nils-herrmann/clean_scirepeval huggingface dataset:
Mindfulness Therapy and its Effects on Working Memory and Prospective Memory By

Mindfulness therapy is an increasingly popular practice that involves acute awareness of the present moment (Fletcher & Hayes, 2005). Recent research has also shown that practitioners show improvements in a range of cognitive skills (Mrazek, Franklin, Phillips, Baird, & Schooler, 2013). In particular, individuals in past literature have shown significant benefits in their working memory when practicing (Mrazek et al., 2013). Working memory is a cognitive ability that has also been correlated with an individual’s prospective memory during high stress situations (Jha, Stanley, Kiyonaga, Wong, & Gelfand, 2010). This raises the question; can mindfulness therapy impact both your working memory and prospective memory? Searching this can lead to potential benefits in aiding individuals with memory deficits. In particular, elders who suffer from dementia are more prone to prospective memory loss (Zimmermann & Meier, 2006). Therefore, if benefits of mindfulness therapy are supported in this study, further research could be performed for the elder population.  Participants were 65 undergraduate students from the University of MichiganDearborn. The students were evaluated for their level of mindfulness practice by a survey followed by three computerized exams. All individuals received two lexical decision tasks in randomized order, followed by the automated operation span task. These tasks measured the individuals’ ability to briefly retain information (working memory capacity) as well as completing a future task (prospective memory).  Results from this study showed support for previous working memory research suggesting that mindfulness therapy has a significant correlation with higher working memory (Mrazek et al., 2013). The research also showed that regular engagement in mindfulness also results in notable changes in how we complete future intentions, prospective memory. In particular it was displayed that individuals who practice specifically meditation have an improved focal prospective memory and a reduced ability in nonfocal prospective memory.  All individuals who practice mindfulness displayed a better working memory compared to those who do not. Individuals who explicitly practice meditation also have a change in their prospective memory. Those who practice meditation showed an improvement in their focal cues but a noteworthy impairment in their nonfocal cues. This suggests that those who practice meditation are so focused on the present that it impacts their ability to perform certain nonfocal future tasks. These findings are discussed in a larger framework of applications to individuals with declining cognitive abilities and/or high prospective memory demands. (e.g., medication adherence. MINDFULNESS THERAPY AND ITS EFFECTS ON MEMORY 1 Chapter
Introduction to Nonnegative Matrix Factorization

In this paper, we introduce and provide a short overview of nonnegative matrix factorization (NMF). Several aspects of NMF are discussed, namely, the application in hyperspectral imaging, geometry and uniqueness of NMF solutions, complexity, algorithms, and its link with extended formulations of polyhedra. In order to put NMF into perspective, the more general problem class of constrained low-rank matrix approximation problems is first briefly introduced.
Insulin degludec, an ultra-longacting basal insulin, versus insulin glargine in basal-bolus treatment with mealtime insulin aspart in type 2 diabetes (BEGIN Basal-Bolus Type 2): a phase 3, randomised, open-label, treat-to-target non-inferiority trial

Basal insulin therapy does not stop loss of β-cell function, which is the hallmark of type 2 diabetes mellitus, and thus diabetes control inevitably deteriorates. Insulin degludec is a new, ultra-longacting basal insulin. We aimed to assess efficacy and safety of insulin degludec compared with insulin glargine in patients with type 2 diabetes mellitus.



In this 52 week, phase 3, open-label, treat-to-target, non-inferiority trial, undertaken at 123 sites in 12 countries, we enrolled adults (aged ≥18 years) with type 2 diabetes mellitus and a glycated haemoglobin (HbA(1c)) of 7·0-10·0% after 3 months or more of any insulin regimen (with or without oral antidiabetic drugs). We randomly allocated eligible participants in a 3:1 ratio to receive once-daily subcutaneous insulin degludec or glargine, stratified by previous insulin regimen, via a central interactive response system. Basal insulin was titrated to a target plasma glucose concentration of 3·9-<5·0 mmol/L self-measured before breakfast. The primary outcome was non-inferiority of degludec to glargine measured by change in HbA(1c) from baseline to week 52 (non-inferiority limit of 0·4%) by ANOVA in the full analysis set. We assessed rates of hypoglycaemia in all treated patients. 
744 (99%) of 755 participants randomly allocated degludec and 248 (99%) of 251 allocated glargine were included in the full analysis set (mean age 58·9 years [SD 9·3], diabetes duration 13·5 years [7·3], HbA(1c) 8·3% [0·8], and fasting plasma glucose 9·2 mmol/L [3·1]); 618 (82%) and 211 (84%) participants completed the trial. After 1 year, HbA(1c) decreased by 1·1% in the degludec group and 1·2% in the glargine group (estimated treatment difference [degludec-glargine] 0·08%, 95% CI -0·05 to 0·21), confirming non-inferiority. Rates of overall confirmed hypoglycaemia (plasma glucose <3·1 mmol/L or severe episodes requiring assistance) were lower with degludec than glargine (11·1 vs 13·6 episodes per patient-year of exposure; estimated rate ratio 0·82, 95% CI 0·69 to 0·99; p=0·0359), as were rates of nocturnal confirmed hypoglycaemia (1·4 vs 1·8 episodes per patient-year of exposure; 0·75, 0·58 to 0·99; p=0·0399). Rates of severe hypoglycaemia seemed similar (0·06 vs 0·05 episodes per patient-year of exposure for degludec and glargine) but were too low for assessment of differences. Rates of other adverse events did not differ between groups.



A policy of suboptimum diabetes control to reduce the risk of hypoglycaemia and its consequences in advanced type 2 diabetes mellitus might be unwarranted with newer basal insulins such as degludec, which are associated with lower risks of hypoglycaemia than insulin glargine.



Novo Nordisk.
Knowing when you're wrong: building fast and reliable approximate query processing systems

Modern data analytics applications typically process massive amounts of data on clusters of tens, hundreds, or thousands of machines to support near-real-time decisions.The quantity of data and limitations of disk and memory bandwidth often make it infeasible to deliver answers at interactive speeds. However, it has been widely observed that many applications can tolerate some degree of inaccuracy. This is especially true for exploratory queries on data, where users are satisfied with "close-enough" answers if they can come quickly. A popular technique for speeding up queries at the cost of accuracy is to execute each query on a sample of data, rather than the whole dataset. To ensure that the returned result is not too inaccurate, past work on approximate query processing has used statistical techniques to estimate "error bars" on returned results. However, existing work in the sampling-based approximate query processing (S-AQP) community has not validated whether these techniques actually generate accurate error bars for real query workloads. In fact, we find that error bar estimation often fails on real world production workloads. Fortunately, it is possible to quickly and accurately diagnose the failure of error estimation for a query. In this paper, we show that it is possible to implement a query approximation pipeline that produces approximate answers and reliable error bars at interactive speeds.
CrossFire: An Analysis of Firefox Extension-Reuse Vulnerabilities

Extension architectures of popular web browsers have been carefully studied by the research community; however, the security impact of interactions between different extensions installed on a given system has received comparatively little attention. In this paper, we consider the impact of the lack of isolation between traditional Firefox browser extensions, and identify a novel extension-reuse vulnerability that allows adversaries to launch stealthy attacks against users. This attack leverages capability leaks from legitimate extensions to avoid the inclusion of security-sensitive API calls within the malicious extension itself, rendering extensions that use this technique difficult to detect through the manual vetting process that underpins the security of the Firefox extension ecosystem. We then present CROSSFIRE, a lightweight static analyzer to detect instances of extension-reuse vulnerabilities. CROSSFIRE uses a multi-stage static analysis to efficiently identify potential capability leaks in vulnerable, benign extensions. If a suspected vulnerability is identified, CROSSFIRE then produces a proof-ofconcept exploit instance – or, alternatively, an exploit template that can be adapted to rapidly craft a working attack that validates the vulnerability. To ascertain the prevalence of extension-reuse vulnerabilities, we performed a detailed analysis of the top 10 Firefox extensions, and ran further experiments on a random sample drawn from the top 2,000. The results indicate that popular extensions, downloaded by millions of users, contain numerous exploitable extension-reuse vulnerabilities. A case study also provides anecdotal evidence that malicious extensions exploiting extension-reuse vulnerabilities are indeed effective at cloaking themselves from extension vetters.
SpeechPy - A Library for Speech Processing and Recognition

SpeechPy is an open source Python package that contains speech preprocessing techniques, speech features, and important post-processing operations. It provides most frequent used speech features including MFCCs and filterbank energies alongside with the log-energy of filter-banks. The aim of the package is to provide researchers with a simple tool for speech feature extraction and processing purposes in applications such as Automatic Speech Recognition and Speaker Verification.
Arabic sign language recognition using leap motion sensor

Researchers in sign language recognition customized different sensors to capture hand signs. Gloves, digital cameras, depth cameras and Kinect were used alternatively in most systems. Due to signs closeness, input accuracy is a very essential constraint to reach a high recognition accuracy. Although previous systems accomplished high recognition accuracy, they suffer from stability in realistic environment due to variance in signing speed, lighting, etc... In this paper, a recognition system for ArSL has been developed based on a new digital sensor called “Leap Motion”. This sensor tackles the major issues in vision-based systems such as skin color, lighting etc... Leap motion captures hands and fingers movements in 3D digital format. The sensor throws 3D digital information in each frame of movement. These temporal and spatial features are fed into a Multi-layer perceptron Neural Network (MLP). The system was tested on 50 different dynamic signs (distinguishable without non-manual features) and the recognition accuracy reached 88% for two different persons. Although Leap motion tracks both hands accurately, unfortunately Leap motion does not track non-manual features. This system can be enhanced by adding other sensors to track other non-manual features such as facial expressions and body poses. The proposed sensor can work simultaneously with leap motion to capture all sign's features.
A PCB Dataset for Defects Detection and Classification

To coupe with the difficulties in the process of inspection and classification of defects in Printed Circuit Board (PCB), other researchers have proposed many methods. However, few of them published their dataset before, which hindered the introduction and comparison of new methods. In this paper, we published a synthesized PCB dataset containing 1386 images with 6 kinds of defects for the use of detection, classification and registration tasks. Besides, we proposed a reference based method to inspect and trained an end-to-end convolutional neural network to classify the defects. Unlike conventional approaches that require pixel-by-pixel processing, our method firstly locate the defects and then classify them by neural networks, which shows superior performance on our dataset.
Comparison of a high-flow humidified nasal cannula to nasal continuous positive airway pressure in children with acute bronchiolitis: experience in a pediatric intensive care unit

The objective of the current study is to compare the use of a nasal continuous positive airway pressure (nCPAP) to a high-flow humidified nasal cannula (HFNC) in infants with acute bronchiolitis, who were admitted to a pediatric intensive care unit (PICU) during two consecutive seasons. We retrospectively reviewed the medical records of all infants admitted to a PICU at a tertiary care French hospital during the bronchiolitis seasons of 2010/11 and 2011/12. Infants admitted to the PICU, who required noninvasive respiratory support, were included. The first noninvasive respiratory support modality was nCPAP during the 2010/11 season, while HFNC was used during the 2011/2012 season. We compared the length of stay (LOS) in the PICU; the daily measure of PCO2 and pH; and the mean of the five higher values of heart rate (HR), respiratory rate (RR), FiO2, and SpO2 each day, during the first 5 days. Thirty-four children met the inclusion criteria: 19 during the first period (nCPAP group) and 15 during the second period (HFNC group). Parameters such as LOS in PICU and oxygenation were similar in the two groups. Oxygen weaning occurred during the same time for the two groups. There were no differences between the two groups for RR, HR, FiO2, and CO2 evolution. HFNC therapy failed in three patients, two of whom required invasive mechanical ventilation, versus one in the nCPAP group.  We did not find a difference between HFNC and nCPAP in the management of severe bronchiolitis in our PICU. Larger prospective studies are required to confirm these findings.
Principles of cognitive science in education: the effects of generation, errors, and feedback.

Principles of cognitive science hold the promise of helping children to study more effectively, yet they do not always make successful transitions from the laboratory to applied settings and have rarely been tested in such settings. For example, self-generation of answers to questions should help children to remember. But what if children cannot generate anything? And what if they make an error? Do these deviations from the laboratory norm of perfect generation hurt, and, if so, do they hurt enough that one should, in practice, spurn generation? Can feedback compensate, or are errors catastrophic? The studies reviewed here address three interlocking questions in an effort to better implement a computer-based study program to help children learn: (1) Does generation help? (2) Do errors hurt if they are corrected? And (3) what is the effect of feedback? The answers to these questions are: Yes, generation helps; no, surprisingly, errors that are corrected do not hurt; and, finally, feedback is beneficial in verbal learning. These answers may help put cognitive scientists in a better position to put their well-established principles in the service of children's learning.
Development of power robot hand with shape adaptability using hydraulic McKibben muscles

We have developed a hydraulic McKibben artificial muscle which realizes great force density approximately ten times larger than the other conventional actuators. In this paper, we have applied this muscle to a power robot hand. The hand finger consists of metal links and the muscles. The contraction of the muscles generates the bending motion of the fingers. This hand has large holding capacity and shape adaptability to grasp objects. The experiments show that maximum holding force of the hand is 5000N. It can hold three types of different shaped objects; cylindrical objects of ø 267mm and ø165mm in diameter and a square cross section of width 200mm in side. This hand can be applied to various applications, for example rescue robots in disaster area and forestry industry.
Study on the coupled bending-torsional vibration of unbalanced rotor system with external excitations

In order to research characteristics of unbalanced rotor system with external excitations, a dynamic model of rotor was established. This model not only considered the influences of the gyroscopic effect and the gravity, but also includes two kinds of unbalance which named static/dynamic unbalance. Use the hypothesis of small angle, expression of forces and torque which caused by translation and rotational of these two unbalances and gravity was derived in detail. Using the Lagrange method with six degree of freedom, motion equations of the system were derived. Combined Runge-Kutta approach, dynamic equations of the model were solved. Moreover, nonlinear vibration characteristics were analyzed by means of three kinds of diagrams. Thus, theoretical foundations are established for optimization design and fault diagnosis of rotor-bearing system.
Thermal Bond Reliability of High Reliability New Palladium-Coated Copper Wire

Pd coated copper (PCC) wire and Au-Pd coated copper (APC) wire have been widely used in the field of LSI device. Recently, higher bond reliability at high temperature becomes increasingly important for on-vehicle devices. However, it has been reported that conventional PCC wire caused a bond failure at elevated temperatures. On the other hand, new-APC wire had higher reliability at higher temperature than conventional APC wire. New-APC wire has higher concentration of added element than conventional APC wire. In this paper, failure mechanism of conventional APC wire and improved mechanism of new-APC wire at high temperature were shown. New-APC wire is suitable for onvehicle devices.
Photocurrent in graphene harnessed by tunable intrinsic plasmons.

Graphene's optical properties in the infrared and terahertz can be tailored and enhanced by patterning graphene into periodic metamaterials with sub-wavelength feature sizes. Here we demonstrate polarization-sensitive and gate-tunable photodetection in graphene nanoribbon arrays. The long-lived hybrid plasmon-phonon modes utilized are coupled excitations of electron density oscillations and substrate (SiO2) surface polar phonons. Their excitation by s-polarization leads to an in-resonance photocurrent, an order of magnitude larger than the photocurrent observed for p-polarization, which excites electron-hole pairs. The plasmonic detectors exhibit photo-induced temperature increases up to four times as large as comparable two-dimensional graphene detectors. Moreover, the photocurrent sign becomes polarization sensitive in the narrowest nanoribbon arrays owing to differences in decay channels for photoexcited hybrid plasmon-phonons and electrons. Our work provides a path to light-sensitive and frequency-selective photodetectors based on graphene's plasmonic excitations.
Digital television based passive bistatic radar system for drone detection

Recently, the widespread availability of consumer grade drones is responsible for the new concerns of air traffic control. This paper investigates the feasibility of drone detection by passive bistatic radar (PBR) system. Wuhan University has successfully developed a digitally multichannel PBR system, which is dedicated for the drone detection. Two typical trials with a cooperative drone have been designed to examine the system's capability of small drone detection. The agreement between experimental results and ground truth indicate the effectiveness of sensing and processing method, which verifies the practicability and prospects of drone detection by this digitally multichannel PBR system.
Organization of CA1 projections to the subiculum: a PHA-L analysis in the rat.

The organization of CA1 projections to the rat subiculum was investigated with the anterograde tracer, Phaseolus vulgaris leucoagglutinin (PHA-L). Discrete iontophoretic injections of PHA-L were placed into various transverse positions of the CA1 field at different septotemporal levels of the hippocampus. The distribution of CA1 projections was observed in dissected and extended hippocampal preparations. CA1 cells located proximally in the field, i.e., close to the CA2 field, gave rise to projections that terminated in the distal third of the subiculum, i.e., close to the presubiculum. CA1 cells located distally in the field, i.e., close to the subiculum, gave rise to projections that terminated proximally in the subiculum, i.e., just across the CA1/subiculum border. CA1 cells in the middle of the field projected to a midtransverse portion of the subiculum. The same general pattern of projections was observed at all septotemporal levels of the hippocampus. Varicose fibers from the CA1 neurons terminated among the basal dendrites of the subicular pyramidal cells, within the pyramidal cell layer, and in the deep portion of the molecular layer. In addition to the CA1 to subiculum projections, the discrete PHA-L injections provided the opportunity of examining the extent of local and associational connections within CA1. In general, associational connections in CA1 are far less extensive than in CA3. CA1 is not entirely without local connections, however. CA1 cells located close to the subicular border, for example, originated axons that first innervated the proximal subiculum and then reentered the CA1 field at the interface between stratum radiatum and stratum lacunosum-moleculare. In most of the experimental cases, there were collaterals located in stratum oriens of CA1 that branched from the fibers directed toward the subiculum. Thus, the basal dendrites of CA1 cells may receive associational inputs. The organization of the CA1 projections to the subiculum is discussed in relation to the organization of CA3 projections to CA1 and the differential output of transverse regions of the subiculum. The possibility is raised that information may be "channeled" through the hippocampal formation via the transverse organization of these connections and ultimately distributed to different recipients of hippocampal efferent projections.
Instance Segmentation of Fibers from Low Resolution CT Scans via 3D Deep Embedding Learning

We propose a novel approach for automatic extraction (instance segmentation) of fibers from low resolution 3D X-ray computed tomography scans of short glass fiber reinforced polymers. We have designed a 3D instance segmentation architecture built upon a deep fully convolutional network for semantic segmentation with an extra output for embedding learning. We show that the embedding learning is capable of learning a mapping of voxels to an embedded space in which a standard clustering algorithm can be used to distinguish between different instances of an object in a volume. In addition, we discuss a merging post-processing method which makes it possible to process volumes of any size. The proposed 3D instance segmentation network together with our merging algorithm is the first known to authors knowledge procedure that produces results good enough, that they can be used for further analysis of low resolution fiber composites CT scans.