bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning evaluation of a hypertension screening program in a university workforce over five years
Authors: Adeleke Olumide , Adebayo Segun , Aworinde Halleluyah , Adeleke Oludamola , Adeniyi Abidemi Emmanuel , Aroba Oluwasegun Julius 
Published: December 2024

AbstractThe global prevalence of hypertension continues excessively elevated, especially among low- and middle-income nations. Workplaces provide tremendous opportunities as a unique, easily accessible and practical avenue for early diagnosis and treatment of hypertension among the workforce class. The evaluation of such a Workplace Screening Strategy can give insight into its possible effects. Innovative machine learning approaches like k-means clustering are underutilized for such assessments. We set out to use this technology to analyze the results of our university’s yearly health checkup of the employees for hypertension. An anonymized dataset including the demographics and blood pressure monitoring information gathered from workers in various departments/units of a learning organization. The overall amount of samples or data values is 1, 723, and the supplied dataset includes six attributes, such as year group (2018, 2019, 2021, 2022), Department/Unit (academic and non-academic), and gender (male and female), with the intended output being the blood pressure status (low, normal, and high). The dataset was analyzed using machine learning approaches. In this longitudinal study, it was discovered that the average age for the workforce is 42. Similarly, it was revealed that hypertension was common among employees over the age of 40, regardless of gender or occupational type (academic or nonacademic). The data also found that there was a consistent drop in the prevalence of hypertension from 2018 to 2022. According to the study findings, the use of machine learning algorithms for periodic evaluations of workplace health status monitoring initiatives (particularly for hypertension) is feasible, realistic, and sustainable in diagnosing and controlling hypertension among those in the workforce.
Incorporating immune cell surrogates into a full-thickness tissue equivalent of human skin to characterize dendritic cell activation
Authors: Hölken Johanna Maria , Wurz Anna-Lena , Friedrich Katja , Böttcher Patricia , Asskali Dounia , Stark Holger , Breitkreutz Jörg , Buhl Timo , Vierkotten Lars , Mewes Karsten Rüdiger , Teusch Nicole 
Published: December 2024

AbstractIn the past decades studies investigating the dendritic cell (DC) activation have been conducted almost exclusively in animal models. However, due to species-specific differences in the DC subsets, there is an urgent need for alternative in vitro models allowing the investigation of Langerhans cell (LC) and dermal dendritic cell (DDC) activation in human tissue. We have engineered a full-thickness (FT) human skin tissue equivalent with incorporated LC surrogates derived from the human myeloid leukemia-derived cell line Mutz-3, and DDC surrogates generated from the human leukemia monocytic cell line THP-1. Topical treatment of the skin models encompassing Mutz-LCs only with nickel sulfate (NiSO4) or 1-chloro-2,4-dinitrobenzene (DNCB) for 24 h resulted in significant higher numbers of CD1a positive cells in the dermal compartment, suggesting a sensitizer-induced migration of LCs. Remarkably, exposure of the skin models encompassing both, LC and DDC surrogates, revealed an early sensitizer-induced response reflected by increased numbers of CD1a positive cells in the epidermis and dermis after 8 h of treatment. Our human skin tissue equivalent encompassing incorporated LC and DDC surrogates allows the investigation of DC activation, subsequent sensitizer identification and drug discovery according to the principles of 3R.
Hu similarity coefficient: a clinically oriented metric to evaluate contour accuracy in radiation therapy
Authors: Hu Harold Yang , Hu Shaw Yang , Yang Min , Hu Yanle 
Published: December 2024

AbstractTo propose a clinically oriented quantitative metric, Hu similarity coefficient (HSC), to evaluate contour quality, gauge the performance of auto contouring methods, and aid effective allocation of clinical resources. The HSC is defined as the ratio of the number of boundary points of the initial contour that doesn’t require modifications over the number of boundary points of the final adjusted contour. To demonstrate the clinical utility of the HSC in contour evaluation, we used publicly available pelvic CT data from the Cancer Imaging Archive. The bladder was selected as the organ of interest. It was contoured by a certified medical dosimetrist and reviewed by a certified medical physicist. This contour served as the ground truth contour. From this contour, we simulated two contour sets. The first set had the same Dice similarity coefficient (DSC) but different HSCs, whereas the second set kept a constant HSC while exhibiting different DSCs. Four individuals were asked to adjust the simulated contours until they met clinical standards. The corresponding contour modification times were recorded and normalized by individual’s manual contouring times from scratch. The normalized contour modification time was correlated to the HSC and DSC to evaluate their suitability as quantitative metrics assessing contour quality. The HSC maintained a strong correlation with the normalized contour modification time when both sets of simulated contours were included in analysis. The correlation between the DSC and normalized contour modification time, however, was weak. Compared to the DSC, the HSC is more suitable for evaluating contour quality. We demonstrated that the HSC correlated well with the average normalized contour modification time. Clinically, contour modification time is the most relevant factor in allocating clinical resources. Therefore, the HSC is better suited than the DSC to assess contour quality from a clinical perspective.
Rarγ-Foxa1 signaling promotes luminal identity in prostate progenitors and is disrupted in prostate cancer
Authors: De Felice Dario , Alaimo Alessandro , Bressan Davide , Genovesi Sacha , Marmocchi Elisa , Annesi Nicole , Beccaceci Giulia , Dalfovo Davide , Cutrupi Federico , Medaglia Stefano , Foletto Veronica , Lorenzoni Marco , Gandolfi Francesco , Kannan Srinivasaraghavan , Verma Chandra S , Vasciaveo Alessandro , Shen Michael M , Romanel Alessandro , Chiacchiera Fulvio , Cambuli Francesco , Lunardi Andrea 
Published: December 2024

Abstract
Retinoic acid (RA) signaling is a master regulator of vertebrate development with crucial roles in body axis orientation and tissue differentiation, including in the reproductive system. However, a mechanistic understanding of how RA signaling governs cell lineage identity is often missing. Here, leveraging prostate organoid technology, we show that RA signaling orchestrates the commitment of adult mouse prostate progenitors to glandular identity, epithelial barrier integrity, and specification of prostatic lumen. RA-dependent RARγ activation promotes the expression of Foxa1, which synergizes with the androgen pathway for luminal expansion, cytoarchitecture and function. FOXA1 mutations are common in prostate and breast cancers, though their pathogenic mechanism is incompletely understood. Combining functional genetics with structural modeling of FOXA1 folding and chromatin binding analyses, we discover that FOXA1F254E255 is a loss-of-function mutation compromising its transcriptional function and luminal fate commitment of prostate progenitors. Overall, we define RA as an instructive signal for glandular identity in adult prostate progenitors. Importantly, we identify cancer-associated FOXA1 indels affecting residue F254 as loss-of-function mutations promoting dedifferentiation of adult prostate progenitors.
Machine learning‐based multivariate forecasting of electric vehicle charging station demand
Authors: Alam Najmul , Rahman M. A. , Islam Md. Rashidul , Hossain M. J. 
Published: December 2024

AbstractThe exponential rise of electric vehicles (EVs) is transforming the global automobile industry, driving a shift towards greater cleanliness and environmental sustainability. EV charging stations (EVCSs) play a pivotal role in this massive transition towards EVs, where accurate forecasting of EVCS demand is crucial for seamlessly integrating EVs into existing power grids. Most of the existing research mainly concentrates on univariate forecasting, neglecting the multiple factors influencing EVCS demand. Hence, this study offers a comparative analysis of different algorithms for univariate forecasting and multivariate forecasting, where the multivariate scheme incorporates metadata such as charging time, greenhouse gas savings, and gasoline savings. The experimental results indicate the superiority of the multivariate scheme over the univariate forecasting. For multivariate forecasting, the gated recurrent unit (GRU) has outperformed other models such as categorical boosting (Catboost), recurrent neural network (RNN), long short‐term memory (LSTM), extreme gradient boosting (XGBoost), random forest, convolutional neural network (CNN), CNN + LSTM, and LSTM + LSTM. The results of this study emphasize the significance of using the GRU model for multivariate forecasting with metadata during normal and noisy scenarios to yield more reliable and accurate predictions. This approach enhances decision‐making, policy development, and efficient grid integration in the growing EV sector.
Fault diagnosis of inter‐turn short circuits in PMSM based on deep regulated neural network
Authors: Mesai Belgacem Ahmed , Hadef Mounir , Ali Enas , Elsayed Salah K. , Paramasivam Prabhu , Ghoneim Sherif S. M. 
Published: December 2024

AbstractPermanent Magnet Synchronous Machine (PMSM) is widely utilised in numerous industrial applications due to its precise control capabilities. However, these motors frequently encounter operational faults, potentially leading to severe safety and performance issues. Consequently, effective health monitoring techniques for early fault detection are essential to maintain optimal performance and extend the lifespan of these systems. This study presents a qualification‐based methodology for diagnosing faults in three‐phase PMSMs through vibration–current data fusion analysis. The stator faults, specifically inter‐turn short circuits (ITSC) induced via bypassing resistances, were investigated using experimental data from a custom‐built test rig. The collected current and vibration signals were transformed into statistical features. Various operating scenarios were diagnosed utilising a deep regulated neural network (RegNet), an improved convolutional neural network based on an enhanced residual architecture. The proposed approach was assessed through various metrics including training efficiency, precision, recall, f1‐score, and accuracy, and compared against several neural network methods. The findings reveal that the proposed RegNet model achieves perfect accuracy, attaining 100%. This research highlights the efficacy of data fusion analysis and deep learning in fault diagnosis, facilitating proactive maintenance strategies and improving the reliability of PMSMs in diverse industrial applications and renewable energy systems.
RABBIT-SpA – nationale Registerdaten zu
Spondyloarthritiden
Authors: Regierer Anne C. , Weiß Anja 
Published: December 2024

ZusammenfassungSeit 2017 wird im Deutschen Rheuma-Forschungszentrum das Krankheitsregister
RABBIT-SpA für die axiale Spondyloarthritis und die Psoriasis-Arthritis
durchgeführt. Fast 80 rheumatologische Einrichtungen in ganz Deutschland sind
aktiv beteiligt. Es liegen inzwischen Daten von je über 1.800 Patient:innen für
beide Erkrankungen vor. Da die Patient:innen zu Beginn einer neuen Therapie
eingeschlossen werden, ist die Krankheitsaktivität im Vergleich zu anderen
Kohorten aus dem Versorgungsalltag relativ hoch. Es wurden bereits einige
Analysen der RABBIT-SpA-Patient:innen publiziert. Es konnte zum Beispiel gezeigt
werden, dass die Therapieretention bei PsA-Patient:innen, die entweder mit einer
b/tsDMARD-Monotherapie oder einer Kombination eines b/tsDMARDs mit MTX behandelt
wurden, gleich war. Eine Analyse zur mentalen Gesundheit zeigte, dass bei ca.
30% der Patient:innen depressive Symptome vorliegen, sowohl bei der axSpA als
auch bei der PsA. In einer weiteren Analyse wurden PsA-Patient:innen, die auch
eine axiale Beteiligung haben mit den axSpA-Patient:innen, die auch eine
Hautpsoriasis haben, verglichen. axPsA-Patient:innen waren älter und weniger
häufig HLA-B27 positiv, zudem war der Frauenanteil höher, als bei den
axSpA+Pso-Patient:innen. Die Krankheitslast gemessen z. B. an der globalen
Krankheitsaktivität berichtet sowohl von den Ärzten als auch von den
Patient:innen war sehr ähnlich in beiden Gruppen. Damit die Daten aus
Krankheitsregistern nutzbringend analysiert werden können und zum Beispiel auch
Analysen über Therapiesicherheit möglich sind, ist es wichtig, dass möglichst
viele Patient:innen eingeschlossen werden und über eine lange Zeit im Register
beobachtet werden. Deshalb freuen wir uns sehr über die aktive Mitarbeit so
vieler Rheumtaolog:innen und ihrer Mitarbeiter:innen und heißen neue
rheumatologische Einrichtungen jederzeit herzlich willkommen.
Primäre und sekundäre Cerclage bei Hochrisiko-Schwangeren: Einfluss
auf die Schwangerschaftsdauer und Frühgeburt
Authors: Markfeld-Erol Filiz , Meschede Julia , Klar Maximilian , Juhasz-Böss Ingolf , Kunze Mirjam 
Published: December 2024

Zusammenfassung
Einleitung Ziel der Studie war es, die Wirksamkeit von Cerclagen bei
Frauen mit belasteter Anamnese zu evaluieren. Das primäre Ziel war die
Verlängerung der Schwangerschaft und das Erreichen einer Termingeburt. Sekundär
wurde untersucht, ob eine Intervention nach einem frühen pathologischen
75-g-oGTT-Befund diese Endpunkte beeinflusst.
Methodik Es wurden 133 Fälle retrospektiv analysiert. 80 Frauen erhielten
eine primäre Cerclage zwischen der 14.–16. Schwangerschaftswoche, 53 Frauen eine
sekundäre Cerclage nach Zervixverkürzung unter 25 mm. Diese Gruppe wurde weiter
unterteilt in eine therapeutische und eine Notfallgruppe. Frauen mit frühem
pathologischem 75-g-oGTT wurden diabetologisch mitbetreut.
Ergebnisse Die primäre Cerclage verlängerte die Schwangerschaft um 20,6
Wochen und führte bei 51 Frauen (63,8%) zu einer Termingeburt. In der Gruppe mit
sekundärer Cerclage kam es bei 25 Frauen (47,2%) zu einer Termingeburt mit einer
Verlängerung um 20,1 Wochen. Bei einem Fruchtblasenprolaps betrug die
Verlängerung 7,9 Wochen. Pathologische 75-g-oGTT-Ergebnisse hatten 63 Frauen.
Eine frühzeitige Intervention hatte keinen signifikanten Einfluss auf die
Verlängerung und die Termingeburt.
Schlussfolgerung Die primäre Cerclage war effektiver für das Erreichen
einer Termingeburt. Frauen mit therapeutischer Cerclage ohne Fruchtblasenprolaps
profitierten ebenfalls. Bei Zervixverkürzung ohne Prolaps war die Verlängerung
in beiden Gruppen gleich. Das schlechteste Ergebnis wurde bei Notfallcerclage
mit Fruchtblasenprolaps beobachtet. Ein frühzeitiger 75-g-oGTT ist wichtig, um
einen Gestationsdiabetes rechtzeitig zu erkennen und zu behandeln.
Structural, electronic, optical, magnetic, and mechanical properties of SmMnO3 perovskite with europium and yttrium doping: A first-principles study
Authors: Pokharel Peshal , Yadav Shashit Kumar , Pantha Nurapati , Sharma Bikash , Adhikari Devendra 
Published: December 2024

This paper explores the impact of europium (Eu) and yttrium (Y) doping on the electronic, magnetic, optical, elastic, and structural properties of SmMnO3 perovskites using the Quantum ESPRESSO code. The cohesive energy and tolerance factor calculations revealed that the perovskite can maintain structural stability up to 25% doping of Eu and Y. Bandgap calculations suggest that when Eu and Y are doped, the energy bandgap of pure SmMnO3 decreases significantly from 2.72 to 0.47 and from 2.72 to 0.76 eV, respectively. Doped SmMnO3 exhibits a UV shift and increased intensity in the absorption coefficient, while the reflectivity peak decreases. These changes in optical properties and bandgap due to Eu and Y doping make SmMnO3 a promising material for advanced applications in photovoltaics, UV photodetectors, and optoelectronic devices. The ferromagnetic property and total magnetic moment of SmMnO3 are found to be increased by Eu doping. Meanwhile, the magnetic moment gets reduced by Y doping. Curie temperature calculations indicate that Eu doping increases the Curie temperature from 255.35 to 314.28 K, while Y doping reduces it from 255.35 to 187.69 K. These changes in magnetic moment and Curie temperature suggest that the doped material is suitable to be used in magnetic sensors and storage devices. The calculated elastic constants, Young’s modulus, shear modulus, Poisson’s ratio, and B/G ratio suggest that both pristine and doped compounds under study show a ductile behavior.
Charm Physics at the Super τ-Charm Factory
Authors: Cheng Hai-Yang , Lyu Xiao-Rui , Xing Zhi-Zhong 
Published: December 2024

Abstract
The high-luminosity Super τ-Charm Factory (STCF) will be a crucial facility for charm-physics research, particularly for the precise measurement of electroweak parameters, measuring D
0-

D
¯

0

mixing parameters, investigating conjugation–parity (CP) violation within the charm sector, searching for the rare and forbidden decays of charmed hadrons, and addressing other foundational questions related to charmed hadrons. With the world’s largest charm-threshold data, the STCF aims to achieve high sensitivity in studying the strong phase of neutral D mesons using quantum correlation, complementing studies at LHCb and Belle II, and contributing to the understanding of CP violations globally. The STCF will also enable world-leading precision in measuring the leptonic decays of charmed mesons and baryons, providing constraints on the Cabibbo–Kobayashi–Maskawa matrix and strong-force dynamics. Additionally, the STCF will explore charmed hadron spectroscopy. The advanced detector and clean experimental environment of the STCF will enable unprecedented precision, help address key challenges in the Standard Model, and facilitate the search for potential new physics.
Quantum-state engineering using enhanced tripartite interactions in atom–photon–phonon hybrid systems
Authors: Guo 郭 Yaowu 耀武 , Zhao 赵 Jiaqiang 加强 , Cao 曹 Lianzhen 连振 , Li 李 Yingde 英德 , Lu 路 Hong-Yan 红艳 
Published: December 2024

Abstract
We introduce a hybrid cavity optomechanical model capable of generating significant genuine tripartite interactions and entanglement among coherent degrees of freedom. However, realizing and controlling such tripartite interactions and their entanglement pose crucial challenges that remain largely unexplored. In this work, we predict a tripartite coupling mechanism within a hybrid quantum system consisting of a vibrating mechanical oscillator, a two-level atom and a single-frequency cavity field. We specifically propose a mechanism for tripartite and cross-Kerr nonlinear coupling through displacement and squeezing transformations. By adjusting the optical amplitude of the pump light, we can effectively enhance these nonlinear couplings, facilitating the manipulation of entangled and squeezed states. The resulting tripartite genuine entanglement exhibits distinct evolutionary characteristics. Notably, when the pump light amplitude is large, the tripartite entanglement persists for longer time. Additionally, the phonon displays characteristics of both cooling and squeezing. Our study presents a pathway for exploring and exploiting controllable multipartite entanglement, as well as achieving phonon cooling and squeezing with the assistance of a mesoscopic harmonic oscillator. This work underscores the innovative potential of our model in advancing the field of optomechanics and quantum entanglement.
Dynamic Adsorptive Carbon Capture in Power-to-Gas Plants
Authors: Barbaresi Andrea , Gambarotta Agostino , Morini Mirko , Saletti Costanza 
Published: December 2024

Abstract
Energy transition can be addressed in the very near future with low investment costs by utilizing already-available technologies and infrastructures. In this regard, among innovative energy carriers, green synthetic methane can tackle the issue by taking advantage of natural gas facilities. Power-to-gas systems enable methane synthesis by combining electrolytic hydrogen and captured carbon dioxide.
This work investigates the adsorptive carbon capture in the context of a power-to-gas system. Carbon dioxide is trapped onto the porous surface of a packed bed by adsorption and is then released during bed regeneration. The alternating process operation is analyzed by means of a dynamic model capable of reproducing both adsorption and desorption. The other system components are dynamically modeled as well to simulate their interaction during the cyclic operation.
The whole cycle is analyzed. Bed regeneration by means of a hydrogen purge flow is evaluated considering the possibility of utilizing the mixture of hydrogen and desorbed carbon dioxide as reactants in a subsequent catalytic methanation process. The boundary limits for the pressure of the hydrogen purge source are identified in order to obtain the desired reactants proportion. Regarding adsorption, different post-combustion flue gases are evaluated as carbon dioxide sources from a plant-management perspective.
NextGen Infrastructures: Enhancing Cyber-Physical Resilience/Sustainability by Virtual Energy Storage
Authors: Ardebili Ali Aghazadeh , Padoano Elio , Longo Antonella , Ficarella Antonio 
Published: December 2024

Abstract
This systematic review investigates the pivotal role of virtual energy storage (VES) in enhancing the resilience of energy systems. By systematically selecting and analyzing 158 articles, we address four key research questions about specific features of VES that enhance energy system resilience, how these features influence the overall resilience of energy systems, the enabler technologies associated with VES that impact the resilience of cyber-physical systems, and lastly, we discuss the challenges, and future research directions pertaining to the utilization of VES for bolstering resilience. Highlighting the importance of VES, the findings provide insights for policymakers, energy practitioners, and researchers aiming to enhance the resilience of energy systems in the face of increasing uncertainties and disruptions. Furthermore, this study provides valuable insights for the resilience engineering and energy engineering communities by identifying main features of energy resilience and key enabler technologies of VES for enhancing energy storage and system resilience.