Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvement of Left Ventricular Function After Cardiac Resynchronization Therapy Is Predicted by Tissue Doppler Imaging Echocardiography

Background—Cardiac resynchronization therapy was shown to reverse left ventricular (LV) remodeling in patients with congestive heart failure (CHF). However, the prediction of benefit is controversial. We aimed to investigate predictive factors of LV functional recovery and reversed remodeling after biventricular pacing. Methods and Results—Forty-nine consecutive patients with CHF and a wide QRS complex (182±32 ms) were studied by echocardiography before resynchronization. Intraventricular and interventricular asynchrony and their combination were assessed by pulsed-wave tissue Doppler imaging from measurements of regional electromechanical coupling times in basal segments of the right and left ventricle. At 6-month follow-up, responders were defined by a relative increase in LV ejection fraction ≥25% compared with baseline (n=27). Receiver operating curve analysis revealed the degree of intraventricular asynchrony (area under the curve=0.77), interventricular asynchrony (area under the curve=0.69), and their combination (area under the curve=0.84) as the best predictors of functional recovery after resynchronization. In addition, the degree of intraventricular and interventricular asynchrony correlated significantly with the improvement of LV ejection fraction (r =0.73, P <0.0001), end-diastolic diameter (r =−0.59, P <0.0001), and end-systolic diameter (r =−0.48, P <0.001) at follow-up. QRS duration and conventional echo-Doppler indices were not predictive of reversed LV remodeling. Conclusions—In patients with CHF, the degree of intraventricular and interventricular asynchrony and their combination are the best predictive factors of LV functional recovery and reversed remodeling after cardiac resynchronization therapy.
A resonance suppression method for a multiple grid-connected-converter system with LCL filter

Multiple resonances may result in instability of a LCL filter based multiple grid connected converter (MGCC) system. This paper investigates the critical factors of multiple resonances in MGCC system. It is found that, closed-loop output admittance of the grid connected converter can be configured to meet the requirements of resonances suppression, by properly designing control method and parameters. To improve the multiple resonances suppression, a control method is applied to the MGCC system, which is a combination of proportional resonant (PR) control and full state feedback control. According to the proposed design principle of the closed-loop output admittance, a case study using the control method above is given. Simulation results are provided to validate the correctness and effectiveness of the proposed design principle and control method.
Magnetic susceptibility: further insights into macroscopic and microscopic fields and the sphere of Lorentz

To make certain quantitative interpretations of spectra from NMR experiments carried out on heterogeneous samples, such as cells and tissues, we must be able to estimate the magnetic and electric fields experienced by the resonant nuclei of atoms in the sample. Here, we analyze the relationships between these fields and the fields obtained by solving the Maxwell equations that describe the bulk properties of the materials present. This analysis separates the contribution to these fields of the molecule in which the atom in question is bonded, the "host" fields, from the contribution of all the other molecules in the system, the "external" fields. We discuss the circumstances under which the latter can be found by determining the macroscopic fields in the sample and then removing the averaged contribution of the host molecule. We demonstrate that the results produced by the, so-called, "sphere of Lorentz" construction are of general validity in both static and time-varying cases. This analytic construct, however, is not "mystical" and its justification rests not on any sphericity in the system but on the local uniformity and isotropy, i.e., spherical symmetry, of the medium when averaged over random microscopic configurations. This local averaging is precisely that which defines the equations that describe the macroscopic fields. Hence, the external microscopic fields, in a suitably averaged sense, can be estimated from the macroscopic fields. We then discuss the calculation of the external fields and that of the resonant nucleus in NMR experiments.
Evaluation of Plasma Proteomic Data for Alzheimer Disease State Classification and for the Prediction of Progression From Mild Cognitive Impairment to Alzheimer Disease

Previous studies that have examined the potential for plasma markers to serve as biomarkers for Alzheimer disease (AD) have studied single analytes and focused on the amyloid-&bgr; and &tgr; isoforms and have failed to yield conclusive results. In this study, we performed a multivariate analysis of 146 plasma analytes (the Human DiscoveryMAP v 1.0 from Rules-Based Medicine) in 527 subjects with AD, mild cognitive impairment (MCI), or cognitively normal elderly subjects from the Alzheimer’s Disease Neuroimaging Initiative database. We identified 4 different proteomic signatures, each using 5 to 14 analytes, that differentiate AD from control patients with sensitivity and specificity ranging from 74% to 85%. Five analytes were common to all 4 signatures: apolipoprotein A-II, apolipoprotein E, serum glutamic oxaloacetic transaminase, &agr;-1-microglobulin, and brain natriuretic peptide. None of the signatures adequately predicted progression from MCI to AD over a 12- and 24-month period. A new panel of analytes, optimized to predict MCI to AD conversion, was able to provide 55% to 60% predictive accuracy. These data suggest that a simple panel of plasma analytes may provide an adjunctive tool to differentiate AD from controls, may provide mechanistic insights to the etiology of AD, but cannot adequately predict MCI to AD conversion.
Green Threads User level threading for a Library OS

Library operating systems have long been researched to study the impact of pushing many functionalities out of the kernel and into userspace, for the purposes of security, compatibility and performance. The Drawbridge[1] project demonstrated that a commercial, large operating system (OS) like Windows can be refactored into a Library OS supporting standalone apps, providing access to low-level resources using only a small set of ABIs. The Graphene project generalizes this idea to the Linux OS, and further adds secure multiprocessing abstractions and new classes of applications to the mix. An interesting artifact of this design decision is the clear demarcation between the unprivileged, userspace component (the library OS) and the privileged, kernel component. This well-defined boundary lends itself well to execution on systems with heterogeneous cores[2], where different cores have different capabilities for varying energy and performance characteristics. In our case, we specifically look at cores which support different protection domains. For example, on the Intel architecture, simple cores will support only ring 3, while complex cores support ring 0 as well. The fact that a library OS limits most of the unprivileged OS code to userspace, with the privileged code being accessed via a narrow API, makes it very well suited for experimentation with heterogeneous multi-core systems. Thus, most of the OS, that is the userspace component, can be executed on a simple core and the kernel component using the complex core. In traditional OSes, user level threading is one model of multi-threading which is employed for its performance benefits. In contrast to kernel level threads, they are light-weight since most of the thread management, including context switching and thread scheduling is done in user space without involving the kernel. Moreover, the application can be in control of the threading, instead of being limited by the kernel. However, this approach is not without its disadvantages; the most prominent ones being: user level threads cannot simultaneously run on multiple processors and no user level thread can proceed if one of them is blocked performing a system call[3]. Despite the suitability of the Graphene Library OS for our purpose, threading is something that is still kernel based. In this project, we aim to support multi-threaded applications on heterogeneous systems by moving the responsibility of creating and managing threads from the kernel to userspace as provided by a user level threading implementation.
Diversity and distribution of porcelain crabs of Gujarat, India

Present paper reports four species of porcelain crabs in three genera from the Gujarat coast, India. Ancylocheles gravelei (Sankolli, 1963), Pisidia dehaanii (Krauss, 1843), P. gordoni (Johnson, 1970) and Polyonyx hendersoni Southwell, 1909 are reported from the Gujarat coast for the first time. Twelve porcellanid species are known from the Gujarat coast, including four species reported in this paper.
Branching and bounds tighteningtechniques for non-convex MINLP

Many industrial problems can be naturally formulated using mixed integer non-linear programming (MINLP) models and can be solved by spatial Branch&Bound (sBB) techniques. We study the impact of two important parts of sBB methods: bounds tightening (BT) and branching strategies. We extend a branching technique originally developed for MILP, reliability branching, to the MINLP case. Motivated by the demand for open-source solvers for real-world MINLP problems, we have developed an sBB software package named couenne (Convex Over- and Under-ENvelopes for Non-linear Estimation) and used it for extensive tests on several combinations of BT and branching techniques on a set of publicly available and real-world MINLP instances. We also compare the performance of couenne with a state-of-the-art MINLP solver.
Impact of IoT-Based Environmental Monitoring on Lab Safety and Sustainability

Several internal and external dangers might threaten a laboratory, the institution, and the public if not addressed properly. These hazards are addressed by our extensive laboratory monitoring system. This device detects elevated temperatures, gas leaks, fires, and solution pH. Elements of this system include an Esp32 microcontroller, LCD, Arduino Uno, mq2 gas sensor, DS18B20 temperature sensor, flame sensor, relay, water pump, and pH sensor for acidity measurement. The Arduino IDE controls sensors. Once the temperature reaches 50 degrees Celsius, an alarm, red LED, and mobile phone notification activate. Gas leaks activate a green LED, an alarm, and a message. Flame sensors notify and start water pumps when fires occur. Gas leaks and fires activate a buzzer. The IoT offers essential incident reporting and remote laboratory monitoring. The code is written in Arduino C++.
Magnetic Resonance Image Tissue Classification Using a Partial Volume Model

We describe a sequence of low-level operations to isolate and classify brain tissue within T1-weighted magnetic resonance images (MRI). Our method first removes nonbrain tissue using a combination of anisotropic diffusion filtering, edge detection, and mathematical morphology. We compensate for image nonuniformities due to magnetic field inhomogeneities by fitting a tricubic B-spline gain field to local estimates of the image nonuniformity spaced throughout the MRI volume. The local estimates are computed by fitting a partial volume tissue measurement model to histograms of neighborhoods about each estimate point. The measurement model uses mean tissue intensity and noise variance values computed from the global image and a multiplicative bias parameter that is estimated for each region during the histogram fit. Voxels in the intensity-normalized image are then classified into six tissue types using a maximum a posteriori classifier. This classifier combines the partial volume tissue measurement model with a Gibbs prior that models the spatial properties of the brain. We validate each stage of our algorithm on real and phantom data. Using data from the 20 normal MRI brain data sets of the Internet Brain Segmentation Repository, our method achieved average kappa indices of kappa = 0.746 +/- 0.114 for gray matter (GM) and kappa = 0.798 +/- 0.089 for white matter (WM) compared to expert labeled data. Our method achieved average kappa indices kappa = 0.893 +/- 0.041 for GM and kappa = 0.928 +/- 0.039 for WM compared to the ground truth labeling on 12 volumes from the Montreal Neurological Institute's BrainWeb phantom.
Connexel visualization: a software implementation of glyphs and edge-bundling for dense connectivity data using brainGL

The visualization of brain connectivity becomes progressively more challenging as analytic and computational advances begin to facilitate connexel-wise analyses, which include all connections between pairs of voxels. Drawing full connectivity graphs can result in depictions that, rather than illustrating connectivity patterns in more detail, obfuscate patterns owing to the data density. In an effort to expand the possibilities for visualization, we describe two approaches for presenting connexels: edge-bundling, which clarifies structure by grouping geometrically similar connections; and, connectivity glyphs, which depict a condensed connectivity map at each point on the cortical surface. These approaches can be applied in the native brain space, facilitating interpretation of the relation of connexels to brain anatomy. The tools have been implemented as part of brainGL, an extensive open-source software for the interactive exploration of structural and functional brain data.
Effectiveness evaluation of the food fortification program of Costa Rica: impact on anemia prevalence and hemoglobin concentrations in women and children.

BACKGROUND Food fortification is one approach for addressing anemia, but information on program effectiveness is limited. OBJECTIVE We evaluated the impact of Costa Rica's fortification program on anemia in women aged 15-45 y and children aged 1-7 y. DESIGN Reduced iron, an ineffective fortificant, was replaced by ferrous fumarate in wheat flour in 2002, and ferrous bisglycinate was added to maize flour in 1999 and to liquid and powdered milk in 2001. We used a one-group pretest-posttest design and national survey data from 1996 (baseline; 910 women, 965 children) and 2008-2009 (endline; 863 women, 403 children) to assess changes in iron deficiency (children only) and anemia. Data were also available for sentinel sites (1 urban, 1 rural) for 1999-2000 (405 women, 404 children) and 2008-2009 (474 women, 195 children), including 24-h recall data in children. Monitoring of fortification levels was routine. RESULTS Foods were fortified as mandated. Fortification provided about one-half the estimated average requirement for iron in children, mostly and equally through wheat flour and milk. Anemia was reduced in children and women in national and sentinel site comparisons. At the national level, anemia declined in children from 19.3% (95% CI: 16.8%, 21.8%) to 4.0% (95% CI: 2.1%, 5.9%) and in women from 18.4% (95% CI: 15.8%, 20.9%) to 10.2% (95% CI: 8.2%, 12.2%). In children, iron deficiency declined from 26.9% (95% CI: 21.1%, 32.7%) to 6.8% (95% CI: 4.2%, 9.3%), and iron deficiency anemia, which was 6.2% (95% CI: 3.0%, 9.3%) at baseline, could no longer be detected at the endline. CONCLUSIONS A plausible impact pathway suggests that fortification improved iron status and reduced anemia. Although unlikely in the Costa Rican context, other explanations cannot be excluded in a pre/post comparison.
Parallel Classification with Two-Stage Bagging Classifiers

The bootstrapped aggregation of classifiers, also referred to as bagging, is a classic meta-classification algorithm. We extend it to a two-stage architecture consisting of an initial voting amongst one-versus-all classifiers or single-class recognizers, and a second stage of one-versus-one classifiers or two-class discriminators used for disambiguation. Since our method constructs an ensemble of elementary classifiers, it lends itself very well to parallelization. We describe a static workload balancing strategy for embarrassingly parallel classifier construction as well as a parallelization of the classification process with the message passing interface. We evaluate our approach both in terms of classification performance and speed-up and demonstrate the utility of our approach.
EPIC: An Architecture for Instruction-Level Parallel Processors

EPIC architecture, VLIW architecture, instruction-level parallelism, MultiOp, nonunit assumed latencies, NUAL, rotating register files, unbundled branches, control speculation, speculative opcodes, exception tag, predicated execution, fully-resolved predicates, wired-OR and wired-AND compare opcodes, prioritized loads and stores, data speculation, cache specifiers, precise interrupts, NUAL-freeze and NUALdrain semantics, delay buffers, replay buffers, EQ and LEQ semantics, latency stalling, MultiOp-P and MultiOp-S semantics, dynamic translation, MultiTemplate and VariOp instruction formats, history of EPIC Over the past two and a half decades, the computer industry has grown accustomed to, and has come to take for granted, the spectacular rate of increase of microprocessor performance, all of this without requiring a fundamental rewriting of the program in a parallel form, without using a different algorithm or language, and often without even recompiling the program. The continuation of this trend is the topic of discussion of this report. For the time being at least, instruction-level parallel processing has established itself as the only viable approach for achieving the goal of providing continuously increasing performance without having to fundamentally re-write applications. In this report, we introduce the Explicitly Parallel Instruction Computing (EPIC) style of architecture which was developed, starting eleven years ago, to enable higher levels of instruction-level parallelism without unacceptable hardware complexity. We explain the philosophy underlying EPIC as well as the challenges faced as a result of adopting this philosophy. We also describe and discuss the set of architectural features that together characterize the EPIC style of architecture, and which can be selectively included in some specific instance of an EPIC instruction set architecture.
Optimal Income Taxation with Asset Accumulation

Several frictions restrict the government's ability to tax assets. First, it is very costly to monitor trades on international asset markets. Second, agents can resort to nonob- servable low-return assets such as cash, gold or foreign currencies if taxes on observable assets become too high. This paper shows that limitations in asset taxation have im- portant consequences for the taxation of labor income. Using a dynamic moral hazard model of social insurance, we find that optimal labor income taxes become less progres- sive when governments face limitations in asset taxation. We evaluate the quantitative effect of imperfect asset taxation for two applications of our model.
Exploring Research Trends with Rexplore

Current systems for exploring scholarly data exhibit a number of shortcomings in their ability to facilitate the identification of research trends and identify 'interesting' connections between researchers. To address these issues we have developed Rexplore, a novel system which combines statistics, human-computer interaction, and semantic technologies, to support knowledge-based exploration and visualization of scholarly data. In this paper we focus on the functionalities provided by Rexplore for visualizing research trends and we use as an example research in "Social Networks", which has experienced dramatic growth in the years 2000-2010.
Epitope Mapping of Antibodies Using a Cell Array–Based Polypeptide Library

The authors describe a technique for mapping the epitopes of protein antigens recognized by mono- or polyclonal antibodies. This method is based on a recombinant polypeptide library, expressed in a bacterial expression system, arrayed at high density, and tested on a membrane with automated procedures. The authors analyzed the epitope of a commercially available monoclonal antibody to vitamin D receptor (VDR). About 2300 overlapping VDR peptides were screened on a test array, and a contiguous stretch of 37 amino acids was identified as the epitope. Its authenticity was confirmed by Western blotting and an immunofluorescence competition assay on human skin tissue samples. The authors define the proposed method as a cell-based protein or peptide array that is adaptable to many applications, including epitope mapping of antibodies and autoantibodies, autoantigen detection from patient sera, whole-proteome approaches such as protein-peptide interactions, or selection of monoclonal antibodies from polyclonal sera. The advantages of this method are (a) its ease of protein array production based on well-established bacterial protein/peptide expression procedures; (b) the large number of printable colonies (as many as ~25,000) that can be arrayed per membrane; (c) there is no need for protein purification of recombinantly expressed proteins; (d) DNA, rather than protein, is the starting material to generate the arrays; and (e) its high-throughput and automatable format.
Measuring Sperm DNA Fragmentation and Clinical Outcomes of Medically Assisted Reproduction: A Systematic Review and Meta-Analysis

Sperm DNA fragmentation has been associated with reduced fertilization rates, embryo quality, pregnancy rates and increased miscarriage rates. Various methods exist to test sperm DNA fragmentation such as the sperm chromatin structure assay (SCSA), the sperm chromatin dispersion (SCD) test, the terminal deoxynucleotidyl transferase mediated deoxyuridine triphosphate nick end labelling (TUNEL) assay and the single cell gel electrophoresis (Comet) assay. We performed a systematic review and meta-analysis to assess the value of measuring sperm DNA fragmentation in predicting chance of ongoing pregnancy with IVF or ICSI. Out of 658 unique studies, 30 had extractable data and were thus included in the meta-analysis. Overall, the sperm DNA fragmentation tests had a reasonable to good sensitivity. A wide variety of other factors may also affect the IVF/ICSI outcome, reflected by limited to very low specificity. The constructed hierarchical summary receiver operating characteristic (HSROC) curve indicated a fair discriminatory capacity of the TUNEL assay (area under the curve (AUC) of 0.71; 95% CI 0.66 to 0.74) and Comet assay (AUC of 0.73; 95% CI 0.19 to 0.97). The SCSA and the SCD test had poor predictive capacity. Importantly, for the TUNEL assay, SCD test and Comet assay, meta-regression showed no differences in predictive value between IVF and ICSI. For the SCSA meta-regression indicated the predictive values for IVF and ICSI were different. The present review suggests that current sperm DNA fragmentation tests have limited capacity to predict the chance of pregnancy in the context of MAR. Furthermore, sperm DNA fragmentation tests have little or no difference in predictive value between IVF and ICSI. At this moment, there is insufficient evidence to recommend the routine use of sperm DNA fragmentation tests in couples undergoing MAR both for the prediction of pregnancy and for the choice of treatment. Given the significant limitations of the evidence and the methodological weakness and design of the included studies, we do urge for further research on the predictive value of sperm DNA fragmentation for the chance of pregnancy after MAR, also in comparison with other predictors of pregnancy after MAR.