bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Survey of Israeli Physical Therapists Regarding Perturbation-Based Balance Training
Authors: Margalit Noam , Kurz Ilan , Wacht Oren , Mansfield Avril , Melzer Itshak 
Published: October 2022

Abstract
Background: ‘Perturbation-based balance training’ was developed to improve balance reactions to unexpected losses of balance. Although this training method is effective, its practical usage in the field of physical-therapy in Israel and world-wide is still unclear.
Aims: This study aimed to evaluate the extent of perturbation-based balance training use in physical-therapy clinics in Israel, to identify the significant barriers to/facilitators for implementing perturbation-based balance training in clinical practice among physical therapists, and to determine which aspects of perturbation-based balance training most interest physical therapists in Israel.
Methods: Physical therapists in Israel completed a survey using a questionnaire regarding their knowledge and use of perturbation-based balance training in their clinical practices. We compared the specific use of perturbation-based balance training among users; non-users; and open-to-use physical therapists. The odds ratios of the facilitators and barriers were calculated using univariate and multivariate logistic regression models.
Results: Four-hundred and two physical therapists responded to a yes/no question regarding their use of perturbation-based balance training. Three-quarters (75.4%) of physical therapists reported using perturbation-based balance training in their practices. The most prevalent barrier cited was insufficient space for setting up equipment and most prevalent facilitator was having a colleague who uses perturbation-based balance training. Most of the respondents wanted to learn more about perturbation-based balance training, and most of the non-users wanted to expand their knowledge and mastery of perturbation-based balance training principles.
Conclusions: There are misconceptions and insufficient knowledge about perturbation-based balance training among physical therapists in Israel. Reliable information may help to improve general knowledge regarding perturbation-based balance training, and to facilitate the more widespread implementation of perturbation-based balance training as an effective fall-prevention intervention method.
Loneliness and trust issues reshape mental stress of expatriates during early COVID-19: a structural equation modelling approach
Authors: Billah Md Arif , Akhter Sharmin , Khan Md. Nuruzzaman 
Published: October 2022

Abstract
Objectives: To explore the relationship of perceived stress (PSS) regarding loneliness (PLS) interpersonal (IPT) and institutional trust (IT) among the expatriates during the early COVID-19 period.
Methods: Using the COVIDiSTRESS global survey data for 21,439 expatriates, this study applied pairwise correlation, structural equation modelling (SEM) and hierarchical linear regression analysis (HLRA). Descriptive statistics were provided for the sample representation.
Results: Expatriates were mostly female (73.85%), married (60.20%), highly educated (47.76%), and employed (48.72%). Over 63% of them reported that the COVID-19 changed their life. Age, PSS, PLS, IPT and IT were moderately interrelated to each other at p<0.001. SEM evaluated that lack of trust enhances the loneliness of expatriates and loneliness increases the perceived stress. Trust in a person was more likely found to be associated with the stress whereas loneliness mediated trusts and perceived stress. HLRA was found an insignificant contributor of institutional trusts.
Conclusion: PSS can be reduced through trusting others and elucidating the loneliness where the loneliness can be reduced through trusting others. This chain of psychosocial facts can be established over in the society for migrants and expatriates for mental wellbeing.
ITransformer_CNN: A Malicious DNS Detection Method with Flexible Feature Extraction
Authors: Zhang Wenyue , Chen Wei , Zhang Zhen , Zhang Fan , Wu Lifa 
Published: October 2022

Abstract
Attackers can use the domain name system (DNS), a crucial service of the network, to carry out harmful activity. The task of detecting malicious domain names has grown in importance in the fight against network crime. The increasing complexity of DNS attack requires new detection methods to deal with new threats. With machine learning and deep learning approaches, malicious DNS detection methods have made considerable strides in recent years. However there are still certain difficulties, such as inflexible feature extraction. To solve this problem, the combination model presented in this paper is based on an enhanced Transformer and a convolutional neural network (CNN). The encoder portion of the Transformer is used to extract domain name features once the network packet has been parsed. Using a multi-head attention mechanism, we pay particular attention to the sequence relationship between the domain name characters. The position relations and word vectors are directly inserted into the word embedding layer using one-hot encoding. They are forwarded to the CNN model for flow-based feature extraction after other traffic information has been analyzed. The features that were extracted by CNN and Transformer are combined into a feature matrix before being categorized, which increases the adaptability of feature extraction. The results of the experiments show that the proposed method is capable of accurately identifying different categories of malicious DNS with various features.
DFT study of regio- and stereo-selective 13DC reaction between diazopropane and substituted chalcone derivatives: Molecular docking of novel pyrazole derivatives as Anti-Alzheimer’s Agents
Authors: Zouaghi Mohamed Oussama , Omrani Rania , Arfaoui Youssef , Koko Waleed , Al-Hazmy Sadeq M. , Mansour Lamjed , Al-Tamimi Jameel , bouazizi younes , hamdi naceur 
Published: October 2022

Abstract
We report a mechanistic DFT study of 1,3-dipolar cycloaddition of diazopropane with substituted chalcones. All calculations were carried out at DFT/B3LYP, M06, and M06-2X with 6-311 + G(d,p) basis set using Gaussian program 09. Based on the IRC calculations, we have shown the stability of the pyrazoles over the oxadiazoles. Also, as a novelty, we have found that the use of two DAP equivalents leads to the obtaining of two thermodynamic products. Docking simulations were performed in order to investigate the biological activities of the studied molecules. We have found that products 1, 3, 4 and 14 were bound mainly to the CAS and PAS of AChE and BuChE inhibitors, respectively.
WITHDRAWN: Analyzing governing equations of multibody dynamic systems through kinematic properties of joints and effects of kinematic chains on closed-form mechanism
Authors: Mohammadi Yousef , Fatouraee Nasser , Bostanshirin Mehdi 
Published: October 2022

Abstract

In this study, the governing equations of dynamic systems were derived using a novel method that integrated the kinematic properties of joints and the complex kinematic chains of multibody systems into a set of governing equations. The governing equations of multibody systems were then transformed into ODE using the calculus of matrix-valued functions. This algorithm can efficiently obtain recursive differential equations of motion for multibody systems. Consequently, the computational cost of the simulation was reduced successfully. Andrew’s squeezing and carpet scraping mechanisms were utilized with kinematic constraints to validate the proposed method. Results indicated that the proposed method was 4.2 and 5.4 times faster than the other methods based on algebraic differential equations in Andrew’s squeezing and carpet scraping mechanism, respectively.
Thermal spread with Voyant 5 mm Fusion versus LigaSure 5 mm Blunt Tip Devices
Authors: Carmack Austin , Satchell Emma K. , Patel Apar S. , Bashiri Amir , Cagir Burt , Rizzo Anne 
Published: October 2022

Abstract
Thermal spread is an unavoidable side-effect of electrocautery, however limiting it is important for minimizing damage to surrounding tissues. LigaSure 5 mm Blunt Tip has been in use since 2009 while Voyant 5 mm Fusion has only been FDA approved since 2018. Our hospital, a rural academic tertiary care center, recently moved to purchasing Voyant because of cost concerns. We aimed to compare the thermal spread of the two tools on raw pork meat at two different cut depths and on both right and left sides. The LigaSure device had significantly less thermal spread than Voyant across all measurements. Based on our data, the LigaSure device should be chosen for use despite the increased cost.
Low immunoglobulin levels affect the course of COPD in hospitalized patients
Authors: Palikhe Nami Shrestha , Niven Malcena , Fuhr Desi , Sinnatamby Tristan , Rowe Brian H , Bhutani Mohit , Stickland Michael , Vliagoftis Harissios 
Published: October 2022

Abstract
Background
Chronic obstructive pulmonary disease (COPD) affects up to 10% of Canadians. Patients with COPD, as a result of chronic disease, poor nutrition, or frequent courses of oral corticosteroids, may present with secondary humoral immunodeficiency that might predispose them to mucosal infections. We hypothesized that decreased serum immunoglobulin (Ig) levels was associated with the severity of an acute COPD exacerbations (AECOPD).
Methods
A prospective study to examine inflammation and cardiovascular risk in patients hospitalized for COPD recruited patients on hospital admission and collected data on length of hospital stay at index admission, subsequent emergency department visits and hospital readmissions. Immunoglobulin levels were measured in serum collected prospectively at recruitment.
Results
Among the 51 patients recruited an admission for an AECOPD, 14 (27%) had low IgG, 1 (2.0%) low IgA and 16 (31.4%) low IgM; in total, 51% had at least one immunoglobulin below the normal range. Patients with low IgM had longer hospital stay during the index admission compared to patients with normal IgM levels (6.0 vs. 3.0 days, p = 0.003), but no difference in other clinical outcomes. In the whole cohort, there was a negative correlation between serum IgM levels and length of hospital stay (R= -0.317, p=0.024). There was no difference in clinical outcomes between subjects with normal and low IgG levels.
Conclusion
In patients presenting with AECOPD, low IgM is associated with longer hospital stay and may indicate a patient phenotype that would benefit from efforts to prevent respiratory infections.
Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet
Authors: Jia Peng , Dong Lianhua , Yang Xiaofei , Wang Bo , Wang Tingjie , Lin Jiadong , Wang Songbo , Zhao Xixi , Xu Tun , Che Yizhuo , Dang Ningxin , Ren Luyao , Zhang Yujing , Wang Xia , Liang Fan , Wang Yang , Ruan Jue , Zheng Yuanting , Shi Leming , Wang Jing , Ye Kai 
Published: October 2022

Abstract
As the state-of-the-art sequencing technologies and computational methods enable investigation of challenging regions in the human genome, an update variant benchmark is demanded. Herein, we sequenced a Chinese Quartet, consisting of two monozygotic twin daughters and their biological parents, with multiple advanced sequencing platforms, including Illumina, BGI, PacBio, and Oxford Nanopore Technology. We phased the long reads of the monozygotic twin daughters into paternal and maternal haplotypes using the parent-child genetic map. For each haplotype, we utilized advanced long reads to generate haplotype-resolved assemblies (HRAs) with high accuracy, completeness, and continuity. Based on the ingenious quartet samples, novel computational methods, high-quality sequencing reads, and HRAs, we established a comprehensive variant benchmark, including 3,883,283 SNVs, 859,256 Indels, 9,678 large deletions, 15,324 large insertions, 40 inversions, and 31 complex structural variants shared between the monozygotic twin daughters. In particular, the preciously excluded regions, such as repeat regions and the human leukocyte antigen (HLA) region, were systematically examined. Finally, we illustrated how the sequencing depth correlated with the de novo assembly and variant detection, from which we learned that 30 × HiFi is a balance between performance and cost. In summary, this study provides high-quality haplotype-resolved assemblies and a variant benchmark for two Chinese monozygotic twin samples. The benchmark expanded the regions of the previous report and adapted to the evolving sequencing technologies and computational methods.
Efficiency Evaluation and Spatial Differences of Infrastructure Investment: Analysis by SBM-Undesirable and Spatial Auto-correlation
Authors: Zhang Qin , Yue Guanglong , Yu Xinping , He Chongyu , Bao Yinzi , Zhang Lening , Ni Taohan 
Published: October 2022

Abstract
Taking ecological benefits outputs into composition of index system, the efficiency of infrastructure investment is evaluated by SBM-Undesirable model, and spatial differences are processed by ArcGIS and Geoda model, based on data from 31 provinces in China. The conclusions are conducted as follows. Firstly, infrastructure investment efficiency in China is generally at a low level, and there are large differences among regions, in which the eastern shows the highest infrastructure investment efficiency, followed by the central region, and then the western region. Secondly, a significant positive spatial autocorrelation of infrastructure investment efficiency shows in each region, after the analysis taking the global Moran's I index. Thirdly, high spatial stability for infrastructure investment efficiency in most regions in China, taking the methodology of the LISA agglomeration plot and significance level plot. Then the suggestions are proposed including expanding input of infrastructure investment, highlighting cooperation among regions and promoting technology innovation in enterprises, to increase the efficiency of infrastructure investment.
Adaptive trio-ensemble deep neural network for high-frequency stock price prediction
Authors: Srivas Lokesh Kumar , KUMAR RAVINDER 
Published: October 2022

Abstract
The analysis and forecasting of stock price is a highly complex task since its inception. Researchers have proposed a hundreds of mathematical and machine learning based models to solve this high frequency prediction problem. The constraints that restricts the effective stock market forecasting method is its dependency on variety of factors like news, announcement of dividends, company policy, drastic changes at management level, launch of new products etc. The characteristics of Deep learning algorithms like choice of network structure, activation function, and other model parameters etc voted it as a best choice for prediction. This paper proposed an ensemble prediction model by exploiting three most promising variant of Deep Neural Network (DNN) namely Gaussian, Poisson, and Gamma out of six available probability distributions (Quantile, Gaussian, Poisson, Laplace, Huber, and Gamma). The experimental results show that the proposed ensemble deep learning model claimed the best accuracy of R2: 0.92 and Root Mean Square Error (RMSE): 0.17 as per the literature reviewed in this category.
Full life-cycle cutting force prediction in ball helical milling based on oblique cutting analysis
Authors: Zhou Zhitong , Wang Haiyan 
Published: October 2022

Abstract
In order to predict the change of cutting force in ball helical milling of titanium alloy, considering the kinematics of helical milling and the geometric model of ball end cutter, the cutting process is divided into three stages, cutting-in, steady and cutting-out stages, and the shape and volume of undeformed chip in different stages are described. Then according to the oblique cutting theory and the principle of maximum shear stress, the constraint relationships among the parameters such as friction angle, shear angle and shear stress in the micro-element are established. Thus based on the position parameters at different stages, a three-direction full life-cycle cutting force model is established, the cutting force coefficients are identified and expressed as Weibull functions of instantaneous undeformed chip thickness. Finally, the predicted cutting forces are compared with the experimental values. The results show that the maximum average error is less than 18%, which verify the accuracy of the model.
Coral reef structural complexity loss exposes coastlines to waves
Authors: Carlot Jérémy , Vousdoukas Michalis , Rovere Alessio , Karambas Theofanis , Lenihan Hunter S. , Kayal Mohsen , Adjeroud Mehdi , Pérez-Rosales Gonzalo , Hedouin Laetitia , Parravicini Valeriano 
Published: October 2022

Abstract
Coral reefs offer natural coastal protection by attenuating incoming waves. Here we combine unique coral disturbance-recovery observations with hydrodynamic models to quantify how structural complexity dissipates incoming wave energy. We find that if the structural complexity of healthy coral reefs conditions is halved, extreme wave run-up heights that occur once in a 100-years will become 50 times more frequent, threatening reef-backed coastal communities with increased waves, erosion, and flooding.
Optimal Design of Photovoltaic/Wind Turbine Systems for Producing Hydrogen Using a PEM Electrolyzer and MPPT Controller
Authors: Elbarbary Z. M. Salem , Awad Mohamed , Omar Ahmed I. 
Published: October 2022

Abstract
The current trend is to use renewable energy such as solar energy and wind energy to produce hydrogen. It is necessary for us to make a comparison of the effect of each of these sources on hydrogen production, and which one is more efficient in different environmental variables. This paper studied and modeled two sources of renewable energy which are Photovoltaic (PV) and Wind Turbine (WT) to power Polymer Electrolyte Membrane Electrolyzer (PEMEL). By using MATLAB software, it is measured the input, and output power of PV and WT, the efficiency of the MPPT controller, and calculated the green hydrogen production rate and efficiency of each system separately. It is analyzed under variable irradiance from 600 to 1000 W/m2 for a PV system and fixed temperature equal to 25°C. While under variable wind speed from 10 to 14 m/s and zero fixed pitch angle for WT system. The results obtained that, the optimal power of WT to feed PEMEL is to be approximately two times PEMEL powered. Also, PV system is designed to be equal to PEMEL power. This study will be a reference for designing PV or WT to feed an electrolyzer.
Techniques predatory journals use to solicit manuscripts: a contrast between Africa (lower- income countries) and Canada (high income country)
Authors: Rafiq Rumana , Ashaba Scholastic , Wechuli Geoffrey , Bortolussi Robert , MacDonald Noni E 
Published: October 2022

Abstract
Background
Predatory journals charge authors for publication without quality peer review or editorial services. They target researchers not only in high-(HIC) but also in lower income countries (LIC). The purpose of this study was to investigate characteristics of predatory journals and their recruitment techniques aimed at researchers in LIC and HIC.
Methods
Four clinician researchers, two in lower income countries (Kenya and Uganda) and two in a high-income country (Canada), identified and collected unsolicited emails from suspected predatory journals over a six-month period in 2019; 50 randomly selected emails from researchers in Canada and 50 from African researchers. These were assessed for similarities and differences using a set of criteria derived from the literature on predatory publishing.
Findings:
Features common to both the LIC and HIC groups included requesting email not website manuscript submission and claiming a very rapid processing timeline. In comparison to the HIC group, emails from the LIC group were significantly more likely to have impersonal greetings, poor integrity, request an urgent reply, and request an email back to unsubscribe from further emails. The websites of journals targeting LIC researchers were significantly more likely to use language that overly flattered authors and lacked a description of the peer review process. HIC target emails were more likely to be from journals out of scope of the authors’ work.
Interpretation:
We identified similarities and differences between LIC and HIC predatory journal submission request emails and their websites. Being aware of these different approaches may help authors better avoid predatory publishing in future.
Prediction of multi-sectoral longitudinal water withdrawals using hierarchical machine learning models
Authors: Shortridge Julie 
Published: October 2022

AbstractAccurate models of water withdrawal are crucial in anticipating the potential water use impacts of drought and climate change. Machine-learning methods are increasingly used in water withdrawal prediction due to their ability to model the complex, nonlinear relationship between water use and potential explanatory factors. However, most machine learning methods do not explicitly address the hierarchical nature of water use data, where multiple observations through time are typically available for multiple facilities, and these facilities can be grouped in a variety of different ways. This work presents a novel approach for prediction of water withdrawals across multiple usage sectors using an ensemble of models fit at different hierarchical levels. A dataset of over 300,000 records of water withdrawal was used to fit models at the facility and sectoral grouping levels, as well as across facility clusters defined by temporal water use characteristics. Using repeated holdout cross validation, it demonstrates that ensemble predictions based on models learned from different data groupings improve withdrawal predictions for 63% of facilities relative to facility-level models. The relative improvement gained by ensemble modeling was greatest for facilities with fewer observations and higher variance, indicating its potential value in predicting withdrawal for facilities with relatively short data records or data quality issues. Inspection of the ensemble weights indicated that cluster level weights were often higher than sector level weights, pointing towards the value of learning from the behavior of facilities with similar water use patterns, even if they are in a different sector.
An integrated organoid omics map extends modeling potential of kidney disease
Authors: Lassé Moritz , Eddy Sean , Saghir Jamal El , Fischer Matthew , Hutzfeldt Arvid , Berthier Celine , Bonin Léna , Dumoulin Bernhard , Menon Rajasree , Vega-Warner Virginia , Eichinger Felix , Alakwaa Fadhl , Fermin Damian , McCown Phillip , Godfrey Bradley , Brandts Paul , Ju Wenjen , Reinhard Linda , Hoxha Elion , Grahammer Florian , Lindenmeyer Maja , Huber Tobias , Schlüter Hartmut , Thiel Steffen , Mariani Laura , Kretzler Matthias , Demir Fatih , Harder Jennifer , Rinschen Markus 
Published: October 2022

Abstract
Kidney organoids are a promising model to study kidney disease, but use is constrained by limited knowledge of their functional protein expression profile. We aimed to define the organoid proteome and transcriptome trajectories over culture duration and upon exposure to TNFα, a cytokine stressor. Older organoids increased deposition of extracellular matrix but decreased expression of glomerular proteins. Single cell transcriptome integration revealed that most proteome changes localized to podocytes, tubular and stromal cells. TNFα-treatment of organoids effected 320 differentially expressed proteins, including cytokines and complement components. Transcript expression of these 320 proteins was significantly higher in individuals with poorer clinical outcomes in proteinuric kidney disease. Key TNFα-associated protein (C3 and VCAM1) expression was increased in both human tubular and organoid kidney cell populations, highlighting the potential for organoids to advance biomarker development. By integrating kidney organoid omic layers, incorporating a disease-relevant cytokine stressor and comparing to human data, we provide crucial evidence of functional relevance of the kidney organoid model to human kidney disease.