Miracle-dz/UniFAR-FTUs huggingface dataset:
On being certain : believing you are right even when you're not

In On Being Certain, neurologist Robert Burton challenges the notions of how we think about what we know. He shows that the feeling of certainty we have when we know something comes from sources beyond our control and knowledge. In fact, certainty is a mental sensation, rather than evidence of fact. Because this feeling of knowing seems like confirmation of knowledge, we tend to think of it as a product of reason. But an increasing body of evidence suggests that feelings such as certainty stem from primitive areas of the brain, and are independent of active, conscious reflection and reasoning. The feeling of knowing happens to us; we cannot make it happen.
Sensitivity Improvement of a 2D MEMS Thermal Wind Sensor for Low-Power Applications

In this paper, we report a novel and low-cost method to improve the sensitivity of a low-power 2D microelectromechanical systems thermal wind sensor by using HF wet etching. After wet etching, the thickness of the glass substrate decreases, so that the sensor's thermal vias become more exposed to the wind. As a result, the conductive heat transfer is weakened and the convective heat transfer is enhanced in sensor operation. Finite-element method simulations verify this analysis. Moreover, the sensor chips with different lengths of silicon vias above the substrate are successfully fabricated and tested. Measurement results show that the wet etching has no influence on the metal film sensing and heating elements of the sensor. Besides, before and after wet etching for 7 and 14 min, at the wind speed of 5 m/s, the measured sensitivities of the sensor with a total power consumption of 24.5 mW are 77.2, 98.6, and 164.1 mK/(m/s). Measurement results also show that the improved sensitivity of the sensor chip can provide a more accurate measurement in wind speed but has little effect on the wind direction measurement. Instead, the accuracy of wind direction measurement is mainly related to the structural and thermal symmetries of the wind sensor. After compensation, the proposed thermal wind sensor can detect the wind direction in a full range of 360° with an mean error of 2.3° and a maximum error of 6°.
Admixture determines genetic diversity and population differentiation in the biological invasion of a lizard species

Molecular genetic analyses show that introduced populations undergoing biological invasions often bring together individuals from genetically disparate native-range source populations, which can elevate genotypic variation if these individuals interbreed. Differential admixture among multiple native-range sources explains mitochondrial haplotypic diversity within and differentiation among invasive populations of the lizard Anolis sagrei. Our examination of microsatellite variation supports the hypothesis that lizards from disparate native-range sources, identified using mtDNA haplotypes, form genetically admixed introduced populations. Furthermore, within-population genotypic diversity increases with the number of sources and among-population genotypic differentiation reflects disparity in their native-range sources. If adaptive genetic variation is similarly restructured, then the ability of invasive species to adapt to new conditions may be enhanced.
Supply-Induced Demand for Hospital Care

Preliminary analysis of hospital utilization data indicates that Roemer's Law may still be operative in rural Iowa: counties with more hospital beds per capita have more hospital utilization per capita. However, when patient origin data are analyzed findings are entirely different. Bed supply is not related to utilization rates in Iowa counties. Instead, the number of unique hospital services is associated with higher utilization rates. The impact of this characteristic of hospital supply, however, is much weaker than the original Roemer effect. The contradiction of these findings with Roemer's Law is apparently a result of a methods effect: use of hospital utilization data which are not derived from actual population experience reveals a relationship which is a statistical artifact. The data also reveal that suburban counties have higher utilization rates than either rural or urban (MSA core) counties.
User interest prediction for tweets using semantic enrichment with DBpedia

This paper focuses on topic-based prediction of interest of individual users to posts in the context of Twitter. Two methods for enriching tweets using DBpedia for the purposes of classification are proposed. The first method incorporates entity linking and uses linked entities in a tweet to improve classification, whereas the second method aims to improve upon the first one by adding information derived from DBpedia about entities found using the first method. The two methods are evaluated with respect to tweet classification.
Polarization Dependence of L-Band Measurements Over the Ocean on Surface Wind at 23-25 Incidence Angles

Polarization dependence of L-band measurements over the ocean on surface wind is investigated for the incidence angle ranging from 23 to 25 degrees, by using the Phased-Array L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) and MetOp/ASCAT wind vectors. Polarization ratio (VV/HH) shows clear incidence angle and wind speed dependencies. It increases with increasing incidence angle and decreases with wind speed, ranging from 1.8 dB at 2 m/s wind to 0.5 dB at strong wind >12 m/s. These dependences are in good quantitative agreement with the Resonant Curvature Approximation (RCA) model proposed by Mouche et al. (2007). Although relative wind direction dependency of the polarization ratio is not so significant, downwind values are larger than cross- and upwind values at strong winds >12 m/s.
Optimizing Process-to-Core Mappings for Application Level Multi-dimensional MPI Communications

Multi-dimensional MPI communications, where MPI communications have to be performed in each dimension of a Cartesian communicator, have been frequently used in many of today's high performance computing applications. While individual MPI collective communications for regular communicators with a one-dimensional linear-ranking of processes have been extensively studied and optimized, little optimizations have been performed for multi-dimensional MPI collective communications on multi-dimensional Cartesian topology. In this paper, we optimize multi-dimensional MPI collective communications for SMP and multi-core systems at the application level. We show that the default Cartesian topology built by the state-of-the-art MPI implementations produce sub-optimal performance for multi-dimensional MPI collective communications. We design optimal process-to-core mapping schemes for Cartesian communicators to minimize the total inter-node communications. The proposed technique improves the performance by up to 80% over the default Cartesian topology built by Cray's MPI implementation MPT 3.1. 02 on the world's current second fastest supercomputer Jaguar at Oak Ridge National Laboratory.
Built-In Self-Test of Transmitter I/Q Mismatch and Nonlinearity Using Self-Mixing Envelope Detector

Built-in self-test (BiST) for transmitters is a desirable choice since it eliminates the reliance on expensive instrumentation to perform radio-frequency signal analysis. Existing on-chip resources, such as power or envelope detectors or small additional circuitry, can be used for BiST purposes. However, due to limited bandwidth, measurement of complex specifications, such as in-phase and quadrature (IQ) imbalance, and third-order intermodulation intercept point (IIP3) is challenging. Since IQ imbalances are most amenable for digital compensation, their characterization and monitoring are desirable. In this paper, we propose a multistep BiST technique for transmitter IQ imbalance and nonlinearity using a self-mixing envelope detector. We derive analytical expressions for the output signal in linear and nonlinear modes. Using linear mode expression, we devise test signals to isolate the effects of gain and phase imbalances, dc offsets, and time skews from other parameters of the system in low-power mode. Once isolated, these parameters are calculated easily with a few mathematical operations. In the next step, using a higher power test signal, the nonlinear behavior of the transmitter is excited and the IIP3 of the transmitter is computed based on the analytical expressions. Simulations and hardware measurements show that the technique can provide accurate characterization of the path.
Nonstationary Distance Metric Learning

Recent work in distance metric learning has focused on learning transformations of data that best align with provided sets of pairwise similarity and dissimilarity constraints. The learned transformations lead to improved retrieval, classification, and clustering algorithms due to the better adapted distance or similarity measures. Here, we introduce the problem of learning these transformations when the underlying constraint generation process is nonstationary. This nonstationarity can be due to changes in either the ground-truth clustering used to generate constraints or changes to the feature subspaces in which the class structure is apparent. We propose and evaluate COMID-SADL, an adaptive, online approach for learning and tracking optimal metrics as they change over time that is highly robust to a variety of nonstationary behaviors in the changing metric. We demonstrate COMID-SADL on both real and synthetic data sets and show significant performance improvements relative to previously proposed batch and online distance metric learning algorithms.
Quality-fair HTTP adaptive streaming over LTE network

In HTTP adaptive streaming (HAS) applications multiple video clients sharing the same wireless channel may experience different video qualities as result of both different video content complexity and different channel conditions. This causes unfairness in the end-user video quality. In this paper, we propose a quality-fair adaptive streaming (QFAS) solution to deliver fair video quality to HAS clients competing for the same resources in an LTE cell. In the QFAS framework the share of radio resource is optimized according to video content characteristics and channel condition. The proposed solution is compared with other state-of-the-art strategies and numerical results in terms of SSIM quality metric shows that it significantly improves the quality fairness among heterogeneous HAS users.
Evolving Deep Neural Networks architectures for Android malware classification

Deep Neural Networks (DNN) have become a powerful, widely used, and successful mechanism to solve problems of different nature and varied complexity. Their ability to build models adapted to complex non-linear problems, have made them a technique widely applied and studied. One of the fields where this technique is currently being applied is in the malware classification problem. The malware classification problem has an increasing complexity, due to the growing number of features needed to represent the behaviour of the application as exhaustively as possible. Although other classification methods, as those based on SVM, have been traditionally used, the DNN pose a promising tool in this field. However, the parameters and architecture setting of these DNNs present a serious restriction, due to the necessary time to find the most appropriate configuration. This paper proposes a new genetic algorithm designed to evolve the parameters, and the architecture, of a DNN with the goal of maximising the malware classification accuracy, and minimizing the complexity of the model. This model is tested against a dataset of malware samples, which are represented using a set of static features, so the DNN has been trained to perform a static malware classification task. The experiments carried out using this dataset show that the genetic algorithm is able to select the parameters and the DNN architecture settings, achieving a 91% accuracy.
Sentence Simplification with Deep Reinforcement Learning

Sentence simplification aims to make sentences easier to read and understand. Most recent approaches draw on insights from machine translation to learn simplification rewrites from monolingual corpora of complex and simple sentences. We address the simplification problem with an encoder-decoder model coupled with a deep reinforcement learning framework. Our model, which we call DRESS (as shorthand for Deep REinforcement Sentence Simplification), explores the space of possible simplifications while learning to optimize a reward function that encourages outputs which are simple, fluent, and preserve the meaning of the input. Experiments on three datasets demonstrate that our model outperforms competitive simplification systems.
Structure and dynamics in solution of the complex of lactobacillus casei dihydrofolate reductase with the new lipophilic antifolate drug trimetrexate

We have determined the three‐dimensional solution structure of the complex of Lactobacillus casei dihydrofolate reductase and the anticancer drug trimetrexate. Two thousand seventy distance, 345 dihedral angle, and 144 hydrogen bond restraints were obtained from analysis of multidimensional NMR spectra recorded for complexes containing 15N‐labeled protein. Simulated annealing calculations produced a family of 22 structures fully consistent with the constraints. Several intermolecular protein‐ligand NOEs were obtained by using a novel approach monitoring temperature effects of NOE signals resulting from dynamic processes in the bound ligand. At low temperature (5 °C) the trimethoxy ring of bound trimetrexate is flipping sufficiently slowly to give narrow signals in slow exchange, which give good NOE cross peaks. At higher temperature these broaden and their NOE cross peaks disappear thus allowing the signals in the lower‐temperature spectrum to be identified as NOEs involving ligand protons. The binding site for trimetrexate is well defined and this was compared with the binding sites in related complexes formed with methotrexate and trimethoprim. No major conformational differences were detected between the different complexes. The 2,4‐diaminopyrimidine‐containing moieties in the three drugs bind essentially in the same binding pocket and the remaining parts of their molecules adapt their conformations such that they can make effective van der Waals interactions with essentially the same set of hydrophobic amino acids, the side‐chain orientations and local conformations of which are not greatly changed in the different complexes (similar x1 and x2 values).
STM probing of local oscillations of the Fano-Kondo effect: a Doniach-Sunjic approach for the Kondo peak

The electron transport through normal metallic junctions at zero temperature is governed by a tunneling transmission probability T through an effective potential barrier formed in the contact region. In a single mode approximation, the conductance is given by the Landauer-Buttiker formula G junc = 2e 2 h T .
Guidelines Abstracted from the American Geriatrics Society Guidelines for Improving the Care of Older Adults with Diabetes Mellitus: 2013 Update

● Incorporate high-quality new evidence with significant effect on diabetes mellitus (DM) care that has become available since the 2003 “Guidelines for Improving the Care of the Older Person with Diabetes Mellitus” into a new 2013 Guideline update. ● Improve the care of older people with DM by providing an updated set of evidence-based recommendations individualized to adults with DM aged 65 and older.
Margins and yield in superconducting circuits with gain

We analyze the relationship between current gain and circuit critical current margins in prototype vortex flow transistor (VFT) circuits. We give a brief review of the relationship between process spread, circuit margins, and yield. We note that modest increases in gain could dramatically improve yield. In some of the circuits previously proposed, however, there is a limit to the gain that can be used if proper operation is to be ensured. We introduce alternative approaches to superconducting digital logic families that overcome this limitation in useful gain.
Association between ABCB1 Polymorphisms and Ischemic Stroke in Korean Population

Neuronal expression of ATP-binding cassette, sub-family B (MDR/TAP), member 1 (ABCB1) has been demonstrated after brain ischemia. To investigate whether ABCB1 polymorphisms are associated with the development, risk factors (hypertension, dyslipidemia, and diabetes mellitus), severity (National Institutes of Health Stroke Scale, NIHSS), and sequelae (Modified Barthel Index, MBI) of ischemic stroke (IS), four single nucleotide polymorphisms (SNPs) of the ABCB1 gene [rs4148727, promoter, -154T>C; rs3213619, 5'-untranslation region (5'UTR), -129T>C); rs1128503, synonymous, Gly412 (C>T); rs3842, 3'UTR, A>G] were analyzed in 121 IS patients and 291 control subjects. SNPStats and SPSS 18.0 were used to obtain odds ratios (OR), 95% confidence intervals (CI), and p values. Multiple logistic regression models (codominant1, codominant2, dominant, recessive, and log-additive models) were applied to analyze the genetic data. The rs3842 SNP was weakly associated with the development of IS (p=0.020 in codominant1 model and p=0.028 in dominant model). In the analysis of clinical phenotypes, ABCB1 polymorphisms were nominally associated with hypertension (rs3213619 and rs3842, p<0.05), dyslipidemia (rs1128503, p<0.05), diabetes (rs3842, p<0.05), and NIHSS (rs4148727, p<0.05). Interestingly, rs3842 showed statistically strong association between IS with hypertension and IS without hypertension (Fisher's exact p=0.003, OR=0.11, 95% CI=0.03-0.51 in recessive model). These results suggest that the ABCB1 gene may be associated with the development and clinical phenotypes of IS in Korean population.
Implementation of large-integer hardware multiplier in Xilinx FPGA

Implementation of wide multipliers for high performance is usually performed by the vendor synthesis/place and route software tool. This paper presents a partition algorithm for large integer multipliers with speed as optimization criteria. The generated solution uses built-in high-speed arithmetic blocks available in the current generation of Xilinx FPGA chip. The proposed technique has shown reduction in delay of more than 30% when compared to both Xilinx Coregen and Xilinx Synthesis Tools generated models.
Autonomic configuration and recovery in a mobile agent‐based distributed event monitoring system

In this paper we present a framework for building policy‐based autonomic distributed agent systems. The autonomic mechanisms of configuration and recovery are supported through a distributed event processing model and a set of policy enforcement mechanisms embedded in an agent framework. Policies are event‐driven rules derived from the system's functional and non‐functional requirements. Agents in the network monitor the system state for policy violation conditions, generate appropriate events, and communicate them to other agents for cooperative filtering, aggregation, and handling. A set of agents perform policy enforcement actions whenever events signifying any policy violation conditions occur. Policies are defined using a specification framework based on XML. The policy enforcement agents interpret the policies given in XML. We illustrate the utility of this framework in the context of an agent‐based distributed network monitoring application. We also present an experimental evaluation of our approach. Copyright © 2006 John Wiley & Sons, Ltd.
Nonstationary job search environment and unemployment insurance : A tale of heterogeneous responses ∗

We take advantage of a quasi-experimental setting to test some predictions of standard nonstationary job search models. The fact that the unemployed differ in terms of their labor market positions elicits heterogeneous responses in terms of unemployment duration to an extension of the unemployment insurance (UI) entitlement period; our empirical exercise focus on such possibility. The results lend support to three theoretical predictions derived from these models. First, the increase in the UI entitlement period has a larger impact at durations closer to the extension period. Secondly, we find also that workers with exante lower probability of long-term unemployment react the least to an increase in the duration of UI benefits; in the data, these are typically low-wage workers. Finally, the results demonstrate also that, conditional on the unemployed’s labor market position, those with more binding liquidity constraints react the most to the extension, a result in line with the liquidity effect of UI.
The role of JAM‐A and PECAM‐1 in modulating leukocyte infiltration in inflamed and ischemic tissues

Innate and adaptive immunological responses are accompanied by leukocyte adhesion to the blood‐vessel wall and their subsequent infiltration into the underlying tissues. In the majority of the cases, leukocytes cross the endothelium by squeezing through the border of apposed endothelial cells, a process that is known as diapedesis. Many data suggest that proteins at endothelial junctions establish homophilic interactions with identical proteins, which are present on leukocytes. These interactions might then direct the passage of leukocytes through the endothelial border. In this review, we focus on two endothelial junctional proteins [junctional adhesion molecule‐A (JAM‐A) and PECAM], which play an important role in leukocyte diapedesis. In vivo data with blocking antibodies or inactivation of JAM‐A and PECAM genes indicate that the role of these two proteins depends on the stimulus and the experimental model used.
Stabilization of affine polynomial families: an LMI approach

This paper deals with the open issue of finding a stable element in an affine polynomial family, a difficult design problem occurring when stabilizing a given SISO plant with a fixed order compensator whose parameters are subject to interval constraints. Using a rank-one LMI formulation of the problem, a tractable linearization heuristic is developed, which proves efficient in practice, as illustrated by intensive numerical experiments.
Learning Disability: The Imaginary Disease

Introduction LD: The Imaginary Disease A Smoke Screen of Precision What Is LD and Where Did It Come From? LD Classification Models Testing Labeling Self-Fulfilling Prophecies Science or Scientism? Increasing Children's Options Predestination Readiness: Rush to Judgment Good Teaching What Really Is LD? Getting Along in Regular Education Getting Kids to Join the Right Club When Your Child Has Already Joined a Club