bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence for telemedicine heterogeneity in rheumatic and musculoskeletal diseases care: a scoping review
Authors: El Aoufy Khadija , Melis Maria Ramona , Magi Camilla Elena , Bellando-Randone Silvia , Tamburini Matteo , Bandini Giulia , Moggi-Pignone Alberto , Matucci-Cerinic Marco , Bambi Stefano , Rasero Laura 
Published: July 2024

AbstractTelemedicine and digital health represent alternative approaches for clinical practice; indeed, its potential in healthcare services for prevention, diagnosis, treatment, rehabilitation, and disease monitoring is widely acknowledged. These are all crucial issues to consider when dealing with chronic Rheumatic and Musculoskeletal Diseases (RMDs). The aim was to determine the current state of telemedicine in the field of rheumatology, considering the tools and devices in use as well as the Patient Reported Outcomes. A scoping review was performed following the PRISMA-ScR, retrieving articles through five databases from 1990 to 2022. Inclusion criteria were as follows: (I) adult patients with RMDs, (II) original research papers in the English language with available abstracts, and (III) telehealth and telemedicine are provided as healthcare services. Within the 62 included studies, multiple tools of telemedicine were used: 21/62 websites/online platforms, 18/62 mobile applications, 16/62 telephone contacts, 5/62 video-consultations, and 1/62 wearable devices. Outcomes were classified based on the economic, clinical, and humanistic framework. Clinical outcomes assessed through digital tools were pain, disease activity, and serum uric acid levels. Humanistic outcomes have been grouped according to four categories (e.g., mental and physical function, health management, and health perception). The heterogeneity of digital tools in the field of rheumatology highlights the challenge of implementing reliable research into clinical practice. Effective telerehabilitation models have been presented, and the use of a tight control strategy has also been mentioned. Future research should focus on establishing studies on other RMDs as well as summarizing and formulating clinical guidelines for RMDs.

Key Points

• Evidence for the usefulness of telemedicine and digital health for managing and monitoring rheumatic and musculoskeletal diseases is progressively increasing.• Several digital tools effectively measure clinical and humanistic and patient reported outcomes in rheumatic and musculoskeletal diseases.• Integrating diverse digital tools in rheumatology is challenging yet promising.• Future research should focus on developing standardized recommendations for practical use of telemedicine in daily practice.
Green business process management in a Polish municipal waste treatment plant-regional case study
Authors: Brajer-Marczak Renata , Seruga Przemysław , Jarossova Małgorzata Agnieszka , Krzywonos Małgorzata 
Published: July 2024

AbstractDespite COVID-19, the world economy still contributes to the growth of production and consumption worldwide. Waste disposal, recycling management and energy generation are challenges for many companies in developing economies, including Poland. This article aims to assess the operation of a municipal waste treatment plant (MWTP) from the perspective of green business process management (BMP) solutions. The processes implemented in the MWTP were discussed, with specific consideration of the mechanical waste processing (sorting) process, including the reuse and recycling of materials, composting, energy production (anaerobic process), landfill storage and efficiency parameters of the sorting line. A sustainable waste management system was identified; the cost as well as social and environmental perspectives were analyzed. Also, strategic goals and key performance indicators were considered. The performed analysis included costs, environmental criteria and key environmental indicators. This paper has shown the successful implementation of green BPM, with potential cost and material savings results. The findings of this case study are expected to inspire other waste management companies to adopt green BPM. The presented case study might help raise awareness and promote the implementation of green BPM in municipal plants in Eastern and Southern Europe.
Traction-separation law parameters for the description of age-related changes in the delamination strength of the human descending thoracic aorta
Authors: Petřivý Zdeněk , Horný Lukáš , Tichý Petr 
Published: July 2024

AbstractAortic dissection is a life-threatening disease that consists in the development of a tear in the wall of the aorta. The initial tear propagates as a discontinuity leading to separation within the aortic wall, which can result in the creation of a so-called false lumen. A fatal threat occurs if the rupture extends through the whole thickness of the aortic wall, as blood may then leak. It is generally accepted that the dissection, which can sometime extend along the entire length of the aorta, propagates via a delamination mechanism. The aim of the present paper is to provide experimentally validated parameters of a mathematical model for the description of the wall’s cohesion. A model of the peeling experiment was built in Abaqus. The delamination interface was described by a piecewise linear traction-separation law. The bulk behavior of the aorta was assumed to be nonlinearly elastic, anisotropic, and incompressible. Our simulations resulted in estimates of the material parameters for the traction-separation law of the human descending thoracic aorta, which were obtained by minimizing the differences between the FEM predictions and the delamination force given by the regression of the peeling experiments. The results show that the stress at damage initiation, Tc, should be understood as an age-dependent quantity, and under the assumptions of our model this dependence can be expressed by linear regression as Tc =  − 13.03·10−4·Age + 0.2485 if the crack front advances in the axial direction, and Tc =  − 7.58·10−4·Age + 0.1897 if the crack front advances in the direction of the aortic circumference (Tc [MPa], Age [years]). Other model parameters were the stiffness K and the separation at failure, δf–δc (K = 0.5 MPa/mm, δf–δc = 0.1 mm). The material parameters provided by our study can be used in numerical simulations of the biomechanics of dissection propagation through the aorta especially when age-associated phenomena are studied.
Freedom Waived: A Systematic Review of Research on People in Prison Who Forgo the Opportunity for Release on Parole
Authors: Dodd Shannon , Sydes Michelle 
Published: July 2024

AbstractThis paper presents a systematic review of 18 studies about people in prison who forgo the opportunity for parole. Employing a Mixed Methods Research Synthesis, the review encompasses qualitative, quantitative, and mixed-methods studies that identify the factors and motivating reasons associated with parole waiver decisions, as well as recidivism outcomes for individuals who decide to forgo parole. Findings reveal a predominance of quantitative research that suggests that individuals who waive parole tend to be high-risk, violent offenders who are serving lengthy sentences. They are male, Indigenous, with a history of mental illness and/or substance addiction, and prior parole experience. Motivating reasons for avoiding parole include perceptions that prison is easier than parole and fear of parole denial and re-entry barriers. Studies also report less favourable recidivism outcomes for ‘maxed-out’ offenders. The study emphasises the necessity for additional in-depth research to understand motives and disincentives influencing parole engagement decisions. In particular, the need for research outside of North America and that uses sources other than administrative data is identified.
Explainable decomposition of nested dense subgraphs
Authors: Tatti Nikolaj 
Published: July 2024

AbstractDiscovering dense regions in a graph is a popular tool for analyzing graphs. While useful, analyzing such decompositions may be difficult without additional information. Fortunately, many real-world networks have additional information, namely node labels. In this paper we focus on finding decompositions that have dense inner subgraphs and that can be explained using labels. More formally, we construct a binary tree T with labels on non-leaves that we use to partition the nodes in the input graph. To measure the quality of the tree, we model the edges in the shell and the cross edges to the inner shells as a Bernoulli variable. We reward the decompositions with the dense regions by requiring that the model parameters are non-increasing. We show that our problem is NP-hard, even inapproximable if we constrain the size of the tree. Consequently, we propose a greedy algorithm that iteratively finds the best split and applies it to the current tree. We demonstrate how we can efficiently compute the best split by maintaining certain counters. Our experiments show that our algorithm can process networks with over million edges in few minutes. Moreover, we show that the algorithm can find the ground truth in synthetic data and produces interpretable decompositions when applied to real world networks.
Ready or not? Investigating in-service teachers’ integration of learning analytics dashboard for assessing students’ collaborative problem solving in K–12 classrooms
Authors: Liu Yiming , Hu Xiao , Ng Jeremy Tzi Dong , Ma Zhengyang , Lai Xiaoyan 
Published: July 2024

Abstract
Collaborative problem solving (CPS) has emerged as a crucial 21st century competence that benefits students’ studies, future careers, and general well-being, prevailing across disciplines and learning approaches. Given the complex and dynamic nature of CPS, teacher-facing learning analytics dashboards (LADs) have increasingly been adopted to support teachers’ CPS assessments by analysing and visualising various dimensions of students’ CPS. However, there is limited research investigating K-12 teachers’ integration of LADs for CPS assessments in authentic classrooms. In this study, a LAD was implemented to assist K-12 teachers in assessing students’ CPS skills in an educational game. Based on the person-environment fit theory, this study aimed to (1) examine the extent to which teachers’ environmental and personal factors influence LAD usage intention and behaviour and (2) identify personal factors mediating the relationships between environmental factors and LAD usage intention and behaviour. Survey data of 300 in-service teachers from ten Chinese K-12 schools were collected and analysed using partial least squares structural equation modelling (PLS-SEM). Results indicated that our proposed model showed strong in-sample explanatory power and out-of-sample predictive capability. Additionally, subjective norms affected technological pedagogical content knowledge (TPACK) and self-efficacy, while school support affected technostress and self-efficacy. Moreover, subjective norms, technostress, and self-efficacy predicted behavioural intention, while school support, TPACK, and behavioural intention predicted actual behaviour. As for mediation effects, school support indirectly affected behavioural intention through self-efficacy, while subjective norms indirectly affected behavioural intention through self-efficacy and affected actual behaviour through TPACK. This study makes theoretical, methodological, and practical contributions to technology integration in general and LAD implementation in particular.
The Associations Between Discrete Emotions and Political Learning: A Cross-Disciplinary Systematic Review and Meta-Analysis
Authors: Graf Elisabeth , Donath Johanna L. , Botes Elouise , Voracek Martin , Goetz Thomas 
Published: July 2024

AbstractIn recent decades, researchers’ interest in the role of emotions in individual political learning has grown. However, it is still unclear whether and how discrete emotions are associated with political learning. Through a cross-disciplinary systematic review and multilevel meta-analysis, we reviewed which discrete emotions have been analyzed in the context of political learning so far and meta-analytically synthesized how these emotions relate to political learning. We addressed this question by synthesizing associations between discrete emotions and various aspects of learning about political matters, such as political attention, information seeking, discussions, knowledge, and knowledge gain. The final dataset included 66 publications with 486 effect sizes, involving more than 100,000 participants. Most of the effect sizes were based on negative-activating emotions (65%; mainly anxiety, 32%, and anger, 19%) and positive-activating emotions (32%; mainly enthusiasm, 15%), while studies on positive-deactivating emotions (e.g., contentment) and negative-deactivating emotions (e.g., sadness) are largely lacking. We uncovered small positive associations (r = .05 to .13) for activating emotions, of both negative (especially anger) and positive valence (e.g., enthusiasm, only in cross-sectional designs), but no associations for negative-deactivating emotions. We discuss theoretical implications and recommend future research to include previously unconsidered emotions in order to extend existing findings.
Compilation of Consolidation Properties Data of Champlain Sea Clay from Ottawa Region
Authors: Tavakkoli N’eem , Oh Won Taek , Vanapalli Sai K. 
Published: July 2024

AbstractEstimation of consolidation settlements in fine-grained soils due to various civil infrastructure loads is traditionally based on results derived from consolidation tests performed on undisturbed soil samples, combined with the data of other soil properties. In many geotechnical engineering applications, consolidation settlements are also estimated using empirical consolidation parameters derived from basic soil properties. This approach relies on correlations from the literature to bypass the time-consuming and expensive sampling techniques, laboratory testing, and other associated expenses. However, these correlations may not provide reasonable consolidation settlement estimations as these correlations are typically developed without considering the influence of stress history, geology, salinity of pore water, gradation, soil fabric, and chemical properties of the soils. This is especially true for Champlain Sea clay deposits from Eastern Ontario region of Canada that are typically with heterogeneous site conditions and exhibit spatial variability of soil properties. In this paper, data from the published literature and industrial and government reports on sensitive Champlain Sea clays were gathered for the Ottawa region. The data collection and clean-up methodology towards enhancing the reliability of the gathered data is comprehensively discussed. The summarized data from this study can be used with a greater degree of confidence towards developing reliable correlations in the estimation of consolidation settlements in geotechnical engineering practice.
TOPCOAT: towards practical two-party Crystals-Dilithium
Authors: Snetkov Nikita , Vakarjuk Jelizaveta , Laud Peeter 
Published: July 2024

AbstractThe development of threshold protocols based on lattice-signature schemes has been of increasing interest in the past several years. The main research focus has been towards protocols constructed for various variants of Crystals-Dilithium, future NIST digital signature standard known as ML-DSA. In this work, we propose TOPCOAT, a two-party lattice-based signature algorithm that embodies Dilithium’s compression techniques. The aforesaid result is achieved by introducing a new hinting mechanism that allows parties to collaboratively calculate $$\textsf {HighBits}$$
HighBits
. Our hinting mechanism allows public key compression similar to Dilithium. Additionally, we suggest an optimization technique to minimize number of restarts both parties need to produce a valid signature. Our approach allows to produce $$\approx 10$$

≈
10

KB signatures within 3 rounds of communication. We prove security of our scheme under MLWE and MSIS assumptions in ROM, and provide implementation of our proposed scheme. As additional contribution, we present vulnerabilities and inconsistencies found in Liu et al. work (Future Generation Computer Systems 2023) which aimed to construct distributed lattice-based signature protocol.
Factors Related to the Recurrence of Sickness Absence Due to Common Mental Health Disorders: A Systematic Review
Authors: in‘t Hout Lydia , van Hees Suzanne G. M. , Vossen Emma , Oomens Shirley , van de Mheen Dike , Blonk Roland W. B. 
Published: July 2024

Abstract
Purpose
Employees who experience sickness absence (SA) due to common mental disorders (CMD) are at increased risk of recurrent sickness absence (RSA). This systematic literature review examines the factors at different levels in the work and non-work context that increase or decrease the likelihood of RSA due to CMD. The resulting knowledge enables more accurate identification of employees at risk of RSA.

Methods
We conducted a search in June 2023 using the following databases: PubMed, PsycInfo, Web of Science, Cumulative Index to Nursing & Allied Health Literature (Cinahl), Embase and Business Source Ultimate (BSU). Inclusion criteria were as follows: (self-)employees, CMD, related factors, RSA. The quality of the studies was assessed using the Mixed Methods Appraisal Tool (MMAT). The Individual, Group, Leader, Organisation and Overarching/social context (IGLOO) model were used to cluster the found factors and these factors were graded by evidence grading.

Results
Nineteen quantitative and one qualitative studies of mainly high and some moderate quality were included in this review. A total of 78 factors were found. These factors were grouped according to the IGLOO levels and merged in 17 key factors. After evidence grading, we found that mainly low socioeconomic status (SES) and the type of previous SA (short-term SA and SA due to CMD) are predictors of an increased risk of RSA.

Conclusions
Having a low SES and previous experience of SA (short term, or due to CMD) are factors that predict the chance of RSA, implying the need for prolonged support from occupational health professionals after the employee has returned to work.
Visible light-driven removal of Rhodamine B using indium-doped zinc oxide prepared by sol–gel method
Authors: Benamara Majdi , Nassar Kais Iben , Essid Manel , Frick Stefanie , Rugmini R. , Sekhar K. C. , Silva José P. B. 
Published: July 2024

AbstractIndustrial dye contamination in wastewater poses significant environmental challenges, necessitating the development of efficient photocatalysts for degradation. In this work, we investigate the In doping effect in the photocatalytic activity of zinc oxide (ZnO) nanoparticles for effective RhB degradation. Indium-doped ZnO nanoparticles were synthesized via sol–gel method and x-ray diffraction (XRD) analysis revealed a wurtzite hexagonal structure, with the crystallite size being varying from 65 nm to 53 nm with the introduction of In content. XPS measurements on the 3% In-doped ZnO sample revealed distinct core level spectra for In 3d, Zn 2p, and O 1s regions, confirming the presence of indium, zinc, and oxygen. Brunauer–Emmett–Teller (BET) analysis revealed increased surface area and pore size, with specific surface areas escalating from 0.9 m²/g for pure ZnO to 10.1 m²/g for 3% indium-doped ZnO. Photocatalytic experiments exhibited significant RhB degradation, with degradation efficiencies reaching 93% for 3% indium-doped ZnO under visible light irradiation due to the effect of the presence of In, which causing light absorption enhancement, narrow the band gap and improve charge carrier separation. These findings underscore the potential of indium-doped ZnO nanoparticles as efficient and sustainable photocatalysts for wastewater treatment, offering a promising avenue to address environmental challenges associated with industrial dye-contaminated effluents.
Graphical Abstract
Heat capacities of active pharmaceutical ingredients nifedipine, griseofulvin, probucol and 5,5-diphenylhydantoin
Authors: Štejfa Vojtěch , Vojtíšková Olga , Pokorný Václav , Rohlíček Jan , Růžička Květoslav , Fulem Michal 
Published: July 2024

AbstractThe isobaric condensed-phase heat capacities of selected pharmaceutical active ingredients (APIs), namely nifedipine (CAS RN: 21829-25-4), griseofulvin (CAS RN: 126-07-8), probucol (CAS RN: 23288-49-5) and 5,5-diphenylhydantoin (CAS RN: 57-41-0), were determined over a wide temperature range starting from 2 K by combination of relaxation (heat pulse) calorimetry, Tian-Calvet calorimetry and power-compensated differential scanning calorimetry. Heat capacity measurements were taken for clearly specified polymorphs, a liquid phase (including subcooled liquid) and a glassy amorphous phase, if feasible. For 5,5-diphenylhydantoin, a heat capacity anomaly was detected in the temperature range 160 to 190 K and interpreted based on additional calorimetric and temperature-variable crystallographic measurements as a sequence of two phase transitions, which are reported for the first time in this work. Based on the determined phase behavior and heat capacity data from near 0 K, standard thermodynamic functions for crystalline and liquid phases were calculated for all APIs studied. This work significantly extends the availability of reliable heat capacity data and related thermodynamic properties for APIs required for modeling their solubility and other applications involving thermodynamic modeling.
Cost-aware workflow offloading in edge-cloud computing using a genetic algorithm
Authors: Abdi Somayeh , Ashjaei Mohammad , Mubeen Saad 
Published: July 2024

AbstractThe edge-cloud computing continuum effectively uses fog and cloud servers to meet the quality of service (QoS) requirements of tasks when edge devices cannot meet those requirements. This paper focuses on the workflow offloading problem in edge-cloud computing and formulates this problem as a nonlinear mathematical programming model. The objective function is to minimize the monetary cost of executing a workflow while satisfying constraints related to data dependency among tasks and QoS requirements, including security and deadlines. Additionally, it presents a genetic algorithm for the workflow offloading problem to find near-optimal solutions with the cost minimization objective. The performance of the proposed mathematical model and genetic algorithm is evaluated on several real-world workflows. Experimental results demonstrate that the proposed genetic algorithm can find admissible solutions comparable to the mathematical model and outperforms particle swarm optimization, bee life algorithm, and a hybrid heuristic-genetic algorithm in terms of workflow execution costs.
Beyond prediction: a new paradigm for understanding suicide risk
Authors: Baston René 
Published: July 2024

AbstractRecent meta-studies have shown that there are no known risk factors for suicidal behavior that could be used for behavior prediction, rendering the classic understanding of high and low risk for suicide questionable. The aim of this manuscript is to propose a new understanding of suicide risk that does not depend on predictive powers. In contrast, the developed Normic account of suicide risk, which is based on a possible world framework rather than probability calculations, suggests that the normalcy of an event determines whether the risk for the event’s occurrence is high or low. I suggest that this normalcy stems from the norms of practical rationality for agents who consider self-killing. The more difficult it is to make sense of possible intentional self-killing, the more abnormal the event is, which renders the event less risky. Consequently, from the Normic account of suicide risk, an individual who has weak or no life-sustaining reasons is at high risk for suicide. In conclusion, although the prediction of suicide is beyond the current scope of clinical psychology, there are still reasonable options for understanding what distinguishes individuals at high risk from those at low risk for suicide.