text:
\section{Introduction}

This decade is witnessing important improvements in the way many diseases and disorders are understood and treated, thanks to advancements spanning from genetics to big data analysis; yet, a large share of them is still eluding our comprehension. Such gap is partly the result of the complexity of translating the symptoms and signs observed in a condition, to the real causes underpinning it - an inverse problem equivalent to the ``genotype to phenotype'' one \cite{benfey2008genotype}. Still an additional important element has mostly been neglected: the way such symptoms and signs are defined.

A standard and {\it prima facie} good option entails detecting changes in the expected value (that is, in the mean) of some variables - {\it i.e.} fever is considered a sign of viral infection as the body temperature is usually higher in patients than in control subjects.
On the other hand, an alternative approach recognises that the complexity of the human body implies that multiple elements may interact in different ways depending on the characteristics of the patient. In other words, if diseases are to be understood as network perturbations \cite{del2010diseases}, such perturbations can affect an individual node in different ways; and, as a result, the observable that increases in one subject may decrease in a different person.
According to this approach to diseases, control subjects are such because they maintain the standard homoeostasis and allostasis \cite{schulkin2004allostasis}, and are hence homogeneous; and, on the other hand, patients loose such homogeneity, and are thus characterised by a higher variability.
This inter-personal variability has recently been recognised within the personalized medicine paradigm \cite{schork2015personalized}; but its origins can be traced back to Hippocrates himself \cite{offit2011personalized}.
In the light of this idea, a different approach of understanding symptoms may be more appropriate, {\it i.e.} one in which the average value of an observable is not as relevant as the corresponding variability. Diseases could then be characterised by abnormal values, {\it i.e.} by an increase in the standard deviation of the corresponding distribution, in sets of parameters that may differ from individual to individual.

A simple example can help clarifying this concept. Suppose a set of control subjects, all characterised by two physiological parameters $a$ and $b$ described by a truncated normal distribution $| \mathcal{N}(0, 1) |$. Most control subjects (actually the $95.45\%$ of them) will thus have values for $a$ and $b$ in the range $[0, 2]$.
Let us further suppose an additional population of people suffering from a disease, whose effect is to unbalance the bodily homoeostasis; as a consequence, patients may be described by the distribution $a_p \sim b_p \sim | \mathcal{N}(0, 2) |$ - note the increased standard deviation. What would a classical symptom analysis yield? The answer would be a fuzzy definition: some patients will show no substantial modification, being both $a$ and $b$ within the standard range; others will have abnormal high values of $a$ or of $b$; and a few of both $a$ and $b$. The pathology would thus be difficult to explain, and even more difficult to diagnose.
The alternative approach entails describing the disease in terms of the variability observed in each group. Control subjects will thus be described as conforming an homogeneous group, with $E[ |(a, b)| ] = 2 / \sqrt{\pi}$; patients a more heterogeneous one, with $E[ |(a_p, b_p)| ] = 4 / \sqrt{\pi}$.

If the hypothesis here presented is true, such that diseases should be defined in terms of higher variability, the expected result would be a high degree of {\it fuzziness} in standard disease definitions, with expressions like ``symptoms may include'' - as such symptom would appear for some patients, but not in all of them, as depicted in the previous example.
This is indeed found, for instance, in the large heterogeneity observed in cancer: cells belonging to a same cancer type, or even to the same patient, can display a strong phenotypic and functional variability \cite{felipe2013cancer, meacham2013tumor}.
Such effect is not exclusive of genetics, but appear in other medical fields. Psychology and psychiatry yields several relevant examples: {\it e.g.} the obsessive-compulsive disorder, displaying an univocal definition and yet a wide range of phenotypes \cite{bloch2008meta, martoni2015evaluating}; similarly, depression \cite{kok2012can}; attention-deficit/hyperactivity disorder \cite{waahlstedt2009heterogeneity}; or borderline personality disorder \cite{bornovalova2010understanding}. As the study of the (possibly) most complex system of all, this problem is also faced in neuroscience, {\it e.g.} in Huntington's \cite{rosas2008cerebral}, Parkinson's \cite{kehagia2010neuropsychological}, or Alzheimer's \cite{lambert2007genetic} diseases, all of them eluding a simple characterization.
This has important clinical repercussions, as it is difficult to provide practitioners with a set of objective diagnostic rules, not partly relying on personal experience and judgement \cite{kienle2011clinical}.

In this contribution we explore the idea of a paradigm shift in diseases characterisation, based on moving from the {\it average} to the {\it dispersion} in the analysis of signs.
For this we propose a computational framework, based on complex networks theory \cite{strogatz2001exploring, newman2003structure}, for the characterisations of groups of healthy subjects and patients. It is based on the identification of the two sets of features that optimise the homogeneity of respectively control subjects and patients; and on the creation of a graph structure representing the pairwise distance between individuals according to those sets. Besides yielding a compact representation of the disease under study, we show how this framework can be successfully used to improve the outcome of classification ({\it i.e.} diagnosis) tasks, especially in situations with limited number of training instances. Results are shown for synthetic and real data sets, the latter representing a wide range of biomedical problems.

\section{Methods}

\subsection{Convergence/divergence network creation}
\label{sec:creation}

Based on the previous considerations, we here describe a computational methodology for creating a network structure in which instances belonging to previously labelled groups are organised according to their internal affinity.
Without loss of generality, we here consider the case of two groups, respectively $g_1$ and $g_2$, such that two networks naturally emerge: one ($N_1$) maximising the coherence of instances belonging to $g_1$, and a second one (namely $N_2$) maximising the coherence of $g_2$.
For the sake of clarity, we here name the two structures respectively as {\it convergence} and {\it divergence} networks - as, in the former, $g_1$ instances converge towards a common pattern, while in the latter they diverge from it.
While the proposed methodology can naturally be extended to additional groups and networks, this example has been chosen due to its simplicity and relevance - as, for instance, most biomedical classification problems deal with characterising control subjects {\it vs.} patients.

In the simplest situation, each instance $i$ would be characterised by a set of features $f_i$. A distance matrix $D$ is then defined, whose element $d_{i, j}$ corresponds to the cosine distance between the two instances $i$ and $j$:

\begin{equation}
d_{i,j} = D_C(f_i, f_j) = 1 - \frac{f_i \cdot f_j}{||f_i|| \cdot ||f_j||}.
\end{equation}

Note that other distance metrics can be used, as will be discussed in Sec. \ref{sec:val:synth}. The internal coherence of each group is then estimated through the average of all pairwise internal distances, {\it i.e.}:

\begin{eqnarray}
c_1 = \frac{1}{n_1 ( n_1 - 1 )} \sum _{i \in g_1, j \in g_1, j \neq i} d_{i, j}, \\
c_2 = \frac{1}{n_2 ( n_2 - 1 )} \sum _{i \in g_2, j \in g_2, j \neq i} d_{i, j},
\end{eqnarray}

$n_1$ and $n_2$ respectively representing the number of instances in groups $g_1$ and $g_2$.

While in this situation, {\it i.e.} using all features, instances of the two groups may naturally be clustered, in general one is interested in finding the two subsets of features, $f^c$ and $f^d$, optimising the creation of the two networks. This corresponds to the following maximisation problem:

\begin{eqnarray}
\argmax_{f^c} \log \frac{c_2}{c_1} \bigg\rvert _{f^c}, \\
\argmax_{f^d} \log \frac{c_1}{c_2} \bigg\rvert _{f^d}.
\end{eqnarray}

Note that, in the first case, we are creating the {\it convergence} network, {\it i.e.} the network in which the first set of instances are more homogeneous, and we thus need to maximise $c_2 / c_1$. On the other hand, the {\it divergence} network requires the instances of the first group to be more heterogeneous than the second group, {\it i.e.} the maximisation of $c_1 / c_2$.

As depicted in Fig. \ref{fig:Method}, bottom part, the result of this first phase is a set of two fully connected networks (cliques), respectively called {\it convergence} and {\it divergence}.
In both networks, nodes represent instances (irrespectively of their group); and the weight of links between them the distance, in the selected feature sub-space, between the corresponding instances. For the sake of clarity, node colours in Fig. \ref{fig:Method} depict the group affiliation, with each group laying in the centre of the corresponding network.

\begin{figure}[!tb]
\begin{center}
\includegraphics[width=0.99\textwidth]{Fig01.pdf}
\caption{Graphical representation of the proposed methodology. The lower inset depicts the process of creating the two {\it convergence}/{\it divergence} networks, while the upper panel integrates them into a general classification task. See main text for definitions and details.}\label{fig:Method}
\end{center}
\end{figure}

\subsection{From networks to classification}

The previously obtained convergence / divergence networks have an intrinsic value, as they can be used to represent the structures created by patients' similarity, and to identify the most relevant features in a data set.
Nevertheless, if the objective is to perform a classification task ({\it e.g.} a diagnosis), it is necessary to transform the two networks into a set of features that can be understood by a data mining algorithm - as directly training a classification algorithm with the adjacency matrices is usually not efficient \cite{zanin2016combining}. As the instances of the first group are, by construction, more connected in the convergence network (as are the instances of the second group in the divergence one), it seems natural to use a centrality measure to describe each node. Specifically, we consider three standard centralities: ({\it i}) the {\it closeness} centrality, defined as the inverse of the average distance from the target node to any other node in the network \cite{okamoto2008ranking}; ({\it ii}) the {\it betweenness} centrality, defined as proportional to the number of shortest paths passing through the considered node \cite{barthelemy2004betweenness}; and ({\it iii}) the {\it eigenvector} centrality, a centrality measure that assess the importance of a node as a function of the importance of its neighbours \cite{bonacich2007some}.
Note that, while all the three metrics assess the importance of nodes from a propagation perspective, they tackle the problem from different points of view.
Consequently, there is no {\it a priori} way of predicting which one of them is more appropriate for the problem here considered, and in what follows all three will be independently tested.

In the proposed framework, each instance of the original data set is finally characterised by two features, {\it i.e.} its centrality in the convergence and divergence networks, as depicted in Fig. \ref{fig:Method}. It is worth noting that this represents an important reduction in the dimensionality of the problem, from $|f|$ to $2$. As is well known in data mining \cite{guyon2003introduction}, such drastic reduction in the number of features yields important benefits, as a lower risk of overfitting, the possibility of working with less instances, and an improved computational cost. If this usually comes at the cost of loosing part of the encoded information, in subsequent sections we will show how here this is not a concern, as enough information is encoded in the networks to actually allow to improve the outcome of several classification tasks.

\section{Validation with synthetic data sets}
\label{sec:val:synth}

In order to evaluate the added value yielded by the proposed framework in a classification task, we here report results corresponding to an ensemble of synthetic random data sets. These have been designed to be of maximal simplicity, while enabling a sensitivity analysis of the algorithm with respect to their characteristics.

First of all, we suppose a binary classification problem, {\it e.g.} aimed at discriminating between healthy people and patients suffering from a given disease. A total of $n_i$ instances are considered, equally distributed between the two classes - in order to avoid classification biases.
Each instance is then described by a set of $n_t$ features, whose values are drawn from the normal distributions defined in Tab. \ref{tab:SynthFeatures}.
These are designed to make some features have a higher variance in patients; some a higher variance in control subjects; and finally, to make some features irrelevant, thus only encoding noise.
Three parameters control the shape of the distributions, namely:

\begin{itemize}
\item $\sigma_2$, increased standard deviation of the relevant features. This parameter is used to simulate the increased heterogeneity in control subjects and patients, hence $\sigma_2 > 1$.

\item $n_r$, number of relevant features for each class, {\it i.e.} features whose heterogeneity is higher than for the other class.

\item $n_t$, total number of features in the data set. A given number of features, namely $n_t - 2n_r$ are completely random and do not depend on the instance's class. Note that $n_t \geq 2n_r$.
\end{itemize}

\begin{table*}[!tb]
\centering
\begin{tabular}{|l|c|c|c|}
\hline
Instance class & Features $[0, n_r)$ & Features $[n_r, 2n_r)$ & Features $[2n_r, n_t)$ \\ \hline
Class 1 & $\mathcal{N}(0, 1)$ & $\mathcal{N}(0, \sigma_2)$ & $\mathcal{N}(0, 1)$ \\ \hline
Class 2 & $\mathcal{N}(0, \sigma_2)$ & $\mathcal{N}(0, 1)$ & $\mathcal{N}(0, 1)$ \\ \hline
\end{tabular}
\caption{Characteristics of the distributions from which synthetic data are drawn. See main text for details.}
\label{tab:SynthFeatures}
\end{table*}

These synthetic data sets have then been used to perform a classification task, using Random Forests (RFs) \cite{breiman2001random} and a Leave-One-Out Cross Validation (LOOCV) \cite{efron1983leisurely}. Results, in terms of the AUC of the classification \cite{fawcett2006introduction} and as a function of the four data set parameters, are shown in Fig. \ref{fig:ResSynth}. The five curves respectively depict:

\begin{itemize}
\item (Grey solid line) The score obtained by training the RFs using the raw data.
\item (Black solid line) The score obtained by training the RFs using the first $2n_r$ features of the raw data, {\it i.e.} the features that actually encode information.
\item (Blue/orange/green dashed lines) The score obtained by using the convergence/divergence network centrality data - respectively closeness, alpha and betweenness centralities.
\end{itemize}

Some interesting conclusions can be drawn. First of all, the proposed approach allows to get a classification score consistently higher than the one obtained by only using the raw data. While this may be a consequence of using a tailored data set, in Sec. \ref{sec:val:real} we will see how this also happens in several real data sets. The convergence / divergence networks thus seem to be an efficient way of synthesising biological information.

Secondly, it can be appreciated that all AUCs increase with the separation ($\sigma_2$), the number of instances ($n_i$) and the number of relevant features ($n_r$), as more information is encoded in the data set. A different behaviour is observed when the total number of features ($n_t$) is increased, while keeping $n_r$ constant: while the network performance is constant, the classification with all raw features degrades. This suggests that the proposed methodology is not affected by redundant and useless information, as the networks are inherently performing a feature selection.

Additionally, convergence/divergence networks yield a relatively higher AUC with low separations ($\sigma_2$), low number of instances ($n_i$) and high number of relevant features ($n_r$). As may be expected, RFs are not efficient in extracting information that is sparsely encoded over a large number of features, when differences between classes are minimal, and when few instances are available for training. In all these cases, the networks help making explicit the information that may not directly be accessible to the classification algorithm.

Finally, in all cases the alpha centrality is the network metric yielding the best results, followed by the closeness and the betweenness centralities. Possibly this is due to the alpha centrality's higher capacity for accounting for the global (macro-scale) structure of the network.

\begin{figure}[!tb]
\begin{center}
\includegraphics[width=0.99\textwidth]{Fig02.pdf}
\caption{Classification score in synthetic data sets, using the raw data (black and grey solid lines), and the new features extracted from the convergence/divergence networks (blue, orange and green dashed lines, respectively for closeness, alpha and betweenness centralities). From left to right, top to bottom, the four panels depict the score as a function of the increased variability of data ($\sigma_2$), the number of instances in the data set, the number of relevant features ($n_r$), and the total number of features ($n_t$). Results correspond to the average of $10^4$ realisations.}\label{fig:ResSynth}
\end{center}
\end{figure}

For the sake of completeness, three aspects of the analyses reported in Fig. \ref{fig:ResSynth} require further consideration: the classification algorithm, the shape of the probability distribution underlying the data, and the way distances between subjects are measures.

As for the first, {\it i.e.} the possibility of using different classification algorithms beyond RF, Fig. \ref{fig:ResOtherDM} Left reports the average and the standard deviation of the classification score, as obtained with the convergence/divergence networks (left part) and the raw filtered data (right part) by several standard classification algorithms: Random Forests (RF) \cite{breiman2001random}, Decision Trees (DT) \cite{murthy1998automatic}, Stochastic Gradient Descent (SGD) with a hinge loss function \cite{ketkar2017stochastic}, Support Vector Machine (SVM) with radial kernels \cite{noble2006support}, and Gaussian Na\"ive Bayes (GNB).

\begin{figure}[!tb]
\begin{center}
\includegraphics[width=0.99\textwidth]{Fig03.pdf}
\caption{Additional sensitivity analyses. (Left) Classification score, as obtained by five different classification algorithms with the convergence/divergence networks' (left group of symbols) and the raw data (right group). (Right) Classification score as a function of the underlying data probability distribution, and of the considered distance function. In both panels, symbols and whiskers respectively represent the average value and the corresponding standard deviation, as obtained in $10^4$ independent realisations. Parameters were fixed to $n_i = 50$, $\sigma_2 = 1.5$, $n_r = 5$ and $n_t = 15$.}\label{fig:ResOtherDM}
\end{center}
\end{figure}

Differences between the five algorithms are small, the Random Forest being the most efficient in both data sets. Nevertheless, two exceptions have to be highlighted.
Firstly, Support Vector Machines yield an extremely low classification score using the convergence/divergence networks. Being this result a clear outlier, it is most probably caused by some idiosyncrasies of the SVMs, than by the method here proposed.
Secondly, the Gaussian Na\"ive Bayes algorithm yields good results in both cases, {\it i.e.} even with the raw data alone. This is nevertheless due to the way the problem is designed ({\it i.e.} by sampling instances from normal distributions) and to the way this classification algorithm is constructed ({\it i.e.} by fitting data to normal distributions of unknown mean and variance). In other words, GNBs perfectly fit the hypothesis underlying the synthetic data, and this results in an increase in the average classification score. Yet, when this advantage is eliminated and instances are sampled from uniform distributions, {\it caeteris paribus}, the classification score in raw data reduces from $0.631$ to $0.583$, {\it i.e.} to the same level of the other algorithms.

Fig. \ref{fig:ResOtherDM} Right further reports the average classification score as obtained when three additional probability distributions were used to create the raw data: log-normal ($\mu = 0.0$, $\sigma = \sigma_2$), uniform and triangular (both in the range $[-\sigma_2, \sigma_2]$). Each symbol also represents a different algorithm for calculating the distance between instances: cosine, euclidean and manhattan. Results are qualitatively similar, with the log-normal and uniform distributions yielding the lowest classification scores - possibly due to the resulting distribution of outliers. Similarly, the use of a different distance measure does not substantially impact the output. The only significant exception arises for the combination uniform distribution / cosine distance, for which the algorithm fails to detect any pattern in the data; this effect seems to be robust, and does not depend on the type of classification model used.

\section{Validation with real biomedical data sets}
\label{sec:val:real}

The validation of the proposed methodology has further been performed using a collection of real biomedical data sets, thus allowing to understand if and when the convergence / divergence concept is of relevance in biology and medicine. For that, nine data sets corresponding to the ``Life science'' area and to a classification problem have been downloaded from the UCI Machine Learning Repository \cite{UCI}. Inclusion criteria were a limited number of instances, thus representing problems for which it is common to have small samples; and the availability of numerical features. The choice of using a public data set has been motivated by three considerations: first, the public availability of those data implies that all results can be seamlessly reproduced (all data sets can be freely downloaded from \url{https://archive.ics.uci.edu/ml/index.php}); second, the website provides references to many research works in which those data have been used, thus offering the possibility of comparing our results with relevant literature; and third, it allows to test the proposed methodology on multiple and diverse scenarios.

Table \ref{tab:ListFeatures} lists the set of features used to create the convergence / divergence networks, along with references in which more details about the data sets can be found. Fig. \ref{fig:ResOtherDS} depicts the evolution of the average classification score for each data set, in terms of the resulting AUC, as a function of the number of instances used in the training, when such classification is performed with a Random Forest model \cite{breiman2001random} and a Leave-One-Out Cross Validation. Three scores are compared: {\it i}) the AUC obtained with the raw data set (blue dashed line); {\it ii}) the AUC for the classification performed using only the convergence / divergence metric (black solid line); and {\it iii}) the AUC obtained when combining both sets of instances (green dashed line). Note that the second metric quantifies how much information about the original problem is retained, and thus how effective are the convergence / divergence metrics in the dimensionality reduction; while the third how complementary the two metrics are, with respect to the raw features. Additional information for each data set, including histograms of the selected features and the distribution of the convergence / divergence metrics, are included in Supplemental Information.

It can be appreciated from Fig. \ref{fig:ResOtherDS} that the convergence / divergence metrics yield heterogeneous classification performances, mainly depending on the data set (and hence, on its characteristics) and on the number of instances.

First, it can happen that the classification score obtained with the convergence / divergence networks is above what obtained with the raw features - see the top row of Fig. \ref{fig:ResOtherDS}. This advantage is smaller for high number of instances, as standard classification algorithms are able to approximate the convergence/divergence pattern. Nevertheless, even for large training groups, the addition of the C/D metrics to the raw features improves the final classification.
Such scenario is clearly the most interesting one, as it implies that, on one hand, the proposed methodology is able to extract the most important information from the instance's characteristics, thus enabling an important dimensionality reduction. On the other hand, when very few instances are available, it is even able to extract information usually not unveiled.

In the second scenario, the proposed methodology is able to extract information that, while not especially useful in itself, can be used to improve a standard classification task. This is represented by the second row of data sets in Fig. \ref{fig:ResOtherDS}, for which the orange dashed line (representing the combined data set) is always above the blue one (raw features only). In these cases, the convergence / divergence mechanism here hypothesised is not the only mechanism underlying the pathological situation; yet, the networks help in making it more explicit, and thus complement a more standard approach.

Finally, it is possible that the proposed approach is not relevant for the problem under study: thus, both the C/D metrics, and their combination with the raw features yield results below those of a standard classification model - as can be observed in the last row of Fig. \ref{fig:ResOtherDS}. This is not surprising, as not all biomedical problems have to be explained by the mechanism here hypothesised.

For the sake of completeness, the results corresponding to the first three data sets are analysed in more detail below, and compared with those available in the literature.

\begin{figure}[!tb]
\begin{center}
\includegraphics[width=0.99\textwidth]{Fig04.pdf}
\caption{Evolution of the classification score (in terms of the AUC) as a function of the number of subjects in the training set, and for the nine UCI data sets here considered - see main text and Tab. \ref{tab:ListFeatures} for details. The three lines respectively correspond to the score obtained with the raw features (blue dashed line), with the convergence / divergence features (solid black), and with both sets of features (dashed orange). Each point corresponds to the average AUC obtained in $2000$ random realisations.}\label{fig:ResOtherDS}
\end{center}
\end{figure}

\begin{table*}[!tb]
\centering
\begin{tabular}{|p{5.2cm}|p{3.7cm}|p{3.7cm}|}
\hline
{\bf Data set} & {\bf Convergence features} & {\bf Divergence features} \\ \hline
\multirow{2}*{Parkinson Speech \cite{sakar2013collection}} & Local jitter & Absolute jitter \\
 & Median pitch & Shimmer (dda) \\ \hline
\multirow{2}*{Mice Protein Expression \cite{higuera2015self}} & pCAMKII & pELK \\
 & pNR2B & pNR1 \\ \hline
\multirow{2}*{Coronary Artery Disease \cite{alizadehsani2013data}} & Triglyceride & Creatine \\
 & Erithrocyte sedimentation rate & Triglyceride \\ \hline
\multirow{2}*{Parkinson's \cite{little2007exploiting}} & Max. fundamental frequency & Avg. fundamental frequency \\
 & DFA & Shimmer (APQ5) \\ \hline
\multirow{2}*{Anuran Calls \cite{colonna2016recognizing}} & MFCC$_2$ & MFCC$_1$ \\
 & MFCC$_4$ & MFCC$_4$ \\ \hline
\multirow{2}*{Breast Tissue \cite{jossinet1996variability}} & Phase angle & Impedance distance \\
 & Slope of p.a. & Length of s.c. \\ \hline
\multirow{2}*{Diabetic Retinopathy \cite{antal2014ensemble}} & MA$_1$ & Exudates$_3$ \\
 & Exudates$_1$ & Diameter \\ \hline
\multirow{2}*{Indian Liver Patient \cite{ramana2012critical}} & Direct bilirubin & Alamine Aminotransferase \\
 & Alkaline phosphotase & Aspartate Aminotransferase \\ \hline
\multirow{2}*{Breast Cancer Wisconsin \cite{street1993nuclear}} & Fractal dimension II & Fractal dimension I \\
 & Concavity III & Area II \\ \hline
\end{tabular}
\caption{List of the nine considered UCI data sets. The second and third columns respectively report the features used to create the convergence / divergence networks, selected according to the procedure described in Sec. \ref{sec:creation}.}
\label{tab:ListFeatures}
\end{table*}

\subsubsection*{Parkinson Speech Dataset.}
This data set was designed to support speech pattern analyses of Parkinson's patients and control subjects, with the final aim of providing a simple diagnostic tool. Multiple types of sounds, including sustained vowels, numbers, words and short sentences, were recorded for each subject, for then extracting $26$ amplitude, frequency and harmonicity based features \cite{sakar2013collection}.
Results, as depicted in Fig. \ref{fig:ResOtherDS} top left, indicate that the proposed method is especially suitable for analysing small sets of instances drawn from this data set.
Interestingly, one of the features, Shimmer (DDA), has previously yielded conflicting results, with evidence in favour \cite{jimenez1997acoustic} and against \cite{rahn2007phonatory} its relevance in diagnosing Parkinson's. Our results indicate that the average value is not relevant for the classification (as the corresponding histograms for control subjects and patients are very similar, see Supplemental Information); but is instead the intra-group variability, when combined with that of the absolute jitter, that is relevant.
While this data set is quite similar to the Parkinson's one \cite{little2007exploiting}, both in terms of scope and feature extracted, the benefit yielded by the proposed approach in the latter case is substantially smaller - see Fig. \ref{fig:ResOtherDS}. We speculate that this may be caused by the type of sounds recorded in each one of them - in the Parkinson's case, the only available information is that they were ``sustained vowel phonations'' \cite{little2009suitability}.
Finally, some additional results, as the evolution of the score as a function of the number of trees included in the Random Forest, and as a function of the number of features used to create the convergence / divergence networks, are included in Supplemental Information.

\subsubsection*{Mice Protein Expression Dataset.}
This second data set encodes the expression levels of $77$ proteins, measured in the cerebral cortex, for control and trisomic (Down syndrome's \cite{davisson1993segmental}) mice \cite{higuera2015self}. Note that the original division into he four groups, {\it i.e.} stimulated / not stimulated to learn, and injected with saline / memantine, has here been disregarded.
It is worth highlighting that three of the four identified proteins ({\it i.e.} pCAMKII, pELK and pNR1) were originally identified as relevant features for distinguish memantine-treated mice {\it vs.} control baseline\cite{higuera2015self}; and that levels of the two N-methyl-D-aspartate receptor subunits pNR2B and pNR1 have been found to be associated to improved learning following an electroacupuncture treatment \cite{lu2016electroacupuncture}.

\subsubsection*{Coronary Artery Disease Dataset.}

The third test case, known in the UCI repository as the Z-Alizadeh Sani Data Set, comprises information about control subjects and people diagnosed with a coronary artery disease, the latter one presenting a narrowing of the coronary artery of $50\%$ or more. Features include demographic, symptom, ECG, and laboratory results \cite{alizadehsani2013data}.
Two important results have to be highlighted. First of all, none of the identified features were considered as important in the original work - only the erithrocyte sedimentation rate (ESR) ranked 11 over 54 in terms of importance in the final classification model. Indeed, if one observes the value distributions of, {\it e.g.}, creatine and triglyceride alone, these are very similar for both patients and control subjects; yet their combination unveil a higher variability in control subjects - see Supplemental Information.
Secondly, it is worth noting that triglyceride appears as a relevant feature both in the creation of the convergence and of the divergence networks - a topic which is further discussed in Supplemental Information.

\section{Discussion and conclusions}

In this contribution we presented a computational framework, based on complex networks, that allows to change the way symptoms and signs are defined. Instead of identifying patterns involving differences in the mean of a given feature between two (or more) groups, we here focus in changes in the variability.
If the latter aspect is usually disregarded by classical classification algorithms, we here showed that it can be used to reconstruct a network structure, with nodes representing subjects, and links the pairwise similarity between them; and that such network structure can be used to improve the performance in a classification task.
This approach has firstly been tested with synthetic data sets, to understand its behaviour under a wide range of controlled conditions; and secondly, following the hypothesis that the feature variability should especially be relevant in biology and medicine, with real data sets representing a wide range of biomedical problems. In some cases a significant increase in the classification score has been observed, thus suggesting that the proposed mechanism is indeed of relevance.

Both Figs. \ref{fig:ResSynth} and \ref{fig:ResOtherDS} indicate that the proposed methodology is especially well suited for the analysis of small data sets - as similar results can be recovered by standard algorithms only in the limit of a very high number of instances. This may {\it prima facie} seem an important limitation, due to the increasing relevance of ``big data'' in today's scientific and clinical environments \cite{obermeyer2016predicting}. Nevertheless, the opposed movement is also gaining momentum: due to increasing privacy and security concerns, or to the need of stratifying instances to a much smaller scale, many applications have to be developed relying on very small data sets \cite{estrin2014small, kitchin2015small}.

Additionally, both Fig. \ref{fig:ResOtherDS} and the discussion of Sec. \ref{sec:val:real} suggest that the proposed framework can be used, in some cases, as a way to identify novel biomarkers. Due to the way features are processed in the convergence / divergence networks, some of them may be useless when considered alone, but of relevance when interacting - as is the case of the features identified in the Coronary Artery Disease Dataset.

Finally, it is worth noting that, while we here focused on classification tasks, the conclusions' validity goes well beyond the data mining field. When the addition of a set of synthetic features ({\it i.e.} constructed on top of the available data) results in an increase in the classification score, it can safely be assumed that these new features are making explicit some information that was originally encoded in the data, but in a form not suitable to be digested by the data mining model. The increased score here observed confirms that the proposed approach is describing the biomedical problems in a way that is more efficient (or explicit) than what done by the raw data; or, in other words, that data are transformed from the raw features' to a more useful space.

\section*{Authors' contributions}
MZ conceived the study and participated in data and statistical analyses; JMT participated in the design of the study and in data analysis; EM coordinated the study. All authors contributed to the preparation of the manuscript, and gave final approval for publication.

\section*{Competing interests}
We have no competing interests.

\bibliographystyle{vancouver}

redpajama_set_name: RedPajamaArXiv


Sadouni Samadia, « The stratified diasporas of Somalians », Mail & Guardian online (South Africa), 13 février 2015.
Le texte est un extrait du chapitre paru en 2014 : « Being an immigrant and facing uncertainty in South Africa  : the case of Somalis », in Harrison, Philip, Gotz, Graeme, Todes, Alison et Wray, Chris (dir.), Changing space, changing city  : Johannesburg after apartheid, Johannesburg (South Africa), Wits university press.


The county seat of Colorado County, the city of Columbus is within reach of Texan heavyweights Houston, Austin, and San Antonio. In contrast to these bustling big cities, Columbus is a well-preserved and peaceful sanctuary with its own rich history and attractions. More than a hundred years since its foundation, the city remains as timeless and hospitable as ever.
A myth surrounds this Texas community; it is said to be the site of the Indian village of the legendary Aztec emperor Montezuma. Although this claim lacks sufficient historical evidence, it definitely adds to Columbus' historic appeal. Columbus' first settlers arrived in 1821 and called the area Beeson's Ferry or Beeson's Ford. Columbus only came to its present name in 1835, supposedly according to the behest of a settler from Columbus, Ohio.
With the help of a good real estate agent, finding your own home in Columbus will be a breeze. Be part of Columbus, home of live oaks and live folks, once you've taken your pick from the city's real estate market. Housing options include rustic and luxurious ranches, farms, raw land, and single-family homes located all throughout the city.
Cattle ranchers of the past built magnificent homes in Columbus, now fully restored and open for viewing if you take the guided Talking Houses Tour, which lets you take a peek into Columbus' colorful history.
Marvel at the grandness of Columbus' courthouse and its Tiffany-style glass dome or at the 1889 Stafford Opera House, which hosts a monthly dinner theater.
A 19th century saloon serves as the home of Live Oaks Art Center, which hosts art shows and exhibits.
Enjoy Columbus' natural beauty and visit its parks and recreational centers. Take a riverboat ride on the Colorado River and get the chance to see some of the local wildlife.
Don't forget to visit Texas' second largest tree. Columbus' Live Oak, which towers at approximately 70 feet, is estimated to be 500 years old.
Columbus is served by the Columbus Independent School District.
The city is located right where State Highway 71 intersects Interstate Highway 10, with Houston 65 miles to the east.
As of 2012, the city had an estimated population of around 3,600.


When the students start to write a particular work, you should be browsing through it in order to make certain that each student's work is an original. Requiring them to submit drafts every now and then would persuade them to really make a work of their own. Once they submit a draft or even an outline to you, it would definitely be best to write comments about what they have written and in turn, once they submit it again, you would be able to check if they were able to apply what you have advised them to do. By doing this, you would be able to see immediately the improvements of your students.
By providing particular topics to your students, this would make you certain that the probability of being able to find a certain paper that has already been written which may be copied would be avoided. Your students would not be constraint with regard to having the means for them to truly express what they would like to say if for instance you would allow them to get an assistant or simply consult with you. You may even set a schedule when you would be able to meet them.
Once you require the students to answer various questions pertaining to the how they would like their work to turn out, like how they go about research, this would aid you in terms of ascertaining whether the students actually know what they are doing or not. Aside from that, your students would also become more at ease with the research that they should do and how they would be able to come up with brilliant ideas that would also contribute a lot to their paper.
The students should learn to make an annotation that is brief and concise so that they would be able to put to good use all the sources that they have. However, it should be taken into consideration that the annotation should be made in such a way that the students do not simply copy whatever is written on the sources that they were able to get. It should be written in such a way that it is based on how the students were able to understand it, which means that they have to write using their own style.
Aside from requiring your students to submit drafts or answer to questions, an alternative to that would be to require them to submit a particular paragraph wherein the students would be discussing how they were able to come up with the topic that they have. The process that they had to undergo in terms of how they started with the research and how they were able to get a hold of sources and what exactly is its significance.
The students should not rely on sources that may have been written long time ago since these may no longer be applicable at present. Sources should be the most recent in order to make certain that all the latest developments regarding the study and the students' work would become even more significant.
The work that your students would submit should be brief yet the essence should still be there. Students may just use ideas that are actually part of their sources.


Harrison Ford Spotted In London With Medical Peg Leg.
Star Trek 3 To Focus On Deep Space And Five Year Mission.
STAR WARS NEWS AND THE BEARDED TRIO NEWS ON THE LATEST COFFEE WITH KENOBI.
Steven Spielberg Giving Words Of Wisdom to Jurassic World Director, Colin Trevorrow.
Solo Could Still Pull It Off. What Could Possibly Go Wrong?
Coffee With Kenobi Presents: A Cup of Clone Wars. With Guest Eric Geller.
Latest Star Wars Battlefront Video Highlights Heroes And Villains.
ILM Pioneer, Jim Nelson Dies 81.
Paramount Confirm 2016 For Star Trek 3.
New Episode Of RebelForce Radio Discuss McQuarrie Archives, Star Wars VII And Lots Lots More.
Pinewood Shepperton To Get $340 Million Expansion. 10 More Stages And 3000 Jobs On The Way.
Steven Spielberg Announces His Next Two Movie Projects.


The RICH INDUSTRY experience and in depth knowledge of our team members has enabled us to have a strong foot-hold in the pharmaceutical industry for developing PCD Pharma Network all over India. For further growth & expansion we once again offer our services to the Marketing Professionals / Wholesalers &Distributors all over India for FRANCHISEE MARKETING on PCD rights basis.Scope of association is available in all the three divisions.Interested Parties may please CONTACT US or write us at arofocus@gmail.com, arofocus@yahoo.com, rubylifesciences@gmail.com or you can also join us on facebook by clicking the link www.facebook.com/focushealthcarepvtltd Team Focus always believes in Transparent Dealings, Timely Services, Committed Monopoly, Long Lasting Relationships and above all Quality Products at very Reasonable Rates. We at FOCUS HEALTHCARE PVT. LTD. are thankful to the esteemed DOCTORS / SPECIALISTS for their continuous and on going valuable support and trust for our products. The Company is also thankful to its PCD Distributors, PCD Franchisee, Stockists /Retailers, Nursing Home Purchasers, Hospital Supply Purchasers who have supported us over the years with their valuable patronage. Company has great regards for our field staff and marketing partners i.e Google, Indiamart, Tradeindia, Yahoo, Pharmamart, yahoo, Quikr, justdial and pharma publishers like Drug Today, Medical Darpan, Drug Update, Pharma News, Dawa Charcha who have been promoting the company through various mediums and channels on ethical as well as on Monopoly Franchisee Basis. We are the company with a strong independant infrastructure which allows us to work with the needs of our customers.
We offer PCD Pharma Franchise state or district wise for all over india on PCD/MONOPOLY basis. We are trader of Pharmaceutical Tablets, Pharmaceutical Capsules, Pharmaceutical Syrups, Pharmaceutical injections, Nutraceuticals and Herbal Products. Due to our quality services we are trusted and well accepted brand name in the field of the Indian PCD Pharma Franchise Companies.


text:
First, wash your hands
Biomedicine: Smart antiseptic dispensers promise to save lives by subtly encouraging medical staff to wash their hands more often
Technology QuarterlySep 5th 2013 edition
GIVING birth was a dangerous endeavour in the 1800s; many women died soon after doing so. Ignaz Semmelweis, an obstetrician working at the time at Vienna General Hospital observed that by washing his hands with bleach before he touched his patients he could reduce their mortality rate by 90%. This was before Louis Pasteur established the germ theory of disease, and Semmelweis could not explain the correlation. After he published his findings, though, many of his colleagues were offended at the suggestion that they did not have clean hands. After all, doctors were gentlemen and as Charles Meigs, another obstetrician, put it, "a gentleman's hands are clean". Discouraged, Semmelweis slipped into depression and was eventually committed to a lunatic asylum. He died 14 days later, after being brutally beaten by the guards.
Hygiene in hospitals has come a long way since Semmelweis's time. But there is still room for improvement. Every year nearly 100,000 people die in America alone from preventable infections acquired in hospitals. An invention devised by Paul Alper of Deb Group, a British skincare company, could help change this.
As in Semmelweis's day, unclean hands are a big cause of infection. Wards abound with devices that dispense antiseptic handwash, but they are not always used as frequently as they should be—the compliance rate is below 40% in most hospitals. The DebMed Group Monitoring System (GMS) is intended to encourage staff to wash their hands.
The invention itself is simple. It consists merely of adding a chip to the dispenser to monitor usage. It is the psychology behind it that is clever, because instead of being intrusive and allocating blame, as happens when dispensers in (say) toilets are monitored by cameras to make sure people who have been to the lavatory do indeed wash and sterilise their hands, it relies on peer pressure. Individuals are not singled out; wards are. What could be oppressive thus becomes a competition between groups, rather than a finger-wagging exercise within them.
The chip in each dispenser sends information to a remote server, where it is recorded, analysed and then made available either on the web or by e-mail to hospital staff in an entirely automated process. The GMS records the number of times dispensers are used in different parts of a hospital and compares this with an estimated reasonable usage, customised to the circumstances of each hospital. This target is based on World Health Organisation's "Five Moments for Hand Hygiene", a guide to the best hand-washing practices for different types of contact with patients. The ratio of actual to target score gives the compliance rate for a particular unit or ward. Because this provides a rating for a group of people, nobody is singled out. And if compliance is low, the offenders can correct their behaviour collectively, behind closed doors, without the need for confrontation.
If the system works as intended, it will save many lives. It should also save money, for treating hospital-induced infections is costly. According to Mr Alper, dozens of hospitals have already signed up for trials. The ghost of Ignaz Semmelweis is no doubt smiling.
Our friends electric
The race is not to the swift
If tooth be told
Bang but no boom
The referee's a robot
The rebirth of the diesel engine
3D printing scales up
This article appeared in the Technology Quarterly section of the print edition under the headline "First, wash your hands"

redpajama_set_name: RedPajamaCommonCrawl


In this section, you will learn about using the Type Hierarchy view by viewing classes and members in a variety of different ways.
from the menu bar by selecting Navigate > Open Type Hierarchy.
from the keyboard by pressing F4 after selecting TestCase.java.
The buttons in the view tool bar control which part of the hierarchy is shown. Click the Show the Type Hierarchy button to see the class hierarchy, including the base classes and subclasses. The small arrow on the left side of the type icon of TestCase indicates that the hierarchy was opened on this type.
Click the Show the Supertype Hierarchy button to see a hierarchy showing the type's parent elements including implemented interfaces. This view shows the results of going up the type hierarchy.
In this "reversed hierarchy" view, you can see that TestCase implements the Test interface.
Click the Show the Subtype Hierarchy button in the view toolbar.
Click the Lock View and Show Members in Hierarchy button in the toolbar of the member pane, then select the runTest() method in the member pane. The view will now show all the types implementing runTest().
In the Type Hierarchy view, click the Show the Supertype Hierarchy button. Then on the member pane, select countTestCases() to display the places where this method is declared.
In the Type Hierarchy view select the Test element and select Focus On 'Test' from its context menu. Test is presented in the Type Hierarchy view.
Activate the Package Explorer view and select the package junit.framework. Use Open Type Hierarchy from its context menu. A hierarchy is opened containing all classes of the package. For completion of the tree, the hierarchy also shows some classes from other packages. These types are shown by a type icon with a white fill.
Use Previous Type Hierarchies to go back to a previously opened element. Click on the arrow next to the button to see a list of elements or click on the button to edit the history list.
Open junit.framework.TestCase.java file in the Java editor if you do not already have it open.
Press Ctrl+T or invoke Navigate > Quick Type Hierarchy and the in-place type hierarchy view is shown.
Pressing Ctrl+T while the type hierarchy view is shown will toggle between supertype hierarchy and subtype hierarchy.


Our Youth Ministry exists to help our youth better understand what and why they believe what they believe. We believe that by teaching them doctrinal truth and theology that they will deepen their understanding and will be better equipped to defend their faith. We tackle the tough issues and believe the youth of today hunger for challenging studies and the deeper things of God. In the words of John MacArthur, "God's truth is the most important thing in the universe."
At HRBC, we strive to provide a dynamic environment where the youth can learn God's Word (verse by verse), grow in Christ, share the gospel, and minister to others in the name of Christ. The youth's main goal is to glorify God in all we do by living a life worthy of Christ.
Not only do we strive to grow in the knowledge of our Lord and Savior Jesus Christ but we also participate and fellowship in many events throughout the year including youth conferences, cookouts, and summer mission trips. At HRBC, there is something for everyone and a number of opportunities to serve Christ.


Are you looking for the best drum box to use? if so, why not to buy a new one for a very reasonable price? Well, there're a lot of shops out there over the web that sells out drum box in a very cheapest prices because usually, these shops has there own warehouse where they make this drum box themselves hence the price are pretty reasonable that wouldn't of course break the pocket that much.
If you were asking me thought, I probably consider drum box available at Musicians Friend because musicians friend is the one leading today when it comes to musical instruments hence they did have all the awesome tools to have as for your music habits.


On FRIDAY, March 16th, 7:00-11:00, NerdNYC will hold its regular Board Game Night at ThinkCoffee (Mercer Street location).
Sad Recess is cancelled? Game with us at Dexcon!
Previous post: True Nerd Trivia: Thursday March 15th!


This is the Graphing Systems Of Linear Inequalities Worksheet Kuta section. Here you will find all we have for Graphing Systems Of Linear Inequalities Worksheet Kuta. For instance there are many worksheet that you can print here, and if you want to preview the Graphing Systems Of Linear Inequalities Worksheet Kuta simply click the link or image and you will take to save page section.


text:
News, Rugby Union
England Surge To Six Nations Win
November 3, 2017 davidnicholson01 Leave a comment
England 61 Scotland 21
by David Nicholson at Twickenham
A TRIUMPHANT England won the Six Nations Championship, the Triple Crown and Calcutta Cup for a second successive year in a comprehensive demolition of Scotland on Saturday.
Remember this was supposed to be a visiting side that had a realistic chance of beating England and reversing decades of misery at Twickenham.
Scotland talked the talk in the build-up, but were left limping not walking after a brutal encounter against a team which had far greater power, precision and ingenuity across the field.
It was a performance from the men in white that saw the home side passing 50 points for the first time against Scotland and equalled the highest winning margin — recorded by Martin Johnson's 2001 side.
This was by far and away the best performance by England this season, after they misfired against Italy and left it late to beat Wales. It also drew them level on 18 successive victories with New Zealand, as the two tier-one sides with the most successive wins.
This was a performance of such ruthlessness and skill that it could have been the All Blacks themselves shattering Scotland's pretensions.
Within minutes of the start a pumped-up Fraser Brown took on Elliot Daly and spear-tackled him into the ground. A dazed Daly left the pitch for a head injury assessment and Brown was sent to the sin bin by referee Mathieu Raynal.
The resulting penalty was kicked to touch and a sharp line-out take by Maro Itoje was swiftly shipped out to
Jonathan Joseph for the centre to open the scoring with a sweet try — the first of three for the centre dropped for the Italy game.
England repeated the line-out move three times during the match with the same try-scoring result, as a shattered Scotland were 20 points down within 24 minutes and at half time were 30-7 down.
Despite being outclassed, Scotland scored three tries, with Huw Jones scoring two.
Coach Vern Cotter was not prepared to make any excuses after the demolition of his side but did ruefully admit that the physicality and power of their opponents left his side littered with injuries and having to reshuffle his back line several times during the game.
"They are a very good side and everything they tried came off. We seem to play with more confidence at home and we need to develop it when we play away," Cotter said.
Captain John Barclay was even more frank in his assessment that his side did not play well, while England did. Barclay said his side "were rubbish and Monday's review will be brutal."
Scotland lost their influential full back, Stuart Hogg, and his replacement Mark Bennett lasted just four minutes before he suffered a leg injury.
What was even more ominous for Scotland, and a watching Ireland, was the increasing strength in depth of England, as they brought on Billy Vunipola for a canter in the second half.
The returning forward is a favourite with the Twickenham crowd and showed why he is considered world-class when he scored a try within minutes of entering the fray.
England coach Eddie Jones greeted the win with a broad grin and explained that there had been an attitude shift in his side to embrace what is to come and to lift themselves to greatness.
Jones praised Owen Farrell and George Ford as the on-field masterminds, creating space for others to score tries at will.
"It was good to have Billy Vunipola back because we need strength in depth in each position to become the No 1 side in the world," Jones said.
Jones was upfront about completing a second successive grand slam and said his team were talking about it in the dressing room.
"Ireland love spoiling parties, and especially the chance to spoil ours next week," Jones cautioned.
"But not many players have the chance to achieve greatness and next week is a chance for the players to do that. How many times will this opportunity be there for them and they have to seize it."
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Saul Zaentz (12 February, 1921-3 January, 2014) was an American film producer who, through Middle-earth Enterprises, owned the worldwide film, stage, and merchandise rights to J.R.R. Tolkien's The Lord of the Rings and The Hobbit.
This page was last modified on 9 January 2014, at 12:20.


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'Fashion Police' Star Melissa Rivers Reveals Trends You'll See At 2017 Oscars
by Taylor Ortega
The Academy Awards are Sunday, February 26, and all us normals are so looking forward to eating our weight in Twizzlers and boxed wine while we watch enchanted porcelain doll Emma Stone deal out awkward hugs on the red carpet.
Though we won't be there in person, due to the aggressively average hand life has dealt us, Melissa Rivers will be in attendance and hopes we'll join her in giving back.
OK, OK, relax. This charitable effort is something you can do while staying fully entrenched in the sadness divot your butt has created in your couch over time.
I know, it's a sweet deal.
Melissa has partnered with Allergan for their #Eyepowerment campaign to donate up to $25,000 to Dress For Success, a global nonprofit organization dedicated to providing women in need with professional attire and development tools necessary to make their economic independence a reality.
It's good for women. It's good for pantsuits. It's good for America. All you have to do is take a selfie of your dang eyeballs.
Melissa told Elite Daily,
Your eyes say so much about you and how you're feeling... A lot of people actually suffer from chronic dry-eye. I personally don't... but I get really red, itchy eyes.
SAME. Ten minutes into wearing contacts, I generally look like I just got a "Minority Report"-level eye transplant. Still, I plan on taking a picture of those dry babies for Allergan's campaign Sunday night.
The "Fashion Police" star added,
During the awards on Sunday night, take a selfie of your eyes watching the awards and, if you hashtag it #Eyepowerment, they will donate $10 — up to $25,000 — to Dress For Success, which is a fantastic charity.
See? You don't even need to put makeup on because the rest of your face will be out of frame sucking white zin through a swirly straw.
Melissa said,
It's very doable… It's so easy… Everybody watches the red carpet for the clothing, so you might as well give a little back while you're sitting there… Put the wine down… take the picture, hashtag #Eyepowerment and pick the wine up again. There you go.
I know Elite Daily readers. This is a crowd who can manage taking an eye selfie with a fist full of alcohol and not spill a drop. This is a crowd of overachievers and the Oscars is where we shine. From home. Alone.
After all, it's the biggest award show of the year.
Melissa confessed,
The Oscars is the most important. It's kind of the grandaddy of them all. I think the Globes are the most fun… First of all, they're serving champagne on the red carpet and you've got TV stars and movie stars and musicians... But the Oscars is still the most important… I always say it's going to your rich grandparents' house for dinner and they haven't quite decided who's in or out of the will yet… You cover up all your tattoos and put on your best behavior.
Fashion-wise, the Oscars brings us the greatest versions of trends that have popped up all awards season. This year, it's all about looking like an angel who fell from heaven, wandered up to the Dolby Theater and somehow just instantly knew exactly what to do with her face when photographed.
We've seen so much of the plunging neckline. We've seen so much of the embellishment — sort of etherial — and I think it's going to be the culmination of all that. It's been a really beautiful awards season so far. There's been lots of color, very romantic, etherial dressing. It's been very pretty.
All those plunging necklines mean the dress tape business is boomin'. Plus, any stars intent on sitting or eating or riding comfortably in a sedan can kiss those plans goodbye for the night.
REX/Sutterstock
Melissa shared,
You've gotta use a lot of tape and stand up super straight. And the hard thing isn't standing up and walking… the hard thing is sitting… I mean, literally there's stories about people — and we've all done it — laying across the back seats of cars so that you don't wrinkle before you get to the carpet.
Frankly, my mother made me do that before senior prom and that was a way lower-stakes event than the Oscars. Also, looking back, my prom dress does not hold up, speaking strictly in terms of style and trends and eternal embarrassment, but that's common of fashion.
Melissa mentioned one particular trend that could use some time on the bench.
I'm tired of the cutout… We all know they have amazing bodies… It's all such a trend and in three years cutouts will look very fresh again, I'm sure… They've been around for a while. It's time to keep it fresh, keep it moving.
But... but... if not cutouts, then what?
CALM DOWN. There are plenty of walking inspirations to look to for guidance.
Emma Stone always looks adorable... I think Nicole Kidman has been, by far, one of the best this whole awards season. She's worn — it's not actual fashion for civilians — but she has worn show piece after show piece after show piece and clearly felt good in them and worked them. And Cate Blanchett, too. They are so far ahead of the rest of us… They're these amazing creatures… They're designers' dreams.
True. So true, in fact, the rest of us may one day have to exercise excruciating physical strain to keep our self-esteem from plummeting every time we spot one of these sorceresses.
Melissa continued,
Ruth Negga is someone you can't ever count out… She's the one that walks in and you just go 'Why did I bother even trying? …I give up.' If everyone is in etherial, she's in architectural.
Ruth Negga already looks like a sentient oil painting or one of those women in romance novels who walk into a room and stops time with her face, so it's no surprise adding flawless designer looks to the equation only serves to create the most intimidating overall aesthetic.
Luckily for us plebes, there's no pressure to compete. Come Sunday, we'll sit in our own filth and watch the beautifuls parade around in their billowy gowns and soft, romantic up-dos. Then, on Monday, we'll tune into "Fashion Police" on 8 pm on E! and trade opinions with Melissa and the gang.
Sure, they won't be able to hear us screaming at our TVs, but we're still part of it all, somehow.
Where Is 'Everything Everywhere All At Once' Filmed? See The Universes
Everything To Know About The 2023 Grammys


Description: Filter used for compatibility purposes on some cards, especialy on Matrox G400, NVidia Geforce etc.
Description: This filter will remove interlace effect on PAL, SECAM and NTSC TV systems. Even and Odd lines of video are each from different time, but they are displayed together on computer monitor, which causes flanged image on moving objects. This filter duplicates number of frames.
Description: Deinterlace filter installed with Gold Black TV application for card PixelView PlayTV@P7000. Based on DScaler filter, is needed to avoid jerky video with audio preview enabled.
Description: Deinterlace filter installed with Leadtek's WinFast PVR application. This filter removes time information from stream, this is needed for USB card WinFast USB II to properly preview video.
Description: Bicubic resizer, best for upscaling. If you are using big monitors, this filter is for you. Great quality, but slow (needs fast CPU).
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SEMIRARA Mining and Power Corp. (SMPC) said on Monday it has spent P5 billion, or nearly a third, of the P8billion threeyear budget allotted until 2019.
SEMIRARA Mining and Power Corp. (SMPC) posted a 24percent increase in net income in the first half of the year to P7.86 billion, from P6.36 billion in the same period a year ago, mainly due to stronger contributions from its power units.
This is Jaycee De Guzman's stock reading for SEMIRARA MINING AND POWER CORP (SCC) in the Philippine stock market as of October 16, 2015.
MANILA Semirara Mining and Power Corp. on Thursday said it received its amended Environmental Compliance Certificate that allows it to boost production at its Molave Coal Project in Antique.
Semirara Mining Corp. is a verticallyintegrated power generation company, engaged in both. coal mining and power generation. The company owns the right to mine the coal resources of. Semirara Island in Caluya, Antique, until July 14, 2027, through its Coal Operating Contract with. the Department of Energy (DOE).
Case Study of Coal Mining on Semirara Island Source: Google Earth, 2010 The Island of Semirara, Antique Semirara Island is found in Caluya Municipality, Antique. Caluya is an island municipality that lies between the islands of Mindoro and Panay, about 45 hours by ferry from both of them.
At the time of his death, Victor Consunji was the vicechairman of the board of directors, as well as the president and chief operating officer of Semirara Mining and Power Corp..
Semirara Mining and Power Corp.'s earnings rose 42 percent in 2016 on the back of record coal sales and the contribution from its newest power plant. Semirara Mining and Power Corp.'s earnings rose 42 percent in 2016 on the back of record coal sales and the contribution from its newest power..
Semirara Mining Corp said Monday that operations of its Calaca coalfired power plant and the construction of additional units to expand it are getting back on. ... Semirara Mining expects 1Q boost from resumption of coal operations Corporate Governance Scorecard for PubliclyListed Companies in the Philippines.


You know where you want to go, and when you want to get there, but it's the "how" of your move that seems like a mountain of impossibility. Knowing what to plan for and how to execute it can make your move easy and your fresh start in a new home enjoyable. We've taken some of our most common questions on moving from our customers and put them from A to Z here so you'll have all the answers. Consider it our Student Movers cheat sheet.
Call your mover well in advance so you know they will be available on the day you need to move. Student Movers is always happy to help accommodate last minute moves, but knowing you will have a team to help you in advance can help settle your nerves and provide a problem moving solution.
Have your mover review all of your belongings you wish to transport and discuss special packing services or containers for some of your more abstract or valuable belongings.
Consider your move date and availability. Do you have a lot of items to move? Do you HAVE to be out of your current residence by the 1st or 31st? If so, it may help to have Student Movers packing service come earlier in the week to guarantee you are ready to go on the last day of your lease or escrow.
Air Conditioners: Consult a local dealer or service provider to see how you should best move your AC unit. Some sealed units should be bolted down for transport.
Bedding: Put your clean sheets in a clean container. Nobody wants to wash everything after they've moved because you put it in a dirty box. Consider throwing light articles into dresser drawers or other pieces of furniture.
Beds: Will you or your mover dismantle the bed and set it up in your new home? Should you need Student Movers to help you assemble or disassemble any items we provide this service at no additional cost. Queen and King size beds do take up a lot of space in a moving truck. Let your mover know if you have a specialty bed, such as a tempurpedic or adjustable bed, that needs to be moved.
Boats: Moving a boat or yacht is a job in itself. Don't surprise your moving company with extremely heave items that you forget to mention like yachts, gun safes, pool tables and pianos.
Books: Stack your books in a strong container with the bindings alternating directions. This will help the pages from sticking together. Books are heavy and can blow out the bottoms of boxes, as well as weigh down furniture, making it impossible to move.
Canned Goods: Make sure you pick a solid box or container to hold these items, as they are heavy. Remember to keep individual containers under 50lbs. A really neat program that the Student Movers is involved with is Move For Hunger. Should you want to donate some canned goods to the local food banke we would be more than happy to deliver the items for you.
China: Wrap these fragile items individually, with large pieces going at the bottom of a container, typically standing on their edge. This means plates going in vertically. Plates are much stronger on edge than they are when sitting flat in a box. Pad the bottom and edges of the container before putting your valuables in them. Please keep in mind that we recommend specialty boxes from HP Corporate Group or Box Bros for specialty packing needs.
Clothing: Clothing is typically light and packs well in suitcases, boxes or trunks. Ask your mover if they can move your hanging items on the hanger. Student Movers does provide free wardrobe boxes through our loaner program. We bring the requested amount of wardrobe boxes the day of your move and you return them when done. If you want to keep them, $10 per box not returned will be added to your bill.
Clocks: Pendulum on clocks should be removed or secured before transport to avoid damage. Small clocks can be wrapped and placed in containers.
Curtains and Drapes: Before moving day, remove your curtains from rods and place them in a container or a dresser drawer. You may also choose to have them dry cleaned while you move and pick them up once you are at your new home.
Drawers in Furniture: Light articles can typically be stored in furniture drawers for transport. Do not place heavy items, liquids, breakables, or firearms in drawers.
Documents: Make sure you have all of your important documents, including, but not limited to: medical records, x-rays, MRI's, tax documents, receipts, logs, photographs, passports, birth certificates, insurance records, and other important documents.
Dryers: Check with your service technician to insure safe transport. Motors may need to be secured before moving them.
Food: Dispose of food in open containers that might spill or spoil en route. Perishable foods should never be stored or shipped.
Freezers: Completely defrost your freezer one to two days before moving. Your unit should be dried and aired to avoid musty odors building up.
Glass Tops to Furniture/Mirrors: Typically, these items should be crated to avoid breakage. Consider investing in mirror packs.
Glassware: Stemware and glassware should be wrapped individually and placed in a padded container. Do not nest unwrapped glasses inside of each other. Place glassware right side up, not on its side.
Grandfather Clocks: Remove chimes. Secure weight chains tightly against the base of the clock with wire or strong string and remove weights and pendulums. Consider contacting a reputable clock technician to prepare the works against damage.
Hangers: Moving is a great time to down size by donating extra hangers and clothes, or even get more if you need them. Ask about Student Movers' wardrobe box loaner program.
Jewelry: Keep valuable jewelry in your immediate possession to insure its safety.
Kitchen Utensils: These items should be clean and placed in containers, with larger items placed on the bottom and lighter ones on the top. Consider padding or wrapping each piece to prevent dents or scratches. Small kitchen appliances such as toasters or waffle irons may be wrapped and placed in the container with your utensils.
Lamps: Remove any ornamental pieces and wrap them individually. Large lamps will typically be transported outside of a container and small lamps can be wrapped and placed in boxes or containers.
Mattresses: Contact your moving service to see if they provide a plastic wrap for your mattress, like Student Movers does. You can also protect your mattress with an old sheet or blanket.
Medicines: Seal bottles and jar stoppers and place in a container upright.
Mowers and Gas Powered Tools: Gas tanks should be drained and oil reservoirs emptied. No flammable mixtures should be transported on public carriers.
Paintings/Pictures: Small pictures can be safely placed in blankets and wrapped for safe travel. Large or valuable paintings should be crated. Ask your mover for details.
Stereos: Secure any tone arms and remove any CDs from the unit before travel.
Records: Place records vertically in a padded container, individually wrapped. Records on edge are more resistant to breakage.
Plants: These should typically be transported and handled personally.
Refrigerators: Defrost and thoroughly dry your refrigerator before moving. This is VERY important, and the doors should be left open for several hours prior to transport to avoid mold and odor build up. All removable parts should be taken out of the refrigerator and packed up separately. Motors may have to be bolted down prior to transport, contact your local serviceman for details. Be sure to allow enough time for your refrigerator ice to melt before the movers arrive. You don't want the ice to melt during transport. The moving truck will get quite warm, especially in summer, and will cause ice to melt even faster. We recommend you consult your user's manual for your refrigerator so that you know the manufacturer recommended way to move the unit.
Rugs: Remove any tacks you may have in your rug or carpet. You mover will roll them up for safe transit. If you are storing your rug, consider having it cleaned prior to storage.
Sewing Machines: These are safe to transit in their case. To avoid any rubbing damage, wrap them in a blanket or place them in a padded container.
Silverware: Wrap silverware individually and place in a padded or original container to avoid scratches.
Stoves: These must be disconnected prior to pick up. Be sure gas lines are shut off tight and capped, if possible. If there are any loose burners, coils, griddles, deep fryers or other removable parts, wrap and pack them separately.
Television Sets: Remove any television antennas, and check with your local service technician to make sure that your unit is ready to move.
Toilet Articles: Seal corks, tops and stoppers of cosmetics, medicines and perfume bottles with natural nail polish, paraffin or masking tape before wrapping separately in paper and placing upright in a container.
Tools: Tools can generally be placed in a strong container without wrapping. Valuable tools should be wrapped to avoid damage.
Valuables: Legal documents, important papers, jewels and currency should be handled by you personally. Keep them in your immediate possession.
Washers: Automatic washers must be serviced by an authorized service man. Motors should be checked and secured, tumbler action protected and fastened in place.
Cable, Newspaper, Trash, Post Office, Banks, Schools, Medical Services, Netflix, Libraries, and Utilities (telephone, electricity, gas, water, fuel oil). Your electric company can turn on and off and transfer your services by visiting them online – SoCal Edison, PG&E.
Check out local amenities that you will plan on using, including: parks, schools, libraries, shopping centers, movie theaters, malls, and restaurants. Have fun and make it a scavenger hunt for your new favorites, or utilize a service such as yelp to find the best places around town.
Moving can be stressful. Make sure you remember to turn off the utilities, lock the windows and doors, and turn in any and all keys you have to the residence. Nylon rope and packing tape are always handy to have around on a moving day. You never know when they'll come in useful. Make sure you putty or repair any holes in the wall left after you have removed your belongings. If you can, touch these items up with paint to avoid costly expenses and the possibility of your security deposit being billed.
Finally, RELAX. Know that you have hired a credible mover and have taken the time to plan your move ahead of time. Leave everything to your mover; they're expertly trained for the job.


EDIT: OH WHAT THE RULE 6 GUYS IT TOOK ME TWO RULE 6ing YEARS TO GET 1000 POSTS AND NOW YA DO THIS. SCREW ALL Y'ALL.
You know, I didn't realize how many posts I had in Off-Subject.
Enable posting in arts and crafts and forum games plz.
What the...Heck happened to the Forum?
Oh, and MHG Announced her climatic return?
Seriously. What the crap? I leave for the night, come back, and everythings screwed up. Something fishy is going on, maybe a prank (I kill the mods and admins if that's what it is), maybe a hack or virus (more than likely). But whatever it is, I'm going to find out.
I'm going from denial to depression over this loss now.
Heres another random thought: What the heck are we going to call this period? The forum depression of 2007? The MHG Deletation Spree? The Meteor shower of August 07???
MHG Destruction/depression era. How 'bout that?
Wait, where did MHG announce her return?
Yes! Except it kind of implies that everything deleted was bad. When we all know that that certainly wasn't the case!
She didn't, someone hacked into account and used her mod powers to delete GTKY, A&C and part of Off-Subject.
uhh, wow. who really cares? we need to name everything?
Last edited by lahimatoa on Fri Aug 17, 2007 3:20 pm, edited 1 time in total.
At least the hacker left R&P alone.
That place is in more dire need of a cleansing than anywhere.
]That place is in more dire need of a cleansing than anywhere.
The irony is kinda thick, isn't it?
Uh, oh. Ath-a-late is not pleased. Someone might get eaten before the day is over.
Are you happy now, Cola?
I'm just wondering how long it'll take until an exodus happens. If whatever it is didn't kill us, then squabbles will.
Exodus already happened about three weeks back, m'ChickenLeg.
OOH! OOH! How about... The Forum Holocaust of 07. Think about it, thread genocide, right?
Pfft, this place won't rebuild fully. The most awesome things ever were deleted. So now this place is a shadow of the shadow that was awesome.


If you are looking for casual sailing style jackets for ashore, you can find a great deal of leading sailing brands here at Coast Water Sports, leading manufacturers such as Gill. Our shore wear fleeces can be worn underneath our jackets for added warmth or can be worn separately depending on the temperature outside. If you require any assistance with sizes and fittings, take a look at our product specifications or contact our amazing team for extra help.


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Home › Press › Press releases › Composition management BAM PPP
Composition management BAM PPP
28 September 2015 10:40 - Invesis bv
Bunnik, the Netherlands, 28 September 2015 – The Executive Board of Royal BAM Group nv has appointed Kieron Meade as managing director of BAM PPP bv with effect from 1 October 2015. Kieron Meade has been a director of BAM PPP since 2009 and will succeed Richard Fielder, who will step down in relation to his retirement.
Richard Fielder has led BAM PPP since 2000 and has made a substantial contribution to the success of the Group in the market for public-private partnerships. The Executive Board is pleased that Mr Fielder will continue within BAM in an advisory role until mid-2016.
With effect from 1 October 2015 the management of BAM PPP bv will consist of Kieron Meade (chairman) and Patrick R.E. Snippe.
Further information: Arno Pronk, +31 (0)30 659 86 21.


Win Books for Your Grandkids!
Thanks! You've been successfully entered. A winner will be chosen on November 9.
Offer only valid for US residents. Shipping location of winner must be within the United States of America.
Offer applies for either a one-month picture of board book subscription. Alternatively the winner may apply the one-month value ($25.99) to a subscription of longer duration.
Elephant Books and Grammy's Grid reserve the right to withdraw this promotion at any time without prior notification.
Entry to the contest also enters the registrant onto the Elephant Books mailing list. You may opt out of mailings at any time.
Winner will be chosen at random on or about November 12, 2018. One entry per person.


Yes, they do a thorough background check.
What is the policy of boyfriend & girlfriend working together that's been living under the same roof for 3 years also with no complaints at other jobs they did together.
There is suppose to be no dating employees but when i first started everybody was dating each other . Even management but the rule book say no dating .
Will they not hire me if I have had too many jobs in the past?
When do you get the 3000$ hiring bonus?


Essentially, the public pilot is now available to sole traders and companies using standard VAT accounting. This applies whether returns are done monthly (excludes very large traders required to make monthly payments on account) or quarterly provided they are up to date.
For those that sign up this means they will need to keep their VAT records digitally from the first day of the period covered by their next VAT Return and for agents wishing to sign up clients they will need to create their Agent Services account, if they haven't done so already, and link any existing agent-client relationship to it, before attempting to sign-up clients to the MTD pilots.
Further pilots both private and public are set to begin for partnerships, those that trade with the EU and users of the Flat Rate scheme, per the timetable below. Those customers with a default surcharge within the last 24 months will also be able to join the pilot by the end of October 2018.
Businesses in this section are NOT deferred and still currently have a mandated start date of 1 April 2019.
Private testing begins with partnerships, those customers that trade with the EU, and users of the Flat Rate Scheme.
Open to other sole traders and companies who are not up to date with their VAT and businesses newly registered for VAT that have not previously submitted a VAT return.
Pilot testing for these groups is expected to open in Spring 2019.


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Prince Euneon (Korean: 은언군, Hanja: 恩彦君) (29 May 1754 – 30 June 1801), personal name Yi In (Korean: 이인, Hanja: 李䄄), was a royal prince of the Joseon Dynasty. He was the grandfather of the 25th King of Joseon, King Cheoljong. After the death of Crown Prince Sado, he was exiled to Ganghwa Island. He was later executed in the 1801 Catholic Purge, due to having a Roman Catholic wife.

Family
 Father:  King Jangjo of Joseon (13 February 1735 – 12 July 1762) (조선 장조)
Grandfather: King Yeongjo of Joseon (조선 영조) (31 October 1694 – 22 April 1776)
Grandmother: Royal Noble Consort Yeong of the Jeonui Yi clan (영빈 이씨) (15 August 1696 – 23 August 1764)
 Mother: Royal Noble Consort Suk of the Buan Im clan (? - 1773) (숙빈 임씨)
Grandfather: Im Ji-beon (임지번)
Grandmother:  Lady Kim of the Gimhae Kim clan (김해 김씨)
 Brother: Yi Jin, Prince Eunsin (11 January 1755 – 29 March 1771) (이진 은신군)
 Consorts and their respective issue(s)
 Royal Princess Consort Sangsan, of the Jincheon Song Clan (상산군부인 진천군송씨) (15 October 1753 – 4 April 1801), catholic name Mary
 Yi Dam, Prince Sanggye (상계군 이담) (21 January 1768 – 20 November 1786)
 Prince Yi Changsun (이창순)
 Prince Yi Changdeok (이창덕)
 Yi Dang, Prince Punggye (풍계군 이당) (1 February 1783 –8 May 1826)
 Princess Yi of the Jeonju Yi clan (성주 이씨) (4 August 1796 – 4 April 1872)
 Unknown concubine
 Prince Yi Seong–deuk (이성득), (1775 –27 November 1817)
 Prince Yi Cheol–deuk (이철득) (b.1780)
 Royal Princess Consort Jeonsan, of the Jeonju Yi clan (전산군부인 전주이씨), daughter of Yi Deok‐hui (이덕희)
 Unknown son
 Yi Gwang, Grand Internal Prince Jeongye (전계대원군 이광) (21 March 1785 – 2 November 1841)

References

1754 births
1801 deaths
Joseon dynasty

redpajama_set_name: RedPajamaWikipedia


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    <link rel="stylesheet" href="./bootstrap.min.css">

    <title>HW4_Users</title>

Angular HW4 Users in factory

redpajama_set_name: RedPajamaGithub


Thornfield Properties and the Bank of Scotland, have been selected as the preferred development partner for a new £25m arts venue in Hemel Hempstead.
Dacorum Borough Council selected the joint venture last week for the scheme which comprises an 85,000 sq ft venue.
The arts space will be accessed through a glass cube in the centre of Waterhouse Square, a new retail, leisure and restaurant square.
The development is part of Thornfield's £350m regeneration project on 37-acres in Hemel Hempstead.
Thornfield and Dacorum Council will now develop more detailed refinements to the plans before incorporating the plans into a master-plan for Waterhouse Square as a whole.
The work, designed by Allies & Morrison, architects on London's Royal Festival Hall, should start in 2010 due with the venue opening in winter 2012.
M G Real Estate has agreed to forward-fund the next phase of build-to-rent homes at Crest Nicholson's Arborfield Green Garden Village scheme in Berkshire.


Javelina is dedicated to providing the highest quality Cannabis concentrates and infused products on the market today. By utilizing one of the most effective extraction systems, they are able to ensure quality and potency.
Javelina will be here January 19th from 5pm to 8pm MST with deals and swag!


We were discharged from the hospital on the Saturday before Easter. I thought for sure that we'd spend yet another holiday in the hospital with Juliette. I was determined to go home and have Easter with our little family that next morning. Plus, Easter is now a difficult day for me emotionally, because last year my grandma passed away on Easter. It may have been a different actual date but Easter will never be the same. Especially since she had always made Easter so special for my sister and I as we were growing up.
As soon as Juliette vomited three times Saturday night, I almost took her back in the emergency room on Easter Sunday morning (2:30am). But the doctor who quickly called me back, after I paged him in the middle of the night, reminded me to calm down and be patient and told me that this is all expected and part of post-concussion syndrome and give it time. As long as her neurological assessment was fine, then there is no need to worry. And literally after she woke up and started vomiting, she saw the Easter baskets on my bedroom floor and wanted down to go play with them. So she was most definitely fine in that regard.
Juliette hasn't vomited since that night and she is on the mend, in my opinion. She's obviously not old enough to tell us that her vision is blurry, or if she feels dizzy, of if she's nauseous, or that there is too much stimulation in the room for her little brain. But she does put her fingers in her ears when it is, in fact, too loud or too much for her and begins to get a little on the fussy side. Sometimes in the car she doesn't like my music on. She likes the silence. But by the Grace of the good Lord, she is healing and doing very well and to me, seems like she's back to her self. She's a toddler on the go. She's back to running and falling, she trips, she falls and she still bangs her head on tables that are her height when she stands under them. I try not to freak out and worry about her "sensitive head". Because it's really not all that sensitive. I'm just trying to heal too from all this trauma lately and I try the best I can to back off and give her space. But I also try my best to follow her around if it's on solid hard ground, but even that, on top of most mom things I do, gets exhausting. I have to trust that she is stronger then I give her credit for and trust that she will be okay, even if she did fall. God gave us one strong little girl. She is a fighter.
Easter was great this year besides both kids were sick with colds (aren't we always sick on events and holidays?), we had to send Bobby's dad home early because he was a disappointment (we both said that we should have known better). We spent most of Bobby's long swap home in the hospital, worried about something constantly, from the health of us four, to his blood pressure, the hospital bills never ending, our taxes were due, the escrow in this community is outrageous, I missed a lot of work (extra pick up shifts I could have potentially worked), and the allergy season is absolutely horrid this year in Texas, which is making both kids miserable on a day to day basis. What is going on with Texas weather ya'll? One day it's 85 degrees and we're playing in the hose/splash pad and the next day it's 52 degrees, gloomy and cold. And it's been this way-on and off weather mess for months and months. I always thought Michigan was bad. But this is 200% worse! I am literally ready for hot, desert, non-stop heat and sun for the next few months like Texas is supposed to be. I'm ready for pool days and ready to meet new people. I'm ready to get out of this house!
Although we were up all night long Saturday cleaning up vomit (twice in her crib and once in our bed), we still managed to play Easter bunny and throw together Easter baskets and hide eggs all around the front and back yard. With the help of Jennifer we added some Matilda Jane and the help of Shelby, we added in some Usborne Books. And Liz came by and hid even more eggs outside our house with presents for the girls which was so sweet. It was bittersweet. Just to have my husband home, despite all the recent trauma lately, we made the best of it, took a ton of photos and then rested (all of us) the rest of the day.
I can't speak for my husband, but the worry about your child, once you leave the hospital, is exhausting and consuming. He sometimes still laughs at me because I still have a baby monitor in my 4-year-olds room. I carry two baby monitors with me around the house when they're asleep. I wake at every peep, cough, whine and fall off the bed (yes-that's happened once so far and just a few days after Juliette got out of the hospital with a head injury). Just the other night I could hear Juliette breathing funny so I went into her room and got down close and it just was her allergies and nose sounded stuffy.
My girls started off with a cold (or so I think it was that), and it's still lingering. It's been about two months or longer now. It's just strictly nasal related. No other symptoms. Runny nose, that's it. And it can get annoying, especially for Josie who keeps asking for tissues until her nose is raw. I'm praying to God no cough sets in because that would mean we'd have to reschedule/cancel OIT again. Yes, we're attempting to try OIT again but more on that later in another post.
As I sit with her, I remember those days as a kid being miserable from seasonal allergies. Bobby and I both suffered in Michigan. As neighbors, he would come to my house and beg me for some Claritin. I was that kid that missed picture day and make up picture day a lot because of my allergies. I woke up with eyes crusted shut and swollen. My eyes itched constantly, I sneezed a ton and ultimately, in my adult years developed chronic sinusitis that required sinus surgery in January 2017 (the BEST decision I ever made). I just look at Josie as she suffers and pray to God that she'll grow out of this or that there is some type of relief for this misery. Or that the weather would just make a decision and stick with it already.


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DISTRICT WIDE LOW VOLTAGE SYSTEMS FOR CENTENNIAL SCHOOL DISTRICT AT MULTIPLE SITES
DISTRICT WIDE LOW VOLTAGE SYSTEMS FOR CENTENNIAL SCHOOL DISTRICT AT MULTIPLE SITES Bids due: July 29, 2021 @ 2:00 pm INVITATION TO BID PROJECT #72921-01 Sealed bids will be received by Centennial School District in the District Office, 18135 SE Brooklyn Street, Portland, OR 97236 until 2:00 p.m. Thursday, July 29, 2021, By U.S. mail:	By hand delivery: Centennial School District	Centennial School District District Office – Bid #72921-01	18135 SE Brooklyn Street 18135 SE Brooklyn Street	Portland, OR 97236 Portland, OR 97236	District Office Bid #72921-01 Project Description: The Contractor will provide all labor, equipment, materials, project management and site supervision as required to complete all scope of work described in the project specifications. The project is estimated to cost $2,500,000. Bids will be opened and read aloud immediately after the bid closing time for their receipt, at which time all interested persons are entitled to attend the bid opening. Bid documents will be available for viewing and/or download beginning on July 14, 2021 at OregonBuys https://oregonbuys.gov/bso/ or Contractor Plan Center http://www.contractorplancenter.com/?Src=UID. Prospective bidders will be required to sign in as an account member to have access to the project documents. Prospective bidders can call OregonBuys at 855.800.5046 or Contractors Plan Center at 503.650.0148 with any questions about setting up an account for viewing and/or downloading documents. No Bid will be considered unless it is in complete accordance with the instruction to bidders and is submitted upon the official bid form provided to prospective bidders (included in the bid documents). A non-mandatory pre-bid conference for Contractors interested in bidding this project will be conducted at 9:00 a.m. on Wednesday, July 21, 2021. The pre-bid conference and tour will commence at Centennial High School – 3505 SE 182nd Ave, Gresham, OR 97030. The Board of Directors of Centennial School District reserves the right to reject any or all bids or portions thereof and waive any informality or irregularities. Paul Southerton Director of Business and Operations Published July 21, 2021. OL208906
Publication: Invitations To Bid
Owner: Centennial School District
Bid Date: 07/29/21
Bid Time: 2:00 PM