bluuebunny/crossref_metadata_2025_split huggingface dataset:
The work–recovery cycle of kidney strain and inflammation in sugarcane workers following repeat heat exposure at work and at home
Authors: Lucas Rebekah A. I. , Hansson Erik , Skinner Bethany D. , Arias-Monge Esteban , Wesseling Catharina , Ekström Ulf , Weiss Ilana , Castellón Zoey E. , Poveda Scarlette , Cerda-Granados Fatima I. , Martinez-Cuadra William Jose , Glaser Jason , Wegman David H. , Jakobsson Kristina 
Published: October 2024

Abstract
Purpose
To examine heat exposure at work and home and the work–recovery cycle and temporal variation of kidney strain, muscle injury and inflammation biomarkers in sugarcane workers.

Methods
20 male sugarcane workers (age: 33 ± 7 years) with a workplace Rest.Shade.Hydration (RSH) intervention were observed over 4 days, at the end (18 h post-shift recovery) and beginning of a work week (42 h post-shift recovery). Measures included work intensity (heart rate), gastro-intestinal temperature, estimated body core temperature (using heart rate), fluid consumption, pre- and post-work blood and urine samples, physical activity (accelerometery) away from work, plus ambient heat exposure at work and home.

Results
On workdays, workers awakened at approx. 02:40 after 5 h sleep in ~ 30 °C. Across work shifts, daily average WBGT ranged from 26 to 29 °C (cooler than normal) and average workload intensity ranged from 55 to 58%HRmax. Workers reported consuming ~ 8 L of water and ~ 4 × 300 mL bags of electrolyte fluid each day. Serum creatinine, cystatin C and creatine phosphokinase markedly increased post-work and decreased during recovery; serum potassium did the opposite (all p < 0.01). Biomarker concentration changes were similar between recovery periods (18 h vs. 42 h; all p > 0.27). C-reactive protein was the highest at the end of the work week (p = 0.01).

Conclusion
Despite RSH intervention, cross-shift kidney strain was marked (recovering overnight) and systemic inflammation increased over the work week. Thus, biomonitoring of kidney function in occupational populations should be performed before a work shift at any point in the work week. This is essential knowledge for field studies and surveillance.
Neuromuscular characteristics of eccentric, concentric and isometric contractions of the knee extensors
Authors: Ruas Cassio V. , Taylor Janet L. , Latella Christopher , Haff G. Gregory , Nosaka Kazunori 
Published: October 2024

Abstract
Purpose
We compared voluntary drive and corticospinal responses during eccentric (ECC), isometric (ISOM) and concentric (CON) muscle contractions to shed light on neurophysiological mechanisms underpinning the lower voluntary drive in a greater force production in ECC than other contractions.

Methods
Sixteen participants (20–33 years) performed ISOM and isokinetic (30°/s) CON and ECC knee extensor contractions (110°–40° knee flexion) in which electromyographic activity (EMG) was recorded from vastus lateralis. Voluntary activation (VA) was measured during ISOM, CON and ECC maximal voluntary contractions (MVCs). Transcranial magnetic stimulation elicited motor-evoked potentials (MEPs) and corticospinal silent periods (CSP) during MVCs and submaximal (30%) contractions, and short-interval intracortical inhibition (SICI) in submaximal contractions.

Results
MVC torque was greater (P < 0.01) during ECC (302.6 ± 90.0 Nm) than ISOM (269.8 ± 81.5 Nm) and CON (235.4 ± 78.6 Nm), but VA was lower (P < 0.01) for ECC (68.4 ± 14.9%) than ISOM (78.3 ± 13.1%) and CON (80.7 ± 15.4%). In addition, EMG/torque was lower (P < 0.02) for ECC (1.9 ± 1.1 μV.Nm−1) than ISOM (2.2 ± 1.2 μV.Nm−1) and CON (2.7 ± 1.6 μV.Nm−1), CSP was shorter (p < 0.04) for ECC (0.097 ± 0.03 s) than ISOM (0.109 ± 0.02 s) and CON (0.109 ± 0.03 s), and MEP amplitude was lower (P < 0.01) for ECC (3.46 ± 1.67 mV) than ISOM (4.21 ± 2.33 mV) and CON (4.01 ± 2.06 mV). Similar results were found for EMG/torque and CSP during 30% contractions, but MEP and SICI showed no differences among contractions (p > 0.05).

Conclusions
The lower voluntary drive indicated by reduced VA during ECC may be partly explained by lower corticospinal excitability, while the shorter CSP may reflect extra muscle spindle excitation of the motoneurons from vastus lateralis muscle lengthening.
GLP-1 receptor agonists are a transformative prehabilitation tool for weight loss in obese patients undergoing elective hernia repair
Authors: Spurzem Graham J. , Broderick Ryan C. , Ruiz-Cota Patricia , Hollandsworth Hannah M. , Sandler Bryan J. , Horgan Santiago , Grunvald Eduardo , Jacobsen Garth R. 
Published: October 2024

Abstract
Background
Obesity is an independent risk factor for complications after abdominal hernia repair. Glucagon-like-peptide-1 (GLP-1) receptor agonists are gaining popularity as pharmacologic weight loss adjuncts and may help patients reach weight loss goals for surgery. We examine our early experience utilizing GLP-1 agonists versus lifestyle modifications alone to achieve weight loss in patients before elective hernia repair.

Methods
This single-center, retrospective review identified obese patients who underwent elective hernia repair from 2014 to 2023. Patients were asked to achieve a BMI ≤ 33 kg/m2 before surgery. Patients who lost weight with GLP-1 therapy in addition to lifestyle changes were compared to a control cohort that achieved similar preoperative weight loss without GLP-1 therapy. Primary outcome was mean time from GLP-1 agonist initiation and initial surgery clinic visit to surgery. Secondary outcomes were 30-day morbidity, mortality, and reoperation rates, and hernia recurrence.

Results
Forty-six patients with ventral/incisional, flank, umbilical, parastomal, inguinal, and hiatal hernias were identified (GLP-1 N = 24, control N = 22). 81.8% (N = 18) of controls had a ventral/incisional hernia, compared to 45.8% (N = 11) of GLP-1 patients (p = 0.03). Mean BMI at GLP-1 agonist initiation was similar to mean BMI at initial clinic visit for controls (38.1 ± 4.9 vs 38.2 ± 2.7 kg/m2, p = 0.66). Preoperative mean percentage total weight loss (14.9 ± 7.5 vs 12.4 ± 6.9 kg, p = 0.39) and mean BMI reduction (6.0 ± 3.8 vs 4.9 ± 2.3 kg/m2, p = 0.43) were similar between groups. The mean time from GLP-1 agonist initiation to surgery was significantly shorter than initial clinic visit to surgery for controls (6.3 ± 4.0 vs 14.7 ± 17.6 months, p = 0.03). There was no statistically significant difference in time from initial clinic visit to surgery between groups (7.6 ± 4.4 vs 14.7 ± 17.6 months, p = 0.06). There was no significant difference in 30-day morbidity between groups (8.3 vs 27.3%, p = 0.13).

Conclusion
GLP-1 agonists accelerate preoperative weight loss for obese hernia patients without negatively impacting postoperative outcomes.
Multi-hierarchical surrogate learning for explicit structural dynamical systems using graph convolutional neural networks
Authors: Kneifl Jonas , Fehr Jörg , Brunton Steven L. , Kutz J. Nathan 
Published: October 2024

Abstract
Highly nonlinear dynamic finite element simulations using explicit time integration are particularly valuable tools for structural analysis in fields like automotive, aerospace, and civil engineering, or in the study of injury biomechanics. However, such state-of-the-art simulation models demand significant computational resources. Conventional data-driven surrogate modeling approaches address this by evolving the dynamics on low-dimensional embeddings, yet the majority of them operate directly on high-resolution data obtained from numerical discretizations, making them costly and unsuitable for adaptive resolutions or for handling information flow over large spatial distances. We therefore propose a multi-hierarchical framework for the structured creation of a series of surrogate models at different resolutions. Macroscale features are captured on coarse surrogates, while microscale effects are resolved on finer ones, while leveraging transfer learning to pass information between scales. The objective of this study is to develop efficient surrogates for a kart frame model in a frontal impact scenario. To achieve this, its mesh is simplified to obtain multi-resolution representations of the kart. Subsequently, a graph-convolutional neural network-based surrogate learns parameter-dependent low-dimensional latent dynamics on the coarsest representation. Following surrogates are trained on residuals using finer resolutions, allowing for multiple surrogates with varying hardware requirements and increasing accuracy.
From process to property: multi-physics modeling of dislocation dynamics and microscale damage in metal additive manufacturing
Authors: Hu Daijun , Grilli Nicolò , Yan Wentao 
Published: October 2024

AbstractMetal additive manufacturing (AM) has the potential to tailor the mechanical performance of materials. Due to the complex thermal history and unique microstructure, AM materials are reported to contain distinct dislocation networks with a high dislocation density, which affect the plastic deformation behavior and fracture. However, it is challenging to experimentally observe the formation of such dislocation structures. In this work, a multi-scale multi-physics crystal plasticity modeling framework that integrates the process-structure-property relationship in metal AM is developed. The temperature field obtained from thermal-fluid flow simulations of the AM process and the microstructure from the phase field model of grain growth are combined into thermo-mechanical crystal plasticity simulations to obtain grain-scale thermal stresses. These stresses are used as input to simulate the evolution of dislocation structures within individual grains. Taking AM 316L stainless steel as the material of interest, the effect of initial dislocation configuration on the slip plane and cross-slip mechanism on the dislocation structure formation are investigated. Furthermore, a phase field damage model is implemented to study the initiation of microscale damage and their relationship with dislocation structures, which is a main novelty of this work. This modeling framework provides comprehensive simulations of all aspects of metal AM and offers insights into the dislocation mechanisms and damage formation at microscale in AM materials, which could be used to guide the manipulation of the mechanical properties of AM materials.
RSDiff: remote sensing image generation from text using diffusion model
Authors: Sebaq Ahmad , ElHelw Mohamed 
Published: October 2024

AbstractThe generation and enhancement of satellite imagery are critical in remote sensing, requiring high-quality, detailed images for accurate analysis. This research introduces a two-stage diffusion model methodology for synthesizing high-resolution satellite images from textual prompts. The pipeline comprises a low-resolution diffusion model (LRDM) that generates initial images based on text inputs and a super-resolution diffusion model (SRDM) that refines these images into high-resolution outputs. The LRDM merges text and image embeddings within a shared latent space, capturing essential scene content and structure. The SRDM then enhances these images, focusing on spatial features and visual clarity. Experiments conducted using the Remote Sensing Image Captioning Dataset demonstrate that our method outperforms existing models, producing satellite images with accurate geographical details and improved spatial resolution.
Group activity recognition using unreliable tracked pose
Authors: Thilakarathne Haritha , Nibali Aiden , He Zhen , Morgan Stuart 
Published: October 2024

AbstractGroup activity recognition in video is a complex task due to the need for a model to recognise the actions of all individuals in the video and their complex interactions. Recent studies propose that optimal performance is achieved by individually tracking each person and subsequently inputting the sequence of poses or cropped images/optical flow into a model. This helps the model to recognise what actions each person is performing before they are merged to arrive at the group action class. However, all previous models rely highly on high-quality tracking and have only been evaluated using ground truth tracking information. In practice, achieving highly reliable tracking information for all individuals in a group activity video is almost impossible. We introduce an innovative deep learning-based group activity recognition approach called Rendered Pose-based Group Activity Recognition System (RePGARS), designed to tolerate unreliable tracking and pose information. Experimental results confirm that RePGARS outperforms all existing group activity recognition algorithms tested, which do not use ground truth detection and tracking information.
Assessing the impact of climate change on spring discharge using hydrological modelling in Musanze District, Rwanda
Authors: Muhumure Joseph , Pohl Eric , Schulz Stephan 
Published: October 2024

AbstractClimate change has far-reaching impacts on water availability globally, with changing precipitation patterns and global warming contributing to increasing scarcity and unreliability of spring water in many regions. Despite this understanding, the implication of climate change on the hydrological system remains limited in certain areas, including the district of Musanze, Rwanda. This study investigates the effects of climate change on the discharge of 14 springs in Musanze using the hydrological model V2Karst. CORDEX data from two global climate models of CMIP5 are used to simulate the future spring discharges over the period 2021–2100. The results reveal significantly higher annual discharges in the RCP2.6 scenario compared to the RCP8.5 for all springs from 2021 to 2100. Nevertheless, no significant long-term trend in spring discharge is observed between the early (2021–2050) and late (2071–2100) periods. However, the intra-annual temporal discharge patterns are changing with a significant increase in the seasonality index for the RCP8.5 scenario towards the end of the twenty-first century. Additionally, for both RCPs, there is a notable increase in the number of days with discharges below 40% of the mean of annual discharges during the baseline period. The overall findings of this study suggest that climate change significantly impacts the future evolution of spring discharges in Musanze, indicating potential risks to the future availability of water in the region.
Identifying the number of latent factors of stochastic volatility models
Authors: Allaj Erindi , Mancino Maria Elvira , Sanfelici Simona 
Published: October 2024

AbstractWe provide a procedure to identify the number of latent factors of stochastic volatility models. The methodology relies on the non-parametric Fourier estimation method introduced by Malliavin and Mancino (Finance Stoch 4:49–61, 2002) and applies to high-frequency data. Based on the Fourier analysis, we first estimate the latent volatility process and then the volatilities and covariances of the processes that are gradually identified, such as volatility of volatility and leverage. The analysis of the eigenvalue spectrum of the Gram matrix can reveal information about the actual number of factors driving the process at hand. We corroborate our analysis by numerical simulations on single and multi factor models. Finally, we apply our methodology to intraday prices from the S &P 500 index futures.
Advancing Our Understanding of Complex Intervention Development in Social Work: Co-Producing Support for Youth Transitioning from Out-of-Home Care
Authors: Olsson Tina M. , Bergström Martin , Välikoski Magda , Karlsson Matilda , Skoog Therése 
Published: October 2024

AbstractResearch on intervention development has expanded over the past decade. However, much of the extant literature on complex intervention development is confined to healthcare and public health broadly or intervention science specifically with scant attention to the process within other fields known for their extensive provision of social interventions such as social work or community-based services. This paper aims to advance understanding of the complex intervention development process within social work using an example from the Swedish municipal social services. We use the Guidance for Reporting Intervention Development Studies (GUIDED) to describe the development and content of My Choice-My Way! an intervention to support youth transitioning from out-of-home care. Youth in out-of-home care is an extremely vulnerable group and one of social welfare services’ core user populations. Coproduction processes were used to develop a theory-, evidence-, and implementation-based approach to intervention development. Implications for future development within social work are discussed.
Review of agronomic and kernel quality traits of 273 almond cultivars
Authors: Calle Alejandro , Aparicio-Durán Lidia , Batlle Ignasi , Eduardo Iban , Miarnau Xavier 
Published: October 2024

AbstractAlmond stands out as one of the best-adapted temperate tree species globally. Its adaptability facilitated a widespread distribution from Central Asia to regions such as the Mediterranean, the United States, and Australia, enabling the adaptation of different genotypes to specific edaphoclimatic conditions. Throughout this spreading process, diverse almond landraces were selected in each growing area, resulting in a collection with varying agronomic and kernel quality properties well adapted to each origin. In addition to these native cultivars, various almond breeding programs, both public and private, released new cultivars to address key issues related to the production and kernel quality of traditional cultivars. This collective effort has resulted in a wide range of cultivars with diverse phenotypic characteristics, available for cultivation and breeding purposes. In this review, we summarize the main agronomic and kernel quality characteristics of globally available cultivated almond germplasm. This germplasm comprises genotypes from Asia, Africa, North America, South America, Australia, and Europe, either locally cultivated or released from breeding programs. For each cultivar, we provide information (if known) on the origin, parentage, year of introduction, self-(in)compatibility, S alleles, blooming time, chilling, and heat requirements, bearing habits, kernel and shell characteristics, harvesting time, tree characteristic, and disease susceptibility/resistance. In conclusion, the global diversity of cultivated almond germplasm presented in this review provides a valuable repository of phenotypic traits and genetic resources to continue advancements in almond cultivation and breeding worldwide.
Association of Maternity Leave Characteristics and Postpartum Depressive Symptoms among Women in New York
Authors: Hecht Hannah K. , Nguyen Angela-Maithy N. , Harley Kim G. 
Published: October 2024

Abstract
Introduction
The United States is the only high-income country without a comprehensive national maternity leave policy guaranteeing paid, job-projected leave. The current study examined associations between maternity leave characteristics (duration of leave, payment status of leave) and postpartum depressive symptoms.

Methods
This study used a sample of 3,515 postpartum women from the New York City and New York State Pregnancy Risk Assessment Monitoring System (PRAMS) from 2016 to 2019. We used logistic regression to examine the association of leave duration and payment status with self-reported postpartum depressive symptoms between 2 and 6 months postpartum.

Results
Compared to having at least some paid leave, having unpaid leave was associated with an increased odds of postpartum depressive symptoms, adjusting for leave duration and selected covariates (adjusted odds ratio [aOR] = 1.41, 95% confidence interval [CI]: 1.04–1.93). There was no significant difference in postpartum depressive symptoms between those with partially and those with fully paid leave. In contrast to prior literature, leave duration was not significantly associated with postpartum depressive symptoms (aOR = 0.99, 95% CI: 0.97–1.02 for each additional week of leave).

Discussion
This study suggests that unpaid leave is associated with increased risk of postpartum depression, which can have long-term health effects for both mothers and children. Future studies can help to identify which communities could most benefit from paid leave and help to inform paid leave policies.
Designing stable ride-sharing for commuting trip chain with role flexibility
Authors: Peng Zixuan , Wang Wensi , Wang Chenyu , Yu Bin 
Published: October 2024

AbstractIn ride-sharing, fixing the roles of commuters with vehicles could come at an opportunity of missed balance between riders and drivers. The decisions made by commuters with vehicles about roles are related to both to-work travel and return-home travel. Commuters may choose not to drive when they have a confirmed ride back home. This study designs a stable ride-sharing model with role flexibility for the commuting trip chain. The preferences of commuters over matching partners in trip chains are formulated. A stable matching algorithm based on commuting trip chain is designed. To assess the performance of the proposed model and algorithm, real-life data from a resident trip survey in Dalian are used to design experimental cases. The results indicate that stable matching based on the trip chain is not a consequence of the repetition of successive one-period stable matching. Compared with matching in two phases, the matching rate of commuters increases by an average of 10%. When the number of commuters with role flexibility increases by four times, the matching rate of commuters increases by an average of 5.6%.
Exposure to superstar firms and financial distress
Authors: Cheng Stephanie F. , Vyas Dushyantkumar , Wittenberg-Moerman Regina , Zhao Wuyang 
Published: October 2024

AbstractA few highly successful firms (“superstar firms”) have captured large market shares and earned massive profits in recent decades. We examine whether superstar firms are associated with a greater likelihood of financial distress for firms exposed to them in product markets. Building on recent research, we identify superstars as firms with the highest markups in the industry and whose industry markup share increases over time. We then measure, with product similarity scores, a firm’s overall product market exposure to superstars. We document that firms with greater exposure are more likely to file for bankruptcy. We examine why superstar exposure is associated with bankruptcy and show that firms with the greater superstar exposure exhibit weaker financial performance and greater riskiness. Furthermore, we show that the association between superstar exposure and the likelihood of bankruptcy strengthens when superstars have greater market power.