bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of windowing techniques for intramuscular EMG-based diagnostic, rehabilitative and assistive devices
Authors: Ashraf Hassan , Waris Asim , Gilani Syed Omer , Kashif Amer Sohail , Jamil Mohsin , Jochumsen Mads , Niazi Imran Khan 
Published: November 2020

Abstract

Objective. Intramuscular electromyography (iEMG) signals, invasively recorded, directly from the muscles are used to diagnose various neuromuscular disorders/diseases and to control rehabilitative and assistive robotic devices. iEMG signals are potentially being used in neurology, kinesiology, rehabilitation and ergonomics, to detect/diagnose various diseases/disorders. Electromyography-based classification and analysis systems are being designed and tested for the classification of various neuromuscular disorders and to control rehabilitative and assistive robotic devices. Many studies have explored parameters such as the pre-processing, feature extraction and selection of classifiers that can affect the performance and efficacy of iEMG-based classification systems. The pre-processing stage includes the removal of any unwanted noise from the original signal and windowing of the signal. Approach. This study investigated and presented the optimum windowing configurations for robust control and better performance results of an iEMG-based analysis system based on the stationarity rate (SR) and classification accuracy. Both disjoint and overlap, windowing techniques with varying window and overlap sizes have been investigated using a machine learning-based classification algorithm called linear discriminant analysis. Main results. The optimum window size ranges are from 200–300 ms for the disjoint and 225–300 ms for the overlap windowing technique, respectively. The inferred results show that for the overlap windowing technique the optimum range of overlap size is from 10%–30% of the length of window size. The mean classification accuracy (MCA) and mean stationarity rate (MSR) were found to be lower in the disjoint windowing technique compared to overlap windowing at all investigated overlap sizes. Statistical analysis (two-way analysis of variance test) showed that the MSR and MCA of the overlap windowing technique was significantly different at overlap sizes of 10%–30% (p-values < 0.05). Significance. The presented results can be used to achieve the best possible classification results and SR for any iEMG-based real-time diagnosis, detection and control system, which can enhance the performance of the system significantly.
About a plausible explanation of ϒ(10860)
Authors: Bruschini R 
Published: November 2020

Abstract
The experimental resonance ϒ(10860) presents some typical properties of conventional bottomonium states as well as apparently unconventional features. In this talk it is shown that some of the properties of ϒ(10860), namely its mass, dilepton decay width and ππϒ production rates, can be explained from its interpretation as ϒ(5s) bottomonium state, given that one has a consistent description of

b

b
¯

hybrid states. It is also pointed out that other puzzling properties (e.g. the dipion transition rate to hb
) can be understood under the assumption that ϒ(10860) is a mixing of the ϒ(5s) with the ground

b

b
¯

hybrid state.
Hadronic transitions in quarkonium
Authors: Castellá Jaume Tarrús 
Published: November 2020

Abstract
We report on a new approach to compute quarkonium hadronic transitions which does not rely on the standard twist expansion of the intermediate octet propagator. The latter cannot be justified for the energy release of hadronic transitions between heavy quarkonium states with different principal quantum numbers. Instead, we use that the octet state spectrum corresponds to the hybrid quarkonium one which can be obtained from nonrelativistic effective field theories (EFT) of QCD and lattice computations of the heavy-quark-antiquark static energies.
TGenBase - universal database for FAIR experiments
Authors: Lavrik E. 
Published: November 2020

Abstract
TGenBase is a ROOT-based virtual database which allows to communicate and store data in different underlying database management systems such as PostgreSQL, MySQL, SQLite, based on the configuration. It is primarily used for physics analysis parameter storage. However, it is universally applicable for any data storage task. There are several key features of the TGenBase for the user applications. It is a versioned insert only database, meaning that there is no need to update single entries and the whole history of the entries is available. The historical versions of the data can be queried with for a certain date. Being written as extension of the ROOT framework, it supports saving the ROOT objects such as graphs or histograms as well.
We provide the data description interface-a web-based application which allows the end-user to define what and in which form they want the data to be stored and define the relations between different entities. Based on this definition the database schemas, server and client side code is generated from templates and easily deployed. Another feature of this approach is that we are able to generate the full-fledged content management systems with user roles for read and write access. Data query, visualization and modification are available in C++, Python, Web and LabVIEW thin clients.
Strangeness production measured with HADES
Authors: Spies Simon 
Published: November 2020

Abstract
HADES is a multi-purpose, charged-particle detector operated at the SIS18 synchrotron located at the GSI Helmholtz Center for Heavy Ion Research in Darmstadt, Germany. The provided ion beam energies of 1-2 A GeV are among the lowest of all currently running heavy-ion experiments and result in the highest baryon net-densities at freeze-out in case of Au+Au collisions. At a beam energy of 1.23 A GeV, particles containing strangeness are produced below the quasi-free NN threshold energy. Since the missing energy has to be provided by the collision system, the investigation of the production of strangeness at such energies is a very promising probe of the created medium. The data sample measured with HADES includes multi-differential analysis of charged and neutral kaons, ϕ mesons and Λ hyperons. We present the analysis method and the results.
Detection of delay in post-monsoon agricultural burning across Punjab, India: potential drivers and consequences for air quality
Authors: Liu Tianjia , Mickley Loretta J , Gautam Ritesh , Singh Manoj K , DeFries Ruth S , Marlier Miriam E 
Published: November 2020

Abstract
Since the Green Revolution in the mid-1960s, a widespread transition to a rice–wheat rotation in the Indian state of Punjab has led to steady increases in crop yield and production. After harvest of the summer monsoon rice crop, the burning of excess crop residue in Punjab from October to November allows for rapid preparation of fields for sowing of the winter wheat crop. Here we use daily satellite remote sensing data to show that the timing of peak post-monsoon fire activity in Punjab and regional aerosol optical depth (AOD) has shifted later by approximately two weeks in Punjab from 2003 to 2016. This shift is consistent with delays of 11–15 d in the timing of maximum greenness of the monsoon crop and smaller delays of 4–6 d in the timing of minimum greenness during the monsoon-to-winter crop transition period. The resulting compression of the harvest-to-sowing period coincides with a 42% increase in total burning and 55% increase in regional AOD. Potential drivers of these trends include agricultural intensification and a recent groundwater policy that delays sowing of the monsoon crop. The delay and amplification of burning into the late post-monsoon season suggest greater air quality degradation and public health consequences across the densely populated Indo-Gangetic Plain.
Empirical anomaly measure for finite-variance processes
Authors: Maraj Katarzyna , Szarek Dawid , Sikora Grzegorz , Wyłomańska Agnieszka 
Published: November 2020

Abstract
Anomalous diffusion phenomena are observed in many areas of interest. They manifest themselves in deviations from the laws of Brownian motion (BM), e.g. in the non-linear growth (mostly power-law) in time of the ensemble average mean squared displacement (MSD). When we analyze the real-life data in the context of anomalous diffusion, the primary problem is the proper identification of the type of the anomaly. In this paper, we introduce a new statistic, called empirical anomaly measure (EAM), that can be useful for this purpose. This statistic is the sum of the off-diagonal elements of the sample autocovariance matrix for the increments process. On the other hand, it can be represented as the convolution of the empirical autocovariance function with time lags. The idea of the EAM is intuitive. It measures dependence between the ensemble-averaged MSD of a given process from the ensemble-averaged MSD of the classical BM. Thus, it can be used to measure the distance between the anomalous diffusion process and normal diffusion. In this article, we prove the main probabilistic characteristics of the EAM statistic and construct the formal test for the recognition of the anomaly type. The advantage of the EAM is the fact that it can be applied to any data trajectories without the model specification. The only assumption is the stationarity of the increments process. The complementary summary of the paper constitutes of Monte Carlo simulations illustrating the effectiveness of the proposed test and properties of EAM for selected processes.
The role of nanostructure morphology of nickel-infused alumina on solar-thermal energy conversion
Authors: Wang Xuanjie , Hsieh Mei-Li , Bur James A , Lin Shawn-Yu , Narayanan Shankar 
Published: November 2020

Abstract
Solar-thermal energy conversion can be useful in many applications, including water desalination, and thermal energy storage. In this regard, using spectrally-selective solar absorbers is vital due to their high solar absorptance and low thermal emittance. While selective absorbers can be created using a wide range of nanomaterials, the underlying geometry may control the overall performance of solar-thermal energy conversion. With different geometries, it is possible to obtain a wide range of optical responses ranging from broadband to selective absorption of light. In this study, we focus on the role of nanostructure morphology of nickel-infused alumina (Ni/NPA) based spectrally-selective solar absorbers. This study demonstrates the use of the design of experiments to analyze the effect of various geometric factors on the resulting optical response of Ni/NPA in the context of solar-thermal energy conversion. We show how this approach can provide a unique insight into the role of various geometric factors on the solar absorptance and thermal emittance of Ni/NPA-based absorbers, and demonstrate how it can guide the development of spectrally-selective materials. We believe a similar approach can be useful in the development of other optical materials for different applications.
Repeatable room-temperature self-healing memory device based on gelatin films
Authors: Chang Yu-Chi , Jian Jia-Cheng , Hsu Ya Lan , Huang Wei-Yun , Chen Zhao-Cheng , Liu Kuan-Miao 
Published: November 2020

Abstract
Flexible gelatin resistive memory device exhibits a high ON/OFF ratio of over 106. Moreover, the bended gelatin resistive memory device can efficiently heal at room temperature without any external stimulus. This self-healing behavior of gelatin resistive memory device was demonstrated based on the metal chelating ligand. Al ions migrating from the top radio frequency Al electrode contributed to the construction of the metal chelating ligand. The carboxylates of gelatin can form multi-dentate coordination compounds with Al ions, which can restore the memory properties of the gelatin resistive memory device. Thus, Al ion migration from the top Al electrodes plays an important role in self-healing capability. The effect of Al ions on the self-healing mechanism was investigated by using secondary ion mass spectrometry, which is useful for the characterization of Al migration from the top electrode. This capability for restoring the electrical properties of gelatin memory device is desirable for flexible electronics and represents a major step toward self-healable bioelectronics.
Canard resonance: on noise-induced ordering of trajectories in heterogeneous networks of slow-fast systems
Authors: D’Huys Otti , Veltz Romain , Dolcemascolo Axel , Marino Francesco , Barland Stéphane 
Published: November 2020

Abstract
We analyse the dynamics of a network of semiconductor lasers coupled via their mean intensity through a non-linear optoelectronic feedback loop. We establish experimentally the excitable character of a single node, which stems from the slow-fast nature of the system, adequately described by a set of rate equations with three well separated time scales. Beyond the excitable regime, the system undergoes relaxation oscillations where the nodes display canard dynamics. We show numerically that, without noise, the coupled system follows an intricate canard trajectory, with the nodes switching on one by one. While incorporating noise leads to a better correspondence between numerical simulations and experimental data, it also has an unexpected ordering effect on the canard orbit, causing the nodes to switch on closer together in time. We find that the dispersion of the trajectories of the network nodes in phase space is minimized for a non-zero noise strength, and call this phenomenon canard resonance.
Consumption of dietary nuts in midlife and risk of cognitive impairment in late-life: the Singapore Chinese Health Study
Authors: Jiang Yi-Wen , Sheng Li-Ting , Feng Lei , Pan An , Koh Woon-Puay 
Published: November 2020

Abstract

Background
evidence from prospective studies investigating the association between consumption of nuts in midlife and risk of cognitive impairment in late life is limited.

Methods
this study analysed data from 16,737 participants in a population-based cohort, the Singapore Chinese Health Study. Intake of nuts was assessed using a validated food-frequency questionnaire at baseline (1993–1998), when participants were 45–74 years old (mean age = 53.5 years). Cognitive function was tested using the Singapore modified Mini-Mental State Examination during the third follow-up visit (2014–2016), when participants were 61–96 years old (mean age = 73.2 years). Cognitive impairment was defined using education-specific cut-off points. Logistic regression models were used to estimate the odds ratio (OR) and the 95% confidence interval (CI) for the association between intake and risk of cognitive impairment.

Results
cognitive impairment was identified in 2,397 (14.3%) participants. Compared with those who consumed &lt;1 serving/month of nuts, participants who consumed 1–3 servings/month, 1 serving/week and ≥2 servings/week had 12% (95% CI 2–20%), 19% (95% CI 4–31%) and 21% (2–36%) lower risk of cognitive impairment, respectively (P-trend = 0.01). Further adjustment for intake of unsaturated fatty acids attenuated the association to non-significance. Mediation analysis showed that the 50.8% of the association between nuts and risk of cognitive impairment was mediated by the intake of total unsaturated fatty acids (P &lt; 0.001).

Conclusion
higher intake of nuts in midlife was related to a lower risk of cognitive impairment in late life, which was partly mediated by unsaturated fatty acids.
Prevalence of atrial fibrillation and outcomes in older long-term care residents: a systematic review
Authors: Ritchie Leona A , Oke Oluwakayode B , Harrison Stephanie L , Rodgers Sarah E , Lip Gregory Y H , Lane Deirdre A 
Published: November 2020

Abstract

Background
anticoagulation is integral to stroke prevention for atrial fibrillation (AF), but there is evidence of under-treatment in older people in long-term care (LTC).

Objective
to synthesise evidence on the prevalence and outcomes (stroke, mortality or bleeding) of AF in LTC and the factors associated with the prescription of anticoagulation.

Methods
studies were identified from Medline, CINAHL, PsycINFO, Scopus and Web of Science from inception to 31 October 2019. Two reviewers independently applied the selection criteria and assessed the quality of studies using the Newcastle Ottawa Scale.

Results
twenty-nine studies were included. Prevalence of AF was reported in 21 studies, ranging from 7 to 38%. Two studies reported on outcomes based on the prescription of anticoagulation or not; one reported a reduction in the ischaemic stroke event rate associated with anticoagulant (AC) prescription (2.84 per 100 person years, 95% confidence interval [CI]: 1.98–7.25 versus 3.95, 95% CI: 2.85–10.08) and a non-significant increase in intracranial haemorrhage rate (0.71 per 100 person years, 95% CI: 0.29–2.15 versus 0.65, 95% CI: 0.29–1.93). The second study reported a 76% lower chance of ischaemic stroke with AC prescription and a low incidence of bleeding (n = 4 events). Older age, dementia/cognitive impairment and falls/falls risk were independently associated with the non-prescription of anticoagulation. Conversely, previous stroke/transient ischaemic attack and thromboembolism were independently associated with an increased prescription of anticoagulation.

Conclusion
estimates of AF prevalence and factors associated with AC prescription varied extensively. Limited data on outcomes prevent the drawing of definitive conclusions. We recommend panel data collection and systems for linkage to create longitudinal cohorts to provide more robust evidence.
Clinical and Financial Implications of Second-Opinion Surgical Pathology Review
Authors: Johnson Steven M , Samulski Teresa D , O’Connor Siobhan M , Smith Scott V , Funkhouser William K , Broaddus Russell R , Calhoun Benjamin C 
Published: November 2020

Abstract

Objectives
Second-opinion pathology review identifies clinically significant diagnostic discrepancies for some patients. Discrepancy rates and laboratory-specific costs in a single health care system for patients referred from regional affiliates to a comprehensive cancer center (“main campus”) have not been reported.

Methods
Main campus second-opinion pathology cases for 740 patients from eight affiliated hospitals during 2016 to 2018 were reviewed. Chart review was performed to identify changes in care due to pathology review. To assess costs of pathology interpretation, reimbursement rates for consultation Current Procedural Terminology billing codes were compared with codes that would have been used had the cases originated at the main campus.

Results
Diagnostic discrepancies were identified in 104 (14.1%) patients, 30 (4.1%) of which resulted in a change in care. In aggregate, reimbursement for affiliate cases was 65.6% of the reimbursement for the same cases had they originated at the main campus. High-volume organ systems with low relative consultation reimbursement included gynecologic, breast, and thoracic.

Conclusions
Preventable diagnostic errors are reduced by pathology review for patients referred within a single health care system. Although the resulting changes in care potentially lead to overall cost savings, the financial value of referral pathology review could be improved.
A deep learning approach for filtering structural variants in short read sequencing data
Authors: Liu Yongzhuang , Huang Yalin , Wang Guohua , Wang Yadong 
Published: November 2020

AbstractShort read whole genome sequencing has become widely used to detect structural variants in human genetic studies and clinical practices. However, accurate detection of structural variants is a challenging task. Especially existing structural variant detection approaches produce a large proportion of incorrect calls, so effective structural variant filtering approaches are urgently needed. In this study, we propose a novel deep learning-based approach, DeepSVFilter, for filtering structural variants in short read whole genome sequencing data. DeepSVFilter encodes structural variant signals in the read alignments as images and adopts the transfer learning with pre-trained convolutional neural networks as the classification models, which are trained on the well-characterized samples with known high confidence structural variants. We use two well-characterized samples to demonstrate DeepSVFilter’s performance and its filtering effect coupled with commonly used structural variant detection approaches. The software DeepSVFilter is implemented using Python and freely available from the website at https://github.com/yongzhuang/DeepSVFilter.
glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data
Authors: Ahlmann-Eltze Constantin , Huber Wolfgang 
Published: November 2020

Abstract

Motivation
The Gamma-Poisson distribution is a theoretically and empirically motivated model for the sampling variability of single cell RNA-sequencing counts and an essential building block for analysis approaches including differential expression analysis, principal component analysis and factor analysis. Existing implementations for inferring its parameters from data often struggle with the size of single cell datasets, which can comprise millions of cells; at the same time, they do not take full advantage of the fact that zero and other small numbers are frequent in the data. These limitations have hampered uptake of the model, leaving room for statistically inferior approaches such as logarithm(-like) transformation.

Results
We present a new R package for fitting the Gamma-Poisson distribution to data with the characteristics of modern single cell datasets more quickly and more accurately than existing methods. The software can work with data on disk without having to load them into RAM simultaneously.

Availabilityand implementation
The package glmGamPoi is available from Bioconductor for Windows, macOS and Linux, and source code is available on github.com/const-ae/glmGamPoi under a GPL-3 license. The scripts to reproduce the results of this paper are available on github.com/const-ae/glmGamPoi-Paper.

Supplementary information
Supplementary data are available at Bioinformatics online.