Miracle-dz/UniFAR-FTUs huggingface dataset:
Antidiabetic therapies affect risk of pancreatic cancer.

BACKGROUND & AIMS Antidiabetic drugs have been found to have various effects on cancer in experimental systems and in epidemiologic studies, although the association between these therapeutics and the risk of human pancreatic cancer has not been explored. We investigated the effect of antidiabetic therapies on the risk of pancreatic cancer. METHODS A hospital-based case-control study was conducted at M. D. Anderson Cancer Center from 2004 to 2008 involving 973 patients with pancreatic adenocarcinoma (including 259 diabetic patients) and 863 controls (including 109 diabetic patients). Information on diabetes history and other risk factors was collected by personal interview. The frequencies of use of insulin, insulin secretagogues, metformin, and other antidiabetic medications among diabetic patients were compared between cases and controls. The risk of pancreatic cancer was estimated using unconditional logistic regression analysis. RESULTS Diabetic patients who had taken metformin had a significantly lower risk of pancreatic cancer compared with those who had not taken metformin (odds ratio, 0.38; 95% confidence interval, 0.22-0.69; P = .001), with adjustments for potential confounders. This difference remained statistically significant when the analysis was restricted to patients with a duration of diabetes >2 years or those who never used insulin. In contrast, diabetic patients who had taken insulin or insulin secretagogues had a significantly higher risk of pancreatic cancer compared with diabetic patients who had not taken these drugs. CONCLUSIONS Metformin use was associated with reduced risk, and insulin or insulin secretagogue use was associated with increased risk of pancreatic cancer in diabetic patients.
Diffusion Tensor MR Imaging Evaluation of Callosal Abnormalities in Schizophrenia: A Meta-Analysis

Widespread white matter (WM) abnormalities have been found in patients with schizophrenia. Corpus callosum (CC) is the key area that connects the left and right brain hemispheres. However, the results of studies considering different subregions of the CC as regions of interest in patients with schizophrenia have been inconsistent. To obtain a more consistent evaluation of the diffusion characteristics change of the corpus callosum (CC) related to schizophrenia. A meta-analysis involving fractional anisotropy (FA) values in the CC of 729 schizophrenic subjects and 682 healthy controls from 22 studies was conducted. Overall FA values in the CC of the schizophrenic group were less than that of the healthy control group [weighted mean difference (WMD) = -0.021,P< 0.001]. So were the FA values in the genus region (WMD = -0.019, P< 0.001) and the splenium region (WMD = -0.020, P< 0.001) of the CC respectively. The FA reduction was also significant in subjects with chronic schizophrenia (WMD = -0.032, P< 0.001) and first-episode schizophrenia (WMD = -0.014, P = 0.001). In present study, we demonstrated an overall FA decrease in the CC of schizophrenic patients. In the two subgroup analyses of the genu vs splenium region and chronic vs first-episode schizophrenia, the decrease of all groups was significant. Further studies with more homogenous populations and standardized DTI protocols are needed to confirm and extend these findings.
Counter-Terrorism and Counter-Extremism: The UK Policy Spirals

The thesis of this paper is that policy spirals have developed around 'Prevent' and 'Counter Extremism'. A 'policy spiral' describes a policy which lacks clear initial purpose or subsequent direction, progression, control and reflection. A policy spiral is therefore susceptible to unresolved contradictions or gaps, dramatic direction changes, and uncertain outcomes. As a result, policy spirals arise from inexact and contested meanings, objectives, and mechanisms which generate dynamics of suspicion as much as persuasion. Spirals can readily spin out of control, since they are not 'unidirectional and deterministic'. The term, 'policy spiral', is coined here to contrast with the more familiar term, 'policy cycle', which follows a more assured progression through stages. One standard conception of policy cycle sequences depicts them as involving: 'agenda-setting, policy formulation, decision making, implementation, and evaluation'. This heuristic concept of a policy cycle has its critics and limits but remains a useful yardstick for analysing and assessing policy processes. The policy cycle notion here highlights deficiencies in the 'Prevent' and 'Counter Extremism' policies. They lack several distinct stages of a policy cycle and so suffer destabilisation into a 'policy spiral' in two ways. The first is that each policy lacks the internal stability which can be acquired through solid agenda-setting, policy formulation, and decision making, or through supportive structures to implement and refine the policy. The second aspect of turbulence arises through the interaction of the two policies; rather than mutual reinforcement, conflict arises from open texture and uncertain borders. This paper will plot and explain the policy spirals by asking: is it necessary and legitimate to embark upon 'Prevent' and 'Counter Extremism’; what has been done to date within 'Prevent'; and what future paths are being plotted within 'Counter Extremism'?
ePadEvo: A tool for the detection of behavioral design patterns

In this demonstration we present ePADevo, an Eclipse plug-in for recovering design pattern instances from object-oriented source code. The tool is able to recover design pattern instances through a static analysis performed on a data model extracted from source code, and a dynamic analysis performed through the instrumentation and the monitoring of the software system. Dynamic analysis is performed with automatically generated test cases exploiting the EvoSuite tool.
Statistical Modeling of Large-Scale Scientific Simulation Data

With the advent of massively parallel computer systems, scientists are now able to simulate complex phenomena (e.g., explosions of a stars). Such scientific simulations typically generate large-scale data sets over the spatio-temporal space. Unfortunately, the sheer sizes of the generated data sets make efficient exploration of them impossible. Constructing queriable statistical models is an essential step in helping scientists glean new insight from their computer simulations. We define queriable statistical models to be descriptive statistics that (1) summarize and describe the data within a user-defined modeling error, and (2) are able to answer complex range-based queries over the spatiotemporal dimensions. In this chapter, we describe systems that build queriable statistical models for large-scale scientific simulation data sets. In particular, we present our Ad-hoc Queries for Simulation (AQSim) infrastructure, which reduces the data storage requirements and query access times by (1) creating and storing queriable statistical models of the data at multiple resolutions, and (2) evaluating queries on these models of the data instead of the entire data set. Within AQSim, we focus on three simple but effective statistical modeling techniques. AQSim's first modeling technique (called univariate mean modeler) computes the ''true'' (unbiased) mean of systematic partitions of the data. AQSim'smore » second statistical modeling technique (called univariate goodness-of-fit modeler) uses the Andersen-Darling goodness-of-fit method on systematic partitions of the data. Finally, AQSim's third statistical modeling technique (called multivariate clusterer) utilizes the cosine similarity measure to cluster the data into similar groups. Our experimental evaluations on several scientific simulation data sets illustrate the value of using these statistical models on large-scale simulation data sets. « less
Text Retrieval in Small World P2P Networks

For the flooding problem in Gnutella, a text retrieval method is proposed in unstructured P2P networks based on small world models. Each node in the P2P networks maintains several long-link neighbors and short-link neighbors to build a small world P2P networks. Neighbors update is processed during the query and response. And after each query, weights of the words in documents of neighbor nodes will be revised. This makes it easy to find out the networks topology and contents of other nodes. Experiment results show that the small world P2P networks outperform Gnutella-like networks in the recall rate and search efficiency.
Human sensors: Case-study of open-ended community sensing in developing regions

With the growing number of cities and population, continuous monitoring of city's infrastructure and automated collection of day-to-day events (such as traffic jam) is essential and can help in improving life style of citizens. It is extremely costly and ineffective to install hardware sensors to sense these events in developing regions. Due to advent of smartphones, citizens can play role of sensors and actively participate in collection of the events which can be shared with others for information or can be used in decisions which affects city development. In this paper, we describe an architecture of crowdsensing testbed for capturing and processing events affecting citizens in cities in India. One of the design principle of our testbed is that it encourages users to do an open-ended sensing under five broad categories: Civic complaints, traffic, neighbourhood issues, emergency and others. As part of testbed, we allow events submissions from different submission modes i.e. mobile application, SMSes and web. Our mobile application exploits different sensing interfaces provided by today's smartphones to add contextual data with event reports such as images, audio, fine-grained location etc. Proposed testbed is used by university students across India to report event happening around them. Finally, we describe the data collected and uncover some of challenges and opportunities which may help future designs of crowdsensing based systems.
Basis Assets

This paper proposes a new method to form basis assets with which to represent investors' opportunity sets and evaluate the goodness-of-fit of asset pricing models. We use return correlations to form a measure of distance between securities, as in Ormerod and Mounfield (2000), and use this distance measure to sort securities into portfolios. We compare the inferences drawn from this set of basis assets with those drawn from other benchmark portfolios commonly used in the literature such as beta and size-sorted portfolios and the Fama and French (1993) size and book-to-market sorted portfolios. Specifically, we compare the results of spanning tests, tests of asset pricing models and inferences about optimal portfolios. The results suggest that the set of basis assets formed by clustering on historical correlations in returns does at least as well as characteristic-based portfolios at generating a proxy for an investor's opportunity set. The proposed set of portfolios also appears capable of generating measures of risk-return trade-off that are estimated with lower error. Finally, we compare the cluster portfolios to principal components extracted from the same sample period, and find that the cluster portfolios generate slightly higher out-of-sample dispersion in mean returns, a slightly lower Sharpe ratio and more stable weights on individual securities.
PRIMe Update: Innovative Content for Plant Metabolomics and Integration of Gene Expression and Metabolite Accumulation

PRIMe (http://prime.psc.riken.jp/), the Platform for RIKEN Metabolomics, is a website that was designed and implemented to support research and analyses ranging from metabolomics to transcriptomics. To achieve functional genomics and annotation of unknown metabolites, we established the following PRIMe contents: MS2T, a library comprising >1 million entries of untargeted tandem mass spectrometry (MS/MS) data of plant metabolites; AtMetExpress LC-MS, a database of transcriptomics and metabolomics approaches in Arabidopsis developmental stages (AtMetExpress Development LC-MS) and a data set of the composition of secondary metabolites among 20 Arabidopsis ecotypes (AtMetExpress 20 ecotypes LC-MS); and ReSpect, hybrid reference MS/MS data resources (acquisitions and literature). PRIMeLink is a new web application that allows access to the innovative data resources of PRIMe. The MS2T library was generated from a set of MS/MS spectra acquired using the automatic data acquisition function of mass spectrometry. To increase the understanding of mechanisms driving variations in metabolic profiles among plant tissues, we further provided the AtMetExpress Development LC-MS database in PRIMe, facilitating the investigation of relationships between gene expression and metabolite accumulation. This information platform therefore provides an integrative analysis resource by linking Arabidopsis transcriptome and metabolome data. Moreover, we developed the ReSpect database, a plant-specific MS/MS data resource, which allows users to identify candidate structures from the suite of complex phytochemical structures. Finally, we integrated the three databases into PRIMeLink and established a walk-through link between transcriptome and metabolome information. PRIMeLink offers a bi-directional searchable function, from the gene and the metabolite perspective, to search for targets seamlessly and effectively.
Phylogeny of Branchiopoda (Crustacea) - Character Evolution and Contribution of Uniquely Preserved Fossils

Phylogeny of Branchiopoda (Crustacea) has received intensive attention the last decade and a widely accepted full resolution of the relationships between the major branchiopod taxa is close. Various well-preserved fossil branchiopods (e.g., Castracollis, Lepidocaris, Kazacharthra, Leptodorosida) combine characters from major recent taxa and are therefore necessary for a full understanding of branchiopod phylogeny and evolution. Here is presented a morphology-based phylogenetic analysis of Branchiopoda, which combines recent taxa with the most well-preserved and informative fossils. The analysis results in support of the following clades: Branchiopoda, Sarsostraca (= Anostraca + Lepidocaris), Phyllopoda, Calmanostraca (= Kazacharthra + Notostraca), an unnamed clade consisting of Castracollis and Calmanostraca, Diplostraca, an unnamed clade consisting of Spinicaudata and Cladoceromorpha, Spinicaudata, Cladoceromorpha, Cladocera, and Gymnomera. The character support for all clades is presented, which provides a basis for a discussion of aspects of branchiopod evolution.
Frequency model based crossover operators for genetic algorithms applied to the quadratic assignment problem

The quadratic assignment problem aims to find an optimal assignment of a set of facilities to a set of locations that minimizes an objective function depending on the flow between facilities and the distance between locations. In this paper we investigate a Genetic Algorithm (GA) using new crossover operators to guide the search towards unexplored regions of the search space. First we define a frequency model which keeps in memory a frequency value for each pair of facility and location. Then, relying on the frequency model we propose three new crossover operators to enhance genetic algorithm for the quadratic assignment problem. The first and second ones, called Highest Frequency crossover (HFX) and Greedy Highest Frequency crossover (GHFX), are based only on the frequency values, while the third one, called Highest Frequency Minimum Cost crossover (HFMCX), combines the frequency values with the cost induced by assigning facilities to locations. The experimental results comparing the proposed crossover operators to three efficient crossover operators, namely, One Point crossover (OPX), Swap Path crossover (SPX) and Sequential Constructive crossover (SCX), show effectiveness of our proposed operators both in terms of solution quality and computational time.
A Critical Review of Literature on Experience Rating in Workers’ Compensation Systems

Abstract In this paper we present a review of the English language peer-reviewed literature on experience rating and critically examine the framing of research questions, methodology selection, study findings, the interpretation of results and underlying logic. Two main questions are addressed: what is known about how experience rating motivates employer and worker behaviour? ; what is known about how experience rating affects workplace health and safety? We conducted a comprehensive search of quantitative and qualitative literature on experience rating and claims management. Studies were appraised on several key characteristics (eg central objective, relevance), study quality (eg study design, interpretation of results) and experience-rating findings (eg how it motivates stakeholders, other health and safety incentives, cost-shifting). While some qualitative studies consider claims management, we found that few focus directly on the topic of experience rating. Several of the qualitative studies do not adequately theorise the power relations, socioeconomic context and politics of experience rating. Many of the quantitative studies were based on simplified understandings of human behaviours, and made substantial conclusions from proxy measures used in statistical models. Several studies aggregate data across multiple jurisdictions and pay little attention to the variety of contextual details. This review finds that the social and economic logic of experience rating, as well as the effects of its implementation, is an important and neglected subject in occupational safety and health research. There is still much to be learned about the topic.
GEODESIC DISTANCE-BASED KERNEL CONSTRUCTION FOR GAUSSIAN PROCESS VALUE FUNCTION APPROXIMATION

Finding accurate approximations to state and action value functions is essential in Reinforcement learning tasks on continuous Markov Decision Processes. Using Gaussian processes as function approximators we can simultaneously represent model confidence and generalize to unvisited states. To improve the accuracy of the value function approximation in this article I present a new method of constructing geodesic distance based kernel functions from the Markov Decision process induced graph structure. Using sparse on-line Gaussian process regression the nodes and edges of the graph structure are allocated during on-line learning parallel with the inclusion of new measurements to the basis vector set. This results in a more compact and efficient graph structure and more accurate value function estimates. The approximation accuracy is tested on a simulated robotic control task.
Turning on Myogenin in Muscle: A Paradigm for Understanding Mechanisms of Tissue-Specific Gene Expression

Expression of the myogenin (Myog) gene is restricted to skeletal muscle cells where the transcriptional activator turns on a gene expression program that permits the transition from proliferating myoblasts to differentiating myotubes. The strict temporal and spatial regulation on Myog expression in the embryo makes it an ideal gene to study the developmental regulation of tissue-specific expression. Over the last 20 years, our knowledge of the regulation of Myog expression has evolved from the identification of the minimal promoter elements necessary for the gene to be transcribed in muscle, to a mechanistic understanding of how the proteins that bind these DNA elements work together to establish transcriptional competence. Here we present our current understanding of the developmental regulation of gene expression gained from studies of the Myog gene.
Towards the matrix model of M-theory on a lattice

The Wilson discretization of the dimensionally reduced supersymmetric Yang-Mills theory is constructed. This gives a lattice version of the matrix model of M-theory. An SU(2) model is studied numerically in the quenched approximation for D=4. The system shows canonical scaling in the continuum limit. A clear signal for a prototype of the "black hole to strings" phase transition is found. The pseudocritical temperature is determined and the temperature dependence of the total size of the system is measured in both phases. Further applications are outlined.
Explorer The E 3 ubiquitin ligase activity of Ring 1 B is not essential for early mouse development

The E3 ubiquitin ligase activity of Ring1B is not essential for early mouse development E3 ubiquitin ligase activity of Ring1B is not essential for early mouse development' Genes & Development, vol 29, no. 18. General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact openaccess@ed.ac. uk providing details, and we will remove access to the work immediately and investigate your claim.
Manifold Based Optimization for Single-Cell 3D Genome Reconstruction

The three-dimensional (3D) structure of the genome is important for orchestration of gene expression and cell differentiation. While mapping genomes in 3D has for a long time been elusive, recent adaptations of high-throughput sequencing to chromosome conformation capture (3C) techniques, allows for genome-wide structural characterization for the first time. However, reconstruction of "consensus" 3D genomes from 3C-based data is a challenging problem, since the data are aggregated over millions of cells. Recent single-cell adaptations to the 3C-technique, however, allow for non-aggregated structural assessment of genome structure, but data suffer from sparse and noisy interaction sampling. We present a manifold based optimization (MBO) approach for the reconstruction of 3D genome structure from chromosomal contact data. We show that MBO is able to reconstruct 3D structures based on the chromosomal contacts, imposing fewer structural violations than comparable methods. Additionally, MBO is suitable for efficient high-throughput reconstruction of large systems, such as entire genomes, allowing for comparative studies of genomic structure across cell-lines and different species.
Effects of Tai Chi and Walking Exercises on Weight Loss, Metabolic Syndrome Parameters, and Bone Mineral Density: A Cluster Randomized Controlled Trial

Tai Chi and walking are both moderate-intensity physical activity (PA) that can be easily practiced in daily life. The objective of the study was to determine the effects of these two PAs on weight loss, metabolic syndrome parameters, and bone mineral density (BMD) in Chinese adults. We randomized 374 middle-aged subjects (45.8 ± 5.3 years) into 12-week training (45 minutes per day, 5 days per week) of Tai Chi (n = 124) or self-paced walking (n = 121) or control group (n = 129). On average, Tai Chi and walking groups lost 0.50 and 0.76 kg of body weight and 0.47 and 0.59 kg of fat mass after intervention, respectively. The between-group difference of waist circumference (WC) and fasting blood glucose (FBG) was −3.7 cm and −0.18 mmol/L for Tai Chi versus control and −4.1 cm and −0.22 mmol/L for walking versus control. No significant differences were observed regarding lean mass, blood pressure, triglycerides, total cholesterol, high-density and low-density lipoprotein cholesterol, and BMD compared to control. Change in lean mass, not fat mass or total weight loss, was significantly correlated to the change in BMD. Our results suggest that both of these two PAs can produce moderate weight loss and significantly improve the WC and FBG in Hong Kong Chinese adults, with no additional effects on BMD.