bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social and non-social risk-taking in adolescence
Authors: Wang Weike , Evans Kylie , Schweizer Susanne 
Published: February 2025

Abstract
The Social Risk Hypothesis of Depression proposes that individuals who perceive themselves as low in value to their social groups are at risk of developing depression. Behaviourally, lower self-perceived social value is proposed to reduce individuals’ propensity to take social risks to avoid further lowering their social worth. This is in contrast with adolescent-typical behaviour, which is characterised by heightened risk-taking in social contexts. The current study aimed to investigate how low self-perceived social value influences risk-taking in social compared to non-social contexts during adolescence. 114 adolescents (aged 12–23 years) completed the Balloon Analogue Risk Task (BART) in individual and social contexts. The results showed that adolescents took more risks in social compared to individual contexts. Risk-taking across social and individual contexts also varied as a function of self-perceived social value. In older—but not younger—youth, lower self-perceived social value was associated with greater risk-taking in social compared to individual contexts. These findings suggest that self-perceived social value differentially influences social risk-taking across adolescence. In later youth, the heightened social risk-taking observed in individuals with low self-perceived social value aligns with developmental theories suggesting that risk-taking at this age serves to increase social rank and avoid social exclusion by peers.
MEMS vibrometer: Dynamic modeling of multimodal inertial transducers
Authors: Haus Jan Niklas , Zhu Zhengchun , Roloff Thomas , Rittmeier Liv , Bornemann Sarah , Sinapius Michael , Dietzel Andreas 
Published: February 2025

Abstract
Guided ultrasonic wave-based structural health monitoring utilizes propagating elastic waves to identify, locate, and characterize damage within aviation structures. Fiber metal laminates, which are composite materials made by layering metal sheets with fiber-reinforced polymers, combine the high strength of composites with the ductility and impact resistance of metals. However, structural health monitoring methods suitable for these materials have to be developed, allowing to monitor also the inner laminate layers. Therefore, laminate-embedded MEMS vibrometers have been introduced recently. Due to the quasi-free operation of these inertial sensors, they are directly sensitive to the displacement induced by propagating guided ultrasonic waves. However, the multimodal excitation of the sensor’s core resonator, when exposed to ultrasound bursts, leads to a pseudo-nonlinear sensor response, which is attributed to the spectrum of guided ultrasonic waves and their interference with higher harmonics of the continuum resonator. The transfer behavior of the sensor can be improved by implementing electrical mode suppression. This research involves analytically modeling the continuous resonator with multiple aggregated resonators, numerically simulating sensor responses to 100 kHz ultrasound bursts, and using a laser scanning micro vibrometer setup for experimental validation, providing a deeper understanding of MEMS vibrometer dynamics for ultrasonic monitoring and demonstrating their applicability.
Inhibition of autophagy in platelets as a therapeutic strategy preventing hypoxia induced thrombosis
Authors: Bandyopadhyay Propanna , Katakia Yash T. , Mukherjee Sudeshna , Majumder Syamantak , Chowdhury Shibasish , Chowdhury Rajdeep 
Published: February 2025

Abstract
Hypoxia triggers activation of platelets, leading to thrombosis. If not addressed clinically, it can cause severe complications and fatal consequences. The current treatment regime for thrombosis is often palliative and include long-term administration of anticoagulants, causing over-bleeding risk and other secondary effects as well. This demands a molecular understanding of the process and exploration of an alternative therapeutic avenue. Interestingly, recent studies demonstrate that platelets exhibit functional autophagy. This cellular homeostatic process though well-studied in non-platelet cells, is under-explored in platelets. Herein, we report autophagy activation under physiologically relevant hypoxic condition (10% O2; associated with high altitude) in ex-vivo platelets and in vivo as well. We show that autophagy inhibition using chloroquine (CQ), a repurposed FDA-approved drug, can significantly reduce platelet activation, both in ex-vivo and in-vivo settings. Further, surgical ligation of inferior vena cava (IVC) was performed to induce thrombus formation. Interestingly, CQ pre-treated rats showed reduced clotting ability in surgical animals as well. Importantly, thrombosis inhibitory dose of CQ was considerably lower than the currently used drug-acetazolamide; CQ was also found to be non-toxic to the tissues. Hence, we propose that repurposing of CQ can attenuate hypoxia-induced thrombosis through inhibition of autophagy and can be explored as an effective therapeutic alternative.
Securing Ports of Web Applications Against Cross Site Port Attack (XSPA) by Using a Strong Session Identifier (Session ID)
Authors: Bhatia Kavita , Pandey Santosh K. , Singh Vivek K. , Gupta Deena Nath 
Published: February 2025

ABSTRACTXSPA vulnerability can be attacked by stealing the cookie's information. In this case, it becomes utmost necessary to secure the information written in a cookie. A cookie contains a session ID that is a unique number generated by the server. This session ID must be a large random number so that no one can guess a valid session ID in real‐time. Numerous research studies have been accomplished on the same but the area still persist gaps in view of emerging threats, such as phishing, pharming, and DoS. This paper proposes a new random‐number generator that produces unique numbers in bulk. This helps the server to match the high demand of unique session IDs from different clients. The proposed generator is suitable for all types of web applications, because it requires the smallest area of only 134 Gate Equivalent on the application specific integrated circuit (ASIC) for its execution. Additionally, the proposed generator passed all tests of EPCglobal. Total time delay of digital circuit and power analysis results presented in the subsequent sections are also in the favour of proposed generator. With the implementation of this proposed technique cookies are expected to be more secure as evident from try‐out results.
A complete in‐cabin monitoring framework for autonomous vehicles in public transportation
Authors: Tsiktsiris Dimitris , Lalas Antonios , Dasygenis Minas , Votis Konstantinos 
Published: February 2025

AbstractAutonomous vehicles (AVs), driven by state‐of‐the‐art deep learning and computer vision technologies, can revolutionize current mobility systems in modern transportation. Driverless AVs are slowly integrated into public transportation with significant advantages for the passengers and public transport operators. However, passenger safety and comfort are two of the main challenges that need to be addressed. This work presents a complete in‐cabin monitoring framework with a suite of services, employing deep learning algorithms using a variety of onboard sensors at the edge. This proposed framework offers various innovative services aimed at enhancing security, monitoring passenger presence, accommodating diverse needs, and personalizing the passengers' travel experience, while also reducing the workload of human safety officers. Experimental results demonstrate the framework's effectiveness in identifying abnormal events with a high accuracy, employing multiple datasets and custom in‐cabin scenarios. Additionally, the system effectively conducts automated passenger counting and facial identification, ensuring real‐time responsiveness under diverse operational conditions. Overall, the novelty of this work lies in the framework's multimodal approach, integrating visual and audio analysis, to achieve robust performance across various scenarios, significantly contributing to the advancement of autonomous driving technologies.
Revitalising DC‐Aged Silicone Rubber Composites: Hybrid‐Silica/Alumina Triumph Over Multi‐Stress Ageing
Authors: Ullah Rahmat , Ullah Israr , Ahmed Rizwan , Reid Alistair , Haddad Manu 
Published: February 2025

ABSTRACTIn this study, various concentrations of high‐temperature vulcanised silicone rubber composites filled with nano/micro silica and alumina were manufactured. In this work, all test specimens were subjected to a variety of environmental stresses as well as DC voltage for 5000 h. Then, different diagnostic methods were used to look at the changes that happened on their surfaces and in their bulk properties. These included hydrophobicity classification, X‐ray photoelectron spectroscopy (XPS) analysis, Fourier transform infrared spectroscopy (FTIR) analysis, thermogravimetric analysis (TGA) analysis, leakage current analysis and mechanical strength analysis. The composite with 2% nano silica and 10% micro alumina had the smoothest surface and the best hydrophobicity (HC‐3). It also had the lowest leakage current (3.1 μA), the least amount of strength loss (31.3%), and good thermal stability compared to the other samples that were studied. Aged samples show a considerable increase in the concentration of the O element and a significant drop in the proportion of the Si component relative to the virgin specimen, which points to the oxidation of chemical bonds during HTV SR and their composites during ageing but with different concentrations. However, two samples (SP2 and SP3) showed comparatively lower concentrations of oxygen degradation in Si contents. This can be attributed to the strong molecular interaction between the fillers and the base matrix.
An energetic absorption outflow in QSO J1402+2330: Analysis of DESI observations
Authors: Dehghanian M. , Arav N. , Sharma M. , Walker G. , Johnston K. , Kaupin M. 
Published: February 2025

Context. Quasar outflows play a significant role in the active galactic nucleus (AGN) feedback, impacting the interstellar medium and potentially influencing galaxy evolution. Characterizing these outflows is essential for understanding AGN-driven processes.
Aims. We aim to analyze the physical properties of the mini-broad absorption line outflow in quasar J1402+2330 using data from the Dark Energy Spectroscopic Instrument (DESI) survey. We seek to measure the outflow’s location, energetics, and potential impact on AGN feedback processes.
Methods. In the spectrum of J1402+2330, we identify multiple ionic absorption lines, including ground and excited states. We measure the ionic column densities and then use photoionization models to determine the total hydrogen column density and ionization parameter of the outflow. We utilized the population ratio of the excited state to the ground state of N III and S IV to determine the electron number density.
Results. The derived electron number density, combined with the ionization parameter, indicates an outflow distance of approximately 2.2 kpc from the central source. Having a mass outflow rate of more than one thousand solar masses per year and a kinetic energy output exceeding 5% of the Eddington luminosity, this outflow can significantly contribute to AGN feedback.
Conclusions. Our findings suggest the absorption outflow in J1402+2330 plays a potentially significant role in AGN feedback processes. This study highlights the value of DESI data in exploring AGN feedback mechanisms.
Nichtabrechnung von Leistungen gegenüber der Kassenärztlichen Vereinigung
Authors: Netzer-Nawrocki Juliane 
Published: February 2025

ZusammenfassungDie Nichtabrechnung von ärztlichen Leistungen gegenüber den Kassenärztlichen Vereinigungen kann durch verschiedenste Beweggründe motiviert sein. Entsprechende Fallkonstellationen sind in nahezu allen vertragsärztlichen Tätigkeitsbereichen denkbar. Exemplarisch zu nennen ist der ermächtigte Krankenhausarzt, der ambulante Leistungen erbringt, die außerhalb seiner Ermächtigung liegen und damit gegenüber der Kassenärztlichen Vereinigung gar nicht abrechenbar sind. Möglich ist auch, dass der niedergelassene Vertragsarzt erbrachte Leistungen nicht abrechnet, weil er einer Plausibilitätsprüfung und ggf. einer Honorarkürzung entgehen möchte, da er am Tag eine zu große Leistungsmenge erbracht hat. Gleiches gilt für drohende Fälle einer Wirtschaftlichkeitsprüfung, wenn der Vertragsarzt im Vergleich zu seinen Fachgruppenkollegen bestimmte Leistungen auffällig häufig abrechnet. Diesen Fällen ist gemein, dass sie im streng regulierten vertragsärztlichen Abrechnungssystem nicht vorgesehen sind und sie entsprechende Sanktionen nach sich ziehen können. Der folgende Beitrag soll einen Überblick über solche Problemfälle geben.
Management of Early and Late Malperfusion Syndrome in Acute Type B Aortic Dissection with Retrograde Extension Using Hybrid Zone 2 Arch Repair and Thoracic Endovascular Aortic Repair: A Case Report
Authors: Votano Daniela , Beaufort Hector W.L. de , Mortel Rob H.W. van de , Sonker Uday , Heijmen Robin H. , Smeenk Hans G. 
Published: February 2025

AbstractThe distal extent of aortic repair in acute aortic dissection and the management of malperfusion in terms of timing and strategy are still debated topics. We present a case of acute type B dissection with retrograde extension to the ascending aorta, with the most proximal intimal tear in the descending thoracic aorta, associated with both early lower extremity and delayed mesenteric malperfusion syndrome, treated effectively by femoral artery open fenestration and hybrid zone 2 arch repair.
A novel multiple-prototype and domain adversarial network for few-shot cross-domain fault diagnosis
Authors: Shi Peiming , Dai Siyu , Xu Xuefang , Han Dongying 
Published: February 2025

Abstract
Since deep learning has been introduced into the field of intelligent fault diagnosis it has made significant accomplishments with large amounts of data. However, in practical industrial settings there is a general lack of labeled data and operating conditions are not stable, therefore existing trained models ignore these problems and diagnostic accuracy and generalization are severely degraded. Therefore, this study proposes a multiple-prototype, domain adversarial network for fault diagnosis of rotating machinery, especially bearings, to address the issues of domain distribution shift and a shortage of labeled samples from the target domain. Firstly, the proposed method adopts a residual network with 12 layers (ResNet12) as the encoder to extract distinct features from the target domain and source domain data. Then, a domain-invariant representation module, using the domain adversarial method, is introduced to bridge the discrepancy between a source and target pair domain. Furthermore, a class typicality weight module is designed to calculate weights by constructing multiple prototypes of the source and target domains to improve the generalization of the model. Extensive experiments are executed on two datasets with variable working conditions to test and verify the feasibility and superiority of the proposed method.
Application of graph networks to a wide-field water-Cherenkov-based Gamma-ray Observatory
Authors: Glombitza J. , Schneider M. , Leitl F. , Funk S. , van Eldik C. 
Published: February 2025

Abstract
With their wide field of view and high duty cycle, water-Cherenkov-based observatories are integral to studying the very high-energy gamma-ray sky. For gamma-ray observations, precise event reconstruction and highly effective background rejection are crucial and have been continuously improving in recent years. In this work, we investigate the application of graph neural networks (GNNs) to background rejection and energy reconstruction and benchmark their performance against state-of-the-art methods.
In our simulation study, we find that GNNs outperform hand-designed classification algorithms and observables in background rejection and find an improved energy resolution compared to template-based methods.
A multi-Hough-based displaced vertex track trigger for the Belle II experiment
Authors: Unger Kai Lukas , Becker Jürgen , Forsthofer Timo , Hiesl Simon , Kiesling Christian , Neu Marc , Schmidt Elia , Meggendorfer Felix , Mi Tiancheng , Ou Zuwen 
Published: February 2025

Abstract
The Belle II experiment at the asymmetric-energy electron positron collider SuperKEKB aims to explore physics beyond the standard model (BSM). One of the widely discussed signatures for BSM are new, long-lived neutral particles, which decay into charged mesons or lepton pairs originating from a vertex usually far from the interaction point (IP) of the colliding beams. The current level-1 (L1) track trigger system is optimized for particles created at the IP and will thus reject, with high probability, such interesting events. This makes it necessary to develop a special L1 track trigger for events with a vertex displaced from IP, the Displaced Vertex Trigger (DVT). The pipelined and deadtime-free L1 trigger system of Belle II utilizes a set of FPGA boards to make rapid decisions within 5 microseconds. The new DVT will be operating in parallel with the existing track trigger systems. The DVT identifies events, where two tracks with opposite charge originate from a common vertex away from the IP. The track finding is done by a set of Hough transformations, each one assuming a certain track origin from a grid spanning the tracking volume. The correct vertex is then determined via a shape analysis of the Hough clusters, using neural networks. To manage the large number of track origin hypotheses, a pre-selection of candidates based on the properties of the Hough map is employed, which significantly reduces the required FPGA resources.
Research on online RF tuning of DTL accelerator for CSNS-II energy upgrade
Authors: Li Ahong , Qu Peihua , Liu Huachang , Meng Lin , Wang Sheng , Wu Xiaolei , Li Bo , Fan Mengxu , Zhou Wenzhong , Zhang Cong , Chen Qiang , Yang Yao , Wang Yuqi 
Published: February 2025

Abstract
With the energy upgrade of the China Spallation Neutron
Source (CSNS-II) and the increasing demand for isotope production,
the RF repetition frequency of the Drift Tube Linac (DTL)
accelerator must be elevated from 25 Hz to 50 Hz. However, the
frequency shifts induced by RF heating exceed the current tuning
range. Traditional tuning methods cannot be applied during DTL
operation, so online tuning technology is explored in this
study. Multi-physics simulations were used to analyze the
electromagnetic and temperature distribution, frequency shifts, and
compensation strategies. It was found that adding tuning blocks on
the side of the cavity is the optimal solution. Two types of tuning
blocks were developed and installed during the summer maintenance,
achieving a beam transmission rate of over 98%. Experimental
results showed that the new tuning blocks effectively compensated
for the frequency deviation without affecting the cavity's stability
or field distribution. This solution improves the high-frequency
performance of the DTL accelerator and meets the upgraded
requirements. It is practical approach that offers valuable insights
for the online tuning of DTL accelerators, as well as other
high-frequency cavities.
The optimal structure of the MRPC detector for 0.511 MeV gamma based on Monte Carlo simulation
Authors: Liu J. , Chen Z. , Wang Y. , Guo B. , Han D. , Li Y. 
Published: February 2025

Abstract
The detailed simulation of the Multi-gap Resistive Plate
Chambers (MRPCs) provides the performance characteristics of MRPCs
with different numbers of gas gaps and gap thicknesses. This helps
in optimizing the structure of MRPCs under specific conditions by
balancing time resolution, detection efficiency, and other
performance metrics. To obtain the optimal structure of MRPCs for
0.511 MeV gammas, a complete simulation framework for gamma
detection by the MRPCs based on Geant4 and Magboltz software is
described in this paper. The simulation shows how gammas interact
with MRPCs and the process of gas ionization, avalanche
multiplication, and signal formation. The simulation results are in
good agreement with the experimental results. By analyzing the time
resolution and detection efficiency, the optimal structure of MRPCs
for 0.511 MeV gammas is proposed.
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation
Authors: Chung Meng-Chi , Su Li-Jen , Chen Chien-Lin , Wu Li-Ching 
Published: February 2025

Abstract
Traditional Chinese Medicine (TCM), with its extensive knowledge base documented in ancient texts, offers a unique resource for contemporary drug discovery, particularly in combatting microbial infections. The success of antimalarial drugs like artemisinin and artesunate, derived from the TCM herb Artemisia annua L., exemplifies the potential of TCM-derived small molecules. This rich repository of natural products and intricate molecular structures could reveal novel compounds with unexplored mechanisms of action. Our study employs a multifaceted approach that combines text mining, detailed textual analysis, and modern antibacterial molecular prediction methodologies to unlock the potential of ancient TCM remedies. We use external knowledge maps, which include databases of known bioactive compounds and their targets, to identify promising TCM candidates. This approach leverages both historical texts and contemporary scientific data to explore the therapeutic potential of TCM. We discovered that herb patterns DiYu→ZeXie and Kushen→ShengJiang potentially combat both Grams-positive and Grams-negative bacteria. We utilized the AntiBac-Pred online tool to identify and analyze the chemical components of herbs, integrating data from ancient texts and TCMDB@Taiwan external knowledge graph. The DiYu→ZeXie groups showed antimicrobial potential against resistant Staphylococcus simulans, while the Kushen→ShengJiang groups exhibited dual antimicrobial effects against Bacillus subtilis. Exploring TCM’s extensive repository offers numerous opportunities for discovering therapeutically active compounds. Our synergistic approach, which combines ancient wisdom with modern science, holds significant promise for enhancing our ability to combat infectious diseases. This method could pave the way for a new era of personalized medicine, addressing the urgent need for innovative treatments against multidrug-resistant bacteria and viruses.