bluuebunny/crossref_metadata_2025_split huggingface dataset:
Can Enterprise Digital Transformation Improve Resource Allocation Efficiency? Evidence From China
Authors: Duan Zheng , Zhang Yifan 
Published: February 2025

ABSTRACTDigital transformation provides enterprises with the momentum for development. This study analyses a sample of Chinese listed companies from 2011 to 2021 to construct a digital transformation index and assess the resource allocation efficiency of the cities in which these companies operate. It empirically investigates the impact of digital transformation on resource allocation efficiency, while addressing issues of heterogeneity. The findings are as follows: (1) digital transformation enhances resource allocation efficiency; (2) it influences this efficiency by optimizing the structure of human capital, fostering enterprise innovation, and mitigating information asymmetries; and (3) the positive impact of digital transformation on resource allocation efficiency is more pronounced in regions with lower per capita income and smaller urban populations, as well as among high‐tech, manufacturing, and state‐owned enterprises in these areas. This study contributes to both theoretical and empirical research on resource allocation efficiency and offers a new perspective on digital transformation. It serves as a reference for policymakers in developing relevant digital policies based on regional contexts, provides a foundation for enterprises to expedite their digital transformation efforts, and establishes the groundwork for future research on the role of digital transformation in promoting development in both developed and developing countries.
Thermodynamics and kinetics of isothermal precipitation in magnesium alloys
Authors: Chen Hongcan , Sun Jingli , Yang Shenglan , Zhang Yu , Tang Kai , Zhang Chuan , Lu Yangfan , Luo Qun , Li Qian 
Published: February 2025

AbstractAs the lightest structural metal materials, Mg alloys are promising for wider applications but are limited by low strength and poor corrosion resistance. Precipitation is an effective way to improve the strength and other performance of Mg alloys. Facing the extremely complex precipitation process, the crystal structures of precipitates, precipitation sequence, and precipitation thermodynamic and kinetics behaviors have stimulated extensive research interests. Precipitation kinetics, which connects composition, aging processes, and precipitate microstructure, is pivotal in determining the performance of age‐hardening Mg alloys. Despite numerous studies on this topic, a comprehensive review remains absent. This work aims to bridge that gap by analyzing precipitation from thermodynamic and kinetic perspectives. Thermodynamically, the stability of precipitates, nucleation driving forces, and resistances of precipitation are discussed. Kinetically, the various kinetic theories including semi‐empirical models, mean‐field models, phase‐field model, and atomistic approaches and their applications in Mg alloys are systematically summarized. Among these, mean‐field models emerge as particularly promising for accurately predicting precipitation processes. Finally, the framework for property prediction based on precipitation kinetics is introduced to illustrating the role of integrated computational materials engineering (ICME) in designing advanced Mg alloys.
MAYA (Multiple ActivitY Analyzer): An Open Access Tool to Explore Structure‐Multiple Activity Relationships in the Chemical Universe
Authors: Espinoza‐Castañeda J. Israel , Medina‐Franco José L. 
Published: February 2025

AbstractHerein, we introduce MAYA (Multiple Activity Analyzer), a tool designed to automatically construct a chemical multiverse, generating multiple visualizations of chemical spaces of a compound data set described by structural descriptors of different nature such as Molecular ACCess Systems (MACCS) keys, extended connectivity fingerprints with different radius, molecular descriptors with pharmaceutical relevance, and bioactivity descriptors. These representations are integrated with various data visualization techniques for the automated analysis focused on structure ‐ multiple activity/property relationships, enabling analysis for various problems set in user‐friendly source software. The source code of MAYA is freely available on GitHub at https://github.com/IsrC11/MAYA.git.
A database of magnetic resonance imaging‐transcranial ultrasound co‐registration
Authors: Alizadeh Maryam , Collins D. Louis , Kersten‐Oertel Marta , Xiao Yiming 
Published: February 2025

AbstractPurposeAs a portable and cost‐effective imaging modality with better accessibility than Magnetic Resonance Imaging (MRI), transcranial sonography (TCS) has demonstrated its flexibility and potential utility in various clinical diagnostic applications, including Parkinson's disease and cerebrovascular conditions. To better understand the information in TCS for data analysis and acquisition, MRI can provide guidance for efficient imaging with neuronavigation systems and the confirmation of disease‐related abnormality. In these cases, MRI‐TCS co‐registration is crucial, but relevant public databases are scarce to help develop the related algorithms and software systems.Acquisition and validation methodsThis dataset comprises manually registered MRI and transcranial ultrasound volumes from eight healthy subjects. Three raters manually registered each subject's scans, based on visual inspection of image feature correspondence. Average transformation matrices were computed from all raters' alignments for each subject. Inter‐ and intra‐rater variability in the transformations conducted by raters are presented to validate the accuracy and consistency of manual registration. In addition, a population‐averaged MRI brain vascular atlas is provided to facilitate the development of computer‐assisted TCS acquisition software.Data format and usage notesThe dataset is provided in both NIFTI and MINC formats and is publicly available on the OSF data repository: https://osf.io/zdcjb/.Potential applicationsThis dataset provides the first public resource for the development and assessment of MRI‐TCS registration with manual ground truths, as well as resources for establishing neuronavigation software in data acquisition and analysis of TCS. These technical advancements could greatly boost TCS as an imaging tool for clinical applications in the diagnosis of neurological conditions such as Parkinson's disease and cerebrovascular disorders.
Pore‐Based Modeling of Hydraulic Conductivity Function of Unsaturated Rooted Soils
Authors: Wang Hao , Chen Rui , Leung Anthony Kwan , Garg Ankit , Jiang Zhenliang 
Published: February 2025

ABSTRACTMualem's approach has been widely used to predict hydraulic conductivity functions (HCFs) of bare soils if a soil water retention curve (SWRC) model is available. The assumption that Mualem's approach holds is that the distribution of soil pores is spatially completely random. Under this assumption, relative hydraulic conductivity (Kr) is determined by the continuance probability of water‐filled pores. However, this assumption is not valid for rooted soils, as root growth causes soil particle rearrangement, and thus soil pore rearrangement, altering the probability of pore connectivity. After reconsidering Mualem's assumption, this study attempts to develop a new approach for predicting HCF of rooted soils by modeling the root‐induced pore rearrangement and the resultant change in the continuance probability of water‐filled pores. Two approaches mentioned were incorporated with a root‐dependent SWRC model to express HCF as a function of matric suction. The proposed model was validated against nine sets of measured HCFs from published studies. It was found that the proposed model reduced the root mean square error (RMSE) of Kr and lg Kr by 33% and 53%, respectively, as compared to traditional Mualem's model. Physically, the model's effectiveness depended on soil texture and root type. In fine‐textured soils, roots were capable of displacing soil particles, thereby causing soil pore rearrangement. Also, coarse roots with high strength tend to alter pore distribution. After considering the effects of pore‐level root‐soil interaction on pore rearrangement, the proposed model provided a significant improvement in the prediction of HCF of unsaturated rooted soils.
Predictive Factors for Complete Response to Desmopressin Treatment in Children With Primary Monosymptomatic Nocturnal Enuresis
Authors: Ozgur Gunal , Sekerci Cagri Akin , Tanidir Yiloren , Tarcan Tufan , Yucel Selcuk 
Published: February 2025

ABSTRACTObjectivesPrimary monosymptomatic nocturnal enuresis (MNE) is a common problem in pediatric urology and desmopressin is the first‐line medical treatment. We aimed to evaluate the predictive factors of complete response to desmopressin and the effect of desmopressin on urinary electrolyte levels in children with primary MNE.MethodsChildren with MNE who were started on sublingual 120 mcg of desmopressin treatment included in the study. Children were evaluated by physical examination, urinalysis, voiding dysfunction symptom score, voiding diary and uroflowmetrics with postvoid residuals. 24‐h urine was collected for density and electrolyte measurements before and at the first and third months of treatment. The children were divided into two groups according to wetting episodes at the third month, as those with complete response to the treatment (group 1) and the others (resistant or partial‐response) (group 2).ResultsThirty‐four children (24 boys, 10 girls) were included in the study. Median age was 8 (5–15) years. There was no difference between the urinary density, sodium, potassium, and calcium values before and during treatment (first and third months) (p = 0.737, 0.549, 0.166, 0.386 respectively). The number of wet nights in a month and the number of wetting at a night were found as the predictive factors for complete response to desmopressin (p = 0.027, p = 0.003, respectively). The number of 17 wet nights per month was calculated as the optimized cut‐off point for predicting desmopressin treatment failure (p = 0.027, sensitivity = 92.3%, specificity = 47.6%, AUC [95%]: 0.729 [0.552–0.906]). Age, gender, family history, maximum voided volume in voiding diary (MVV)/expected bladder capacity (EBC) ratio, maximum bladder capacity (MBC)/EBC ratio and pretreatment urinary density, sodium, potassium, calcium levels could not predict complete response (p = 0.292, 0.051, 0.533, 0.552, 0.101, 0.570, 0.326, 0.735, 0.246 respectively).ConclusionsDesmopressin treatment had no effect on urine density and urinary sodium, potassium, calcium electrolytes similar to the literature. Urine density and electrolyte levels are not helpful in predicting desmopressin treatment response in enuretic children. Low frequency of wet nights (< 17) in a month and single bedwetting at a night are the significant factors to predict complete response to desmopressin treatment in children with primary MNE.Clinical Trial RegistrationThe study does not have a clinical trial registration number, because the study was not a randomized controlled trial and the data in the study were collected retrospectively.
Implications of human‐nature interactions for livelihoods and conservation in Kasungu, Malawi
Authors: Mandoloma Lessah , Clark Michael , Coad Lauren , Hughes Karl , MilnerGulland Eleanor Jane 
Published: February 2025

Abstract

Effective conservation strategies require a comprehensive understanding of human‐nature relationships, including the factors driving these interactions. Without this context, interventions risk being impractical or ineffective, potentially leaving both people and nature worse off.

We used mixed methods to understand human‐nature interactions in Kasungu, Malawi. We specifically examined people's use of natural resources and perceptions of wildlife conservation and their implications for livelihoods and conservation.

Over 90% of participants reported collecting natural resources such as firewood, grass, medicinal plants and fruits to support their livelihoods. While most resources were collected for household use, some served both income generation and domestic purposes. Kasungu National Park plays a critical role in providing resources, though harvesting is illegal, alongside neighbouring farms and community forests. Households near the park, women and those of lower economic status were more likely to rely on the park for resources. Additionally, crop and livestock loss experiences were linked to higher resource collection rates.

Participants generally expressed positive attitudes towards wildlife and conservation. However, certain factors including proximity to the park, women, food insecurity, and crop and livestock loss were linked to negative attitudes.

Our findings offer valuable insights for the design and implementation of conservation initiatives and policies, particularly in communities heavily dependent on natural resources for their livelihoods. Conservation programmes and policies around protected areas should capitalise on the existing positive attitudes towards nature by fostering better community engagement. Locally led, inclusive and nature‐positive programmes could simultaneously benefit conservation efforts and improve livelihoods.

Read the free Plain Language Summary for this article on the Journal blog.
Performance optimization and reliability analysis of CFRP adhesive‐rivet hybrid joint
Authors: Su Hailiang , Wei Zhenxiao , Deng Kaibiao , An Deng , He Yuyan 
Published: February 2025

AbstractThis study investigates the adhesive‐rivet hybrid joining technique between carbon fiber reinforced polymer (CFRP) laminates and aluminum alloy sheets, aiming to enhance connection performance in lightweight automotive structures. By employing a synergistic approach that integrates experimental and theoretical analyses, the research systematically examines the effects of lap length, adhesive layer thickness, and rivet length on joint performance. A regression model was developed to derive a second‐order response surface equation relevant to these variables. Comprehensive testing and high‐precision fitting analyses validate the model's robust predictive capabilities. Additionally, interaction analyses involving both single and dual factors were conducted to further confirm the model's reliability and generalizability. A surrogate model coupled with the elite non‐dominated sorting genetic algorithm (NSGA‐II) algorithm was employed for multi‐objective optimization, resulting in significant enhancements in both failure load and energy absorption values. Post‐optimization, the hybrid joint exhibited an 8.48% increase in failure load and a 14.22% improvement in energy absorption value compared to pre‐optimization levels. Experimental validation confirmed that the performance of the optimized joints fell within an acceptable error margin relative to the predictions. Reliability analysis, utilizing the Kriging model and the optimal Latin hypercube design method, demonstrated the high reliability of the optimized process. This analysis further validated the effectiveness of the optimized hybrid joints. This research provides both theoretical and practical insights into hybrid connections between CFRP and metal materials, thereby crucially improving the reliability of structural connections.Highlights
The impact of joint geometry on hybrid CFRP‐AL connection performance was studied.
Synergistic effects of lap length, adhesive layer thickness, and rivet length were identified.
Hybrid joint durability was improved and failure risks through optimization were reduced.
Optimized parameter interactions significantly improved joint reliability to 97.1%.
Optimized hybrid joints increased failure load by 8.48% and energy absorption value by 14.22%.
Differential lateralization to faces in infants at risk of autism spectrum disorder with expressive language delay
Authors: Araya Junko , Ikeda Takashi , Hasegawa Chiaki , Iwasaki Sumie , Yaoi Ken , Yoshimura Yuko 
Published: February 2025

AbstractAimFace‐to‐face communication between caregiver and infant is essential for the development of language and social skills in infancy. A previous study on brain response toward human faces showed that a lateralization right fusiform gyrus (FG) response when viewing faces was associated with better social skills. However, the relationship, between infant face processing and language development remains unclear. This study aimed to examine whether brain responses to faces vary based on the ability level of language expression.MethodsOverall, 42 Japanese infants (aged 18–34 months, Mean of age (Mage) = 24.7 months, standard deviation (SD) = 4.57, 47% female) were assessed for expressive communication skills and classified into two groups: a delayed group (20 infants) and a control group (infants with typical expressive language development, 22 infants). Brain activity was recorded using a child‐customized magnetoencephalography during presentation of a mother's face, a stranger's face, and a nonface (scrambled image). The lateralization index of the FG during face viewing was calculated using the following formula: (L − R)/(L + R).ResultsThe results showed a significant difference in the lateralization index between the delayed and control groups. The control group showed rightward dominance of the FG activity when viewing the mother's face and others' faces, whereas the delayed group did not exhibit this lateralization. Based on behavioral observations, 75% of the delayed group met the criteria of autism spectrum disorder (ASD) risk, and infants with a high risk of ASD who had poor expressive language showed poor right hemispheric dominance compared to the control group in their brain responses to their mothers' faces.ConclusionThis study suggests that lateralization of face processing in infancy may be a predictor of expressive language abilities.
4D‐printed TPU‐based magnetorheological elastomer using simplified feedstock preparation
Authors: Sukarman Ahmad Fitri , Mohd Yusuf Shahir , Mazlan Saiful Amri , Nordin Nur Azmah , Patel Dipalkumar M. , Johari Mohd Aidy Faizal , Lazim Nurul Hakimah , Kadir Khairul Anwar Abdul 
Published: February 2025

AbstractMagnetorheological elastomers (MRE) show promise in creating adaptive, multifunctional materials, especially with advances in 4D printing. Preparing MRE feedstock has typically involved complex processes and multiple thermal treatments, which can degrade material quality. This study simplifies feedstock preparation by using tetrahydrofuran (THF) as a solvent for fused granulate fabrication (FGF) 3D printing, ensuring uniform dispersion of carbonyl iron particles (CIP) in a thermoplastic polyurethane (TPU) matrix. Printed samples were characterized for thickness, diameter, and hardness, confirming dimensional consistency and increased stiffness with higher CIP content. Microstructural analysis revealed uniform CIP distribution, supporting consistent magnetorheological properties and performance integrity. The rheological properties under strain sweep of the samples were evaluated under varying magnetic fields, which showed a significant increase in storage modulus with increased field strength due to CIP alignment. Additional assessments of rheological properties under current sweep, including the absolute magnetorheological (MR) effect, demonstrated that higher CIP content enhanced the MR effect and sample stiffness. These results indicate that 4D‐printed MREs with simplified feedstock preparation offer tunable properties suitable for adaptive applications, such as soft robotics and vibration control. Integrating MRE with 4D printing advances the creation of magnetically responsive materials with programmable mechanical performance.Highlights
Simplification of the complex feedstock preparation process by introducing solvent casting.
Elimination of multiple thermal processing steps during feedstock preparation.
Achieving uniform carbonyl iron particle distribution within the 4D‐printed TPU matrix.
4D‐printed MRE exhibits similar trends in rheological properties as conventionally fabricated counterparts.
A Refined Score, Namely Thoracic Ultrasound Score, to Predict the Need for Surfactant in Preterm Neonates: A Prospective, Multicenter, Observational Study
Authors: Forcellini Carlo Alberto , Rossignoli Sara , Ficial Benjamim , Cenci Giorgia , Santoro Leonardo , Bonadies Luca , Franchetti Enrico , Vallortigara Francesca , Mardegan Veronica , Vecchiato Luca , Scollo Massimo , Zanetto Lorenzo , Vedovato Stefania , Tsatsaris Nicola , Cattarossi Luigi , Beghini Renzo , Pietrobelli Angelo 
Published: February 2025

ABSTRACTIntroductionLung ultrasound score (LUS) is used to predict the need for surfactant in preterm neonates. Its performance is lower in neonates with a gestational age (GA) ≥ 34 weeks. We developed a score, thoracic ultrasound score (TUS), to overcome the shortcomings of LUS.ObjectivesTo assess the feasibility and diagnostic accuracy of TUS to evaluate oxygenation and predict the need for surfactant administration, compared to LUS.Materials and MethodsThis was a prospective, multicenter, observational study. Preterm neonates in noninvasive ventilation with GA between 24 + 0 and 36 + 6 weeks were assessed for eligibility. Lung ultrasound were performed within 3 h of life, and TUS and LUS were calculated.ResultsFifty‐eight neonates who received surfactant were compared with 112 neonates who did not receive surfactant: GA 30.2 ± 3.1 weeks versus 32.6 ± 2.3 weeks, (p < 0.001), and birth weight 1466 ± 674 g versus 1725 ± 519 g, (p = 0.006), respectively. TUS and LUS showed a similar association with S/F ratio (r = −0.670 and r = 0.615) and OSI (r = 0.524 and r = 0.423), all p < 0.001. In neonates with GA < 34 weeks, the AUC (95% CI) was similar: 0.956 (0.923–0.989) versus 0.952 (0.921–0.984). In neonates with GA ≥ 34 weeks, the AUC (95% CI) of TUS was superior to LUS: 0.971 (0.914–1.000) versus 0.797 (0.639–0.980), p = 0.02.ConclusionCompared to LUS, TUS showed a similar association with the oxygenation status and a superior ability to predict the need for surfactant in neonates with GA ≥ 34 weeks. The latter was similar in neonates with GA < 34 weeks.