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Featured ArticleArticles, Behavioral/Systems/Cognitive
Tagging the Neuronal Entrainment to Beat and Meter
Sylvie Nozaradan, Isabelle Peretz, Marcus Missal and André Mouraux
Journal of Neuroscience 13 July 2011, 31 (28) 10234-10240; DOI: https://doi.org/10.1523/JNEUROSCI.0411-11.2011
Sylvie Nozaradan
Isabelle Peretz
Marcus Missal
André Mouraux
Feeling the beat and meter is fundamental to the experience of music. However, how these periodicities are represented in the brain remains largely unknown. Here, we test whether this function emerges from the entrainment of neurons resonating to the beat and meter. We recorded the electroencephalogram while participants listened to a musical beat and imagined a binary or a ternary meter on this beat (i.e., a march or a waltz). We found that the beat elicits a sustained periodic EEG response tuned to the beat frequency. Most importantly, we found that meter imagery elicits an additional frequency tuned to the corresponding metric interpretation of this beat. These results provide compelling evidence that neural entrainment to beat and meter can be captured directly in the electroencephalogram. More generally, our results suggest that music constitutes a unique context to explore entrainment phenomena in dynamic cognitive processing at the level of neural networks.
Beat perception in music refers to the ability to perceive periodicities from sounds that are not necessarily periodic in reality (e.g., spontaneous head bouncing, foot tapping on the beat when listening to music) (Large, 2008). Beats can be organized in meters, corresponding to subharmonics (i.e., integer ratios) of the beat frequency.
How beat and meter are processed in the human brain remains largely unknown. The resonance theory for beat and meter perception (Large and Kolen, 1994; van Noorden and Moelants, 1999; Large, 2008) proposes that beat perception emerges from the entrainment of neuronal populations resonating at the beat frequency, itself giving rise to higher-order resonance at subharmonics of beat frequency, corresponding to the meter. Several studies have explored the neural processes underlying beat and meter perception using original but indirect approaches to examine how beat and meter structures create temporal expectancies and metrical representations. For example, investigators have examined how beat and meter may influence the transient evoked potentials (EPs) elicited by brief violations or accentuations inserted in a beat structure (Brochard et al., 2003; Snyder and Large, 2005; Grube and Griffiths, 2009), or how the transient EPs elicited by auditory stimuli may be modulated as a function of their position with respect to the beat structure (Iversen et al., 2009; Fujioka et al., 2010; Schaefer et al., 2011). All these findings are compatible with the theory of neural resonance. Indeed, neuronal oscillations have been shown to be instruments of entrainment in sensory cortices. In particular, Lakatos et al. (2008) showed that neuronal oscillations in primary sensory cortices may entrain to attended rhythmic streams. Hence, the observed modulations of transient EPs by beat and meter could be interpreted as the consequence of a periodic modulation of the responsiveness of the neuronal populations giving rise to these transient EPs. However, direct neurophysiological evidence supporting this resonance theory in the context of musical beat and meter is still lacking.
Here, we chose a novel approach: we hypothesized that neuronal entrainment to beat and meter can be captured directly as a steady-state EP, that is, the electrocortical activity generated by a population of neurons resonating by entrainment at the frequency of a periodic stimulus (Galambos et al., 1981; Regan, 1989; Draganova et al., 2002; Plourde, 2006). To this aim, we asked participants to listen to a sound pattern from which they could perceive a 2.4 Hz beat. They were asked to voluntarily imagine the meter of this beat as either binary or ternary (Fig. 1). We predicted that the beat extracted from the sound pattern would elicit a steady-state EP at the beat frequency (f = 2.4 Hz) and, most importantly, that the meter imagery would elicit a distinct steady-state EP at the metrically related subharmonic of beat frequency (f/2 and f/3 for binary and ternary meters, respectively). Thereby, we aimed to tag directly the neuronal entrainment hypothesized to subtend beat perception, as well as the higher-order resonance phenomenon hypothesized to underlie the representation of meter.
Experimental design. A, A 6 s excerpt of the 33 s auditory stimulus (x-axis: time; y-axis: sound amplitude). Note the pseudo-periodic beat structure, visible as a slightly irregular modulation of amplitude. From this pseudo-periodic stimulus, subjects perceived the 2.4 Hz beat represented in blue. In the binary and ternary meter conditions (shown in red and green, respectively), subjects were asked to imagine a binary (1.2 Hz) and ternary (0.8 Hz) metric structure onto this beat. B, The frequency spectrum of the sound stimulus. Note the peak corresponding to the frequency of the tone (333.33 Hz), as well as the sideband frequencies resulting from the convolution of that carrier frequency with the two different amplitude modulation frequencies (2.4 and 11 Hz). C, The frequency content of the sound envelope obtained by convoluting the two different amplitude modulation frequencies (2.4 and 11 Hz). Note that the sound envelope contains a peak at the frequency corresponding to the beat (2.4 Hz), but does not contain any sideband frequencies at the frequency of the binary (1.2 Hz) and ternary (0.8 Hz) meters.
Eight healthy volunteers (3 females, 7 right-handed; mean age, 30 ± 4 years; age range, 22–32 years) took part in the study after providing written informed consent. They all had musical experience, either in performance (3 participants with 15–25 years of practice) or as amateur listeners or dancers (5 participants). They had no history of hearing, neurological, or psychiatric disorder, and were not taking any drug at the time of the experiment. The study was approved by the local ethics committee.
Auditory stimulation.
Each auditory stimulus lasted 33 s. The stimulus consisted of a 333.3 Hz pure tone in which a 2.4 Hz auditory beat was introduced by modulating the amplitude of the tone with a 2.4 Hz periodicity (i.e., 144 beats/min), using an asymmetrical Hanning envelope (22 ms rise time and 394 ms fall time, amplitude modulation between 0 and 1). A 2.4 Hz periodicity was chosen because (1) pilot participants were comfortable in imagining binary (1.2 Hz) and ternary (0.8 Hz) rhythms using this 2.4 Hz tempo and (2) these tempi lie in the ecological range of tempo perception and production (Drake and Botte, 1993). The sound was then amplitude modulated using an 11 Hz sinusoidal function oscillating between 0.3 and 1. Because the 2.4 Hz frequency was not an integer ratio of the 11 Hz frequency, the convolution of the two frequencies generated subtle irregularities in terms of amplitude and occurrence of the beats, thus resulting in a pseudo-periodic beat structure (Fig. 1A). Importantly, the frequency content of the sound envelope obtained by convoluting the two different amplitude modulation frequencies (2.4 and 11 Hz) contained a peak at the frequency of the beat (2.4 Hz) but did not contain any sideband frequencies corresponding to the frequencies of the binary or ternary meters (i.e., 1.2 and 0.8 Hz, respectively) (Fig. 1C). The subtle irregularities of the beat were perceived by all subjects and were purposely created to avoid induction of an involuntary binary subjective meter in the control condition (Bolton, 1894; Vos, 1973). Furthermore, the pseudo-periodicity of the beat structure, resulting from these irregularities, was closer to the more ecological situation where beat perception refers to the perception of periodicity from a non-strictly periodic framework (Large, 2008).
The auditory stimuli were generated using the PsychToolbox extensions (Brainard, 1997) running under Matlab 6.5 (The MathWork), and presented binaurally through earphones at a comfortable hearing level (BeyerDynamic DT 990 PRO).
Meter mental imagery and control conditions.
Participants were asked to perform three different tasks: a control task, a binary meter imagery task, and a ternary meter imagery task, in separate conditions (Fig. 1). Each condition consisted of 10 trials during which the 33 s auditory stimulus was presented after a 3 s foreperiod. Stimulus presentation was self-paced. During the first condition, participants performed the control task. They were asked to detect a very short (4 ms) sound interruption that was inserted at a random position in two additional trials interspersed within the block. This control task required a sustained level of attention as the stimulus had a complex structure. The two trials containing a short interruption were excluded from further analyses. During the second condition, participants performed the binary meter imagery task. They were asked to imagine a binary metric structure onto the perceived beat (f/2 = 1.2 Hz). During the third condition, they performed the ternary meter imagery task, by imagining a ternary metric structure onto the beat (f/3 = 0.8 Hz). Before the binary and ternary meter conditions, to ensure that participants understood the task, they were asked to perform overt movements (e.g., hand tapping, aloud counting) paced to the imposed metric structure, first with the help of the experimenter, and then alone. Subjective evaluation by the experimenter of the synchrony of those movements with the meter indicated that all participants performed the task without difficulty. The participants were then asked to begin their meter imagery as soon as they heard the first auditory beat of the stimulus, and to maintain this imagery as consistently as possible throughout the entire trial. During debriefing, participants reported that they had performed the mental imagery task without difficulty, although it did require a relatively high level of attention.
EEG recording.
Subjects were comfortably seated in a chair with their head resting on a support. They were instructed to relax, avoid any head or body movement during the recordings, and keep their eyes fixated on a point displayed on a computer screen in front of them. The experimenter remained in the recording room to monitor compliance to these instructions. The EEG was recorded using 64 Ag-AgCl electrodes placed on the scalp according to the International 10/10 system (Waveguard64 cap, Cephalon A/S). Vertical and horizontal eye movements were monitored using four additional electrodes placed on the outer canthus of each eye and in the inferior and superior areas of the right orbit. Electrode impedances were kept at <10 kΩ. The signals were amplified, low-pass filtered at 500 Hz, digitized using a sampling rate of 1000 Hz, and referenced to an average reference (64 channel high-speed amplifier, Advanced Neuro Technology).
EEG analysis.
Continuous EEG recordings were filtered using a 0.1 Hz high-pass Butterworth zero-phase filter to remove very slow drifts in the recorded signals. EEG epochs lasting 32 s were then obtained by segmenting the recordings from +1 to +33 s relative to the onset of the auditory stimulus at the beginning of each trial, thus yielding 10 epochs for each subject and condition. The EEG recorded during the first second of each epoch was removed (1) to discard the transient auditory evoked potential related to the onset of the stimulus (Saupe et al., 2009), (2) because previous studies have shown that steady-state EPs require several cycles of stimulation to be steadily entrained (Regan, 1989), and (3) because previous studies have shown that several repetitions of the beat are required to elicit a steady perception of beat and meter (Repp, 2005). These EEG processing steps were performed using Analyzer 1.05 (Brain Products).
The following EEG processing steps were performed using Letswave (Mouraux and Iannetti, 2008), Matlab (The MathWorks), and EEGLAB (http://sccn.ucsd.edu).
Artifacts produced by eye blinks or eye movements were removed using a validated method based on an independent component analysis (Jung et al., 2000), using the runica algorithm (Bell and Sejnowski, 1995; Makeig et al., 1996), as implemented in EEGLAB. For each subject and condition, EEG epochs were averaged across trials to reduce the contribution of activities non-phase locked to the stimulation train. The time-domain-averaging procedure was used to enhance the signal-to-noise ratio by attenuating the contribution of activities that were not strictly phase locked across trials (i.e., activities that were not phase locked to the sound stimulus). The obtained average waveforms were then transformed in the frequency domain using a discrete Fourier transform (Frigo and Johnson, 1998), yielding a frequency spectrum of signal amplitude (μV) ranging from 0 to 500 Hz with a frequency resolution of 0.031 Hz (Bach and Meigen, 1999).
Within the obtained frequency spectra, signal amplitude may be expected to correspond to the sum of (1) EEG activity induced by the auditory beat and/or the meter imagery task (i.e., beat- and meter-related steady-state EPs) and (2) unrelated residual background noise due, for example, to spontaneous EEG activity, muscle activity, or eye movements. Therefore, to obtain valid estimates of the beat- and meter-related steady-state EPs, the contribution of this noise was removed by subtracting, at each bin of the frequency spectra, the average amplitude measured at neighboring frequency bins (two frequency bins ranging from −0.15 to −0.09 Hz and from +0.09 to +0.15 Hz relative to each frequency bin). The validity of this subtraction procedure relies on the assumption that, in the absence of a steady-state EP, the signal amplitude at a given frequency bin should be similar to the signal amplitude of the mean of the surrounding frequency bins.
Finally, the magnitude of beat- and meter-related steady-state EPs was estimated by averaging the signal amplitude measured at the three frequency bins centered on the target frequency of each steady-state EP (i.e., 2.4 Hz: bins ranging from 2.356 to 2.418 Hz; 1.2 Hz: bins ranging from 1.178 to 1.240 Hz; 0.8 Hz: bins ranging from 0.775 to 0.837 Hz; 1.6 Hz: bins ranging from 1.581 to 1.643 Hz), thereby accounting for a possible spectral leakage due to the fact that the discrete Fourier transform did not estimate signal amplitude at the exact frequency of each steady-state EP.
Statistical analyses.
For each participant, condition, and target frequency, the magnitude of steady-state EPs was averaged across all scalp electrodes, thus excluding any electrode selection bias (see Figs. 2, 3). This approach was used because there was no a priori assumption on the scalp topography of the beat- and meter-induced responses. Group-level results were expressed using the median and interquartile range (see Fig. 4). To examine whether the beat and meter induced a significant steady-state response, one-sample t tests were used to determine whether the noise-subtracted amplitudes measured at the target frequencies were significantly different from zero. Indeed, in the absence of a steady-state response, the average of the subtracted signal amplitude may be expected to tend toward zero.
To compare the beat- and meter-induced steady-state responses across experimental conditions, for each target frequency a one-way repeated-measures ANOVA was used to compare the noise-subtracted amplitudes obtained in the control, binary meter, and ternary meter conditions. Degrees of freedom were corrected using the Greenhouse–Geisser correction for violations of sphericity. Size effects were expressed using the partial η2. When significant, post hoc pairwise comparisons were performed using paired-sampled t tests. The significance level was set at p < 0.05.
Transient auditory event-related potentials.
To examine whether the beat and meter elicited transient auditory event-related potentials that could be identifiable in the time domain, average waveforms were computed after bandpass filtering (0.3 Hz to 30 Hz) and epoch segmentation from +1 s to +33 s relative to the onset of the sound stimulus (see Fig. 5).
As shown at the individual level (Fig. 2) as well as in the group-level average of the global field amplitude spectra (Fig. 3), the auditory beat elicited, in all three conditions, a clear increase of EEG signal amplitude at 2.4 Hz, corresponding to the frequency of the beat, and referred to as beat-related steady-state EP. Furthermore, binary meter imagery elicited an additional response at 1.2 Hz (corresponding to the frequency of the binary meter), whereas ternary meter imagery elicited an additional response at 0.8 Hz (corresponding to the frequency of the ternary meter) and 1.6 Hz (corresponding to the first upper harmonic of the frequency of the ternary meter), referred to as binary and ternary meter-related steady-state EPs, respectively.
Beat- and meter-related steady-state EPs recorded in a single representative subject. Bottom, The EEG amplitude spectrum (in microvolts) from 0 to 45 Hz, averaged across all scalp electrodes, after applying the noise subtraction procedure (see Materials and Methods). The EEG spectrum obtained in the control condition is shown in blue, whereas the EEG spectra obtained in the binary and ternary meter imagery conditions are shown in red and green, respectively. Middle, The EEG amplitude spectrum (in microvolts) within a frequency range comprising the frequency of the beat (2.4 Hz) and the frequency of the imagined binary and ternary meters (1.2 and 0.8 Hz, respectively). Note that in all three conditions, the auditory stimulus elicited, at f = 2.4 Hz, a clear beat-related steady-state EP. Also note the emergence of a meter-related steady-state EP at 1.2 Hz in the binary meter imagery condition, and at 0.8 and 1.6 Hz in the ternary meter imagery condition. Top, The topographical maps of EEG signal amplitude at 0.8, 1.2, 1.6, and 2.4 Hz, obtained in each of the three conditions.
Group-level average of the beat- and meter-related steady-state EPs elicited by the 2.4 Hz auditory beat in the control condition (top), the binary meter imagery condition (middle), and the ternary meter imagery condition (bottom). The frequency spectra represent the amplitude of the EEG signal (in microvolts) as a function of frequency, averaged across all scalp electrodes, after applying the noise subtraction procedure (see Materials and Methods). The group-level average frequency spectra are shown using a thick colored line, while single-subject spectra are shown in gray lines. Note that in all three conditions, the auditory stimulus elicited a clear beat-related steady-state EP at f = 2.4 Hz. Also, note the emergence of a meter-related steady-state EP at 1.2 Hz in the binary meter imagery condition, and at 0.8 and 1.6 Hz in the ternary meter imagery condition.
Beat-related steady-state EP
The median noise-subtracted amplitude of the 2.4 Hz beat-related steady-state EP, averaged across all scalp electrodes, was 0.23 μV (interquartile range, 0.12–0.27 μV) in the control condition; 0.20 μV (interquartile range, 0.12–0.28 μV) in the binary meter condition; and 0.22 μV (interquartile range, 0.14–0.35 μV) in the ternary meter condition (Figs. 3, 4). This increase in signal amplitude was significant in all three conditions (control condition: t = −8.1, p < 0.0001; binary meter condition: t = −4.3, p = 0.003; ternary meter condition: t = −4.4, p = 0.03).
Amplitude of the beat- and meter-related steady-state EPs elicited in the control condition, the binary meter imagery condition, and the ternary meter imagery condition. Dots represent individual amplitude values of the EEG signal for each experimental condition at each target frequency (1.2, 0.8, 1.6, and 2.4 Hz), averaged across all scalp electrodes after applying the noise subtraction procedure. The whisker plots represent the group-level median and interquartile range.
The scalp topography of the beat-related steady-state EP was widely distributed over both hemispheres, and most often maximal over frontocentral and temporal regions (Fig. 2, in one subject, as shown).
The magnitude of the beat-related steady-state EP was not significantly different across conditions (F(1.6,11.5) = 0.7, p = 0.494, η2 = 0.09) (Figs. 2⇑–4).
Meter-related steady-state EPs
In the binary meter condition, the noise-subtracted amplitude of the 1.2 Hz meter-related steady-state EP was 0.12 μV (interquartile range, 0.05–0.24 μV). This increase in signal amplitude was significant (t = −3.1, p = 0.01). In contrast, the amplitude of the noise-subtracted signal at 1.2 Hz obtained in the control condition (0.004 μV; interquartile range, −0.04–0.03 μV) and in the ternary meter condition (0.004 μV; interquartile range, −0.01–0.03 μV) was not significantly greater than zero (control condition: t = −0.2, p = 0.81; ternary meter condition: t = −0.10, p = 0.92) (Figs. 2, 3).
The magnitude of the 1.2 Hz meter-related steady-state EP differed significantly across conditions (F(1.2,13.4) = 11.5, p = 0.008, η2 = 0.62). Post hoc comparisons revealed that the magnitude of the EEG signal at 1.2 Hz was significantly greater in the binary meter condition than in the control condition (t = 3.4; p = 0.012) and the ternary meter condition (t = 3.6; p = 0.009) (Fig. 4).
In the ternary meter condition, the noise-subtracted amplitude of the 0.8 Hz meter-related steady-state EP was 0.18 μV (interquartile range, 0.10–0.21 μV) and that of the 1.6 Hz meter-related steady-state EP was 0.08 μV (interquartile range, 0.05–0.14 μV). Both increases in signal amplitude were significant (t = 5.7, p = 0.001; and t = 26.8, p < 0.0001, respectively). In contrast, the amplitude of the noise-subtracted signals obtained at 0.8 and 1.6 Hz in the control condition [0.8 Hz: −0.02 μV (−0.05–−0.01 μV); 1.6 Hz: 0.02 μV (−0.02–0.023 μV)] and in the binary meter condition [0.8 Hz: −0.002 μV (−0.07–0.02 μV); 1.6 Hz: −0.003 μV (−0.01–0.02 μV)] were not significantly greater than zero (control condition at 0.8 Hz: t = 0.1, p = 0.91, and 1.6 Hz: t = −0.3, p = 0.74; binary meter condition at 0.8 Hz: t = 1.4, p = 0.21, and 1.6 Hz: t = −0.4, p = 0.71) (Figs. 2, 3).
The magnitude of the 0.8 and 1.6 Hz meter-related steady-state EP differed significantly across conditions (0.8 Hz: F(1.8,12.4) = 12.5, p = 0.001, η2 = 0.64; 1.6 Hz: F(1.2,7.9) = 22.1, p = 0.001, η2 = 0.76). Post hoc comparisons revealed that at both 0.8 and 1.6 Hz the magnitude of the EEG signal was significantly greater in the ternary meter condition than in both the control condition (0.8 Hz: t = 4.1, p = 0.005; 1.6 Hz: t = 6.1, p < 0.001) and the binary meter condition (0.8 Hz: t = 4.0, p = 0.005; 1.6 Hz: t = 10.8, p < 0.001) (Fig. 4).
The topographical distribution of the 1.2, 0.8, and 1.6 Hz meter-related steady-state EPs varied largely across subjects (Fig. 2, scalp topographies obtained in one subject).
Transient auditory event-related potentials
As shown in Figure 5, the onset of the auditory stimulus elicited a clear auditory evoked potential (N1 and P2 peaks), maximal at frontocentral electrodes. However, probably because the auditory beats were not induced by abrupt changes in the sound stream such as auditory "clicks," the beat onsets did not show measurable transient event-related potentials.
Transient auditory event-related potentials elicited by the 33 s sound stimulus (group-level average waveforms recorded at FCz) in the control condition (blue), the binary meter condition (red), and the ternary meter condition (green). Top, The onset of the auditory stimulus elicited a clear auditory evoked potential consisting of a negative peak (N1) followed by a positive peak (P2). In contrast, beat onsets (represented by the dashed vertical lines) did not elicit a measurable transient event-related potential.
Our results show that neural entrainment to beat and meter can be captured directly in the human EEG as a periodic response entrained at the frequency of the beat and meter, respectively. Indeed, we found that the perception of a beat in a complex auditory signal was related to the emergence of a sustained periodic response in the EEG spectrum, appearing as a steady-state EP at the beat frequency (f = 2.4 Hz). More importantly, although the auditory stimulus was identical in all experimental conditions, we found that the voluntary metric interpretation of the beat as binary or ternary induced the emergence of an additional periodic signal in the EEG, at the corresponding subharmonic of beat frequency (f/2 = 1.2 Hz and f/3 = 0.8 Hz for binary and ternary interpretations, respectively).
These findings provide strong and direct support to the resonance theory for beat and meter processing, which proposes that beat perception is subtended by the entrainment of neurons resonating at the beat frequency, and to the idea that endogenous metric representations of the beat are subtended by higher-order resonance products at frequencies corresponding to specific subharmonics of the beat frequency (Large and Kolen, 1994; van Noorden and Moelants, 1999; Large, 2008; Large and Snyder, 2009).
Neuronal entrainment to the beat
In the present study, the beat was induced by a continuous sound pattern whose amplitude envelope was not strictly periodic, thus requiring the endogenous reconstruction of beat periodicity. Musical beats are usually induced by acoustic features, such as a periodic modulation of loudness, melodic or harmonic accents, or timbre variations (Drake et al., 2000; London, 2004). Musical beats can also be generated by mental representations shaped by prior musical experience, by the expectation of a periodicity, and by a natural human tendency to generate periodic motions at rates corresponding to musical tempo range (Palmer and Krumhansl, 1990; van Noorden and Moelants, 1999; London, 2004).
How the brain performs these processes remains unclear. In the dynamic attending model proposed by Jones and Boltz (1989) and Large and Jones (1999), beat perception is considered to be the result of a dynamic process in which the periodic structure of the beat synchronizes or entrains the listener's attention, leading to a periodic modulation of expectancy as a function of time. Building on this notion, the resonance theory for beat and meter perception (Large and Kolen, 1994; van Noorden and Moelants, 1999; Large, 2008) proposes that beat perception is subtended by neuronal entrainment at the beat frequency. Here, we show that the periodic activity resulting from this neuronal entrainment can be captured directly in the human EEG, as a steady-state EP. Nevertheless, whether or not the beat- and meter-induced steady-state responses reported in the present study reflected the entrainment of the neuronal populations contributing to transient auditory-evoked potentials remains, at present, an open question (Navarro Cebrian and Janata, 2010).
Furthermore, we propose that the beat-induced periodic EEG response identified in the present study may constitute a direct correlate of the actual mechanism through which attentional and perceptual processes are dynamically modulated as a function of time. Indeed, the responsiveness of the neuronal population that is entrained to the beat may be expected to vary according to the phase of the beat-induced cycle. Most importantly, this hypothesis would account for the previous observations that event-related potentials elicited at different time points relative to the beat or meter cycle exhibit differences in amplitude (Brochard et al., 2003; Snyder and Large, 2005; Pablos Martin et al., 2007; Grube and Griffiths, 2009; Iversen et al., 2009; Fujioka et al., 2010; Schaefer et al., 2011). Indeed, several electrophysiological studies in primates including humans have suggested that when the activity of a neuronal population synchronizes at a given frequency, the phase of the induced oscillations can elicit a cyclic fluctuation of the excitability of the responding neuronal population, leading to an amplitude modulation of the event-related brain potentials that can be generated by these populations (Varela et al., 1981; Haig and Gordon, 1998; Makeig, 2002; Buzsáki and Draguhn, 2004; Lakatos et al., 2008; Schroeder et al., 2008; Sirota et al., 2008), but also a modulation of behavioral performance (Busch et al., 2009).
Neuronal entrainment to the meter
Musical beats can be organized in meters. As for the beat, meters in music are usually induced by accents, defined as periodic physical changes in the beat sequence such as changes in duration, loudness, timbre, or pitch (Lerdahl and Jackendoff, 1983). When these accents are impoverished, ambiguous, or even absent, the perception of a meter can still emerge, based on mental representations of meter (Lerdahl and Jackendoff, 1983; Repp, 2010). Perception of meter can emerge involuntarily as in the "tick tock" phenomenon (Bolton, 1894; Vos, 1973; Brochard et al., 2003) or, as in the present study, be induced voluntarily by imposing onto the beat the mental imagery of a given meter (Iversen et al., 2009; Fujioka et al., 2010; Schaefer et al., 2011).
Perceiving a given metric structure introduces additional periodicities, corresponding to integer ratios, or subharmonics, of the beat frequency (e.g., f/2 for a binary meter, as in a march; f/3 for a ternary meter, as in a waltz). A number of psychophysical and electrophysiological studies have shown that humans have a natural preference for such integer ratios in timing perception and production (Essens, 1986; Brochard et al., 2003; Repp, 2005; Pablos Martin et al., 2007), corroborating the resonance theory for beat and meter processing (Large, 2008). Our finding that an internally driven metric structure applied onto the beat induces a periodic response in the EEG at the frequency of the applied meter suggests that the metric interpretation of the beat could emerge from the facilitation or enhancement of specific subharmonics within the neuronal network entrained by the beat. Importantly, because, in the present study, this metric interpretation was entirely driven by mental imagery, one must hypothesize that the emergence of these subharmonics of beat frequency can be generated through a dynamic top-down biasing of auditory beat processing.
Interestingly, when participants performed the ternary meter imagery task, this led not only to the emergence of a steady-state EP at the frequency of the corresponding meter (f/3 = 0.8 Hz), but also at twice this frequency (1.6 Hz). The frequency of this additional steady-state EP corresponds to the frequency of the first upper harmonic of the meter frequency [i.e., 2 × (f/3) = 1.6 Hz] and could thus reflect the involuntary emergence of an additional metric level, here corresponding to a binary metric level spontaneously emerging alongside the voluntary ternary metric representation. This interpretation would suggest that the representation of multiple metric levels could be represented by such higher-order resonance products and would agree with the natural human bias for binary structures in timing perception and production (Essens, 1986; Brochard et al., 2003; Repp, 2005; Pablos Martin et al., 2007). Conversely, the frequency of this additional steady-state EP also corresponds to the frequency of the cross-modulation product between beat and meter frequencies [i.e., f − (f/3) = 1.6 Hz]. Several studies have shown that when two or more steady-state EPs are elicited simultaneously, cross-modulation products can appear due to the nonlinear convergence of the two oscillators (Regan, 1989; Sutoyo and Srinivasan, 2009). Hence, this additional steady-state EP could reflect an interaction between beat and meter processing in the human brain, in the form of a specific higher-order resonance product, or "integration frequency" (Regan, 1989; Sutoyo and Srinivasan, 2009).
The results of the present study constitute direct experimental evidence for the entrainment of neuronal populations at the frequency of the beat, and at the subharmonics corresponding to the metric interpretation of this beat. These findings thus bring strong support for the resonance theory for beat and meter perception in humans (Large and Kolen, 1994; van Noorden and Moelants, 1999; Large, 2008). More generally, the finding that a mental representation of a given metric structure can induce a marked neuronal entrainment at the frequency of the meter provides a compelling empirical evidence of the theory of neuronal oscillations for dynamic cognitive processing (Buzsáki and Draguhn, 2004) and suggests that, due to their inherent periodic temporal structures, music and dance constitute a unique context to explore the phenomenon of entrainment at the level of neural networks.
S.N. and M.M. are supported by the Fund for Scientific Research of the French-speaking community of Belgium. I.P. is supported by the Natural Sciences and Engineering Research Council of Canada, the Canadian Institutes of Health Research, and a Canada Research Chair. We thank Giandomenico Iannetti (University College London, London, UK), Valery Legrain (Ghent University, Ghent, Belgium), and Bruno Rossion (Université Catholique de Louvain, Brussels, Belgium) for their highlighting comments and suggestions.
Correspondence should be addressed to Dr. André Mouraux, Institute of Neuroscience (IONS), Université Catholique de Louvain, 53, Avenue Mounier—UCL 53.75, B-1200 Brussels, Belgium. andre.mouraux{at}uclouvain.be
Bach M,
Meigen T
(1999) Do's and don'ts in Fourier analysis of steady-state potentials. Doc Ophthalmol 99:69–82.
Bell AJ,
Sejnowski TJ
(1995) An information-maximization approach to blind separation and blind deconvolution. Neural Comput 7:1129–1159.
Bolton TL
(1894) Rhythm. Am J Psychol 6:145–238.
Brainard DH
(1997) The psychophysics toolbox. Spat Vis 10:433–436.
Brochard R,
Abecasis D,
Potter D,
Ragot R,
Drake C
(2003) The "tick-tock" of our internal clock: direct brain evidence of subjective accents in isochronous sequences. Psychol Sci 14:362–366.
Busch NA,
Dubois J,
VanRullen R
(2009) The phase of ongoing EEG oscillations predicts visual perception. J Neurosci 29:7869–7876.
Buzsáki G,
Draguhn A
(2004) Neuronal oscillations in cortical networks. Science 304:1926–1929.
Draganova R,
Ross B,
Borgmann C,
Pantev C
(2002) Auditory cortical response patterns to multiple rhythms of AM sound. Ear Hear 23:254–265.
Drake C,
Botte MC
(1993) Tempo sensitivity in auditory sequences: evidence for a multiple look model. Percept Psychophys 54:277–286.
Jones MR,
Baruch C
(2000) The development of rhythmic attending in auditory sequences: attunement, referent period, focal attending. Cognition 77:251–288.
Essens PJ
(1986) Hierarchical organization of temporal patterns. Percept Psychophys 40:69–73.
Frigo M,
Johnson SG
(1998) Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing FFTW: an adaptive software architecture for the FFT (IEEE, Washington, DC), Vol 3, pp 1381–1384.
Fujioka T,
Zendel BR,
Ross B
(2010) Endogenous neuromagnetic activity for mental hierarchy of timing. J Neurosci 30:3458–3466.
Galambos R,
Makeig S,
Talmachoff PJ
(1981) A 40-Hz auditory potential recorded from the human scalp. Proc Natl Acad Sci U S A 78:2643–2647.
Grube M,
Griffiths TD
(2009) Metricality-enhanced temporal encoding and the subjective perception of rhythmic sequences. Cortex 45:72–79.
Haig AR,
Gordon E
(1998) Prestimulus EEG alpha phase synchronicity influences N100 amplitude and reaction time. Psychophysiology 35:591–595.
Iversen JR,
Repp BH,
Patel AD
(2009) Top-down control of rhythm perception modulates early auditory responses. Ann NY Acad Sci 1169:58–73.
Boltz M
(1989) Dynamic attending and responses to time. Psychol Rev 96:459–491.
Jung TP,
Westerfield M,
Townsend J,
Courchesne E,
(2000) Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects. Clin Neurophysiol 111:1745–1758.
Lakatos P,
Karmos G,
Mehta AD,
Ulbert I,
Schroeder CE
(2008) Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320:110–113.
Grondin S
Large EW
(2008) in The psychology of time, Resonating to musical rhythm: theory and experiment, ed Grondin S (Emerald, West Yorkshire, UK), pp 189–232.
Large EW,
Jones MR
(1999) The dynamics of attending: how people track time-varying events. Psychol Rev 106:119–159.
Kolen JF
(1994) Resonance and the perception of musical meter. Connect Sci 6:177–208.
Snyder JS
(2009) Pulse and meter as neural resonance. The neurosciences and music III—disorders and plasticity. Ann NY Acad Sci 1169:46–57.
Lerdahl F,
Jackendoff R
(1983) A generative theory of tonal music (MIT, Cambridge, MA).
London J
(2004) Hearing in time: psychological aspects of musical meter (Oxford UP, London).
Makeig S
(2002) Response: event-related brain dynamics—unifying brain electrophysiology. Trends Neurosci 25:390.
Touretzky D,
Mozer M,
Hasselmo M
(1996) in Advances in neural information processing systems, Independent component analysis of electroencephalographic data, eds Touretzky D, Mozer M, Hasselmo M (MIT, Cambridge, MA), Vol 8, pp 145–151.
Mouraux A,
Iannetti GD
(2008) Across-trial averaging of event-related EEG responses and beyond. Magn Reson Imaging 26:1041–1054.
Navarro Cebrian A,
Janata P
(2010) Electrophysiological correlates of accurate mental image formation in auditory perception and imagery tasks. Brain Res 1342:39–54.
Pablos Martin X,
Deltenre P,
Hoonhorst I,
Markessis E,
Rossion B,
Colin C
(2007) Perceptual biases for rhythm: the mismatch negativity latency indexes the privileged status of binary vs non-binary interval ratios. Clin Neurophysiol 118:2709–2715.
Palmer C,
Krumhansl CL
(1990) Mental representations for musical meter. J Exp Psychol Hum Percept Perform 16:728–741.
Plourde G
(2006) Auditory evoked potentials. Best Pract Res Clin Anaesthesiol 20:129–139.
Regan D
(1989) Human brain electrophysiology: evoked potentials and evoked magnetic fields in science and medicine (Elsevier, New York).
Repp BH
(2005) Sensorimotor synchronization: a review of the tapping literature. Psychon Bull Rev 12:969–992.
(2010) Do metrical accents create illusory phenomenal accents? Atten Percept Psychophys 72:1390–1403.
Saupe K,
Schröger E,
Andersen SK,
Müller MM
(2009) Neural mechanisms of intermodal sustained selective attention with concurrently presented auditory and visual stimuli. Front Hum Neurosci 3:58.
Schaefer RS,
Vlek RJ,
Desain P
(2011) Decomposing rhythm processing: electroencephalography of perceived and self-imposed rhythmic patterns. Psychol Res 75:95–106.
Schroeder CE,
Kajikawa Y,
Partan S,
Puce A
(2008) Neuronal oscillations and visual amplification of speech. Trends Cogn Sci 12:106–113.
Sirota A,
Montgomery S,
Fujisawa S,
Isomura Y,
Zugaro M,
Buzsáki G
(2008) Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron 60:683–697.
Snyder JS,
(2005) Gamma-band activity reflects the metric structure of rhythmic tone sequences. Brain Res Cogn Brain Res 24:117–126.
Sutoyo D,
Srinivasan R
(2009) Nonlinear SSVEP responses are sensitive to the perceptual binding of visual hemifields during conventional "eye" rivalry and interocular "percept" rivalry. Brain Res 1251:245–255.
van Noorden L,
Moelants D
(1999) Resonance in the perception of musical pulse. J New Music Res 28:43–66.
Varela FJ,
Toro A,
John ER,
Schwartz EL
(1981) Perceptual framing and cortical alpha rhythm. Neuropsychologia 19:675–686.
Vos PG
(1973) Waarneming van metrische toon reeksen (Stichting Studentenpers, Nijmegen, The Netherlands).
You are going to email the following Tagging the Neuronal Entrainment to Beat and Meter
Sylvie Nozaradan, Isabelle Peretz, Marcus Missal, André Mouraux
Journal of Neuroscience 13 July 2011, 31 (28) 10234-10240; DOI: 10.1523/JNEUROSCI.0411-11.2011
Choice Behavior Guided by Learned, But Not Innate, Taste Aversion Recruits the Orbitofrontal Cortex
Maturation of Spontaneous Firing Properties after Hearing Onset in Rat Auditory Nerve Fibers: Spontaneous Rates, Refractoriness, and Interfiber Correlations
Insulin Treatment Prevents Neuroinflammation and Neuronal Injury with Restored Neurobehavioral Function in Models of HIV/AIDS Neurodegeneration
Behavioral/Systems/Cognitive
Episodic Reinstatement in the Medial Temporal Lobe
Musical Expertise Induces Audiovisual Integration of Abstract Congruency Rules
The Laminar Development of Direction Selectivity in Ferret Visual Cortex
Show more Behavioral/Systems/Cognitive


Who would have thought that the European garden charm can be brought to the U.S. in its full splendor not losing a bit of its beauty? Julie и Ben Pruet impressed by their European trip have recreated the original European garden charm in the privacy of their property in Little Rock, Arkansas. The garden shares different approaches in decorating: there is definatelly English-inspired outlines, however, there are also details influenced by Tuscany decorating style.
After returning from their trip to Europe, Pruet couple has decided to fulfill their distant dream. When they finished the construction of the house, they have started to renovate the outdoors drawing inspiration from English landscapes and Tuscany patios they have seen during their long stay in Italy and England. The garden has classy English hedges along with beautiful fountain focal points in classy art forms. Another attraction of this American garden is a beautiful wooden pergola with a slightly arched roof. The pergola hosts a charming French-styled furniture for outdoor leisure activities.
We liked the idea of the garden having a European flavor. We were members of the National Trust when we lived in England and had the opportunity to see many English-manor-style gardens through that experience.
The patio was the sole object that remained from the previous outdoor area. Taking patio as a starting point the couple managed to recreate the traditional English garden charm with a hint of relaxed Tuscany patio in decor. This is an excellent example when passion and inspiration can lead to creation of something truly exceptional and touching. Photoes via Athomearkansas.


text:
Thomas George Bonney  (27 July 1833 – 10 December 1923) was an English geologist, president of the Geological Society of London.

Career
Bonney was born in Rugeley, Staffordshire, England, the eldest son of the Reverend Thomas Bonney, headmaster of Rugeley Grammar School. His uncle was the Australian explorer Charles Bonney, and one of his brothers, Frederic Bonney, is remembered for his photography and ethnology in Australia. Thomas was educated at Uppingham School and St John's College, Cambridge, where he graduated as 12th wrangler in 1856, and was ordained in the following year.

From 1856 to 1861 he was mathematical master at Westminster School, and he pursued geology only as a recreational activity, mainly in Alpine regions. In 1868 he was appointed tutor at St John's College, Cambridge and lecturer in geology. His attention was specially directed to the study of the igneous and metamorphic rocks in Alpine regions and in various parts of England (e.g.: the Lizard in Cornwall, at Salcombe and in the Charnwood Forest), Wales and the Scottish Highlands.

From 1877 to 1901 he was professor of geology in University College London. He became secretary and later president of the Geological Society of London (1884–1886), and also a fellow; secretary of the British Association (1881–1885) and its president for the year 1910–1911; president of the Mineralogical Society. He was president of the Alpine Club, 1881–1883. In 1887, Bonney was appointed honorary canon of Manchester.

He was elected a Fellow of the Royal Society on 6 June 1878. He died in Cambridge on 10 December 1923. Lake Bonney in Antarctica is named after him.

Publications
His purely scientific works are:
 Cambridgeshire Geology (1875)
 The Story of our Planet (1893)
 Charles Lyell and Modern Geology (1895)
 Ice Work, Past and Present (1896)
 Volcanoes (1899).

In addition to many papers published in the Quarterly Journal of the Geological Society and Geological Magazine, he wrote several popular works on Alpine Regions, on English and Welsh scenery, as well as on theological subjects.

See also
Geology of the United Kingdom
Mount Bonney

References

David Oldroyd, 'Bonney, Thomas George (1833–1923)', Oxford Dictionary of National Biography, Oxford University Press, 2004

External links

1833 births
1923 deaths
People from Rugeley
English mountain climbers
English geologists
People educated at Uppingham School
Alumni of St John's College, Cambridge
People educated at Westminster School, London
Presidents of the Alpine Club (UK)
Fellows of St John's College, Cambridge
Fellows of the Geological Society of London
Fellows of the Royal Society
Wollaston Medal winners

redpajama_set_name: RedPajamaWikipedia


Childcare center inspires children to pursue their education with new experiences to encourage a love for learning through a hands-on teaching approach. Curriculum is based on the concept that children learn best through hands-on learning. Children learn social skills, problem-solving, following directions, and life skills as well as math, science, social studies and literacy concepts for kindergarten readiness.
Lil' Explorers is a licensed daycare center.


text:
Why Trying to Beat the S&P 500 Is a Bad Idea
Kate Stalter
U.S.News & World Report December 4, 2019
An advertisement on social media touts a trading product that is, apparently, beating the S&P 500 index.
The ad shows performance of the domestic large-cap index in 2018, as compared to the performance of this product. According to the data shown, the product had a better return last year.
Setting aside the highly unlikely scenario that buyers of the product were responsible for making all the right trades at the precise times, the question remains: Why is beating the S&P 500 even relevant?
[See: Beware of These 7 Blind Spots in Your Portfolio.]
Frequently, you'll see the S&P 500 described as the "benchmark index." The index measures performance of the 500 largest domestic public companies. Exchange-traded funds that track the index are widely held. The SPDR S&P 500 ETF (ticker: SPY), launched in 1993, was the first fund to track its namesake index, and the first ETF to trade in the U.S.
It currently holds about $286 billion in assets under management.
Because of the fund's long history and its popularity, it's understandable that investors might believe the S&P 500 is the most important index. That's compounded by home country bias, a term for a narrow focus on one's home-country investments. Morningstar research has identified this phenomenon among investors in several developed countries, including Canada, the U.K., Germany and Japan.
Home country bias results in American investors and financial reporters placing outsized emphasis on this index, as well as the Nasdaq composite and the Dow Jones Industrial Average.
Certainly, as the index that tracks the biggest U.S. companies, the S&P 500 is not to be dismissed. But neither is the importance of broad diversification, which is why the notion of "beating the S&P 500" is erroneous.
In most calendar years or quarters, there is some other asset class that outperforms the S&P 500.
In fact, U.S. investors don't even need to give up home country bias to find an asset class with a better year-to-date track record. Mid-cap growth stocks, which are not included in the S&P 500, advanced 3 5.9 % year to date, vs. 28.6 % for the S&P 500.
This may cause some investors to feel buyer's remorse, if they decided the S&P was the only necessary domestic investment. However, outperformance of mid-caps should not really be all that shocking, considering that stocks with smaller market capitalizations typically outperform their larger peers, over time.
Think of it this way: Say you want to improve your health, and you join a gym. You decide that a well-known, familiar exercise is all you need to do, so four times a week, you do bicep curls. Nothing but bicep curls.
Now, you might end up with some great-looking guns after a few weeks, but to what effect? Has that improved your overall health?
[See: Do Bull Markets Scare You?]
You've overlooked all your other muscle groups, both upper and lower body. You've also overlooked your core muscles. In addition, there's no cardio in the mix to improve your heart and lung health.
It's pretty easy to see how this analogy applies to investing. You're probably at least somewhat familiar with the S&P 500, and you've heard it called "the benchmark index." But why should a group of the largest U.S. stocks be a benchmark for broader market performance, any more than one muscle group should be the benchmark for your overall physical health?
Part of the focus on large U.S. stocks goes back decades, before other asset classes were widely available to retail investors. Before the widespread availability of ETFs, domestic investors were largely relegated to choosing from a handful of large-cap single stocks for their portfolios.
Buying a single foreign stock can still be difficult, and that's where funds come into the picture. Even buying a stake in a small U.S. company can be a bit daunting, as there is often little research into smaller firms, and there's often a lack of liquidity, as fewer shares are available.
Here again, mutual funds and ETFs allow today's investors easy access that previous generations didn't enjoy.
[See: 8 Things to Remember When Reviewing Your 401(k).]
So if you see some trading product or even an index being touted as having performance superior to the S&P 500, ask yourself a few questions:
-- Does that particular asset class outperform large-cap U.S. stocks over time?
-- Are you looking at comparisons of asset classes at all, or simply some trade suggestions, which, if executed perfectly, would have outpaced the S&P 500?
-- Why is it even important that one asset class outperform another, if your portfolio is allocated properly, to generate the return you need to meet your financial goals?
It all comes down to your financial needs, and your unique situation.
Just as in the gym, a focus on one particular area probably won't do much for optimal health.
BAE Systems Announces Proposed Acquisition of Collins Aerospace's Military Global Positioning System Business and Raytheon's Airborne Tactical Radios Business

redpajama_set_name: RedPajamaCommonCrawl


text:
using System;
using System.Data;
using MySql.Data.MySqlClient;

namespace Utilities.Dap.Tests.Common
{
    public class MysqlBase
    {
        protected string Connstr = "data source=192.168.1.21;Database=test;Password=;User ID=root;";

        public MysqlBase()
        {

            // base(connstr);
        }

        public MysqlBase(string connstr)
        {

            Connstr = connstr;
        }

        public IDbConnection GetConnection()
        {
            var conn = new MySqlConnection(Connstr);
            conn.Open();
            return conn;
        }

        public IDbConnection GetConnection(string strConn)
        {
            var conn = new MySqlConnection(strConn);
            conn.Open();
            return conn;
        }

        public Tuple<bool, string> TestConn(string connstring)
        {
            bool isopen = false;
            string msg = string.Empty;

            try
            {
                var conn = GetConnection(connstring);
                if (conn.State == ConnectionState.Open)
                {
                    isopen = true;
                }
            }
            catch (Exception ex)
            {
                msg = ex.Message;
            }

            return new Tuple<bool, string>(isopen, msg);
        }
        public Tuple<bool, string> TestConn()
        {
            bool isopen = false;
            string msg = string.Empty;

            try
            {
                var conn = GetConnection(Connstr);
                if (conn.State == ConnectionState.Open)
                {
                    isopen = true;
                }
            }
            catch (Exception ex)
            {
                msg = ex.Message;
            }

            return new Tuple<bool, string>(isopen, msg);
        }
    }
}

redpajama_set_name: RedPajamaGithub


Discussion in 'Proxmox VE: Installation and configuration' started by Jason Morris, Dec 6, 2018.
I have been having issues importing OVAs into my Proxmox cluster. I had given up completely on being able to do this and built a ESXi box for all my OVAs but I am determined to make it work now. This is what's going on.
and it imports my disk but when I start the VM it tells me that there is no bootable disk and I get stuck in an endless loop at that point. I cannot stop the VM, can't delete it or anything. Totally locked. The only option at that point that I have found is to attach an ISO to the VM and install an OS on top of it. Then I can stop and remove the VM.
I've been using Proxmox for a while and had the same experience about 2 years ago when I first attempted this. That was by converting the vmdk to a qcow2 file. I tried raw also with no better results.
I wish there was in import ova/ovf native feature in the GUI. It would make using Proxmox exclusively an option.
Anyways if anyone can assist I would greatly appreciate it.
It seems like such basic functionality. I'm amazed it doesn't already exist.
Minor update. I was able to get the VM to boot with using qm importovf but it won't create/recognize the second disk still so the system just blows up. I have gotten it to this point before by manually converting the vmdk. Such a bother.
The way I've done this, granted has always been done with OVA files, is to just extract the VMDK from the OVA file. IIRC, the difference between OVA and OVF was whether or not compression was enabled? It's been a while since I rolled VMs in ESXi.
Once I have the VMDK file, I use the qemu-img command to convert it to qcow2, as I've had a lot of problems with VMDKs working for 1 boot in Proxmox, and then becoming corrupted.
Once that's done you can either create a VM with the appropriate number of disks in qcow2 format, and then copy your freshly converted virtual disks over the ones that Proxmox creates. Or you can manually add entries in the VM's configuration file. I highly recommend the former.
Don't forget to check your boot order just to make sure that it's selecting a valid virtual disk as the first boot option. Boot options don't change automatically.
Your process is how I have done it in the past. For single disk VMs I seem to have fairly good luck but for multiple disk ones it's a crapshoot. I need a process that's simple enough for some of our less technically skilled engineers to import OVA/OVFs without having to jump threw a bunch of hoops.
I just tried that method again (fairly desperate for a fix) and now I get an error 17 when booting. That's new. On a positive note I figured something out. When this happens I cannot shutdown or stop the VM. Which is very annoying. If you delete the lock file you can stop and delete the offending VM. That's a handy trick and much faster than installing Centos on it so I can get to a point where I can shut it down.
I have successfully added an OVA VM into proxmox yesterday. I unpacked the OVA file which contained the .vmdk disk.
I than created a VM in proxmox with the appropriate configuration.
- Copied my .vmdk file for the VM into the directory /var/lib/vz/images ....... renamed them to match the already created .vmdk proxmox vm file.
The VM started and is working !!!!!
That is good to know ..... I was a bit on clear regarding what needed to be done.
I've tried all the suggestions here and nothing has helped. It doesn't look like improved OVA/OVF functionality is even being considered which is unfortunate. I can keep running both platforms but why when I can just run ESXi and do everything (well sort of).
This can never work reliable, as we run our GUI in a browser. VM images are much too big, so there is technical limit here.
Can't someone just put a OVA/OVF in an ISO image repository and then from the GUI you pick that image to install?


Through Energy Upgrade California, you can be like Ann, who saved $1,000 a year and found rebates to save water and electricity via sealing leaks, add insulation, and increase the comfort of her home.
This program is the only one of its kind in California.
To help California residents and businesses reduce carbon pollution and climate change by reducing energy.
It was created by California state and local governments, nonprofits and utilities for residents and businesses.
Pamela Wellner, Manager, Research and Climate Change Programs at Energy Upgrade California, Center for Sustainable Energy, 415-795-2149, Pamela.Wellner@energycenter.org.


text:
Father William J. Collins, MM
Ordained: September 17, 1939
Died: January 20, 1974
William J. Collins was born in South Boston on September 10, 1913. He attended parochial schools and was graduated from Boston Latin School. He joined Maryknoll in 1931 and was ordained on September 17, 1939 (as a member of the Class of 1940). He studied Canon Law at Catholic University and in 1940 went to Rome as secretary to Cardinal Fumasoni-Biondi of the Congregation for the Promotion of the Faith. Father Collins spent the World War II years in Rome and returned to the United States in December of 1945. He received his Canon Law Doctorate (J.C.D.) from the Lateran University in Rome in 1943.
After a brief period teaching at Brookline in early 1946 he was named superior of the first four men to go to East Africa, arriving in the Mwanza-Musoma area of Tanganyika in October, 1946. Elected to the General Council at the Fourth General Chapter in 1956, he served as Secretary General until 1966, and did valuable work preparing the Constitutions and the Fifth General Chapter documents for publication in 1966 – 1967. He was reassigned to Africa in July of 1967 and taught Canon Law at the Nairobi Seminary in Kenya until his return to the U.S. in October, 1973.
Father Collins was an exemplary Maryknoller as a student in Rome, as a missioner in Africa, on the General Council and during his final illness. He combined a keen mind and solid piety with a tremendous spirit of openness to others and a delightful sense of humor. A humble man, he stressed that "For reasons of conscience, I cannot accept any ecclesiastical dignity." Early reports describe him as "full of the devil at recreation, and full of the angels at times of spiritual exercises."
Father Collins died at St. Teresa's Residence at 2:30 a.m. on January 20, 1974. A Vigil Service was held on January 21 at the Maryknoll chapel. Mass of the Resurrection was concelebrated the following day and burial took place at Maryknoll. Bishop John W. Comber, with whom Father served on the Council, was principal concelebrant and Father George 14. Buckley, a classmate, was the homilist.


Hamburg, 13 March 2018. The energy utility of the city of Zurich ewz has ordered its third wind farm from the Nordex Group in quick succession. The project entails the installation of four N117/3000 turbines at the 12-MW "Graincourt" wind farm. The contract covers project development, turn-key installation of the wind farm and service for the wind power systems over a period of 20 years. Installation work is scheduled to commence in October of this year.
The technical configuration of the wind farm will ensure optimum use of the good local wind conditions. With a projected annual energy yield of 34 GWh, a capacity factor of well over 32 percent will be achieved, thus helping to expand the availability of clean energy.
13.03.2018 Dissemination of a Corporate News, transmitted by DGAP - a service of EQS Group AG.


text:
AAC150
AAC History
AAC News
Tyra Patterson, Wrongly Imprisoned for Two Decades Receives Honorary Bachelor's Degree
November 10, 2020 Chelsey Hughes 1 comment
Wrongly Incarcerated Artist and Activist, Tyra Patterson, Receives Honorary Degree from the Art Academy of Cincinnati.
Tyra Patterson was born and raised in Dayton, Ohio. On December 25, 2017, she walked out of prison after serving 23 years for crimes she did not commit.
Today, Tyra travels the country speaking at law schools, colleges, prisons, conferences, and high schools, leveraging her story to educate people on social justice, mass incarceration, and wrongful convictions.
She currently lives in Cincinnati and works at the Ohio Justice & Policy Center, where she serves as the Director of Community Outreach. Tyra also maintains paralegal duties at OJPC working on cases on behalf of people, both guilty and innocent of the crimes for which they have been convicted. She is also an Ambassador for Represent Justice.
During the Art Academy's 151st Commencement Celebration, at the Carnegie in Covington, Kentucky, artist, and activist Tyra Patterson, addressed the graduates as the commencement speaker.
Patterson's story of resilience championed the class of 2020 to realize their creative visions and to be emboldened to change the world during a time of such division.
Patterson shared her history of being wrongfully incarcerated, serving 23 years for crimes she did not commit. Her story has been shared worldwide from ABC News to the Guardian.
"I'm so humbled to be your commencement speaker. But I have to admit my imposter syndrome kicked in," said Patterson.
"I dropped out of elementary school when I was only 11 years old. I went to prison, not knowing how to read or write. I'm good at a few things, but I don't consider myself an expert in anything. But there is one thing I know better than almost anyone, and that is to…never give up."
Patterson's perseverance and how that has fueled her activism was a theme in her address.
"People typically ask graduates to go out and accomplish their goals and make the world a better place. While that is still true, today, in 2020, the plea for you is a little bit different. In a time of segregation, both mandated and self-imposed, we need you to be emboldened to change the world. We need artists unlike ever before."
After her address, Art Academy President Joe Girandola awarded Patterson a Bachelor of Fine Arts Honoris Causa and the 2020 Creative Perseverance Award.
"When Tyra Patterson enters a room, the Earth stands still and listens," said Girandola.
"Tyra speaks wisdom from the depths of sorrow and sadness to the heights of sheer joy and social justice. The ability to express that everyone on this planet breathes the same molecules of life, connecting us together, enables us all to move forward with compassion and creativity, is Tyra's gift to humanity."
The Art Academy of Cincinnati is honored to welcome Tyra Patterson to the class of 2020.


text:
Assessment of Contraceptive
Assessment of Contraceptive Uptake among Men Aged 20-50 Years in Mwembe Estate, Kisii Town, Kisii County, Kenya
DOI: 10.21522/TIJPH.2013.04.01.Art002
Authors : Taratisio Ndwiga, Angela Maiyo, Moraro R Bosire
Background: Comprehensive contraception uptake involving not only women but also their male partners is very vital if the projected decline in fertility rates by 2025 is to be attained. Men's involvement is of great essence if potential acceptability of contraception programs is to be achieved.
Objective: The main objective of the study was to assess the utilization of contraceptives among men aged 20-50 years in Mwembe estate, Kisii Town.
Methodology: A cross-sectional study design was employed on 288 sampled men aged 20-50 years. Stratified random sampling technique was used to select the respondents for the study. The data was collected using structured questionnaires and key informant guides.
Data Analysis: Analyses of quantitative data was done in SPSS version 20. Chi-square test was used to measure the strength of associations between the various variables where a p-value of = or < 0.05 was considered statistically significant.
Findings: Condoms and vasectomy were the modern contraceptive methods available to men. 99% of the study subjects had the knowledge on contraceptives but only 56% admitted consistent use. Among those who used, condoms were most preferred at 58% with traditional methods still being employed. Only 32% of respondents had objections to contraception, among which 16% based on religious, 12% on personal and 4% on cultural reasons. The use of contraceptives was closely associated with religion (χ2 = 6.67, df = 2, PV = 0.036).
Discussion: The high awareness levels (99%) can be attributed to technological advancements. Condoms use was leading (56%) because they were easily available and accessible, they required no prescription and they offered dual protection. Vasectomy service utilization was low (1%) as it had not been embraced in most societies. Religion was the major barrier of contraception (16%) since contraception was thought to be against God's will. Other men (14%) had personal reasons against contraception owing to the perceived side effects of female contraceptives in order to protect their women's health
Conclusion: Condoms were most common (70%) than other methods hence information on proper use of condoms should be given. Knowledge on contraception was high (99%) with low use (56%) hence more is required to bridge the knowledge-practice gap. Utilization of contraceptives still low (56%) compared to that of developing regions (67%+). Religion, societal and personal holds hinder contraception practice.
Recommendations: Innovations of other contraceptive options through research by government. Men should be encouraged to take up contraception with communication among partners being emphasized. Health personnel to adopt religious-based and individual-based FP promotion approaches.
Keywords: Contraceptive, Utilization, Prevalence, Total Fertility Rate
[1]. Abdulla, S. (2014) Religious Affiliation and Contraceptive Use in Kenya. University of Witwatersrand. Johannesburg. Pg 65.
[2]. Atieno, P. O. (2010) "Men's knowledge, attitude and practise of family planning in Kenya." Digital Repository: University of Nairobi.
[3]. Berhane, A., Biadgilign, S., Amberbir, A., Morankar, S., Berhane, A., & Deribe, K. (2011). Men's knowledge and spousal communication about modern family planning methods in Ethiopia. African journal of reproductive health, 15(4), 24-32.
[4]. Briggs, P and Kovacs, G. (2013) Contraception: A Casebook from Menarche to Menopause. Cambridge: Cambridge University Press.
[5]. Callahan, T and Caughey, A. B. (2013) Blueprints Obstetrics and Gynecology. Baltimore: Lippincott Williams & Wilkins.
[6]. Carroll, J. (2015) Sexuality Now: Embracing Diversity. Boston: Cengage Learning.
[7]. Castaneda, D. M. (2013) The Essential Handbook of Women Sexuality [2 Volumes]. Santa Barbara: ABC - CLIO.
[8]. Cunha, C and Manuela. M. (2009) Handbook of Research on Developments in E-Health and Telemedicine: Technological and Social Perspectives. New York: Medical Information Science Reference.
[9]. Dahal, G.P., Sabu, S., Padmadas, R and Hinde, A. (2008) Fertility-Limitng Behaviour and Contraceptive Choice among Men in Nepal. International Family Planning Perspectives: Guttmacher institute. pages 23.
[10]. Edberg, M. (2010) Essential Readings in Health Behaviour: Theory and Practise. Sodbury: Jones & Barlett Publishers.
[11]. Eldra, S., Martin, C and Martin, D. (2014) Biology. New York: Cengage Learning.
[12]. Fisher, A. A., Laing, J. E. and Strocker, J.E. (1998) Handbook for Family Planning, Operation Research Design in Sampling. Population Council, 40-45.
[13]. Fogel, C.I and Woods, N. F. (2008) Women's Health Care in Advanced Practise Nursing. New York: Springer Publing Company.
[14]. Haider, T.L and Sharma, M. (2013) Barriers to Family Planning and Contraception Uptake in sub - Saharan Africa: A Systematic Review. Bethesda: PubMed Publisher.
[15]. Handler A and Kennelly. J (2010) Reducing Racial/Ethnic Disparities in Reproductive and Perinatal Outcomes. Chicago: Springer Science & Business Media.
[16]. Hanson S. J and Burke A E (2011) Fertility Control: Contraception, sterilization and abortion: In K.J Hurt; M. W guile; J. L Bienstock. The John Hopkins Manual of gynecology and obstetrics, 4th edition.
[17]. Imhoff, D and Baumgartner, J. A. (2012) Farming and the Fate of Wild Nature: Essays in Conservation-based Agriculture. Santa Rosa, California: Post Carbon Institute.
[18]. Inhorn. M.C., Thomsen. T.-T., Goldberg, H and Mosegaard, C. (2009) Reconceiving the Second Sex: Men, Masculinity and Reproduction. New York: Berghahn Books.
[19]. Iribhoghe, O.O., Akpamu, U., Nwaopara, A.O., Osifo, C.U and Otamare, H.O. (2012) Contraceptive Choice among Men in Ekpoma, Nigeria. African Journal of Biomedical Research. Pages 8.
[20]. Jones, M. M. (2012) Human Reproductive Biology. San Diego, California: Academic Press.
[21]. Jones, T.(2010) Comprehensive Medical Terminology. New York: Cengage Learning.
[22]. Jensen, S. M. (2010) Encyclopedia of Contemporary American Social Issues. Santa Barbara: ABC-CLIO.
[23]. Kibagenyi, A., Ndugga, P., Wandera, S.O and Kwagala, B. (2014) "Modern contraceptive use among sexually active men in Uganda: does discussion with a health worker matter." BioMed Central - Public Health: Page 8.
[24]. Khurram, A.S and Graham, B (2008) Barriers and Perceptions of Opinion Leades Regarding the Use of Modern Contraception Methods in Slum Areas of Karachi, Pakistan: A Qualitative Study. Perth: Curtin University of Technology. Pg 43.
[25]. Khana. O. P and Jain T.R (2007) Development Problems and Policies. Delhi: Vimla Kumari Publications.
[26]. KNBS (2014) Kenya Demographic and Health Survey: Key Indicators. Nairobi: Government Printers
[27]. KNBS (2010): Kenya Demographic and Health Survey (2008-09). Nairobi: Government Printers.
[27a]. MoFP (2009) Kisii Central District Development Plan (2002 - 2008) Nairobi: Government Printers.
[27b]. MoFP (2009) Nakuru District Development Plan (2002 - 2008) Nairobi: Government Printers.
[28]. Ladipo, L., Ademola A and Philomena O (2013) International Conference on Family Planning Addis Ababa, Ethiopia. 28 April 2015.
[29]. Lancet. (2012) Lancet: Family Planning: Global Health Series. New York: Elsevier Health Science.
[30]. Liebert, M. A. (2008) AIDS Patient Care and STDs. North Hollywood: Mary Ann Liebert, Inc. Publishers.
[31]. Manuh, T and Addy, E.S. (2014) Africa in Contemporary Perspective: A Textbook for Undergraduate Students. Accra: Sub - Saharan Publishers.
[32]. May, W. E. (2009): Marriage: The Rock on which the Family is Built. San Francisco: Ignatius Press.
[33]. Mazur, L. A. (2013) Beyond the Numbers: A Reader on Population, Consumption and the Environment. Washington: Island Press.
[34]. MedicineNet. (2012) Definition of Birth Control. Retrieved from MedicineNet.com: www.medicinenet.com/script/main/mobileart.asp?articlekey=53351 Accessed on 27 March, 2015.
[35]. Morna Collen Lowe, Dube Sifiso, Makamure Lucia and Cathrine N robinson (2014) The SADC Protocol on gender and development. Southern Africa gender protocol alliance. Johannesburg, South Africa.
[36]. Mundo, F. D. (2012) Primary Maternal and Neonatal Health: A Global Concern. Chicago: Springer Science & Media Centre.
[37]. Nasir, J. T. (2010) Contraceptive Attitude and Behaviuor among University Men: A Study From Punjab, Pakistan. J AyubMed Coll Abbottabad, pg 1-4.
[38]. Nieschlag, E., Behre, H. M and Nieschlag, S.(2010) Andrology: Male Reproductive Health and Dysfuction. Munster: Springer Science & Business Media.
[39]. Oxford English Dictionary (2012) Oxford: Oxford University Press.
[40]. Osei, I. M. (2014) Fertility Decisions and Contraceptive Use at Different Stages of Relationships: Windows of Risk among Men and Women in Accra. International Perspectives on Sexual and Reproductive Health, pg 32-40.
[41]. Ochako, R., Mbondo, M., Aloo, S., Kaimenyi, S., Thompson, R., Temmerman, M and Megan K (2015) Barriers to modern contaceptive methods uptake among young women in Kenya: A qualitative study. BioMed Central: Public Health. Pg 11.
[42]. Steinfeld, R.L., Newmann, S.J., Onono M., Cohen, C.R., Bukusi, E.A and Grossman, D. (2013) Overcoming Barriers to Family Planning through Integration: Perspectives of HIV-Positive Men in Nyanza Province, Kenya. Nairobi: Hindawi Journals. Pg 8.
[43]. Tsehaye, W.T., Mengistu, D., Birhanu, E and Berhe, K.K. (2013) "Assessment of Preference and its Determinant Factors to Ward Modern Contraceptive Methods among Women of Reproductive Age Group in Shire Indaselassie Town, Northern Ethiopia, 2011." International Journal of Family Medicine: page 8.
[44]. Tountas, Y., Creatsas, G and Dimitrakaki, C. (2004) Information sources and level of knowledge of contraception issues among Greek women and men in the reproductive age: a country-wide survey. Eur J Contracept Reprod Health Care: Pg10.
[45]. WHO. (2013) Task Shifting to Improve Access to Contraceptive Methods. Sexual and Reproductive Health, 4. Retrieved from WHO.
[46]. WHO. (2015) Health Topics. Family Planning. http://www.who.int/mediacentre/factsheets/fs351/en/ Accessed on 27 March 2015.
[47]. Weigl, C. (2010) Reproductive Health Behaviour and Decision-making of Muslim Women. Munster: LIT Verlag.
[48]. World Bank (2010) Available from http://data.worldbank.org/indicator/SP.DYN.TFRT.IN, data assessed 24th September, 2015.


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December 6, 2018 By David Andrzejewski
Careful Data Science with Scala
This post gives a brief overview of some ideas we presented at the recent Scale By the Bay conference in San Francisco, for more details you can see a video of the talk or take a look at the slides.
The Problems of Sensitive Data and Leakage
Data science and machine learning have gotten a lot of attention recently, and the ecosystem around these topics is moving fast. One significant trend has been the rise of data science notebooks (including our own here at Sumo Logic): interactive computing environments that allow individuals to rapidly explore, analyze, and prototype against datasets.
However, this ease and speed can compound existing risks. Governments, companies, and the general public are increasingly alert to the potential issues around sensitive or personal data (see, for example, GDPR). Data scientists and engineers need to continuously balance the benefits of data-driven features and products against these concerns. Ideally, we'd like a technological assistance that makes it easier for engineers to do the right thing and avoid unintended data processing or revelation.
Furthermore, there is also a subtle technical problem known in the data mining community as "leakage". Kaufman et al won the best paper award at KDD 2011 for Leakage in Data Mining: Formulation, Detection, and Avoidance, which describes how it is possible to (completely by accident) allow your machine learning model to "cheat" because of unintended information leaks in the training data contaminating the results. This can lead machine learning systems which work well on sample datasets but whose performance is significantly degraded in the real world. As this can be a major problem, especially in systems that pull data from disparate sources to make important predictions. Oscar Boykin of Stripe presented an approach to this problem at Scale By the Bay 2017 using functional-reactive feature generation from time-based event streams.
Information Flow Control (IFC) for Data Science
My talk at Scale By the Bay 2018 discussed how we might use Scala to encode notions of data sensitivity, privacy, or contamination, thereby helping engineers and scientists avoid these problems. The idea is based on programming languages (PL) research by Russo et al, where sensitive data ("x" below) is put in a container data type (the "box" below) which is associated with some security level. Other code can apply transformations or analyses to the data in-place (known as Functor "map" operation in functional programming), but only specially trusted code with an equal or greater security level can "unbox" the data.
To encode the levels, Russo et al propose using the Lattice model of secure information flow developed by Dorothy E. Denning. In this model, the security levels form a partially ordered set with the guarantee that any given pair of levels will have a unique greatest lower bound and least upper bound. This allows for a clear and principled mechanism for determining the appropriate level when combining two pieces of information. In the Russo paper and our Scale By the Bay presentation, we use two levels for simplicity: High for sensitive data, and Low for non-sensitive data.
To map this research to our problem domain, recall that we want data scientists and engineers to be able to quickly experiment and iterate when working with data. However, when data may be from sensitive sources or be contaminated with prediction target information, we want only certain, specially-audited or reviewed code to be able to directly access or export the results. For example, we may want to lift this restriction only after data has been suitably anonymized or aggregated, perhaps according to some quantitative standard like differential privacy. Another use case might be that we are constructing data pipelines or workflows and we want the code itself to track the provenance and sensitivity of different pieces of data to prevent unintended or inappropriate usage. Note that, unlike much of the research in this area, we are not aiming to prevent truly malicious actors (internal or external) from accessing sensitive data – we simply want to provide automatic support in order to assist engineers in handling data appropriately.
Implementation and Beyond
Depending on how exactly we want to adapt the ideas from Russo et al, there are a few different ways to implement our secure data wrapper layer in Scala. Here we demonstrate one approach using typeclass instances and implicit scoping (similar to the paper) as well as two versions where we modify the formulation slightly to allow changing the security level as a monadic effect (ie, with flatMap) having last-write-wins (LWW) semantics, and create a new Neutral security level that always "defers" to the other security levels High and Low.
Implicit scoping Most similar to the original Russo paper, we can create special "security level" object instances, and require one of them to be in implicit scope when de-classifying data. (Thanks to Sergei Winitzki of Workday who suggested this at the conference!)
Value encoding For LWW flatMap, we can encode the levels as values. In this case, the security level is dynamically determined at runtime by the type of the associated level argument, and the de-classify method reveal() returns a type Option[T] where it is None if the level is High. This implementation uses Scala's pattern-matching functionality.
Type encoding For LWW flatMap, we can encode the levels as types. In this case, the compiler itself will statically determine if reveal() calls are valid (ie, against the Low security level type), and simply fail to compile code which accesses sensitive data illegally. This implementation relies on some tricks derived from Stefan Zeiger's excellent Type-Level Computations in Scala presentation.
Data science and machine learning workflows can be complex, and in particular there are often potential problems lurking in the data handling aspects. Existing research in security and PL can be a rich source of tools and ideas to help navigate these challenges, and my goal for the talk was to give people some examples and starting points in this direction.
Finally, it must be emphasized that a single software library can in no way replace a thorough organization-wide commitment to responsible data handling. By encoding notions of data sensitivity in software, we can automate some best practices and safeguards, but it will necessarily only be a part of a complete solution.
Watch the Full Presentation at Scale by the Bay
David Andrzejewski
David Andrzejewski is a senior engineering manager at Sumo Logic, where he works on applying statistical modeling and analysis techniques to machine data such as logs and metrics. He also co-organizes the SF Bay Area Machine Learning meetup group. David holds a PhD in Computer Sciences from the University of Wisconsin–Madison.
More posts by David Andrzejewski.


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Lúcio Domício Enobarbo () foi um político da gente Domícia da República Romana eleito cônsul em 54 a.C. com Ápio Cláudio Pulcro. Foi um dos grandes adversários do triunvirato e defensor da facção dos optimates no Senado Romano. Quando irrompeu a guerra civil entre César e Pompeu, aliou-se a este último. Era filho de Cneu Domício Enobarbo, cônsul em 96 a.C., irmão de Cneu Domício Enobarbo, genro de Cina, e pai de Cneu Domício Enobarbo, cônsul em 32 a.C.. É trisavô pela linha paterna do imperador romano Nero.

Carreira
Enobarbo foi citado, em 70 a.C., por Cícero como uma das testemunhas da acusação no julgamento do antigo governador da Sicília Caio Verres. Em 61 a.C., foi eleito edil curul e, nos jogos que promoveu, exibiu uma centena de leões númidas, alongando tanto o espetáculo que os romanos foram obrigados a sair no meio para comer, a primeira vez que isto ocorreu em Roma. Esta pausa nos jogos passou a ser chamada de diludium.

Casou-se com Pórcia, a irmã de Catão, o Jovem, a quem, durante seu mandato como edil, apoiou em sua luta para aprovar leis contra o suborno escancarado durante as eleições, direcionadas principalmente contra Pompeu, que estava comprando votos para seu aliado Lúcio Afrânio. As opiniões políticas de Enobarbo coincidiam com as de Cato e acredita-se que ele tenha sido um dos mais fervorosos defensores do partido aristocrático (optimates). Ele se opôs ativamente às medidas de Júlio César e Pompeu e, em 59 a.C., foi acusado, por incitação de César, de ser cúmplice num suposto complô contra a vida de Pompeu.

Em 58 a.C., Enobarbo foi eleito pretor e, três anos depois, candidatou-se ao consulado com a proposta de, se eleito, executar uma medida que já havia proposto durante seu pretorado: retirar César de sua província (a Gália). Foi derrotado, porém, por Pompeu e Crasso, que se candidataram para impedi-lo, e acabou expulso do Campo de Marte no dia da eleição à força. Foi candidato novamente no ano seguinte e os dois ex-cônsules, firmemente estabelecidos no poder como triúnviros, não se opuseram. Foi eleito então, em 54 a.C., com Ápio Cláudio Pulcro, um parente de Pompeu, mas nada conseguiu realizar contra os dois, que se envolveram novamente num escândalo eleitoral no final do ano. Enobarbo não seguiu para uma província no final de seu consulado e, conforme a relação entre César e Pompeu se deteriorou, foi tornando-se cada vez mais próximo deste último.

Enobarbo foi eleito para ser o magistrado que presidiu o julgamento contra Tito Ânio Milão em 52 a.C. por causa do assassinato do tribuno Públio Clódio segundo o relato de Ascônio. Durante os dois ou três anos seguintes, período no qual Cícero estava ausente na Cilícia, as informações que temos sobre ele derivam principalmente das cartas de seu inimigo, Coelius a Cícero. Em 50 a.C., foi candidato para uma posição no Colégio de Áugures liberada pela morte de Quinto Hortênsio Hórtalo, mas foi derrotado por Marco Antônio por causa da influência de César.

O Senado nomeou-o para suceder César como governador da província da Gália Cisalpina e, durante a invasão da Itália por César, em 49 a.C., foi o único dos optimates a demostrar coragem ou energia para enfrentá-lo. Ele seguiu para Corfínio com cerca de vinte coortes esperando o apoio de Pompeu, que, contudo, não o apoiou, obrigando-o a render suas tropas a César. Seus soldados foram incorporados ao exército de César enquanto que o próprio Enobarbo foi dispensado por César ileso — um ato de clemência que ele não esperava e que dificilmente ele certamente não realizaria se fosse um conquistador. Porém, seus sentimentos em relação a César não mudaram, mas é certo que ele ficou bastante ofendido com Pompeu por ele não ter vindo ajudá-lo. Num primeiro momento, Enobarbo seguiu para Cosa, na Etrúria, e, em seguida, foi para Massília, que ele defendeu contra César. Dali, Enobarbo continuou lutando com vigor contra os cesarianos, mas a cidade acabou sendo conquistada. Escondido num barril, Enobarbo parece ter sido o único a ter conseguido fugir.

Enobarbo seguiu depois para se encontrar com Pompeu na Tessália e propôs que, logo depois da guerra, que todos os senadores deveriam ser julgados para descobrir os que haviam permanecido neutros. Cícero, que ele marcou como um "covarde", não temia a acusação. Enobarbo foi morto logo depois da Batalha de Farsalos, em 48 a.C., na qual ele comandou a ala esquerda com Públio Cornélio Sula. Foi assassinado tentando escapar depois que a cidade foi capturado. Segundo uma proposta de Cícero em sua segunda "Filípicas", o próprio Marco Antônio acreditava ter sido ele a desferir o golpe mortal.

Influência
Enorbarbo era um homem de grande energia; apesar de se manter firme em seus princípios políticos, mas era inescrupuloso.

O poeta Lucano utilizou Enobarbo como um de seus personagens no livro VII de seu livro "Pharsalia", no qual é chamado "Domício", importante no poema por ser o único senador que morreu apoiando Pompeu em Farsalos e tornou-se, por isso, um símbolo da República que morria.

Árvore genealógica

Ver também

Bibliografia

Cônsules da República Romana
Romanos antigos do século I a.C.
Pretores da República Romana
Domitii
Áugures romanos
Optimates
Guerra Civil de César
Pompeianos
Governadores romanos da Gália Transalpina
Procônsules na Gália


text:
El Cantó de Francescàs és un cantó francès del departament d'Òlt i Garona, situat al districte de Nerac. Té 7 municipis i el cap és Francescàs.

Municipis
 Fieus
 Francescàs
 La Montjòia
 La Sèrra
 Montcrabeu
 Nomdieu
 Sent Vincenç de la Montjòia

Història

Demografia

Francescas