degree coefficients and periodical variation caused by the solid earth tides and the pole tide [24], gravity of the third-bodies (the moon, sun, and planets) computed with JPL ephemeris DE405, and the general relativistic effects. For each satellite, without any a priori model, the ECOM model [25] was used to model the force acting on the satellites from solar radiation pressure with five parameters (\( D_{0} ,Y_{0} ,B_{0} ,B_{c} \), and \( B_{s} \)), estimated together with the initial state vector. The Saastamoinen model [24] was used to calculated the hydrostatic zenith troposphere delay, with wet zenith delay parameter estimated every 2 h for the monitoring stations and every 24 h for anchor stations. The Global Mapping Function [26] was adopted to map the troposphere delay from the zenith to the line of sight. The satellite clock drift was replaced with the first order coefficient of the broadcast clock correction model. In order to remove the rank defects caused by clock parameters, one clock parameter was chosed as the reference and constrained to 0 in each time slot. Since none of the monitoring stations, anchor stations, and satellites have observation data covering the whole arc, reference clock often changes in different time slots and can be a monitoring station, satellite, or an anchor station, at a certain time slot, depending on their observation number. In EXP2 and EXP5 (see "Orbit determination and time synchronization with single one-way ISL" section), one Ka-bias is chosen as the reference and constrained to 0 because not all Ka-biases are estimable, e.g., the receiving Ka-bias of B21. The pseudoranges and phases of the monitoring stations are weighted according to a prior precisions of 2 m and 0.02 m, respectively, and the Ka-pseudorange is weighted according to a prior precision of 0.1 m.
In order to evaluate the accuracy of the obtained orbits and clocks, differences of values in a 48-h overlap arc of adjacent solutions are calculated. The RMS differences for orbits are computed as an indicator of orbit accuracy. Mean value of differences over all satellites are firstly computed and deducted from the original overlapping differences at each epoch; then, the 95th percentile of the resultant differences is an indicator of clock accuracy.
Figure 2 shows the RMSs in R, T, and N directions for each satellite obtained by the four experiments (note that the RMSs of EXP2, EXP3 and EXP4 have a tenfold magnification). It can be seen that in EXP1, the RMSs are larger than 0.3 m for R, larger than 1 m for T, and range from 1.2 to 2.3 m for N. In EXP2, the RMSs are smaller than 0.025 m in R, are not larger than 0.1 m for T, and are not larger than 0.15 m for N. With the Ka-biases of each satellite fixed to the multi-day average estimation in EXP2, the orbit accuracy in EXP3 is further improved. In EXP4, the orbit accuracy in R is very close to those in EXP2 and EXP3 for each individual satellite. However, the orbit accuracies in T and N are worse than those of EXP2 and EXP3, as there are only two anchor stations leading to looser constraints on the constellation orientation.
RMS of overlap orbit differences in R, T, and N for each satellite. The values of EXP2, EXP3, and EXP4 have a tenfold magnification to illustrate the differences between them
Figure 3 shows the clock accuracy measured with overlap differences (95%) for each satellite in the four experiments. It can be seen that in EXP1 the clock accuracy for each satellite is between 1.5 and 2.5 ns. The accuracies for each satellite are better than 0.25 ns and 0.07 ns for EXP2 and EXP3, respectively, and the accuracy for each satellite in EXP4 is better than that in EXP3.
Overlap clock differences (95%) in the 4 experiments for each satellite. The values of EXP2, EXP3 and EXP4 have a tenfold magnification to illustrate the differences
Table 2 shows the accuracies of orbits and clocks obtained by different schemes. Compared with EXP1, improvements of orbit accuracies in EXP2 are 95.7%, 94.5%, 92.6%, and 93.4% in R, T, N, and 3D position, respectively. While, in EXP3, improvements of 95.7%, 94.5%, 92.6%, and 93.4% are achieved for R, T, N, and 3D position, respectively. In EXP4, the orbit accuracy in the R direction for each satellite is close to that in EXP3 but less than those of EXP2 and EXP3 in T and N directions. For satellite clocks, compared with EXP1, the accuracies are improved by 90.5% and 97.2% in EXP2 and EXP3, respectively. Since the overlap clock differences in EXP2 include the difference of estimated Ka-biases, the nominal accuracy of clocks is less than those in EXP3 and EXP4. The orbit accuracy in EXP4 is less than those in EXP3 and EXP2 but the clock accuracy is greater, implying model inaccuracies. For example, there may be biases of the antenna phase center for the Ka-band and the L-band, or there may be non-ignorable variation of the hardware delay for the Ka-band and the L-band signal.
Table 2 Accuracies of orbits and clocks obtained by different OD and TS schemes
Figure 4 shows the variations of estimated receiving and transmitting Ka-biases of each satellite obtained in EXP2 with the bias removed for each individual satellite, so all the values are within the range of the y-axis. The Ka-biases of each satellite are stable in time. In Table 3, the standard deviation (SD) of the receiving and transmitting hardware biases for each satellite is smaller than 0.15 m (or equally 0.5 ns).
Variations of estimated receiving and transmitting Ka-biases for ISL equipment of each satellite obtained in EXP2. A large bias has been removed for each individual satellite, so all the values of all satellites are within the range of the y-axis
Table 3 Repeatability of the estimated Ka-biases for each satellite obtained in EXP2 (unit: m)
Figure 5 shows the RMS of residuals for one-way Ka-pseudoranges observed at each satellite or anchor station in EXP2, EXP3, and EXP4. The RMSs of all satellites are smaller than 0.08 m; the RMSs for satellite B27–B30 are larger than those of other satellites, and satellite B28 has the largest RMS. The RMSs of individual satellites from different experiments are very close to each other. In EXP2, the average RMS is 0.054 m for all satellites, while it is 0.040 m for B19–B22 and 0.067 m for B27–B28. It can be seen that the RMSs of the two anchor stations are larger than those of the satellites. It is noticed that the RMSs for satellite B27–B30 in EXP2 and EXP3 are larger than those in EXP4, which may also be due to incorrect assumptions for the stability of hardware delays.
The RMS of residuals of one-way Ka-pseudoranges observed at each satellite or anchor station in EXP2, EXP3, and EXP4
Figure 6 shows the percentage of valid one-way Ka-pseudorange data in EXP3 and EXP4 for each satellite or anchor station. The percentage of valid data received or transmitted at satellites and anchor stations is more than 97% and the percentage of valid data received at B28 is the lowest. In EXP4, the percentage for each satellite is larger than that in EXP3. The average percentage for all satellites is 98.82% in EXP3 and 99.55% in EXP4. This also confirms that there are possible modeling errors, when the Ka-band data and the L-band monitoring data are jointly processed.
The percentage of valid one-way Ka-pseudorange data in EXP3 and EXP4 for each satellite or anchor station. R and E in the legend represent reception and transmission, respectively
Orbit determination and time synchronization with single one-way ISL
Compared to the existing methods, only single one-way ranging data is necessary for OD and TS in the proposed method. In order to prove this point, EXP5, EXP6, and EXP7 were performed with the same data processing strategies as used in EXP2, EXP3, and EXP4, but only single one-way Ka-pseudorange data from measurement links were used (denoted by the red "√" in Table 1).
The accuracies of orbits for each satellite in EXP5, EXP6, and EXP7 are shown in Fig. 7. We can see that, the accuracies of orbits in each component in all experiments are all greater than 0.05 m. As expected, the accuracies in EXP6 are slightly higher than those in EXP5, and the accuracies are greater than 0.04 m, 0.1 m, and 0.2 m in R, T, and N, respectively, for both experiments. In EXP7, the orbit accuracy in R is similar to those in EXP5 and EXP6, but the accuracies in T and N are about 0.3 m and much worse than those in EXP5 and EXP6, for the same reason mentioned above.
The accuracies in R, T, and N of the orbits for each satellite obtained in EXP5, EXP6, and EXP7
Figure 8 compares the clock accuracies obtained by different processing modes under the condition of single or double one-way Ka-pseudoranges. It can be seen that in EXP5, the clock accuracies of different satellites are between 0.2 and 0.35 ns, and the clock accuracies obtained by EXP6 and EXP7 are similar, and all of them are no more than 0.2 ns.
Comparison of clock accuracies obtained by different experiments
Table 4 shows the accuracies for orbits and clocks obtained by EXP5, EXP6, and EXP7. It can be seen that the orbit accuracy in R is greater than 0.027 m in the three experiments, and the accuracies are decreased by up to 60% compared with those obtained with double one-way data. In other words, the radial orbital accuracies are improved by up to 40% using double one-way data. The clock accuracies obtained by the three experiments are greater than 0.3 ns and greater than 0.16 ns in EXP6 and EXP7. Compared with the results obtained with double one-way data as shown in Table 3, the clock accuracies decreased by 42%, 183%, and 297% in EXP5, EXP6, and EXP7, respectively. This implies that the clocks benefit more from double one-way data than the orbits do.
Table 4 Accuracies for orbits and clocks obtained by different OD and TS schemes under the condition of single one-way Ka-pseudoranges
Table 5 provides the repeatability of the estimated Ka-biases for each satellite obtained by EXP5 and the differences between the mean estimated Ka-biases obtained by EXP5 and those obtained by EXP2. The SDs of the obtained receiving biases in EXP5 do no exceed 0.18 m and the differences compared with those in EXP2 are less than 0.082 m. For the transmitting biases, the SDs are smaller than 0.14 m while the differences do not exceed 0.04 m.
Table 5 Repeatability of the estimated Ka-biases for each satellite obtained by EXP5 and the differences (denoted by ▽) between the mean estimated Ka-biases obtained by EXP5 and those obtained by EXP2
Since the ISL of BDS-3 runs in a TDMA mode, the Ka-pseudorange observations at a certain satellite are generated at different times, and each observation contains two unique clock offset parameters that remove redundant observations. Existing methods for OD and TS with ISL data firstly derive the raw Ka-pseudorange observations from different times to some specified time epoch, and then the DCMs and the DEMs are formed to separate the orbit and clock information so that OD and TS are separated [17]. This idea has been first proposed by Ananda et al. [8] and applied to OD and TS for BDS-3 satellites in the operational control center [2,3,4, 6]. It may have advantages in stability and computational efficiency for on-board distributed autonomous OD and TS, but for routine OD and TS at the operational control center or for the centralized autonomous OD and TS, its shortcomings are obvious. For example, data processing with this method is cumbersome, and it is difficult to calibrate the hardware delay of ISL equipment. To compute DEMs and DCMs, if either of the required double one-way pseudorange observations is not present (e.g., satellite observations do not arrive in time) or lacks quality, then the other will be discarded. If the method of polynomial interpolation or fitting is employed to compute derived pseudorange observations for a certain satellite-pair, a sequence of one-way pseudorange observations with a certain length is needed for each derived observation, and the interval of the sequence must contain the "observing" time of the required derived observation.
The method proposed in this paper directly uses the raw ISL pseudoranges for OD and TS simultaneously, and does not require either to generate derived observation or to match one-way pseudoranges observed at satellite-pairs. The procedure of data processing is very simple, almost the same as that for processing observation monitoring station data. Compared with the existing methods, the greatest advantage of this method is that it can simultaneously determine satellite orbits and clocks and the hardware delay biases of ISL equipment on satellites, if observations from monitoring stations are jointly processed. The obtained orbits and clocks are more self-consistent, and the estimated ISL hardware biases can be used to correct the ISL observation data for autonomous OD and TS. Another advantage of directly processing raw one-way pseudorange data is that data quality or performance of each ISL transmitting or receiving device at each satellite can be analyzed independently.
The proposed method for OD and TS requires only single one-way pseudorange data, so there is no need to wait for the return of the data observed at those satellites that are beyond tracking by the ground stations, increasing the data availability. Only 20% of all the ISL data were used for validation (the length of time slots was 1 min and the sampling interval was 5 min). This implies that the frequency for ranging or transferring ISL data can be reduced to allow more time for inter-satellite communication or more channel resources for transferring other information.
For OD and TS of BDS-3 satellites with the ISL operated in a TDMA mode, a general model using simultaneous or non-simultaneous observation data is proposed. The proposed approach was validated with experiments for two representative and important modes of OD and TS: (1) jointly processing ISL Ka-pseudoranges between satellites and ionosphere-free pseudorange and phase data from monitoring stations, and (2) jointly processing Ka-pseudoranges between satellites and between satellites and anchor stations. The results show that by jointly processing ISL data and the data of seven iGMAS stations located in China, the average RMS overlap orbit difference of the eight BDS-3 satellites is 0.019 m for radial direction and 0.156 m for 3D position; the overlap clock differences (95%) are 0.185 ns, and the standard deviation of the estimated Ka-biases is greater than 0.5 ns. Compared with the results obtained with only the seven monitoring stations, the improvements for orbits in radial and clocks are 95.7% and 90.5%, respectively. If the Ka-biases are fixed to known (pre-estimated) values, the accuracies of orbits and clocks are further improved; e.g., the overlap clock difference (95%) reduces to 0.054 ns. By jointly processing Ka-pseudoranges observed by satellites and two anchor stations, the average RMSs of overlap orbit differences are 0.017 m in the radial direction and 0.235 m in the 3D position, while the overlap clock difference (95%) is 0.037 ns. It is also shown that under the condition of single one-way ranging link, the accuracy of orbits and clocks obtained by the two modes is still significantly better than that obtained by only using data from monitoring stations. The RMS orbit difference is no more than 0.03 m in R, the overlap clock difference (95%) is no more than 0.3 ns, and the SDs of estimated Ka-biases are less than 0.6 ns.
As shown in the paper, the accuracy of clocks obtained by processing Ka-pseudoranges observed at anchor stations and satellites is greater than that obtained by jointly processing ISL data and monitoring station data. This may imply that not all error is modeled correctly; this could be due to the phase center offsets for the L-band and Ka-band signal or the time variation of hardware delay in the L-band and Ka-band equipment.
The data analyzed during the current study are not publicly available due to relevant laws of China.
Yang, Y., Xu, Y., Li, J., & Yang, C. (2018). Progress and performance evaluation of BeiDou global navigation satellite system: Data analysis based on BDS-3 demonstration system. Sci China Earth Sci.,61(5), 614–624.
Tang, C., Hu, X., Zhou, S., & Liu, L. (2018). Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements. Journal of Geodesy,92(10), 1155–1169.
Yang, D., Yang, J., Li, G., Zhou, Y., & Tang, C. (2017). Globalization highlight: Orbit determination using BeiDou inter-satellite ranging measurements. GPS Solutions,21(3), 1395–1404. https://doi.org/10.1007/s10291-017-0626-5.
Pan, J., Hu, X., Zhou, S., Tang, C., Guo, R., Zhu, L., et al. (2018). Time synchronization of new-generation BDS satellites using inter-satellite link measurements. Advances in Space Research,61(1), 145–153. https://doi.org/10.1016/j.asr.2017.10.004.
Song, X., Mao, Y., Feng, L., Jia, X., & Ji, J. (2017). The preliminary result and analysis for BD orbit determination with inter-satellite link data. Acta Geodaetica et Cartographica Sinica,46(5), 547–553.
Ren, X. (2018). Research on the theory and method of BDS autonomous orbit determination. Ph.D. Information Engineering University, Zhengzhou.
Ren, X., Yang, Y., & Zhu, J. (2017). Orbit determination of the Next-Generation BeiDou satellites with Inter-satellite link measurements and a priori orbit constraints. Advances in Space Research,60(10), 2155–2165. https://doi.org/10.1016/j.asr.2017.08.024.
Ananda, M. P., Bernstein, H., Cunningham, K. E., Feess, W. A., & Stroud, E. G. (1990). Global positioning system (GPS) autonomous navigation. Paper presented at the IEEE position location and navigation symposium.
Lin, Y., Qin, Z., Chu, H., & Wang, H. (2010). A satellite cross link-based GNSS distributed autonomous orbit determination algorithm. Journal of Astronautics,2010(31), 2088–2094.
Zhu, J. (2011). Research on orbit determination and time synchronizing of navigation satellite based on crosslinks. Ph.D., National University of Defense Technology, Changsha.
Mao, Y., Song, X., Jia, X., & Wu, X. (2013). Naturalisation method research on inter-satellite link observation data. Geomatics and Information Science of Wuhan University,38(9), 1201–1206.
Song, X. (2009). Study on the orbit determination of COMPASS navigation satellites. Ph.D., Chang'an University, Xi'an.
Hein, G. W. (2011). Inter satellite links for GNSS. Presentation at University of FAF Munich, Xi'an.
Fernández, F. A. (2011). Inter-satellite ranging and inter-satellite communication links for enhancing GNSS satellite broadcast navigation data. Advances in Space Research,47(5), 786–801.
Chen, J., You, Z., & Jiao, W. (2005). Research on autonav of navigation satellite constellation based on crosslink range and inter-satellite orientation observation. Journal of Astronautics,26(1), 43–46.
Ruan, R., Feng, L., Jia, X., Wu, X., Song, X., & He, T. (2012). Estimation of crosslink equipment delay and its contribution to GNSS orbit determination and time synchronization. Paper presented at the China Satellite Navigation Conference(CSNC) 2012 Proceedings (Vol. 160) Guangzhou.
Ruan, R., Feng, L., & Jia, X. (2014). Equipment delay estimation for GNSS satellite combined orbit determination with satellite-ground link and inter-satellite link observations. Acta Geodaetica et Cartographica Sinica,43(02), 137–142, 157.
Liu, W., Gong, X., & Zhang, W. (2011). GPS orbit determination with real ground tracking observations and simulative crosslink ranging observations. Paper presented at the CSNC 2011, Shanghai.
Ruan, R. (2018). Research on key technologies of precise data processing for GNSS networks. Ph.D., Information Engineering University, Zhengzhou.
Ruan, R., Wei, Z., & Jia, X. (2019). BDS-3 satellite orbit and clock determination with one-way inter-satellite pseudorange and monitoring station data. Acta Geodaetica et Cartographica Sinica, 48(3), 267–275.
Ruan, R., & Wei, Z. (2019). Between-satellite single-difference integer ambiguity resolution in GPS/GNSS network solutions. Journal of Geodesy.. https://doi.org/10.1007/s00190-019-01251-z.
Wei, Z., Ruan, R., Jia, X., Wu, X., Song, X., Mao, Y., et al. (2014). Satellite positioning and orbit determination system SPODS: Theory and test. Acta Geodaetica et Cartographica Sinica,43(1), 1–4.
Ruan, R., Jia, X., Wu, X., Feng, L., & Zhu, Y. (2014). SPODS software and its result of precise orbit determination for GNSS satellites. Paper presented at the China Satellite Navigation Conference (CSNC) 2014 Proceedings (Vol. III) Nanjing.
McCarthy, D. D., & Petit, G. (2004). IERS conventions (2003). International Earth Rotation and Reference Systems Service (IERS).
Springer, T. A. (1999). Modeling and validating orbits and clocks using the global positioning system. Phi, Astronomical Institute, University of Berne, Berne, Switzerland.
Beohm, J., Neill, A., Tregoning, P., & Schuh, H. (2006). Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data. Geophysical Research Letters,33, L07304.
Thanks to the International GNSS Monitoring and Assessment System for providing the monitoring station data.
This study was supported by the National Natural Science Foundation of China (Grant Nos. 41704035 and 42774012) and Office of China Navigation Satellite System (Project No. GFZX03010403).
Xi'an Research Institute of Surveying and Mapping, Xi'an, 710054, China
Rengui Ruan, Xiaolin Jia, Laiping Feng & Ziqing Wei
State Key Laboratory of Geo-information Engineering, Xi'an, 710054, China
Information Engineering University, Zhengzhou, 450001, China
Rengui Ruan
China Xi'an Satellite Control Center, Xi'an, 710043, China
Jun Zhu, Zongbo Huyan & Jie Li
State Key Laboratory of Astronautic Dynamics, Xi'an, 710043, China
Xiaolin Jia
Laiping Feng
Jun Zhu
Zongbo Huyan
Jie Li
Ziqing Wei
XJ, LF, and ZW evaluated the accuracy of the clock solutions. JZ, ZH, and JL evaluated the accuracy of orbit solutions. All authors read and approved the final manuscript.
Correspondence to Rengui Ruan.
Ruan, R., Jia, X., Feng, L. et al. Orbit determination and time synchronization for BDS-3 satellites with raw inter-satellite link ranging observations. Satell Navig 1, 8 (2020). https://doi.org/10.1186/s43020-020-0008-y
BDS-3
Inter-satellite link
Anchor station
Time synchronization
Hardware delay bias


text:
Making medicines and medical devices safer
What is being reported
Industry and other reporting guidance
Side effects from medicines
Patients, carers, parents and healthcare professionals in the UK are encouraged to report suspected suspected side effects, or suspected adverse drug reactions using the Yellow Card scheme using this website, the app or through some healthcare professional IT clinical systems (EMIS, SystmOne, Vision, MiDatabank, and Ulysses).
See our guidance on what to report. For more information about side effects from medicines, vaccine, herbal products or complementary remedies see here. For information about e-cigarettes see here.
Healthcare professionals can report suspected side effects where harm occurs as a result of a medication error as a Yellow Card or through their local risk management systems that feed into the National Reporting and Learning System (NRLS). If reported to the NRLS, these will be shared with the MHRA. If the NRLS is not available and harm occurs, report using a Yellow Card.
There is a legal requirement for pharmaceutical companies to report suspected adverse drug reactions directly to the MHRA for their products. See here for more information on their submission.
Medical device adverse incidents
Medical devices adverse incident reporting links:
for industry,
for a healthcare professional in Northern Ireland or Scotland (additionally please also report the incident to your employer's local risk management system).
Anyone else should use the Yellow Card scheme. For more information about medical device adverse incidents see here.
Defective medicines
If you are reporting a defective product as a manufacturer, marketing authorisation holder, or other (e.g. university, clinical trial sponsor), please send details of your report via email: dmrc@mhra.gov.uk
Falsified (Fake) medicines
Falsified reporting links:
for industry, please report via email: fakemeds@mhra.gov.uk
Anyone else should use the Yellow Card scheme. For example, if you are a member of the public or identify yourself as reporting from non-healthcare setting (Her Majesty's Revenue and Customs, UK Border Force, from Law Enforcement (e.g. Home Office, Police, National Crime Agency or other), Trading Standards) please use the Yellow Card scheme.
Privacy PolicyAccessibility StatementCookie Policy
For more detailed information please check our Cookies page
Allow analytic cookies
We'd like to set Google Analytics and third party cookies to help us to improve our website and your user experience, by collecting and reporting information on how you use it. The cookies collect information in a way that does not directly identify anyone. For more information on how these cookies work, please see our 'Cookie policy'.

redpajama_set_name: RedPajamaCommonCrawl


The journal "Elemente der Naturwissenschaft" (Elements of science) publishes articles based on a holistic research approach in all the natural sciences. It focuses especially on work with a basis in Goethean and/or anthroposophically extended science that contributes to the spiritual development of the sciences as sketched out by Rudolf Steiner. In addition to original research, it also publishes communications and reports from the Natural Science Section of the School of Spiritual Science at the Goetheanum, as well as reviews of publications.
Most of the contributions are in German, but frequently there are some in English.
Here you can retrieve the index of the latest volume no. 109 (german only).


text:
Q: How would I detect a pattern in text? I am creating a Python script that is able to understand human inputted text for actions to make on the stock market. For example all of these mean the same thing:

*

*$EXAMPLE 12 Aug 21 $22.5 Call Average Price = $0.8

*$EXAMPLE $22.5 CALLS EXP. 8/12 @ $0.8

*$EXAMPLE $22.5 CALLS EXP. 8/12 @ $0.8

*$EXAMPLE $22.5c 8/12 @ .8

*$EXAMPLE 22.5c 8/12 @ .8

*Lorem ipsum dolor sit amet, consectetur $EXAMPLE 22.5c 8/12 @ .8 adipiscing elit, sed do eiusmod

The components that I need to extract: the ticker ($EXAMPLE), the call price ($22.5), expiration (8/12 or August 12), and the average price ($0.8). The issue is that sometimes formatting differs as shown in the examples above. Sometimes the 'calls' will be denoted as 22.5c and sometimes the average price may be written as Average Price = 0.8 or @ 0.8. Something else to note: sometimes the string may have text prefixing or following the parts I would like to extract (as shown in the last example).
How should I approach this? Will machine learning be useful in this case since the formatting isn't the same every time?

A: This is not a trivial problem, and I assume there will be cases where two humans would give different answers for the same text. Especially if you don't want to specify the allowed formats.
I would recommend going with an approach similar to what PW1990 suggested, it's the most predictable and maintainable solution. However, instead of having only one regexp per semantic structure, you could have a method that tries its best to extract a property with a set of regexps.
If you have enough data, you could also do machine learning. For that, you need to have a dataset with a mapping of each "text" to each {action}. From my experience, I would start with 100k-1M data points (mappings).
You could try a bidirectional RNN that returns a number for each character, assigning it to one of the classes [ticker, price, avg, date, type, other]. Then you could parse and validate each of the substrings manually. This is straightforward if you know what you are parsing.
Of course, you could try an end-to-end approach where an RNN returns you a reformatted string that you feed into a regexp. However, it significantly increases the complexity of the model and the amount of data you need.
There was a similar StackOverflow thread here: https://stats.stackexchange.com/questions/35249/machine-learning-techniques-for-parsing-strings
My personal recommendation is to avoid machine learning if it is not absolutely needed. ML is not a silver bullet, and it requires a lot of work to get it correctly. So it will be a project of its own. On the other hand, regular expressions are a much more straightforward solution for this problem, although I understand that it is tedious to hardcode all possible regexps. Just keep in mind that most likely, you are aiming at getting 99% of the cases.

A: using regex you can find the first instance of a desired word using re.search. I put all of your examples into a txt file called "question.txt" and did a simple search.
import re

open_txt = open("question.txt", "r")
read = open_txt.read()
try:
    starts_with_example = re.search(r'[$]EXAMPLE.*', read).group()
    starts_with_lorem = re.search(r'Lorem.*', read).group()
except:
    print("No instance")

print(starts_with_example)
print(starts_with_lorem)

If you want to have every instance in a list, replace re.search with re.findall.

redpajama_set_name: RedPajamaStackExchange


text:
Men's volleyball picked third in EIVA Tait pre-season poll
HUNTINGDON, Pa. -- The Juniata College men's volleyball team has been picked to finish third in the EIVA Tait Division in 2010 according to a preseason poll of the league's head coaches, the results of which were released Monday.
Defending EIVA champions Penn State were picked to repeat as EIVA Tait champions in 2010, receiving five of the six first-place votes. Saint Francis University received the remaining first-place vote and was second in the poll, ahead of Juniata.
Trailing the Eagles were Princeton University in fourth place, while George Mason University and Springfield College were tied for fifth place.
In the Hay Division, Rutgers-Newark was picked to win the division with four first-place votes. New Jersey Institute of Technology was second, followed by NYU and Harvard University tied for third. Sacred Heart University was picked to finish last in the Hay. The Violets received the remaining first-place vote in the Hay Division poll.
Juniata posted an 18-8 record in 2009, advancing to the championship match of the 2009 EIVA Tournament where the Eagles dropped a 3-0 decision to Penn State.
The Eagles return a pair of EIVA Second team All-East performers in outside hitter Zach Wanner (Lancaster, Pa./Hempfield) and libero Anthony Damiano (Lititz, Pa./Manheim Township), and an AVCA Second team Division III All-American in middle hitter Evan Halteman (Perkiomenville, Pa./Christopher Dock). Juniata will have to replace a four-time AVCA All-American in setter Matt Werle (Meadville, Pa./Meadville), as well as an EIVA Second team All-East middle hitter in Dan Powers (Lancaster, Pa./Manheim Township).
Juniata opens its 2010 season on Monday, Jan. 18, when it hosts Ohio State University at 6:00 p.m. at the Kennedy Sports + Recreation Center.
The complete EIVA pre-season poll is listed below:
EIVA 2010 Pre-Season Poll
Tait Division
1. Penn State (5)
2. Saint Francis (1)
3. Juniata
4. Princeton
5. George Mason
5. Springfield
Hay Division
1. Rutgers-Newark (4)
2. NJIT
3. NYU (1)
3. Harvard
4. Sacred Heart


Whether it's personal or professional, we're making some serious progress toward our goals this month, but there is a bit of a twist! In order to evolve, grow, or be more productive or effective, we must first un-learn the things we thought we knew. There are habits or practices that may have sounded right on paper, but when put into practice were not yielding the results we expected. We need to un-learn, and start to replace those ideas, habits or practices with more constructive behaviours and methods.
Last month the lack of balance from the reversed six of pentacles was tipped in our favour, but unfortunately this month the scales are tipped in the opposite direction. Rather than money being the balance measured, for the month of April it will be time. Our heads are bursting with new ideas and revelations. We find ourselves now being able to pin-point past mistakes. This is fantastic! And although it is better to discover this knowledge sooner than later, it still means that in order to move forward, we have to take a few steps back. Our challenge now is time: time lost, or simply not enough hours in the day. Try not to be discouraged, you are still on the right path.
When you start to feel overwhelmed because your to-do list is growing faster than you can keep up with, or you just aren't seeing the results you want fast enough, take a step back and place your focus and priorities on the things that include spreading joy to others. How can you share your passions with others? Do you have something to teach? Can you provide fun experiences for guests or loved ones? Can you find a community/group/club that shares a common interest in your local city or online? If you are experiencing frustration, stress or unhappiness, you need to switch gears. Take some time to laugh, play and enjoy the company of others. Everything else can wait.


text:
<?php
/**
 * BusinessLogicServiceGuestInviteInfo
 *
 * PHP version 5
 *
 * @category Class
 * @package  Alfaview
 * @author   Swagger Codegen team
 * @link     https://github.com/swagger-api/swagger-codegen
 */

/**
 * businessLogicService/businessLogicService.proto
 *
 * No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen)
 *
 * OpenAPI spec version: version not set
 *
 * Generated by: https://github.com/swagger-api/swagger-codegen.git
 * Swagger Codegen version: 2.4.27
 */

/**
 * NOTE: This class is auto generated by the swagger code generator program.
 * https://github.com/swagger-api/swagger-codegen
 * Do not edit the class manually.
 */

namespace Alfaview\Model;

use \ArrayAccess;
use \Alfaview\ObjectSerializer;

/**
 * BusinessLogicServiceGuestInviteInfo Class Doc Comment
 *
 * @category Class
 * @package  Alfaview
 * @author   Swagger Codegen team
 * @link     https://github.com/swagger-api/swagger-codegen
 */
class BusinessLogicServiceGuestInviteInfo implements ModelInterface, ArrayAccess
{
    const DISCRIMINATOR = null;

    /**
      * The original name of the model.
      *
      * @var string
      */
    protected static $swaggerModelName = 'businessLogicServiceGuestInviteInfo';

    /**
      * Array of property to type mappings. Used for (de)serialization
      *
      * @var string[]
      */
    protected static $swaggerTypes = [
        'email' => 'string',
        'customer_name' => 'string',
        'room_name' => 'string',
        'join_link' => 'string',
        'expiry_in_days' => 'int',
        'locale' => 'string'
    ];

    /**
      * Array of property to format mappings. Used for (de)serialization
      *
      * @var string[]
      */
    protected static $swaggerFormats = [
        'email' => null,
        'customer_name' => null,
        'room_name' => null,
        'join_link' => null,
        'expiry_in_days' => 'int64',
        'locale' => null
    ];

    /**
     * Array of property to type mappings. Used for (de)serialization
     *
     * @return array
     */
    public static function swaggerTypes()
    {
        return self::$swaggerTypes;
    }

    /**
     * Array of property to format mappings. Used for (de)serialization
     *
     * @return array
     */
    public static function swaggerFormats()
    {
        return self::$swaggerFormats;
    }

    /**
     * Array of attributes where the key is the local name,
     * and the value is the original name
     *
     * @var string[]
     */
    protected static $attributeMap = [
        'email' => 'email',
        'customer_name' => 'customerName',
        'room_name' => 'roomName',
        'join_link' => 'joinLink',
        'expiry_in_days' => 'expiryInDays',
        'locale' => 'locale'
    ];

    /**
     * Array of attributes to setter functions (for deserialization of responses)
     *
     * @var string[]
     */
    protected static $setters = [
        'email' => 'setEmail',
        'customer_name' => 'setCustomerName',
        'room_name' => 'setRoomName',
        'join_link' => 'setJoinLink',
        'expiry_in_days' => 'setExpiryInDays',
        'locale' => 'setLocale'
    ];

    /**
     * Array of attributes to getter functions (for serialization of requests)
     *
     * @var string[]
     */
    protected static $getters = [
        'email' => 'getEmail',
        'customer_name' => 'getCustomerName',
        'room_name' => 'getRoomName',
        'join_link' => 'getJoinLink',
        'expiry_in_days' => 'getExpiryInDays',
        'locale' => 'getLocale'
    ];

    /**
     * Array of attributes where the key is the local name,
     * and the value is the original name
     *
     * @return array
     */
    public static function attributeMap()
    {
        return self::$attributeMap;
    }

    /**
     * Array of attributes to setter functions (for deserialization of responses)
     *
     * @return array
     */
    public static function setters()
    {
        return self::$setters;
    }

    /**
     * Array of attributes to getter functions (for serialization of requests)
     *
     * @return array
     */
    public static function getters()
    {
        return self::$getters;
    }

    /**
     * The original name of the model.
     *
     * @return string
     */
    public function getModelName()
    {
        return self::$swaggerModelName;
    }

    /**
     * Associative array for storing property values
     *
     * @var mixed[]
     */
    protected $container = [];

    /**
     * Constructor
     *
     * @param mixed[] $data Associated array of property values
     *                      initializing the model
     */
    public function __construct(array $data = null)
    {
        $this->container['email'] = isset($data['email']) ? $data['email'] : null;
        $this->container['customer_name'] = isset($data['customer_name']) ? $data['customer_name'] : null;
        $this->container['room_name'] = isset($data['room_name']) ? $data['room_name'] : null;
        $this->container['join_link'] = isset($data['join_link']) ? $data['join_link'] : null;
        $this->container['expiry_in_days'] = isset($data['expiry_in_days']) ? $data['expiry_in_days'] : null;
        $this->container['locale'] = isset($data['locale']) ? $data['locale'] : null;
    }

    /**
     * Show all the invalid properties with reasons.
     *
     * @return array invalid properties with reasons
     */
    public function listInvalidProperties()
    {
        $invalidProperties = [];

        return $invalidProperties;
    }

    /**
     * Validate all the properties in the model
     * return true if all passed
     *
     * @return bool True if all properties are valid
     */
    public function valid()
    {
        return count($this->listInvalidProperties()) === 0;
    }

    /**
     * Gets email
     *
     * @return string
     */
    public function getEmail()
    {
        return $this->container['email'];
    }

    /**
     * Sets email
     *
     * @param string $email email
     *
     * @return $this
     */
    public function setEmail($email)
    {
        $this->container['email'] = $email;

        return $this;
    }

    /**
     * Gets customer_name
     *
     * @return string
     */
    public function getCustomerName()
    {
        return $this->container['customer_name'];
    }

    /**
     * Sets customer_name
     *
     * @param string $customer_name customer_name
     *
     * @return $this
     */
    public function setCustomerName($customer_name)
    {
        $this->container['customer_name'] = $customer_name;

        return $this;
    }

    /**
     * Gets room_name
     *
     * @return string
     */
    public function getRoomName()
    {
        return $this->container['room_name'];
    }

    /**
     * Sets room_name
     *
     * @param string $room_name room_name
     *
     * @return $this
     */
    public function setRoomName($room_name)
    {
        $this->container['room_name'] = $room_name;

        return $this;
    }

    /**
     * Gets join_link
     *
     * @return string
     */
    public function getJoinLink()
    {
        return $this->container['join_link'];
    }

    /**
     * Sets join_link
     *
     * @param string $join_link join_link
     *
     * @return $this
     */
    public function setJoinLink($join_link)
    {
        $this->container['join_link'] = $join_link;

        return $this;
    }

    /**
     * Gets expiry_in_days
     *
     * @return int
     */
    public function getExpiryInDays()
    {
        return $this->container['expiry_in_days'];
    }

    /**
     * Sets expiry_in_days
     *
     * @param int $expiry_in_days expiry_in_days
     *
     * @return $this
     */
    public function setExpiryInDays($expiry_in_days)
    {
        $this->container['expiry_in_days'] = $expiry_in_days;

        return $this;
    }

    /**
     * Gets locale
     *
     * @return string
     */
    public function getLocale()
    {
        return $this->container['locale'];
    }

    /**
     * Sets locale
     *
     * @param string $locale locale
     *
     * @return $this
     */
    public function setLocale($locale)
    {
        $this->container['locale'] = $locale;

        return $this;
    }
    /**
     * Returns true if offset exists. False otherwise.
     *
     * @param integer $offset Offset
     *
     * @return boolean
     */
    public function offsetExists($offset)
    {
        return isset($this->container[$offset]);
    }

    /**
     * Gets offset.
     *
     * @param integer $offset Offset
     *
     * @return mixed
     */
    public function offsetGet($offset)
    {
        return isset($this->container[$offset]) ? $this->container[$offset] : null;
    }

    /**
     * Sets value based on offset.
     *
     * @param integer $offset Offset
     * @param mixed   $value  Value to be set
     *
     * @return void
     */
    public function offsetSet($offset, $value)
    {
        if (is_null($offset)) {
            $this->container[] = $value;
        } else {
            $this->container[$offset] = $value;
        }
    }

    /**
     * Unsets offset.
     *
     * @param integer $offset Offset
     *
     * @return void
     */
    public function offsetUnset($offset)
    {
        unset($this->container[$offset]);
    }

    /**
     * Gets the string presentation of the object
     *
     * @return string
     */
    public function __toString()
    {
        if (defined('JSON_PRETTY_PRINT')) { // use JSON pretty print
            return json_encode(
                ObjectSerializer::sanitizeForSerialization($this),
                JSON_PRETTY_PRINT
            );
        }

        return json_encode(ObjectSerializer::sanitizeForSerialization($this));
    }
}

redpajama_set_name: RedPajamaGithub


Badaboom. You know what we're talking about. The kind of comic book action that can only be described with an action word in a speech balloon. WOW! BAM! BADABOOM!
Your kid knows all about that kind of stuff, and if he needs to wear a suit for the first time, well, wait till he gets a load of this one. He can combine his love of comics with his fashion style when you get him this boy's Badaboom OppoSuit! OppoSuits revolutionized menswear with their outlandishly awesome men's suits, and now for the first time, they're available in kid's sizes. Why dress him up in a plain, old regular suit when now you can do it with a little extra BOOM!
This suit is indeed a real suit. 100 percent polyester, the printed suit jacket is fully lined. Slim fit pants accommodate a range of waist sizes with a belt or quick tailor. Matching clip-on tie completes the suit set, and will have your little guy looking extra dapper. He's sure to feel like a hero no matter the event you're attending. Because if he has to dress up, he might as well have a fun way to do it. This Badaboom suit is sure to be just the thing!
4T - $64.99 Only 5 left! Size 6 - $64.99 Only 7 left!


Nikon have a great reputation for producing good cameras and the CoolPix L310 is an excellent bridge camera. Its main attribute is its superb 21x zoom Nikkor lens (equivalent to 25- 500mm) that lets you shoot wide angle close-ups and capture distant images with equally good image quality and clarity. The rest of the camera is built to support this feature.
The 14 Mega-pixel file size is large enough to blow up your photos up to poster size and the Anti-blur functions help you the keep the pictures sharp, even at the lens' full length.
The ISO extends to 6400, which means that the camera can shoot comfortably in low-light and the large LCD back screen is high resolution and has good clarity in playback. The Nikon Smart Portrait systems help you avoid the more common errors, even taking the shot when your subject smiles.
The Auto scene selector chooses the most appropriate scene setting for you and Easy Auto Mode sets the options to the light you are shooting in. It also has 17 scene options to choose from, from Sunset, Snow, Fireworks, Backlighting and many others. It has 720p video, which can be operated easily at the touch of a button and which utilizes the zoom and Autofocus. It runs on AA batteries.


text:
Headline, Homepage, News Blog
ACLU Defends Satire in Response to Coal CEO's Suit Against John Oliver
by Maren Williams • August 3, 2017 • Comments Off on ACLU Defends Satire in Response to Coal CEO's Suit Against John Oliver
The American Civil Liberties Union of West Virginia came to the defense of John Oliver and Mr. Nutterbutter the giant squirrel yesterday, filing an amicus brief in a lawsuit against the comedian from notoriously litigious coal baron Bob Murray over a segment that aired on Last Week Tonight in June. While the brief exploits the comic aspects of the case to great effect, it also condemns Murray's "frequent attempts to use our legal system to chill speech, threaten the fundamental right of the media to criticize public figures and speak candidly on matters of public concern."
Originally, Murray Energy and its CEO were to get only a passing mention in the 24-minute segment delving into the question of whether the coal industry can actually be revived as President Donald Trump has often promised. But when Last Week Tonight staff contacted the company for comment and received the show's first ever cease-and-desist letter in response, Murray suddenly became a much larger component of the bit, which ended with a person in a giant squirrel costume holding up a novelty check made out to "Eat shit, Bob!"
Within days, Murray filed suit against Oliver, HBO, and a passel of unidentified defendants that may include Mr. Nutterbutter himself. The lawsuit claims that the segment was "detrimental to both [Murray's] business and his physical condition" and also seeks a gag order to prevent Oliver or his representatives from discussing the pending case. In the amicus brief filed yesterday, ACLU-WV's general counsel Jamie Lynn Crofts cites ample precedent establishing Oliver's right to discuss a matter of public concern, even if it implicates a specific person who does not like the discussion:
It is axiomatic that "the First Amendment to the United States Constitution placed limits on the application of the state law of defamation" and in particular on "the type of speech which may be the subject of state defamation actions." Milkovich v. Lorain Journal, 497 U.S. 1, 14, 16 (1990). The Complaint itself makes it clear that Defendants' speech was about matters of public concern, as it repeatedly alleges that Defendants' broadcast this episode to advance their political agenda. "[S]peech concerning public affairs is more than self-expression; it is the essence of self-government." Garrison v. Louisiana, 379 U.S. 64, 74-75 (1964).
Later in the 12-page brief, Crofts tackles the various constitutional violations that would be incurred by the requested gag order:
Bob Murray thinks John Oliver was mean to him, and he doesn't want him to be mean again. While that is sad for Bob Murray, it is unconstitutional for a court to order such relief. With Plaintiffs' request for a (1) prior restraint (2) that is a content-based restriction (3) on a matter of public concern (4) related to a public figure, they have really hit the protected speech jackpot! The requested injunction, "actually forbid[ding] speech activities," is a classic example of a prior restraint. See Alexander v. United States, 509 U.S. 544, 550 (1993).
The case is being heard in a West Virginia district court–possibly, as Crofts notes in the brief, because Murray has worn out his welcome with courts in his home state of Ohio due to the number of frivolous lawsuits he's filed there over the years. Check out the full brief here, as well as Crofts' further commentary on the case in a post for the ACLU blog here.
Help support CBLDF's important First Amendment work in 2017 by visiting the Rewards Zone, making a donation, or becoming a member of CBLDF!
Contributing Editor Maren Williams is a reference librarian who enjoys free speech and rescue dogs.
Tags: aclu bob murray defamation john oliver last week tonight mr. nutterbutter satire united states west virginia
← CBLDF is Back from SDCC with GNs Signed by Kevin Eastman, Stan Sakai, Walter Simonson, and more!
RETAILERS: Engage Your Community with the CBLDF Banned Books Week Handbook! FOCs 8/7! →


text:
Unsolicited Press Presents a Evening Reading with Terry Tierney and Anne Leigh Parrish
Join us for an evening of festivities, literature, and potential technical glitches as we host a virtual reading with esteemed authors Anne Leigh Parrish and Terry Tierney. Both authors will read from a selection of their choosing and we will banter/converse afterwards. The event is on October 2, 2021 at 5PM Pacific. You can RSVP here.
Terry Tierney is a writer who hails from the Midwest, but has planted roots in the San Francisco Bay Area. After serving in the Seabees, he completed his BA and MA at Binghamton University; Tierney completed a PhD in Victorian Literature at Emory University. For years, he taught college composition and creative writing courses, and survived several Silicon Valley startups as a software engineer. He lives in the San Francisco Bay Area with his wife Michaelyn Burnette, a Librarian from the University of California, their son, and their goofy Golden Retriever. Tierney's work has appeared in countless publications. Lucky Ride, an irreverent Vietnam-era road novel is set to release in 2022.
Anne Leigh Parrish is the author of nine previously published books: the moon won't be dared (Unsolicited Press 2021); A Winter Night, a novel (Unsolicited Press, 2021); What Nell Dreams, a novella & stories (Unsolicited Press, 2020); Maggie's Ruse, a novel, (Unsolicited Press, 2017); The Amendment, a novel (Unsolicited Press, 2017); Women Within, a novel (Black Rose Writing, 2017); By the Wayside, stories (Unsolicited Press, 2017); What Is Found, What Is Lost, a novel (She Writes Press, 2014); Our Love Could Light The World, stories (She Writes Press, 2013); and All The Roads That Lead From Home, stories (Press 53, 2011). Learn more at https://anneleighparrish.com/.
Books by Terry Tierney and Anne Leigh Parrish


Click here to sign-up to get the latest commercial real estate insights and news from our Houston team, delivered to your inbox.
Learn more about our services and our professionals to see how they've helped clients throughout the Houston area with their commercial real estate needs.
Our brokerage platform continues to expand, and last month industry veterans Donna Kolius, Pierce Owens and Kaylie Walker joined JLL in Houston. The team focuses on multi-market dispositions, national portfolio strategies, and sale leasebacks for corporations, private equity firms, real estate investment trusts, investors and retailers.
They recently returned from ICSC RECon. Here's what they had to say about some key takeaways from the shopping center industry's largest convention.
Malls are getting a lot of attention.
Mall owners now recognize the need to create new methods of increasing mall traffic. (Amenities such as food courts, theaters or skating rinks help keep shoppers at the mall once they arrive, but do not create new mall traffic.) The recent closure of department stores has motivated mall owners to change their perception of attractive mall anchors. Many mall operating agreements restrict uses to retail only. But department store closures have created an opportunity to fill the space with entertainment or restaurant concepts. The buzzword for this phenomenon is "retail-tainment" and includes anchors such as Crayola, Kidzania, Dave and Busters, Main Event and/or restaurants. We even know of one Texas mall that has created the concept of "date night," which encourages couples to dine at a different restaurant at the nearby mall every Saturday night. In fact, anchors like Kidzania and Crayola promote children drop-off while the parents shop. These entertainment-based anchors create new mall traffic and are re-energizing the role of the mall in American retail shopping.
This was the catch phrase among REITs and institutional net lease investors when discussing their real estate portfolios. Tenants with service related uses that cannot be replicated by e-commerce or the internet are highly desirable. For example, oil change tenants and car washes are physical activities that cannot be replaced in cyberspace. Once considered mundane, these types of tenants are becoming more desirable to investors. Wall Street will favor property portfolios that demonstrate internet resistance.
Quick serve restaurants (QSRs) are beginning to imitate the wildly popular fast casual concept by adopting an increased customer focus into their own prototypes. Traditionally QSRs are thought of as a product of efficiency, synchronization and cost reduction. Lately, we're seeing more and more quick service concepts make the investment into a more customer-centric experience. QSRs are buying into the idea of providing perks such as expanded menu options, alcohol sales, catering/delivery and technology integration. It really is a win-win as these areas of exploration provide QSRs the opportunity to accommodate changing customer tastes, all while promoting larger profit potential through extended business lines and cost mitigating measures.
Want to learn more? Get to know our Disposition Services team.
Sign-up for the research you want.
Bayous once served as Houston's transit corridors. Let's do it again.
Holiday shopping 2017: When, where, why, how & how much?
They call him "Papa Gator"
"Onshoring" Leads to the Growth of Niche Industry in the U.S.
What's in store for Houston retail?
Office Stats Predict Villanova/OU Winner to Have "One Shining Moment"
Why Hire A Project Manager?
© 2019 JLL Houston Blog. All Rights Reserved.


What's the best thing to give your dad on Father's Day? Aftershave? Golf balls? What about the gift of love?
Susie and Molly are giggling up a storm on a sleep over the night before Easter Sunday. Molly starts to learn what Easter is really about . . but her "dream" really tells the story!
A boy finds himself rejected by the "cool" crowd and reaches out to the kid no one wants to befriend. Although reluctant at first, he soon finds real, honest friendship.


at Deal Zone. Limit one per customer. Max discount of 500 for JET and Powermatic, 200 for all other brands. Choose new items, too, and youll still enjoy discount prices.
Shop the brands you trust, including Makita, Dremel, Milwaukee, Rheem, Jobox, Ridgid, and Black Decker. Please check back later. View Sale, used 2 times today, free Light w/ Select 18V Items. Subject to change without notice. The online tool retailers outlets, gathered together at the CPO Outlets site, feature new and factory-refurbished brand-name power tools and accessories at discounts of as much as 30 off original retail prices.


text:
review Vizio P-Series Quantum LED TV Review
how-to How to download Netflix movies to your phone to watch...
Vizio Finally Sheds Light on Its UHD Reference TVs
The company's highly ambitious premium series is finally here.
Written by Lee Neikirk
Vizio today announced the arrival of its ultra-premium Reference Series. The company's flagship lineup was first announced during CES 2014 in Las Vegas, Nevada, but until today the R-series has remained an elusive, unicorn product for cinephiles and A/V junkies.
The Reference Series delivers High Dynamic Range and Dolby Vision.
The Reference Series will be available in 65- and 120-inch screen sizes, though no pricing has been confirmed yet. The company made some very big claims about this series when it first debuted, promising best-in-class picture quality and next-generation hardware.
According to Vizio, the Reference Series is one of the first UHD (4K) lineups to promote High Dynamic Range and Dolby Vision compatibility. Like Vizio's other 2015 models, the Reference Series televisions wield a Full Array LED backlight scheme with up to 384 dimming zones—compare that to the 32 zones of the company's new M-Series.
In 2014, Vizio claimed massive color abilities—a color space called "Rec. 2020"—that so far no manufacturer has been able to achieve. Today's announcement appeared to scale back expectations a bit, instead gunning for the Ultra-Color Spectrum, which may or may not exceed the color abilities of this year's Quantum Dot-equipped UHD televisions.
Credit: Vizio
The new Reference Series marks Vizio's ultra-premium, top-of-the-line UHD entry for 2015.
The 65-inch Reference Series TV will come bundled with an integrated 5.1-channel sound bar, but anyone courting the gigantic 120-inch version will hopefully already have a wired-and-ready home theater to accompany it.
While many manufacturers have claimed specular highlight abilities of 1000 nits (or brighter), Vizio seems a bit more reserved, citing a peak of 800 nits for the Reference Series. And as a Dolby Vision-equipped set, that will likely come in handy. We'll have to wait until we have the set and appropriate content to go with it, but Vizio claims that several compatible Warner Bros. movies will be available when the series launches.
What is mini-LED and how does it make TVs better?
The Best TVs for PlayStation 5 of 2022
Content capable of Dolby Vision should be available alongside the Reference Series.
The company also confirmed an "effective" refresh rate of 240 Hz, which probably means 120 Hz native. According to Matt McRae, Vizio's CTO, the Reference Series will "shatter the limits of what's possible for cinephiles."
Naturally, both TVs in Vizio's Reference Series will be smart and equipped with all of the latest codecs and hardware measures to allow native 4K playback and 4K streaming from app partners. No pricing information for either TV has been announced, but interested consumers can sign-up for updates on Vizio's website.
Stay tuned for our first impressions and full review of Vizio's long-awaited Reference Series.
Source: IRVINE, CA - April 13, 2015 - VIZIO, the maker of the top-selling Ultra HD TV1, introduced today details behind the industry's first-ever line of High Dynamic Range Ultra HD TVs to support Dolby Vision - the VIZIO Reference Series Ultra HD Full-Array LED Smart TVs - available in 65" and 120" class screen sizes. The result of a decade of knowledge in pushing the boundaries of picture and audio quality, the beautifully designed VIZIO Reference Series is packed with groundbreaking, innovative technologies. Equipped with Dolby Vision for a dramatically different visual experience and Ultra-Color Spectrum for a wider color gamut, the Reference Series displays stunningly beautiful Ultra HD detail with over eight million pixels in every image. An 800-Nit, Full-Array LED backlight and 384 Active LED Zones create a stunningly vivid Ultra HD picture with striking contrast. Several 4K Ultra HD Dolby Vision titles will be available from Warner Bros. streaming through VUDU, Walmart's video-on-demand service for movies and television. When combined with the integrated 5.1 sound bar system on the 65" model, home theater aficionados will not only enjoy unprecedented cinematic picture quality, but a powerful home audio experience that delivers a Sound Pressure Level of up to 101dB.
The 2015 Reference Series was designed for the cinephile, pushing the boundaries of brightness, color and contrast and featuring an integrated home theater system to perfectly round out the consumer experience. A Full-Array 800-Nit LED backlight makes for an incredible picture, enabling a wider and more dynamic range of luminance with an unprecedented 384 Active LED Zones for precise contrast control. Clear Action 1800 is set by a whole new standard that allows consumers to enjoy fast-action sports and movies with superior motion clarity thanks to powerful image processing and blazing 240Hz effective refresh rate. The new VM50 Ultra HD engine, a dedicated Ultra HD motion and picture-processing engine, provides enhanced clarity in every Ultra HD image. for sharper detail and ensure fast moving scenes appear clearer than ever.
"The Reference Series redefines 'best-in-class' picture quality and audio standards," said Matt McRae, Chief Technology Officer, VIZIO. "We leveraged our deep understanding of the consumer experience to fuel innovative technologies that take critical drivers of picture quality - like color and contrast - to new levels, transforming long-existing standards. Packed with breakthrough achievements like High Dynamic Range and Ultra-Color Spectrum for a wider-than-ever color gamut, the Reference Series shatters the limits of what's possible for cinephiles. The addition of an unbelievably powerful integrated 5.1 audio solution with a 10-inch wireless subwoofer and two rear satellite speakers further reinforces that the VIZIO Reference Series delivers the most immaculate home theater experience possible."
Unlike most TVs, which can only reproduce a limited color gamut of Rec 709, the Reference Series features an Ultra-Color Spectrum which widens the color gamut, rendering colors closer to the range a human eye can see, something never before possible on a home TV screen. Taking advantage of this capability, Dolby Vision content on the Reference Series delivers captivating color, astonishing brightness and a contrast range with brighter highlights and deeper darks. This complete High Dynamic Range solution more accurately reproduces the nuances in every picture, revealing fine details found in real scenes that are brought to life on the VIZIO References Series.
"We are proud for Dolby Vision to be introduced to consumers through the VIZIO Reference Series, providing a dramatically different visual experience that engages the senses and further draws viewers into the picture," said Giles Baker, SVP, Broadcast Business Group, Dolby Laboratories. "VIZIO Reference Series customers will have access to a slate of 4K Ultra HD Dolby Vision content, bringing viewers closer than ever before to viewing content as it was intended by filmmakers."
On top of redefined picture quality, the VIZIO Reference Series gives consumers access to unparalleled Ultra HD streaming with an initial slate of Warner Bros. 4K Ultra HD Dolby Vision titles that will be available through VUDU, a leader in quality over-the-top (OTT) video for digital movies and TV.The content-delivery service will deliver easily accessible Dolby Vision content in 4K Ultra HD to enable the ultimate home cinema experience. Consumers can find an ongoing list of upcoming Warner Bros. titles in Dolby Vision at VUDU.com/UHD.
"Customers expect VUDU to use the latest technology to create a cinema-quality experience and thanks to Dolby and the VIZIO Reference Series, it's now possible," said Scott Blanksteen, Vice President of Product, VUDU. "The most advanced home entertainment experience is now a reality and we couldn't be more proud to be the service sharing content with consumers."
Equipped with blazing fast 802.11ac dual-band WiFi for a fast, efficient streaming experience, the Reference Series features VIZIO Internet Apps Plus®, offering entertainment enthusiasts Dolby Vision playback capabilities through VUDU and also instant access to Ultra HD content through other apps2 including Netflix, Amazon Instant Video, UltraFlix and Toon Goggles3. Supported by the HEVC H.265 codec and powered by the VIZIO V6 six-core processor, the Reference Series provides consumers with seamless discovery and organization of apps.
For sports, movies or TV shows only available to consumers in 720p and 1080p, the Reference Series is equipped with a powerful Spatial Scaling Engine, which beautifully transforms the ordinary pixels to finer, more accurate Ultra HD pixels, sharpening details to provide an all-around better viewing experience. The Reference Series supports future ready HDMI ports to ensure consumers using next generation cable and satellite receivers, Blu-ray players and game consoles, won't miss out. The Pure Cinema Engine displays frame rates at an authentic 24 frames per second, giving movie-loving consumers the exact experience filmmakers intended. Additionally, the Reference Series is also great for gamers, with a High Velocity Mode that triggers an explosive 120 frames per second for legendary gaming speeds with high responsiveness and low latency.
If the best picture quality with the most innovative technologies isn't enough to entice consumers to upgrade, perhaps the high-end design or integrated 5.1 Sound Bar System will do the trick. Reference Series sets an industry standard for beauty and marks a breakthrough achievement for integrated home theater audio in the 65" class model. From the near edge-to-edge display and ultra-thin bezel to the aluminum frame and precision crafted base, each detail is meticulously produced from select materials. The innovative integrated sound bar built into the base of the 65" model is supplemented by a powerful 10" wireless subwoofer and two rear satellite speakers. The audio experience is further enhanced by top-of-the-line audio technologies from Dolby and DTS™, including over 101dB of crystal-clear sound with less than 1% harmonic distortion4. To find the right fit for any home theater, the Reference Series enables a modular configuration, allowing consumers to install the TV with or without the sound bar, setting the stage for the ideal custom home theater entertainment environment.
Customers interested in the VIZIO Reference Series Ultra HD TV can sign up to receive email updates on the product and browse additional information at VIZIO.com.
The Best Universal Remote Controls
Sonos Arc vs Bose Smart Soundbar 900: Atmos minimalism
Intel Core i9-12900K and Core i5-12600K Review
View all Tech


Reads: "It's beginning to look a lot like cocktails"
Reads: " Home: where the pants are stretchy and wifi connects automatically."
Reads: " More mimosas please!"
Reads: "I have mixed drinks about feelings"
Reads: "A state of anger caused by lack of food; hunger causing a negative change in emotional state."


text:
Prep Football Pick 'Em: Voice your opinion on Level 1's matchups
Nov 8, 2020 Updated Nov 11, 2020
D1: No. 1 Menomonie (5-1) at No. 4 Marshfield (0-5), 7 p.m. Friday
Menomonie completed its regular season with a 37-21 victory against New Richmond in a late-scheduled game last week. Marshfield is still looking for its first win after a close 14-12 loss to Hortonville. The Mustangs beat the Tigers earlier this year 32-0.
No. 4 Rice Lake (2-5) at No. 1 Medford (6-1), 7 p.m. Friday
Rice Lake has won two straight, including a 27-6 upset of this Medford team. The Warriors most recently bested Wausau West 26-23 on a late field goal, while Medford last beat Rhinelaner 24-7.
D3: No. 4 Altoona (0-4) at No.1 Baldwin-Woodville (3-4), 7 p.m. Friday
Altoona last played on Oct. 23, a 25-8 loss to Viroqua. Baldwin-Woodville fell below .500 in the regular season last week with a 34-12 loss to Osceola.
Baldwin-Woodville
D4: No. 4 St. Croix Falls (3-3) at No. 1 Bloomer (3-3), 7 p.m. Friday
These two Heart O' North squads meet again in the playoffs. Bloomer, which last beat Cameron 36-27 on Oct. 30, won the first meeting between these teams 34-28. St. Croix Falls is coming off a 21-0 victory against Spooner.
D4: No. 3 Spooner (4-3) at No. 2 Elk Mound (4-3), 7 p.m. Friday
Elk Mound is coming off a 32-16 victory against Osseo-Fairchild, while Spooner last fell 21-0 to St. Croix Falls.
D4: No. 4 Stanley-Boyd (5-2) at No. 1 Colby (5-0), 7 p.m. Friday
The Orioles earned an impressive 27-20 victory against Mondovi in their Cloverbelt finale. They play a former Cloverbelt member in Colby, which stayed undefeated with a 44-6 win against Abbotsford. Colby was victorious in the meeting between these teams last year, 33-6.
Stanley-Boyd
D4: No. 3 Spencer/Columbus (5-2) at No. 2 Cumberland (7-0), 7 p.m. Friday
Cumberland completed an undefeated regular season with a 18-14 victory against Durand on Friday. Spencer/Columbus is coming off a 30-29 win against Amherst.
Spencer/Columbus
D5: No. 2 Mondovi (4-3) at No. 1 Luther (2-3), 7 p.m. Friday
This game was supposed to be a Level 2 matchup, but was pushed up when both Level 1 games were forfeited. Mondovi dropped a 27-20 contest to Stanley-Boyd in the Buffaloes' regular season finale. Luther dropped below .500 last week with a 34-14 loss to Potosi/Cassville.
D5: No. 4 Unity (4-2) at No. 1 Spring Valley (6-0), 7 p.m. Friday
Spring Valley secured an undefeated regular season, rolling to a 54-0 win against Rib Lake/Prentice in a late-scheduled matchup. Unity is coming off as a 25-6 win against Lake Holcombe/Cornell. The Cardinals defeated Unity 47-20 in last year's playoffs.
D5: No. 3 Durand (5-2) at No. 2 Grantsburg (4-2), 7 p.m. Friday
Durand dropped a second straight, falling 18-14 in a nonconference clash against Cumberland. Grantsburg is coming off a 44-7 win against Ladysmith.
D6: No. 4 Webster (3-3) at No. 1 Boyceville (5-1), 7 p.m. Friday
Boyceville last played two weeks ago, a 16-8 win against Cadott. Webster has also been off a week, when the team dropped a 38-7 contest to Unity.
D6: No. 4 Cochrane-Fountain City (1-3) at No. 1 Blair-Taylor (6-0), 7 p.m. Friday
The playoffs bring these two Dairyland squads back together. Blair-Taylor, coming off a 24-0 win against Melrose-Mindoro, won the first meeting 24-14. Cochrane-Fountain City is coming off a 30-25 loss to Eleva-Strum.
Cochrane-Fountain City
Blair-Taylor
D6: No. 3 Independence/Gilmanton (1-3) at No. 2 Loyal (1-4), 7 p.m. Friday
Independence/Gilmanton last played on Oct. 23, a 13-8 loss to Whitehall. Loyal has had a week off since a 46-8 loss to Iola-Scandinavia.
Independence/Gilmanton
8-man: No. 2 Siren (1-3) at No. 1 McDonell (4-3), 7 p.m. Friday
McDonell fell to Gilman for a second time this year last week, 53-14. Siren is coming off a 54-30 loss to Three Lakes.
McDonell
Pepin/Alma (5-2) at Augusta (1-5), 7 p.m. Friday
These two squads will play in a late-scheduled game after their playoff opponents both canceled.
Pepin/Alma


Bring the casino feel to your home game with this set of 10 high-quality, poker-size, green plastic cut cards.
A cut card is most commonly used when cutting a deck of cards, and to prevent the card on the bottom of the deck from being exposed when dealing.
Each cut card measures 2.5" x 3.5" and is made from 100 percent plastic. These are thick cut and extra durable for a long life span.


text:
Q: Getting first day of month in PHP 5.2.6? I have following scenario: Datepicker for user to choose Year,Month, and use it to display records for the selected month. The selected value is passed to details_subcontractor.php, using Ajax. Datepicker has been modified from accepted answer in jQuery UI DatePicker to show month year only. Sample code as below:
/**
 *  Datepicker in datepicker.php
 *
 */

$("#year_month").datepicker({"dateFormat":"yy-mm-dd",
    changeMonth: true,
    changeYear: true,
    dateFormat: 'yy-mm',
    showButtonPanel: true,
    onClose: function(dateText, inst) {
        var month = $("#ui-datepicker-div .ui-datepicker-month :selected").val();
        var year = $("#ui-datepicker-div .ui-datepicker-year :selected").val();
        $(this).datepicker('setDate', new Date(year, month, 1));
    }
});

/**
 *  Ajax call
 *
 */

var year_month = $("#year_month").val();
$.ajax({
    url:"details_subcontractor.php",
    data:{
        year_month:year_month
    },
    success:function(data){
        $("#content_report").html(data);
    }
});

/**
 *  details_subcontractor.php
 *
 */

//$_GET['year_month']; //2012-12
$start = date('Y-m-d', strtotime($_GET['year_month']));                     //2012-12-18
$start = date('Y-m-d', strtotime('first day of ' . $_GET['year_month']));   //1970-01-01
$start = date('Y-m-d', strtotime($_GET['year_month'] . ' first day'));      //2012-12-19
$end   = date('Y-m-d', strtotime('last day of ' . $_GET['year_month']));    //1970-01-01
$end   = date('Y-m-d', strtotime($_GET['year_month'] . ' last day'));       //2012-12-17

However, as the inline comment shows, I can't get first day and last day of the Month. I'm aware that 'of' is introduced at PHP 5.3, where the 2 lines that contain 'of' are failed, but I don't understand the output of other three.
I ended up with appending '-01' and '-31' to indicate first and last day of month. Does anyone have a better solution, that works in PHP 5.2.6?

A: You can safely assume that the first day of every month is 1.  Use
date('Y-m-t', strtotime($_GET['year_month']));

for the last day of the month.

A: // The first day is always 01, so you can hardcode it
$start = date('Y-m-01', strtotime($_GET['year_month']));

// last day you can get by `t` format parameter, which contains total days count for given month.
$end = date('Y-m-t', strtotime($_GET['year_month']));


text:
package org.ovirt.engine.core.bll;

import static org.junit.Assert.assertTrue;
import static org.mockito.Mockito.when;

import org.junit.Test;
import org.ovirt.engine.core.common.TimeZoneType;
import org.ovirt.engine.core.common.config.ConfigValues;
import org.ovirt.engine.core.common.queries.TimeZoneQueryParams;

public class GetDefaultTimeZoneQueryTest extends AbstractSysprepQueryTest<TimeZoneQueryParams, GetDefaultTimeZoneQuery<TimeZoneQueryParams>> {

    /** The default time zone for the test */
    private static final String DEFAULT_WINDOWS_TIME_ZONE = "Israel Standard Time";
    private static final String DEFAULT_GENERAL_TIME_ZONE = "Asia/Jerusalem";

    @Test
    public void testQueryDefaultWindowsTimeZone() {
        mcr.mockConfigValue(ConfigValues.DefaultWindowsTimeZone, DEFAULT_WINDOWS_TIME_ZONE);
        when(getQueryParameters().getTimeZoneType()).thenReturn(TimeZoneType.WINDOWS_TIMEZONE);
        getQuery().executeQueryCommand();

        @SuppressWarnings("unchecked")
        String result = (String) getQuery().getQueryReturnValue().getReturnValue();

        assertTrue("Wrong default time zone: " + result, result.equals(DEFAULT_WINDOWS_TIME_ZONE));
    }

    @Test
    public void testQueryDefaultGeneralTimeZone() {
        mcr.mockConfigValue(ConfigValues.DefaultGeneralTimeZone, DEFAULT_GENERAL_TIME_ZONE);
        when(getQueryParameters().getTimeZoneType()).thenReturn(TimeZoneType.GENERAL_TIMEZONE);
        getQuery().executeQueryCommand();

        @SuppressWarnings("unchecked")
        String result = (String) getQuery().getQueryReturnValue().getReturnValue();

        assertTrue("Wrong default time zone: " + result, result.equals(DEFAULT_GENERAL_TIME_ZONE));
    }
}


text:
package com.planet57.gshell.event;

import org.sonatype.goodies.lifecycle.Lifecycle;

/**
 * Manages event subscriptions and publishes events.
 *
 * @since 3.0
 */
public interface EventManager
  extends Lifecycle
{
  /**
   * Register event listener.
   */
  void register(Object listener);

  /**
   * Remove event listener.
   */
  void unregister(Object listener);

  /**
   * Publish an event.
   */
  void publish(Object event);
}


Iketeru will be offering a fivecourse Japanese menu with highlights that include assorted sushi and sashimi, teppanyaki grilled wagyu sirloin and sweet pan cake with green tea ice cream. There's even a Japaneseinspired version of fish and chips. You can add a bottle of saké to your meal for an additional RM160nett.