bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive flexibility and depression: The moderator roles of humor styles
Authors: Altan-Atalay Ayse , Fatih Boluvat Mustafa 
Published: April 2024

AbstractHumor style, which involves both adaptive and maladaptive forms, refers to the ways people use humor in daily life. Maladaptive humor styles (self-defeating and aggressive) can be risk factors for various mental disorders, including depression and anxiety. In contrast, adaptive humor styles (affiliative and self-enhancing) are perceived as resilience factors and buffer the negative impact of other risk factors. Cognitive flexibility reflects a capacity to come up with alternative interpretations and resolutions to demanding situations while perceiving them as controllable. Although the connection of high cognitive flexibility with low depression levels has been consistently documented, its interaction with trait-like factors received limited attention. The current study aims to explore the moderator role of humor styles in the association of cognitive flexibility with depression. Data were gathered from 436 (320 women) participants aged 18 and 70 (M = 35.4, SD = 9.18) through scales assessing humor styles, cognitive flexibility, and depression. The results revealed that the interaction of affiliative humor style with cognitive flexibility was significantly linked to the individual differences in depression levels, highlighting that affiliative humor is functional if individuals have difficulty approaching problematic situations from different angles. However, a similar pattern was not observed for other humor styles.
BRD4 inhibitors broadly promote erastin-induced ferroptosis in different cell lines by targeting ROS and FSP1
Authors: Fan Chenyang , Guo Xiaohong , Zhang Jie , Zheng Wen , Shi Chonglin , Qin Yongwei , Shen Haoliang , Lu Yang , Fan Yihui , Li Yanli , Chen Liuting , Mao Renfang 
Published: April 2024

AbstractFerroptosis, an iron-dependent form of programmed cell death, is a promising strategy for cancer treatment. Bromodomain-containing protein 4 (BRD4) is an epigenetic reader and a promising target for cancer therapeutics. However, the role of BRD4 in ferroptosis is controversial and the value of the interaction between BRD4 inhibitors and ferroptosis inducers remains to be explored. Here, we found that BRD4 inhibition greatly enhanced erastin-induced ferroptosis in different types of cells, including HEK293T, HeLa, HepG2, RKO, and PC3 cell lines. Knocking down BRD4 in HEK293T and HeLa cells also promoted erastin-induced cell death. BRD4 inhibition by JQ-1 and I-BET-762 or BRD4 knockdown resulted in substantial accumulation of reactive oxygen species (ROS) in both HEK293T and HeLa cells. The effect of BRD4 inhibition on ferroptosis-associated genes varied in different cells. After using BRD4 inhibitors, the expression of FTH1, Nrf2, and GPX4 increased in HEK293T cells, while the levels of VDAC2, VDAC3, and FSP1 decreased. In HeLa cells, the expression of FTH1, VDAC2, VDAC3, Nrf2, GPX4, and FSP1 was reduced upon treatment with JQ-1 and I-BET-762. Consistently, the level of FSP1 was greatly reduced in HEK293T and HeLa cells with stable BRD4 knockdown compared to control cells. Furthermore, ChIP-sequencing data showed that BRD4 bound to the promoter of FSP1, but the BRD4 binding was greatly reduced upon JQ-1 treatment. Our results suggest that ROS accumulation and FSP1 downregulation are common mechanisms underlying increased ferroptosis with BRD4 inhibitors. Thus, BRD4 inhibitors might be more effective in combination with ferroptosis inducers, especially in FSP1-dependent cancer cells.
Development of chitosan-folate modified PLGA nanoparticles for targeted delivery of diosgenin as an anticancer agent
Authors: Teymouri Fatemeh , Karimi Ehsan 
Published: April 2024

AbstractDiosgenin as a potential phytoconstituent and steroidal saponin manifested significant anticancer agents against various cancers. To enhance its solubility and bioavailability in cancer treatment, we loaded diosgenin (PubChem CID: 99474) in poly(lactic-co-glycolide) (PLGA) nanoparticle coated with folic acid-chitosan (Da-PFC-NPs). The diosgenin nano-formulation was characterized and its antioxidant and anticancer properties were surveyed respectively. The obtained results illustrated that the Da-PFC-NPs were spherical and stable with a size of 218 nm and a polydispersity index of 0.41. The Da-PFC-NPs indicated potential free radical scavenging using ABTS and DPPH assay. Meanwhile, it demonstrated selective toxicity against the TUBO breast cancer cell with IC50 values of 104.45 μg/ml and did not show toxicity on normal cells (I929 cell line). The invivo funding exhibited that Da-PFC-NPs notably altered the liver enzymes (AST, ALT, ALP) and immunoglobulins (IgA, IgG, IgM). Besides that, different doses of Da-PFC-NPs (50 and 100 mg/kg) remarkedly enhance the expression of caspase 3 and decrease HER2 genes. In light of this experiment, we can conclude that Da-PFC-NPs have promise as novel carrier for improving the delivery of diosgenin in cancer therapy.
MAP3K4 kinase action and dual role in cancer
Authors: Huang Yuxin , Wang Guanwen , Zhang Ningning , Zeng Xiaohua 
Published: April 2024

AbstractIt is commonly known that the MAPK pathway is involved in translating environmental inputs, regulating downstream reactions, and maintaining the intrinsic dynamic balance. Numerous essential elements and regulatory processes are included in this pathway, which are essential to its functionality. Among these, MAP3K4, a member of the serine/threonine kinases family, plays vital roles throughout the organism's life cycle, including the regulation of apoptosis and autophagy. Moreover, MAP3K4 can interact with key partners like GADD45, which affects organism's growth and development. Notably, MAP3K4 functions as both a tumor promotor and suppressor, being activated by a variety of factors and triggering diverse downstream pathways that differently influence cancer progression. The aim of this study is to provide a brief overview of physiological functions of MAP3K4 and shed light on its contradictory roles in tumorigenesis.
Tracking long-term modal behaviour of a footbridge and identifying potential SHM approaches
Authors: Ao Wai Kei , Hester David , O’Higgins Connor , Brownjohn James 
Published: April 2024

AbstractNumerous studies have investigated the long-term monitoring of natural frequencies, primarily focusing on medium–large highway bridges, using expensive monitoring systems with a large array of sensors. However, this paper addresses the less explored issue of monitoring a footbridge, examining four critical aspects: (i) sensing system, (ii) frequency extraction method, (iii) data modelling techniques, and (iv) damage detection. The paper proposes a low-cost all-in-one sensor/logger unit instead of a conventional sensing system to address the first issue. For the second issue, many studies use natural frequency data extracted from measured acceleration for data modelling, the paper highlights the impact of the input parameters used in the automated frequency extraction process, which affects the number and quality of frequency data points extracted and subsequently influences the data models that can be created. After that, the paper proposes a modified PCA model optimised for computational efficiency, designed explicitly for sparse data from a low-cost monitoring system, and suitable for future on-board computation. It also explores the capabilities and limitations of a data model developed using a limited data set. The paper demonstrates these aspects using data collected from a 108 m cable-stayed footbridge over several months. Finally, the detection of damage is achieved by employing the one-class SVM machine learning technique, which utilises the outcomes obtained from data modelling. In summary, this paper addresses the challenges associated with the long-term monitoring of a footbridge, including selecting a suitable sensing system, automated frequency extraction, data modelling techniques, and damage detection. The proposed solutions offer a cost-effective and efficient approach to monitoring footbridges while considering the challenges of sparse data sets.
Sensitivity analysis of near solidus forming (NSF) process with digital twin using Taguchi approach
Authors: Sajjad Muhammad , Trinidad Javier , Plata Gorka , Lozares Jokin , Mendiguren Joseba 
Published: April 2024

AbstractForging at near solidus material state takes advantage of the high ductility of the material at the semi solid or soft-solid state while keeping most of the mechanical properties of a forged part. The technology is at maturity level ready for its industrial implementation. However, to implement the process for complex cases the development of an appropriate digital twin (DT) is necessary. While developing a material model, a strong experimental and DT is necessary to be able to evaluate the accuracy of the model. Aimed at having a reliable DT under control, for future material model validations, the main objective of this work is to develop a sensitivity analysis of three NSF industrial cases such as Hook, R spindle and H spindle to develop an adequate DT calibration procedure. Firstly, the benchmark experimentation process parameter noise and experimentation boundary conditions (BCs) parameter uncertainty are identified. Secondly, the three industrial benchmark DTs are constructed, and a Taguchi design of experiments (DoEs) methodology is put in place to develop the sensitivity analysis. Finally, after simulations the results are critically evaluated and the sensitivity of each benchmark to the different inputs (process parameter noise and BC parameter uncertainty) is studied. Lastly, the optimum DT calibration procedure is developed. Overall, the results stated the minimum impact of the material model in terms of dies filling. Nevertheless, even if the material model is the highest impacting factor for the forging forces other inputs, such as heat transfer and friction must be under control first.
Effect of temperature on tribofilm growth and the lubrication of the piston ring-cylinder liner system in two-stroke marine engines
Authors: Lyu Xiuyi , Hu Jiang , Wang Yunchuan , Sheng Jinlu , Ma Xuan , Li Tongyang , Ge Chang , Lu Xiqun 
Published: April 2024

AbstractThis study is an optimized extension based on the authors’ previous research on the tribo-chemical reaction under constant temperature field of two-stroke internal combustion engines (ICEs). It establishes a coupled analysis model that considers the tribo-chemical reactions, dynamic contact, and interface lubrication of the piston ring-cylinder liner (PRCL) system under transient temperature conditions. In this study, for the first time, the prediction of the tribofilm thickness and its influence on the surface micro-topography (the comprehensive roughness) are coupled in the working temperature field of the PRCL system, forming an effective model framework and providing a model basis and analytical basis for subsequent research. This study findings reveal that by incorporating temperature and tribofilm into the simulation model, the average friction deviation throughout the stroke decreases from 8.92% to 0.93% when compared to experimental results. Moreover, the deviation during the combustion regime reduces from 39.56% to 7.34%. The proposed coupled model provides a valuable tool for the evaluation of lubrication performance of the PRCL system and supports the analysis software forward design in two-stroke ICEs.
A novel method for imitating true-triaxial stress path with conventional triaxial apparatus
Authors: Li Xuefeng , Ma Zhigang 
Published: April 2024

AbstractThe stress paths of the cylindrical specimen in the p–q stress space by controlling the ratio of the axial and the radial loading is guaranteed to be consistent with the cuboid specimen, a novel method for imitating true-triaxial stress path by conventional triaxial apparatus was presented. Under the condition that p and q were variables and b was constant, the true-triaxial stress paths were realized by conventional triaxial apparatus strictly and easily. Under the condition that b and p were invariants, the b was used to control the ratio of axial and radial loading to ensure p constant, the method can be used to measure the strength on the π plane. If the tests were conducted at the different p with the same b, the critical state line of different b could be obtained. Under the condition that p and q were constant, the proposed method of nonlinear loading with b as a parameter could be used to design the various stress paths of true-triaxial under the condition of deviatoric stress consolidation, and which could be used to determine the deformation and the plastic flow of soil in 3D space. The proposed method could be used to achieve the equivalent stress path in the p–q stress space to obtain the 3D mechanical properties, and the stress path controlled by stress, strain, and a hybrid of stress and strain. Once the software of conventional triaxial apparatus was developed by the novel method, the measuring range of stress paths could be expanded greatly.
Die Verbreitung antisemitischer Einstellungen in Deutschland: Befunde aktueller repräsentativer Befragungen zu Trends seit 2021 und den Einflüssen von Migrationshintergrund, Religionszugehörigkeit und Religiosität
Authors: Fischer Jannik M. K. , Wetzels Peter 
Published: April 2024

ZusammenfassungSeit den Anschlägen vom 7. Oktober 2023 und im Gefolge des anschließenden Gaza-Krieges erfährt Antisemitismus in Deutschland wieder erheblich gesteigerte Aufmerksamkeit. Ein besonders sensibles Thema ist dabei Antisemitismus unter in Deutschland lebenden Muslim:innen. Auf Basis der Daten aus drei repräsentativen, bundesweiten Befragungen untersucht der vorliegende Beitrag Trends der Verbreitung antisemitischer Einstellungen seit 2021. Analysen erfolgen sowohl in Bezug auf die erwachsene Bevölkerung insgesamt als auch kontrastierend für verschiedene gesellschaftliche Subgruppen. Im Ergebnis finden sich für die erwachsene Gesamtbevölkerung keine signifikanten Anstiege von Formen tradierter antisemitischer Einstellungen zwischen 2021 und 2023. Es sind jedoch deutliche Binnendifferenzen zu erkennen. Insbesondere sind bei Muslim:innen nicht nur erheblich erhöhte Raten antisemitischer Einstellungen zu registrieren, sondern auch statistisch signifikante Zuwächse zwischen 2021 und 2023, die sich bei anderen Gruppen so nicht finden. Auch nach multivariaten Kontrollen soziodemografischer Merkmale und weiterer aus der Forschung bekannter sozialer Einflussgrößen sind bei ihnen weiterhin signifikant erhöhte Ausprägungen antisemitischer Einstellungen nachweisbar. Ferner erweisen sich Neigungen zur Akzeptanz von Verschwörungsnarrativen für alle Gruppen als ein stabiler, signifikanter Prädiktor. Bei Christ:innen wie Muslim:innen finden sich daneben keine Zusammenhänge der persönlichen Gläubigkeit oder der Zentralität der Religion mit Antisemitismus. Es zeigen sich aber Zusammenhänge der Ausprägung eines fundamentalistischen Religionsverständnisses mit erhöhten antisemitischen Ressentiments bei beiden Gruppen. Nur bei Muslim:innen ist darüber hinaus die Intensität der kollektiven Religionspraxis, gemessen über die Häufigkeit des Besuchs von Moscheen, nach multivariaten Kontrollen der Intensität der individuellen Gläubigkeit sowie sozialer Kontrollvariablen, mit einer Erhöhung antisemitischer Vorurteile verbunden. Politische Implikationen dieser Ergebnisse für die Prävention von Antisemitismus in der modernen deutschen Migrationsgesellschaft werden daran anknüpfend diskutiert.
Analyzing the influence of web search behavior on electricity market price: a case study of Japan electric power exchange
Authors: Gotoh Ryosuke 
Published: April 2024

AbstractThe Japan Electric Power Exchange (JEPX) has introduced a feed-in premium to promote the trading of renewable energy electricity in the market; thus, the exchange has become increasingly important for RE companies to maintain profitability in market trading. However, electricity prices are not only affected by directly measurable factors such as electricity demand, fuel prices, and weather but also by corporate bidding strategies, social conditions, and other human behaviors, making it difficult to predict electricity prices. Given that electricity demand is related to human behavior, this study focuses on web search behavior and clarifies the relationship between keyword search volumes and electricity market prices in Japan. Correlation and vector autoregression analyses results show a moderately strong positive correlation between the logarithmic difference of the keyword search volume and that of the electricity price. In addition, we find that the logarithmic difference of the electricity price tends to increase when that of the keyword search volume on the previous day increases. These results suggest that search volumes of specific keywords can be effective explanatory variables for area price prediction models and can help identify signs of price spikes.
From video to vital signs: using personal device cameras to measure pulse rate and predict blood pressure using explainable AI
Authors: van Putten Lieke Dorine , Bamford Kate Emily , Veleslavov Ivan , Wegerif Simon 
Published: April 2024

AbstractIn this study, we address the need for low-cost, rapid, and reliable methods for blood pressure measurement to facilitate timely diagnosis and treatment of hypertension. We aim to enhance understanding and trust in the novel remote photoplethysmography technology, specifically as deployed by Lifelight$$^\circledR$$

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, for vital sign monitoring. Lifelight$$^\circledR$$

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utilizes remote photoplethysmography to extract physiologically meaningful features from video recordings on personal devices. This study describes the accurate calculation of pulse rates and the extraction of morphological and time series features from the remote photoplethysmography signal for blood pressure prediction. Unlike common approaches, distinct model types are employed for predicting systolic and diastolic blood pressure. Evaluation on an independent clinical laboratory’s dataset demonstrates the efficacy of the proposed method. The pulse rate accuracy, measured as root mean square error, is 1.9 beats per minute. The model for systolic blood pressure prediction shows a mean error of 1.2 mmHg and a standard deviation of 15.9 mmHg. The model for diastolic prediction shows a mean error of $$-$$
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3.2 mmHg and a standard deviation of 13.1 mmHg. This research establishes the validity of remote photoplethysmography technology by showcasing accurate pulse rate calculations and effective feature extraction for blood pressure prediction. The results indicate the potential for widespread adoption of remote photoplethysmography in measuring blood pressure and other vital signs.
Design and simulation of soft decision decoding based on chaotic M-ary spread spectrum system
Authors: Liu Ruopeng , Wang Pengyi , Wang Xiduo 
Published: April 2024

AbstractIn this paper, chaos sequence is used to replace the traditional spread spectrum sequence. From the perspective of the communication partner, a new method of generating the initial value of chaotic sequence is proposed, which is more suitable for the multi-base spread spectrum system and easy to extract. In order to further improve the error performance of the system and ensure the integrity of the system, an improved suboptimal soft information extraction method based on log-likelihood ratio (LLR) is proposed in the channel coding module, which can further improve the error performance of the system. On this basis, we choose the synchronization mode of multiple transmission of one reference signal to solve the problem that chaotic sequence is difficult to obtain synchronization because of its aperiodic characteristics. Finally, the system is simulated in the channel with low SNR. The simulation results show that chaotic sequence as spread spectrum code can make the signal transmit accurately in the worse channel environment. The performance gain of applying soft information decoding decision in the multibase spread spectrum system with chaotic sequence as spread spectrum code can reach 5.2 dB compared with the traditional direct spread spectrum system.
Ethical decision-making in human-automation collaboration: a case study of the nurse rostering problem
Authors: Bebien Vincent , Bellenguez Odile , Coppin Gilles , Ma-Wyatt Anna , Stephens Rachel 
Published: April 2024

AbstractAs artificial intelligence (AI) is increasingly present in different aspects of society and its harmful impacts are more visible, concrete methods to help design ethical AI systems and limit currently encountered risks must be developed. Taking the example of a well-known Operations Research problem, the Nurse Rostering Problem (NRP), this paper presents a way to help close the gap between abstract principles and on-the-ground applications with two different steps. We first propose a normative step that uses dedicated scientific knowledge to provide new rules for an NRP model, with the aim of improving nurses’ well-being. However, this step alone may be insufficient to comprehensively deal with all key ethical issues, particularly autonomy and explicability. Therefore, as a complementary second step, we introduce an interactive process that integrates a human decision-maker in the loop and allows practical ethics to be applied. Using input from stakeholders to enrich a mathematical model may help compensate for flaws in automated tools.
Bringing clarity and transparency to the consultative process underpinning the implementation of an ethics framework for AI-based healthcare applications: a qualitative study
Authors: Goirand Magali , Austin Elizabeth , Clay-Williams Robyn 
Published: April 2024

AbstractArtificial intelligence (AI) has been applied in healthcare to address various aspects of the COVID-19 crisis including early detection, diagnosis and treatment, and population monitoring. Despite the urgency to develop AI solutions for COVID-19 problems, considering the ethical implications of those solutions remains critical. Implementing ethics frameworks in AI-based healthcare applications is a wicked issue that calls for an inclusive, and transparent participatory process. In this qualitative study, we set up a participatory process to explore assumptions and expectations about ethical issues associated with development of a COVID-19 monitoring AI-based app from a diverse group of stakeholders including patients, physicians, and technology developers. We also sought to understand the influence the consultative process had on the participants’ understanding of the issues. Eighteen participants were presented with a fictitious AI-based app whose features included individual self-monitoring of potential infection, physicians’ remote monitoring of symptoms for patients diagnosed with COVID-19 and tracking of infection clusters by health agencies. We found that implementing an ethics framework is systemic by nature, and that ethics principles and stakeholders need to be considered in relation to one another. We also found that the AI app introduced a novel channel for knowledge between the stakeholders. Mapping the flow of knowledge has the potential to illuminate ethical issues in a holistic way.