Miracle-dz/UniFAR-FTUs huggingface dataset:
Do 'All-Age' Bicycle Helmet Laws Work? Evidence from Canada

Twenty-one states and the District of Columbia require youths to wear helmets when riding a bicycle, and there has been a push to extend such laws to adults. We provide new evidence on helmet laws by studying Canada using difference-in-differences models and restricted area-identified public health survey data with information on cycling and helmet use for nearly 800,000 individuals from 1994-2014. We first confirm prior patterns from the US that laws requiring youths to wear helmets significantly increased youth helmet use. We then provide the literature’s first comprehensive evidence that ‘all-age’ bicycle helmet laws significantly increased both adult and youth helmet use by 50 to 190 percent relative to pre-reform levels, with larger effects for younger adults, and less-educated adults. All-age helmet laws had modest effects at reducing cycling and increasing in-home exercise during winter months among adults but did not meaningfully affect weight. Finally, we find larger effects of helmet laws at increasing helmet use for adults with children in the household, consistent with role-modeling behavior. Overall our findings confirm that all-age helmet laws can be effective at increasing population helmet use without significant unintended adverse health consequences.
Approximating Eigenvectors by Subsampling

We show that averaging eigenvectors of randomly sampled submatrices efficiently approximates the true eigenvectors of the original matrix under certain conditions on the incoherence of the spectral decomposition. This incoherence assumption is typically milder than those made in matrix completion and allows eigenvectors to be sparse. We discuss applications to spectral methods in dimensionality reduction and information retrieval.
Machine Learning Approaches for Credit Card Fraud Detection

With the extensive use of credit cards, fraud appears as a major issue in the credit card business. It is hard to have some figures on the impact of fraud, since companies and banks do not like to disclose the amount of losses due to frauds. At the same time, public data are scarcely available for confidentiality issues, leaving unanswered many questions about what is the best strategy. Another problem in credit-card fraud loss estimation is that we can measure the loss of only those frauds that have been detected, and it is not possible to assess the size of unreported/undetected frauds. Fraud patterns are changing rapidly where fraud detection needs to be re-evaluated from a reactive to a proactive approach. In recent years, machine learning has gained lot of popularity in image analysis, natural language processing and speech recognition. In this regard, implementation of efficient fraud detection algorithms using machine-learning techniques is key for reducing these losses, and to assist fraud investigators. In this paper logistic regression, based machine learning approach is utilized to detect credit card fraud. The results show logistic regression based approaches outperforms with the highest accuracy and it can be effectively used for fraud investigators.
Why Classification Models Using Array Gene Expression Data Perform So Well: A Preliminary Investigation of Explanatory Factors

Results in the literature of classification models from microarray data often appear to be exceedingly good relative to most other domains of machine learning and clinical diagnostics. Yet array data are noisy, and have very small sample-to-variable ratios. What is the explanation for such exemplary, yet counterintuitive, classification performance? Answering this question has significant implications (a) for the broad acceptance of such models by the medical and biostatistical community, and (b) for gaining valuable insight on the properties of this domain. To address this problem we build several models for three classification tasks in a gene expression array dataset with 12,600 oligonucleotides and 203 patient cases. We then study the effects of: classifier type (kernelbased/non-kernel-based, linear/non-linear), sample size, sample selection within cross-validation, and gene information redundancy. Our analyses show that gene redundancy and classifier choice have the strongest effects on performance. Linear bias in the classifiers, and sample size (as long as kernel classifiers are used) have relatively small effects; train-test sample ratio, and the choice of cross-validation sample selection method appear to have small-to-negligible effects.
Volumetric measurement of the anatomic regurgitant orifice area in mitral regurgitation: Comparison with two-dimensional flow convergence analysis

Mitral effective regurgitant orifice area (EROA) using the flow convergence (FC) method is the current method of choice for quantifying the severity of mitral regurgitation (MR). However, this methodology has limitations, especially in patients with complex mitral valve (MV) pathology. The superior image quality of the transesophageal real-time 3D echocardiography (RT3D-TEE) offers an opportunity for direct visualization and 3D measurement of the anatomic regurgitant orifice area (AROA). Accordingly, we developed a 3D technique to measure AROA from RT3DE-TEE datasets and compared it with the conventional FC derived measurements of EROA. We studied 61 patients, undergoing clinically indicated TEE, with well visualized FC. ROA calculations obtained from TEE images using FC technique (EROA); and zoomed RT3DE-TEE acquisitions using prototype software for direct 3D orifice area measurements (AROA) correlated well (r=0.81) and showed only a non-significant bias (0.05 cm2). In conclusion, visualization of the true, anatomic MV orifice area from RT3DE-TEE images is feasible in most patients. 3D volumetric analysis of AROA may become a useful alternative to quantify MR in patients in whom EROA measurement by FC technique is challenging.
Paracrine Met signaling triggers epithelial–mesenchymal transition in mammary luminal progenitors, affecting their fate

HGF/Met signaling has recently been associated with basal-type breast cancers, which are thought to originate from progenitor cells residing in the luminal compartment of the mammary epithelium. We found that ICAM-1 efficiently marks mammary luminal progenitors comprising hormone receptor-positive and receptor-negative cells, presumably ductal and alveolar progenitors. Both cell populations strongly express Met, while HGF is produced by stromal and basal myoepithelial cells. We show that persistent HGF treatment stimulates the clonogenic activity of ICAM1-positive luminal progenitors, controlling their survival and proliferation, and leads to the expression of basal cell characteristics, including stem cell potential. This is accompanied by the induction of Snai1 and Snai2, two major transcription factors triggering epithelial–mesenchymal transition, the repression of the luminal-regulatory genes Elf5 and Hey1, and claudin down-regulation. Our data strongly indicate that paracrine Met signaling can control the function of luminal progenitors and modulate their fate during mammary development and tumorigenesis. DOI: http://dx.doi. org/10.7554/eLife.06104. 001
An effective machine learning algorithm using momentum scheduling

This paper proposes a new algorithm to improve learning performance in support vector machine by using the kernel relaxation and the dynamic momentum. Compared with the static momentum, the dynamic momentum is simultaneously obtained by the learning process of pattern weight and reflected into different momentum by the current state. Therefore, the proposed dynamic momentum algorithm can effectively control the convergence rate and performance. The experiment using SONAR data shows that the proposed algorithm has better convergence rate and performance than the kernel relaxation using static momentum.
Spectral techniques applied to sparse random graphs

We analyze the eigenvalue gap for the adjacency matrices of sparse random graphs. Let λ1 ≥ … ≥ λn be the eigenvalues of an n‐vertex graph, and let λ = max[λ2,|λn|]. Let c be a large enough constant. For graphs of average degree d = c log n it is well known that λ1 ≥ d, and we show that $\lambda = O(\sqrt{d})$. For d = c it is no longer true that $\lambda = O(\sqrt{d})$, but we show that by removing a small number of vertices of highest degree in G, one gets a graph G′ for which $\lambda = O(\sqrt{d})$. Our proofs are based on the techniques of Friedman Kahn and Szemeredi from STOC 1989, who proved similar results for regular graphs. Our results are useful for extending the analysis of certain heuristics to sparser instances of NP‐hard problems. We illustrate this by removing some unnecessary logarithmic factors in the density of k‐SAT formulas that are refuted by the algorithm of Goerdt and Krivelevich from STACS 2001. © 2005 Wiley Periodicals, Inc. Random Struct. Alg. , 2005
SAT03-3: Joint Time Slot Optimization and Fair Bandwidth Allocation for DVB-RCS Systems

This paper introduces a novel operational framework for the problem of time slot assignment in a digital video broadcast-return channel via satellite (DVB-RCS) system. The approach is compliant with the latest technical specifications emitted by the European telecommunications standards institute (ETSI) about quality of service (QoS) in satellite earth stations and systems (SES). It is a cross-layer MAC-PHY optimization approach sustained by the powerful framework of convex optimization. The paper proposes a hierarchical dynamic bandwidth allocation approach, which is motivated by the computational complexity of the single-step solution. More specifically, we obtain and analyze the optimal time duration of the time slots and jointly, we make a fair allocation of slots to areas, which is the highest level in the bandwidth allocation hierarchy. Results show up to a 10% increase in transported capacity.
Embedded all relevant feature selection with Random Ferns

Many machine learning methods can produce variable importance scores expressing the usability of each feature in context of the produced model; those scores on their own are yet not sufficient to generate feature selection, especially when an all relevant selection is required. Although there are wrapper methods aiming to solve this problem, they introduce a substantial increase in the required computational effort. In this paper I investigate an idea of incorporating all relevant selection within the training process by producing importance for implicitly generated shadows, attributes irrelevant by design. I propose and evaluate such a method in context of random ferns classifier. Experiment results confirm the effectiveness of such approach, although show that fully stochastic nature of random ferns limits its applicability either to small dimensions or as a part of a broader feature selection procedure.
Robust Object Replication in a DHT Ring

There have been a lot of studies on distributed storage systems and peer-to-peer file systems based on distributed hash tables (DHTs), in which nodes have global unique identifiers generated by a hash function. Since such distributed systems are built on top of a heterogeneous and unreliable infrastructure, replication techniques are often used to improve object availability. However, typical consecutive replication technique provided by DHTs can encounter replication failures caused by storage imbalance due to some reasons such as storage heterogeneity, various file size distribution, or insert rush to some ID regions. In this project, we develop heuristics to provide robust object replication by exploring more nodes than the traditional replication technique. According to the simulation result conducted on PlanetSim, the suggested heuristics significantly diminish replication failure rate with a little overhead. In addition, we present how to maintain replicas with the suggested heuristics in churn situations which is pretty common in wide-area distributed systems.
Social and political activism amongst British Sikhs: Responses to issues of equality and human rights – a new way forward?

ABSTRACT This article discusses two key issues relating to activism amongst British Sikhs. The exploration focuses upon the mobilisation of Sikhs at rallies and protests surrounding human rights issues, as well as their overall objection to caste legislation in British Law. The revelations surrounding the British Government’s involvement in Operation Bluestar came as a huge shock not only to British Sikhs but also to Sikhs worldwide. This paper will discuss whether the British Sikh community has taken on a fresh approach when confronted with issues surrounding equality and human rights and will explore how youth led Sikh groups and organisations have responded to contemporary challenges by using Sikhi to encourage activism amongst British Sikhs.
Pancreatic-Duodenal Homeobox 1 Regulates Expression of Liver Receptor Homolog 1 during Pancreas Development

ABSTRACT Liver receptor homolog 1 (LRH-1) and pancreatic-duodenal homeobox 1 (PDX-1) are coexpressed in the pancreas during mouse embryonic development. Analysis of the regulatory region of the human LRH-1 gene demonstrated the presence of three functional binding sites for PDX-1. Electrophoretic mobility shift assays and chromatin immunoprecipitation analysis showed that PDX-1 bound to the LRH-1 promoter, both in cultured cells in vitro and during pancreatic development in vivo. Retroviral expression of PDX-1 in pancreatic cells induced the transcription of LRH-1, whereas reduced PDX-1 levels by RNA interference attenuated its expression. Consistent with direct regulation of LRH-1 expression by PDX-1, PDX-1−/− mice expressed smaller amounts of LRH-1 mRNA in the embryonic pancreas. Taken together, our data indicate that PDX-1 controls LRH-1 expression and identify LRH-1 as a novel downstream target in the PDX-1 regulatory cascade governing pancreatic development, differentiation, and function.
Enhanced binding of peptide antigen to purified class II major histocompatibility glycoproteins at acidic pH

Helper T lymphocytes recognize peptide antigens stably associated with class II major histocompatibility complex (MHC) glycoproteins on the surface of antigen-presenting cells and serve to regulate a wide variety of immune responses. A previous study from our laboratory had demonstrated that the functional association of various peptide antigens with the antigen-presenting cell membrane was increased at pH 5 as compared to pH 7, consistent with the potential role of acidic endosomal compartments in antigen processing. The mechanism for this effect was not determined. In the present study, assays using purified class II glycoprotein were used to further define this mechanism. The potential requirement for pH-dependent interactions involving non-MHC membrane components was excluded in functional assays with purified class II reconstituted in artificial membranes containing only neutral phospholipids and cholesterol. The association of HEL(104-120) with I- Ed, and OVA(323-339) with I-Ad, was increased at pH 5, as measured by activation of specific T cell hybridomas. An enzyme immunoassay was developed to measure the binding of biotin-labeled peptides to purified class II in detergent micelles. The pH dependence of binding paralleled our previous functional results. Optimum binding of biotin-HEL(104-120) to I-Ed was observed at pH approximately 4.5, whereas maximum binding of biotin-Myo(106-118) to I-Ad occurred at pH approximately 5.5. The latter peptide also bound weakly to I-Ed, but with a pH dependence similar to that observed using HEL(104-120). Further experiments with biotin-HEL(104-120)/I-Ed indicated that both the apparent affinity and the apparent concentration of peptide-binding sites are increased as hydrogen ion concentration is increased from pH 7 to pH 5. The effect of pH in this range was largely reversible and was not associated with a change in peptide dissociation that could be measured with our assay system. Binding was not inhibited in the presence of 1.5 M NaCl, suggesting that electrostatic interactions between HEL(104-120) and I- Ed are not essential for binding. It is proposed that protonation of a critical group(s) in the class II molecule regulates its capacity to form stable complexes with peptide. However, this effect alone does not fully account for the rapid kinetics of peptide binding observed in experiments with intact antigen-presenting cells.
Experiments on using semantic distances between words in image caption retrieval

Traditional approaches to information retrieval are based upon representing a user's query as a bag of query terms and a document as a bag of index terms and computing a degree of similarity between the two based on the overlap or number of query terms in common between them. Our long-term approach to IR applications is based upon pre-computing semantically-based word-word similarities, work which is described elsewhere, and using these as part of the document-query similarity measure. A basic premise of our word-to-word similarity measure is that the input to this computation is the correct or intended word sense but in information retrieval applications, automatic and accurate word sense disambiguation remains an unsolved problem. In this paper we describe our (cid:12)rst successful application of these ideas to an information retrieval application, speci(cid:12)-cally the indexing and retrieval of captions describing the content of images. We have hand-captioned 2714 images and to circumvent, for the time being, the problems raised by word sense disambiguation, we manually disambiguated polysemous words in captions. We have also built a collection of 60 queries and for each, determined relevance assessments. Using this environment we were able to run experiments in which we varied how the query-caption similarity measure used our pre-computed word-word semantic distances. Our experiments, reported in the paper, show signi(cid:12)cant improvement for this environment over the more traditional approaches to information retrieval.
Seroprevalence of Antibodies to Avian Influenza A (H5) and A (H9) Viruses among Market Poultry Workers, Hanoi, Vietnam, 2001

Background The frequency of avian influenza A virus infections among poultry workers is not well understood. Methods A seroprevalence study of market poultry workers and persons without occupational poultry exposure was conducted during 2001 in Hanoi, Vietnam. Sera were tested for avian influenza H5 and H9 antibodies by microneutralization and Western blot assays. Results Seroprevalence of H5 and H9 antibodies was 4% and 3% in poultry workers and 1% and 3.5% in non-poultry workers, respectively. Conclusions Seroprevalence of H5 and H9 antibodies was low among Hanoi market poultry workers in 2001, but can serve as a baseline for additional studies.
Reduction in Topoisomerase II Activity Differentiation of Human Leukemia Cells Associated with a Novobiocin-and Phorbol-12-myristate-13-acetate-induced Updated

Studies were conducted to determine the possible involvement of DNA topoisomerase II (Topo II) in the induction of differentiation in two human promyeloc)tic 111 (ill leukemia cell variants that are either sus ceptible or resistant to differentiation induced by phorbol-12-myristate13-acetate (I'M \). a protein kinase C activator. The acquisition of maturation markers and changes in the activity, level, and phosphorylation of Topo II were determined after treatment with either novobiocin, a Topo II inhibitor, or I'MA. Novobiocin at 50-150 MMinduced differ entiation in the 111-20? cells but not in the HL-525 cells, although both cell types were equally susceptible to novobiocin-evoked cytotoxicity. In both cell types, novobiocin induced similar reductions in topoisomerase I activity but different reductions in Topo II activity. Treatment with novobiocin at 150 n\\ for 6 h or at 2 HIMfor 30 min resulted in a 4-fold or higher reduction in Topo II activity in the differentiation-susceptible III -2(1? cells but not in the differentiation-resistant HL-525 cells. A differential response in Topo II activity was also observed after treatment with I'M \. The novobiocin-evoked decrease in Topo II activity seems to be due to an enhanced enzyme proteolysis, whereas the PMA-elicited decrease in Topo II activity is associated with an increase in Topo II phosphor) lai ion. l-(5-Isoquinolinesulfonyl)-2-methylpiperazine, which is an inhibitor of protein kinases, including protein kinase C, diminished the novobiocin-elicited proteolysis of Topo II and the PMA-induced Topo II phosphorylation, as well as the decrease in Topo II activity and the acquisition of differentiation markers induced by either novobiocin or PMA. These results suggest that induction of differentiation in HL-60 cells by novobiocin or PMA is associated with a reduction in Topo II activity, mediated directly or indirectly by a protein kinase(s), perhaps protein kinase C.
Physically Based Deformable Models in Computer Graphics

Physically based deformable models have been widely embraced by the Computer Graphics community. Many problems outlined in a previous survey by Gibson and Mirtich have been addressed, thereby making these models interesting and useful for both offline and real‐time applications, such as motion pictures and video games. In this paper, we present the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass‐spring systems, mesh‐free methods, coupled particle systems and reduced deformable models‐based on modal analysis. For completeness, we also make a connection to the simulation of other continua, such as fluids, gases and melting objects. Since time integration is inherent to all simulated phenomena, the general notion of time discretization is treated separately, while specifics are left to the respective models. Finally, we discuss areas of application, such as elastoplastic deformation and fracture, cloth and hair animation, virtual surgery simulation, interactive entertainment and fluid/smoke animation, and also suggest areas for future research.
Automapper : Relational Database Semantic Translation using OWL and SWRL

General purpose query interfaces to relational databases can expose vast amounts of content to the Semantic Web. In this paper, we discuss Automapper, a tool that automatically generates data source and mapping ontologies using OWL and SWRL. We also describe the use of these ontologies in our Semantic Distributed Query architecture, an implementation for mapping RDF queries to disparate data sources, including SQL-compliant databases, using SPARQL as the query language. This paper covers Automapper functionality that exploits some of the expressive nature of OWL to produce more accurate translations. A comparison with related work on Semantic Web access to relational databases is
E- and B-mode mixing from incomplete knowledge of the shear correlation

Context. Aims. We quantify the mixing of the measured cosmic-shear E- and B-modes caused by the lack of shear-correlation measurements on small and large scales, arising from a lack of close projected galaxy pairs and the finite field size, respectively. Methods. We calculate the aperture-mass statistics $\langle M_{\rm ap, \perp}^2 \rangle$ and the E-/B-mode shear-correlation functions $\xi_{\rm E, B \pm}$ where small- and large-scale cutoffs are taken into account. We assess the deviation of the obtained E-mode to the true E-mode and the introduction of a spurious B-mode. Results. The measured aperture-mass dispersion is underestimated by more than 10% on scales smaller than 12 times the lower cutoff. For a precise measurement of the E- and B-modes at the percent level using a combination of $\xi_{\rm E, B +}$ and $\xi_{\rm E, B -}$, a field as large as 7 (2.4) degrees is necessary for ground-based (space-based) observations.