nils-herrmann/clean_scirepeval huggingface dataset:
Vacuum-assisted closure therapy increases local interleukin-8 and vascular endothelial growth factor levels in traumatic wounds.

Clinical observations are suggesting accelerated granulation tissue formation in traumatic wounds treated with vacuum-assisted closure (VAC). Aim of this study was to determine the impact of VAC therapy versus alternative Epigard application on local inflammation and neovascularization in traumatic soft tissue wounds.



Thirty-two patients with traumatic wounds requiring temporary coverage (VAC n = 16; Epigard n = 16) were included. At each change of dressing, samples of wound fluid and serum were collected (n = 80). The cytokines interleukin (IL)-6, IL-8, vascular endothelial growth factor (VEGF), and fibroblast growth factor-2 were measured by ELISA. Wound biopsies were examined histologically for inflammatory cells and degree of neovascularization present.



All cytokines were found to be elevated in wound fluids during both VAC and Epigard treatment, whereas serum concentrations were negligible or not detectable. In wound fluids, significantly higher IL-8 (p < 0.001) and VEGF (p < 0.05) levels were detected during VAC therapy. Furthermore, histologic examination revealed increased neovascularization (p < 0.05) illustrated by CD31 and von Willebrand factor immunohistochemistry in wound biopsies of VAC treatment. In addition, there was an accumulation of neutrophils as well as an augmented expression of VEGF (p < 0.005) in VAC wound biopsies.



This study suggests that VAC therapy of traumatic wounds leads to increased local IL-8 and VEGF concentrations, which may trigger accumulation of neutrophils and angiogenesis and thus, accelerate neovascularization.
Improving classification accuracy of feedforward neural networks for spiking neuromorphic chips

Deep Neural Networks (DNN) achieve human level performance in many image analytics tasks but DNNs are mostly deployed to GPU platforms that consume a considerable amount of power. New hardware platforms using lower precision arithmetic achieve drastic reductions in power consumption. More recently, brain-inspired spiking neuromorphic chips have achieved even lower power consumption, on the order of milliwatts, while still offering real-time processing. However, for deploying DNNs to energy efficient neuromorphic chips the incompatibility between continuous neurons and synaptic weights of traditional DNNs, discrete spiking neurons and synapses of neuromorphic chips need to be overcome. Previous work has achieved this by training a network to learn continuous probabilities, before it is deployed to a neuromorphic architecture, such as IBM TrueNorth Neurosynaptic System, by random sampling these probabilities. The main contribution of this paper is a new learning algorithm that learns a TrueNorth configuration ready for deployment. We achieve this by training directly a binary hardware crossbar that accommodates the TrueNorth axon configuration constrains and we propose a different neuron model. Results of our approach trained on electroencephalogram (EEG) data show a significant improvement with previous work (76% vs 86% accuracy) while maintaining state of the art performance on the MNIST handwritten data set.
Design and optimization of a compact, large amplification XY flexure-mechanism

This article presents the design methodology, optimization, and computational verification of a compact, high-gain planar XY flexure mechanism. The presented mechanism consists of a decoupled XY mechanism, and a modified Scott-Russel mechanism, which maintain linear XY motion, and amplify the input piezoelectric actuator (PEA) displacement respectively. Each mechanism offers the potential for use in isolation. When operated together, the combined mechanism is capable of nanometer scale precision and millimeter scale range in a vacuum-compatible design. The presented mechanism could therefore be used in micro-assembly operations including those performed in electron microscopes. The design methodology and mechanism models are presented, with the selected design computationally optimized and analyzed. By using a broad design space, and minimizing assumptions, the optimized mechanism produces workspace of approximately 930 × 940 μm2 from 15 μm of input displacement.
Online job dispatching and scheduling in edge-clouds

In edge-cloud computing, a set of edge servers are deployed near the mobile devices such that these devices can offload jobs to the servers with low latency. One fundamental and critical problem in edge-cloud systems is how to dispatch and schedule the jobs so that the job response time (defined as the interval between the release of a job and the arrival of the computation result at its device) is minimized. In this paper, we propose a general model for this problem, where the jobs are generated in arbitrary order and times at the mobile devices and offloaded to servers with both upload and download delays. Our goal is to minimize the total weighted response time over all the jobs. The weight is set based on how latency sensitive the job is. We derive the first online job dispatching and scheduling algorithm in edge-clouds, called OnDisc, which is scalable in the speed augmentation model; that is, OnDisc is (1 + ε)-speed O(1/ε)-competitive for any constant ε ∊ (0,1). Moreover, OnDisc can be easily implemented in distributed systems. Extensive simulations on a real-world data-trace from Google show that OnDisc can reduce the total weighted response time dramatically compared with heuristic algorithms.
Attentive Semantic Video Generation Using Captions

This paper proposes a network architecture to perform variable length semantic video generation using captions. We adopt a new perspective towards video generation where we allow the captions to be combined with the long-term and short-term dependencies between video frames and thus generate a video in an incremental manner. Our experiments demonstrate our network architecture’s ability to distinguish between objects, actions and interactions in a video and combine them to generate videos for unseen captions. The network also exhibits the capability to perform spatio-temporal style transfer when asked to generate videos for a sequence of captions. We also show that the network’s ability to learn a latent representation allows it generate videos in an unsupervised manner and perform other tasks such as action recognition.
Automated misspelling detection and correction in clinical free-text records

Accurate electronic health records are important for clinical care and research as well as ensuring patient safety. It is crucial for misspelled words to be corrected in order to ensure that medical records are interpreted correctly. This paper describes the development of a spelling correction system for medical text. Our spell checker is based on Shannon's noisy channel model, and uses an extensive dictionary compiled from many sources. We also use named entity recognition, so that names are not wrongly corrected as misspellings. We apply our spell checker to three different types of free-text data: clinical notes, allergy entries, and medication orders; and evaluate its performance on both misspelling detection and correction. Our spell checker achieves detection performance of up to 94.4% and correction accuracy of up to 88.2%. We show that high-performance spelling correction is possible on a variety of clinical documents.
Abstract and Concrete Categories - The Joy of Cats

and Concrete Categories The Joy of Cats Dedicated to Bernhard Banaschewski The newest edition of the file of the present book can be downloaded from http://katmat.math.uni-bremen.de/acc The authors are grateful for any improvements, corrections, and remarks, and can be reached at the addresses Jǐŕı Adámek, email: adamek@iti.cs.tu-bs.de Horst Herrlich, email: horst.herrlich@t-online.de George E. Strecker, email: strecker@math.ksu.edu All corrections will be awarded, besides eternal gratefulness, with a piece of delicious cake! You can claim your cake at the KatMAT Seminar, University of Bremen, at any Tuesday (during terms).  A copy of the license is included in the section entitled “GNU Free Documentation License”. See p. 512 ff.
Design of ANSI S1.11 Filter Bank for Digital Hearing Aids

Existing digital hearing aids, to our knowledge, all exclude ANSI S1.11-compliant filter banks because of the high computational complexity. Most ANSI S1.11 designs are IIR- based and only applicable in applications where linear phase is not important. This paper presents an FIR-based ANSI S1.11 filter bank for digital hearing aids, which adopts a multi-rate architecture to reduce the data rates on the bandwidth-limited bands. A systematic way is also proposed to minimize the FIR orders thereof. In an 18-band digital hearing aid with 24 kHz input sampling rate, the proposed design with linear phase has comparable computational complexity with IIR filter banks. Moreover, our design requires only 4% multiplications and additions of a straightforward FIR implementation.
Relationships between land use, spatial scale and stream macroinvertebrate communities

1. The structure of lotic macroinvertebrate communities may be strongly influenced by land-use practices within catchments. However, the relative magnitude of influence on the benthos may depend upon the spatial arrangement of different land uses in the catchment. 2. We examined the influence of land-cover patterns on in-stream physico-chemical features and macroinvertebrate assemblages in nine southern Appalachian headwater basins characterized by a mixture of land-use practices. Using a geographical information system (GIS)/remote sensing approach, we'quantified land-cover at five spatial scales; the entire catchment, the-Tiparian corridojvand three riparian 'sub-corridors' extending 200, 1000 and 2000 m upstream of sampling reaches. 3. Stream water chemistry was generally related to features at the catchment scale. Conversely, stream temperature and substratum characteristics were strongly influenced by land-cover patterns at the riparian corridor and sub-corridor scales. 4. Macroinvertebrate assemblage structure was quantified using the slope of rankabundance plots, and further described using diversity and evenness indices. Taxon richness ranged from 24 to 54 among sites, and the analysis of rank-abundance curves defined three distinct groups with high, medium and low diversity. In general, other macroinvertebrate indices were in accord with rank-abundance groups, with richness and evenness decreasing among sites with maximum stream temperature. 5. Macroinvertebrate indices were most closely related to land-cover patterns evaluated at the 200 m sub-corridor scale, suggesting that local, streamside development effectively alters assemblage structure. 6. Results suggest that differences in macroinvertebrate assemblage structure can be explained by land-cover patterns when appropriate spatial scales, are employed. In actdition, the influence of riparian forest patches on in-stream habitat features (e.g. the thermal regime) may be critical to the distribution of many taxa in headwater streams draining catchments with mixed land-use practices.
Clinical and economic burden of surgical site infection (SSI) and predicted financial consequences of elimination of SSI from an English hospital.

Although surgical site infections (SSIs) are known to be associated with increased length of stay (LOS) and additional cost, their impact on the profitability of surgical procedures is unknown.



To determine the clinical and economic burden of SSI over a two-year period and to predict the financial consequences of their elimination.



SSI surveillance and Patient Level Information and Costing System (PLICS) datasets for patients who underwent major surgical procedures at Plymouth Hospitals NHS Trust between April 2010 and March 2012 were consolidated. The main outcome measures were the attributable postoperative length of stay (LOS), cost, and impact on the margin differential (profitability) of SSI. A secondary outcome was the predicted financial consequence of eliminating all SSIs.



The median additional LOS attributable to SSI was 10 days [95% confidence interval (CI): 7-13 days] and a total of 4694 bed-days were lost over the two-year period. The median additional cost attributable to SSI was £5,239 (95% CI: 4,622-6,719) and the aggregate extra cost over the study period was £2,491,424. After calculating the opportunity cost of eliminating all SSIs that had occurred in the two-year period, the combined overall predicted financial benefit of doing so would have been only £694,007. For seven surgical categories, the hospital would have been financially worse off if it had successfully eliminated all SSIs.



SSI causes significant clinical and economic burden. Nevertheless the current system of reimbursement provided a financial disincentive to their reduction.
Videolization: knowledge graph based automated video generation from web content

Web content nowadays can also be accessed through new generation of Internet connected TVs. However, these products failed to change users’ behavior when consuming online content. Users still prefer personal computers to access Web content. Certainly, most of the online content is still designed to be accessed by personal computers or mobile devices. In order to overcome the usability problem of Web content consumption on TVs, this paper presents a knowledge graph based video generation system that automatically converts textual Web content into videos using semantic Web and computer graphics based technologies. As a use case, Wikipedia articles are automatically converted into videos. The effectiveness of the proposed system is validated empirically via opinion surveys. Fifty percent of survey users indicated that they found generated videos enjoyable and 42 % of them indicated that they would like to use our system to consume Web content on their TVs.
Applications of the FDTD method to lightning electromagnetic pulse and surge simulations

Electromagnetic computation methods (ECMs) have been widely used in analyzing lightning electromagnetic pulses (LEMPs) and lightning-caused surges in various systems. One of the advantages of ECMs, in comparison with circuit simulation methods, is that they allow a self-consistent full-wave solution for both the transient current distribution in a 3D conductor system and resultant electromagnetic fields, although they are computationally expensive. Among ECMs, the finite-difference time-domain (FDTD) method for solving Maxwell's equations has been most frequently used in LEMP and surge simulations. In this paper, we review applications of the FDTD method to LEMP and surge simulations, including (i) lightning electromagnetic fields at close and far distances; (ii) lightning surges on overhead power transmission line conductors and towers, (iii) lightning surges on overhead distribution and telecommunication lines; (iv) lightning electromagnetic environment in power substations; (v) lightning surges in wind-turbine-generator towers; (vi) lightning surges in photovoltaic (PV) arrays; (vii) lightning electromagnetic environment in electric vehicles (EVs); (viii) lightning electromagnetic environment in airborne vehicles; (ix) lightning surges and electromagnetic environment in buildings; and (x) surges on grounding electrodes.
Multidetector high-resolution computed tomography of the lungs: protocols and applications.

Advances in computed tomography (CT) scanner technology have made isotropic volumetric, multiplanar high-resolution lung imaging possible in a single breath-hold, a significant advance over the incremental high-resolution CT (HRCT) technique in which noncontiguous images sampled the lung, but lacked anatomic continuity. HRCT of the lungs is an established imaging technique for the diagnosis and management of interstitial lung disease, emphysema, and small airway disease, providing a noninvasive detailed evaluation of the lung parenchyma, and providing information about the lungs as a whole and focally. In addition to having a high degree of specificity for diagnosing conditions such as emphysema, sarcoidosis, usual interstitial pneumonitis, Langerhans cell histiocytosis, and small airway disease, there is a growing body of medical evidence to support the use of HRCT findings or diagnosis to predict patient prognosis. In this article, we review the technique, advantages, and clinical applications of the current HRCT technique.
Anthropometry of elderly residents in the city of São Paulo, Brazil.

The article presents gender and age-specific selected anthropometric data for a representative sample of elderly Brazilians in the city of São Paulo. This was a cross-sectional, population-based household survey. A total of 1,894 older adults (men and women, > 60 years) were examined from January to March 2001. Data were presented as means and percentiles for body mass (BM); height or stature (ST); body mass index (BMI); waist (WC), hip (HC), arm (AC), and calf (CC) circumferences; triceps skinfold thickness (TST); and arm muscle circumference (AMC), and differences were described according to age (all variables) and gender (BMI). Except for HC (men), all anthropometric variables were lower in the oldest than in the youngest individuals (p < 0.01) in both genders. BMI was significantly higher (p < 0.01) in women than men (all age groups). The observations suggest that there is loss of muscle mass and redistribution and reduction of fat mass with age (both genders). The data can be used in clinical practice and epidemiological studies based on interpretation of anthropometric measurements in the elderly in São Paulo.
Selection of entropy-measure parameters for knowledge discovery in heart rate variability data

Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds r F and r L for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning r F and r L showed that there is no optimal choice, but r = r F = r L is reasonable with r = rChon or r = 0.2σ. Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical conditions are unknown beforehand, compromises had to be made. Optimal parameter combinations are suggested for the methods considered. Yet, due to the high number of potential parameter combinations, further investigations of entropy for heart rate variability data will be necessary.
Exergy Analysis and Human Body Thermal Comfort Conditions: Evaluation of Different Body Compositions

This article focuses on studying the effects of muscle and fat percentages on the exergy behavior of the human body under several environmental conditions. The main objective is to relate the thermal comfort indicators with exergy rates, resulting in a Second Law perspective to evaluate thermal environment. A phenomenological model is proposed of the human body with four layers: core, muscle, fat and skin. The choice of a simplified model is justified by the facility to variate the amount of mass in each tissue without knowing how it spreads around the body. After validated, the model was subjected to a set of environmental conditions and body compositions. The results obtained indicate that the area normalization (Watts per square meter) may be used as a safe generalization for the exergy transfer to environment. Moreover, the destroyed exergy itself is sufficient to evaluate the thermal sensation when the model is submitted to environmental temperatures lower than that considered for the thermal neutrality condition (and, in this text, the thermal comfort) . Nevertheless, for environments with temperatures higher than the calculated for the thermal neutrality, the combination of destroyed exergy and the rate of exergy transferred to the environment should be used to properly evaluate thermal comfort.
Parametric survival models for interval-censored data with time-dependent covariates.

We present a parametric family of regression models for interval-censored event-time (survival) data that accomodates both fixed (e.g. baseline) and time-dependent covariates. The model employs a three-parameter family of survival distributions that includes the Weibull, negative binomial, and log-logistic distributions as special cases, and can be applied to data with left, right, interval, or non-censored event times. Standard methods, such as Newton-Raphson, can be employed to estimate the model and the resulting estimates have an asymptotically normal distribution about the true values with a covariance matrix that is consistently estimated by the information function. The deviance function is described to assess model fit and a robust sandwich estimate of the covariance may also be employed to provide asymptotically robust inferences when the model assumptions do not apply. Spline functions may also be employed to allow for non-linear covariates. The model is applied to data from a long-term study of type 1 diabetes to describe the effects of longitudinal measures of glycemia (HbA1c) over time (the time-dependent covariate) on the risk of progression of diabetic retinopathy (eye disease), an interval-censored event-time outcome.