bluuebunny/crossref_metadata_2025_split huggingface dataset:
Symptom patterns of comorbid depression and anxiety among older adults in China and their predictors
Authors: Yu Lingling , Chen Chuqian 
Published: January 2024

AbstractComorbid depression and anxiety causes serious psychological and physiological damage for older people. This study aimed to identify heterogeneous classes of comorbid depression and anxiety (CDA) among older people in China and to ascertain predictors of latent class membership. Cross‐sectional data of 10,919 cases were extracted from the Chinese Longitudinal Healthy Longevity Survey. Latent profile analysis (LPA) was used to identify symptom patterns of comorbid depression (measured by the 10‐item Center for Epidemiologic Studies Depression Scale) and anxiety (measured by the Generalized Anxiety Disorder 7‐item Scale). Multinomial logistic regressions following bivariate analyses were used to explore the relationship between the derived classes and individual‐ and social‐level factors. Four patterns of CDA were identified: low symptoms of depression and anxiety (30.52%; n = 3333), mild depression only (53.26%; n = 5815), moderate depression and anxiety (13.82%; n = 1509), and severe depression and anxiety (2.40%; n = 262). Older people who are male, suffer from multimorbidity, and lack a healthy lifestyle are more likely to have problematic symptom profiles. While intimate relationships with partners and children significantly predicted CDA patterns, the effects of sibling relationships, daily life, and emotional support from the community were insignificant. LPA identified four distinct CDA patterns among a representative sample of older Chinese people. While restless sleep, lack of positive emotions, uselessness, and weak concentration are salient across all profiles, “difficult to relax” is prominent in profiles high in anxiety. In addition to individual‐level variables, social‐level factors, especially intimate relationships with partners and children rather than general links to siblings or the community, have unneglectable impacts on whether and to what extent older Chinese adults suffer from CDA in the cultural context of relationism, patriarchy, and filial piety.
Performance reliability degradation analysis and lifetime prediction based on generalized normal grey cloud Bayesian Wiener process
Authors: Niu Cuiping , Fang Zhigeng 
Published: January 2024

AbstractThis study addresses the problem of performance reliability degradation and lifetime prediction in complex systems with high reliability but insufficient information. It comprehensively considers the effects of various uncertainties, such as measurement, cognitive, and stochastic uncertainties, and proposes a generalized normal grey cloud Bayesian Wiener process (GNGCBWP) stochastic degradation model. First, based on the historical degradation information of the system, the interval grey number sequence of the degradation increment is constructed, and the performance degradation path of the system is analyzed to determine the degradation model type. Then, combining the normal grey cloud and Bayesian estimation theory, the relevant definitions and theorems of generalized normal grey cloud Bayesian estimation (GNGCBE) are proposed. Finally, the parameter estimation results obtained using the GNGCBE method are substituted into the grey Wiener process degradation model to dynamically analyze performance reliability degradation and predict the remaining useful life (RUL) in real‐time. And the validity and scientificity of the proposed model is verified through a case study of laser equipment. Moreover, the comparison results of the models indicate that the proposed model has advantages in dynamic analysis of performance reliability degradation and real‐time RUL prediction for highly reliable complex systems with limited or poor degradation information. It can significantly reduce the impact of multiple uncertainties on the analysis results and improve the accuracy and reliability of the final prediction results.
Structural, electronic, and optical properties of Cd‐halide‐based inorganic LiCdX3 (X = F, Cl) perovskites for photovoltaic applications: A density functional theory study
Authors: Ghani Muhammad Usman , Sagir Muhammad , Tahir Muhammad Bilal , Ullah Sami , Assiri Mohammed Ali 
Published: January 2024

AbstractHalide base perovskite LiCdX3 (X = F, Cl) is tested by CASTEP (Cambridge Serial Total Energy Package) based on density function theory (DFT). The presented discussion is to explore the structural, electronic, and optical properties of LiCdX3 (X = F, Cl). The calculated values of the lattice parameter are found to be 3.8 Å and 5.27 Å of LiCdF3 and LiCdCl3 respectively. The ideal structure of LiCdX3 (X = F, Cl) is cubic and dynamically stable. Electronic properties show that materials are semiconductors. The results from band structure are further evaluated by the total and partial density of states. The partial and total density of states confirms the degree of localization of electrons. In optical properties, the highest absorption coefficient is observed in LiCdCl3. The material is half metallic and has a narrow indirect band gap which may be used in photovoltaic applications.
Randomly Pruning the Sachdev‐Ye‐Kitaev Model
Authors: Berkovits Richard 
Published: January 2024

AbstractThe Sachdev‐Ye‐Kitaev model (SYK) is renowned for its short‐time chaotic behavior, which plays a fundamental role in its application to various fields such as quantum gravity and holography. The Thouless energy, representing the energy scale at which the universal chaotic behavior in the energy spectrum ceases, can be determined from the spectrum itself. When simulating the SYK model on classical or quantum computers, it is advantageous to minimize the number of terms in the Hamiltonian by randomly pruning the couplings. In this paper, it is demonstrated that even with a significant pruning, eliminating a large number of couplings, the chaotic behavior persists up to short time scales. This is true even when only a fraction of the original couplings in the fully connected SYK model, specifically , is retained. Here, represents the number of sites, and . The properties of the long‐range energy scales, corresponding to short time scales, are verified through numerical singular value decomposition (SVD) and level number variance calculations.
Untangling asthma, inducible laryngeal obstruction, and dysfunctional breathing in a competitive sportsperson
Authors: Crawford Alice L. , Setty Niranjan , Kyle Brooke , Baumwol Kate , Blakey John D. 
Published: January 2024

AbstractA young woman with historically mild asthma experienced worsening breathlessness and cough with competitive ice skating. Despite optimizing and escalating treatment for her eosinophilic asthma, and addressing known exacerbating factors, her symptoms remained uncontrolled and refractory to bronchodilators and oral corticosteroids. Objective testing suggested her presentation was out of keeping with asthma alone, and she was suspected to have comorbid dysfunctional breathing and/or inducible laryngeal obstruction. Evidence was required to confirm the diagnoses, assess each condition's contribution to her symptom burden, and guide therapy. As exercise was a predominant trigger, she proceeded to cardiopulmonary exercise test with continuous laryngoscopy during exercise (CPET‐CLE). Testing confirmed the presence of two forms of inducible laryngeal obstruction and evidence of hyperventilation predominant dysfunctional breathing. This case highlights the importance of identifying coexisting conditions in difficult‐to‐treat asthma, and the value of structured multidisciplinary assessment in referral centres for such individuals.
Study of a bounded interval perks distribution with quantile regression analysis
Authors: Al‐Essa Laila A. , Shafiq Shakaiba , Ozonur Deniz , Jamal Farrukh 
Published: January 2024

AbstractIn this article, a novel bounded interval model called the unit‐Perks model is developed by suitably transforming the positive random variable of the Perks distribution. Numerous statistical features of the bounded interval Perks model are being explored based on the expansion of the density function. Eight distinct estimation approaches are being used to estimate the parameters of the unit‐Perks model. A throughout simulation analysis is also included to evaluate the precision of the resulting estimators from eight estimating approaches. Two real bounded interval data sets are being utilized to investigate the practical applicability of the unit‐Perks model. A comparison is also made to determine which method of estimation works better for the given model. According to a comparison of eight different estimation approaches, the maximum likelihood estimation approach outperformed than the other seven estimating approaches. The unit‐perks model is then used to introduce the quantile regression model named as quantile unit‐Perks distribution. Application to real data set for the quantile unit‐Perks distribution is also performed. The quantile residuals are used for the residual analysis of the fitted regression model. On the basis of mathematical, computational, and pictorial evidences, it is concluded that the presented model exhibited greater modeling capabilities.
Ce‐Modified MgFe−LDH Supported Au Particles: An Efficient Catalyst for Base‐Free Selective Oxidation of 5‐Hydroxymethylfurfural to 2,5‐Furandicarboxylic Acid
Authors: Moradi Hanieh , Kulinich Sergei A. , Wunderlich Wilfried , Ghiaci Mehran 
Published: January 2024

Abstract5‐hydroxymethylfurfural (HMF) was selectively oxidized to 2,5‐furandicarboxylic acid (FDCA) using an effective catalytic system made of Au particles supported on Ce‐modified MgFe layered double hydroxide. The structural features and performance of the as‐prepared catalysts were examined using a range of characterizations, and the impact of altering reaction parameters was explored. It was demonstrated that the presence and quantity of Ce and Mg species in the catalyst formulation were the primary determinants of the activity of the Au@Mg−N−M−LDH catalysts (M=Ce, Cu, Mn, Zr, and N=Fe, Al). The catalyst Au@MgFeCe−LDH, loaded with 1 wt % Au, exhibited outstanding catalytic activity in the production of FDCA, achieving complete HMF conversion and 90 % FDCA selectivity. This was accomplished through a two‐step heating procedure, involving initial heating of the reaction medium at 40 °C for 2 hours followed by a subsequent heating at 100 °C for 6 hours, conducted under an oxygen pressure of 5 bar.
X‐Ray Crystallography and Antimicrobial Activity of Synthetic Cyanoguanidinophenytoin Cocrystals
Authors: Mabied Ahmed F. , Moustafa Amr H. , Abdelhamid Antar A. , Tiama Taha M. , Amer Amer A. 
Published: January 2024

AbstractA novel series of 1 : 1 cocrystals of 2‐cyanoguanidinophenytoin (CNG‐DPH) with primary, secondary, and tertiary aliphatic amines has been presented through this work. The antimicrobial activities of all new CNG‐DPH‐amine cocrystals were studied. The existence of cocrystals has been proven through crystal structure results. The 5‐Oxo‐4,4‐diphenylimidazolidin‐2‐ylidenecyanamide‐piperidine cocrystal (10) is located in an orthorhombic crystal system, and the cocrystal is connected via the N−H−N hydrogen bond between the cyanide group and the piperidine molecule. Hirshfeld surface analysis authenticated supramolecular contacts. Ring puckering analysis revealed a chair stereochemistry at the 6‐membered piperidine. The crystal packing has been stabilized through intermolecular forces, hydrogen bonds, and interactions within the gravity center of rings (Cg). The antimicrobial activities of the newly synthesized compounds were only effective against Gram‐positive bacteria, demonstrating that the antibacterial spectrum of these compounds was restricted. In vitro cytotoxicity of the synthesized cocrystals was assessed in normal cells, giving the highest half‐maximal inhibitory concentration (IC50) ratio (637.63 μg/ml) and the lowest value (181.98 μg/ml).
Infant emotion regulation in the context of stress: Effects of heart rate variability and temperament
Authors: Weiss Sandra J. , Keeton Victoria F. , Leung Cherry , Niemann Sandra 
Published: January 2024

AbstractStressful events are inherently emotional. As a result, the ability to regulate emotions is critical in responding effectively to stressors. Differential abilities in the management of stress appear very early in life, compelling a need to better understand factors that may shape the capacity for emotion regulation (ER). Variations in both biologic and behavioural characteristics are thought to influence individual differences in ER development. We sought to determine the differential contributions of temperament and heart rate variability (HRV; an indicator of autonomic nervous system function) to infant resting state emotionality and emotional reactivity in response to a stressor at 6 months of age. Participants included 108 mother‐infant dyads. Mothers completed a measure of infant temperament at 6 months postnatal. Mother and infant also participated in a standardized stressor (the Repeated Still Face Paradigm) at that time. Electrocardiographic data were acquired from the infant during a baseline resting state and throughout the stressor. Fast Fourier Transformation was used to analyse the high frequency (HF) domain of HRV, a measure of parasympathetic nervous system activity. Infant ER was measured via standardized coding of emotional distress behaviours from video‐records at baseline and throughout the stressor. Severity of mothers' depressive symptoms was included as a covariate in analyses. Results of linear regression indicate that neither temperament nor HRV were associated significantly with an infant's emotional resting state, although a small effect size was found for the relationship between infant negative affectivity and greater emotional distress (β = 0.23, p = 0.08) prior to the stressor. Higher HF‐HRV (suggesting parasympathetic dominance) was related to greater emotional distress in response to the stressor (β = 0.34, p = 0.009). This greater emotional reactivity may reflect a more robust capacity to mount an emotional response to the stressor when infants encounter it from a bedrock of parasympathetic activation. Findings may inform eventual markers for assessment of ER in infancy and areas for intervention to enhance infant management of emotions, especially during stressful events.
Piezo‐catalysis in BiFeO3@In2Se3 Heterojunction for High‐Efficiency Uranium Removal
Authors: Guo Rongshuo , Jin Linghua , Zhang Ye 
Published: January 2024

AbstractPiezo‐catalysis emerges as an efficient, safe, and affordable strategy for removing hazardous substances from aquatic environments. Here, the BiFeO3@In2Se3 heterojunction demonstrates remarkable prowess as a piezo‐catalyst, enabling the high‐efficiency removal of uranium (U) from U(VI)‐containing water. A total U(VI) removal efficiency of 94.6% can be achieved under ultrasonic vibration without any sacrificial agents. During the entire catalytic process, piezo‐induced electrons, hydroxyl radicals, and superoxide radicals play important roles in U(VI) removal, while the generated H2O2 is responsive to the transformation of soluble U(VI) into insoluble (UO2)O2•2H2O and UO3. Furthermore, auxiliary illumination can accelerate the increase of free charges, enabling the piezo‐catalyst to retain more charges. This leads to an improved U(VI) removal efficiency of 98.8% and a significantly increased reaction rate constant. This study offers a comprehensive analysis of the fabrication of high‐efficiency piezo‐catalysts in the removal or extraction of U(VI) from U(VI)‐containing water.
Enhanced Spin‐Polarized Electric Field Modulating p‐Band Center on Ni‐Doped CdS for Boosting Photocatalytic Hydrogen Evolution
Authors: Wu Fei , Zhang Xinlei , Wang Lei , Li Guicun , Huang Jianfeng , Song Aili , Meng Alan , Li Zhenjiang 
Published: January 2024

AbstractIt is a challenge to regulate charge separation dynamics and redox reaction kinetics at the atomic level to synergistically boost photocatalytic hydrogen (H2) evolution. Herein, a robust Ni‐doped CdS (Ni‐CdS) photocatalyst is synthesized by incorporating highly dispersed Ni atoms into the CdS lattice in substitution for Cd atoms. Combined characterizations with theoretical analysis indicate that local lattice distortion and S‐vacancy of Ni‐CdS induced by Ni incorporation lead to an increased dipole moment and enhanced spin‐polarized electric field, which promotes the separation and transfer of photoinduced carriers. In this contribution, charge redistribution caused by enhanced internal electric field results in the downshift of the S p‐band center, which is conducive to the desorption of intermediate H* for boosting the H2 evolution reaction. Accordingly, the Ni‐CdS photocatalyst shows a remarkably improved photocatalytic performance with an H2 evolution rate of 20.28 mmol g−1 h−1 under visible‐light irradiation, which is 5.58 times higher than that of pristine CdS. This work supplied an insightful understanding that the enhanced polarization electric field governs the p‐band center for efficient photocatalytic H2 evolution activity.
Flexural behavior of cold‐formed U‐shaped steel members encasing concrete composite beam using continues stud bolts
Authors: Al‐Lami Karrar , Jabir Hussain A. , Shamsaldeen Hassan A. , Algasham Thaar , Mhalhal Jasim M. , Goaiz Hussam A. , Abid Sallal 
Published: January 2024

AbstractThe current paper presents an innovative form of the cold‐formed U‐shape steel encasing concrete composite beam (CUCB). The suggested CUCB consists of a cold‐formed U‐shaped steel encasing plain concrete beam which are connected to each other using continuous transversal threaded stud bolts. The experimental program consisted of eight beam specimens tested in the four‐point bending set‐up. One of them was a normal reinforced concrete beam and considered as a reference specimen while the remaining specimens were CUCB specimens without ordinary flexural and shear reinforcement. Four parameters were studied in this paper: (i) the thickness of the U‐shaped steel, (ii) the spacing between the stud bolts, (iii) the arrangement of the bolts, and (iv) the number of the bolt's rows. Results indicated an overall improvement in the load‐carrying capacity and stiffness of most CUCB specimens in comparison with the reference specimen. It was found that the using of three rows of bolts can significantly improve the ductility and toughness of the CUCB specimen in comparison with two rows of bolts. On the contrary, an increase in the bolt spacing entails a decrease in the CUCB specimens' toughness.
Causal‐mechanical explanations in biology: Applying automated assessment for personalized learning in the science classroom
Authors: Ariely Moriah , Nazaretsky Tanya , Alexandron Giora 
Published: January 2024

AbstractOne of the core practices of science is constructing scientific explanations. However, numerous studies have shown that constructing scientific explanations poses significant challenges to students. Proper assessment of scientific explanations is costly and time‐consuming, and teachers often do not have a clear definition of the educational goals for formulating scientific explanations. Consequently, teachers struggle to support their students in this process. It is hoped that recent advances in machine learning (ML) and its application to educational technologies can assist teachers and learners in analyzing student responses and providing automated formative feedback according to well‐defined pedagogical criteria. In this study, we present a method to automate the entire assessment‐feedback process. First, we developed a causal‐mechanical (CM)‐based grading rubric and applied it to student responses to two open‐ended items. Second, we used unsupervised ML tools to identify patterns in student responses. Those patterns enable the definition of “meta‐categories” of explanation types and the design of personalized feedback adapted to each category. Third, we designed an in‐class intervention with personalized formative feedback that matches the response patterns. We used natural language processing and ML algorithms to assess students' explanations and provide feedback. Findings from a controlled experiment demonstrated that a CM‐based grading scheme can be used to identify meaningful patterns and inform the design of formative feedback that promotes student ability to construct explanations in biology. We discuss possible implications for automated assessment and personalized teaching and learning of scientific writing in K‐12 science education.
Systemic therapies in hepatocellular carcinoma: A revolution?
Authors: Fortuny Marta , Sanduzzi‐Zamparelli Marco , Reig Maria 
Published: January 2024

AbstractThe evolution in systemic therapies in hepatocellular carcinoma (HCC) signifies a strategy of high‐cost, high‐gain innovation that originated with sorafenib, despite its limited impact on tumor response. This strategic approach paved the way for the emergence of a second wave of the short‐lived competitive advantage, exemplified by the incorporation of atezolizumab plus bevacizumab and tremelimumab plus durvalumab. In the context of safety concerns within the liver cancer domain, the IMBRAVE150 and HIMALAYA trials boldly incorporated bevacizumab and tremelimumab, respectively, demonstrating the continuation of the high‐risk, high‐reward innovation paradigm. This review delves into the strengths, weaknesses, opportunities, and threats analysis of systemic therapies in the field of HCC.
An experimental study on the identification of the root bolts' state of wind turbine blades using blade sensors
Authors: Gao Feng , Qian Chenkai , Xu Lin , Liu Juncheng , Zhang Hong 
Published: January 2024

AbstractBolt looseness may occur on wind turbine (WT) blades exposed to operational and environmental variability conditions, which sometimes can cause catastrophic consequences. Therefore, it is necessary to monitor the loosening state of WT blade root bolts. In order to solve this problem, this paper proposes a method to monitor the looseness of blade root bolts using the sensors installed on the WT blade. An experimental platform was first built by installing acceleration and strain sensors for monitoring bolt looseness. Through the physical experiment of blade root bolts' looseness, the response data of blade sensors is then obtained under different bolt looseness numbers and degrees. Afterwards, the sensor signal of the blade root bolts is analyzed in time domain, frequency domain, and time‐frequency domain, and the sensitivity features of various signals are extracted. So the eigenvalue category as the input of the state discrimination model was determined. The LightGBM (light gradient boosting machine) classification algorithm was applied to identify different bolt looseness states for the multi‐domain features. The impact of different combinations of sensor categories and quantities as the data source on the identification results is discussed, and a reference for the selection of sensors is provided. The proposed method can discriminate four bolt states at an accuracy of around 99.8% using 5‐fold cross‐validation.
Discrete fracture‐matrix model of poroelasticity
Authors: Březina Jan , Stebel Jan 
Published: January 2024

AbstractThe paper presents the derivation and analysis of a poroelasticity model in a domain with fracture represented by a codimension‐one manifold. The system of saturated flow and linear elasticity both in the rock matrix and in the fracture coupled through an appropriate interface condition is obtained from a continuum description by integration and semi‐discretization in the normal direction of the fracture. The existence and uniqueness of a weak solution are proved with the help of an iterative splitting, whose convergence rate is analyzed. The analysis is complemented by a numerical example.