bluuebunny/crossref_metadata_2025_split huggingface dataset:
MicroElectroThermoForming (μETF): One-step Versatile 3D Shaping of Flexible Microelectronics for Enhanced Neural Interfaces
Authors: Jeong Joonsoo , Lee Dong Hyeon , Park Younghoon , Seo Yoon , Jeong Hyunbeen , Seo Jong-Mo , Seo Min-Ho , Eom Kyungsik 
Published: September 2024

Abstract

Increasing the proximity of microelectrode arrays (MEA) to targeted neural tissues is crucial for establishing efficient neural interfaces for both recording and stimulation applications. This has been achieved by constructing protruding three-dimensional (3D) structures on top of conventional planar microelectrodes via additional micromachining steps. However, this approach adds fabrication complexities and limits the 3D structures to certain shapes. We propose a one-step fabrication of versatile microscopic 3D structures for thin-film MEAs via “microelectrothermoforming (µETF)” of thermoplastics, by utilizing 3D-printed molds to locally deform planar MEAs into desired protruding and recessing shapes. Electromechanical optimization of the µETF process enabled a 3D MEA with 80 µm protrusions and/or recession for 100 µm diameter. Its versatile shaping capabilities are demonstrated by simple and simultaneous forming of diverse 3D structures on a single MEA. The benefits of 3D MEA are evaluated in retinal stimulation through numerical simulations and ex vivo experiments, confirming a threshold lowered by 1.7 times and spatial resolution enhanced by 2.2 times.
Childhood Predictors of Perceptions of Social Trust: A Cross-National Analysis in the Global Flourishing Study
Authors: Kim Young-IL , VanderWeele Tyler , Johnson Byron 
Published: September 2024

Abstract

Despite several decades of research on social trust, empirical evidence on the impact of childhood experiences on generalized trust in later life has long been lacking. This is surprising because mounting evidence suggests that trusting disposition is largely determined during the formative periods of childhood. Using nationally representative samples from 22 countries of six continents (N = 202,898), we identified several childhood predictors associated with perceptions of generalized trust in adulthood. The quality of the relationship with one’s mother and father, childhood socioeconomic status, childhood health, and childhood religious service attendance are significantly associated with greater levels of social trust perceptions later in life. Conversely, experiences of abuse during childhood are significantly associated with lower levels of social trust perceptions. We also find that the strength of these associations markedly vary across countries, highlighting diverse societal influences and cultural contexts that characterize each country. The results of the current study suggest that family environment plays a significant role in the formation of perceptions of generalized trust.
Development of a Ground Motion Model for Taiwan Using XGBoost and Its Implementation in Seismic Hazard Assessment
Authors: Chang Chih-Yu , Chan Chung-Han , Gao Jia-Cian , Ma Kuo-Fong 
Published: September 2024

Abstract

This study utilizes the XGBoost model integrated with the Flatfile database, strong ground motion records derived from the Taiwan Strong Motion Instrumentation Program (TSMIP), to establish a crustal ground motion model (GMM) in forms of PGA, PGV, and spectral acceleration. When evaluating the performance of these models, particular attention is paid to the standard deviation of residuals and the R² score, as well as multiple analysis methods such as distance response, response spectra, and residual distribution to thoroughly assess the effectiveness and rationality of the models. Additionally, a key aspect of the methodology is the application of SHAP (SHapley Additive exPlanations) values to validate the importance of different predictors within our model. This approach not only clarifies the impact of various factors on strong ground motion but also highlights the interpretability of the model, addressing the traditional demands of engineering seismology for model rationality and explainability. Considering the imbalance in the earthquake dataset, especially lack of larger-scale and near-field events, the Smoter and Gaussian Noise (SMOGN) method is used for data augmentation. This method effectively balances the dataset, thereby enhancing the model to learn from rare but significant large-scale and/or near-field seismic events. The study also demonstrates the applicability of the model in seismic hazard assessment using the seismic hazard analysis software, incorporating our strong motion attenuation model for seismic motion simulation. The incorporation of machine learning techniques into the development of GMM marks a significant step forward in the advancement of seismic hazard assessment in Taiwan. This research could have a substantial impact on earthquake preparedness strategies, infrastructure resilience planning, and public safety protocols, demonstrating the potential of machine learning in engineering seismology.
Exploring the mechanism of Pim-1 upregulation of tissue factor to initiate hypercoagulable state in sepsis
Authors: Wang Qing , Wang Ying , Hong Yun , Zhang Rongrong , Zhou Chen , Pan Jingye 
Published: September 2024

Abstract

Background
During sepsis-induced coagulopathy (SIC), the balance of coagulation, anticoagulation, and fibrinolysis is disrupted, and endothelial dysfunction plays a key role in the disease progression. Current studies have indicated that the Proviral integration site for Moloney murine leukemia virus 1 (Pim-1) can promote thrombosis and activate an autoimmune response. This study aimed to assess the relevance of inhibiting Pim-1 as a potential therapeutic target for SIC.
Methods
Wild-type, Pim-1-KO, and TLR4-KO mice were categorized into the sham and cecal ligation and puncture (CLP) groups. Human umbilical vein endothelial cells were classified into the control, lipopolysaccharide (LPS) stimulation, and intervention groups. Enzyme-linked immunosorbent assay was used to detect plasma coagulation index in mice. Western blotting and immunofluorescence were employed to examine protein expression in tissues or cells. Additionally, immunohistochemistry and hematoxylin and eosin staining were conducted to detect liver/lung tissue damage. Tissue factor (TF) promoter activity was detected using a dual-luciferase reporter assay. Moreover, the correlation between variables was determined using Pearson correlation analysis.
Results
Pim-1 inhibition can decrease the coagulation response of sepsis mice and improve the survival rate. Pim-1 administration activated LPS-induced endothelial injury via mTOR/Sp1/TF signaling pathways, and Pim-1 acts in endothelial cells via the TLR4 pathway.
Conclusions
These findings indicated that Pim-1 promotes TF upregulation, leading to the initiation of a hypercoagulable state in sepsis. Therefore, inhibiting Pim-1 activity may be a therapeutic approach for SIC.
Characteristics of Transition to Turbulence in a Thoracic Aorta Using Large Eddy Simulation
Authors: Cheng Kuiyu , Akhtar Shehnaz , Lee Kwan Yong , Lee Sang-Wook 
Published: September 2024

Abstract

This study employed Large Eddy Simulation (LES) with the wall-adapting local eddy-viscosity (WALE) model to investigate transitional flow characteristics in an idealized thoracic aortic model. The OpenFOAM solver pimpleFoam was used to simulate blood flow as an incompressible Newtonian fluid, with the aortic walls treated as rigid boundaries. Simulations were conducted for 30 cardiac cycles and ensemble averaging was employed to ensure statistically reliable results. Main hemodynamic parameters, such as velocity fields, turbulence intensity and wall shear stress (WSS) were analyzed throughout the circulatory system. Through 3D computational fluid dynamics (CFD) visualization, we explained the transition from laminar to turbulent flow and its development throughout the cardiac cycle. Results demonstrated that turbulence originates in the aortic arch following the peak systole phase and further develops in the aortic arch and descending aorta during the mid-deceleration and end-systole phases. The WSS at the aortic arch is relatively high, which may be related to the development of various diseases, such as type A aortic dissection and atherosclerosis.
Efficacy of a Continuous Dean Flow UV-C System in Almond Milk Pasteurization Using Computational Fluid Dynamics and Biodosimetry
Authors: Singh Amritpal , Sharma Aakash , Pendyala Brahmaiah , Balamurugan Sampathkumar , Patras Ankit 
Published: September 2024

Abstract

A continuous Dean flow UV-C system was designed using fluorinated ethylene propylene tubing with UV-C transmission ≈ 60% wrapped in a serpentine path to improve axial mixing with a Dean number > 140. The microbial inactivation efficiency of the system was evaluated using Salmonella Typhimurium, E. coli O157:H7, Staphylococcus aureus, Saccharomyces Cerevisiae, and T1UV inoculated in almond milk (AM) and treated at various fluence levels at an optimized flow rate of 515 ml/min. In addition, a detailed examination of the velocity magnitude at various locations in a dean flow system, especially at the bends, was quantified. The findings indicate that a reduction > 4 log was attained for all specified microorganisms with a reduction equivalent fluence of 22.05 mJ/cm2. Additionally, computational fluid dynamics were employed to examine the velocity magnitude and incident radiation field within the tubing. In summary, the system demonstrated effectiveness in inactivating target microorganisms present in almond milk.
Bounded Satisfiability Checking of FOL * Formulas with Aggregations
Authors: Feng Nick , Marsso Lina , Kholodetska Yuliia , Chechik Marsha 
Published: September 2024

Abstract

Software systems handling data are increasingly required to comply with legal properties (LPs) aimed at ensuring security and data privacy. Automated reasoning of LPs can be carried out by solving constraint satisfiability problems in first-order logic. However, the current logic-based reasoning approaches have limited support for capturing and reasoning about LPs with aggregation constraints, which are commonly found in financial and privacy policies. In this work, we extend first-order logic with quantifiers over relational objects (FOL *) to support aggregation, resulting in a language FOL * + , and propose a satisfiability checking algorithm, LEGOS-A, for FOL * + which supports reasoning about aggregation by over-and under-approximating the aggregated values and incrementally refining these approximations to derive the satisfiability result. Running LEGOS-A on real world and academic examples with aggregation from various domains showed that LEGOS-A was able to solve many previously intractable problems and provided substantial speed-ups compared to the state-of-the-art FOL * satisfiability checker and other SMT-based alternatives.
Soft sensor modeling for the fermentation process of Pichia pastoris based on the transfer modeling of substructural domain
Authors: Wang Bo , Wei Jun , Zhang Le , Jiang Hui , Jin Cheng , Huang Shanwei 
Published: September 2024

Abstract

Aiming at the problem that traditional transfer methods are prone to lose data information in the overall domain-level transfer, and it is difficult to achieve the perfect match between source and target domains, thus reducing the accuracy of the soft sensor model, this paper proposes a soft sensor modeling method based on the transfer modeling framework of substructural domain. Firstly, the Gaussian mixture model clustering algorithm is used to extract local information, cluster the source and target domains into multiple substructural domains, and adaptively weight the substructural domains according to the distances between the sub-source domains and sub-target domains. Secondly, the optimal subspace domain adaptation method integrating multiple metrics is used to obtain the optimal projection matrices Ws and Wt that are coupled with each other, and the data of source and target domains are projected to the corresponding subspace to perform spatial alignment, so as to reduce the discrepancy between the sample data of different working conditions. Finally, based on the source and target domain data after substructural domain adaptation, the least squares support vector machine algorithm is used to establish the prediction model. Taking Pichia pastoris fermentation to produce inulinase as an example, the simulation results verify that the proposed soft sensor modeling method can accurately predict Pichia pastoris concentration and inulinase concentration online under different working conditions, and has higher prediction accuracy than the traditional soft sensor modeling method.
Experimental Investigations of Fluid-to-Vehicle Interactions during a Reusable Launcher’s Touchdown Impact
Authors: Krämer Caroline , Witte Lars 
Published: September 2024

Abstract

Several programmes are dedicated worldwide to the development of reusable vertical take-off vertical landing (VTVL) launch vehicles. Thereby, the touchdown event with its associated impact forces and shocks poses load cases to the vehicle being new in the launcher domain. Furthermore, the application of related knowledge from planetary, exploration-type landers has to be taken cautiously due to the differences between those types of vehicle, particularly with regard to their tank configuration and structural sizing. Depending on flight test conditions and operational concept, non-neglectable amounts of liquid propellant can still be inside the tanks at landing and interact with the vehicle. These interactions cause dynamic and structural effects that affect the landing stability and structural integrity of the vehicle. This study aims to experimentally investigate the fluid-vehicle interactions of a fully functional touchdown demonstrator during touchdown. For this, a vehicle landing engineering model is equipped with a circular cylindrical tank and a series of touchdown test with varying horizontal landing velocities and fill levels is conducted. Thereby, the main objectives are to prove repeatable landing behaviour under sloshing impact for constant landing conditions, characterise the fluid impact on landing stability and investigate the fluid-structure interactions on the tank. Therefor test data of different test cases is compared and analysed with regards to dynamic behaviour and structural responses.
Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis
Authors: Zhang Ya , Jiang Aofan , Huang Chaoqin , Cao Qing , Xu Yuchen , Zeng Zi , Chen Kang , Wang Yanfeng 
Published: September 2024

Abstract

Current computer-aided ECG diagnostic systems struggle with the underdetection of rare but critical cardiac anomalies due to the imbalanced nature of ECG datasets. This study introduces a novel approach using self-supervised anomaly detection pretraining to address this limitation. The anomaly detection model is specifically designed to detect and localize subtle deviations from normal cardiac patterns, capturing the nuanced details essential for accurate ECG interpretation. Validated on an extensive dataset of over one million ECG records from clinical practice, characterized by a long-tail distribution across 116 distinct categories, the anomaly detection-pretrained ECG diagnostic model has demonstrated a significant improvement in overall accuracy. Notably, our approach yielded a 94.7% AUROC, 92.2% sensitivity, and 92.5% specificity for rare ECG types, significantly outperforming traditional methods and narrowing the performance gap with common ECG types. The integration of anomaly detection pretraining into ECG analysis represents a substantial contribution to the field, addressing the long-standing challenge of long-tail data distributions in clinical diagnostics. Furthermore, prospective validation in real-world clinical settings revealed that our AI-driven approach enhances diagnostic efficiency, precision, and completeness by 32%, 6.7%, and 11.8% respectively, when compared to standard practices. This advancement marks a pivotal step forward in the integration of AI within clinical cardiology, with particularly profound implications for emergency care, where rapid and accurate ECG interpretation is crucial. The contributions of this study not only push the boundaries of current ECG diagnostic capabilities but also lay the groundwork for more reliable and accessible cardiovascular care.
Demographic Variation and Childhood Predictors of Perceived Discrimination Across 22 Countries
Authors: Yancey George , Grigoropoulou Nikolitsa , Emerson Michael , VanderWeele Tyler , Johnson Byron 
Published: September 2024

Abstract

Discrimination remains widespread around the globe, but less is known about the prevalence, variability, and determinants of perceived discrimination across diverse cultures. This study investigates the variation in perceived discrimination across 22 countries and identifies key demographic and childhood factors shaping these perceptions. Using data from the Global Flourishing Study, we document substantial cross-national differences in perceived discrimination, with countries like Egypt, South Africa, and Nigeria reporting higher levels, while Sweden, Poland, and Tanzania exhibiting lower levels. Demographically, younger adults, separated individuals, the unemployed, frequent religious service attenders, and Muslims are more likely to report discrimination, although patterns vary by country. Importantly, we also identify significant childhood predictors of perceived discrimination in adulthood. Adverse childhood experiences (ACEs), including abuse and feeling like an outsider within the family, significantly increase the risk of perceived discrimination later in life. However, childhood predictors’ effects vary across countries, suggesting both universal and culturally specific influences. Our study underscores the enduring impact of early life experiences on adult perceptions of discrimination and highlights the need for targeted interventions to address these root causes globally. The findings provide crucial insights for policymakers and scholars aiming to reduce discrimination and promote social equity across diverse cultural contexts.
Irreversible glacier change and trough water for centuries after overshooting 1.5°C
Authors: Schuster Lilian , Maussion Fabien , Rounce David , Ultee Lizz , Schmitt Patrick , Lacroix Fabrice , Frölicher Thomas , Schleussner Carl-Friedrich 
Published: September 2024

Abstract

Due to past climate inaction, exceeding a global mean temperature level of 1.5°C above pre-industrial levels has become a distinct possibility. Yet the consequences of such an overshoot are not well understood, including mountain glaciers' contribution to rising sea levels and regional water availability. Here we show that exceeding and then returning to the 1.5°C Paris Agreement limit has irreversible consequences for glacier mass and runoff over centuries. Novel global climate and glacier simulations project that a 3.0°C peak and decline scenario leads to 11% additional loss in global glacier mass by 2500 compared to limiting warming to 1.5°C without overshoot. In basins where glaciers regrow after peak temperature, glacier runoff reduces further than if the glaciers would stabilise, a newly documented phenomenon we call ″trough water″. Half of the studied glaciated basins show a lower glacier contribution to runoff with overshoot than without for decades to centuries post peak warming. These previously undocumented risks to glacier mass loss and runoff underscore the urgency of near-term emission reductions and limiting any potential climate overshoot.
Electrochemically-enhanced nuclear fusion of deuterium
Authors: Berlinguette Curtis , Chen Kuo-Yi , Schauer Phil , Issinski Sergey , Garcia Fatima H. , Oldford Ryan , Egoriti Luca , Higashino Shota , Maiwald Jannis , Vakili Aref E. , Wen Yunzhou , Koh Joseph , Schenkel Thomas , Stolar Monika , Brown Amanda K. 
Published: September 2024

Abstract

The ultimate goal of nuclear fusion research is to achieve a reaction that generates more energy than it consumes. Fuels such as deuterium need to be confined to increase the collision probability of particles. We therefore set out to investigate whether electrochemically loading a metal lattice with deuterium fuel could increase the probability of nuclear fusion events. Here, we report a benchtop fusion reactor that enabled us to bombard a palladium metal target with deuterium ions. These deuterium ions undergo deuterium-deuterium (D-D) fusion reactions within the palladium metal. We showed that the in situ electrochemical loading of deuterium into the palladium target resulted in a 15(2)% increase in D-D fusion rates. This experiment shows how electrochemical reactions at the eV energy scale can impact nuclear reactions at the MeV energy scale.
Contrasting human influences that shaped the vegetation of the Upano Valley, Ecuador.
Authors: Bush Mark , Sales Rachel , Neill David , León-Yánez Susana , Sinkler Wyllana , Stanley Amie , Bennett Isabel , Gomes Bianca Tacoronte , Land Klaas , McMichael Crystal 
Published: September 2024

Abstract

Long histories of human occupation are emerging for the wet forests of the Andean flank, even ones that are apparently ‘pristine’. The past habitations were societally and temporally complex with sophisticated cultures emerging, flourishing, and disappearing. The Upano River in eastern Ecuador supported such cultures, and yet the timing of occupation and whether their impact on the local ecosystem resulted in lasting ecological changes is not known. Here, using paleoecological reconstructions from Lake Cormorán, located immediately adjacent to the Upano Valley and within 5 km of abandoned mound complexes, we provide a timeline of human influence spanning the last 2770 years. We document the onset of maize cultivation c. 570 BCE, changes in land use within the occupation phase, with evidence of slash-and-burn, slash-and-mulch and silviculture. A gradual decline in forest exploitation presaged an apparent abandonment of the site c. 550 CE. A much later wave of land use that began about 1500 CE, coupled with a regional transition to a wetter climate, produced a distinctive forest composition unique to the last 120 years.
Macroeconomics Dynamics: Exploring the Impact of Stock Market Development on Economic Growth in Mali
Authors: CISSE Boubacar Amadou , TEME Aminata , KEITA Salimou , SÖNMEZ Yahya 
Published: September 2024

Abstract

Economic growth is often influenced by various factors, with stock market development playing a crucial role. This study investigates the relationship between the stock market development, specifically the Bourse Régionale des Valeurs Mobilières (BRVM), and economic growth in Mali. The BRVM serves eight West African countries, including Mali, and its development may impact regional economies. Utilizing monthly data from January 2009 to December 2020, this research examines the effects of BRVM Market Capitalization, BRVM Composite Index, Capital Flow, and Inflation on Mali's Gross Domestic Product (GDP). The study employs an Autoregressive Distributed Lag (ARDL) model and Vector Error Correction (VEC) model to analyze both short-run and long-run relationships. Findings suggest a significant long-run relationship between stock market development and economic growth in Mali, with inflation and capital flow having negative impacts, while market capitalization and the BRVM Composite Index show positive but less significant effects. The study contributes to understanding the macroeconomic dynamics within West African economies and the importance of stock market development in promoting economic growth.
Gel: E02, E20, O10, F43