bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Model Predictive Control for Steady-state Drifting and Tracking of Electronic-Two-Rear-Wheel Drive Automobiles
Authors: He Lei , Wang Yixiao , Gao Zhenhai , Chen Guoying 
Published: July 2022

Abstract
Drifting enables the vehicle to quickly adjust its posture and velocity, with the potential to enhance vehicle safety and maneuverability in extreme operating conditions. To improve the handling stability and tracking accuracy of drift control, a controller framework is presented based on model predictive control theory for electronic-two-rear-wheel drive (e-2RWD) automobiles. Primarily, the non-linear bicycle dynamics model is constructed, and in which the motion relationship between the vehicle and the specified trajectory is revealed.Then, a set of reference states are solved for the specified trajectory and desired sideslip. Finally, the MPC drift controller is used to work in conjunction with the wheel speed closed-loop controller to provide coordinated control of the steering angle and both rear wheel drive torques. The performance of the proposed drift controller is assessed in software simulations in two high sideslip driving scenarios with different trajectories. The simulation results show that the proposed controller is able to rapidly enter the steady-state drifting and effectively reduce the fluctuations of vehicle states, striking a reasonable balance between satisficing the accuracy demands and keeping vehicle handling stability. The major contribution of this paper is the first application of the MPC and wheel speed controller combined operation mode to drift control. Due to the advantage of proposed method predicting the vehicle's future dynamic behavior in advance, the controller outputs can be effectively constrained and optimized.
Bioprospecting of endophytic actinobacterium associated with Aloe ferox Mill for antimicrobial activity
Authors: Maliehe Tsolanku Sidney , Mbambo Melusi , Ngidi Londeka Sibusisiwe , Shandu Jabulani Siyabonga Emmanuel , Pooe Ofentse Jacob , Selepe Tlou Nelson 
Published: July 2022

Abstract
Background: The emergence of drug resistance among pathogens has resulted in renewed interest in bioprospecting for natural microbial products. Methods: This study aimed to bioprospecting endophytic actinobacterium associated with Aloe ferox Mill for its antibacterial activity. Endophytic actinomycetes were isolated from the gel of A. ferox Mill by surface sterilization technique using actinomycete isolation agar. The isolate with a promising antibacterial activity was identified using 16S rRNA sequence analysis. The minimum inhibitory concentration (MIC) of the extract was assessed by the micro-dilution method and its effect on the respiratory chain dehydrogenase (RCD) activity was ascertained by the iodonitrotetrazolium chloride (INT) assay. Fourier transform-infrared spectrophotometer (FTIR) and gas chromatography-mass spectrophotometry (GC-MS) were employed to identify functional groups and the chemical constituents, respectively. Results: The actinobacterium was found to be Streptomyces olivaceus CP016795.1. Its extract displayed noteworthy antibacterial activity (MIC ≤ 1 mg/mL) against Staphylococcus aureus (ATCC 25925), Bacillus cereus (ATCC 10102), and Escherichia coli (ATCC 25922); and showed an inhibitory effect on the RCD activity. FTIR spectrum displayed hydroxyl, amine, and aromatic groups, and the GC–MS revealed 5-Hydroxymethylfurfural as the main constituent (19.47%). Conclusions: S. olivaceus CP016795.1 can serve as a potential source of effective antibacterial compounds.
Daytime Nap and Depression Risk: a meta-analysis of observational studies
Authors: Li Liqing , Zhang Qi , Zhu Liyong , Zeng Guohua , Huang Hongwei , Zhuge Jian , Kuang Xiaorui , Yang Sule , Yang Di , Chen Zhensheng , Gan Yong , Lu Zuxun , Wu Chunmei 
Published: July 2022

Abstract
Background: Relationship between daytime napping and the risk of depression remains debatable. Thus, a meta-analysis in this study was conducted to evaluate the relationship between daytime napping and the depression risk.Methods: PubMed, Embase, Web of Science and China National Knowledge Infrastructure databases were searched through up to February 2022, and the reference lists of the included studies were also retrieved. A random-effects model was used to estimate the combined effect size.Results: Nine studies with 649,111 participants were included in the final analysis. The pooled odd ratio (OR) was 1.15 (95% confidence interval: 1.01-1.31) with a significant heterogeneity (I2=91.3%, P for heterogeneity < 0.001), and the results demonstrated an increasing risk of depression were observed among daytime nappers. Visual inspection of funnel plot, Egger’s and Begg’s tests identified no obvious evidence of publication bias.Conclusion: This meta-analysis indicates that daytime nap plays a predictor for depressive symptom. These findings might obtain important implications for depression prevention.
Programmable Microfluidics for Dynamic Multiband Camouflage
Authors: Liu Kang , Liu Huidong , Feng Chunzao , Mao Mingran , Zhang Xiaohui , Liao Yutian , Xiao Xiaohui 
Published: July 2022

Abstract
Multiband optic manipulation covering both visible and infrared region is challenging due to the wide involved wavelengths and differentiated regulation demand in diverse regions. In this work, we propose a programmable microfluidic strategy, which use dye molecules in layered fluids to manipulate visible light and infrared semi-transparent solvent to manipulate infrared lights. With three primary fluids input, we achieve 64 chromaticity values and 8 emissivities from 0.42 to 0.90. In view of the wide tuning range, we demonstrate the microfluidic film can dynamically change its surface reflectance to blend into varying backgrounds both in visible and infrared images. Moreover, we fabricate the microfluidic device in a textile form and demonstrate its ability in matching exactly with natural leaves of different seasons in full hyper-spectrum. Considering the broadband modulation and ease of operation, the programmable microfluidic strategy provides a feasible approach for smart optical surfaces in long span optical spectrum.
A simple parasitological technique to increase detection of Strongyloides stercoralis in Bolivian primary health care system
Authors: Camacho-Alvarez Ivana , Chavez-Mamani Elia M. , Goyens Philippe , Luizaga-López Jenny Marcela , Torrico Mary Cruz , Gétaz Laurent , Jacobs Fredériqué 
Published: July 2022

Abstract
Background: Strongyloides stercoralis is widespread; however, there is limited information on its prevalence owing to laboratory underestimation and low clinical manifestations. The Baermann method and agar culture stand out among the parasitological techniques. Strongyloides stercoralis is present in Bolivia, but its prevalence in children remains unknown. The objective of this study was to estimate the applicability of simple parasitological techniques to increase the detection of this parasite in children living in the tropics. Methods: This cross-sectional study was conducted in a tropical village in Cochabamba, Bolivia. Participants were 304 children aged 5 – 12 years who provided stool samples for different parasitological analyses (direct examination, Ritchie, Barman, and Dancescu techniques), and their parents provided informed consent. Results: Up to 64.8% of pathogenic parasites were detected using the modified Ritchie method. The Baermann technique identified 17.8% of Strongyloides stercoralis cases, and a high sensitivity with respect to the Baermann technique was only for the Dancescu technique (75.9%) that is also specific for Strongyloides stercoralis, followed by 66.7% for the modified Ritchie technique, which is used in second-line care. Discussion: The Baermann technique is the best parasitological option for improving Strongyloides stercoralis diagnosis in the first-line care of the Primary Health Care System. A particular cycle of reinfection, combined with the environment and some other risk factors are related with persistence. Control is difficult without a proper diagnosis, and the Baermann technique is an approach to the solution. We conclude that with a high suspicion of the presence of Strongyloides stercoralis, the use of the Baermann technique is strongly recommended as support for direct examination in primary health care systems especially in tropical areas.
Content-Based Image Retrieval Using Multilevel Robust Mechanism
Authors: R Isaac Sajan , V Bibin Christopher , S Akhila T , M Joselin Kavitha 
Published: July 2022

Abstract
Content-Based Image Retrieval only concentrates on the information about the image like its texture, color, shape, homogeneity, and contrast rather than the image tags, description, and keywords. Traditionally many machine learning algorithms are used to retrieve the information but fail to acquire accuracy and created overfitting problems. Not only that large image database handling becomes quite hard to achieve quicker results without human intervention. Hence, we are opting for a robust mechanism for every step of retrieval. Image pre-processing inhibited AlexNet architecture with latent feature extraction and feature selection wear out Mutual Information neural estimation, which is used to handle high dimensional images with fixed resolution and removes the redundancy of images in the database. The similarity measure using Euclidean distance is employed to retrieve the images. The accuracy and performance efficiency is considerably high and pertinent.
Sabbaticals in U.S. Medical Schools
Authors: Robiner William N , Buum Heather Thompson , Eckerstorfer Margaret , Kim Michael H , Kirsch Jonathan D 
Published: July 2022

Abstract
Background: Sabbaticals are an important feature of academia for faculty and their institutions. Whereas sabbaticals are common in institutions of higher learning, little is known about their role and utilization in U.S. medical schools. This study examining sabbaticals in medical school faculty was undertaken at a time that wellbeing of health professionals was increasingly recognized as workforce and health reform priorities. Methods: We surveyed associate deans at U.S. medical schools in 2021 about faculty who had taken sabbaticals within the past three years, the parameters of the sabbaticals, as well as institutional policies and respondents' predictions of future sabbatical use. Results: 53% of respondents reported any faculty had taken sabbaticals in the past three years ( M = 6.27; Median = 3; range = 1-60). Institutions rated enhancing research as the most important objective, while recognizing other benefits. Sabbaticals were more commonly taken by male, White, senior faculty Ph.Ds. Details about sabbaticals, including eligibility, expectations, length, financial support, and benefits were reviewed. Most (54.8%) respondents expected no change in the number of faculty seeking sabbaticals. Nearly all anticipated the COVID-19 pandemic would not affect sabbatical policies. Conclusion: In contrast to other institutions of higher learning, sabbatical-taking by medical school faculty is rare. We explore factors that may contribute to this phenomenon, e.g., the tripartite mission, faculty clinical responsibilities, culture of medicine, and student debt. Despite financial and other barriers, a closer look at the benefits of sabbaticals is warranted as a mechanism that may support faculty well-being, retention, and mental health.
A new evolutionary ensemble learning of multimodal feature selection from microarray data
Authors: Nekouie Nadia , Romoozi Morteza , Esmaeili Mahdi 
Published: July 2022

Abstract

In the last decades, data has grown exponentially with respect to the number of samples and features, which makes feature selection more challenging. An optimization method called multimodal optimization techniques is employed to find several optimal solutions. The main contribution of multimodal optimization techniques is providing several optimal solutions instead of a single solution. Since multimodal optimization algorithm naturally provides several answers, in this paper the potential and information of several answers are used to address the issues of selecting features from microarray data, using hidden information in the data, and creating an ensemble of classifiers. After pre-processing of data, several optimal feature subsets are obtained by firefly-based multimodal optimization algorithm to tap the potential of and information in several answers. The mutual information method is used as the fitness function to evaluate the suggested subset of features. Then, each subset of features is used to learn a classifier and such classifiers are learned on data whose features are presented by a multimodal optimization algorithm, and these classifiers are combined. To select a proper combination, a particle swarm optimization algorithm is used. Finally, the algorithm for the datasets of the microarray is evaluated in terms of cancer diagnosis. The algorithmic method efficiency is evaluated by applying it on 11 datasets. The results suggested the superiority and proper function of the multimodal feature selection method compared with other methods.
Factor Structure and Longitudinal Measurement Invariance of the K6 among a national representative elder sample of China
Authors: Zhang Lisong , Li Zhongquan 
Published: July 2022

Abstract
BackgroundAs the number of older people is rapidly growing, prevention, screening, and treatment of mental health problems (including anxiety and depression) in this population increasingly become a heavy burden to individuals, families, and even the whole society. The Kessler-6 screening measure (K6) is an efficient and effective instrument for general mental health problems. However, few studies have examined its measurement invariance across time, which is particularly important in longitudinal studies, such as exploring developmental trajectories of non-specific psychological distress and evaluating the effects of certain interventions.MethodsThe current study investigated the factor structure and the longitudinal measurement invariance of the K6 among a national representative elder sample of China. Longitudinal data in two survey waves (the year 2010, the year 2014) from the China Family Panel Studies were drawn for secondary data analysis. A total of 3845 participants aged 60 years old and above (52.2% male, mean age = 66.99 years, SD = 5.93 years) responded to both waves of the survey. ResultsA comparison of four existing models with confirmatory factor analysis supported a two-factor solution of the K6. A series of multi-group confirmatory factor analyses further indicated that the K6 held strict longitudinal measurement invariance across time. Additionally, the internal consistency indices across time and the stability coefficients over time were acceptable.ConclusionsThe findings further confirmed the psychometric defensibility of the K6 when used in the old Chinese population. The longitudinal measurement invariance justified comparisons of psychological distress scores among different measurement time points.
Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods
Authors: Ye Ling-Fang , Wu Li-Da 
Published: July 2022

Abstract
Aim
As the most common cardiomyopathy, dilated cardiomyopathy (DCM) often leads to progressive heart failure and sudden cardiac death. This study was designed to investigate the molecular subgroups of DCM.
Methods
Three datasets of DCM were downloaded from GEO database (GSE17800, GSE79962 and GSE3585). After log2-transformation and background correction with “limma” package in R software, the three datasets were merged into a metadata cohort. The consensus clustering was conducted by the “Consensus Cluster Plus” package to uncover the molecular subgroups of DCM. Moreover, clinical characteristics of different molecular subgroups were compared in detail. We also adopted Weighted gene co-expression network analysis (WGCNA) analysis based on subgroup-specific signatures of gene expression profiles to further explore the specific gene modules of each molecular subgroup and its biological function. Two machine learning methods of LASSO regression algorithm and SVM-RFE algorithm was used to screen out the genetic biomarkers, of which the discriminative ability of molecular subgroups was evaluated by receiver operating characteristic (ROC) curve.
Results
Based on the gene expression profiles, heart tissue samples from patients with DCM were clustered into three molecular subgroups. No statistical difference was found in age, body mass index (BMI) and left ventricular internal diameter at end-diastole (LVIDD) among three molecular subgroups. However, the results of left ventricular ejection fraction (LVEF) statistics showed that patients from subgroup 2 had a worse condition than the other group. We found that some of the gene modules (pink, black and grey) in WGCNA analysis were significantly related to cardiac function, and each molecular subgroup had its specific gene modules functions in modulating occurrence and progression of DCM. LASSO regression algorithm and SVM-RFE algorithm was used to further screen out genetic biomarkers of molecular subgroup 2, including TCEAL4, ISG15, RWDD1, ALG5, MRPL20, JTB and LITAF. The results of ROC curves showed that all of the genetic biomarkers had favorable discriminative effectiveness.
Conclusions
Patients from different molecular subgroups have their unique gene expression patterns and different clinical characteristics. More personalized treatment under the guidance of gene expression patterns should be realized.
In-silico molecular screening of the constituents of sea buckthorn identifies potential inhibitors of coronary artery disease targets
Authors: M Sudhan , V Janakiraman 
Published: July 2022

Abstract
Background Based on network pharmacology we forecast the targets and signal pathways of Sea buckthorns (SB) in the treatment of coronary artery disease (CAD).MethodsSB active components and possible targets were taken from the ChEMBL and SWISS-Prot prediction database. CAD-related targets were collected from the Genome-Wide Association Study database (GWAS). The STRING analysis was used to identify the " SB -active ingredient-target" network utilizing the common targets. Then, using a string database, we built and examined protein-to-protein interactions (PPI). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed. Further, we performed molecular docking analysis to identify the binding interaction of key targets and the SB active components. ResultsWe found 10 active SB components and 3 potential CAD targets. That Campesterol is the most active compound according to molecular docking results. Our GO enrichment study revealed 42 biological processes and 42 GO items. The apoptosis, focal adhesion, and T cell receptor signaling pathways were among the 33 KEGG signaling pathways found. SB might have a role in CAD therapy by modulating distinct signaling pathways, according to our findings. The target-compound correlation was validated by the molecular docking experiment.ConclusionsWe identified SB active compound campesterol can be used for the treatment of CAD. Further, experimental and clinical study needed to confirm the efficacy of the active compound.
GW4869 can inhibit epithelial-mesenchymal transition promoted by extracellular HSP90α in EGFR-mutated NSCLC cells
Authors: Wan Xuan , Du Jiangzhou , Fang Yuting , Huang Danhui , Dong Hangming , Cai Shaoxi 
Published: July 2022

Abstract
Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer with the high morbidity and mortality in the world. Meanwhile, the acquired drug resistance against EGFR-mutated NSCLC is increasingly serious. HSP90α might play critical roles in NSCLC, but the effect of GW4869 on extracellular HSP90α remains unclear. We collected plasma samples from 22 NSCLC and 10 healthy individuals, and measured the plasma HSP90α levels by ELISA. Western blot was used to detect the levels of HSP90α, E-cadherin, N-cadherin, and Vimentin in HCC827 and PC9 cells. We found that extracellular HSP90α was upregulated in NSCLC mutated patients and accelerated epithelial-mesenchymal transition (EMT) and invasion/migration capacity in EGFR-mutated NSCLC cells. Meanwhile, we also confirmed that GW4869 inhibited the expression of eHSP90α, EMT and invasion/migration abilities in HCC827 and PC9, and enhanced the antitumor activity of gefitinib in BALB/C nude mice in vivo. These studies suggest that GW4869 can inhibit epithelial-mesenchymal transition promoted by extracellular HSP90α in non-small cell lung cancer, which provides new strategies for delaying the development of acquired resistance to gefitinib for EGFR-mutated NSCLC.
Large Eddy Simulation of Flow Field in Thermal Vapor Compressor
Authors: Ren Xiaotong , Guo Yali , Shen Shengqiang , Zhang Kun 
Published: July 2022

Abstract
In the low-temperature multi-effect evaporation (LT-MEE) desalination plant, improving the performance of thermal vapor compressor (TVC) could reduce the energy loss, increase the gained output ratio (GOR) and consequently improve the system economy efficiency. Implementing large eddy simulation (LES) as the numerical method, a 3-D computational fluid dynamics model of TVC is established to simulate the flow field under various conditions. The effects of motive steam pressure on the flow field, vortex core, turbulent viscosity and vortex iso-surface of the TVC are discussed, and the corresponding interior flow field distribution is obtained as well. Q criterion and normailzed Q criterion are applied to visualize the vortex cores and vortex iso-surfaces. The distributions of vortexes in different scales are displayed, large-scale vortexes are mainly distributed in exit area of the nozzle, the constant section of the mixing chamber and the diffuser. Additionally, the large-scale vortexes are primarily located along the axis in different morphology while the small-scale ones are randomly distributed near the wall.
A hybrid real-time radiation monitoring system by utilizing RPL glass for proton beam profile measurement
Authors: Cho Jaeyoung , Jegal Jin , Jeong Dongwoo , Kang Sinchul , Bang Inha , Aryal Pabitra , Kim Hongjoo , Park HyeoungWoo 
Published: July 2022

Abstract
A precise measurement of radiation energy corresponding to position is important in radiation monitoring as well as proton therapy technique utilizing a particle accelerator. Proton Bragg peak makes it possible to modulate dose distribution in target by charged particle energy loss. We develop and test a real-time system using radio-photoluminescence (RPL) glass for accelerator particle beam tuning. The RPL glass has promising characteristics, such as a linear dosimeter equivalent to ionizing irradiation, no fading, data accumulation, and repeatability through thermal treatment. Utilizing this system, the energy deposit of the proton beam irradiated RPL glass is measured under an ultraviolet (UV) excitation source in real-time. 45 MeV and 100 MeV proton beams are generated from a cyclotron and a linear accelerator respectively. The proton Bragg curve corresponding to the proton energy and RPL is verified by GEANT4 simulation. This system promises to provide useful information on beam tuning techniques and quality verification through real-time radiation monitoring and recordings of the accumulated dose on repeatable RPL glass.