Miracle-dz/UniFAR-FTUs huggingface dataset:
Decomposing Isotonic Regression for Efficiently Solving Large Problems

A new algorithm for isotonic regression is presented based on recursively partitioning the solution space. We develop efficient methods for each partitioning subproblem through an equivalent representation as a network flow problem, and prove that this sequence of partitions converges to the global solution. These network flow problems can further be decomposed in order to solve very large problems. Success of isotonic regression in prediction and our algorithm's favorable computational properties are demonstrated through simulated examples as large as 2 x 105 variables and 107 constraints.
Longitudinal and transverse magnetoelectric voltage coefficients of magnetostrictive/piezoelectric laminate composite: theory

This paper presents a novel, long-type of magnetostrictive and piezoelectric laminate composite design in which the layers are, respectively, magnetized/poled along their length axes, and a theory for modeling its behavior. Using piezoelectric and magnetostrictive constitutive equations, and an equation of motion, a magneto-elasto-electric bieffect equivalent circuit is developed. The circuit is used to predict the longitudinal and transverse magnetoelectric (ME) voltage coefficients of our Terfenol-D/Pb(Zr/sub 1-x/Ti/sub x/)O/sub 3/ laminate design. It is found that the longitudinal ME voltage coefficient is significantly higher (/spl sim/5x) than the transverse one, and that our new laminate design has significantly higher ME voltage coefficients under small applied direct current (DC) magnetic bias fields than designs reported previously by other groups. Experimental values were found to be coincidental with predicted ones.
Performance Analysis of Vertex-centric Graph Algorithms on the Azure Cloud Platform

Finding key vertices in large graphs is an important problem in many applications such as social networks, bioinformatics, and distribution networks. Betweenness centrality is a popular algorithm for finding such vertices and has been studied extensively, yielding several parallel formulations suitable to supercomputers and clusters. In this paper we implement and study betweenness centrality in the context of cloud-based platforms using Microsoft Windows Azure as our case study. We demonstrate scalable parallel performance and investigate key issues related to a cloud-based implementation including mitigating penalties associated with VM failures as well as the impact of communication overheads in the cloud. We use a combination of empirical and analytical evaluation using both synthetic small-world and real-world social interaction graphs. KeywordsGraph; Cloud computing; Azure; performance analysis; betweennness centrality; scalability
Abstract 12587: Sodium Current Deficit and Arrhythmogenesis in a Murine Model of Plakophilin-2 Haploinsufficiency

Mutations in desmosomal protein Plakophilin 2 (PKP2) associate with arrhythmogenic cardiomyopathy (“ARVC”). Cardiac arrhythmias and sudden death can occur in the “concealed” phase of the disease, prior to overt structural damage. The mechanisms underlying these arrhythmias are not understood. Based on previous in vitro data showing cross-talk between PKP2 and the sodium channel (SC) complex, we propose that a decrease in PKP2 causes sodium current (INa) dysfunction, which predisposes the heart to severe arrhythmias if the SC is further challenged. We studied the morphology, histology and ultrastructural features of PKP2-heterozygous-null (PKP2-Hz) murine hearts, and explored the relation between PKP2 abundance, INa and arrhythmias. PKP2-Hz hearts did not show anatomical or histological differences compared to wild-type (WT). Western blot revealed reduced abundance of PKP2, without changes in abundance of other intercalated disc proteins. Tomographic electron microscopy showed loss of desmosomes and expand.
MPE-based discriminative linear transform for speaker adaptation

We present a discriminative method for speaker adaptation, where the minimum phone error (MPE) criterion is used to estimate the discriminative linear transforms (DLTs), including both mean and diagonal variance transforms. The I-smoothing technique is essential to improve the generalization of DLTs. Experiments on supervised adaptation for non-native speakers on the North American Business (NAB) Spoke 3 task show that MPE-based DLT outperforms both MLLR and a previously proposed discriminative method for transform estimation. Preliminary experiments on unsupervised DLT estimation are also reported for conversational telephone speech transcription.
Semaphorin3a Enhances Endocytosis at Sites of Receptor–F-Actin Colocalization during Growth Cone Collapse

Axonal growth cone collapse is accompanied by a reduction in filopodial F-actin. We demonstrate here that semaphorin 3A (Sema3A) induces a coordinated rearrangement of Sema3A receptors and F-actin during growth cone collapse. Differential interference contrast microscopy reveals that some sites of Sema3A-induced F-actin reorganization correlate with discrete vacuoles, structures involved in endocytosis. Endocytosis of FITC-dextran by the growth cone is enhanced during Sema3A treatment, and sites of dextran accumulation colocalize with actin-rich vacuoles and ridges of membrane. Furthermore, the Sema3A receptor proteins, neuropilin-1 and plexin, and the Sema3A signaling molecule, rac1, also reorganize to vacuoles and membrane ridges after Sema3A treatment. These data support a model whereby Sema3A stimulates endocytosis by focal and coordinated rearrangement of receptor and cytoskeletal elements. Dextran accumulation is also increased in retinal ganglion cell (RGC) growth cones, in response to ephrin A5, and in RGC and DRG growth cones, in response to myelin and phorbol-ester. Therefore, enhanced endocytosis may be a general principle of physiologic growth cone collapse. We suggest that growth cone collapse is mediated by both actin filament rearrangements and alterations in membrane dynamics.
Candoia: A Platform and an Ecosystem for Building and Deploying Versatile Mining Software Repositories Tools

Research on mining software repositories (MSR) has shown great promise during the last decade in solving many challenging software engineering problems. There exists, however, a ‘valley of death’ between these significant innovations in the MSR research and their deployment in practice. The significant cost of converting a prototype to software; need to provide support for a wide variety of tools and technologies e.g. CVS, SVN, Git, Bugzilla, Jira, Issues, etc, to improve applicability; and the high cost of customizing tools to practitioner-specific settings are some key hurdles in transition to practice. We describe Candoia, a platform and an ecosystem that is aimed at bridging this valley of death between innovations in MSR research and their deployment in practice. We have implemented Candoia and provide facilities to build and publish MSR ideas as Candoia apps. Our evaluation demonstrates that Candoia drastically reduces the cost of converting an idea to an app, thus reducing the barrier to transitioning research findings into practice. We also see versatility, in Candoia app’s ability to work with a variety of tools and technologies that the platform supports. Finally, we find that customizing Candoia app to fit project-specific needs is often well within the grasp of developers.
Optimal location of terminal voltage nonlinear excitation controller to mitigate small signal stability problem

This paper aims at the selection of optimal location of the terminal voltage nonlinear excitation controller to mitigate small signal stability problem. The controller consists of inverse compensator and proportional controller. One is designed to cancel nonlinear characteristics of the controlled object, the other is used to formulate the closed loop. Based on the simplified model of the generator with terminal voltage nonlinear excitation controller, the linear model of a multi-machine power system is derived. The objective of the optimization is to maximize the sum of damping ratios as much as possible, and the Particle Swarm Optimization (PSO) algorithm is used to investigate this problem in order to optimize the location and parameter of nonlinear controller. To show the validity of the proposed method, simulation results are presented and discussed for IEEE 9-bus system.
Substance Abuse and Bipolar Affective Disorder

This interview study was conducted to explore the onset, course, and features of bipolar affective disorder complicated by substance abuse. Forty-four patients with a diagnosis of bipolar affective disorder were interviewed using the Structured Clinical Interview for DSMIII- R, Hamilton Rating Scale for Depression, Young Mania Rating Scale, and a questionnaire concerning psychiatric history. Current substance users averaged twice as many hospitalizations for mood problems. The age of onset of mood problems for substance users was significantly earlier than that of the nonusers (p<.05). Substance users were four times as likely to have other comorbid axis I disorders (p<.05) and twice as likely to have dysphoric mania at time of interview. This preliminary study suggests that individuals with bipolar affective disorder complicated by substance abuse may have more hospitalizations, a higher incidence of dysphoric mania, earlier onset of mood problems, and more comorbid axis I disorders
A nonparametric Bayesian approach to time series alignment

We propose a nonparametric Bayesian approach to time series alignment. Time series alignment is a technique often required when we analyze a set of time series in which there exists a typical structural pattern common to all the time series. Such a set of time series is usually obtained by repeated measurements of a biological, chemical or physical process. In time series alignment, we required to estimate a common shape function, which describes a common structural patter shared among a set of time series, and time transformation (time warping) functions, each of which represents time shifts involved in individual time series. In our approach, the common shape function and the time transformation functions are modeled nonparametrically by using Gaussian process priors. We introduce an effective Markov Chain Monte Carlo algorithm and it enables a fully Bayesian analysis of time series alignment.
Teaching Meta-cognitive Skills: Implementation and Evaluation of a Tutoring System to Guide Self- Explanation While Learning from Examples

The SE-Coach is a tutoring module designed to help students learn effectively from examples through guiding self-explanation, a meta-cognitive-skill that involves clarifying and explaining to oneself the worked out solution for a problem. The SE-Coach provides this guidance through (a) an interface that allows the student to interactively build self-explanations based on the domain-theory (b) a student model that assesses the quality of the student's explanations and the student's understanding of the example. The SE-Coach uses the assessment in the student model to elicit further self-explanation to improve example understanding. In the paper we describe how the SE-Coach evolved from its original design to the current implementation via an extensive and thorough process of iterative design, based on continuous evaluations with real students. We also present the results of the final laboratory experiment that we have performed with 56 college students. We discuss some hypotheses to explain the obtained results, based on the analysis of the data collected during the experiment.
Learners’ motivation to learn vocabulary in English

Current motivation research defines online motivational possibilities and self-motivational elements. In the present paper I describe the constituents of language learners’ motivation in primary education in three age groups. The self-motivational elements, which have been obtained from interviews conducted on young learners’ vocabulary learning habits, can be discussed as having two distinctive functions. Based on the interviews, the results of a multi-layered research allow us to gain insights into the role of initial motivation, which includes treatment of difficulties and anxiety, and the function of the elements of motivational outcome, such as rewarding, efficacy and satisfaction. The study, through the analysis of the components of motivation, highlights the apparent areas of development.
Epistemological sensitisation causes deeper elaboration during self-regulated learning

Previous research indicates that students' adaptation to task complexity in the planning stages of self-regulated learning are related to their epistemological beliefs (Stahl, Pieschl, & Bromme, 2006), but it is an open issue if students enact similar strategies in subsequent stages. Based on the COPES-model (Winne & Hadwin, 1998) the impact of epistemological beliefs on learning is tested here experimentally. In this study, students (21 humanities students, 14 biology students) had to solve five tasks of different complexity (Anderson et al., 2001) with a hypertext on "genetic fingerprinting". Results indicate that students adapted their concurrent thoughts and concurrent actions to task complexity in this enactment stage. An epistemological sensitisation was administered that elicited more "sophisticated" beliefs and caused more elaborate learning processes. For example, students with this sensitisation employed more metacognitive planning, especially for more complex tasks. Additionally, effects of prior domain knowledge were investigated.
Managing Identity Conflicts in Organizations

How nonprofit organizations manage multiple and conflicting identities is not well understood. In a case study of a nonprofit welfare organization, we use Pratt and Foreman’s (2000) framework of identity management responses to illuminate different ways that nonprofit organizations can seek to manage and potentially resolve identity conflicts. We focus on the actual practices nonprofit organizations use to manage multiple identities and, in particular, reveal the important role of organizational routines and artifacts in facilitating or constraining particular identity management responses.
Quantitative Models of the Mechanisms That Control Genome-Wide Patterns of Transcription Factor Binding during Early Drosophila Development

Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6–0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision.
Mobilization of mercury and arsenic in humans by sodium 2,3-dimercapto-1-propane sulfonate (DMPS).

Sodium 2,3-dimercapto-1-propane sulfonate (DMPS, Dimaval) is a water-soluble chelating agent that can be given by mouth or systemically and has been used to treat metal intoxication since the 1960s in the former Soviet Union and since 1978 in Germany. To better approximate the body burdens of Hg and As in humans, DMPS-Hg andDMPS-As challenge tests have been developed. The tests involve collecting an overnight urine, administering 300 mg DMPS at zero time, collecting the urine from 0 to 6 hr, and determining the urinary Hg before and after DMPS is given. The challenge test, when applied to normal college student volunteers with and without amalgam restorations in their mouths, indicated that two-thirds of the Hg excreted in the urine after DMPS administration originated in their dental amalgams. In addition, there was a positive linear correlation between the amalgam score (a measure of amalgam surface) and urinary Hg after the challenge test. When the DMPS-Hg challenge test was used to study dental personnel occupationally exposed to Hg, the urinary excretion of Hg was 88, 49, and 35 times greater after DMPS administration than before administration in 10 dental technicians, 5 dentists, and 13 nondental personnel, respectively. DMPS also was used to measure the body burden of humans with a history of drinking water containing 600 microgram As/liter. DMPS administration resulted in a tripling of the monomethylarsonic acid percentage and a halving of the dimethylarsinic acid percentage as related to total urinary As. Because South American animals studied were deficient in arsenite methyltransferase, a hypothesis is presented that arsenite and arsenite methyltransferase may have had a role in the evolution of some South American animals. ImagesFigure 1Figure 3Figure 4Figure 6Figure 7Figure 8Figure 9
Effect of fibrinogen on blood coagulation detected by optical coherence tomography

Our previous work demonstrated that an optical coherence tomography (OCT) technique and the parameter 1/e light penetration depth (d1/e) were able to characterize the whole blood coagulation process in contrast to existing optical tests that are performed on plasma samples. To evaluate the feasibility of the technique for quantifying the effect of fibrinogen (Fbg) on blood coagulation, a dynamic study of d1/e of blood in various Fbg concentrations was performed in static state. Two groups of blood samples of hematocrit (HCT) in 35, 45, and 55% were reconstituted of red blood cells with: 1) treated plasma with its intrinsic Fbg removed and commercial Fbg added (0–8 g L−1); and 2) native plasma with commercial Fbg added (0–8 g L−1). The results revealed a typical behavior due to coagulation induced by calcium ions and the clotting time is Fbg concentration-dependent. The clotting time was decreased by the increasing amount of Fbg in both groups. Besides, the blood of lower HCT with various levels of Fbg took shorter time to coagulate than that of higher HCT. Consequently, the OCT method is a useful and promising tool for the detection of blood-coagulation processes induced with different Fbg levels.
A Hand Gesture Recognition Model Based on Semi-supervised Learning

The traditional vision based hand gesture recognition technology requires a lot of light environment and backgrounds. Focused on these above problems, this paper presents a new hand gesture recognition model, in which, the unsupervised sparse auto-encoder neural network model is applied to train the image patches, in order to extract the edge feature that is the weight, and the pooled features are used as the input of the classifier for classification. The fine turning for the parameter of the entire net is to improve the classification accuracy finally.
Stable isotope deltas: tiny, yet robust signatures in nature

Although most of them are relatively small, stable isotope deltas of naturally occurring substances are robust and enable workers in anthropology, atmospheric sciences, biology, chemistry, environmental sciences, food and drug authentication, forensic science, geochemistry, geology, oceanography, and paleoclimatology to study a variety of topics. Two fundamental processes explain the stable isotope deltas measured in most terrestrial systems: isotopic fractionation and isotope mixing. Isotopic fractionation is the result of equilibrium or kinetic physicochemical processes that fractionate isotopes because of small differences in physical or chemical properties of molecular species having different isotopes. It is shown that the mixing of radioactive and stable isotope end members can be modelled to provide information on many natural processes, including 14C abundances in the modern atmosphere and the stable hydrogen and oxygen isotopic compositions of the oceans during glacial and interglacial times. The calculation of mixing fractions using isotope balance equations with isotope deltas can be substantially in error when substances with high concentrations of heavy isotopes (e.g. 13C, 2H, and 18O ) are mixed. In such cases, calculations using mole fractions are preferred as they produce accurate mixing fractions. Isotope deltas are dimensionless quantities. In the International System of Units (SI), these quantities have the unit 1 and the usual list of prefixes is not applicable. To overcome traditional limitations with expressing orders of magnitude differences in isotope deltas, we propose the term urey (symbol Ur), after Harold C. Urey, for the unit 1. In such a manner, an isotope delta value expressed traditionally as−25 per mil can be written as−25 mUr (or−2.5 cUr or−0.25 dUr; the use of any SI prefix is possible). Likewise, very small isotopic differences often expressed in per meg ‘units’ are easily included (e.g. either+0.015 ‰ or+15 per meg can be written as+15 μUr.