Miracle-dz/UniFAR-FTUs huggingface dataset:
Mortality and Morbidity Reduction With Candesartan in Patients With Chronic Heart Failure and Left Ventricular Systolic Dysfunction: Results of the CHARM Low–Left Ventricular Ejection Fraction Trials

Background—Patients with symptomatic chronic heart failure (CHF) and reduced left ventricular ejection fraction (LVEF) have a high risk of death and hospitalization for CHF deterioration despite therapies with angiotensin-converting enzyme (ACE) inhibitors, β-blockers, and even an aldosterone antagonist. To determine whether the angiotensin-receptor blocker (ARB) candesartan decreases cardiovascular mortality, morbidity, and all-cause mortality in patients with CHF and depressed LVEF, a prespecified analysis of the combined Candesartan in Heart Failure Assessment of Reduction in Mortality and morbidity (CHARM) low LVEF trials was performed. CHARM is a randomized, double-blind, placebo-controlled, multicenter, international trial program. Methods and Results—New York Heart Association (NYHA) class II through IV CHF patients with an LVEF of ≤40% were randomized to candesartan or placebo in 2 complementary parallel trials (CHARM-Alternative, for patients who cannot tolerate ACE inhibitors, and CHARM-Added, for patients who were receiving ACE inhibitors). Mortality and morbidity were determined in 4576 low LVEF patients (2289 candesartan and 2287 placebo), titrated as tolerated to a target dose of 32 mg once daily, and observed for 2 to 4 years (median, 40 months). The primary outcome (time to first event by intention to treat) was cardiovascular death or CHF hospitalization for each trial, with all-cause mortality a secondary end point in the pooled analysis of the low LVEF trials. Of the patients in the candesartan group, 817 (35.7%) experienced cardiovascular death or a CHF hospitalization as compared with 944 (41.3%) in the placebo group (HR 0.82; 95% CI 0.74 to 0.90; P<0.001) with reduced risk for both cardiovascular deaths (521 [22.8%] versus 599 [26.2%]; HR 0.84 [95% CI 0.75 to 0.95]; P=0.005) and CHF hospitalizations (516 [22.5%] versus 642 [28.1%]; HR 0.76 [95% CI 0.68 to 0.85]; P<0.001). It is important to note that all-cause mortality also was significantly reduced by candesartan (642 [28.0%] versus 708 [31.0%]; HR 0.88 [95% CI 0.79 to 0.98]; P=0.018). No significant heterogeneity for the beneficial effects of candesartan was found across prespecified and subsequently identified subgroups including treatment with ACE inhibitors, β-blockers, an aldosterone antagonist, or their combinations. The study drug was discontinued because of adverse effects by 23.1% of patients in the candesartan group and 18.8% in the placebo group; the reasons included increased creatinine (7.1% versus 3.5%), hypotension (4.2% versus 2.1%), and hyperkalemia (2.8% versus 0.5%), respectively (all P<0.001). Conclusion—Candesartan significantly reduces all-cause mortality, cardiovascular death, and heart failure hospitalizations in patients with CHF and LVEF ≤40% when added to standard therapies including ACE inhibitors, β-blockers, and an aldosterone antagonist. Routine monitoring of blood pressure, serum creatinine, and serum potassium is warranted.
The genic view of plant speciation: recent progress and emerging questions

The genic view of the process of speciation is based on the notion that species isolation may be achieved by a modest number of genes. Although great strides have been made to characterize ‘speciation genes’ in some groups of animals, little is known about the nature of genic barriers to gene flow in plants. We review recent progress in the characterization of genic species barriers in plants with a focus on five ‘model’ genera: Mimulus (monkey flowers); Iris (irises); Helianthus (sunflowers); Silene (campions); and Populus (poplars, aspens, cottonwoods). The study species in all five genera are diploid in terms of meiotic behaviour, and chromosomal rearrangements are assumed to play a minor role in species isolation, with the exception of Helianthus for which data on the relative roles of chromosomal and genic isolation factors are available. Our review identifies the following key topics as being of special interest for future research: the role of intraspecific variation in speciation; the detection of balancing versus directional selection in speciation genetic studies; the timing of fixation of alleles of major versus minor effects during plant speciation; the likelihood of adaptive trait introgression; and the identification and characterization of speciation genes and speciation gene networks.
Hard Times

We show that the stock market downturns of 2000-2002 and 2007-2009 have very different proximate causes. The early 2000’s saw a large increase in the discount rates applied to profits by rational investors, while the late 2000’s saw a decrease in rational expectations of future profits. We reach these conclusions using a VAR model of aggregate stock returns and valuations, estimated both freely and imposing the cross-sectional restrictions of the ICAPM. Our findings imply that the 2007-2009 downturn was particularly serious for rational long-term investors, whose losses were not offset by improving stock return forecasts as in the previous recession.
Precise memory leak detection for java software using container profiling

A memory leak in a Java program occurs when object references that are no longer needed are unnecessarily maintained. Such leaks are difficult to understand because static analyses typically cannot precisely identify these redundant references, and existing dynamic analyses for leak detection track and report fine-grained information about individual objects, producing results that are usually hard to interpret and lack precision. We introduce a novel container-based heap-tracking technique, based on the observation that many memory leaks in Java programs occur due to containers that keep references to unused data entries. The novelty of the described work is two-fold: (1) instead of tracking arbitrary objects and finding leaks by analyzing references to unused objects, the technique tracks only containers and directly identifies the source of the leak, and (2) the approach computes a confidence value for each container based on a combination of its memory consumption and its elements' staleness (time since last retrieval), while previous approaches do not consider such combined metrics. Our experimental results show that the reports generated by the proposed technique can be very precise: for two bugs reported by Sun and for a known bug in SPECjbb, the top containers in the reports include the containers that leak memory.
Digital fountains in information-centric networking

In this paper, we revisit digital fountains as an information theoretic approach for disseminating information. We embed this approach, however, into the architectural context of information centric networking (ICN). We discuss how our information-centric network architecture enables efficient information dissemination through fountain coding and we present the basic network operations for disseminating information from publishers to subscribers.
Parboil: A Revised Benchmark Suite for Scientific and Commercial Throughput Computing

The Parboil benchmarks are a set of throughput computing applications useful for studying the performance of throughput computing architecture and compilers. The name comes from the culinary term for a partial cooking process, which represents our belief that useful throughput computing benchmarks must be “cooked”, or preselected to implement a scalable algorithm with fine-grained paralle l tasks. But useful benchmarks for this field cannot be “fully cooked”, because the architectures and programming models and supporting tools are evolving rapidly enough that static benchmark codes will lose relevance very quickly. We have collected benchmarks from throughput computing application researchers in many different scientific and commercial fields including image processing, biomolec ular simulation, fluid dynamics, and astronomy. Each benchmark includes several implementations. Some implementations we provide as readable base implementations from which new optimization efforts can begin, and others as examples of the current state-of-the-art targeting specific CPU and GPU architectures. As we continue to optimiz e these benchmarks for new and existing architectures ourselves, we will also gladly accept new implementations and benchmark contributions from developers to recognize those at the frontier of performance optimization on each architecture. Finally, by including versions of varying levels of optimization of the same fundamental algorithm, the benchmarks present opportunities to demonstrate tools and architectures that help programmers get the most out of their parallel hardware. Less optimized versions are presented as challenges to the compiler and architecture research communities: to develop the technology that automatically raises the performance of simpler implementations to the performance level of sophisticated programmer-optimized implementations, or demonstrate any other performance or programmability improvements. We hope that these benchmarks will facilitate effective demonstrations of such technology.
Text Categorization Using Word Similarities Based on Higher Order Co-occurrences

12 In this paper, we propose an extension of the χ-Sim coclustering algorithm to deal with the text categorization task. The idea behind χ-Sim method [1] is to iteratively learn the similarity matrix between documents using similarity matrix between words and vice-versa. Thus, two documents are said to be similar if they share similar (but not necessary identical) words and two words are similar if they occur in similar documents. The algorithm has been shown to work well for unsupervised document clustering. By introducing some “a priori” knowledge about the class labels of documents in the initialization step of χ-Sim, we are able to extend the method to deal for the supervised task. The proposed approach is tested on different classical textual datasets and our experiments show that the proposed algorithm compares favorably or surpass both traditional and state-of-the-art algorithms like k-NN, supervised LSI and SVM.
Development of a Gene Knockout System for the Halophilic Archaeon Haloferax volcanii by Use of the pyrE Gene

ABSTRACT So far, the extremely halophilic archaeon Haloferax volcanii has the best genetic tools among the archaea. However, the lack of an efficient gene knockout system for this organism has hampered further genetic studies. In this paper we describe the development of pyrE-based positive selection and counterselection systems to generate an efficient gene knockout system. The H. volacanii pyrE1 and pyrE2 genes were isolated, and the pyrE2 gene was shown to code for the physiological enzyme orotate phosphoribosyl transferase. A ΔpyrE2 strain was constructed and used to isolate deletion mutants by the following two steps: (i) integration of a nonreplicative plasmid carrying both the pyrE2 wild-type gene, as a selectable marker, and a cloned chromosomal DNA fragment containing a deletion in the desired gene; and (ii) excision of the integrated plasmid after selection with 5-fluoroorotic acid. Application of this gene knockout system is described.
Neuron–glia crosstalk in health and disease: fractalkine and CX3CR1 take centre stage

An essential aspect of normal brain function is the bidirectional interaction and communication between neurons and neighbouring glial cells. To this end, the brain has evolved ligand–receptor partnerships that facilitate crosstalk between different cell types. The chemokine, fractalkine (FKN), is expressed on neuronal cells, and its receptor, CX3CR1, is predominantly expressed on microglia. This review focuses on several important functional roles for FKN/CX3CR1 in both health and disease of the central nervous system. It has been posited that FKN is involved in microglial infiltration of the brain during development. Microglia, in turn, are implicated in the developmental synaptic pruning that occurs during brain maturation. The abundance of FKN on mature hippocampal neurons suggests a homeostatic non-inflammatory role in mechanisms of learning and memory. There is substantial evidence describing a role for FKN in hippocampal synaptic plasticity. FKN, on the one hand, appears to prevent excess microglial activation in the absence of injury while promoting activation of microglia and astrocytes during inflammatory episodes. Thus, FKN appears to be neuroprotective in some settings, whereas it contributes to neuronal damage in others. Many progressive neuroinflammatory disorders that are associated with increased microglial activation, such as Alzheimer's disease, show disruption of the FKN/CX3CR1 communication system. Thus, targeting CX3CR1 receptor hyperactivation with specific antagonists in such neuroinflammatory conditions may eventually lead to novel neurotherapeutics.
A Score Recommendation System Towards Automating Assessment In Professional Courses

We present a preliminary version of an automated evaluation system that provides recommended scores for descriptive answers. The system is designed in the context of professional courses, such as from Applied Sciences, for questions that have an answer-key. The recommendation of a score is based on an analysis of the student's answer against an answer-key that comprises key phrases of the solution and alternatives, if any. We rely on five algorithms from literature on natural language processing to assess various aspects of a student's answer, such as the quantity and extent of match between keywords in a student's answer and the answer-key, while ensuring merely verbatim comparisons are not performed. The similarity scores are then combined using machine learning to output a recommended score for the answer. The system learns weights for the output of each of the five methods to map these to a score based on training data, comprising questions with answer-keys, student answers from actual exams and the scores provided by course instructors/ graders. It is noteworthy that the methods presented in this paper do not rely on any kind of a corpus or prior-knowledge that is subject-specific. Even though the accuracies are modest and improvements ought to be made to accommodate the kind of variety observed in students' answers, the avenue is a promising one towards enhancing learning assessment.
Adult T-cell acute lymphoblastic leukemia: prognostic impact of myeloid-associated antigens

Evaluation of: Khabori M, Samiee S, Fung S et al. Adult precursor T-lymphoblastic leukemia/lymphoma with myeloid-associated antigen expression is associated with a lower complete remission rate following induction chemotherapy. Acta Haematol. 120, 5–10 (2008). Despite the recent improvement in the treatment of the disease, the prognosis of adult T-cell acute lymphoblastic leukemia (T-ALL) remains poor. In the last several decades, many reports analyzed clinical and/or biological factors in order to identify prognostic parameters suitable for risk stratification of T-ALL patients. The article under review analyzed the prognostic impact of myeloid-associated antigen expression in a monocentric cohort of adult T-ALL patients.
Mitigating Parameter Variation with Dynamic Fine-Grain Body Biasing

Parameter variation is detrimental to a processor's frequency and leakage power. One proposed technique to mitigate it is fine-grain body biasing (FGBB), where different parts of the processor chip are given a voltage bias that changes the speed and leakage properties of their transistors. This technique has been proposed for static application, with the bias voltages being programmed at manufacturing time for worst-case conditions. In this paper, we introduce dynamic FGBB (D-FGBB), which allows the continuous re-evaluation of the bias voltages to adapt to dynamic conditions. Our results show that D-FGBB is very versatile and effective. Specifically, with the processor working in normal mode at fixed frequency, D-FGBB reduces the leakage power of the chip by an average of 2%-A2. % compared to static FGBB. Alternatively, with the processor working in a high-performance mode, D-FGBB increases the processor frequency by an average of 7-9% compared to static FGBB - or 7-16% compared to no body biasing. Finally, we also show that D-FGBB can be synergistically combined with dynamic voltage and frequency scaling (DVFS), creating an effective means to manage power.
Breakthrough pressure and permeability in partially water-saturated shales using methane–carbon dioxide gas mixtures: An experimental study of Carboniferous shales from the eastern Qaidam Basin, China

As an important unconventional and alternative resource, shale gas has attracted worldwide attention. The breakthrough pressure is a major factor in the generation and migration of shale gas as well as in the evaluation of the caprock sealing capacity. Carboniferous shales are considered to have great potential for the exploitation of shale gas; thus, investigations of the breakthrough pressure and gas effective permeability are significant. Two shale samples taken from the Carboniferous Hurleg Formation in the eastern Qaidam Basin, China, were chosen to conduct breakthrough experiments to investigate the effects of water saturation and CO2–CH4 mixed mole fractions on the breakthrough pressure and gas effective permeability. Prior to the experiments, various relevant parameters (e.g., the porosity, mineral composition, and organic geochemistry; the total organic content, thermal maturity and kerogen type; and microstructure) of these samples were also measured. The results of our breakthrough experiments show that the breakthrough pressure increases with the water saturation and decreases with the CO2 mole fraction in the gas mixture. The situation for the gas effective permeability is just the opposite. Pore-size distribution measurements indicate that there are many nanoscale micropores that can easily be blocked by water molecules. This results in the reduced connectivity of gas pathways; thus, the breakthrough pressure increases and the gas effective permeability decreases with increasing water saturation. The breakthrough pressure decreases with the CO2 mole fraction because the interfacial tension of the CO2–water system is smaller than that of the CH4–water system. The viscosity of the CO2–CH4 mixture was found to increase with the CO2 mole fraction by fitting a series of values under the same temperature and pressure conditions, leading to an increase in the gas effective permeability. Furthermore, CO2 molecules are smaller than CH4 molecules, making it easier for CO2 to move across pathways. After each breakthrough experiment, the CO2 mole fraction in the effluent was less than that in the injected gas, and it increased over time until reaching the initial injected gas composition. This is because the adsorption and solubility of CO2 in water are greater than those of CH4. This study provides practical information for further investigations of shale gas migration and extraction and the sealing capacities of caprocks.
The design of Adaptive Immune Genetic Algorithm based on vector distance

Aiming at the problems which exist in Genetic Algorithm (GA), including reduction in diversity, prematureness, weak local searching ability and slow convergence rate, this paper studies the effect of antigens recognition module, immune memory module, antibodies self-adjusting module of Immune Algorithm, and adaptive probability crossover and mutation operator to GA, and proposes Adaptive Immune Genetic Algorithm (AIGA) based on vector distance. After exploration, this paper solves the problems in GA above. This paper takes a controlled object as example to test the effect of each module to GA by simulation. Simulation results show that the four modules effectively improve the drawbacks of GA. At the same time, this paper proves the convergence of the algorithm, and verifies algorithm by testing function. Simulation results show that AIGA is better than GA on global optimization capability. The algorithm can obtain the optimal solution with high fitness value, and also has good convergence stability.
Household Behavior and Social Norms : A Conjugal Contract Model

We present a model of household behavior to explore the complex interactions between the decision-making process within the household and social norms. The household is viewed as two separate spheres – the female and the male – both linked by a public good and a "conjugal contract" trough which spouses exchange resources. The conjugal contract negotiated within the couple is partly influenced by social norms given the conformism of individuals. Social norms are endogenously determined as the average conjugal contract. We find that the closer spouses' wages are in the labor market, the more equally they share household tasks. Wage policies promoting gender wage equality lead all couples to renegotiate the terms of their conjugal contract, which in turn changes social norms. Even though spouses aim at maximizing the household's welfare, the resulting equilibrium allocation is not Pareto efficient and inefficiency increases with social conformism.
Transactions Costs and Agricultural Productivity: Implications of Isolation for Rural Poverty in Madagascar

This paper examines the mechanisms that transmit isolation into poverty in Madagascar using household survey data combined with a census of administrative communes. Given the importance of agriculture to the rural poor, where nine out of ten poor persons is engaged in farming, we concentrate on isolation manifesting itself in the form of high transaction costs such as the cost of transporting agricultural commodities to major market centers. We find that (a) the incidence of poverty in rural Madagascar increases with remoteness; (b) yields of major staple crops fall considerably as one gets farther away from major markets; (c) and the use of agricultural inputs declines with isolation. Simulation results using output from rice production function estimates suggest that halving travel time per kilometer on major highways (feeder roads) will increase primary season rice production by 1.3 (1.0) percent.