bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coupled system of three sequential Caputo fractional differential equations: Existence and stability analysis
Authors: Ganie Abdul Hamid , Houas Mohamed , AlBaidani Mashael M. , Fathima Dowlath 
Published: April 2023

Recently, many studies on fractional coupled systems involving different sequential fractional derivatives have appeared during the past several years. The paper is dealing with a coupled system of three sequential Caputo fractional differential equations, and the designed system absorbs none of the commutativity and the semigroup properties. The Banach contraction principle is used for proving the existence and uniqueness results. We prove the existence of at least one is obtained by using the Leray–Schauder alternative. The Ulam–Hyers–Rassias stability of the considered system is defined and discussed. An illustrative example is also presented.
Physics‐based iterative scheme for computing antenna array embedded element patterns
Authors: Chose Matthews , Conradie André S. , Cilliers Pierre I. , Botha Matthys M. 
Published: April 2023

AbstractRigorously accounting for mutual coupling effects in antenna array synthesis, generally requires that embedded element patterns (EEPs) be determined. The method of moments (MoM) is typically used. Multiple linear system solutions are required, corresponding to every excitation vector associated with an EEP. This paper presents the direct coupling technique (DCT) to obtain the MoM solution for arrays with disjoint elements, by iteratively solving a series of localized subproblems, one associated with each array element. It utilizes a physics‐based, direct‐coupling approximation to incorporate global coupling into the local problems. Local matrices do not change between iterations or with excitation vectors, hence they can be inverted as a preprocessing step, allowing for efficient solution of multiple excitation configurations. Numerical results demonstrate rapid convergence. The convergence rate can be controlled via local problem domain sizing. Since the DCT is ideally suited to parallelization, it is applicable to very large arrays.
Wideband second‐order bandpass frequency selective surface with high selectivity
Authors: Zhao Minxin , Li Huangyan , Wu Zhen , Wang Bin , Min Xiaofan , Cao Qunsheng 
Published: April 2023

AbstractA wideband second‐order bandpass frequency selective surface (FSS), which is composed of three metallic arrays and two dielectric substrate layers, is proposed in this paper. The proposed design has high selectivity and wide passband properties simultaneously and is insensitive to incident angles and different polarizations. The equivalent circuit method and field distribution are analyzed to explain the mechanism of the proposed design. A prototype is fabricated and measured, demonstrating a well wideband second‐order passband ranging from 4.8 to 8.8 GHz with 58.8% bandwidth (−3 dB), and the insertion loss (IL) in‐band is less than 0.4 dB. Meanwhile, the transitional bands at both sides of the passband are 0.64 GHz (9.4%) and 0.6 GHz (8.8%), respectively. Moreover, the frequency responses of the proposed structure are stable up to 60° for both TE and TM polarizations.
Innovative integration of augmented reality and optical surface imaging: A coarse‐to‐precise system for radiotherapy positioning
Authors: Zhang Gongsen , Jiang Zejun , Zhu Jian , Dai Tianyuan , He Xiaolong , Liu Xinchao , Chang Yankui , Wang Linlin 
Published: April 2023

AbstractBackgroundTraditional methods of radiotherapy positioning have shortcomings such as fragile skin‐markers, additional doses, and lack of information integration. Emerging technologies may provide alternatives for the relevant clinical practice.PurposeTo propose a noninvasive radiotherapy positioning system integrating augmented reality (AR) and optical surface, and to evaluate its feasibility in clinical workflow.MethodsAR and structured light‐based surface were integrated to implement the coarse‐to‐precise positioning through two coherent steps, the AR‐based coarse guidance and the optical surface‐based precise verification. To implement quality assurance, recognition of face and pattern was used for patient authentication, case association, and accessory validation in AR scenes. The holographic images reconstructed from simulation computed tomography (CT) images, guided the initial posture correction by virtual‐real alignment. The point clouds of body surface were fused, with the calibration and pose estimation of structured light cameras, and segmented according to the preset regions of interest (ROIs). The global‐to‐local registration for cross‐source point clouds was achieved to calculate couch shifts in six degrees‐of‐freedom (DoF), which were ultimately transmitted to AR scenes. The evaluation based on phantom and human‐body (4 volunteers) included, (i) quality assurance workflow, (ii) errors of both steps and correlation analysis, (iii) receiver operating characteristic (ROC), (iv) distance characteristics of accuracy, and (v) clinical positioning efficiency.ResultsThe maximum errors in phantom evaluation were 3.4 ± 2.5 mm in Vrt and 1.4 ± 1.0° in Pitch for the coarse guidance step, while 1.6 ± 0.9 mm in Vrt and 0.6 ± 0.4° in Pitch for the precise verification step. The Pearson correlation coefficients between precise verification and cone beam CT (CBCT) results were distributed in the interval [0.81, 0.85]. In ROC analysis, the areas under the curve (AUC) were 0.87 and 0.89 for translation and rotation, respectively. In human body‐based evaluation, the errors of thorax and abdomen (T&A) were significantly greater than those of head and neck (H&N) in Vrt (2.6 ± 1.1 vs. 1.7 ± 0.8, p < 0.01), Lng (2.3 ± 1.1 vs. 1.4 ± 0.9, p < 0.01), and Rtn (0.8 ± 0.4 vs. 0.6 ± 0.3, p = 0.01) while relatively similar in Lat (1.8 ± 0.9 vs. 1.7 ± 0.8, p = 0.07). The translation displacement range, after coarse guidance step, required for high accuracy of the optical surface component of the integrated system was 0–42 mm, and the average positioning duration of the integrated system was significantly less than that of conventional workflow (355.7 ± 21.7 vs. 387.7 ± 26.6 s, p < 0.01).ConclusionsThe combination of AR and optical surface has utility and feasibility for patient positioning, in terms of both safety and accuracy.
Mechanical Properties and Blocking Resistance of Films Cast from Core–Shell Latex Particles
Authors: Perez Adrián , Kynaston Emily , Lindsay Christopher , Ballard Nicholas 
Published: April 2023

AbstractThe mechanical properties and blocking resistance of films cast from latex particles can be improved by addition of a reinforcing polymer of high modulus that acts as a “hard” phase. This work demonstrates that blocking resistance, a key performance parameter for use in coatings, of such films can be understood in terms of the relative contribution of the “hard” and “soft” components to the rheological properties of the material. In order to do so, representative latexes that contain a semicrystalline core of poly(stearyl acrylate) as a reinforcing phase and a shell of amorphous poly(styrene‐co‐butyl acrylate) are synthesized. By varying the composition of the amorphous phase (glass transition temperature, molar mass) and the relative amorphous/semicrystalline fraction, it is demonstrated that the improvement in blocking resistance is strongly correlated with the increase in the modulus of the material but is also affected by the dynamics of polymer diffusion of chains in the soft phase. This work allows to establish design rules for polymer and colloidal structures that can be targeted to maximize blocking resistance.
Reconstruct lower‐dimensional crack paths from phase‐field point cloud
Authors: Xu Yue , You Tao , Zhu Qizhi 
Published: April 2023

AbstractBecause of the smeared representation of phase‐field fracture, reconstructing lower‐dimensional crack paths is challenging, which may impede the further applications of the phase‐field method in the modeling of fault friction and fluid flow in fracture. In the present work, we propose to capture the crack curves or surfaces from two‐dimensional or three‐dimensional phase‐field point cloud using an optimized ridge regression algorithm, and k‐nearest neighbor and principal component analysis are used to estimate the normal direction of each segment on the identified discrete crack path. The sensitivity and computational efficiency of the proposed method are investigated thoroughly. Subsequently, this method is extended to reconstruct the complex discrete fracture networks. Finally, several benchmarks for fracture, fault friction and fluid flow problems are presented to demonstrate the strength of the proposed approach.
The experiences of patients with amyotrophic lateral sclerosis of their decision‐making processes to invasive home mechanical ventilation—A qualitative study
Authors: Thorborg Tina , Finderup Jeanette , Winther Dorte Skriver , Lorenzen Charlotte Kirkegaard , Dreyer Pia 
Published: April 2023

AbstractAimTo explore and gain knowledge of the experiences and needs among patients with amyotrophic lateral sclerosis (ALS) of their decision‐making processes whether to choose invasive home mechanical ventilation or not.DesignA qualitative study.MethodsA phenomenological‐hermeneutic approach influenced by Ricoeur's interpretation theory was used. Seven patients with ALS were interviewed. The Consolidated Criteria for Reporting Qualitative Research checklist was used for reporting.ResultsThree themes were evident in patients' accounts of the decision‐making process: (1) being taken care of directly after receiving the diagnosis, (2) living in uncertainty about what the future would bring and (3) doubt causing patients with ALS to change their minds. Patients with ALS were burdened with everyday life challenging decision‐making processes about future treatment and doubt caused patients to change their minds about their future treatment. It is necessary to support patients in their decision‐making processes using shared decision‐making.Patient or Public ContributionNo Patient or Public Contribution.
The Effect of Safety Net Generosity on Maternal Mental Health and Risky Health Behaviors
Authors: Schmidt Lucie , Shore‐Sheppard Lara , Watson Tara 
Published: April 2023

ABSTRACTSingle mothers are more likely to experience mental health problems and stress‐related negative health behaviors than their married counterparts, but a more generous safety net may improve these outcomes. We use a simulated safety net eligibility approach that accounts for interactions across safety net programs and relies on changing policies across states and time to identify causal effects of safety net generosity on psychological distress and risky behaviors of single mothers. Results suggest that a more generous safety net is protective of maternal mental health: a $1,000 increase to the simulated potential combined cash and food benefit package reduces severe psychological distress by 8.4 percent. Breaking out effects by individual programs while still controlling for potential benefits from other programs, we find protective effects of tax credits, cash benefits provided by Temporary Assistance for Needy Families, and food benefits provided by Supplemental Nutritional Assistance, but no effects of Medicaid eligibility. The effects are primarily driven by single mothers with the lowest levels of education. We find no significant effects of generosity on daily smoking, but we find evidence that benefits reduce the likelihood of heavy drinking. Results suggest that government investments in resources available to low‐income families can be effective at improving well‐being.
Dynamic viscoelastic behavior and interlaminar performance of glass/epoxy composites with binary nano‐fillers at different in‐situ elevated temperature environments
Authors: Shubham  , Prusty Rajesh Kumar , Ray Bankim Chandra 
Published: April 2023

AbstractFor commercial civil applications of laminated composite material, characterizations to forecast the interlaminar shear behavior and viscoelastic response across a wide temperature range are essential. In this study, the interlaminar shear strength (ILSS) of glass/epoxy (GE) composites dispersed with binary nanofillers nanosilica‐multilayer graphene (NS‐MLG) and nanosilica‐nanoclay (NS‐NC) was analyzed at an in‐situ testing temperature of 20, 70, and 110°C. Further, the viscoelastic property of the composites was studied using a dynamic mechanical thermal analyzer (DMTA) in the temperature range of 35–165°C. An increase in the ILSS value of around 9% and 10% was observed at room temperature for GE/MLG‐NS and GE/NC‐NS, respectively, compared to control GE composites. In contrast, the trend was seen to change at higher temperatures. There was a slight decrement in the storage modulus (E′) of GE/MLG‐NS and GE/NC‐NS composites in the glassy region compared to control GE composites. The mean Tg of the GE composite (control) was nearly 107.3°C when the E′ decline onset temperature was taken into account, but after the addition of MLG‐NS, it was 10.1°C below. The mean Tg of GE/NC‐NS was determined to be 106.3°C, and in the glass transition as well as rubbery regions, it was observed to compete with the E′ value of the control GE composites. Fractography was done using micrographs obtained from environmental scanning electron microscope (ESEM). Traces of polymeric material found at the fiber surface certified the improved interfacial adhesion between glass fiber and polymer in the matrix‐modified composite samples.
Bias in observational studies on the effectiveness of in hospital use of hydroxychloroquine in COVID‐19
Authors: Hempenius Mirjam , Bots Sophie H. , Groenwold Rolf H. H. , de Boer Anthonius , Klungel Olaf H. , Gardarsdottir Helga 
Published: April 2023

AbstractPurposeDuring the first waves of the coronavirus pandemic, evidence on potential effective treatments was urgently needed. Results from observational studies on the effectiveness of hydroxychloroquine (HCQ) were conflicting, potentially due to biases. We aimed to assess the quality of observational studies on HCQ and its relation to effect sizes.MethodsPubMed was searched on 15 March 2021 for observational studies on the effectiveness of in‐hospital use of HCQ in COVID‐19 patients, published between 01/01/2020 and 01/03/2021 on. Study quality was assessed using the ROBINS‐I tool. Association between study quality and study characteristics (journal ranking, publication date, and time between submission and publication) and differences between effects sizes found in observational studies compared to those found in RCTs, were assessed using Spearman's correlation.ResultsEighteen of the 33 (55%) included observational studies were scored as critical risk of bias, eleven (33%) as serious risk and only four (12%) as moderate risk of bias. Biases were most often scored as critical in the domains related to selection of participants (n = 13, 39%) and bias due to confounding (n = 8, 24%). There were no significant associations found between the study quality and the characteristics nor between the study quality and the effect estimates.DiscussionOverall, the quality of observational HCQ studies was heterogeneous. Synthesis of evidence of effectiveness of HCQ in COVID‐19 should focus on RCTs and carefully consider the added value and quality of observational evidence.
Improving learning science: Evaluating and comparing academic interventions using measures of learning speed
Authors: Skinner Christopher H. , Fowler Kristen , Cates Gary L. , Poncy Brain , Duhon Gary J. , Solomon Benjamin G. , Belfiore Phillip J. 
Published: April 2023

AbstractMeasures of learning speed (i.e., the amount of learning/cumulative time learner spends engaged in an intervention) are rarely included in research designed to evaluate and compare academic interventions. We build a case that includes analyses of learning speed metrics in academic intervention research can provide more useful information for prevention and remediation efforts, deter researchers from drawing misleading data‐based conclusions, and promote scientific parsimony. Research is reviewed where the same learning data is analyzed across different metrics (i.e., same amount of learning, different measurement scales) including learning per event, learning speed, and growth. Patterns are analyzed and examples are provided that demonstrate how altering metrics can influence relative effectiveness conclusions and applied recommendations when researchers compare two or more interventions, conduct component analysis or optimization studies, and apply meta‐analytic techniques. Opportunity costs for learners, educators, and learning scientists that may be caused by failure to measure learning speed are identified and analyzed. Our review and analyses support the conclusion that, in most instances, researchers can better inform prevention and remediation efforts by including precise measures of learning speed as dependent variables when they evaluate and compare interventions designed to enhance academic skills. Limitations and challenges associated with measuring learning speed are described and directions for future research are provided.
Perceived school climate and adolescent behaviors among Chinese adolescents: Mediating effect of social‐emotional learning competencies
Authors: Pan Yangu , Liang Shuang , Shek Daniel T. L. , Zhou Di , Lin Xueqin 
Published: April 2023

AbstractAlthough school climate plays an important role in the development of adolescent prosocial behaviors and problem behaviors, little is known about the mechanisms underlying school climate's impact on such behaviors, particularly in Chinese adolescents. This study used a multi‐informant approach to investigate the mediating role of social‐emotional learning (SEL) competencies on the association of school climate with prosocial behaviors and problem behaviors (i.e., internalizing and externalizing behaviors) among Chinese adolescents. A total of 699 students (Mage = 12.89 years, SD = 0.70) in 7th and 8th grades from three middle schools in Chengdu, China completed measures of perceived school climate and SEL competencies. Their guardians also completed ratings on adolescent prosocial and problem behaviors. As predicted, while perceived school climate was positively associated with adolescent prosocial behaviors, it was negatively related to adolescent internalizing and externalizing behaviors. Analyses using PROCESS further showed that SEL competencies mediated the relationship between perceived school climate and adolescent behaviors. The findings underscored the importance of promoting positive school climate as well as SEL competencies to foster positive adolescent development.
A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data
Authors: Cohen Shon , Schneidman‐Duhovny Dina 
Published: April 2023

AbstractMacromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. The integrative structure modeling approach characterizes multi‐subunit complexes by computational integration of data from fast and accessible experimental techniques. Crosslinking mass spectrometry is one such technique that provides spatial information about the proximity of crosslinked residues. One of the challenges in interpreting crosslinking datasets is designing a scoring function that, given a structure, can quantify how well it fits the data. Most approaches set an upper bound on the distance between Cα atoms of crosslinked residues and calculate a fraction of satisfied crosslinks. However, the distance spanned by the crosslinker greatly depends on the neighborhood of the crosslinked residues. Here, we design a deep learning model for predicting the optimal distance range for a crosslinked residue pair based on the structures of their neighborhoods. We find that our model can predict the distance range with the area under the receiver‐operator curve of 0.86 and 0.7 for intra‐ and inter‐protein crosslinks, respectively. Our deep scoring function can be used in a range of structure modeling applications.
Electronegative clusters modulate folding status and RNA binding of unstructured RNA‐binding proteins
Authors: Zaharias Steve , Fargason Talia , Greer Rory , Song Yuhua , Zhang Jun 
Published: April 2023

AbstractElectronegative clusters (ENCs) made up of acidic residues and/or phosphorylation sites are the most abundant repetitive sequences in RNA‐binding proteins. Previous studies have indicated that ENCs inhibit RNA binding for structured RNA‐binding domains (RBDs). However, this is not the case for the unstructured RBD in histone pre‐mRNA stem‐loop binding protein (SLBP). The SLBP RBD contains 70 amino acids and is followed by a phosphorylatable ENC. ENC phosphorylation increases RNA‐binding affinity of SLBP to the sub‐picomolar range. In this study, we use NMR and molecular dynamics simulations to elucidate the mechanism for this tight binding. Our NMR data demonstrate that the ENC transiently folds apo SLBP into an RNA‐bound resembling state. We find that in the RNA‐bound state, the phosphorylated ENC interacts with the loop region opposite to the RNA‐binding site. This allosteric interaction stabilizes the complex and therefore enhances RNA binding. To evaluate the generality of our findings, we graft an ENC onto endoribonuclease homolog 1's first double‐stranded RNA‐binding motif (DRBM1), an unstructured RBD that shares no homology with SLBP. We find that the engineered ENC increases the folded species of DRBM1 and inhibits RNA binding. On the contrary, introducing basic residues to DRBM1 makes the domain more unfolded, enhances RNA binding, and mitigates the inhibitory effect of the engineered ENC. In summary, our study suggests that ENCs promote folding of unstructured RNA‐binding domains, and their effects on RNA binding depend on the electropositive charges on the RBD surface.
Population PK/PD model of tacrolimus for exploring the relationship between accumulated exposure and quantitative scores in myasthenia gravis patients
Authors: Chen Di , Yao Qingyu , Chen Wenjun , Yin Jian , Hou Shifang , Tian Xiaoxin , Zhao Ming , Zhang Hua , Yang Liping , Zhou Tianyan , Jin Pengfei 
Published: April 2023

AbstractTacrolimus is an important immunosuppressant used in the treatment of myasthenia gravis (MG). However, the population pharmacokinetic (PK) characteristics together with the exposure‐response of tacrolimus in the treatment of MG remain largely unknown. In this study, we aimed to develop a population PK/pharmacodynamic (PK/PD) model of tacrolimus in patients with MG, in order to explore the relationships among tacrolimus dose, exposure, and its therapeutic efficacy. The genotype of CYP3A5, Osserman's classification, and status of thymus, as well as demographic characteristics and other biomarkers from laboratory testing were tested as covariate, and simulations were performed based on the final model. The population PK model was described using a one‐compartment model with first‐order elimination and fixed absorption parameters. CYP3A5 genotype significantly influenced the apparent clearance, and total protein (TP) influenced the apparent volume of distribution as covariates. The quantitative MG scores were characterized by the cumulated area under curve of tacrolimus in a maximum effect function. Osserman's classification was a significant covariate on the initial score of patients with MG. The simulations demonstrated that tacrolimus showed an unsatisfying effect possibly due to insufficient exposure in some patients with MG. A starting dose of 2 mg/d and even higher dose for patients with CYP3A5 *1/*1 and *1/*3 and lower TP level were required for the rapid action of tacrolimus. The population PK/PD model quantitatively described the relationships among tacrolimus dose, exposure, and therapeutic efficacy in patients with MG, which could provide reference for the optimization of tacrolimus dosing regimen at the individual patient level.