bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of the diamond passing exercise modelnand triangle against passing accuracy football on extracurriculars
Authors: Hakim Nurwahidin , Candra Juli , Yahya Andi Amry , Kahar Irsan 
Published: January 2023

Abstract
This study aims to determine the effect of diamond passing and passing triangle training models on football passing accuracy in SMP Negeri 8 Palopo football extracurriculars. This research is a type of Quantitative research. The population and sample of this study were extracurricular participants in SMP Negeri 8 Palopo, which numbered 20 students. The research design used is One group pretest-posttest design. What is given is diamond passing and passing triangle training. The data obtained is processed using SPSS version 26.0. The results of the t-test of experimental group 1 can be seen t count > t table: 8,189 > 2,306 with a significance of 0.000 < 0.05. in experimental group 2 can be seen t count > t table:7,875 > 2,306 with a significance of 0.000 < 0.05. So, this result shows that there is a significant difference. From the results of the pre-test and post-test comparison test of experimental group I and experiment group II, it is known that the passing diamond > passing triangle: 8,189 > 7,875. Thus, it can be concluded that "There is an influence of the diamond passing training model on passing accuracy in football extracurriculars
Role of Emotional Intelligence in Aggressive and Violent Behaviors among Undergraduates in a Lower Resource Setting
Authors: Fayaz Fazla , Nilaweera Irosha , Cassim Riyas , Samaranayake Dulani 
Published: January 2023

Abstract

Introduction:Various forms of Aggressive and Violence Behavior(AVB) among undergraduates have been studied and shown considerable evidence of a significant link between Emotional-Intelligence(EI).
Objective:is to assess the prevalence of AVB and its association with EI among second-year undergraduatesin a lower resource setting.
Method:A descriptive-cross-sectional study was carried out among 1290, second-year undergraduates using multi-stage stratified cluster sampling in four randomly selected universities in Sri Lanka. UniHRB-Inventory is a self-administered questionnaire developed, translated and validated in a local setting. The domain measures AVB with 14 items, scoring from 0 for “never” and 4 for “more than 5 times”. The minimum-threshold-score for the presence of AVB was 32. Schutte’s Self-reported-EItool was used to assess EI. Total EI score was compared between those with and without AVB using the Mann-Whitney U test. A Multiple Logistic Regression (MLR) analysis was performed to control confounders.
Results:Overall response-rate for the study was 88.1% (n=1136). Prevalence of AVB was 2.6% (95%CI:1.8%-3.7%). There was a statistically significant difference between the median total EI among undergraduates with and without AVB (median 72 vs 126; p<0.0001). EI had a significant negative effect on the likelihood of AVB following MLR. When EI increases by one unit the odds of having AVB decreases by a factor of 0.93 (95%CI:0.89-0.98;p<0.05).
Conclusion and Recommendation: People with better EI are less likely to have AVB. It is recommended to include EI in the routine of undergraduates’ curriculum to prevent AVB in a lower resource setting.
The perceptions and attitudes of obstetric staff and midwives towards perinatal mental health disorders screening: a qualitative study in Shenzhen, China
Authors: Xiao Xiao , Ma Haixia , Zhu Shening , Li Qiaomeng , Chen Yu 
Published: January 2023

Abstract
Background: The perinatal period is a crucial time both for women, who will experience biological, psychological, and social stressors. The complexity of this vulnerable time leads to a prevalence of depressive and anxiety disorders for women during pregnancy. As a pilot city of the Opening Policy in China, The Health Commission of Shenzhen initiated perinatal mental health screening in 2019, but medical staff perceptions and attitudes on implementating mental health disorders screening during pregnancy are still unclear. The aim of this study was to explore the perceptions and attitudes of obstetric staff and midwives towards perinatal mental disorders screening of pregnant women, and identify their perceived needs and motivation to take on the task.
Methods: This is a qualitative descriptive study. Data were collected through in-depth, semi-structured, face-to-face interviews. The dataset was analysed using inductive content analysis. Purposive sampling was used to recruit participants at a tertiary maternal hospital in Shenzhen from September to November, 2019.
Results: A total of 13 obstetric staff was interviewed, including two obstetricians, three midwives, and eight nurses. Four themes were identified from this study: views on perinatal mental health disorders screening, competency in identifying and supporting high-risk groups, barriers to dealing with psychological problems during pregnancy, and the support needs of medical staff in undertaking the tasks of mental health disorders screening.
Conclusion: Medical staff were not well prepared for the task of screening pregnant women for mental health disorders due to insufficient knowledge and skills in perinatal psychological health. Medical organisations and relevant government sectors should provide training to medical staff on perinatal mental health disorders, enhance public awareness of perinatal mental health disorders, establish a model of multidisciplinary collaboration for the screening of women’s perinatal mental disorders, and provide continuous and holistic care for pregnant women.
The Prediction of the Bulk Modulus and its Temperature-Derivative of the Crystalline β-SiC Ceramic
Authors: Abdul-Hafidh Esam H. 
Published: January 2023

Abstract
The prediction of the isothermal bulk modulus BT and the temperature-derivative (∂BT/∂T)p of crystalline silicon carbide (β -SiC) from experimental data are presented in this work. Using the experimental measurements of the coefficient of thermal expansion found by Z. Li and R. C. Bradt and the empirical value of the Anderson parameter, the variations in bulk modulus as a function of temperature and pressure are traced. Both BT and its temperature-derivative were calculated within the temperature range of 273-1573K. The bulk modulus has been found to decrease by 2.4% from its value at 273K upon heating to a temperature of 1573K. The temperature derivative of the bulk modulus decreases from − 0.003 GPa/K at 273K to a minimum of -0.0046 at Debye's temperature (1173K), and then increases again as the temperature increases. The bulk modulus has been also calculated by thermodynamical equations for the purpose of comparison, where the empirical and the thermodynamical results match to within a negligible margin of error. Both results for BT were compared to previous LDA predictions and were found to deviate by 1.72% at 237K to 5.27% at 937K, respectively. The bulk modulus BT has also been investigated as the pressure is varied from 0 to 70 GPa, where BT has been found to increase from 226.9 GPa at 0 GPa to 513.9 GPa at 70 GPa.
Schwarzian derivative for convex mappings of order $\alpha$
Authors: Carrasco Pablo , Hernández Rodrigo 
Published: January 2023

Abstract
The main purpose of this paper is to obtain sharp bounds of the norm of Schwarzian derivative for convex mappings of order \(alpha\) in terms of the value of \(f''(0)\), in particular, when this quantity is equal to zero. In addition, we obtain sharp bounds for distortion and growth for this mappings and we generalized the results obtained by Suita \cite{SUITA} and Yamashita \cite{Y} for this particular case.
MSC Classification: 30C45 , 30C80 , 30A10
The earlier, the better? An in-depth interview study on the ethics of early detection with parents of children at an elevated likelihood for autism.
Authors: Vanaken Gert-Jan , Noens Ilse , Steyaert Jean , Esch Lotte van , Warreyn Petra , Hens Kristien 
Published: January 2023

Abstract

Autism is increasingly viewed as an expression of neurodiversity deserving accommodation, rather than merely as a disorder in need of remediation or even prevention. This reconceptualization has inspired calls to broaden the ethical debate on early autism care beyond matters of efficient screenings and effective interventions. We conducted 14 in-depth interviews with 26 parents of infants at an increased likelihood for autism (siblings, preterms and children with persistent feeding difficulties) to understand which benefits and risks these parents see for the implementation of a systematic, early autism detection program in our region [name blinded for review]). With this study, we aim to contribute empirically to the ethical debate on good and just early autism care in the age of neurodiversity. Data were analyzed according to the QUAGOL-methodology. Three main themes emerged from our analysis. In their evaluation of early autism detection, parents discussed how a diagnosis helps gain a different perspective fostering understanding and recognition for both child and parent. Second, a diagnosis supports parents in adjusting their parenting practices, to justify this deviation from “normal” parenting and to strive for such adjusted environments beyond the nuclear family. Third, an autism diagnosis induces ambiguities parents need to navigate, involving questions on whether and when to mobilize the diagnostic label and which language to use to talk about autism. We discuss the complex position of parents of a (potentially) autistic child in terms of moving back and forth across the ab/normal binary and describe implications for the ethical debate on early autism detection.
Breakdown Prediction Utilizing Data Mining Algorithms in Combination With Performance Measures Derived From Connected Vehicle Data
Authors: Mata Hector Donaldo , Jabin Atika , Hadi Mohammed 
Published: January 2023

Abstract
Connected vehicles (CV) will provide an important source of data to support real-time management of traffic operations and off-line analysis of traffic operations. CV data allows the derivation of metrics not currently computed for use in freeway management such as the standard deviation of speed, acceleration/deceleration, and jerk. This study explores the utilization of CV data to derive such metrics for use in traffic management. The study then investigates the use of the derived metrics in combination with data analytic techniques to assess and predict the onset of congestion on freeways in real-time operations.
The analysis revealed using cluster analysis and classification decision tree that the traffic states of the freeway facility used as a case study could be classified into groups representing six different traffic conditions based on speed, standard deviation of speed between vehicles, standard deviation between points, as well as the deceleration values. The study also compared the performance of three data mining/machine learning techniques for the prediction of congestion using a decision tree, a fuzzy rules-based system that utilizes the decision tree results, and a neuro-fuzzy inference system model utilizing the backpropagation optimization method for optimization. The comparison of the performance of the three prediction models demonstrated that the neuro-fuzzy inference system model achieved the best performance in terms of various performance measures that are commonly used to assess machine learning performance.
Evolutionary finance: A model with endogenous asset payoffs
Authors: Evstigneev Igor , Hens Thorsten , Mohammad Javad Vanaei 
Published: January 2023

Abstract
Evolutionary Finance (EF) explores financial markets as evolving biological systems. Investors pursuing diverse investment strategies compete for the market capital. Some "survive" and some "become extinct". A central goal is to identify evolutionary stable (in one sense or another) investment strategies. The problem is analyzed in a framework combining stochastic dynamics and evolutionary game theory. Most of the models currently considered in EF assume that asset payoffs are exogenous and depend only on the underlying stochastic process of states of the world. The present work develops a model where the payoffs are endogenous: they depend on the share of total market wealth invested in the asset.
JEL-classification: D53, E21, G11.
Effects of Multi-Surface Texturing on the Tribological Properties of Aluminum Based Self-Lubricating Joint Bearing under Grease Condition
Authors: Owusu-Mensah Daniel , Hua Xijun , Tian Zhixiang , Chen Ya Lin 
Published: January 2023

Abstract
Joint bearing contact surfaces of high-tech precision machinery applied particularly in the manufacturing industry undergo varying range of extreme temperature and pressure conditions, which subject them to frictional wear, tear and stress during operation in different environments of application. A continuous assessment of their resilient capacities is therefore necessary to avoid operational failure of core base component parts. The aim of this study is to assess the effects of multi-surface treatment and texturing processes on the frictional and stress performance of aluminum based self-lubricating joint bearing under grease condition. Using ANSYS software based on the Hertz contact theory and Boussinesqmodel for numerical simulations of rated static load contact, the study showed that under dry friction and grease lubrication, PTFE/ardex pad stabilizes the surface friction coefficient and effectively reduces the friction coefficient. Again, the friction coefficient of the aluminum self-lubrication increases with the texture share and the sample with 15% share shows the lowest friction coefficient (0.114), under lipid lubrication conditions. It is recommended for future research to conduct a wobble (transient dynamics) and thermodynamic analysis for the model, and attempt to optimize the friction resistance of self-lubricating joint bearing by adjusting the deposition process parameters like current value, temperature and element contact.
A Policy-Graph Approach to Explain Reinforcement Learning Agents: A Novel Policy-Graph Approach with Natural Language and Counterfactual Abstractions for Explaining Reinforcement Learning Agents
Authors: Liu Tongtong , McCalmon Joe , Le Thai , Lee Dongwon , Alqahtani Sarra 
Published: January 2023

Abstract
As reinforcement learning (RL) continues to improve and be appliedin situations alongside humans, the need to explain the learned behaviorsof RL agents to end-users becomes more important. Strategies forexplaining the reasoning behind an agent’s policy, called policy-levelexplanations, can lead to important insights about both the task and theagent’s behaviors. Following this line of research, in this work, we proposea novel approach, named as CAPS, that summarizes an agent’s policy inthe form of a directed graph with natural language descriptions. A decisiontree based clustering method is utilized to abstract the state space ofthe task into fewer, condensed states which makes the policy graphs moredigestible to end-users. We then use the user-defined predicates to enrich the abstract states with semantic meaning. To introduce counterfactual state explanations to the policy graph, wefirst identify the critical states in the graph then develop a novel counterfactualexplanation method based on action perturbation in those criticalstates.We generate explanation graphs using CAPS on 5 RL tasksfor deterministic and stochastic policies. We evaluate the effectivenessof CAPS on human participants who are not RL experts in twouser studies. When provided with our explanation graph, end-users are ableto accurately interpret policies of trained RL agents 80% of the time and 68.2%of users demonstrated an increase in their confidence in understandingan agent’s behavior.
A parallel iterative procedure for weak Galerkin methods for second order elliptic problems
Authors: Wang Chunmei , Wang Junping , Zhang Shangyou 
Published: January 2023

Abstract
A parallelizable iterative procedure based on domain decomposition is presented and analyzed for weak Galerkin finite element methods for second order elliptic equations. The convergence analysis is established for the decomposition of the domain into individual elements associated to the weak Galerkin methods or into larger subdomains. A series of numerical tests are illustrated to verify the theory developed in this paper.
Association Between Follicle Size, Endometrial Thickness, and Types of Ovarian Stimulation (Clomiphene Citrate and Letrozole) With Biochemical Pregnancy Rate in Women Undergone Intrauterine Insemination
Authors: Rachmawati Anita , Krisnadi Sofie Rifayani , Santoso Shasya Aniza , Nugrahani Annisa Dewi 
Published: January 2023

Abstract
Objective: There was also a lack of data regarding the effect of follicle size, endometrial thickness, and ovarian stimulation as predictors of intrauterine insemination (IUI) success rate in Indonesia, especially in the Aster Clinic and Bandung Fertility Centre. This study was performed to explore the relationship between follicle size, endometrial thickness, and types of ovarian stimulation (Clomiphene citrate/CC vs Letrozole) with biochemical pregnancy rate in women undergone IUI. We performed a case-control study in 122 women aged 20-40 years with unexplained infertility who had completed the IUI program for a maximum of three cycles. Data were extracted from medical records. Independent T-test and multivariate analyses were used to analyse the difference between variables using IBM SPSS 24.0. P-value < 0.05 was considered statistically significant.
Result: Follicle sizes of 18-22 mm in both Clomiphene citrate (CC) and Letrozole groups were shown to increase biochemical pregnancy rate (P= 0.001). There is no relationship between endometrial thickness and pregnancy rate. Biochemical pregnancy rate in women using Letrozole was 1.513 times higher than women using CC. The follicle size of 18-22 mm and using Letrozole rather than CC as ovarian stimulators are predictive factors associated with a higher pregnancy rate in women undergone IUI.
Toeplitz Operators with Positive Measures on Harmonic Fock Spaces
Authors: Gou Xue , Huang Sui 
Published: January 2023

Abstract
In this paper, we study the basic properties of Toeplitz Operators Tµ with positive measures µ on harmonic Fock spaces such as boundedness, compactness and Schatten class Sp with the methods of Berezin transform of operators.
MSC(2020) 47B10, 47B35
Local well-posedness of the periodic nonlinear Schrödinger equation with a quadratic nonlinearity ū2 in negative Sobolev spaces
Authors: Liu Ruoyuan 
Published: January 2023

Abstract
We study low regularity local well-posedness of the nonlinear Schrödinger equation (NLS) with the quadratic nonlinearity ū2, posed on one-dimensional and two-dimensional tori. While the relevant bilinear estimate with respect to the Xs,b-space is known to fail when the regularity s is below some threshold value, we establish local well-posedness for such low regularity by introducing modifications on the Xs,b-space.
The Analysis between Clinicopathological Aspect of Early-Onset vs Late-Onset Colorectal Cancer and Mortality Rate
Authors: Lukman Kiki , Mulyawan Andi , Nugrahani Annisa Dewi , Rudiman Reno , Primastari Etis 
Published: January 2023

Abstract
Objective: Early-onset colorectal cancer (EOCRC) has different clinical and pathological characteristics compared to late-onset CRC (LOCRC). Mortality rate as a post-operative outcome is a patient's postoperative outcome considered based on the state of life or death. The objective of this research is to analyze the comparison between clinicopathological aspect of early-onset vs late-onset CRC as well as their correlation with the mortality rate in Indonesia to support global data. We performed a case-control study on 170 subjects with CRC from November 2021- November 2022 in Dr. Hasan Sadikin General Hospital. Data were extracted from electronic medical records Colorectal Cancer (CRC) Registry. Bivariate and correlation analyses were used to analyse the difference between variables using IBM SPSS 24.0. P<0.05 was considered statistically significant.
Result: Anemia and tumor location variables were significantly different in the early-onset group compared to the late-onset group (P<0.001). It was also found that anemia (P<0.001), pathological features (P<0.001), and tumor location (P=0.013) had significantly low correlation with onset of CRC (r=0.325; r=0.397; r=0.342, respectively). There is no statistically significant correlation between the clinicopathological features of CRC in both onset and mortality rates in this study.
A velocity decomposition-based 3D optical flow method for accurate Tomo-PIV measurement
Authors: Kang Menggang , Yang Hua , Yin Zhouping 
Published: January 2023

Abstract
3D velocity field estimation is the key to high spatial resolution and high-accuracy measurements in tomographic particle image velocimetry (Tomo-PIV), especially when characterizing flow fields with delicate vortex structures. However, the cross-correlation velocity estimation method has limited spatial resolution due to the limitation of the interrogation sub-volume size. The 3D optical flow method can improve the spatial resolution of the velocity field, but its accuracy needs to be improved because it does not take into account the physical properties of the fluids. In this study, we propose a novel velocity decomposition-based 3D variational optical flow (VD-3DVOF) method to achieve high spatial resolution and high-accuracy measurement of 3D fluids. First, we present a novel regularization term based on the velocity decomposition theorem to constrain the different physical quantities, which can prevent the physical quantities from being over-smoothed. Second, we present a novel data term based on particle volume reconstruction feature weighting to reduce the influence of reconstruction errors on the velocity field estimation accuracy. Third, we present a multiscale technique and a volume warping operation to prevent the solution from falling into local optimal solutions. The newly proposed method considers both the physical properties of the fluid and the errors of reconstructed particle volumes. Velocity fields are estimated over synthetic and experimental particle volumes, and the results and comparisons show that the newly proposed VD-3DVOF method successfully achieves better performance and greater measurement accuracy than existing 3D motion estimation methods.
Evaluation of the simultaneous combination of bed sill and sacrificial piles in the reduction of local scour depth around the bridge pier and three-dimensional analysis of turbulent flow structure around them
Authors: Vahdati Vahid Javidi , Ahmadi Ahmad , Abedini Amirabbas , Heidarpour Manouchehr 
Published: January 2023

Abstract

In the present experimental study, the simultaneous use of bed sill and sacrificial piles around the cylindrical bridge pier was studied, to investigate whether the combination of these two countermeasures could be effective in reducing scour depth. Toward this goal, 14 experiments were conducted. Since it is important to understand the state of sediment entrainment around the pier, the coherent turbulent ﬂow structure around the best combination of bed sill and sacrificial piles was investigated and its effect on the bed scouring pattern was studied. The results related to the flow structure in the unprotected pier were considered for comparison. It was found that the simultaneous use of bed sill and sacrificial piles was completely effective in the control and reduction of local scouring and in the best configuration, it reduced the scour depth by 51.1%. Therefore, the use of this combination can be recommended to reduce the scour depth around the cylindrical pier. In this paper, 3D analysis of the bursting process (octant analysis) was used. Various characteristics of turbulence, such as turbulent kinetic energy, Reynolds shear stress and occurrence and transition probabilities of bursting events, were calculated. Investigating the sediment entrainment around the pier with bed sill and sacrificial piles confirmed the reduction of the scour depth by the combination of these two countermeasures.