bluuebunny/crossref_metadata_2025_split huggingface dataset:
Living with a Rare Disease: Psychosocial Impacts for Parents and Family Members – a Systematic Review
Authors: Atkins Jenny C. , Padgett Christine R. 
Published: February 2024

AbstractAs rare diseases often have an onset of symptoms in childhood, the burden of the disease and associated challenges commonly fall to the individual’s family members. Managing this burden, and navigating these challenges, has been found to affect the health and lifestyle of family members and lead to them experiencing negative psychosocial impacts and lower quality of life. The aim of the current study was to consolidate and summarise the published quantitative evidence on the psychosocial impacts experienced by individuals who have a family member with a rare disease. We performed a systematic literature search including quantitative studies on psychosocial impacts experienced by family members of individuals with a rare disease across three databases (PubMed, PsychINFO, and CINAHL) from inception to November 2021. Of the 2024 titles identified, 30 studies met the inclusion criteria and were included in the review. A narrative analysis revealed that family members of individuals with rare disease experience a wide range of psychosocial impacts, some of which appear to be unique to, or amplified by, the rarity of the disease. Whilst there are occasional positive outcomes of having a family member with a rare disease, overall family members have been found to experience increased psychological distress, lower quality of life, higher caregiver burden and changes to their social support. Clinical and practical implications of these findings are discussed, as well as implications and directions for future research.
Ant diversity along elevational gradients in the European Alps: insights for conservation under a changing climate
Authors: Schifani Enrico , Grasso Donato A. , Gobbi Mauro , Spotti Fiorenza A. , Pedrotti Luca , Vettorazzo Enrico , Mori Alessandra , Castracani Cristina 
Published: February 2024

Abstract
Due to particular vulnerabilities and environmental constraints, Alpine faunas are exposed to significant threats from climate change. However, baseline diversity and distribution data to monitor the trends of key arthropod groups are often scarce. Ants are highly diversified and key ecological actors across terrestrial ecosystems, including mountain ranges. We investigated ant diversity and distribution in the Southern European Alps to provide detailed data over wide elevational gradients and make a first assessment of potential vulnerabilities in the face of global warming. We detected 40 species from 700 to over 2600 m asl, with progressively less diversity corresponding to higher elevations and lower temperatures. Maximum temperature was weakly related to ant diversity as compared to mean and minimum temperature. In shaping ant diversity, the highest elevation species had wide elevation ranges, consistent with Rapoport’s rule. We documented a fauna characterized by cold-adapted genera, species with wide geographic distributions and presumably high dispersal capabilities, no dietary specializations, and a high frequency of social parasitism. Concerning Bergmann’s rule, average ant species size was not larger in the coldest environments. Red wood ants, characterized by much more populous colonies as compared to the other ant species, had the highest number of ant individuals to be found at intermediate elevations and in woodland habitats. On the other hand, grasslands and shrublands proved to be the most species-rich habitats. Our data lay the groundwork for further investigation on elevational shifts and provide context for the discussion of key aspects of the management and conservation of European alpine ants.

Implications for insect conservation
The cold climate of the European Alps has so far protected its ant fauna from the incursion of alien competitors as compared to what is observed in the Mediterranean region. The scarcity of species with restricted distribution ranges or high-elevation specialists, as well as diet specialists, may grant ants of the European Alps more resilience to climate change as compared to other Alpine arthropod groups. On the other hand, many species are highly interconnected by social parasitism relationships that may be vulnerable to ecological cascade effects. While forest habitats host red wood ants, which are often protected for their important ecological role, the importance of grassland must not be overlooked as they support the highest ant species richness.
Gambling in Victoria: Changes in Participation, Problem Gambling and Gambling Environment Between 2008 and 2018
Authors: Stone Christine Anne , Yeung Kristal , Shaw Lindsay , Billi Rosa 
Published: February 2024

AbstractGambling and its impacts are an important public health issue. The relationship between gambling, problem gambling and gambling harm is complex and dynamic. Replicate prevalence studies are useful for surveillance and monitoring gambling impacts within jurisdictions. The purpose of this study was to compare changes in gambling and problem gambling in the Victorian adult population between 2008 and 2018 by investigating individual gambling activities and exploring their relationship with the Victorian gambling ecosystem. Gambling participation has decreased; problem gambling prevalence has not. Investigation beyond these summary measures reveals important details: (a) Electronic Gaming Machines (EGMs), casino table games, race and sports betting (‘high-risk activities’), informal private betting, and Keno, and their associations with problem gambling endure. Further, the strength of this association is unaffected by changes in product technology, delivery, or the Victorian environment in which they reside, (b) participation in high-risk activities, excluding EGMs, increased while for other activities they decreased, (c) EGMs continue to pose the greatest risk for Victorians, (d) males and young adults continue having a higher problem gambling prevalence rate and preferring both online gambling and high-risk activities (excluding racing favoured by an ageing, older cohort, and Keno, by all ages), and (e) gambling access and exposure proliferated enabling single site multiple gambling opportunities on high-risk activities. Young adults represented a new vulnerable group as they reach the legal gambling age. The most effective interventions (based on major falls in real expenditure (losses) on EGMs, the highest risk activity) were the smoking bans, removal of ATMs from venues and decreases in bet size. There is great potential for prevention, intervention, and minimising harm in the gambling environment.
One (Financial Well-Being) Model Fits All? Testing the Multidimensional Subjective Financial Well-Being Scale Across Nine Countries
Authors: Sorgente Angela , Atay Bünyamin , Aubrey Marc , Bhatia Shikha , Crespo Carla , Fonseca Gabriela , Güneri Oya Yerin , Lep Žan , Lessard David , Negru-Subtirica Oana , Portugal Alda , Ranta Mette , Relvas Ana Paula , Singh Nidhi , Sirsch Ulrike , Zupančič Maja , Lanz Margherita 
Published: February 2024

AbstractA multidimensional model of emerging adults’ subjective financial well-being was proposed (Sorgente and Lanz, Int Journal of Behavioral Development, 43(5), 466–478 2019). The authors also developed a 5-factor scale (the Multidimensional Subjective Financial Well-being Scale, MSFWBS) intending to measure this construct in the European context. To date, data using this instrument have been collected in nine countries: Austria, Canada, Finland, India, Italy, Portugal, Romania, Slovenia, and Turkey. In the current study, data from these countries were analysed to test the validity of this model internationally. In particular, using an international sample of 4,475 emerging adults, we collected the following kinds of validity evidence for the MSFWBS: score structure, reliability, generalizability, convergent, and criterion-related evidence. Findings suggest that the MSFWBS (1) yields valid and reliable scores, and (2) works well in individualistic and economically developed countries, producing comparable scores. Implications for researchers and practitioners are discussed.
The Helmholtz Equation with Uncertainties in the Wavenumber
Authors: Pulch Roland , Sète Olivier 
Published: February 2024

AbstractWe investigate the Helmholtz equation with suitable boundary conditions and uncertainties in the wavenumber. Thus the wavenumber is modeled as a random variable or a random field. We discretize the Helmholtz equation using finite differences in space, which leads to a linear system of algebraic equations including random variables. A stochastic Galerkin method yields a deterministic linear system of algebraic equations. This linear system is high-dimensional, sparse and complex symmetric but, in general, not hermitian. We therefore solve this system iteratively with GMRES and propose two preconditioners: a complex shifted Laplace preconditioner and a mean value preconditioner. Both preconditioners reduce the number of iteration steps as well as the computation time in our numerical experiments.
Novel Fluoroboric Acid Additive for Blend Membrane to be Used in PEM Fuel Cell, Characterization Studies, and Performance Test
Authors: Yagizatli Yavuz , Ar Irfan 
Published: February 2024

AbstractThis study focuses on developing an alternative membrane for PEMFC due to the disadvantages of using Nafion. Fluoroboric acid (FBA) was used as an additive material to SPEEK-PVA blend membranes at different weight ratios (1%, 5%, 7.5%, 10%, and 12.5%), and a synthesis procedure was carried out with the solution-casting. Thermal crosslinking was performed with all membranes. Utilizing FBA, with its highly electronegative fluorine groups, is a novel approach expected to enhance proton conductivity. The structural, morphological, and thermal properties of the synthesized membranes were determined by FTIR, XRD, SEM, TGA-DTG, and DSC. Water uptake capacity (WUC), swelling property, area change, dynamic mechanical analysis, ion exchange capacity (IEC), AC impedance analysis, hydrolytic stability, and oxidative stability analyses were performed for fuel cell applications. Although FBA does not have a crystal structure, the synergy it created with the SPEEK-PVA membrane increased the crystallinity of the membrane and, accordingly, glass transition temperature. SEM images of membranes at a ratio above 7.5% show that agglomerations occur in the structure and this is supported by other analyses. It was determined that the membrane composition with the highest WUC (16.44%), IEC (1.55 meq/g), and proton conductivity (0.57 S/cm) values contained 7.5% FBA from the characterization studies, and a single-cell performance test was actualized with this. 418 mA/cm2 current density and 250.8 mW/cm2 power density were obtained at 0.6 V cell potential, with the membrane containing 7.5% FBA. This study shows that the synthesized membrane, especially the FBA, is a promising option for PEMFC application.
Graphical Abstract
Grazing distribution of wild guanacos and livestock in Patagonian rangelands: an ecological approach to assess mixed carrying capacity and overgrazing risk in extensive pastoral systems
Authors: Rodríguez Victoria , Marino Andrea , Schroeder Natalia 
Published: February 2024

Abstract
Context
Along with forage availability, rangeland’s carrying capacity (CC) is determined by other landscape features limiting the spatial distribution of the animals, such as water sources or topography. However, livestock management is often based on the stock adjustment to an estimated CC, assuming that the animals use the entire paddocks and wild herbivores are absent.

Objectives
Our objectives were to address how the CC estimation deviates from the classic outcome when the effective space use by livestock is considered, and when the forage consumption by co-occurring wild herbivore is accounted for. Finally, we evaluated large herbivores densities regarding this mixed CC.

Methods
Based on herbivore counts and geo-referenced explanatory variables within a ranch of Chubut, Argentina, we predicted sheep and guanaco distribution at a scale of 0.25 km2 cells. Addressing the relationship between the predicted sheep stock and the CC in each cell, we then re-calculated the CC adjusted by spatial use. We also estimated a mixed CC by computing the forage consumption by sheep and guanacos.

Results
Sheep distribution was shaped mainly by drinking water location, promoting over and under-grazed areas. Guanaco distribution pattern opposed livestock density. Accounting for the restrictions in sheep spatial use resulted in a reduction of the estimated CC compared to the classic approach, whereas the mixed approach resulted in higher CC estimates.

Conclusions
Accounting for herbivore presence and distribution modifies the CC estimation and therefore the diagnosis of overstock situations. The proposed adjustments to CC assessment methods can contribute to the sustainable management of livestock and wildlife in rangelands.
Goal-conditioned offline reinforcement learning through state space partitioning
Authors: Wang Mianchu , Jin Yue , Montana Giovanni 
Published: February 2024

AbstractOffline reinforcement learning (RL) aims to create policies for sequential decision-making using exclusively offline datasets. This presents a significant challenge, especially when attempting to accomplish multiple distinct goals or outcomes within a given scenario while receiving sparse rewards. Prior methods using advantage weighting for offline goal-conditioned learning improve policies monotonically. However, they still face challenges from distribution shift and multi-modality that arise due to conflicting ways to reach a goal. This issue is especially challenging in long-horizon tasks, where the presence of multiple, often conflicting, solutions makes it hard to identify a single optimal policy for transitioning from a state to a desired goal. To address these challenges, we introduce a complementary advantage-based weighting scheme that incorporates an additional source of inductive bias. Given a value-based partitioning of the state space, the contribution of actions expected to lead to target regions that are easier to reach, compared to the final goal, is further increased. Our proposed approach, Dual-Advantage Weighted Offline Goal-conditioned RL, outperforms several competing offline algorithms in widely used benchmarks. Furthermore, we provide a theoretical guarantee that the learned policy will not be inferior to the underlying behavior policy.
Goal exploration augmentation via pre-trained skills for sparse-reward long-horizon goal-conditioned reinforcement learning
Authors: Wu Lisheng , Chen Ke 
Published: February 2024

AbstractReinforcement learning often struggles to accomplish a sparse-reward long-horizon task in a complex environment. Goal-conditioned reinforcement learning (GCRL) has been employed to tackle this difficult problem via a curriculum of easy-to-reach sub-goals. In GCRL, exploring novel sub-goals is essential for the agent to ultimately find the pathway to the desired goal. How to explore novel sub-goals efficiently is one of the most challenging issues in GCRL. Several goal exploration methods have been proposed to address this issue but still struggle to find the desired goals efficiently. In this paper, we propose a novel learning objective by optimizing the entropy of both achieved and new goals to be explored for more efficient goal exploration in sub-goal selection based GCRL. To optimize this objective, we first explore and exploit the frequently occurring goal-transition patterns mined in the environments similar to the current task to compose skills via skill learning. Then, the pre-trained skills are applied in goal exploration with theoretical justification. Evaluation on a variety of spare-reward long-horizon benchmark tasks suggests that incorporating our method into several state-of-the-art GCRL baselines significantly boosts their exploration efficiency while improving or maintaining their performance.
Review: Human stem cell-based 3D in vitro angiogenesis models for preclinical drug screening applications
Authors: Esparza Aibhlin , Jimenez Nicole , Borrego Edgar A. , Browne Shane , Natividad-Diaz Sylvia L. 
Published: February 2024

Abstract
Vascular diseases are the underlying pathology in many life-threatening illnesses. Human cellular and molecular mechanisms involved in angiogenesis are complex and difficult to study in current 2D in vitro and in vivo animal models. Engineered 3D in vitro models that incorporate human pluripotent stem cell (hPSC) derived endothelial cells (ECs) and supportive biomaterials within a dynamic microfluidic platform provide a less expensive, more controlled, and reproducible platform to better study angiogenic processes in response to external chemical or physical stimulus. Current studies to develop 3D in vitro angiogenesis models aim to establish single-source systems by incorporating hPSC-ECs into biomimetic extracellular matrices (ECM) and microfluidic devices to create a patient-specific, physiologically relevant platform that facilitates preclinical study of endothelial cell-ECM interactions, vascular disease pathology, and drug treatment pharmacokinetics. This review provides a detailed description of the current methods used for the directed differentiation of human stem cells to endothelial cells and their use in engineered 3D in vitro angiogenesis models that have been developed within the last 10 years.
SR-MACL: Session-Based Recommendation with Multi-layer Aggregation Augmentation in Contrastive Learning
Authors: Gao Shiwei , Zeng Yufeng , Dang Xiaochao , Dong Xiaohui 
Published: February 2024

AbstractSession-based recommendation (SBR) aims to predict the next item of interest in chronological order based on a given sequence of short-term behaviour of anonymous users. Due to the limited data available for short-term user interactions, its performance is more susceptible to data sparsity problems than traditional recommendation methods. Contrastive learning is often used to solve the data sparsity problem due to its ability to extract general features from the raw data. Existing session-based recommendation methods based on graph contrastive learning typically build graph contrastive learning by using information from other sessions to generate augmented views. While this avoids the problem that the use of dropout in traditional contrast learning methods can cause damage to the session context, it inevitably introduces irrelevant item information, which interferes with accurately modelling user interests and leads to sub-optimal model performance. To address these issues, we propose a new session recommendation method based on multi-layer aggregation augmentation contrastive learning, namely SR-MACL. In SR-MACL we construct a contrastive view by adding noise to the embedding representation and forming a contrastive embedding representation by multi-layer aggregation, which not only effectively solves the problem that traditional graph enhancement methods can destroy the context of the whole session, but also avoids the interference of irrelevant items. Experimental results on three real datasets have shown that SR-MACL can improve the accuracy of recommendation results and predict the user's next interaction more effectively.
Designing policies that could work: understanding the interaction between policy design spaces and organizational responses in public sector
Authors: Capano Giliberto , Lepori Benedetto 
Published: February 2024

AbstractThe goal of this paper is to contribute toward bridging the gap between policy design and implementation by focusing on domains, such as education, healthcare and community services, where policy implementation is largely left to the autonomous decision of public service providers, which are strategic actors themselves. More specifically, we suggest that two characteristics of policy design spaces in which policies are designed, i.e., the level of ideational coherence and the prevailing function of the adopted policy instruments, generate systematic patterns of responses in terms of the extent of compliance with policy goals, the presence of strategic gaming and possible defiance. We illustrate our model through a contrastive case study of the introduction of performance-based funding in the higher education sector in four European countries (France, Italy, Norway, and the United Kingdom). Our analysis displays that policy designs chosen by governments to steer public systems have different trade-offs in terms of responses of the public organizations involved that are essential to effectively implement governmental policies. The model we are proposing provides therefore a framework to understand how these interactions unfold in specific contexts, what are their effects on the achievement of policy goals and how policymakers could exploit their degrees of freedom in policy design to reduce unwanted effects.
DFT and QSAR study of Catechol-O-methyltransferase (COMT) as inhibitors for Parkinson’s disease treatment
Authors: Sherif Salma , Sameh Ahmed , Salah Sohaila Mohammed , Omar Amina , Elhaes Hanan , Ibrahim Asmaa , Refaat Ahmed , Ibrahim Medhat A. 
Published: February 2024

AbstractParkinson’s disease is characterized by a lack of the neurotransmitter or cell-signaling molecule dopamine. Levodopa is a well-known drug for Parkinson’s disease since it induces dopamine. Catechol-O-methyltransferase (COMT) are enzymes that break down levodopa, limiting the amount delivered to the brain. COMT inhibitors act by extending the duration of action of levodopa, thus improving the amount of time benefit from levodopa. There are several FDA-approved COMT inhibitors used, such as Entacapone and Tolcapone. Tolcapone can penetrate blood-brain barrier (BBB), but most of the drug stays in the plasma because its high protein bound, and it has severe side effects, while Entacapone cannot penetrate BBB, which reduces drug efficiency. This study aims to design higher-efficiency drug inhibitors by investigating the physical properties in terms of total energy, total dipole moment and HOMO/LUMO band gap at DFT: B3LYP level using the LAN2DZ basis set, in addition to quantitative structure activity relationship (QSAR) calculations to test the biological activity of these drug inhibitors for the treatment of Parkinson’s disease.
The Oxidation Behaviors of NiCoCrAlY Coatings After Pre-Oxidation Treatment During High-Temperature Oxidation at 800 ℃ and 900 ℃
Authors: Negami Masahiro , Yamabe-Mitarai Yoko 
Published: February 2024

AbstractThermal barrier coatings (TBCs) are essential for protecting the high-temperature components in gas turbines. However, the durability of TBCs is limited, and new technologies to improve their lifetime are necessary. This study focuses on the pre-oxidation treatment of the NiCoCrAlY bond coat in TBCs to reduce the growth rate of the thermally grown oxide (TGO) and improve the TBC lifetime. The mechanism of the TGO growth rate reduction by the pre-oxidation treatment of NiCoCrAlY was investigated. Oxidation behaviors of the surface of NiCoCrAlY coating samples with or without pre-oxidation treatment were evaluated in air at 800 °C and 900 °C. In-situ X-ray diffraction (XRD) measurements and isothermal oxidation tests were performed. The obtained results revealed that the growth rate of TGO is significantly suppressed by α-Al2O3 layer formed by the pre-oxidation treatment. The generation of γ-Al2O3 and θ-Al2O3, which are typically formed below 900 °C, was significantly reduced by pre-oxidation. It is suggested that this reduction suppresses of the TGO growth.