bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic detection of ischemic-stroke-lesion with CNN segmentation: a study
Authors: Al Attar FerasNadhimHasoon , Kadry Seifedine , Manic K. Suresh , Meqdad Maytham N. 
Published: September 2022

Abstract
The vital organ in human physiology is the brain, and abnormality in the brain will reason for various behavioural problems. Ischemic-Stroke is a medical emergency, and early detection and action will help the patient recover quickly. This scheme aims to implement Convolutional-Neural-Network (CNN) segmentation method to extract and evaluate the infected portion from the MRI slice of the brain. In our study the pre-trained UNet scheme is adopted to extract the stroke region from the Flair modality MRI slice with axial-, coronal- and sagittal plane. In this work, the ISLES2015 database is used for the experimental investigation. The segmented portion is further evaluated to the ground-truth and the metrics such as Jaccard, Dice and Accuracy are computed. The experimental investigation is implemented using Python software. The experimental outcome of this research proves that the proposed CNN scheme aids to improve segmentation accuracy on axial-plane images compared with other images. The performance of the CNN segmentation scheme is then validated with other related results existing in the literature. The outcome of this study confirms that UNet supported technique helps extract the stroke lesion from the MRI slice with more accurate accuracy.
Exposure of agricultural workers in California to wildfire smoke under past and future climate conditions
Authors: Marlier Miriam E , Brenner Katherine I , Liu Jia Coco , Mickley Loretta J , Raby Sierra , James Eric , Ahmadov Ravan , Riden Heather 
Published: September 2022

Abstract
Wildfire activity in the western U.S. has increased in frequency and severity in recent decades. Wildfire smoke emissions contribute to elevated fine particulate matter (PM2.5) concentrations that are dangerous to public health. Due to the outdoor and physically demanding nature of their work, agricultural workers are particularly vulnerable to wildfire smoke pollution. In this study, we quantify the potential exposure of agricultural workers in California to past (2004–2009) and future (2046–2051) smoke PM2.5. We find that while absolute increases in smoke PM2.5 exposure are largest in northern California, agricultural regions in the Central Valley and Central Coast may be highly vulnerable to future increases in smoke PM2.5 concentrations. We find an increase from 6 to 8 million worker smoke exposure days (+35%) of ‘smokewave’ exposure for agricultural workers across the state under future climate conditions, with the largest increases in Tulare, Monterey, and Fresno counties. Under future climate conditions, we find 1.9 million worker smoke exposure days of agricultural worker exposure to levels of total PM2.5 pollution deemed ‘Unhealthy for Sensitive Groups.’ This is a 190% increase over past climate conditions. Wildfire smoke PM2.5 contributes, on average, to more than 90% of these daily PM2.5 exceedances compared with non-fire sources of air pollution. Using the recent extreme wildfire season of 2020 as a case study, we show that existing monitoring networks do not provide adequate sampling of PM2.5 in many future at-risk wildfire regions with large numbers of agricultural workers. Policies will need to consider the changing patterns of smoke PM2.5 exposure under future climate conditions to better protect outdoor agricultural workers.
Cotangent bundle reduction and Routh reduction for polysymplectic manifolds
Authors: Capriotti S , Díaz V , García-Toraño Andrés E , Mestdag T 
Published: September 2022

Abstract
We discuss Lagrangian and Hamiltonian field theories that are invariant under a symmetry group. We apply the polysymplectic reduction theorem for both types of field equations and we investigate aspects of the corresponding reconstruction process. We identify the polysymplectic structures that lie at the basis of cotangent bundle reduction and Routh reduction in this setting and we relate them by means of the Routhian function and its associated Legendre transformation. Throughout the paper we provide examples that illustrate various aspects of the results.
Scaling asymptotics of spectral Wigner functions*
Authors: Hanin Boris , Zelditch Steve 
Published: September 2022

Abstract
We prove that smooth Wigner–Weyl spectral sums at an energy level E exhibit Airy scaling asymptotics across the classical energy surface Σ
E
. This was proved earlier by the authors for the isotropic harmonic oscillator and the proof is extended in this article to all quantum Hamiltonians −ℏ
2Δ + V where V is a confining potential with at most quadratic growth at infinity. The main tools are the Herman–Kluk initial value parametrix for the propagator and the Chester–Friedman–Ursell normal form for complex phases with a one-dimensional cubic degeneracy. This gives a rigorous account of Airy scaling asymptotics of spectral Wigner distributions of Berry, Ozorio de Almeida and other physicists.
Orbital angular momentum in optical manipulations
Authors: Li Manman , Yan Shaohui , Zhang Yanan , Zhou Yuan , Yao Baoli 
Published: September 2022

Abstract
Since Allen et al recognized that light beams possessing a helical phase structure can carry orbital angular momentum (OAM), OAM of light has witnessed groundbreaking developments and has founded tremendous applications in a broad range of fields. In this article, beginning with a general introduction to OAM, basic theories, and computational approaches, we provide an overview on recent advances in optical manipulation with OAM. Owing to the distinct characteristics of OAM beams feature, i.e. helical wave front, doughnut intensity profile and certain OAM per photon. Optical manipulation using OAM has demonstrated innovative landscapes, realized the manipulation of particles with different functions ranging from optical spanner, manipulating of low-refractive-index particles, optical sorting and guiding, up to optical spin–orbit interaction and chiral discrimination. This review will be helpful for understanding the mechanisms behind light–matter interaction.
MXene (Ti3C2T
x
) modified α-Co(OH)2 battery-type cathode and highly capacitive binder-free Ti3C2T
x
anode for high-performance electrochemical hybrid capacitor
Authors: Rohit R C , Jagadale Ajay D , Shinde Surendra K , Kim D-Y 
Published: September 2022

Abstract
The layered nanostructure of cobalt hydroxide has received great attention in the field of the electrochemical hybrid capacitor (EHC). However, the poor electrical conductivity and cyclic stability hinder its practical applicability. Surface modification of electrodes is considered one of the effective strategies to improve these properties. In this work, the surface of α-Co(OH)2 is modified via Ti3C2T
x
MXene using a simple drop-casting method with different mass loadings and corresponding electrochemical performance is evaluated. The α-Co(OH)2 surface modified with 0.05 mg cm−2 Ti3C2T
x
MXene (CM0.05) shows the maximum specific capacity of 403 C g−1 at the current density of 3 A g−1. The aqueous EHC fabricated with CM0.05 as a positive electrode and two-dimensional (2D) Ti3C2T
x
MXene nanosheets as a negative electrode outperforms the EHC fabricated with the activated carbon as a negative electrode. The CM0.05//MXene EHC shows the maximum energy density of 44.5 Wh kg−1 at the power density of 2762 W kg−1. This also shows appreciable stability of 72% even after 5000 cycles. The flexible EHC fabricated using polyvinyl alcohol: KOH gel electrolyte demonstrates a superior energy density of 1.17 mWh cm−2 at the power density of 11.9 mW cm−2 with a wide operating potential of 1.6 V. Therefore, MXene (Ti3C2T
x
) modified α-Co(OH)2 can be considered as a promising electrode material for flexible EHCs.
How We Look At Mature Faces—An Eye-Tracking Investigation Into the Perception of Age
Authors: Frank Konstantin , Ehrl Denis , Bernardini Francesco , Walbrun Alina , Moellhoff Nicholas , Alfertshofer Michael , Davidovic Kristina , Mardini Samir , Gotkin Robert H , Cotofana Sebastian 
Published: September 2022

Abstract

Background
It is still unclear which facial region contributes most to the perception of an aged face when evaluated by eye-tracking analyses.

Objectives
The authors sought to apply eye-tracking technology to identify whether mature faces require longer fixation durations than young faces and which facial region contributes most to the perception of a mature face.

Methods
Eye-tracking analyses were conducted in 74 volunteers (37 males, 37 females; 43 ≤ 40 years, 31 &gt; 40 years) evaluating their gaze pattern and the fixation durations for the entire face and 9 facial subregions. Frontal facial images of 16 younger (&lt;40 years) and older (&gt;40 years) gender-matched individuals were presented in a standardized setting.

Results
Independent of age or gender of the observer, a younger stimulus image was viewed shorter than an older stimulus image with 0.82 (0.63) seconds vs 1.06 (0.73) seconds with P &lt; 0.001. There was no statistically significant difference in their duration of a stable eye fixation when observers inspected a male vs a female stimulus image [0.94 (0.70) seconds vs 0.94 (0.68) seconds; P = 0.657] independent of the observer’s age or gender. The facial image that captured the most attention of the observer (rank 9) was the perioral region with 1.61 (0.73) seconds for younger observers and 1.57 (0.73) seconds for older observers.

Conclusions
It was revealed that the perioral region attracts the most attention of observers and contributes most to an aged facial appearance. Practitioners should be mindful of the importance of the perioral region when designing an aesthetic treatment plan.
AEON.py: Python library for attractor analysis in asynchronous Boolean networks
Authors: Beneš Nikola , Brim Luboš , Huvar Ondřej , Pastva Samuel , Šafránek David , Šmijáková Eva 
Published: September 2022

Abstract

Summary
AEON.py is a Python library for the analysis of the long-term behaviour in very large asynchronous Boolean networks. It provides significant computational improvements over the state-of-the-art methods for attractor detection. Furthermore, it admits the analysis of partially specified Boolean networks with uncertain update functions. It also includes techniques for identifying viable source-target control strategies and the assessment of their robustness with respect to parameter perturbations.

Availability and implementation
All relevant results are available in Supplementary Materials. The tool is accessible through https://github.com/sybila/biodivine-aeon-py.

Supplementary information
Supplementary data are available at Bioinformatics online.
ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data
Authors: Fry Joshua , Li Yangyang , Yang Rendong 
Published: September 2022

Abstract

Summary
Exitron splicing is a type of alternative splicing where coding sequences are spliced out. Recently, exitron splicing has been shown to increase proteome plasticity and play a role in cancer. Long-read RNA-seq is well suited for quantification and discovery of alternative splicing events; however, there are currently no tools available for the detection and annotation of exitrons in long-read RNA-seq data. Here, we present ScanExitronLR, an application for the characterization and quantification of exitron splicing events in long-reads. From a BAM alignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at the individual transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. In addition, ScanExitronLR optionally reports exitron annotations such as truncation or frameshift type, nonsense-mediated decay status and Pfam domain interruptions. We demonstrate that ScanExitronLR performs better on noisy long-reads than currently published exitron detection algorithms designed for short-read data.

Availability and implementation
ScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index.

Supplementary information
Supplementary data are available at Bioinformatics online.
SQuAPP—simple quantitative analysis of proteins and PTMs
Authors: Ergin Enes K , Uzozie Anuli C , Chen Siyuan , Su Ye , Lange Philipp F 
Published: September 2022

Abstract

Summary
The comprehensive analysis of the proteome and its modulation by post-translational modification (PTM) is increasingly used in biological and biomedical studies. As a result, proteomics data analysis is ever more carried out by scientists with limited expertise in this type of data. While excellent software solutions for comprehensive and rigorous analysis of quantitative proteomic data exist, most are complex and not well suited for non-proteomics scientists. Integrative analysis of multi-level proteomics data on protein and diverse PTMs, like phosphorylation or proteolytic processing, remains particularly challenging and inaccessible to most biologists. To fill this void, we developed SQuAPP, an R-Shiny web-based analysis pipeline for the quantitative analysis of proteomic data. SQuAPP uses a streamlined workflow model to guide expert and novice users through quality control, data pre-processing, statistical analysis and visualization steps. Processing the protein, peptide and PTM datasets in parallel and their quantitative integration enable rapid identification of protein-level-independent modulation of protein modifications and intuitive interpretation of dynamic dependencies between different protein modifications.

Availability and implementation
SQuAPP is available at http://squapp.langelab.org/. The source code and local setup instructions can be accessed from https://github.com/LangeLab/SQuAPP.
Efficient maximum power point tracker based on neural network and sliding-mode control for buck converters
Authors: Attia Hussain , Hossin Khaled 
Published: September 2022

Abstract
This paper presents detailed design steps of an effective control system aiming to increase the solar energy harvested via photovoltaic power-generation systems. The design of an intelligent maximum power point tracker (MPPT) supported by a robust sliding-mode (SM) controller is discussed in this study. The proposed control scheme is designed to track the MPP and provide a smooth system response by removing the overshoot in the load current during any variation in the connected load. Such a system is suitable for DC–DC buck converter applications. The study begins with modelling the buck converter for a continuous current mode operation. The reference voltage of the tracking system is produced by the proposed neural network (NN) algorithm. The proposed intelligent MPPT integrated with an SM controller is simulated in a MATLAB®/Simulink® platform. The simulation results are analysed to investigate and confirm the satisfaction level of the adopted four-serially connected PV-modules system. The system performance is evaluated at a light intensity of 500 W/m2 and an ambient temperature of 25°C. Applying only the proposed NN algorithm guarantees the MPP tracking response by delivering 100 W at a resistive load of 13 Ω, and 200 W at a load of 6.5 Ω, respectively, with 99.77% system efficiency. However, this simultaneously demonstrates a current spike of ~0.5 A when the load is varied from 50% to 100%. The integrated SM controller demonstrates a robust and smooth response, eliminating the existing current spike.
A neural stem cell paradigm of pediatric hydrocephalus
Authors: Duy Phan Q , Rakic Pasko , Alper Seth L , Robert Stephanie M , Kundishora Adam J , Butler William E , Walsh Christopher A , Sestan Nenad , Geschwind Daniel H , Jin Sheng Chih , Kahle Kristopher T 
Published: September 2022

AbstractPediatric hydrocephalus, the leading reason for brain surgery in children, is characterized by enlargement of the cerebral ventricles classically attributed to cerebrospinal fluid (CSF) overaccumulation. Neurosurgical shunting to reduce CSF volume is the default treatment that intends to reinstate normal CSF homeostasis, yet neurodevelopmental disability often persists in hydrocephalic children despite optimal surgical management. Here, we discuss recent human genetic and animal model studies that are shifting the view of pediatric hydrocephalus from an impaired fluid plumbing model to a new paradigm of dysregulated neural stem cell (NSC) fate. NSCs are neuroprogenitor cells that comprise the germinal neuroepithelium lining the prenatal brain ventricles. We propose that heterogenous defects in the development of these cells converge to disrupt cerebrocortical morphogenesis, leading to abnormal brain–CSF biomechanical interactions that facilitate passive pooling of CSF and secondary ventricular distention. A significant subset of pediatric hydrocephalus may thus in fact be due to a developmental brain malformation leading to secondary enlargement of the ventricles rather than a primary defect of CSF circulation. If hydrocephalus is indeed a neuroradiographic presentation of an inborn brain defect, it suggests the need to focus on optimizing neurodevelopment, rather than CSF diversion, as the primary treatment strategy for these children.
An Investigative Review for Pharmaceutical Analysis of Fenofibrate
Authors: Saha Moumita , Dhiman Shubham , Gupta G D , Asati Vivek 
Published: September 2022

AbstractHMG-CoA reductase inhibitors (statins), lipoprotein lipase activators (PPARα agonists) or fibrates are commonly used for controlling increased lipid levels in hyperlipidemia. Fenofibrate (FEN) belongs to the second generation prodrug fibric acid (isobutyric acid) derivative belonging to lipoprotein lipase activator class of drug. Results of clinical studies suggest that FEN can substantially reduce severe acute respiratory syndrome coronavirus 2. alpha and beta variant infection in human cell efficiently. This review article provides an in-depth examination of critical analytical methodologies used in the pharmaceutical analysis of FEN in pure forms, biological samples and pharmaceuticals. According to literature study reports several analytical techniques have been used for determination of FEN alone or in the combined dosage forms. Based on the literature, it was determined that high-performance liquid chromatography and UV/vis-spectrophotometry are the most widely used methods for FEN analysis. Sahoo et al. have developed the best HPLC method in bulk and pharmaceutical dosage form with the retention time of 19.268 min using phosphate buffer (pH 3.0): acetonitrile in the ratio of 30:70 (% v/v) as mobile phase. The information presented here may provide a solid foundation for future research on FEN in the field of drug analysis.
Low BMI and high waist-to-hip ratio are associated with mortality risk among hemodialysis patients: a multicenter prospective cohort study
Authors: Yang Yaya , Zhang Haixia , Lan Xiaolei , Qin Xianhui , Huang Yan , Wang Jieyu , Luo Pei , Wen Zhen , Li Yumin , Kong Yaozhong , Wan Qijun , Wang Qi , Huang Sheng , Liu Yan , Liu Aiqun , Liu Fanna , Yang Shenglin , Lu Yongxin , Zhao Yanhong , Chen Junzhi , Lei Zihan , He Yanhuan , Lin Zizhen , Li Youbao , Liang Min 
Published: September 2022

ABSTRACT

Background
Data are limited on the relationship between waist-to-hip ratio (WHR) and mortality risk among maintenance hemodialysis (MHD) patients. Moreover, the combined association of body mass index (BMI) and WHR with mortality remains uncertain. Therefore, we aimed to explore the individual and combined association of BMI and WHR with the all-cause and cardiovascular disease (CVD) mortality.

Methods
In this multicenter prospective cohort study, we enrolled 1034 MHD patients. The primary outcome was all-cause mortality and secondary outcome was CVD mortality. Multivariable Cox proportional hazards models were used to evaluate the individual and combined association of BMI and WHR with the risk of mortality.

Results
A nonlinear inverse relationship was found between BMI and risk of all-cause mortality (P for nonlinearity &lt;.05). Being underweight (&lt;18.5 kg/m2) was associated with higher all-cause mortality risk (HR 1.45; 95% CI 1.08–1.94) compared with normal weight (18.5–23.9 kg/m2), while being overweight (24–27.9 kg/m2; HR 0.96; 95% CI 0.70–1.31) and obese (≥28 kg/m2; HR 1.19; 95% CI 0.62–2.26) showed no significant differences. Of note, WHR was independently and positively associated with all-cause mortality (per standard deviation increase, HR 1.13; 95% CI 1.00–1.27). When analyzed jointly, patients with low BMI (&lt;18.5 kg/m2) and high WHR (≥0.95) had the highest risk of all-cause mortality. Similar results were obtained for CVD mortality.

Conclusions
In patients undergoing hemodialysis from China, low BMI and high WHR were individually and jointly associated with higher risk of mortality. Our results emphasize that BMI and WHR may jointly affect the prognosis of MHD patients.
Variation in network evolution through competitive progress via link connection/disconnection
Authors: Sakiyama Tomoko 
Published: September 2022

AbstractParameter tuning is a useful method for modelling complex phenomena and replacing one collective pattern with another pattern. However, this approach may not explain how agents in a complex system select an adequate parameter or respond flexibly to a changeable environment. Similar problems are also found in the network evolution where the emergence of characteristic network structures poses a problem. In a previous work, I developed a hawk–dove game on the network where individual players sometimes disconnected links from their partners or connected a link to a new partner in addition to the strategy update. In this game, players coordinated the link connection/disconnection rule by considering the local hierarchy; I found that the coordination of this rule presented the emergence of a scale-free network at one time but not so at another time. Hub nodes may emerge when hawk players are extinct. In this work, I investigated the relationship between the link evolution and the evolution of hub nodes that will be linked to the network structure and found that the network structure could evolve differently according to the competitive progress of the link connection/disconnection.