bluuebunny/crossref_metadata_2025_split huggingface dataset:
Skeletal Findings Consistent with Signs of Rigorous Jewish Religious Practice in Four Skeletons from Qumran (Near-East), First-Century CE
Authors: Charlier P. , Conlon E. , Huynh I. , Humbert J. B. 
Published: January 2025

Abstract
Anthropological and palaeopathological examination of four male skeletons from Qumran (Near-East) revealed skeletal lesions that may be linked to an intense practice of traditional Jewish rituals within this hyper-religious community of the first-century CE: chronic inflammation of the external auditory canals linked to frequent immersion in sacred baths (mikvah), and osteo-articular lesions following intense and repeated genuflection and anteflexion of the trunk.
Good classification matters: conceptual engineering in data science
Authors: Köhler Sebastian 
Published: January 2025

Abstract
Recent years have seen incredible advances in our abilities to gather and store data, as well as in the computational power and methods—most prominently in machine learning—to do things with those data. These advances have given rise to the emerging field “data science.” Because of its immense power for providing practically useful information about the world, data science is a field of increasing importance. This paper argues that a core part of what data scientists are doing should be understood as conceptual engineering. At all stages of the data science process, data scientists need to deliberate about, evaluate, and make classificatory choices in a variety of ways, including as part of training and evaluating machine learning models. Viewing these activities as involved in conceptual engineering offers a new way to think about them, one that helps to clarify what is at stake in them, what sorts of considerations are relevant, and how to systematically think about the choices faced. Given the increasing importance of data science, if conceptual engineering is relevant for activities in data science, this also highlights the relevance and impact of conceptual engineering as a method. Furthermore, the paper also suggests that machine learning opens distinctive and novel ways in which data scientists engage in conceptual engineering.
Deep learning reveals diverging effects of altitude on aging
Authors: Teklu Amanuel Abraha , Heckenbach Indra , Petr Michael Angelo , Bakula Daniela , Keijzers Guido , Scheibye-Knudsen Morten 
Published: January 2025

Abstract
Aging is influenced by a complex interplay of multifarious factors, including an individual’s genetics, environment, and lifestyle. Notably, high altitude may impact aging and age-related diseases through exposures such as hypoxia and ultraviolet (UV) radiation. To investigate this, we mined risk exposure data (summary exposure value), disease burden data (disability-adjusted life years (DALYs)), and death rates and life expectancy from the Global Health Data Exchange (GHDx) and National Data Management Center for Health of Ethiopia for each subnational region of Ethiopia, a country with considerable differences in the living altitude. We conducted a cross-sectional clinical trial involving 227 highland and 202 lowland dwellers from the Tigray region in Northern Ethiopia to gain a general insight into the biological aging at high altitudes. Notably, we observed significantly lower risk exposure rates and a reduced disease burden as well as increased life expectancy by lower mortality rates in higher-altitude regions of Ethiopia. When assessing biological aging using facial photographs, we found a faster rate of aging with increasing elevation, likely due to greater UV exposure. Conversely, analysis of nuclear morphologies of peripheral blood mononuclear cells (PBMCs) in blood smears with five different senescence predictors revealed a significant decrease in DNA damage-induced senescence in both monocytes and lymphocytes with increasing elevation. Overall, our findings suggest that disease and DNA damage-induced senescence decreases with altitude in agreement with the idea that oxidative stress may drive aging.
Pedagogical AI conversational agents in higher education: a conceptual framework and survey of the state of the art
Authors: Yusuf Habeeb , Money Arthur , Daylamani-Zad Damon 
Published: January 2025

Abstract
The ever-changing global educational landscape, coupled with the advancement of Web3, is seeing rapid changes in the ways pedagogical artificially intelligent conversational agents are being developed and used to advance teaching and learning in higher education. Given the rapidly evolving research landscape, there is a need to establish what the current state of the art is in terms of the pedagogical applications and technological functions of these conversational agents and to identify the key existing research gaps, and future research directions, in the field. A literature survey of the state of the art of pedagogical AI conversational agents in higher education was conducted. The resulting literature sample (n = 92) was analysed using thematic template analysis, the results of which were used to develop a conceptual framework of pedagogical conversational agents in higher education. Furthermore, a survey of the state of the art was then presented as a function of the framework. The conceptual framework proposes that pedagogical AI conversational agents can primarily be considered in terms of their pedagogical applications and their pedagogical purposes, which include pastoral, instructional and cognitive, and are further considered in terms of mode of study and intent. The technological functions of the agents are also considered in terms of embodiment (embodied/disembodied) and functional type and features. This research proposes that there are numerous opportunities for future research, such as, the use of conversational agents for enhancing assessment, reflective practice and to support more effective administration and management practice. In terms of technological functions, future research would benefit from focusing on enhancing the level of personalisation and media richness of interaction that can be achieved by AI conversational agents.
Wie kann Gender Mainstreaming-Beratung für Fachvorhaben in einer Landesverwaltung gelingen?
Authors: Thege Britta , Jansen-Schulz Bettina 
Published: January 2025

Zusammenfassung
Der Beitrag beschreibt erste Erfahrungen einer externen Gender Mainstreaming Beratung von Beteiligten verschiedener Fachvorhaben einer Landesverwaltung. Darin wurden die Anwendung einer 4‑Schritte-Matrix zur Genderanalyse erprobt und chancengerechte Umsetzungsmaßnahmen für die jeweiligen Fachvorhaben entwickelt. Die Beratung bezog sich auf die Befähigung der Beteiligten, gleichstellungsrelevante Aspekte bereits in der Planung eines Vorhabens identifizieren zu können, um mögliche geschlechtsspezifische Diskriminierungen zu vermeiden oder bestehende Nachteile auszugleichen.
Lipid Changes 10–15 Years After Roux-en-Y Gastric Bypass: A Prospective Observational Study
Authors: Barkhall Eirin Rosø , Tro Johanne , Sandvik Jorunn , Nymo Siren , Kulseng Bård , Johnsen Gjermund , Hoff Dag Arne Lihaug , Hole Torstein 
Published: January 2025

Abstract

Background
Several studies have documented a beneficial short-term effect on lipid profile after Roux-en-Y gastric bypass (RYGB), but there is limited data on long-term changes.

Objectives
To describe long-term (> 10 years) changes in lipid profile after RYGB and to explore the relationship of lipid changes to changes in weight and baseline and demographic parameters.

Methods
The BAROBS study is a prospective observational study post RYGB conducted at three different hospitals. Surgical procedures were performed between 2003 and 2009, and the collection of data was in 2018–2020. Data on lipid profile, weight, body mass index (BMI), percentage of total weight loss (%TWL), and pre- and postoperative type II diabetes mellitus (DMII) was collected at baseline, 1–2, 5, and 10 years post-surgery and was available for 314 of 546 patients in the study.

Results
The mean (SD) follow-up was 11.5(± 1.5) years, with a mean reduction of 11.7% for LDL, 29.7% for TG, and 7.7% for total cholesterol compared to baseline. Except for HDL and total-/HDL-cholesterol-ratio, all lipid variables reached their greatest change after 1–2 years with an attenuation of changes at end of study. HDL and total-/HDL-cholesterol-ratio had stable values from 5 to 10 years post-surgery. Lipid profile improved more in patients with greater weight loss. There was a 59% reduction in DMII at end of study, and there was a significant relation between preoperative DMII and long-term lipid values.

Conclusion
There is an improvement of all lipid parameters after 10 years post RYGB related to both the magnitude of weight loss and the presence of DMII.

Graphical Abstract
Meta-Analysis of Larval Bivalve Growth in Response to Ocean Acidification and its Application to Sea Scallop Larval Dispersal in the Mid-Atlantic Bight
Authors: Wright-Fairbanks Elizabeth K. , Munroe Daphne M. , Hunter Elias J. , Wilkin John , Saba Grace K. 
Published: January 2025

Abstract
Ocean acidification, caused by increasing atmospheric carbon dioxide and coastal physical, biological, and chemical processes, is an ongoing threat to carbonate-utilizing organisms living in productive coastal shelves. Bivalves exposed to acidification have shown reduced growth, reproduction, and metabolic processes, with larval stages exhibiting the greatest susceptibility. Here, we compile results from published studies on larval bivalve growth responses to acidification to estimate a relationship between larval growth and seawater aragonite saturation state. We then apply this relationship to a larval dispersal individual-based model for Atlantic sea scallops (Placopecten magellanicus), an economically vital species in the Mid-Atlantic Bight that is historically under-studied in acidification research. To date, there have been no published studies on sea scallop larval response to ocean acidification. Model simulations allowed the identification of potential impacts of acidification on scallop success in the region. Results show that larval sea scallops that are sensitive to ocean acidification had a 17% lower settlement success rate and over 50% reduction in larval passage between major Mid Atlantic Bight fisheries habitats than those that are not sensitive to acidification. Additionally, temperature and ocean acidification interact as drivers of larval success, with aragonite saturation states > 3.0 compensating for temperature-induced mortality (> 19 ˚C) in some cases. This balance between drivers influences larval settlement success across spatial and interannual scales in the Mid Atlantic Bight.
Fördern Frauen in politischen Ämtern auf lokaler Ebene die politische Deliberation?
Authors: Stocker Simon 
Published: January 2025

Zusammenfassung
Der Beitrag geht der Frage nach, welchen Einfluss Frauen in kommunalpolitischen Ämtern auf die Nutzung dialogorientierter Beteiligungsverfahren haben. Grundlage der Analyse ist eine einzigartige Zusammenstellung makro-quantitativer Daten aus 817 Gemeinden in Baden-Württemberg. Die Ergebnisse zeigen einen signifikanten positiven Einfluss ausgehend von der Frauenpräsenz im Gemeinderat und dem Bürgermeister*innenamt auf die Anzahl in den Gemeinden stattfindender dialogischer Beteiligungsereignisse. Außerdem zeigt sich, dass ein höherer Sitzanteil der Grünen in den Gemeinderäten mit mehr dialogischer Beteiligung assoziiert ist, wobei ein Teil dieses Zusammenhangs durch den Frauenanteil im Gemeinderat mediiert wird.
Causally Mapping the Cerebellum in Children and Young Adults: from Motor to Cognition
Authors: Veyrie Marina , Beffara Bertrand , Richard Nathalie , Mottolese Carmine , Szathmari Alexandru , Di Rocco Federico , Faure Conter Cécile , Leblond Pierre , Desmurget Michel , Cristofori Irene , Beuriat Pierre-Aurélien 
Published: January 2025

Abstract
While the cerebellum’s role in orchestrating motor execution and routines is well established, its functional role in supporting cognition is less clear. Previous studies claim that motricity and cognition are mapped in different areas of the cerebellar cortex, with an anterior/posterior dichotomy. However, most of the studies supporting this claim either use correlational methods (neuroimaging) or are lesion studies that did not consider central covariates (such as age, gender, treatment presence, and deep nuclei impairment) known to influence motor and cognitive recoveries in patients. Here, we used voxel-based lesion-symptom mapping (VLSM) on children and young adults having undergone cerebellar tumor resection. This approach allows to control for these covariates and evaluate causal relationships between brain anatomy and behavioral performances to disentangle the anatomic substrate of motor and cognitive functions. VLSM analyses showed that both motor and cognitive impairments were greater in children and young adults with lesions of the posterior cerebellum. These results highlight distinct and overlapping structural correlates of motor and cognitive performance in the cerebellum and are consistent with structural and functional hypotheses of integration of the cerebellum in motor and cognitive functions.
Promoting inclusion of peers with special educational needs: effects of a curriculum-based diversity awareness program
Authors: Wüthrich Sergej , Sahli Lozano Caroline , Wicki Matthias 
Published: January 2025

Abstract
Students with special educational needs (SEN) often face rejection from peers. Research suggests that intervention programs can enhance students’ attitudes and social participation of peers with SEN. However, many teachers lack the resources or time to implement comprehensive programs. The extent to what easy-to-implement teaching units have positive effects is less clear. Based on the Theory of Planned Behavior, this study assessed the effect of a series of classroom lessons based on the teaching resource Prinzip Vielfalt on students’ attitudes, subjective norms, perceived behavioral control (PBC), and their intentions to include peers with SEN.
In a cluster-controlled trial, 51 elementary school classes (3rd–6th grade) were assigned to either the experimental or waiting-control group based on the timing of teachers’ registration for a continuing education course. The experimental group consisted of 34 classes (652 students), where teachers implemented a standardized 12-lesson plan over a 6-week period, while the control group continued with their regular curriculum. Data were collected at three points: pre-test, post-test, and follow-up three months later. Student self-report measures were analyzed using mixed-effects and mediation models in R.
Analyses indicated no significant long-term effects for PBC or inclusion intentions. However, attitudes and subjective norms toward peers with disabilities improved significantly. Further, mediation analyses revealed significant indirect effects of attitudes and subjective norms on inclusion intentions. Thus, while the intervention did not directly influence intentions, it had a positive effect on attitudes and subjective norms, which could enhance inclusive behavior over time. Thus, carefully constructed, accessible, and easy-to-implement teaching resources such as Prinzip Vielfalt demonstrate promising effects on inclusive peer behavior.
A novel group-based framework for nature-inspired optimization algorithms with adaptive movement behavior
Authors: Robson Adam , Mistry Kamlesh , Woo Wai-Lok 
Published: January 2025

Abstract
This paper proposes two novel group-based frameworks that can be implemented into almost any nature-inspired optimization algorithm. The proposed Group-Based (GB) and Cross Group-Based (XGB) framework implements a strategy which modifies the attraction and movement behaviors of base nature-inspired optimization algorithms and a mechanism that creates a continuing variance within population groupings, while attempting to maintain levels of computational simplicity that have helped nature-inspired optimization algorithms gain notoriety within the field of feature selection. Through this functionality, the proposed framework seeks to increase search diversity within the population swarm to address issues such as premature convergence, and oscillations within the swarm. The proposed frameworks have shown promising results when implemented into the Bat algorithm (BA), Firefly algorithm (FA), and Particle Swarm Optimization algorithm (PSO), all of which are popular when applied to the field of feature selection, and have been shown to perform well in a variety of domains, gaining notoriety due to their powerful search capabilities.
Preference learning based deep reinforcement learning for flexible job shop scheduling problem
Authors: Liu Xinning , Han Li , Kang Ling , Liu Jiannan , Miao Huadong 
Published: January 2025

Abstract
The flexible job shop scheduling problem (FJSP) holds significant importance in both theoretical research and practical applications. Given the complexity and diversity of FJSP, improving the generalization and quality of scheduling methods has become a hot topic of interest in both industry and academia. To address this, this paper proposes a Preference-Based Mask-PPO (PBMP) algorithm, which leverages the strengths of preference learning and invalid action masking to optimize FJSP solutions. First, a reward predictor based on preference learning is designed to model reward prediction by comparing random fragments, eliminating the need for complex reward function design. Second, a novel intelligent switching mechanism is introduced, where proximal policy optimization (PPO) is employed to enhance exploration during sampling, and masked proximal policy optimization (Mask-PPO) refines the action space during training, significantly improving efficiency and solution quality. Furthermore, the Pearson correlation coefficient (PCC) is used to evaluate the performance of the preference model. Finally, comparative experiments on FJSP benchmark instances of varying sizes demonstrate that PBMP outperforms traditional scheduling strategies such as dispatching rules, OR-Tools, and other deep reinforcement learning (DRL) algorithms, achieving superior scheduling policies and faster convergence. Even with increasing instance sizes, preference learning proves to be an effective reward mechanism in reinforcement learning for FJSP. The ablation study further highlights the advantages of each key component in the PBMP algorithm across performance metrics.
Chevalley groups over $${{\mathbb {Z}}}$$: a representation-theoretic approach
Authors: Ali Abid , Carbone Lisa , Murray Scott H. 
Published: January 2025

Abstract
Let

$$G({{\mathbb {Q}}})$$

G
(
Q
)

be a simply connected Chevalley group over

$${{\mathbb {Q}}}$$

Q

corresponding to a simple Lie algebra

$${\mathfrak {g}}$$

g

over

$${{\mathbb {C}}}$$

C

. Let V be a finite-dimensional faithful highest weight

$${\mathfrak {g}}$$

g

-module and let

$$V_{{\mathbb {Z}}}$$

V
Z

be a Chevalley

$${{\mathbb {Z}}}$$

Z

-form of V. Let

$$\Gamma ({{\mathbb {Z}}})$$

Γ
(
Z
)

be the subgroup of

$$G({{\mathbb {Q}}})$$

G
(
Q
)

that preserves

$$V_{{{\mathbb {Z}}}}$$

V
Z

and let

$$G({{\mathbb {Z}}})$$

G
(
Z
)

be the group of

$${{\mathbb {Z}}}$$

Z

-points of

$$G({{\mathbb {Q}}})$$

G
(
Q
)

. Then

$$G({{\mathbb {Q}}})$$

G
(
Q
)

is integral if

$$G({{\mathbb {Z}}})=\Gamma ({{\mathbb {Z}}})$$

G
(
Z
)
=
Γ
(
Z
)

. Chevalley’s original work constructs a scheme-theoretic integral form of

$$G({{\mathbb {Q}}})$$

G
(
Q
)

which equals

$$\Gamma ({{\mathbb {Z}}})$$

Γ
(
Z
)

. Here we give a representation-theoretic proof of integrality of

$$G({{\mathbb {Q}}})$$

G
(
Q
)

using only the action of

$$G({{\mathbb {Q}}})$$

G
(
Q
)

on V, rather than the language of group schemes. We discuss the challenges and open problems that arise in trying to extend this to a proof of integrality for Kac–Moody groups over

$${{\mathbb {Q}}}$$

Q

.
Association of frailty index with incidence of chronic kidney disease: China Health and Retirement Longitudinal Study
Authors: Zhang Lisha , Zhang Yan , He Yanru , Deng Fuxue , Xue Jiahong 
Published: January 2025

Abstract

Aim
Frailty is an important risk factor for a wide range of chronic diseases and for mortality risk. This study aims to explore the relationship between frailty and incidence of chronic kidney disease (CKD), particularly on the change and accumulation of frailty.

Methods
Frailty status was assessed using the frailty index (FI, constructed by 31 items) and categorized as robust, pre-frail, and frail. The accumulation and change in frailty were assessed on the basis of frailty status at baseline and a second survey 4 years after baseline. Logistic regression was used to estimate the association between frailty and developing CKD.

Results
A total of 3597 participants (mean age: 59.08 ± 8.94 years old, male: 49.9%) from CHARLS were included. Participants with pre-frailty or frailty status had a higher risk of developing CKD compared with robust participants (pre-frail vs robust, OR 1.78, 95% CI 1.37–2.32, p < 0.001; frail vs robust, OR 2.52, 95% CI 1.67–3.79, p < 0.001). Participants who had a robust status in the two surveys had a significantly lower risk of developing CKD (OR 0.51, 95% CI 0.36–0.75, p < 0.001) compared with those who never had a robust status.

Conclusion
Frailty status is significantly associated with the incidence of CKD. The risk of CKD was lower in those who ever had a robust status than in participants who never had a robust status.
Adapting to climate change and multi-risk governance: toward sustainable adaptation and enhancing urban resilience—Indonesia
Authors: Abdillah Abdillah , Widianingsih Ida , Buchari Rd Ahmad , Nurasa Heru 
Published: January 2025

Abstract
Climate change has contributed to an increase in natural catastrophes over the past five years in Indonesia, causing various forms of damage in urban areas and posing a severe danger to multi-risk governance for municipal governments in Indonesia. This study explores how multi-risk governance strategies encourage sustainable adaptation to climate change and increase urban resilience in Bandung and Makassar City, Indonesia. This study method uses a qualitative-exploratory approach with a case study in two (2) climate-vulnerable cities in Indonesia. Data analysis uses qualitative-interactive analysis. The results of this study show that the impact of climate change in Bandung and Makassar City, Indonesia has caused an increase in the potential for erosion, reduced wetlands along the coast, an increase in the rate of seawater intrusion, a decrease in food production, damage to infrastructure, a reduction in clean water sources, an increase in disease. respiratory, floods, droughts, and other hydrological disasters. This has resulted in many climate approaches and actions being taken to respond to the impact of climate change in Indonesia (Bandung and Makassar City), the results of which are still not optimal to date. This study suggests a sustainable adaptation approach to climate action in Bandung and Makassar City which prioritizes social justice and environmental integrity so that it has a real impact on community vulnerability and environmental damage due to the impacts of climate change. The contribution of this study provides sufficient insight into the institutional approaches and adaptive sustainability measures needed to promote resilience in Indonesia. At the same time, this study will be a useful reference in future research on multi-risk governance and sustainable adaptation strategy for climate action and enhancing urban governance.