bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Anisotropic Thermal–Mechanical Coupling Failure Criterion for Slate
Authors: Weng Meng-Chia , Lin Shih-Shiang , Lee Chih-Shan , Wu Wei-Han , Li Jia Han , Liu Chih-Hsi 
Published: June 2024

AbstractThis study investigates the thermal–mechanical behavior of slates in geothermal reservoirs and establishes an anisotropic thermal–mechanical coupling failure criterion. Slate samples obtained from a geothermal site were subjected to a series of direct-shear and triaxial-compression tests at various confining pressures and temperatures. The results showed that the orientation angle within a specific range caused shear sliding failure of the slate, primarily due to foliation strength; beyond this range, intrinsic rock properties led to different failure modes. Elevated temperatures significantly diminished the strength anisotropy of the slate. These findings provided a foundation for the development of an anisotropic thermal–mechanical coupling failure criterion. The validity of the proposed criterion, which incorporates both the orientation angle and thermal degradation effects, was demonstrated through experimental results. A three-dimensional surface diagram was constructed to visualize the relationship between the temperature, orientation angle, and failure principal stress, highlighting the anisotropic thermal-degradation characteristics of the slate under varying confining pressures. This study enhances the understanding of the thermal–mechanical behavior of these materials in geothermal reservoirs.
Identification and characterization of two Bacillus anthracis bacteriophages
Authors: Li Lun , Zhang Huijuan , Jin Haixiao , Guo Jin , Liu Pan , Yang Jiao , Wang Zijian , Zhang Enmin , Yu Binbin , Shi Liyuan , He Jinrong , Wang Peng , Wei Jianchun , Zhong Youhong , Li Wei 
Published: June 2024

AbstractAnthrax is an acute infectious zoonotic disease caused by Bacillus anthracis, a bacterium that is considered a potential biological warfare agent. Bacillus bacteriophages shape the composition and evolution of bacterial communities in nature and therefore have important roles in the ecosystem community. B. anthracis phages are not only used in etiological diagnostics but also have promising prospects in clinical therapeutics or for disinfection in anthrax outbreaks. In this study, two temperate B. anthracis phages, vB_BanS_A16R1 (A16R1) and vB_BanS_A16R4 (A16R4), were isolated and showed siphovirus-like morphological characteristics. Genome sequencing showed that the genomes of phages A16R1 and A16R4 are 36,569 bp and 40,059 bp in length, respectively. A16R1 belongs to the genus Wbetavirus, while A16R4 belongs to the genus Hubeivirus and is the first phage of that genus found to lyse B. anthracis. Because these two phages can comparatively specifically lyse B. anthracis, they could be used as alternative diagnostic tools for identification of B. anthracis infections.
A history of depression and prenatal depression are associated with a lower likelihood of breastfeeding initiation and maintenance, and more breastfeeding problems
Authors: Braithwaite Elizabeth C. , Oftedal Aurora , Kaasen Anne , Ayorech Ziada , Bekkhus Mona 
Published: June 2024

Abstract

Purpose
This study tests the hypotheses that lifetime history of depression, and prenatal depression, are associated with a reduced likelihood of breastfeeding initiation (giving the baby any breastmilk during the first week of life) and breastfeeding maintenance (giving the baby breastmilk for at least 6 months), and a greater likelihood of reporting breastfeeding problems.

Methods
We analyzed data from the Norwegian Mother, Father, and Child cohort study (MoBa), N = 78,307. Mothers reported a lifetime history of depression during the second trimester of pregnancy, and current symptoms of depression during the third trimester using the Hopkins Symptoms Checklist short version (SCL-8). At six months postpartum, mothers self-reported breastfeeding initiation, maintenance, and difficulties.

Results
Using binary logistic regression analyses, we report that a lifetime history of depression is associated with a lower likelihood of breastfeeding initiation (OR = 0.751, 95%CI = 0.650–0.938), breastfeeding maintenance (OR = 0.712, 95%CI = 0.669–0.785), and a greater likelihood of breastfeeding difficulties (OR = 1.86, 95%CI = 1.72–2.06). Similarly, prenatal depression was associated with a lower likelihood of breastfeeding initiation (OR = 0.904, 95%CI = 0.878–0.929), breastfeeding maintenance (OR = 0.929, 95%CI = 0.920–0.938), and a greater likelihood of breastfeeding difficulties (OR = 1.10, 95%CI = 1.09–1.12). Results remained largely unchanged when covaried for several confounding variables, including medication use.

Conclusion
We provide novel evidence that pre-conception and prenatal symptoms of depression are associated with breastfeeding outcomes. This information could be used to identify women very early in pregnancy who may need additional support with breastfeeding. There is also a need to fully understand the biopsychosocial mechanisms that mediate the relationship between depression prior to birth and breastfeeding outcomes.
Significance of Dynamic Axial Stretching on Estimating Biomechanical Behavior and Properties of the Human Ascending Aorta
Authors: Parikh Shaiv , Giudici Alessandro , Huberts Wouter , Delhaas Tammo , Bidar Elham , Spronck Bart , Reesink Koen 
Published: June 2024

AbstractContrary to most vessels, the ascending thoracic aorta (ATA) not only distends but also elongates in the axial direction. The purpose of this study is to investigate the biomechanical behavior of the ascending thoracic aorta (ATA) in response to dynamic axial stretching during the cardiac cycle. In addition, the implications of neglecting this dynamic axial stretching when estimating the constitutive model parameters of the ATA are investigated. The investigations were performed through in silico simulations by assuming a Gasser–Ogden–Holzapfel (GOH) constitutive model representative of ATA tissue material. The GOH model parameters were obtained from biaxial tests performed on four human ATA tissues in a previous study. Pressure–diameter curves were simulated as synthetic data to assess the effect of neglecting dynamic axial stretching on estimating constitutive model parameters. Our findings reveal a significant increase in axial stress (~ 16%) and stored strain energy (~ 18%) in the vessel when dynamic axial stretching is considered, as opposed to assuming a fixed axial stretch. All but one artery showed increased volume compliance while considering a dynamic axial stretching condition. Furthermore, we observe a notable difference in the estimated constitutive model parameters when dynamic axial stretching of the ATA is neglected, compared to the ground truth model parameters. These results underscore the critical importance of accounting for axial deformations when conducting in vivo biomechanical characterization of the ascending thoracic aorta.
A hierarchical Bayesian model to monitor pelagic larvae in response to environmental changes
Authors: Granata Alessia , Abbruzzo Antonino , Patti Bernardo , Cuttitta Angela , Torri Marco 
Published: June 2024

AbstractEuropean anchovies and round sardinella play a crucial role, both ecological and commercial, in the Mediterranean Sea. In this paper, we investigate the distribution of their larval stages by analyzing a dataset collected over time (1998–2016) and spaced along the area of the Strait of Sicily. Environmental factors are also integrated. We employ a hierarchical spatio-temporal Bayesian model and approximate the spatial field by a Gaussian Markov Random Field to reduce the computation effort using the Stochastic Partial Differential Equation method. Furthermore, the Integrated Nested Laplace Approximation is used for the posterior distributions of model parameters. Moreover, we propose an index that enables the temporal evaluation of species abundance by using an abundance aggregation within a spatially confined area. This index is derived through Monte Carlo sampling from the approximate posterior distribution of the fitted models. Model results suggest a strong relationship between sea currents’ directions and the distribution of larval European anchovies. For round sardinella, the analysis indicates increased sensitivity to warmer ocean conditions. The index suggests no clear overall trend over the years.
Examining chronic kidney disease screening frequency among diabetics: a POMDP approach
Authors: Wu Chou-Chun , Cao Yiwen , Suen Sze-chuan , Lin Eugene 
Published: June 2024

AbstractForty percent of diabetics will develop chronic kidney disease (CKD) in their lifetimes. However, as many as 50% of these CKD cases may go undiagnosed. We developed screening recommendations stratified by age and previous test history for individuals with diagnosed diabetes and unknown proteinuria status by race and gender groups. To do this, we used a Partially Observed Markov Decision Process (POMDP) to identify whether a patient should be screened at every three-month interval from ages 30-85. Model inputs were drawn from nationally-representative datasets, the medical literature, and a microsimulation that integrates this information into group-specific disease progression rates. We implement the POMDP solution policy in the microsimulation to understand how this policy may impact health outcomes and generate an easily-implementable, non-belief-based approximate policy for easier clinical interpretability. We found that the status quo policy, which is to screen annually for all ages and races, is suboptimal for maximizing expected discounted future net monetary benefits (NMB). The POMDP policy suggests more frequent screening after age 40 in all race and gender groups, with screenings 2-4 times a year for ages 61-70. Black individuals are recommended for screening more frequently than their White counterparts. This policy would increase NMB from the status quo policy between $1,000 to $8,000 per diabetic patient at a willingness-to-pay of $150,000 per quality-adjusted life year (QALY).
‘If I Don’t Have My Support Worker in the Room…’: A Multi-perspective Mixed Methods Study of Remote Daily Living Support for Neurodivergent Young Adults
Authors: Löthberg Maria , Wirström Eda , Meyer Jenny , Girdler Sonya , Bölte Sven , Jonsson Ulf 
Published: June 2024

Abstract
Purpose
Information technology is increasingly being employed for providing support and interventions in disability and health service contexts. This study aimed to investigate service users’ and support workers’ perspectives on remote support in daily living for young adults with neurodevelopmental conditions.

Methods
Using a convergent mixed methods approach, we integrated qualitative and quantitative findings from survey responses and focus groups. Young service users (aged 18 to 29) diagnosed with ADHD and/or autism (n = 35) and support workers (n = 64) from four municipalities in Sweden responded to a survey designed to tap into their lived experiences and views. The topic was explored further in focus groups with young service users (n = 7) and support workers (n = 3). Open-ended survey questions were analyzed using qualitative content analyses and complemented with information from the focus groups, while closed survey questions were summarized descriptively. Inferences were merged in a joint display.

Results
While participants reported having access to digital devices, service routines for remote contact were not in place. Service users were more hesitant than support workers in endorsing remote support, expressing concerns that this approach would be inferior to in-person support (e.g., owing to miscommunications and insufficient social and emotional contact). Still, both groups expressed that remote contact may at times be a beneficial complement to in-person meetings, increasing accessibility and user choice.

Conclusion
Service providers planning to implement remote support elements should explore the demand, acceptability, and organizational readiness for this approach. Moving forward, user engagement will be crucial to meet individual preferences, values, and needs.
Co-relation between Rietveld analysis, dielectric studies and impedance spectroscopy of the Ba1−xSrxTiO3 ceramics
Authors: Devi Sheela , Chaudhary Shristi , Hashim Mohd. , Batoo Khalid Mujasam , Hadi Muhammad , Shirsath Sagar E. 
Published: June 2024

AbstractBarium strontium titanate (BST), with varying Sr doping levels (x = 0, 0.05, 0.075, 0.1, 0.15, 0.3), was successfully synthesized using the solid-state reaction technique. The aim was to investigate the microstructural, dielectric, and impedance properties as Sr doping increases. X-ray diffraction analysis revealed a tetragonal phase structure for these materials, belonging to the P4mm space group, confirmed via Rietveld refinement using the Fullprof suite. SEM analysis indicated the decrement in grain sizes ranging from 0.198 to 0.0582 μm as doping concentration increases. The temperature and frequency dependencies of the dielectric constant were examined, with the Curie temperature observed in the range of 295 to 351 K with decreasing trend with substitution of strontium in pure barium titanate, showing an increase in dielectric constant with rising temperatures and non-relaxor behavior. P–E loops of BST samples illustrated bulk ferroelectric behavior, with maximum values of retentivity and coercivity reaching 1.56 and 13.97, respectively, in the highly doped BST sample. Various analytical techniques, including Nyquist plots, real and imaginary components of impedance, conductivity measurements, modulus formalism, and determination of charge carrier activation energy, were employed to elucidate the relationships between microstructure and electrical properties. Temperature-dependent resistivity demonstrated the negative temperature coefficient of resistance (NTCR) behavior in Sr-doped barium titanate. Impedance studies revealed semicircular arcs in Nyquist plots, indicating contributions from both grains and grain boundaries. The formation of well-defined grains in the BST samples was further confirmed through modulus spectroscopy.
White matter connectivity and social functioning in survivors of pediatric brain tumor
Authors: Hocking Matthew C. , Schultz Robert T. , Yerys Benjamin E. , Minturn Jane E. , Fantozzi Peter , Herrington John D. 
Published: June 2024

Abstract
Objective
Survivors of pediatric brain tumors (SPBT) are at risk for social deficits, fewer friendships, and poor peer relations. SPBT also experience reduced brain connectivity via microstructural disruptions to white matter from neurological insults. Research with other populations implicates white matter connectivity as a key contributor to poor social functioning. This case-controlled diffusion-weighted imaging study evaluated structural connectivity in SPBT and typically developing controls (TDC) and associations between metrics of connectivity and social functioning.

Methods
Diffusion weighted-imaging results from 19 SPBT and 19 TDC were analyzed using probabilistic white matter tractography. Survivors were at least 5 years post-diagnosis and 2 years off treatment. Graph theory statistics measured group differences across several connectivity metrics, including average strength, global efficiency, assortativity, clustering coefficient, modularity, and betweenness centrality. Analyses also evaluated the effects of neurological risk on connectivity among SPBT. Correlational analyses evaluated associations between connectivity and indices of social behavior.

Results
SPBT demonstrated reduced global connectivity compared to TDC. Several medical factors (e.g., chemotherapy, recurrence, multimodal therapy) were related to decreased connectivity across metrics of integration (e.g., average strength, global efficiency) in SPBT. Connectivity metrics were related to peer relationship quality and social challenges in the SPBT group and to social challenges in the total sample.

Conclusions
Microstructural white matter connectivity is diminished in SPBT and related to neurological risk and peer relationship quality. Additional neuroimaging research is needed to evaluate associations between brain connectivity metrics and social functioning in SPBT.
Defoliation modifies the impact of drought on the transfer of recent plant-assimilated carbon to soil and arbuscular mycorrhizal fungi
Authors: Xu Tianyang , Johnson David , Bardgett Richard D. 
Published: June 2024

Abstract
Aims
The allocation of recent plant photosynthates to soil via arbuscular mycorrhizal (AM) fungi is a critical process driving multiple ecosystem functions in grasslands. Yet, our understanding of how defoliation modifies below-ground allocation of recent plant photosynthate and its response to drought, which is becoming more intense and frequent, remains unresolved.

Methods
Here we undertook a 13C pulse-labelling experiment in a mesotrophic temperate grassland to evaluate in situ how defoliation intensity modifies the transfer of recently assimilated 13C from plant shoots to roots, extraradical AM fungal hyphae, soil, and 13C-CO2 efflux (soil respiration) in response to simulated drought.

Results
We found that, individually, both defoliation and drought reduced initial plant 13C uptake, but when defoliation and drought were combined, we detected a significant reduction in below-ground 13C allocation to soil. Furthermore, while defoliation stimulated 13C transfer to plant roots and soil, high intensity defoliation amplified 13C-CO2 efflux relative to the amount of 13C taken up by plants. Drought stimulated 13C transfer to fungal hyphae relative to initial plant uptake. High intensity defoliation, however, suppressed both 13C enrichment of extraradical AM fungal hyphae and 13C transfer to fungal hyphae relative to initial uptake.

Conclusions
Our findings suggest that defoliation can reduce the transfer of recent photosynthate below-ground under simulated drought and provide new insights into how defoliation may influence grassland C allocation dynamics and cycling between plants and AM fungi in grasslands facing drought.
Social learning in models and minds
Authors: Yon Daniel , Heyes Cecilia 
Published: June 2024

AbstractAfter more than a century in which social learning was blackboxed by evolutionary biologists, psychologists and economists, there is now a thriving industry in cognitive neuroscience producing computational models of learning from and about other agents. This is a hugely positive development. The tools of computational cognitive neuroscience are rigorous and precise. They have the potential to prise open the black box. However, we argue that, from the perspective of a scientific realist, these tools are not yet being applied in an optimal way. To fulfil their potential, the shiny new methods of cognitive neuroscience need to be better coordinated with old-fashioned, contrastive experimental designs. Inferences from model complexity to cognitive complexity, of the kind made by those who favour lean interpretations of behaviour (‘associationists’), require social learning to be tested in challenging task environments. Inferences from cognitive complexity to social specificity, made by those who favour rich interpretations (‘mentalists’), call for non-social control experiments. A parsimonious model that fits current data is a good start, but carefully designed experiments are needed to distinguish models that tell us how social learning could be done from those that tell us how it is really done.
Development of simplified probabilistic models for predicting phytoextraction timeframes of soil contaminants: demonstration at the DDX-contaminated Kolleberga tree nursery in Sweden
Authors: Drenning Paul , Enell Anja , Kleja Dan Berggren , Volchko Yevheniya , Norrman Jenny 
Published: June 2024

AbstractPhytoextraction, utilizing plants to remove soil contaminants, is a promising approach for environmental remediation but its application is often limited due to the long time requirements. This study aims to develop simplified and user-friendly probabilistic models to estimate the time required for phytoextraction of contaminants while considering uncertainties. More specifically we: i) developed probabilistic models for time estimation, ii) applied these models using site-specific data from a field experiment testing pumpkin (Cucurbita pepo ssp. pepo cv. Howden) for phytoextraction of DDT and its metabolites (ΣDDX), iii) compared timeframes derived from site-specific data with literature-derived estimates, and iv) investigated model sensitivity and uncertainties through various modelling scenarios. The models indicate that phytoextraction with pumpkin to reduce the initial total concentration of ΣDDX in the soil (10 mg/kg dw) to acceptable levels (1 mg/kg dw) at the test site is infeasible within a reasonable timeframe, with time estimates ranging from 48–123 years based on literature data or 3 570–9 120 years with site-specific data using the linear or first-order exponential model, respectively. Our results suggest that phytoextraction may only be feasible at lower initial ΣDDX concentrations (< 5 mg/kg dw) for soil polishing and that alternative phytomanagement strategies should be considered for this test site to manage the bioavailable fraction of DDX in the soil. The simplified modes presented can be useful tools in the communication with site owners and stakeholders about time approximations for planning phytoextraction interventions, thereby improving the decision basis for phytomanagement of contaminated sites.
Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue
Authors: Ngo Austin , Hernandez Kristen , Olatunde Ayorinde E. , Ciardi Thomas G. , Harding Alex , Nihar Arafath , Mondal Anirban , French Roger H. , Bruckman Laura S. , Lewandowski John J. 
Published: June 2024

AbstractFatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.