Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Information Extraction of Key Trial Design Elements from Clinical Trial Publications

Clinical trials are one of the most valuable sources of scientific evidence for improving the practice of medicine. The Trial Bank project aims to improve structured access to trial findings by including formalized trial information into a knowledge base. Manually extracting trial information from published articles is costly, but automated information extraction techniques can assist. The current study highlights a single architecture to extract a wide array of information elements from full-text publications of randomized clinical trials (RCTs). This architecture combines a text classifier with a weak regular expression matcher. We tested this two-stage architecture on 88 RCT reports from 5 leading medical journals, extracting 23 elements of key trial information such as eligibility rules, sample size, intervention, and outcome names. Results prove this to be a promising avenue to help critical appraisers, systematic reviewers, and curators quickly identify key information elements in published RCT articles.
Journal of Graph Algorithms and Applications a Binomial Distribution Model for the Traveling Salesman Problem Based on Frequency Quadrilaterals 412 Wang & Remmel a Binomial Distribution Model for Tsp

We study the symmetric traveling salesman problem via frequency graphs. One computes the frequency of edges by computing how many times an edge occurs in an optimal path involving four vertices. The edges that are in the Optimal Hamiltonian Cycle (OHC) have a higher frequency than most edges that are not in the OHC and thus edges with a low frequency can safely be ignored when searching for the optimal solution. A binomial distribution model is introduced for the symmetric traveling salesman problem based on frequency quadrilaterals. When the frequency of each edge is computed with N frequency quadrilaterals, our model suggests that the minimum frequency of an edge in the OHC is Fmin = (min +1)N where 4 3 + 4 3(n−2) < min < 4. This suggests a heuristic to reduce the number of edges that need to be considered in the search for the OHC which is to keep only those edges whose frequencies are ≥ Fmin. We explore this heuristic in several real-world examples.
Energy reduction in cyclic flow shop plants through on-off control of robots

This paper addresses the design of an on-off control strategy for operating robots in a cyclic flow shop plant. The main goal is to properly switch off and on the robots to save energy consumption without any reduction of the plant desired throughput. To fulfill this goal, first mathematical conditions, which characterize movement of parts in the plant and the on-off control for robots, are presented. Then a mathematical model which measures energy reduction in robots is introduced. Constrained to the conditions, a mixed integer linear programming model with the energy monitor as the objective function is developed. Solving this model, the set points for decision parameters are obtained to reduce energy consumption in idle robots. This model is applied to a case study and the related results are presented and discussed.
Changes in angiogenic growth factor levels after gefitinib treatment in non-small cell lung cancer.

BACKGROUND To investigate the changes in angiogenic growth factor expression before and after gefitinib treatment, and the association between this expression and response to gefitinib treatment, we measured circulating levels of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), matrix metalloproteinase (MMP) -2 and -9, and tissue inhibitors of metalloproteinase (TIMP) -1 and -2 in patients with non-small cell lung cancer (NSCLC). METHODS Serum and plasma samples were collected from 52 patients before and after gefitinib treatment. The levels of VEGF, bFGF, MMP-2, MMP-9, TIMP-1 and TIMP-2 were measured using a sandwich enzyme immunoassay kit. RESULTS Of the 52 patients, 17 (32.7%) achieved a partial response, 19 (36.5%) had stable disease and 16 (30.8%) had progressive disease. The levels of VEGF, bFGF, MMP-2, MMP-9, TIMP-1 and TIMP-2 did not change significantly after gefitinib treatment, even in responders. The levels of VEGF in volunteers, responders and non-responders were 384 +/- 86.4, 404 +/- 94.3 and 719 +/- 99.8 pg/ml, respectively. The difference between volunteers and responders was not significant (P = 0.540), while the differences between volunteers and non-responders (P = 0.031), and responders and non-responders (P = 0.028) were significant. CONCLUSIONS Although our results indicate that gefitinib treatment does not affect circulating levels of angiogenic growth factors even in patients who showed a response to gefitinib treatment, low levels of VEGF may predict response to gefitinib treatment in patients with NSCLC.
Health and the Decision to Invest in Education

Summary The paper analyses the relationship between health and education in a two period human capital framework. The resulting substitution and investment effects between health and advanced training work in opposite direction and leave open questions for the empirical part. As econometric model we use a random effects probit model for panel data. Our data consist of 322 individuals for the two years 2004 and 2006. Thereby, we take into account that self-reported measures of health are usually vulnerable to a reporting bias due to anticipation and measurement errors. Estimation results show a dominant substitution effect between different levels of education, indicating that good health implies higher learning efficiency so that the same income can be achieved with lower investment in advanced training. In contrast, we find a dominant investment effect within an educational level, indicating that better health leads individuals with higher education to invest more in additional training.
Title : CAD in mammography : lesion-level vs . case-level analysis of the effects of prompts on human decisions

Title: CAD in mammography: lesion-level vs. case-level analysis of the effects of prompts on human decisions Abstract OBJECT: To understand decision processes in CAD-supported breast screening by analysing how prompts affect readers' judgements of individual mammographic features (lesions). To this end we analysed hitherto unexamined details of reports completed by mammogram readers in an earlier evaluation of a CAD tool. Assessments of lesions were extracted from 2889 reports for 59 cancer cases. Statistical analyses of these data focused on what features readers considered when recalling a cancer case and how readers reacted to CAD prompts. RESULTS: 13.5% of recall decisions were found to be caused by responses to features other than those indicating actual cancer. Effects of CAD: lesions were more likely to be examined if prompted; the presence of a prompt on a cancer increased the probability of both detection and recall especially for less accurate readers in more subtle cases; lack of prompts made cancer features less likely to be detected; false prompts made non-cancer features more likely to be classified as cancer. The apparent lack of impact reported for CAD in some studies is plausibly due to CAD systematically affecting readers' identification of individual features, in a beneficial way for certain combinations of readers and features and a damaging way for others. Mammogram readers do not ignore prompts. Methodologically, assessing CAD by numbers of recalled cancer cases may be misleading.
Affect of network structure on influence maximization in dynamic networks

In this work we examine how density and modularity of dynamic networks affect the choice of influence maximization heuristics and the optimality of the resulting solutions. In recent years, online social networks, such as Facebook and Twitter, have provided real examples for understanding diffusion of information, ideas, and adoption of products in fast evolving networks [1, 8]. Other than social networks, applications like contamination detection in water distribution networks or spread of diseases also inherently rely on the dynamic process of diffusion [5, 6]. In the past, almost all efforts focus on " static " networks [4] in which the ties among nodes remain fixed over time. In recent years, there has been some work done in studying diffusion in " evolutionary " networks, such as co–authorship networks. However, this is also a limiting example of social networks as the assumption here is that links are never lost. Yet, most networks are highly dynamic. In social networks, individuals maintain different connections in different contexts, such as friends or work colleagues and these relationships change with time. Similarly, the animal networks change with age, migration, and risk factors in the environment. Despite all the real world examples, there has been little work done in incorporating these relationship dynamics while analyzing the extent of influence in such networks. And most of the work that has been done focused on designing algorithms or heuristics that work for any general dynamic networks. We analyze the global structure of explicitly dynamic networks for understanding when to employ a sophisticated algorithm vs a simple heuristic. Moreover, we propose simple structural measures that can guide this choice. Specifically, we analyze networks in term of their changing density and community structure to investigate the trends in extent of diffusion of influence. It has long been shown that maximizing the influence in a static network is an NP–hard problem [3]. Even the best approximation is infeasible for very large networks [3]. A number of heuristics have been shown to work very well in practice [7]. However, they do not provide any guarantees of performance. In this work, we use density of a dynamic network as an indicator of influence maximization: (a) when it is necessary to employ a sophisticated yet computationally expensive method? or (b) when even a random set of spread initiators perform as well as the best in expectation for maximizing the spread in the network? and …
Efficient estimation of rare-event kinetics

The efficient calculation of rare-event kinetics in complex dynamical systems, such as the rate and pathways of ligand dissociation from a protein, is a generally unsolved problem. Markov state models can systematically integrate ensembles of short simulations and thus effectively parallelize the computational effort, but the rare events of interest still need to be spontaneously sampled in the data. Enhanced sampling approaches, such as parallel tempering or umbrella sampling, can accelerate the computation of equilibrium expectations massively - but sacrifice the ability to compute dynamical expectations. In this work we establish a principle to combine knowledge of the equilibrium distribution with kinetics from fast "downhill" relaxation trajectories using reversible Markov models. This approach is general as it does not invoke any specific dynamical model, and can provide accurate estimates of the rare event kinetics. Large gains in sampling efficiency can be achieved whenever one direction of the process occurs more rapid than its reverse, making the approach especially attractive for downhill processes such as folding and binding in biomolecules.
Thermal management of ARM SoCs using Linux CPUFreq as cooling device

While the performance of modern ARM System on Chips (SoCs) increases significantly than the previous generation, the power dissipation and on-chip temperature becomes dramatically high. The existing thermal management solutions are mostly built on Advanced Configuration and Power Interface (ACPI) and Dynamic Thermal Management (DTM) model for traditional desktop and server machines. They do not directly apply on mobile ARM SoCs as it is. This paper proposes a solution for thermal management on high performance ARM SoCs based on a model which is built on some ACPI thermal concepts and DTM DVFS mechanism. The thermal model is implemented on Freescale i.MX6Q SoC with Linux Kernel 3.6. It uses a lot of help from Linux thermal infrastructural and CPUFreq subsystem, and builds a cooling device backed by CPUFreq driver. A comparison testing on i.MX6Q shows that the cooling device can effectively controls the on-chip temperature around a designed threshold value. The thermal model is built on generic thermal hardware support and common software infrastructural, and therefore should work universally for other ARM SoCs.
The effects of a disc field on bulge surface brightness

Collisionless N-body simulations are used in an effort to reproduce the observed tendency of the surface brightness profile of bulges to change progressively from an R-1/4 law to an exponential, going from early-to late-type spirals. A possible cause for this is the formation of the disc, later in the history of the galaxy, and this is simulated by applying on the N-body bulge the force field of an exponential disc the surface density of which increases with time. It is shown that n, the index of the Sersic law Sigma(n)(r) proportional to exp[-(r/r(0))(1/n)] that best describes the surface brightness profile, does indeed decrease from 4 (de Vaucouleurs law) to smaller values; this decrease is larger for more massive and more compact discs. A large part of the observed trend of n with B/D ratio is explained, and many of the actual profiles can be matched exactly by the simulations. The correlation between the disc scalelength and bulge effective radius, used recently to support the 'secular evolution' origin for bulges, is also shown to arise naturally in a scenario like this. This mechanism, however, saturates at around n = 2 and exponential bulges cannot be produced; as n gets closer to 1,the profile becomes increasingly robust against a disc field. These results provide strong support to the old-bulge hypothesis for the early-type bulges. The exponential bulges, however, remain essentially unexplained; the results here suggest that they did not begin their Lives as R-1/4 spheroids, and hence were probably formed, at least in part, by different processes from those of early-type spirals.
Replicating the Classic Sugarscape in MASON

Replication is essential in science and agent-based computational social science is no exception. We present results from a replication of the Sugarscape model (Eptstein and Axtell, 1996) as initially presented in Growing Artificial Societies (GAS ). Sugarscape is a classic agent-based model and contemporary simulation toolkits usually only have a partial replication consisting of a few core model rules without documenting simulation outcomes; code supplied with Repast, Swarm, and NetLogo, for example implement very few of the rules in Sugarscape. By contrast, we demonstrate a detailed replication of Sugarscape in the MASON (Multi-Agent Simulator of Neighborhoods and Networks) environment, and describe various outcomes such migration waves. For major outcomes documenteed in GAS, we describe the degree to which we replicated those results and conclude by outlining major challenges in replication activities and the young field of agent-based modeling in general.
Combining Multi-Material Rapid Prototyping and Pseudo-Rigid Body Modeling for a new compliant mechanism

Multi-Material Rapid Prototyping (MM-RP) is a promising fabrication process for compliant mechanisms, for instance when compactness is a concern. The Pseudo-Rigid Body Model (PRBM) approach is well-known for the synthesis of compliant mechanisms. It is usually based on the use of compliant joints to provide the mechanism mobilities. In this paper, we propose the HSC joint as a new type of revolute compliant joint that is well adapted to MM-RP, and that offers interesting properties in terms of stiffness and range of motion. Based on the HSC joint, a new compliant mechanism, suitable for interventional MRI, is introduced with assessment of a first prototype that is entirely made out of a single polymer part. The interest is twofold. First, the device constitutes a promising solution in this medical context. Second, the impact of the use of MM-RP in combination with PRBM can be evaluated, and their use is discussed as a conclusion.
Association between the Catechol-O-Methyltransferase (COMT) Val158Met Polymorphism and Alexithymia in Patients with Obsessive-Compulsive Disorder

Purpose Alexithymia, defined as a deficit in the ability to recognize and describe one's own feelings, may be related to the development and maintenance of obsessive-compulsive symptoms. The aim of this study was to evaluate the association between the catechol-O-methyltransferase (COMT) Val158Met polymorphism and alexithymia in patients with obsessive-compulsive disorder (OCD). Materials and Methods We recruited 244 patients with OCD (169 males, 75 females). Alexithymia was assessed using the 20-item Toronto Alexithymia Scale (TAS-20), and genotyping of the COMT Val158Met polymorphism was evaluated. Results Patients with the COMT Val/Val genotype had significantly higher total and "difficulty identifying feelings" (DIF) subdimension scores than those with the Val/Met or Met/Met genotypes. Patients with the COMT Val/Val genotype had significantly higher "difficulty describing feelings" (DDF) subdimension scores than those with the COMT Val/Met genotype. However, there were no differences in the scores for the "externally oriented thinking" (EOT) subdimension among the three genotypes. Conclusion These results indicate that the high-activity Val allele of the COMT Val158Met polymorphism is associated with increased alexithymic traits in patients with OCD. The present finding suggests that alexithymia is an endophenotype of OCD that is mediated by the COMT Val158Met polymorphism.
Differential Histopathological and Behavioral Outcomes Eight Weeks after Rat Spinal Cord Injury by Contusion, Dislocation, and Distraction Mechanisms

Abstract The objective of this study was to compare the long-term histological and behavioral outcomes after spinal cord injury (SCI) induced by one of three distinct biomechanical mechanisms: dislocation, contusion, and distraction. Thirty male Sprague-Dawley rats were randomized to incur a traumatic cervical SCI by one of these three clinically relevant mechanisms. The injured cervical spines were surgically stabilized, and motor function was assessed for the following 8 weeks. The spinal cords were then harvested for histologic analysis. Quantification of white matter sparing using Luxol fast blue staining revealed that dislocation injury caused the greatest overall loss of white matter, both laterally and along the rostrocaudal axis of the injured cord. Distraction caused enlarged extracellular spaces and structural alteration in the white matter but spared the most myelinated axons overall. Contusion caused the most severe loss of myelinated axons in the dorsal white matter. Immunohistochemistry for the neuronal marker NeuN combined with Fluoro Nissl revealed that the dislocation mechanism resulted in the greatest neuronal cell losses in both the ventral and dorsal horns. After the distraction injury mechanism, animals displayed no recovery of grip strength over time, in contrast to the animals subjected to contusion or dislocation injuries. After the dislocation injury mechanism, animals displayed no improvement in the grooming test, in contrast to the animals subjected to contusion or distraction injuries. These data indicate that different SCI mechanisms result in distinct patterns of histopathology and behavioral recovery. Understanding this heterogeneity may be important for the future development of therapeutic interventions that target specific neuropathology after SCI.
THE ADAPTIVE ANTENNA DEMONSTRATOR

The Adaptive Antenna Demonstrator (AAD) project is an eight element antenna array that is processed adaptively such that external radio-frequency interference is minimised. AAD is the first stage of the Square Kilometer Array Interferometer (SKAI) project which will ultimately be the next generation of radio telescopes. The AAD experimental setup is described in this paper, including the anechoic chamber, positioner, system electronics and the Minimum Variance (MV) beamforming technique. Results from AAD are then presented to illustrate the capabilities of adaptive processing and also future developments for the system discussed.
Smart Money: The Forecasting Ability of CFTC Large Traders in Agricultural Futures Markets

The forecasting content of the Commodity Futures Trading Commissionâ€™s Commitments of Traders (COT) report is investigated. Bivariate Granger causality tests show very little evidence that tradersâ€™ positions are useful in forecasting (leading) returns in 10 agricultural futures markets. However, there is substantial evidence that traders respond to price changes. In particular, noncommercial traders display a tendency for trend following. The other trader classifications display mixed styles, perhaps indicating those trader categories capture a variety of traders. The results generally do not support use of the COT data in predicting price movements in agricultural futures markets.
A Generative Model for Identifying Target Companies of Microblogs

Microblogging services have attracted hundreds of millions of users to publish their status, ideas and thoughts, everyday. These microblog posts have also become one of the most attractive and valuable resources for applications in different areas. The task of identifying the main targets of microblogs is an important and essential step for these applications. In this paper, to achieve this task, we propose a novel method which converts the target company identification problem to the translation process from content to targets. We introduce a topic-specific generative method to model the translation process. Topic specific trigger words are used to bridge the vocabulary gap between the words in microblogs and targets. We examine the effectiveness of our approach via datasets gathered from real world microblogs. Experimental results demonstrate a 20.2% improvement in terms of F1-score over the state-of-the-art discriminative method.
A simplified method for the preparation of detergent-free lipid rafts Published, JLR Papers in Press, February 16, 2005. DOI 10.1194/jlr.D400041-JLR200

Lipid rafts are small plasma membrane domains that contain high levels of cholesterol and sphingolipids. Traditional methods for the biochemical isolation of lipid rafts involve the extraction of cells with nonionic detergents followed by the separation of a low-density, detergent-resistant membrane fraction on density gradients. Because of concerns regarding the possible introduction of artifacts through the use of detergents, it is important to develop procedures for the isolation of lipid rafts that do not involve detergent extraction. We report here a simplified method for the purification of detergent-free lipid rafts that requires only one short density gradient centrifugation, but yields a membrane fraction that is highly enriched in cholesterol and protein markers of lipid rafts, with no contamination from nonraft plasma membrane or intracellular membranes.