text:
Q: Getting 400 error on executing groovy script to POST through VSTS api in SoapUI I am creating a groovy script to run from SoapUI to create test plans in VSTS through VSTS api, But on executing it I am getting HTTP400 error. While the same request runs successfully with same headers in REST step of SoapUI.
Initialy I was getting error for authorization but now that got resolved..
It seems the way I am passing the Request body is incorrect
import groovyx.net.http.HTTPBuilder
import static groovyx.net.http.ContentType.JSON
import org.apache.commons.codec.binary.Base64;
import com.eviware.soapui.support.types.StringToStringMap
import org.apache.http.client.methods.HttpPost;
import java.io.File;
import java.io.IOException;
import groovy.json.JsonBuilder
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.ClientProtocolException;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.mime.MultipartEntity;
import org.apache.http.entity.mime.content.FileBody;
import org.apache.http.entity.mime.content.StringBody;
import org.apache.http.impl.client.DefaultHttpClient;
import org.apache.http.util.EntityUtils;
import static groovyx.net.http.Method.*;
import groovyx.net.http.*
import static groovyx.net.http.ContentType.*
import static groovyx.net.http.Method.*
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.protocol.HTTP;
import org.apache.commons.httpclient.methods.PostMethod;
import org.apache.http.entity.StringEntity;
import static groovy.json.JsonOutput.toJson;

HttpClient httpclient = new DefaultHttpClient();
def post = new HttpPost("https://dev.azure.com/xxx?api-version=1.0");

def jsonBody = [:]
// Test title
jsonBody.put("title", "Test title")

def http = new HTTPBuilder( 'https://dev.azure.com/xxx?api-version=1.0' )
post.addHeader("Authorization","Basic
Onvdfdsfgsdgdfhgfhgfhgfhjgfhtrhtrhtrhtrbvdfb=");
post.addHeader("Accept","application/json");
post.setEntity(jsonBody)

HttpResponse response = httpclient.execute(post);

Expected Result: New test plan should be created in VSTS with the Provided name.
Actual Result: Getting Error: Tue Jan 15 17:03:14 IST 2019:INFO:HTTP/1.1 400 Bad Request [Cache-Control: no-cache, no-store, must-revalidate, Pragma: no-cache, Content-Length: 207, Content-Type: application/json; charset=utf-8, Expires: -1, P3P: CP="CAO DSP COR ADMa DEV CONo TELo CUR PSA PSD TAI IVDo OUR SAMi BUS DEM NAV STA UNI COM INT PHY ONL FIN PUR LOC CNT", Set-Cookie: VstsSession=%7B%22PersistentSessionId%22%3A%22b53ba5ae-5940-4bc4-b464-24b72350fd09%22%2C%22PendingAuthenticationSessionId%22%3A%2200000000-0000-0000-0000-000000000000%22%2C%22CurrentAuthenticationSessionId%22%3A%2200000000-0000-0000-0000-000000000000%22%7D; domain=.dev.azure.com; expires=Sun, 14-Jan-2024 11:36:12 GMT; path=/; secure; HttpOnly, X-TFS-ProcessId: ffde6ea4-0faa-4f90-b5d8-07ed687398f7, Strict-Transport-Security: max-age=31536000; includeSubDomains, ActivityId: 3b96e21f-0539-4724-b31f-178b14072bb1, X-TFS-Session: 3b96e21f-0539-4724-b31f-178b14072bb1, X-VSS-E2EID: 3b96e21f-0539-4724-b31f-178b14072bb1, X-VSS-UserData: 3486938b-c20d-69ff-9eca-14d4011c8ebf:bmalviya@xxx.com, X-FRAME-OPTIONS: SAMEORIGIN, X-AspNet-Version: 4.0.30319, X-Powered-By: ASP.NET, X-Content-Type-Options: nosniff, X-MSEdge-Ref: Ref A: BD9BB78BC2814FFD94BEE99ECAE98955 Ref B: BY3EDGE0205 Ref C: 2019-01-15T11:36:12Z, Date: Tue, 15 Jan 2019 11:36:11 GMT]

A: If you can get it working with a regular REST TestStep, I would build your functionality around that.

*

*Create a TestCase with that REST TestStep.

*Disable it. SoapUI should not run it. Your Groovy Script should.

*Add a Properties TestStep, and add the variables you want to control in the REST TestStep.

*Add the variables inside your REST Request. If it's a GET, then just add them in the URI.

*Then modify your Groovy Script TestStep. It shouldn't actually DO the REST Request, but rather activate/run your REST Request TestStep, using something like:

def result = testRunner.testCase.getTestStepByName("The Name Of Your Rest Request TestStep").run(testRunner, context)
You may then want to check if the teststep executed as expected. But that should do it. Your Groovy Script TestStep will be the only one activated by the TestCase Runner, but the script will then activate your REST Request TestStep 0-N times depending on your code. Make sure your Groovy Script modifies the values of your Properties TestStep as needed on the fly.

A: I created 4 new test steps in my suite:
1: Properties
2: Groovy test step
3: 2 HTTP request method test steps
In the properties test step I stored the value of 2 flags viz PassFlag and FailFlag with value as "T" depending upon the result from the test result.
In the groovy test step I fetched the value from properties test step and once the code finds the value of PassFlag as "T" it moves to test step "HTTP method" with details to pass the test case else to the "HTTP method" with details to fail the test case. below is the groovy code:
import com.eviware.soapui.support.*;
import com.jcraft.jsch.*

def groovyUtils = new com.eviware.soapui.support.GroovyUtils( context )
def myTestCase = testRunner.getTestCase()//myTestCase contains the test case
propTestStep = myTestCase.getTestStepByName("PassFailStatus") // get the Property
TestStep object
def testCase = testRunner.getTestCase()
def propTestStep = testCase.getTestStepByName("PassFailStatus")
def Passvalue = propTestStep.getPropertyValue("PassFlag").toString()
def Failvalue = propTestStep.getPropertyValue("FailFlag").toString()

if(Passvalue == "T"){

Thread.sleep(30000)
testRunner.gotoStep(testRunner.testCase.getTestStepIndexByName('PassTestCase'))

log.info("success")
}else{

testRunner.gotoStep(testRunner.testCase.getTestStepIndexByName('FailTestCase'))

log.info("Failure")
}


Jon Azpillaga Urrutia, one of the towering figures–both literally and metaphorically–of contemporary bertsolaritza (Basque poetic oral improvisation) passed away last Thursday, February 2, at the age of 81.
He was born in Pasaia, Gipuzkoa, in 1935, where his father Juan–originally from Ondarroa, Bizkaia–worked in the port. His mother, Veronica Urrutia, was originally from the Torre baserri (farmstead) in Berriatu, Bizkaia. After his father was killed in the Spanish Civil War, when he was barely a year and a half, the family moved back to the baserri in Berriatu. Azpillaga grew up on that baserri, which in total provided a home for 16 people, carrying out the obligatory farm chores. At age 14 he began earning a living for himself away from home, in a boatyard in Ondarroa, cycling to and from work everyday. After completing the obligatory Spanish military service, he eventually started his own repair business, alongside his brother and some other partners, in his mid-20s. Now living in Ondarroa, he also joined the local choir as a tenor. He married Maria Arrizabalaga Itsasmendi in 1960 and the couple moved to neighboring Mutriku, Gipuzkoa, where she owned a hair salon. And the couple eventually had 6 children.
Azpillaga dedicated a lot of his free time in Mutriku to fundraising for the ikastola or Basque-language school and establishing a bertso eskola (a bertso school) there to train young people in the art. The Church was an important part of his life and he even recited the Sermon on the Mount in verse. He also attended the annual July 4 church service and celebration held in honor of Saint Balentin Berriotxoa, one of the two patron saints of Bizkaia (alongside Saint Ignatius Loiola) in Elorrio. On a personal level, he was always noted as a calm, composed, and fearless bertsolari with a great towering physical presence and a classic exponent of the bertso postura (stance). This all meant that he was invariably asked to begin any bertso session, hence the epithet "Hasi Azpillaga!" (Take it away Azpillaga!), which was also the tile of a free-to-download 2001 biography about him by Mikel Aizpurua.
Jon Azpillaga Urrutia, at the online Auñamendi Eusko Entziklopedia.
Voicing the Moment: Improvised Oral Poetry and Basque Tradition, edited by Samuel G. Armistead and Joseba Zulaika, free to download here.
January 20, 1935 is a key date in Basque cultural history as it marks the first time a national championship was held for bertsolaritza (improvised sung oral poetry) one of the most dynamic and singular forms of Basque cultural expression.
Inazio Eizmendi or "Basarri" (1913-1999) in October 1937. One of the great figures of bertsolaritza who dominated the art form for thirty years. Image by Jesus Elosegui, courtesy of Wikimedia Commons.
Termed at the time the First Bertsolari Day, the event was held in the Poxpolin Theater in Donostia and included the participation of some nineteen competitors. In the collective mindset of the organizers it was hoped that this relatively new format, an organized contest with a panel of judges evaluating the quality of the bertsoak (verses) on their technical features alone (or their degree of difficulty if you will) on a points-based system, would help to propel bertsolaritza into the twentieth century and away from what some at least considered its rather dubious connections with the raucous world of taverns and cider houses. That said, some of the traditional older bertsolariak (oral improvisers) who came from the latter tradition did take part in the championship, most famously of all Txirrita (Jose Manuel Lujanbio), the greatest of all cider house bertsolariak. As Gorka Aulestia observes in Voicing the Moment, "Txirrita, the elderly patriarch of traditional bertsolaritza –at the age of seventy five, weighing 260 pounds and dressed in the customary long black shirt– did not fit the image envisaged by" the more progressive organizers.
In the end, and much to their relief, the event was won by a young twenty-two-year-old from Gipuzkoa, born in Errezil but who had lived in Zarautz from age seven: Inazio Eizmendi, who went by the name "Basarri." And the runner-up was Matxin Irabola from Senpere, Lapurdi. Basarri was the ideal winner for the modernizers who had encouraged the idea of moving bertsolaritza toward a championship format. He was young, forward-thinking, and would ultimately lead bertsolaritza out of the taverns and into more the neutral public settings of towns and squares. In short, this first national championship served a s a springboard to change the whole face of bertsolaritza, marking not just a generational change among its leading exponents but also a transformation in the very way the art form was conceived and performed.
Voicing the Moment: Improvised Oral Poetry and Basque Tradition, edited by Samuel G. Armistead and Joseba Zulaika. Free to download here. The definitive introductory guide to bertsolaritza in English that not only outlines the history and sociocultural impact of the art form in the Basque Country but also explains how it functions, the changes that have taken place in recent years with the coming of the technological age, and sets all this within a global framework by also discussing other worldwide examples of improvised oral art forms.
Improvisational Poetry from the Basque Country by Gorka Aulestia. An essential history of bertsolaritza to the modern age.
Bertsolaritza: The Reality, Tradition and Future of Basque Oral Improvisation by Joxerra Garzia. Free to download here. History and contemporary analysis of the art form by a leading theoretician of bertsolaritza.
Alan Lomax (1915-2002) was one of the great American collectors of twentieth-century folk music. A scholar, writer, and activist, he was one of the main architects behind the folk revivals of the 1940s, 50s, and 60s, blazing the trail for the likes of Woody Guthrie, Bob Dylan, Joan Baez (who of course sings a memorable version of the traditional Basque song Txoria txori), and many others.
Alan Lomax in front of American Patchwork video, c. 1984. From the Cultural Equity website.
Together with his father, the folklorist and collector, John A. Lomax, he also recorded thousands of songs and interviews for the Archive of American Folk Song at the Library of Congress. Today, the Lomax Family Collections are housed at the American Folklife Center. To get some idea of the range of his activity, see the Alan Lomax Archive here.
In 1952-53, Lomax spent some time in the Basque Country, where he recorded many traditional songs as well as bertsos (improvised oral poems). The Association for Cultural Equity was founded by Lomax to explore and preserve the world's expressive traditions with humanistic commitment and scientific engagement, and it generously posts Lomax's Basque recordings here.
As well as making up a historical archive of incalculable value, these recordings serve to capture a time and place in Basque history in which public cultural expression in the Basque language was strictly limited by the Franco dictatorship.
This is a truly invaluable resource for anyone interested in Basque culture in general or, more specifically, traditional Basque music and bertsolaritza. It is a fitting tribute to the life and work of Alan Lomax, and the Association for Cultural Equity is to be applauded for its efforts in posting these recordings online.
If you're interested in these topics, the CBS publishes Alejandro Aldekoa: Master of Pipe and Tabor Music in the Basque Country, by Sabin Bikandi. Ostensibly a biography of one of the most renowned Basque taborers and dance masters, this work actually involves a wider description and discussion of the relationship between music and dance in the Basque tradition. What's more, it is accompanied by a DVD that includes, among many other things, historic footage of Basque ritual dances in the 1920s, archive images of traditional Basque instrument makers and performers, and recordings of two different types of bertso performances (in both a formal championship and a less formal "bertso dinner" setting).
On bertsolaritza, more specifically, although the work that also includes a chapter on the musical foundations of the genre, see Voicing the Moment: Improvised Oral Poetry and Basque Tradition, edited by Samuel G. Armistead and Joseba Zulaika. This book is available free to download here.


Current school education status on Computer science, problems & challenges, and what we can do about it. Share Girls Who Code story, and encourage to volunteer.
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text:
\section{Introduction}

 Faults slip in a variety of modes, from dynamic earthquakes to transient slow earthquakes and aseismic creep \cite{Avouac:2015bs,Burgmann:2018fg}. The classical picture of faults being either locked and prone to dynamic and damaging earthquakes, or unlocked and quietly creeping to accommodate tectonic stress, is evolving. Growing evidence indicates complex fault behaviours and interactions among and between modes of slip \cite{Jolivet:2020ku}. Evidence includes fault segments hosting both slow and dynamic earthquakes, as well as slow earthquake preceding and possibly triggering the nucleation phase of dynamic earthquakes \cite{McLaskey2019a,Obara2016,scholz_2019}.  Answering a number of fundamental questions such as what controls the slip mode on a fault, whether there exists a continuous spectrum of slip modes on faults, and what determines the possible evolution of a slow earthquake into a dynamic seismic rupture, requires exhaustive characterization of all slip phenomena. Interferometric Synthetic Aperture Radar (InSAR) holds the promise of continuous geodetic monitoring of fault systems at a global scale, which may well hold the key to address these questions. However, although the data exists, current algorithms are not suited for global monitoring because they require time-consuming manual intervention, and the final product requires exhaustive expert interpretation.

InSAR is routinely used to measure ground deformation due to hydrologic, volcanic, and tectonic processes\cite{Fialko2012,Chaussard2014,Jolivet2015a}. The apparent range change in the satellite Line-Of-Sight (LOS) between two SAR acquisitions is, after corrections from orbital configurations and topography, the combination of atmospheric phase delay and ground deformation. Rapid, large-amplitude deformation signals such as coseismic displacement fields often exceed the amplitude of other known sources of noise\cite{Simons2002}. Similarly, slow but steady accumulation of deformation over long periods of time may be quantified using InSAR either through stacking, e.g. \cite{Peltzer2001}, or time series analysis\cite{Jolivet2012,Weiss:2020aa}. However, detecting low-amplitude deformation related to transient sources such as slow slip events, episodes of volcanic activity or hydrologic related motion remains challenging and requires significant human intervention and interpretation \cite{Chaussard2014,Rousset2016,Khoshmanesh2018}. Measuring Earth surface deformation is fundamental to characterizing diverse tectonic processes and the impact, as well as surface and undergound changes induced by human activities.

The most pressing issue in InSAR processing for small, mm-scale, deformation monitoring remains the separation between atmospheric propagation delays and ground deformation. Spatial and temporal variations in atmospheric pressure, temperature and relative humidity modify the refraction index of the air, resulting in spatial and temporal delay variations in the two way travel time of the radar carrier between a SAR imaging satellite and the ground \cite{Hanssen2001,Doin2009a}. Such delays directly affect the phase of an interferogram, that combines two SAR acquisitions. Atmospheric propagation delays in a single interferogram can be equivalent to tens of centimeters in apparent range change \cite{Hanssen2001}. Current correction methods based either on empirical estimations, e.g. \cite{Elliott2008,Cavalie2008} or on independent data, e.g. \cite{Li:2006ia,Jolivet2011,Yu2018,Shen:2019aa} reduce the contribution of the stratified atmosphere -- the long wavelength atmospheric perturbation that, to first order, correlates with topography. Nonetheless, remaining delays, corresponding to the turbulent portion of the troposphere may represent centimeters of apparent range change. Propagation delays in the atmosphere decorrelate after periods of 6 to 24 hours, as shown by the temporal structure function of GNSS zenith delays \cite{Emardson2003}. Therefore, remaining tropospheric delays, which are coherent in space, can be considered random in time given the time span between SAR acquisitions (e.g. 6 days for Sentinel 1, 46 days for ALOS-2). However, it can be shown that, because of potential temporal aliasing \cite{Doin2009a} and loss of spatial coherence of the radar phase echo, spatio-temporal filtering can lead to biased results. Therefore, deciphering a consistent, days- to month-long transient signal in time series of InSAR remains a critical challenge, especially when automation is envisioned.

Here we describe a deep learning-based method to automatically detect and extract transient ground deformation signals from noisy InSAR time series. Our approach, based on a purely convolutional auto-encoder, is specifically designed for removing noise in InSAR time series. In the following, we consider the evolution of the interferometric phase with time with respect to a reference both in space and time. We consider classical Small Baseline (SBAS)-like approaches for the reconstruction of the time series e.g.\cite{Berardino2002,Dalaison:2020aa}. Approaches include inversion from a sequence of SAR interferograms previously corrected from orbital and topographic contributions \cite{Simons2007}, with a first-order atmospheric correction derived from global atmospheric re-analysis products \cite{Jolivet2011,Jolivet2014}.

Convolutional neural networks (CNN) are central to most recent dramatic advances in computer vision and natural language processing. Auto-encoders have been developed to create sparse representations of data --the model copies its input to its output through a bottleneck that forces a reduction of dimension equivalent to a compressed knowledge representation of the original input, enabling noise removal. Of note are recent developments applied to classify InSAR data in order to detect ground uplift and subsidence, and specifically to identify volcanic unrest \cite{Schwegmann2017,Anantrasirichai2018,Anantrasirichai:2020aa}. Although promising, these developments do not make use of the different temporal signatures of signals of interest to reconstruct de-noised deformation patterns. Our auto-encoder takes as input a noisy InSAR time series reconstructed from successive SAR acquisitions, and outputs accumulated ground deformation taking place during the time series interval, with the atmospheric noise removed.

In the following, we first introduce the notion of auto-encoders before describing the architecture of our neural network. We then describe our training set and perform preliminary tests on synthetic data. We finally highlight the efficiency of our algorithm on two reconstructed time series of ground deformation, the first one derived from COSMO-SkyMed acquisitions and the second one derived from Sentinel 1A-B SAR acquisitions.

\section{Results}

\subsection{Description and Validation of the deep auto-encoder}

\subsubsection*{Auto-encoder architecture}

Our goal is to extract ground deformation from noisy InSAR time series. We assume that input time series are the combination of three physical contributions: ground deformation, the stratified component of the atmosphere and the turbulent component of the atmosphere. In most cases, the stratified component can be corrected for using Global Atmospheric Models (hereafter referred to as GAMs, often corresponding to re-analysis products), e.g. \cite{Jolivet2014}, or Global Navigation Satellite System (GNSS) data, e.g. \cite{Onn2006}, for instance. However, such a correction is often incomplete and part of the remaining, often turbulent, atmospheric delays may still correlate with topography. Attempts have been made to estimate tropospheric delays using multi-spectral radiometric data \cite{Li:2006ia}; however, the acquisition of such independent data must be coincident with the SAR acquisition and over a terrain with minimal cloud cover for optimal performance, conditions rarely met. In addition, it can be shown that GAMs-derived correction sometimes worsen the situation as the local estimate of the state of atmospheric variables may be incorrect \cite{Jolivet2014}.

\begin{figure*}[!ht]
    \begin{center}
        \includegraphics[width=0.9\linewidth,trim= 0 0 0 0]{Fig1_v2.png}
        \caption{\footnotesize{\textbf{Auto-encoding InSAR time series.} Schematic of our deep learning model. Top row (left to right): a sequence of synthetic InSAR time series on which the model is trained, where ground deformation signal is corrupted with atmospheric noise, including turbulence and layering of the atmosphere. Second to fourth rows: architecture of our model. Our model is purely convolutional with progressive pooling on the time dimension during the encoding. After time is removed, at the 7th layer, ground elevation is added as a secondary input. Fourth row: The last layers of the model are tasked with decoding ground deformation accumulated during the input time series, here compared with actual deformation that takes place in the synthetic time series shown above. A  detailed description of this neural network can be found in the methods section.}}
        \label{fig1}
    \end{center}
\end{figure*}

Our deep learning model must recognize transient deformation in InSAR time series in the presence of remaining atmospheric noise. To this end, it must distinguish the spatial and temporal statistical differences between deformation signals and atmospheric patterns. As mentioned above, the structure of atmospheric delays decorrelates for periods longer than 6 hours\cite{Emardson2003}. Therefore, as ground deformation related to transient tectonic events might take place over seconds to minutes for dynamic rupture, to weeks or months or even years for slow slip events \cite{Jolivet2013,Rousset2016,Khoshmanesh2018,Materna:2019kk}, and remains until further ground deformation occurs, the temporal signature is very different from that of atmospheric delays. We make use of this different temporal signature to learn appropriate filters to remove atmospheric perturbations and extract ground deformation in InSAR time series.

Here, we build and train an auto-encoding architecture to directly output the deformation signal, formulating the problem as a regression task. We rely on the following assumptions: (1) atmospheric delays are random in time, considering two successive SAR acquisitions, (2) ground deformation has a temporal coherence considering the rate at which SAR images are acquired and (3) part of the atmospheric delay correlates with topography. We therefore use as inputs a time series of interferometric phase change and a map of ground elevation to produce a time series of cumulative surface displacements.

In order to separate deformation from atmospheric delays, we developed the deep learning architecture shown in Fig. 1. This architecture consists of 11 purely convolutional layers. The first 6 layers of the model are tasked with encoding signals that are persistent in time, by progressively removing the time dimension of the input. The remaining layers decode the ground deformation map. In short, we build a model tasked with reconstructing ground deformation given input InSAR time series and ground elevation from noisy input.

Initially developed for feature extraction by projecting high-dimensional datasets onto a lower-dimension manifold by forcing the reconstruction of the data through a bottleneck in deep learning architectures \cite{Vincent2008}, auto-encoders have also evolved into powerful denoising \cite{Feng2014,Zhang2017} and image enhancing techniques \cite{Cui2014,Mao2016}. In this work we exploit this aspect of deep learning auto-encoding and tailor it to the problem of cleaning InSAR time series, building a deep learning auto-encoder to effectively automate the design of filters in time and space to recover ground deformation.

\subsubsection*{Training on synthetic data}

Because deep learning models require large amounts of data and there exists no ground truth for InSAR time series, we rely on synthetic data to train the deep auto-encoder. The synthetic data are randomly-generated cumulative surface deformation time series mimicking 9 successive `acquisitions'. These cumulative deformation maps include surface displacements in the line of sight (LOS) due either to a slipping fault with random latitude and longitude (position in a virtual box), depth, strike angle, dip angle and width (based on Okada's model \cite{Okada1992}) or to an inflating or deflating point source (Mogi's model \cite{Mogi1958}). Deformation onset occurs at a random time with a random duration within the time series, excluding the first and last acquisitions which are taken as non-deforming reference by the model. The model is therefore tasked with finding cumulative deformation in the 7 middle acquisitions of the time series arising from a wide variety of transient processes. We then corrupt each map of these ground deformation time series with different noise signals. At each time step we create both turbulent and stratified synthetic atmospheric delays. Spatially correlated Gaussian noise mimics delays from atmospheric turbulence of various length scales \cite{lohman2005,Sudhaus:2009jw} (Fig. 1 top row) and a quadratic function of pixels' elevation mimics the atmospheric delays that correlate with topography \cite{Hanssen2001,Bekaert:2015eta}. Each of the steps of the time series results from a random realization of noise built following these assumptions.

We train two independent models with the synthetic time series of deformation, one tasked with recovering point source deformation, the other with recovering deformation on faults. All other phase delays are identified as noise. Both models are trained to map synthetic noisy time series to the synthetic cumulative displacements.  We trained our deep auto-encoder with $2.5 \times 10^7$ randomly generated time series for which we provide as input the apparent line of sight (LOS) deformation time series, corrupted by the sum of synthetic noise described above. The training includes a LOS with random orientation (30-45 degrees incidence and any azimuth), so that the model is directly trained for various SAR satellite configurations and for any fault azimuth. The output is the target ground deformation accumulated during the time series. All 482,185 trainable parameters are adjusted during that training phase with the Adam variation of stochastic gradient descent \cite{Kingma2014}.

We note that our deep auto-encoder only considers time series of 9 acquisitions, as a good compromise between the tractability of the training phase (the time series are long enough for the model to learn the temporal differences between signal and noise) and a minimum duration of the analysed time series of displacements. When working with longer time series of $n$ acquisitions, we apply the algorithm using a sliding window with a width of 9 time steps and obtain $n-8$ images of cumulative deformation. In this way, our model acts as a moving integral of actual deformation.

\subsubsection*{Performance on synthetic data set}

Once trained, we test the deep auto-encoder on synthetic realizations of time series that have not been used to train the model. We randomly generate 3200 time series of 9 time frames using the same procedure as that described for the training phase. For each of the 3200 time series, we evaluate the signal-to-noise ratio (hereafter referred to as SNR) as the ratio of the mean absolute ground deformation and the standard deviation of the noise. We then apply the deep auto-encoder to these time series in order to evaluate the performance of the model. We evaluate the resulting, cleaned time series using the coefficient of determination R$^2$, a standard regression metric, equal to 1 for a perfect reconstruction, 0 for a reconstruction no better than the empirical average, and negative for the worst reconstructions (for example reconstructions anti-correlated with the ground truth).

\begin{figure*}[!ht]
    \begin{center}
        \includegraphics[width=\linewidth,trim= 0 0 0 0]{Fig2_v4.pdf}
        \caption{\footnotesize{\textbf{Performance on synthetic test data.} Left: Performance of the reconstruction of fault deformation by our deep auto-encoder, on synthetic noisy time series, as measured by the coefficient of determination R$^2$ (a metric of goodness of fit that compares model error with the error of predicting the empirical average) as a function of signal to noise ratio (SNR, see Methods). Each point represents the average over 64 synthetic time series with the same SNR. Right: examples of the data (last frame of the input), the ground truth and its reconstruction, for different signal to noise ratios. Note that the model outperforms the eye, recovering with reasonable fidelity (R$^2>0.6$) deformation signals with SNRs below 0.1.}}
        \label{fig2}
    \end{center}
\end{figure*}

We find that the deep auto-encoder applied to synthetic data accurately reconstructs deformation signals on faults, even in circumstances very challenging to expert interpretation (SNRs lower than 1; Fig. 2). For SNRs above 0.1, our algorithm provides a very accurate reconstruction ($0.6<$R$^2 <1.0$) of the cumulative ground deformation. For very low SNRs (0.1 and below), no signal can be visually observed, while the goodness of fit is still correct and the overall deformation signal is recovered down to SNRs of approximately 0.02, below which our model fails. Therefore, our architecture allows us to exceed the ability of the expert eye to detect signals in noisy time series of deformation, provided their noise structure resembles the training set.

In the following we show the application of our auto-encoder to two case studies that have been independently analyzed by InSAR experts.

\subsection{Application to real data}

\subsubsection*{Extracting deformation from a slow earthquake along the North Anatolian Fault, Turkey}

Our deep auto-encoder is trained to isolate and reconstruct cumulative ground deformation signals in 40x40 pixel time series of 9 acquisitions. However, a fundamental property of purely convolutional deep learning models is that the filters they learn do not depend on input size. As a result, we can create an auto-encoder with exactly the same architecture as the model described in Fig. 1, but with an input size matching the number of pixels in the InSAR time series of interest. Because the parameters of the model do not depend on input size, we can copy every parameter (i.e. weights and biases of the filters) of the model trained on synthetics to the new model, which can then be applied to InSAR data of any size.

Here, we apply the model to a time series built from images acquired by the COSMO-SkyMed constellation over the central section of the North Anatolian fault in Turkey (Fig. \ref{fig3}). This major plate boundary fault accommodates the motion of rotation of the Anatolia plate with respect to Eurasia and has ruptured in large, Mw 7 earthquakes multiple times over the last century \cite{Stein:1997du}. An 80-km-long section of the fault has been slipping aseismically, at least since the 1944, Mw 7.3, earthquake located near the small town of Ismetpasa \cite{Ambraseys1970}. {\it In situ} measurements based on creepmeters indicate that this fault experiences transient aseismic slip episodes \cite{Altay:1991wb,Bilham2016,Cetin:2014hp}.

Rousset et al. produced an approximately one year long time series from COSMO-SkyMed SAR acquisitions and detected a significant slow slip episode that lasted one month during 2013 with a maximum of 2 cm of fault-parallel slip \cite{Rousset2016}. Average long-term velocity maps covering the whole region derived from InSAR data show aseismic slip over an 80-km-long section of the fault. This average relative displacement was found to result from successive transient events \cite{Rousset2016,Bilham2016}, which were not apparent in data from older constellations of SAR satellites due to the long time span between acquisitions.

In the InSAR time series processed by Rousset et al., large atmospheric delays are apparent, despite careful correction of atmospheric delays using ECMWF re-analysis products \cite{Jolivet2011,Rousset2016}. Therefore, knowledge of the fault location was key in the interpretation of the surface displacement field.

Here we revisit the same time series in order to assess if our model is able to recover the known surface slip in real time series of data. We stress that we do not provide the location of the fault to the model.

With no human intervention and no \textit{a priori} knowledge of the local tectonics and fault location, the model automatically isolates and recovers clean deformation signals where expert analysis previously found signal attributed to tectonic activity (Fig. \ref{fig3}). Importantly, the recovered deformation is obtained after training only on synthetic data and with no further fine tuning on real data.  Our model finds up to 1.5 cm line of sight relative displacement across the fault, that we interpret as the signature of surface slip, as previously found \cite{Rousset2016}.

\begin{figure*}[!hb]
\vspace{-1cm}
\begin{center}
        \includegraphics[width=0.9\linewidth]{Fig3_v5_lowres.png}

        \caption{\footnotesize{\textbf{Application to real data: the North Anatolian Fault 2013 slow earthquake.} In order to identify ground deformation signals in the noisy COSMO-SkyMed InSAR time series, we create a deep auto-encoder that has an input size equal to the size of the acquisitions, 200x650 pixels, and the same parameters as the auto-encoder trained on synthetic data, shown in Fig. 1. Inputs are the InSAR time series. The auto-encoder outputs ground deformation (bottom plot). The ground deformation is manifest as an offset across the fault. The deep auto-encoder finds a strong slip signal of about 1 cm (in LOS) on the fault, in agreement with previous expert analysis of the time series \cite{Rousset2016}, with no \textit{a priori} knowledge of the fault's existence. {\bf a.} Seismic setting of the region of the creeping section of the North Anatolian Fault. Thick red lines are the main faults of the NAF system, separating the Eurasia plate from the Anatolia microplate. Thin red lines are other mapped structures. Colored lines indicate the extent of historical ruptures. {\bf b.} Input raw time series from COSMO-SkyMed data (subset of the data from Rousset et al. 2016). Color is the apparent range change between the ground and the satellite. {\bf c.} Denoised cumulative deformation as output by the deep-autoencoder. The color scale shows ground deformation in the direction of the LOS. Dark lines are the surface trace of the NAF, shown here for reference. Thin dashed lines indicate the cross-sections shown in figure \ref{fig4}.}}
        \label{fig3}
    \end{center}
\end{figure*}

\FloatBarrier
\begin{figure*}[!ht]
    \begin{center}
        \includegraphics[width=0.9\linewidth]{Fig4_v2.pdf}
        \caption{\footnotesize{\textbf{Application to real data: the North Anatolian Fault 2013 slow earthquake.} LOS deformation along fault-perpendicular cross sections. Location of the cross-sections are shown in Fig. \ref{fig3}. Black dots are the difference between phases averaged over acquisitions between September 5th and 21st, 2013 and over acquisitions between August 4th and 28th, 2013, taken along a fault perpendicular line. The main slow slip event detected by Rousset et al. occurred during this period. Red dots are the output of the model highlighting the cleaned deformation pattern. The sharp offset in the input InSAR data observed exactly on the fault was interpreted as a slow slip event by Rousset et al., in spite of the very high noise level presumably caused by atmospheric delays. Such interpretation was only made possible owing to knowledge of the location of the fault and knowledge that this segment of the North Anatolian Fault slips aseismically. Our model knows neither and automatically extracts actual ground deformation. Our current model interprets wavelengths longer than a kilometer as noise, although experts might interpret those as the signature of slip at depth.}}
        \label{fig4}
    \end{center}
\end{figure*}
\FloatBarrier

Fault perpendicular cross sections illustrate that even in regions where slip would not have been convincingly identified by an expert (Fig. \ref{fig4}), our model recovers 2 mm of slip, extending the previous estimate of along-strike length of this slip event. Rousset et al. identified a 10-km-long slow slip event while the deep learning model determines that the portion that slipped was 15-20 km in length. Interestingly, the new 2 mm slow slip we find is on a segment adjacent to the previously identified 1 cm slow slip, and the two segments are separated by a kink on the fault, suggesting an interplay between fault geometry and slip \cite{Jolivet2015,Romanet2020}.

\subsubsection*{Extracting ground deformation signal at the Coso geothermal system, California}

In a second example, we use our deep learning architecture to detect surface deformation caused by underground pressure changes. As above, our model is trained on several million examples of synthetic noisy InSAR time series. In this case, surface deformation is modeled by a point pressure source using Mogi's equation of elastic deformation\cite{Mogi:1958wk}, corrupted as before by synthetic atmospheric delays. Mogi pressure sources are used extensively for the modeling of volcanic inflation and deflation signals, e.g. \cite{Segall:2010,Grandin:2010gl}. Further, the combination of multiple sources allows one to model complex subsidence/uplift patterns.

After training exclusively on synthetic data, we apply our model to real data from the Coso geothermal field (California, USA), again without further training (details on the InSAR processing are in the Methods section). Because InSAR time series may be very noisy, even after correcting predicted atmospheric effects \cite{Jolivet2014}, analysis of inflation or subsidence of less than a few centimeters per year in InSAR have relied to date on deriving long term cumulative deformation \cite{Hoyt:2020aa}, such that random atmospheric delays cancel out. Detecting transient subsidence and uplift signals in SBAS time series below a few centimeter remains challenging, just as it does for faulting.

As with identifying deformation on faults, our model is able to disentangle actual ground deformation from atmospheric noise at short time scales, with a resolution of a few millimeters. In Fig. \ref{fig5} we show the application of our deep denoising model to a time series over Coso in 2016. Contrary to what could be inferred from long term cumulative deformation, we find that ground subsidence at Coso is primarily due to transient episodes of deformation.  The cumulative deformation from these transients we detect account for most of the cumulative deformation observed in the data (see Supplementary for details and for other examples of transient deformation). Interestingly, we find a number of transient events that are constituted of well separated pressure sources, in agreement with geochemical observations showing that the geothermal field is constituted of isolated reservoirs\cite{adams2000geologic}.

\begin{figure*}[!ht]
    \vspace{-2.5cm}
    \begin{center}
        \thispagestyle{empty}
        \includegraphics[width=0.8\linewidth]{Fig5_v2_lowres.png}

        \caption{\footnotesize{\textbf{Application to real data: the Coso Geothermal Field in California.} After training our deep auto-encoder architecture exclusively on synthetic InSAR time series of point sources of deformation corrupted with atmospheric noise, we apply it to the time series obtained from Sentinel 1A-B from 2016-04-14 to 2016-11-16, that spans the Coso Geothermal Field in California. Our model detects a transient episode of subsidence of 5 to 7 mm (in line of sight), where the operational wells are located, with no \textit{a priori} knowledge of the area. {\bf a.} Geographic setting with the coverage of the subset of the Sentinel 1 track used here. Red and blue dots indicate the geothermal wells, respectively for injection and production. Background color is the terrain rendering from Stamen ({http://maps.stamen.com}). {\bf b.} Input raw time series of 9 successive images from Sentinel 1 data. Color is the apparent range change between the satellite and the ground along the LOS. {\bf c.} Denoised cumulative deformation as output by our deep auto-encoder. Color is ground deformation in the LOS. The thin dashed line indicates the location of the cross section shown in the Supplementary.}}
        \label{fig5}
    \end{center}
\end{figure*}

\FloatBarrier

\section{Discussion}

As the properties of the atmosphere cannot be measured at the same spatial and temporal resolution as InSAR acquisitions, InSAR time series still contain large amplitude atmospheric delays, on the order of centimeters, in spite of recent marked improvements in atmospheric correction and processing strategies \cite{Jolivet2014,Shen:2019aa}. For this reason, expert processing and analysis is required to interpret InSAR data. Furthermore, since the onset of the Sentinel 1 mission, the amount of available InSAR data has grown at a pace that is already challenging the ability of the community to process and analyze it, and the upcoming NISAR mission will increase the amount of available InSAR data several fold. Therefore, significant effort has been put into developing strategies to build time series with such vast data sets, e.g. \cite{Weiss:2020aa,Flatsim,Dalaison:2020aa}. Nonetheless automatic, autonomous InSAR interpretation methods are poised to become essential, if just to leverage the increasing spatial and temporal resolution of the data.

We note that several avenues of improvement should improve the ability of our neural network to detect finer and finer deformation signals in the future. First, we did not include sources of noise representative of ionospheric perturbations. The total electronic content of the ionosphere introduces a differential delay in interferograms that can bias analysis further \cite{Hanssen2001}. Although this effect is more pronounced for L-band SAR satellites \cite{Hanssen2001,Shen:2009ds}, long-wavelength ionosphere delays can be problematic for large images acquired with C-band SAR systems such as Sentinel 1 \cite{Liang:2019hv}. Although these delays can be corrected for using techniques such as the range split-spectrum method \cite{Fattahi:2017fp,Liang:2019hv}, the structure of the remaining noise associated with imperfect corrections must still be evaluated and could then be used in the training of our model. Second, we considered atmospheric turbulence to be isotropic and equivalent everywhere in the image (i.e. noise is second-order stationary) while some anisotropy can be observed in the phase delay of some interferograms. However, such anisotropy depends on the scale of the image observed, which would involve complex considerations in the construction of an adequate tropospheric noise model to train our model. In general, any improvement in the forward modeling of the nature of noise in InSAR should lead to a significant improvement in the detection capability of the models.

Finally, the receptive field of the autoencoder and the pixel size of the input InSAR data restrict the size of the deformation signal that can be deciphered. For instance, interseismic deformation related to loading of a fault by plate motion extends over 10s of kilometers, e.g. \cite{Peltzer2001,fialko2006,Jolivet2012}. Additional developments may be necessary for the detection and cleaning of long wavelength deformation patterns.

The initial application of our method on InSAR time series enables the direct observation of a slow earthquake, refining previous estimates, autonomously and without prior knowledge. In particular, we expect that the ability to systematically observe fault and pressure source deformation at a global scale will further the understanding of hydrologic, volcanic and tectonic processes, and may bring us closer to bridging the observational that exists for transient surface deformation.

\bibliographystyle{naturemag}
\newpage

redpajama_set_name: RedPajamaArXiv


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text:
Caledonian Crushers put Digby Brown to the test
Digby Brown are proud supporters and sponsors of the Caledonian Crushers, Scotland's only wheelchair rugby club.
This inspirational club began in 2011 with the goal to get more people in Scotland involved with wheelchair rugby. The club made their debut in the British Wheelchair Rugby League in 2012/13 and have gone from strength to strength ever since.
Earlier this week, members of Digby Brown joined Caledonian Crushers at their training session at Tollcross International Swimming Centre. Our staff were definitely put through their paces, as the video clearly shows below.
This was combined with a cheque presentation for £2,500 to mark our continued sponsoring and support for the Caledonian Crushers. We very much look forward to cheering the team throughout the upcoming year.
Paul Black, Head Coach at Caledonian Crushers, said: "The players and support staff at the Caledonian Crushers are really appreciative of the continuing support from Digby Brown to allow us to run our club which enhances the wellbeing of individuals with life changing illnesses and disabilities.
"We will use the funds to enable our weekly training sessions to be held at Tollcross Sports Centre each week. We will also use it to cover accommodation costs when we travel to tournaments as we are the only wheelchair rugby team in Scotland we need to travel to England to take part in the British league."
Kirsten Smith, Corporate Social Responsibility Manager at Digby Brown, said: "The Caledonian Crushers are an inspirational group of athletes who put us through our paces and introduced us to a sport that is hard work but more importantly a lot of fun.
"It is a real pleasure to continue our support for the Caledonian Crushers Wheelchair Rugby Team and see the camaraderie they offer wheelchair users seeking a bit of an adrenaline rush."

redpajama_set_name: RedPajamaCommonCrawl


text:
search filter All ContentAll JournalsOctober
October at JSTOR
Writings and correspondence: 1961-1985
Hubert Damisch,
Hubert Damisch
HUBERT DAMISCH, a philosopher and art historian, is a former head of studies at the École des hautes études en sciences sociales in Paris. Among his books are The Origin of Perspective (MIT Press, 1994), Skyline: The Narcissistic City (Stanford, 2001), and A Theory of /Cloud/: Towards a History of Painting (Stanford, 2002).
Online Issn: 1536-013X
© 2015 October Magazine, Ltd. and Massachusetts Institute of Technology
October (2015) (154): 8–68.
https://doi.org/10.1162/OCTO_a_00236
Hubert Damisch, Jean Dubuffet; Writings and correspondence: 1961-1985. October 2015; (154): 8–68. doi: https://doi.org/10.1162/OCTO_a_00236
This dossier comprises a selection of the correspondence between Hubert Damisch and Jean Dubuffet as well as six essays written by Damisch on Dubuffet between 1962 and 1985. Both the correspondence and texts are here published in English for the first time. "Jean Dubuffet and the Awakening of Images" (1962), Damisch's second article on Dubuffet, discusses the relationship between material object and idea, or painting and image, in Dubuffet's art since the 1940s. "Work, Art, Artwork" (1962) examines Dubuffet's return to figuration following his abstract works of the late 1950s. "Paris Circus" (1962) is an extended review of the recently completed series Paris Circus, and "Second Method" (1964) investigates Dubuffet's cycle of the Hourloupe in the light of questions of perception present in Maurice Merleau-Ponty's The Eye and The Mind. "DUBUFFET (Jean)" (1969) was written as an entry of the Encyclopedia Universalis. The final essay, "Starting Ground" (1985), was written at the time of the artist's death. It evokes, among other themes, contemporaneity and posterity and Dubuffet's complicated embrace of an artistic career. This essay lays the ground for subsequent texts by Damisch on Dubuffet. The correspondence, which is interspersed amidst the writings, is complete save for a few technical letters concerning the editing of Dubuffet's writings by Damisch in 1967. Damisch himself defines it as "work correspondence." In these letters, artist and writer debate specific terms, discuss the artist's work and the writer's essays, and provide a glimpse of their complex personal relations.
Order/Subscribe
Nothing Is Erased: Hubert Damisch and Jean Dubuffet
October (October,2015)
Dubuffet avec Damisch
Paint Boldly! : Dubuffet's DIY Manual
Jean Dubuffet: The Butterfly Man
October (January,2007)
Make It Clear: Speak and Write to Persuade and Inform
Correspondence Theories
The Nature of Truth: Classic and Contemporary Perspectives
Technical Writing Practices
Everyday Engineering: An Ethnography of Design and Innovation
Morton Salt Disaster
On Institutional Democratization and Reflexive Resistance: A Conversation with Andrea Fraser
Art Communities at Risk: An Introduction
Art Work as Life Work: Lu Märten's Feminist "Objectivity"
Lubitsch, Shakespeare, and the Theatricality of Power
Online ISSN 1536-013X


Albany Entertainment Centre is inviting locals to participate in our Reclaimed Pianos Survey.
We are inviting you to share stories about your connections to music and pianos, listening, learning and playing. Music can play a significant role throughout different periods of our lives, music can cross generational boundaries, foster personal growth and unite community. The power of music to trigger happy, sad and funny memories can be palpable.
Albany Entertainment Centre and Circa are working together with your community to create a new work called Reclaimed Pianos. Circa has been at the frontier of new circus – creating powerful works of circus art that challenge, thrill and delight. At the centre of Circa is the art, they push the boundary of the circus artform and blur the lines between movement, dance, theatre and circus.
Your stories and responses will be shared with Circa as they create their new work, which will tour in October / November 2018.
The information you provide may or may not be used for the creative development of the show.
There is NO need to answer every question, any contribution or comments will be appreciated. We look forward to reading and sharing your responses.
Please complete your survey by 30th July.


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text:
Q: How to receive INSTALL_SHORTCUT broadcast on Android I try to receive an event everytime a new shortcut on the Homescreen/Luncher was created. After my app receive the event I like to modify the shortcut. My current configuration is listed below, but I never receive an event.
<uses-permission android:name="com.android.launcher.permission.INSTALL_SHORTCUT" />
<uses-permission android:name="com.android.launcher.permission.UNINSTALL_SHORTCUT" />
<application>
  <receiver
     android:name=".InstallShortcutReceiver"
     android:permission="com.android.launcher.permission.INSTALL_SHORTCUT">
    <intent-filter>
      <action android:name="com.android.launcher.action.INSTALL_SHORTCUT" />
    </intent-filter>
  </receiver>
</application>

Is my idea possible ?
Best Regards,
André

A: What happens if you remove the permission line from the receiver? The permission you specify in a receiver like that is the permission necessary to call it, not for it to receive broadcasts.

A: I found it. When I shortcut is created using drap and drop from the menu no INSTALL_SHORTCUT event is published.

redpajama_set_name: RedPajamaStackExchange


text:
THE YOUTH VOTE UK
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Political Empowerment
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The Cambridgeshire and Peterborough Mayoral Election: A Breakdown
The election for the mayor of Cambridgeshire and Peterborough is set to take place on the 6th of May 2021. This will be only the second election of its kind after 2017. It will elect the mayor for the Combined Authority of Cambridgeshire and Peterborough.
Mayor of Cambridgeshire and Peterborough
The Cities and Local Government Devolution Act 2016 led to the creation of 'Metro mayors' who would lead combined authorities. Cambridgeshire and Peterborough became one of these combined authorities. As part of the devolution deal the mayor of Cambridgeshire and Peterborough has the following responsibilities:
£600 million budget for local economic growth
£170 million budget for housing, including affordable and council housing, with £70 million of that specifically for Cambridge
Provision of skills (training and apprenticeships)
Integration of local health and social care resources
Integration of local employment services, and design of a National Work and Health Programme alongside the Department for Work and Pensions (DWP)
Figure 1: Current mayor of Cambridgeshire and Peterborough, James Palmer, Conservative
Elections for mayors of combined authorities use the Supplementary Vote system (SV). This system produces a single winner. Voters are given a first and second preference choice; if one candidate receives over 50% of the first preference votes, then they are declared the winner. However, if no candidate gets over this threshold then all but the top two candidates are eliminated, and the second preference votes are counted. The second preference votes for the top two candidates are added to their respective scores and whoever receives the most votes after this is elected to the position.
Last Election
The First election for the mayor of Cambridgeshire and Peterborough took place in 2017. The Conservative candidate, James Palmer, won in the second round beating the Liberal Democrat candidate, Rod Cantrill, to become the first Metro Mayor of Cambridgeshire & Peterborough. Although Rod Cantrill got nearly 8,000 more second preference votes than Palmer, the Conservative candidate was still able to win by 21,621 votes.
Figure 2: Mayor of Cambridgeshire & Peterborough Election Results, BBC
James Palmer (Conservative Party) the current mayor of Cambridgeshire and Peterborough is running for re-election. He is running on the following policies:
100k Homes Initiative
Provide affordable homes for first time buyers
Each home is covenanted so that they cannot be bought to let or be sold on at market value for profit
Fund the completion of the new university ARU Peterborough
Develop Cambridge Autonomous Metro (CAM)
Aidan Van Der Weyer (Liberal Democrats) plans to transform the area with the following policies:
Create a green transport option that offers a realistic alternative to the car
Build affordable homes
Help renters get stable long-term tenancies
Get more young people into good training
Improve access to post-16 education
Nik Johnson (Labour Party) is a current district councillor in Huntingdonshire and is running on the following platform:
Build a Northern Cambridgeshire Powerhouse by harnesses the unique qualities of the area
Develop better transport links so the county is better connected
Improve public health by delivering:
High quality housing
Integrated transport systems promoting freedom without pollution
Promote work, education and skills opportunities in a digital era for all
Participation is typically low in these kinds of local elections, however, we at The Youth Vote want to change that. We would like to encourage young people in the Cambridgeshire and Peterborough area to engage with politics and to participate in this upcoming mayoral election on the 6th of May 2021. Local politics has a direct impact on young people's lives so if you want to have your voice heard then register to vote and vote at the next election.
Register to vote here: https://www.gov.uk/register-to-vote
Jonas Volkwein, Head of Policy and News
2021 G7: Northern Ireland takes centre stage amid talks on hard borders and sausages
The Group of Seven, or G7, is an informal, exclusive club of wealthy democratic nations. As an inter-governmental organisation, it meets annually to discuss and offer solutions to global issues. This
Queen's Speech 2021: Higher Education (Freedom of Speech) Bill
The Queen's Speech sets out what legislative plans the government want to pursue over the next parliamentary year. This year, it was announced the government would introduce a Higher Education (Freedo
Queen Speech 2021: Electoral Integrity Bill
The Queen's Speech sets out what legislative plans the government want to pursue over the next parliamentary year. Electoral Integrity Bill The Electoral Integrity Bill, as it is provisionally known,
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The Careers Group includes over 200 careers and employability professionals and employability consultants working across its member services. The majority of staff are based within the member institutions, providing expertise and experience to support undergraduates and postgraduates, research staff and recent graduates; liaising with graduate recruiters from all sectors; and working with academic and other staff to embed employability learning within the student experience.
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Q: How to extract the Euler rotation angles used to transform a point? If you rotate an input point located on the Y axis around the X axis, and then around the Z axis, you get a new point at a new location.
However, how do you do the opposite? I.e. start with the new point and determine the two rotation angles needed to arrive at the original input point located on the Y axis?
Also, is there a general method that can be used for rotations starting on and rotated around other axes?


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nXu Education
Interested applicants should apply at the website below.
Website: https://boards.greenhouse.io/togethereducation
Position: Recruiting Coordinator
Location: Virtual
Type: Part-Time Consultant (~8 hours/week)
OVERVIEW OF NXU
nXu (https://www.nxueducation.org/) is a national non-profit organization whose mission is to catalyze and equip youth and adults to explore, articulate, and pursue their purpose by leveraging social capital. Overseen by nationally recognized educators including the co-founders of Transcend Education, nXu has developed a research & evidence-based purpose development methodology, curriculum, and program model that can be deployed in-person, online, and on a blended basis. We offer a training program as well as a purpose development curriculum to schools, and they also directly implement programming both online and in person with students both in school and out of school.
OVERVIEW OF ROLE
We're looking for a Recruiting Coordinator to support the growth of our team. This individual will support nXu by screening, interviewing, and recommending candidates. The person will also work closely with the nXu team to refine existing application systems and processes to ensure diversity and equity. This is a fast-paced, part-time and virtual role that will report to nXu's team.
Areas of Responsibility:
Posting Job Openings: Design and execute strategies for engaging mission-aligned candidates through various channels. Post and manage nXu job openings with an eye to generating a diverse pool of candidates.
Select and Screen Candidates: Manage the Applicant Tracking System (ATS) through Greenhouse. Identify candidates to screen and conduct initial interviews. Support candidates through our talent pipeline while maintaining our commitment to inclusive hiring practices.
Recommend Candidates: Based on screen conversations, recommend candidates to the nXu team for further consideration.
Additional Support: Support the nXu team in additional areas of the recruiting process as needed.
Skills/Experience:
Candidates for this position must possess the following qualifications:
Belief in nXu's mission and a passion for helping people explore, articulate and pursue their purpose in life.
Excellent interpersonal and relationship-building skills.
Strong written and verbal communication skills combined with a passion for meeting and engaging with people across lines of difference.
Commitment to approaching the recruitment process through a lens of diversity, equity, and inclusion.
Some flexibility in schedule for conducting screens with candidates.
Ability to receive and implement feedback.
Comfort in working with a remote team, often independently.
At least two years of experience in working in a recruiting function, ideally in the education industry.
Current authorization to work in the United States secured by the first day of employment.
Compensation/Benefits:
nXu offers competitive compensation for this consulting role.
nXu provides equal employment opportunity for all applicants and employees.
nxueducation.org
Youth / Children
nXu is a non-profit organization whose mission is to catalyze and equip youth and adults to explore, articulate, and pursue their purpose.
Our Methodology: We have developed a research & evidence-based, 4-phase, purpose development methodology called "The Compass" that serves as our learning standards.
Our Products & Services: We offer a training program as well as our purpose development curriculum to schools, and we also directly implement programming with students both in school and out of school.
Our Target: Through our products and services, we have served high school students from over 50 district, charter, and private schools across the country. We are seeking to partner with additional schools and organizations that are interested in fostering a sense of purpose among their students.
Why Work For Us?:
A sense of purpose acts as an inner compass that—when combined with skills training and community support—allows young people to live in alignment with their highest potential. Thus, we have developed a research & evidence-based purpose development methodology and curriculum that we have implemented in-school and out-of-school with high school students in Chicago, Newark, New York, San Antonio and Seattle. Through this direct programming, we have cultivated a deep understanding of the implementation needs of our purpose development program. Leveraging these insights, we are establishing a teacher training program and school-based curriculum that will allow a growing number of high schools to cultivate a sense of purpose in the lives of their students.
Read more about nXu Education
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The Boy Who Lived...
My Harry Potter imitation. Yeah, I'm the "boy who lived,"
too. And Mom says I've got magic, even if she's a muggle.
Four years old, four and a half years of love and inspiration, of learning and growing.
We were talking the other night about Aaron's birth with my sister who acted as point for letting my family know what was happening. (She was house sitting for my parents and I didn't have to look up that number.) As we were talking, William shared some things I don't think I'd heard before.
I knew he wasn't breathing when he was born. I didn't know that as the team worked on them, they started to get worried, too. But he did it, he took that first breath, and then a second and a third. And four years later, he's still breathing, mostly on his own.
And over the last two weeks, he's pulled another trick out of the bag. Anyone who's followed us knows that the common cold, rhino virus, is the bane of my existence. I'd almost rather have pneumonia. At least we can do something about that besides just trying to support him while he works through his symptoms.
Well, for those who don't know, hospitals are nasty, germy places. They try to keep them clean, try to heal people, but the simple fact that sick people are there mean so are the germs. And while we were there for his adenoidectomy, he managed to pick up a cold.
Now, the reason we took out his adenoids was to (hopefully) reduce or even eliminate his constant ear infections. For us normal mouth/nose breathers, it would also have the potential to improve breathing. But remember, Aaron has a trach. His nose shouldn't play into it. Except, it does. Within 24 hours of surgery, his oxygen needs dropped to 3/4 of a liter. Yeah, less than one. We haven't seen that in over a year.
The next day though, the snot started. And kept coming. And coming. And coming some more. I felt like I was sucking the poor kid's brains out of his nose! And true to form, his oxygen needs went up. But because they were already so low, we could support it! I think I bumped five liters, twice. And he's been great!! I didn't dare put this up earlier, 'cause I was afraid of jinxing myself. But given that our last symptoms were last week, I think we've done it!
Yeah, my little neck breather apparently does breathe through his nose. My mom reminded me that through his whole life Aaron has been doing things he's "not supposed" to be able to do, so why should he stop now? And isn't that a great thing?
Last week, a few of the kids went up to Fantasy Con. Andrew picked up some Harry Potter glasses while he was there, and then tried them on Aaron. Yeah, I think "the boy who lived" should apply to Aaron as well. It's love and faith and the support of so many that have kept him alive. And I think that may also be true for all of us.
Love cures people—both the ones who give it and the ones who receive it. ~Karl Menninger
Posted by CompatibleWithJoy at 6:17 PM
Clint C. July 13, 2014 at 5:12 PM
Love it! He keeps on keeping on!
Lisa July 14, 2014 at 5:13 AM
I love it when our special kids do things that the doctors say they never will. Yay for Aaron! :)
Yea for Simple Fixes (We Hope)
My Country, 'Tis of Thee
Living the Good Life, BECAUSE of the Challenges


Innate lymphoid cells (ILCs) residing in adipose tissue participate in the pathogenesis of obesity, but their contribution toward adipose tissue homeostasis in the lean state is unclear. Boulenouar et al. (2017) now report that heterogenous type 1 ILCs in adipose tissues regulate macrophage homeostasis through cytotoxicity. Click here to view article in Cell. Click here to download.
Regulatory iNKT cells lack PLZF and control Treg and macrophage homeostasis in adipose tissue.


Home » Bra Top » Crochet Bra - 1 XS LEFT!
DYI's bra in this white crochet lace is so pretty you'll want to where it to class, on the weekend, maybe even to the beach! It offers a longer length to prevent ride up, a keyhole back, a feminine neckline, and tons of support. Pair this bra with DYI's Denim Signature tight for a complete look.
This style fits small. We suggest going up a size to get the fit perfect.
Model is 5`9" and wearing a size "Medium"


Tess C. Taylor, PHR, The HR WriterAs Obamacare officially launched across America this year, new requirements forced employers to look for ways to boost their compensation and benefit programs without raising healthcare premium costs. The new law permits employers to use as much as 30 percent of each worker's health care premium on wellness incentive programs (up from 20 percent last year). The challenge to find cost-effective ways to maintain the well-being and productivity of workers is on.
As Obamacare officially launched across America this year, new requirements forced employers to look for ways to boost their compensation and benefit programs without raising healthcare premium costs. The new law permits employers to use as much as 30 percent of each worker's health care premium on wellness incentive programs (up from 20 percent last year). The challenge to find cost-effective ways to maintain the well-being and productivity of workers is on.
In many workplaces, stress has become the norm, and addictions and obesity have skyrocketed – causing the cost of even basic healthcare programs to rise over the last few years. With medical costs nearing astronomical highs and an overburdened healthcare system lacking enough support, the need to control healthcare costs by preventing diseases and reducing poor lifestyle choices has become critical. This is why corporate wellness programs, backed up by generous incentives, can be a solution for any organization.
It's not surprising that as early as the 1980s, companies began exploring ways to improve productivity at work at the same time as reducing absenteeism. This is the foundation of what transformed simple personnel departments into full human resource teams, focused on the revenue generating power of employees. Human capital management has become a central effort of many companies today, with programs designed to prevent rather than react to employee problems.
Wellness at work has been linked to many benefits for companies. Multiple studies have shown that when employees are feeling great they are happier, require less time off, and their overall healthcare insurance premiums are much less costly. The pursuit of work life balance is supported by many employers, who now understand people are not just robots for a company. Preventing illness, leading a healthier lifestyle and taking care of employee well-being literally equate to dollars and cents for a company. It's a win-win situation for everyone.
Offering a corporate wellness program does not mean that everyone will participate. It's long been known that financial incentives can encourage participation. For example, a smoking cessation study conducted by the University of Pennsylvania concluded that participants who received compensation for meeting specific goals were more likely to quit smoking for long-term vs. those who received no compensation. Although one would think that the idea of being healthy and fit is a good enough incentive, some employees need that little extra push to make it happen.
Earlier this year, Aon Hewitt, an HR solutions firm, released the results of a survey of 800 large and mid-size employers representing 7 million US employees. They found that 83 percent of these companies offer some form of incentives for participating in wellness programs. Additionally, nearly 80 percent use rewards based incentives, while only 5 percent used punishment. Of those companies that offer monetary incentives (64 percent) this can range from $50 to as much as $500 for reaching important health goals. Clearly, companies understand the connection between participating and reward.
There are various incentives that any company can provide to employees who actively participate in corporate-sponsored wellness programs.
Free healthy lunches for employees who participate in a weekly walk around the campus.
Onsite fitness center and wellness services that employees can use on their breaks and off-time.
Discounts for local gyms, dietary support programs, fitness retailers, and health food stores.
Access to free and confidential addictions counseling and financial support for rehabilitation treatment.
Corporate events and entertainment that centers on mental and physical well-being.
Gift cards and cash incentives for meeting certain health and fitness goals.
Wellness committees and clubs to promote peer support and respect for those making a positive change in their lives.
Paid time off and flexible scheduling to attend wellness programs and restore work life balance.
The incentives above are just a handful of ways you can support the wellness of your employees, while reducing healthcare costs and employee illness. Just one employee who makes the effort to lose weight, stop smoking, or live a less stressful life can have a positive impact on your workplace. Get behind your corporate wellness initiative and provide effective incentives for those who participate.


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Superfood chain opening location
BY Grand Rapids Business Journal – A national "superfood café" chain is prepping to open the first Michigan location. Vitality Bowls will open a location on Nov. 2 in the Shops at CenterPoint in Grand Rapids, at 3569 28th St. SE, according to the chain last...
'Superfood café' opening doors
BY Grand Rapids Magazine – A "superfood café" is about to open in Grand Rapids. Vitality Bowls will open a location on Nov. 2 in the Shops at CenterPoint, at 3569 28th St. SE, according to the brand last week. A family-friendly grand opening will be held from...
Vitality Bowls to Open First Location in Michigan
BY the Rebusiness Online – Leading Superfood Concept Ranked #487 on Prestigious List of Largest United States Franchises Vitality Bowls is set to open its first location in Michigan. The café, slated to open on Saturday, Nov. 2, is located within the...
Health food restaurant Vitality Bowls opens doors in Grand Rapids
BY Rejournals – Vitality Bowls, a restaurant serving super foods, opened its first café in Grand Rapids, Michigan. The café, which specializes in acai bowls, will be open for breakfast, lunch, dinner, snacks or dessert. Slated to open Nov. 2, the new locally...
GRAND RAPIDS, MICH. — Vitality Bowls is set to open its first location in Michigan. The café, slated to open on Saturday, Nov. 2, is located within the 575,000-square-foot Shops at CenterPoint. Vitality Bowls specializes in acai bowls, including the acai berries and a...
@eastdrinkstl Visits Vitality Bowls St. Louis
Vitality Bowls Claims Spot on Franchise Times Top 200+ List
Vitality Bowls Seasonal Apple Pie Bowl
Vitality Bowls encourages healthy living, sharing experiences
@slcfoodie Posts About Vitality Bowls On Instagram
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About Vitality Bowls
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As we diligently follow COVID-19 updates and developments from the Center for Disease Control (CDC), most Vitality Bowls locations remain open as our team closely follows all public health recommendations to keep our customers, employees and communities healthy and safe.
Our goal has always been to provide the most nutritious food possible to our customers, and we are dedicated to that mission now more than ever.
Some aspects of the Vitality Bowls experience have been modified, including some locations limiting dining experiences to take-out and delivery only. Please contact your local Vitality Bowls regarding in-store dining availability.
We are confident that we will get through this together as a community. In the meantime, Vitality Bowls is here for you, to provide healthy, nutritious meals for you and your family.


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Will Greenhalgh Act Over Cllr. Lucy Ivimy's Race Slur?
The Daily Mail has scooped a story exposing Ravenscourt Park Councillor Lucy Ivimy (Con) writing racial slurs in an official email. Cllr. Ivimy was promoted to be H&F Council's new Cabinet Member for Housing on May 28th this year. One of her first acts seems to have been to write to Nick Johnson, the Chief Executive of H&F Council's housing management company, in which she expressed her "personal" prejudice about "foreign born residents". You can read the Mail's online version here. BBC and ITV London also headlined the story all day yesterday. You may still be able to view the ITV version here.
Having been told by residents that Woodfood Court had increased levels of litter (presumably after the cuts to the caretaking service) Cllr. Lucy Ivimy, wrote to Nick Johnson, to say "I know that in India, throwing rubbish out of a window and total disregard for the cleanliness of a public area is normal behaviour and I dare say a number would change behaviour if firmly told that in London this is not acceptable behaviour." You can read more of her comments in the article.
The Daily Mail says there are "only a handful of Indian families" living in the area. Cllr. Ivimy clearly had no evidence on which to base her views. There are problems with littering but it is done by a minority of people from a wide range of backgrounds and completely wrong to say it is the fault of "foreign born" or "Indian" residents.
Defending herself Cllr Ivimy told the Mail that "This was a hastily written, ill thought out, stupid, personal email" Let's unravel that explanation. Firstly, when someone writes down their "personal" views they are expressing their inner-most private thoughts. Thoughts that in this case expose Cllr. Ivimy's gut "personal" prejudice against Hammersmith and Fulham's "foreign born" and "Indian" residents. To say her comments were written in "haste" simply means that she did not spend the time to ensure she had camouflaged those "personal" views.
There has been no comment from Cllr. Stephen Greenhalgh (Con), the Leader of the Council. I guess he is hoping that by keeping his head down this problem will go away. This is a failure of his leadership as it won't. I am sorry to say that he is obliged to immediately sack Cllr. Ivimy from her new role as the Cabinet Member for Housing. Any cabinet position requires a politician who will engage their brain when dealing with the myriad of issues they are presented with. Not someone who engages their "personal" prejudices. The housing role makes Cllr. Ivimy responsible for 18,000 local council homes and for deciding the policy of how vacant homes are allocated. She is also currently in charge of deciding the development policy for all of the borough's new housing and has a responsibility for community cohesion and integration. Hammersmith and Fulham has residents from a diverse range of backgrounds. All have a right to expect that the politician elected to deal with those issues will do so without "personal" prejudice. Cllr. Ivimy has disqualified herself from that brief.
Sadly, for Cllr. Ivimy, Greenhalgh must go further. David Cameron has been telling the public for some time now that the Conservatives have changed. Mr. Cameron calls it his "strategy to decontaminate the Conservative brand". Well, if that is to be believed then Cllr. Stephen Greenhalgh has to remove the whip from Cllr. Ivimy and call a by-election in Ravenscourt Park ward. It is unfair on her constituents to do anything else.
Meanwhile, Cllr. Ivimy's comments have brought H&F Council into disrepute. That's certainly the view in India which is one of the world's great democracies and a country which modern Britain enjoys long-standing friendship, family and cultural links and increasingly important trading ties. The Hindustan Times covers the story here and the Mumbai Mirror covers it here. The Times of India says this and Yahoo India published this. The Hindu has this take on the story and the Telegraph (India) said this. India's IBN network is broadcasting the story today (you can read the text here) as is the Indian News Channel. The story has been covered on all the main Indian media but is also getting other international coverage including in Malaysia, China and the United States.
Does she know this is 2008, not 1948?
Thank God she does not represent me.
She cannot stay in her job. Does Cameron know?
Greg Wiseman
Thanks to Stephen for raising this.
This is a fundamental issue made all the more worrying by the "personal email" nature of the communication. Has this lady been saying one thing in public whilst expressing another view in private?
This is not a party political issue.
I understood that the Leader of the Council, Mr Greenhalgh was also closely engaged with Boris Johnson the mayor.
How does the mayor feel about one of his closest advisors condoning this action by one of his team, by his lack of action? Does this reflect on a position held privately by many in the Conservatives?
Has Shaun Bailey commented yet?
Greenhalgh and Cameron have made it worse as they have implicitly condoned her comments by failing to sack her. I am deeply offended by this.
Hmmm... Lucy Ivimy? This is the lady who last autumn, as chair of planning, pushed through the big strawberry looking office building at the bottom of Hammersmith Grove, is it not? It seems that her judgement is worse than I originally thought.
I am an "Indian" business woman in hammersmith and have just been given a court summons on what is an unfair penalty from 12 months ago. Contacting Lucy & her co-councillors last summer to discuss the case and resolve it, clearly did not work and this came out of the blue 9 months later. To top that LBHF waste guys take our recycling waste bagged for another company and put it into their general (non-recyclable) truck. We called their office and they know it's happening, yet do nothing! Paid by the tonne I guess? Where's the justice. Anyone got contacts in news desks.
Is this a growing problem? Over the weekend the London Mayor lost an aide for comments that were made see http://news.bbc.co.uk/1/hi/uk_politics/7468434.stm for detail.
This has been dealt with swiftly.
This story http://www.telegraph.co.uk/news/1938171/Boris-Johnson-vows-to-end-corruption.html lists Stephen Greenhaigh as a member as refered to in my previous post.
David Cameron promoted Mrs Ivimy to be the Vice Chairman of Housing for all London within just a few months of this happening. That act alone says all we need to know about Cameron's real feelings toward tackling this sort of racism does it not?
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We've drawn up a list of the best combinations of rods, reels, line, leaders, hooks & lures to make sure you're properly equipped to fish at all of our destinations.
We also have a selection of tackle for rent at very reasonable rates. Please let us know if you want to rent tackle at the time of your booking.


to see which one is most compatible for you.
3. All dogs will be up to date on their vaccinations & rabies shots. They will be dewormed.
4. Be available for a home visit by our adoption team before your application is approved and for follow up visits if your application is approved.
3. If the dog will be kept in a cage, the cage should be big enough so the dog can stand and walk around. Cage must be sturdy, and the dog should be allowed out of the cage or kennel several times a day for exercise.
4. Children and other pets in the household may not be advisable for certain dogs, this will have to be discussed with the adoption team when deciding which dog is the best match for you.
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A unique opportunity for a true lifestyle change. A traditional Dales stone-built house, being carefully converted from a former mill into a 1600 sq ft 2 bedroom home, with an integrated office/work room incorporated and separately accessible. Perfect for someone wishing to relocate and run a business from home.
1) The property should be ready for occupation (subject to legals) by September 2013.2) A copy of the plans and planning permission is available from this office.3) All work is architect supervised and certificated.4) For an early purchaser an agreed specification will be supplied.


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Application performance is critical to business performance according to 98 per cent of businesses, yet 89 per cent of executives say the poor performance of enterprise applications has negatively impacted their work, and 58 per cent say it impacts their work at least weekly.
This is the key finding of application performance specialist Riverbed Technology's Global Application Performance Survey 2015. 71 per cent of respondents say they have felt frequently 'in the dark' about why their enterprise applications are running slowly, highlighting a disconnect between IT teams and business executives, and 27 per cent would sacrifice chocolate for peak app performance.
"The results of the survey reflect what we're hearing every day from IT leaders who are looking to deliver superior application performance in the midst of rapidly evolving, highly complex and hybrid IT environments," says Jerry M Kennelly, Chairman and CEO of Riverbed. "With apps, data and end users everywhere today, companies need end-to-end application visibility, optimisation, and control everywhere as well to close the performance gap. Riverbed helps organisations improve application performance to drive tangible business benefits and performance".
The top benefits of good app performance are identified as improved employee productivity (51 per cent), time savings (50 per cent), and cost savings (47 per cent). The main effects of poor performance according to respondents are, dissatisfied clients or customers (41 per cent), contract delays (40 per cent), and missing critical deadlines (35 per cent).
When asked what they'd be willing to sacrifice to have peak app performance at all times, 33 per cent of executives said would give up their full lunch break. They would also be willing to give up a portion of their program budget (32 per cent), caffeine (29 per cent), and even chocolate (27 per cent).
Whilst 78 per cent of respondents say that moving key enterprise applications to the cloud has increased productivity, there's evidence that it also increases complexity. 83 per cent of respondents say they believe trouble-shooting application performance issues is more difficult in a hybrid IT environment.
More detail is available in the full report which can be found on the Riverbed website.