The Voting Behavior of Labor Union Members in the 2016 Presidential Election

The conventional wisdom surrounding the 2016 United States presidential election suggests that Donald Trump, the Republican candidate, received significant support from labor union members. This has drawn attention, as labor union members have long been considered a crucial Democratic voting bloc. Previous studies have shown that Democratic support from organized labor groups has been declining over time. The stereotypical labor union member has long been a white working class male with a high school level of education in a private sector union, and recent work has primarily focused solely on these individuals. However, those traditional labor union members have been found to make up a declining share of labor union members. Therefore, there is a considerable gap in the understanding of who labor union members in the United States are. This paper will consider the changing demographics of labor union members, and analyze ANES data to consider their behavior in the 2016 U.S. presidential election

Travelled distance estimation for GPS-based round trips car-sharing use case

Traditional travel survey methods have been widely used for collecting information about urban mobility although Global Position System (GPS) has become an automatic option for collecting more precise data of the households since mid-1990s. Many studies on mobility patterns have focused on the GPS advantages leaving aside its issues such as the quality of the data collected. However, when it comes to extract the frequency of the trips and travelled distance, this technology faces some gaps due to the related issues such as signal reception and time-to-first-fix location that turns out in missing observations and respectively unrecognised or over-segmented trips. In this study, we focus on two aspects of GPS data for a car-mode, (i) measurement of the gaps in the travelled distance and (ii) estimation of the travelled distance and the factors that influence the GPS gaps. To asses that, GPS tracks are compared to a ground truth source. Additionally, the trips are analysed based on the land use (e.g. urban and rural areas) and length (e.g. short, medium and long trips). Results from 170 participants and more than a year of GPS-tracking show that around 9 % of the travelled distance is not captured by GPS and it affects more short trips than long ones. Moreover, we validate the importance of the time spent on the user activity and the land use as factors that influence the gaps in GPS

Travelled distance estimation for GPS-based round trips : car-sharing use case

Traditional travel survey methods have been widely used for collecting information about urban mobility although, since middle of the 90’s Global Position System (GPS) has become an automatic option for collecting more precise data of the households. But how good is the collected data? many studies on mobility patterns have focused on the GPS advantages and leaving aside its issues. However, when it comes to extract the frequency of the trips and travelled distance this technology faces some gaps due to related issues, such as signal reception and time-to-first-fix location that turns out in missing observations and respectively unrecognised or over-segmented trips. In this study, we focus on two aspects of GPS data for a car-mode, (i) measurement of the gaps in the travelled distance and (ii) estimation of the travelled distance and the factors that influence the GPS gaps. To asses that, GPS tracks are compared to a ground truth source. Additionally, the trips are analysed based on the land use (e.g., urban and rural areas) and length (e.g., short, middle and long trips). Results from 170 participants and more than a year of GPS-tracking show that around 9% of the travelled distance is not captured by the GPS and it affects more to short trips than long ones. Moreover, we validate the importance of the time spent on the user activity and the land use as factors that influence the gaps on GPS

Characterizing correlations of flow oscillations at bottlenecks

"Oscillations" occur in quite different kinds of many-particle-systems when two groups of particles with different directions of motion meet or intersect at a certain spot. We present a model of pedestrian motion that is able to reproduce oscillations with different characteristics. The Wald-Wolfowitz test and Gillis' correlated random walk are shown to hold observables that can be used to characterize different kinds of oscillations

Tumor exome sequencing and copy number alterations reveal potential predictors of intrinsic resistance to multi-targeted tyrosine kinase inhibitors

Multi-targeted tyrosine kinase inhibitors (TKIs) have broad efficacy and similar FDA-approved indications, suggesting shared molecular drug targets across cancer types. Irrespective of tumor type, 20-30% of patients treated with multi-targeted TKIs demonstrate intrinsic resistance, with progressive disease as a best response. We conducted a retrospective cohort study to identify tumor (somatic) point mutations, insertion/deletions, and copy number alterations (CNA) associated with intrinsic resistance to multi-targeted TKIs. Using a candidate gene approach (n=243), tumor next-generation sequencing and CNA data was associated with resistant and non-resistant outcomes. Resistant individuals (n=11) more commonly harbored somatic point mutations in NTRK1, KDR, TGFBR2, and PTPN11 and CNA in CDK4, CDKN2B, and ERBB2 compared to non-resistant (n=26, p<0.01). Using a random forest classification model for variable reduction and a decision tree classification model, we were able to differentiate intrinsically resistant from non-resistant patients. CNA in CDK4 and CDKN2B were the most important analytical features, implicating the cyclin D pathway as a potentially important factor in resistance to multi-targeted TKIs. Replication of these results in a larger, independent patient cohort has potential to inform personalized prescribing of these widely utilized agents

Critical function of AP-2gamma/TCFAP2C in mouse embryonic germ cell maintenance

Formation of the germ cell lineage involves multiple processes, including repression of somatic differentiation and reacquisition of pluripotency as well as a unique epigenetic constitution. The transcriptional regulator Prdm1 has been identified as a main coordinator of this process, controlling epigenetic modification and gene expression. Here we report on the expression pattern of the transcription factor Tcfap2c, a putative downstream target of Prdm1, during normal mouse embryogenesis and the consequences of its specific loss in primordial germ cells (PGCs) and their derivatives. Tcfap2c is expressed in PGCs from Embryonic Day 7.25 (E 7.25) up to E 12.5, and targeted disruption resulted in sterile animals, both male and female. In the mutant animals, PGCs were specified but were lost around E 8.0. PGCs generated in vitro from embryonic stem cells lacking TCFAP2C displayed induction of Prdm1 and Dppa3. Upregulation of Hoxa1, Hoxb1, and T together with lack of expression of germ cell markers such Nanos3, Dazl, and Mutyh suggested that the somatic gene program is induced in TCFAP2C-deficient PGCs. Repression of TCFAP2C in TCam-2, a human PGC-resembling seminoma cell line, resulted in specific upregulation of HOXA1, HOXB1, MYOD1, and HAND1, indicative of mesodermal differentiation. Expression of genes indicative of ectodermal, endodermal, or extraembryonic differentiation, as well as the finding of no change to epigenetic modifications, suggested control by other factors. Our results implicate Tcfap2c as an important effector of Prdml activity that is required for PGC maintenance, most likely mediating Prdm1-induced suppression of mesodermal differentiation

Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem

We study the Bipartite Boolean Quadratic Programming Problem (BBQP) which is an extension of the well known Boolean Quadratic Programming Problem (BQP). Applications of the BBQP include mining discrete patterns from binary data, approximating matrices by rank-one binary matrices, computing the cut-norm of a matrix, and solving optimisation problems such as maximum weight biclique, bipartite maximum weight cut, maximum weight induced sub-graph of a bipartite graph, etc. For the BBQP, we first present several algorithmic components, specifically, hill climbers and mutations, and then show how to com- bine them in a high-performance metaheuristic. Instead of hand-tuning a standard metaheuristic to test the efficiency of the hybrid of the components, we chose to use an automated generation of a multi- component metaheuristic to save human time, and also improve objectivity in the analysis and compar- isons of components. For this we designed a new metaheuristic schema which we call Conditional Markov Chain Search (CMCS). We show that CMCS is flexible enough to model several standard metaheuristics; this flexibility is controlled by multiple numeric parameters, and so is convenient for automated genera- tion. We study the configurations revealed by our approach and show that the best of them outperforms the previous state-of-the-art BBQP algorithm by several orders of magnitude. In our experiments we use benchmark instances introduced in the preliminary version of this paper and described here, which have already become the de facto standard in the BBQP literature

Measuring the capability to raise revenue process and output dimensions and their application to the Zambia revenue authority

The worldwide diffusion of the good governance agenda and new public management has triggered a renewed focus on state capability and, more specifically, on the capability to raise revenue in developing countries. However, the analytical tools for a comprehensive understanding of the capability to raise revenue remain underdeveloped. This article aims at filling this gap and presents a model consisting of the three process dimensions ‘information collection and processing’, ‘merit orientation’ and ‘administrative accountability’. ‘Revenue performance’ constitutes the fourth capability dimension which assesses tax administration’s output. This model is applied to the case of the Zambia Revenue Authority. The dimensions prove to be valuable not only for assessing the how much but also the how of collecting taxes. They can be a useful tool for future comparative analyses of tax administrations’ capabilities in developing countries.Die weltweite Verbreitung der Good-Governance- und New-Public-Management-Konzepte hat zu einer zunehmenden Konzentration auf staatliche Leistungsfähigkeit und, im Besonderen, auf die Leistungsfähigkeit der Steuererhebung in Entwicklungsländern geführt. Allerdings bleiben die analytischen Werkzeuge für ein umfassendes Verständnis von Leistungsfähigkeit unterentwickelt. Dieser Artikel stellt hierfür ein Modell vor, das die drei Prozess-Dimensionen „Sammeln und Verarbeiten von Informationen“, „Leistungsorientierung der Mitarbeiter“ und „Verantwortlichkeit der Verwaltung“ beinhaltet. „Einnahmeperformanz“ ist die vierte Dimension und erfasst den Output der Steuerverwaltung. Das mehrdimensionale Modell wird für die Analyse der Leistungsfähigkeit der Steuerbehörde Zambias (Zambia Revenue Authority) genutzt. Es erweist sich nicht nur für die Untersuchung des Wieviel, sondern auch des Wie des Erhebens von Steuern als wertvoll. Die vier Dimensionen können in Zukunft zur umfassenden und vergleichenden Analyse der Leistungsfähigkeit verschiedener Steuerverwaltungen in Entwicklungsländern genutzt werden

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts