bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of different telerehabilitation protocols for urogenital symptoms in females with multiple sclerosis: a randomized controlled trial
Authors: Deodato Manuela , Fornasaro Mia , Martini Miriam , Zelesnich Francesca , Sartori Arianna , Galmonte Alessandra , Buoite Stella Alex , Manganotti Paolo 
Published: September 2024

AbstractTelerehabilitation has been suggested to be equally effective than in-person rehabilitation, and could be helpful to increase participation and reduce barriers. People with multiple sclerosis (MS) often present urogenital dysfunctions, impairing independence and quality of life (QoL). Since the different available telerehabilitation protocols, the present study aimed to compare a live video urogenital rehabilitation intervention protocol (REMOTE) with a home-based pre-recorded video protocol (SELF). A randomized-controlled trial was performed, with 14 females with MS being allocated in the REMOTE group (36 ± 9 y) and 14 females in the SELF group (37 ± 7 y). Both telerehabilitation protocols were identical in terms of contents (including pelvic floor training and relaxation exercises), frequency and duration, consisting of 10 sessions of 45 min each, every 5 days. Questionnaires were administered at the beginning and the end of the study: Short Form Health Survey 36 (SF-36), Beck Depression Inventory (BDI), Female Sexual Function Index (FSFI), International Consultation on Incontinence Questionnaire (ICIQ) symptoms and related QoL, the main outcome being ICIQ incontinence score. Despite most of the outcomes improved in both groups, REMOTE was found to be more effective than SELF in most of the SF-36 domains (from p < 0.001 pη2 0.555 to p = 0.044 pη2 0.147), FSFI (p = 0.001 pη2 0.373), ICIQ (p = 0.003 pη2 0.291). Despite the home-based pre-recorded videos could be effective in improving urogenital symptoms, live video urogenital rehabilitation results in larger improvements. Telerehabilitation should be encouraged for urogenital dysfunctions in females with MS, and pre-recorded videos could represent an alternative when live sessions are not available.
Clinical trial registration This randomized controlled trial was registered on ClinicalTrials.gov with the number NCT05984095.
Metal(loid)s Removal Response to the Seasonal Freeze–Thaw Cycle in Semi-passive Pilot Scale Bioreactors
Authors: Desmau Morgane , Simister Rachel , Baldwin Susan A. , Nielsen Guillaume 
Published: September 2024

AbstractThere is an increasing demand for cost-effective semi-passive water treatment that can withstand challenging climatic conditions and effectively and sustainably manage mine-impacted water in (sub)arctic regions. This study investigated the ability of four pilot-scale bioreactors inoculated with locally sourced bacteria and affected by a freeze–thaw cycle to remove selenium and antimony. The bioreactors were operated at a Canadian (sub)arctic mine for a year. Two duplicate bioreactors were installed in a heated shed that was maintained at 5 °C over the winter, while two other duplicates were installed outdoors and left to freeze. The removal rate of selenium and antimony was monitored weekly, while a genomic characterization of the microbial populations in the bioreactors was performed monthly. The overall percentage of selenium and antimony removal was similar in the outside (10–93% Se, 20–96% Sb) and inside (35–94% Se, 10–95% Sb) bioreactors, apart from the spring thawing period when removal in the outdoor bioreactors was slightly lower for Se. The dominant taxonomic groups of microbial populations in all bioreactors were Bacteroidota, Firmicutes, Desulfobacterota and Proteobacteria. The microbial population composition was consistent and re-established quickly after spring thaw in the outside bioreactors. This demonstrated that the removal capacity of bioreactors inoculated with locally sourced bacteria was mostly unaffected by a freeze–thaw cycle, highlighting the strength of using local resources to design bioreactors in extreme climatic conditions.
Towards Standardized benchmarks of LLMs in software modeling tasks: a conceptual framework
Authors: Cámara Javier , Burgueño Lola , Troya Javier 
Published: September 2024

Abstract
The integration of Large Language Models (LLMs) in software modeling tasks presents both opportunities and challenges. This Expert Voice addresses a significant gap in the evaluation of these models, advocating for the need for standardized benchmarking frameworks. Recognizing the potential variability in prompt strategies, LLM outputs, and solution space, we propose a conceptual framework to assess their quality in software model generation. This framework aims to pave the way for standardization of the benchmarking process, ensuring consistent and objective evaluation of LLMs in software modeling. Our conceptual framework is illustrated using UML class diagrams as a running example.
The effects of a risk-based approach to tax examinations: evidence from a tax pilot programme in Tanzania
Authors: Ebrahim Amina , Kisanga Elineema , Swema Ezekiel , Leyaro Vincent , Mhede Edwin P. , Mdee Ephraim , Palviainen Heikki , Pirttilä Jukka 
Published: September 2024

AbstractTechnical assistance and increased use of ICT in tax administrations hold promise for greater revenue collection. Yet, the evidence on how these activities work in the real-world circumstances of developing countries is scant. The paper attempts to fill this gap by evaluating an intervention undertaken jointly by the Finnish and Tanzanian revenue administrations. The programme introduced a new risk-based case selection method for enhancing the effectiveness of firm tax examinations in Tanzania complemented by supplementary staff training and developing management practices. Our results, stemming from a difference-in-differences analysis and administrative data from the Tanzanian Revenue Authority, indicate that the intervention increased the corrected amount of taxable income by approximately 20% during the first year of the new approach.
Three-dimensional printed calcium phosphate scaffolds emulate bone microstructure to promote bone regrowth and repair
Authors: Takase Kyohei , Niikura Takahiro , Fukui Tomoaki , Kumabe Yohei , Sawauchi Kenichi , Yoshikawa Ryo , Yamamoto Yuya , Nishida Ryota , Matsumoto Tomoyuki , Kuroda Ryosuke , Oe Keisuke 
Published: September 2024

AbstractThe interconnected structures in a 3D scaffold allows the movement of cells and nutrients. Therefore, this study aimed to investigate the in-vivo bioactivity of 3D-printed β-tricalcium phosphate (β-TCP) and hydroxyapatite (HAP) scaffolds that replicate biological bone. This study included 24-week-old male New Zealand white rabbits. A cylindrical bone defect with a diameter of 4.5 mm and a depth of 8 mm was created in the lateral aspect of the distal femur. A 3D-printed scaffold was implanted in the right femur (experimental side), whereas the left femur was kept free of implantation (control side). Micro-CT analysis and histological observations of the bone defect site were conducted at 4, 8, and 12 weeks postoperatively to track the bone repair progress. No evidence of new bone tissue formation was found in the medullary cavity of the bone defect on the control side. In contrast, on the experimental side, the 3D scaffold demonstrated sufficient bioactivity, leading to the growth of new bone tissue. Over time, new bone tissue gradually extended from the periphery toward the center, a phenomenon evident in both micro-CT images and biopsy staining. In the current study, we observed that the cells involved in bone metabolism adhered, spread, and proliferated on our newly designed 3D-printed scaffold with a bone microstructure. Therefore, it is suggested that this scaffold has sufficient bioactivity to induce new bone formation and could be expected to be a more useful artificial bone than the existing version.
Graphical Abstract
Interpersonal Processes in the Duration of Sick Leave of Workers with Chronic Diseases: A Dyadic Analysis
Authors: de Vries Haitze J. , Snippen Nicole C. , Roelen Corné A. M. , Hagedoorn Mariët , Brouwer Sandra 
Published: September 2024

Abstract
Purpose
Although there is increasing awareness that significant others’ perceptions and behavior can affect health outcomes, the role of interpersonal processes between sick-listed workers and significant others in sick leave and return to work (RTW) has hardly been studied. This study aims to examine the associations between illness perceptions, RTW expectations, and behaviors of significant others (engagement, buffering and overprotection) with sick leave duration within dyads of sick-listed workers with chronic diseases and their significant others.

Methods
We used survey data linked with sick leave registry data of 90 dyads. Pearson correlations were used to study the interdependence within dyads. Multiple linear regression analyses were conducted to examine associations between survey data of both dyad members and sick leave duration.

Results
We found moderate to strong correlations between workers and significant others, indicating interdependence within dyads regarding illness perceptions, RTW expectations and perceived significant other behaviors. Dyad members’ illness perceptions (R2 = .204, p = .001) and RTW expectations (R2 = .326, p =  < .001) were associated with sick leave duration, explaining respectively 12.3% and 24.5% of the variance. We found no associations between sick leave duration and active engagement, protective buffering and overprotection.

Conclusions
This study indicates that negative illness perceptions and RTW expectations of both workers and their significant others are associated with a longer sick leave duration. Considering the interdependence within dyads, involving significant others when intervening on maladaptive illness perceptions and RTW expectations may be more effective than solely focusing on the worker’s perceptions and expectations.
Commuting in dual-earner households: international gender differences with time use surveys
Authors: Echeverría Lucía , Gimenez-Nadal J. Ignacio , Molina José Alberto 
Published: September 2024

AbstractPrior studies show men commute longer than women, often due to household responsibilities. However, research on commuting differences within couples is limited. This study examines gender gaps in commuting times and mode choices among dual-earner couples in Spain, Italy, South Korea, and the UK. Using Ordinary Least Squares regressions, we find that the presence of children significantly increases gender gaps in commuting times in Italy and the UK, supporting the household responsibility hypothesis. Conversely, no significant link between children and gender gaps is observed in Spain and Korea. Additionally, children’s presence affects commuting mode choices in Italy across all modes, and in Korea for public transit only, with Italian women showing the most changes in commuting mode when children are present.
On the Relations Between Non-Verbal Signs and Norms
Authors: Bacchini Fabio 
Published: September 2024

Abstract
Although the presumption that norms are necessarily expressed by words has traditionally prevailed in the scientific community, some scholars are challenging verbal-centrism in the normative domain. While sympathising with this cause, this paper argues that not every case in which a norm is expressible by a non-verbal sign is a case in which that norm is genetically or ontologically word-free. After mapping the different relations that can exist between a sign and a norm, the paper shows that the holding of many of them should not be taken per se as evidence for the thesis that some norms are genetically or ontologically word-independent, no matter that the sign is non-verbal. In particular, the paper analyses why some eminent examples of normative non-verbal signs like red traffic lights, traffic warden’s outstretched arms, referee’s whistles, and word-free no smoking signs, are not good evidence for the claim that some norms are not produced by or do not consist of verbal signs.
Experimental Verification of Low-Pressure Kinetics Model for Direct Synthesis of Dimethyl Carbonate Over CeO2 Catalyst
Authors: Ibrahim G. , Abdelbar A. , Choudhury H. A. , Challiwala M. S. , Prakash A. , Mondal K. , Solim S. , Elbashir Nimir O. 
Published: September 2024

AbstractDimethyl carbonate (DMC) has emerged as a promising candidate for sustainable chemical processes due to its remarkable versatility and low toxicity. From a green chemistry perspective, the direct synthesis of DMC has been considered the most promising route, as water is the only byproduct generated in the reaction between CO2 and methanol. However, this synthetic route has faced significant thermodynamic limitations, even at elevated pressure conditions. Therefore, a two-part study explored low-pressure synthesis of DMC via the direct route, and a low-pressure kinetic model for the CeO2 catalyst was developed based on the results. Proposed Langmuir–Hinshelwood mechanisms were verified using experimental data generated in our labs. The investigation suggests that DMC formation in the direct synthetic route is a surface reaction of CO2 and methanol on the catalyst. The kinetic model predictions closely aligned with experimental data, demonstrating a 17% mean absolute percentage error and indicating a high level of predictability. Additionally, a rigorous assessment was conducted on CO2 fixations in DMC synthesis, quantifying CO2 capture and its conversion into stable or high-value products, formally designated as CO2 Fixation (CO2Fix). The CO2Fix analysis revealed that, at a conversion rate of 27%, the process can achieve a "net zero" state when operated at an approximate pressure of 30 bar, thereby supporting the viability of low-pressure synthesis. Increasing the conversion rate to levels exceeding 95% significantly enhances the CO2Fix metric, potentially surpassing 3.5 or higher.
A Tale of Two Tributaries: Source Delineation of Chloride in a Distressed Watershed (Grand Lake St. Marys, Ohio)
Authors: Kane Douglas D. , Manning Nathan F. , Jacquemin Stephen J. , Johnson Laura T. 
Published: September 2024

AbstractVarious sources of pollution have been assigned as contributing to the Freshwater Salinization Syndrome (FSS), by which water bodies are undergoing concurrent salinization and alkalinization. In many urban areas that receive substantial snowfall, road salt application has been ascribed as the main source of chloride driving the FSS. In rural areas, however, inorganic (e.g. chemical) and organic (e.g. manure) fertilizer applications have been found to be the most important sources of chloride. Herein, we compared daily mean concentrations of chloride over the past decade of time between Coldwater Creek and Chickasaw Creek, two tributaries of Grand Lake St. Marys, the largest reservoir in Ohio. We also used Weighted Regressions on Time, Discharge, and Season (WRTDS) analyses to visualize trends in chloride data and compared chloride vs. nitrate levels to delineate likely sources of chloride for the two streams. We found that road salt application increased over time in both subwatersheds and that 37% and 25% of the chloride could be apportioned to road salt as a source in Coldwater Creek and Chickasaw Creek, respectively. Additionally, in Coldwater Creek, 37% of the chloride was apportioned to animal or septic sources, while 25% was apportioned to inorganic fertilizers, in comparison with 30% and 42% for Chickasaw Creek. Monitoring and assessing salinized streams for both chemical and biological water quality is important, particularly since the FSS has become increasingly linked to declines in water quality (e.g. harmful algal blooms, including recent upticks in Prymnesium parvum blooms) and is expected to be exacerbated with global climate change (e.g. increased precipitation causing increased runoff of chloride from the land).
Seasonal and spatial variations of arsenic and its species in particulate matter in an urban environment of Brno, Czech Republic
Authors: Michalicová Romana , Hegrová Jitka , Svoboda Josef , Ličbinský Roman 
Published: September 2024

AbstractThe present paper deals with an analysis of total arsenic concentration using ICP-MS/MS and an analysis of concentration of several arsenic species, arsenite (AsIII), arsenate (AsV), monomethylarsonate (MMA), dimethylarsenite (DMA), and trimethylarsine oxide (TMAO), using HPLC-ICP-MS/MS in the PM10 fraction of airborne urban aerosol. The samples were collected during two campaigns, in the autumn of 2022 and in the winter of 2023, at three locations within the central European city of Brno, with the aim to evaluate the seasonal and spatial variations in the PM10 composition. The results confirmed only the seasonal variability in the content of the methylated arsenic species in PM10 influenced by biomethylation processes. To gain better understanding of the possible arsenic origin, a supplementary analysis of the total arsenic concentrations was performed in samples of different size fractions of particulate matter collected using ELPI + . Local emissions, including industrial activities and heating during the winter season, were suggested as the most likely predominant source contributing to the total As content in PM10.
Graphical abstract
The effect of cumulative eye movements’ guidance of experts on transition from novice to expert
Authors: Yondemir Çalişkan Neslihan , Şendurur Emine 
Published: September 2024

AbstractBased on the assumptions of cognitive load theory, this study aims to utilize the eye movement data collected from multiple experts to scaffold novice graphic designers. The study has two main stages. In the first stage, eye tracking was used to record the eye movements of 7 experts, who covered eight topics explaining how to use Photoshop. The areas of interest and fixation durations were analyzed for each topic to extract the common patterns. Instructional videos were produced with the guidance of both eye movement patterns and multimedia design principles. In the second stage of this study, those videos were delivered to 30 university students. The experiment group watched the guided videos, whereas the control group watched straight videos, i.e., content without guidance. The guidance elements were reduced (faded) as students got familiar with the interface. All participants were assigned to perform tasks as soon as they completed the videos. The findings showed that the knowledge scores did not significantly differ between groups. Still, the average performance scores of the experiment group were considerably higher than that of the control group. Considering the transition process, the experiment group outperformed the others. The topics in which experts’ eye movements highly matched each other resulted in high-performance gaps among groups.
A Framework for Measuring Neighborhood Walkability for Older Adults—A Delphi Consensus Study
Authors: Koller Daniela , Bödeker Malte , Dapp Ulrike , Grill Eva , Fuchs Judith , Maier Werner , Strobl Ralf 
Published: September 2024

Abstract While mobility in older age is of crucial importance for health and well-being, it is worth noting that currently, there is no German language framework for measuring walkability for older adults that also considers the functional status of a person. Therefore, we combined the results of an expert workshop, a literature review, and a Delphi consensus survey. Through this, we identified and rated indicators relevant for walkability for older adults, additionally focusing on their functional status. The expert workshop and the review led to an extensive list of potential indicators, which we hope will be useful in future research. Those indicators were then adapted and rated in a three-stage Delphi expert survey. A fourth additional Delphi round was conducted to assess the relevance of each indicator for the different frailty levels, namely “robust,” “pre-frail,” and “frail.” Between 20 and 28 experts participated in each round of the Delphi survey. The Delphi process resulted in a list of 72 indicators deemed relevant for walkability in older age groups, grouped into three main categories: “Built environment and transport infrastructure,” “Accessibility and meeting places,” and “Attractiveness and sense of security.” For 35 of those indicators, it was suggested that functional status should be additionally considered. This framework represents a significant step forward in comprehensively covering indicators for subjective and objective walkability in older age, while also incorporating aspects of functioning relevant to older adults. It would be beneficial to test and apply the indicator set in a community setting.
An artificial neural network based deep collocation method for the solution of transient linear and nonlinear partial differential equations
Authors: Mishra Abhishek , Anitescu Cosmin , Budarapu Pattabhi Ramaiah , Natarajan Sundararajan , Vundavilli Pandu Ranga , Rabczuk Timon 
Published: September 2024

AbstractA combined deep machine learning (DML) and collocation based approach to solve the partial differential equations using artificial neural networks is proposed. The developed method is applied to solve problems governed by the Sine–Gordon equation (SGE), the scalar wave equation and elasto-dynamics. Two methods are studied: one is a space-time formulation and the other is a semi-discrete method based on an implicit Runge–Kutta (RK) time integration. The methodology is implemented using the Tensorflow framework and it is tested on several numerical examples. Based on the results, the relative normalized error was observed to be less than 5% in all cases.
ResGAT: Residual Graph Attention Networks for molecular property prediction
Authors: Nguyen-Vo Thanh-Hoang , Do Trang T. T. , Nguyen Binh P. 
Published: September 2024

AbstractMolecular property prediction is an important step in the drug discovery pipeline. Numerous computational methods have been developed to predict a wide range of molecular properties. While recent approaches have shown promising results, no single architecture can comprehensively address all tasks, making this area persistently challenging and requiring substantial time and effort. Beyond traditional machine learning and deep learning architectures for regular data, several deep learning architectures have been designed for graph-structured data to overcome the limitations of conventional methods. Utilizing graph-structured data in quantitative structure–activity relationship (QSAR) modeling allows models to effectively extract unique features, especially where connectivity information is crucial. In our study, we developed residual graph attention networks (ResGAT), a deep learning architecture for molecular graph-structured data. This architecture is a combination of graph attention networks and shortcut connections to address both regression and classification problems. It is also customizable to adapt to various dataset sizes, enhancing the learning process based on molecular patterns. When tested multiple times with both random and scaffold sampling strategies on nine benchmark molecular datasets, QSAR models developed using ResGAT demonstrated stability and competitive performance compared to state-of-the-art methods.