bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oxysterol binding protein (OSBP) is needed for hepatitis E virus replication
Authors: Zhang Yanjin 
Published: July 2024

Abstract

Hepatitis E virus (HEV) is a positive-sense, single-stranded RNA virus and causes primarily acute self-limiting infections. The ORF1 of the HEV genome encodes a polyprotein around 190 kDa, which contains several putative domains, including helicase and RNA-dependent RNA polymerase. The HEV-encoded helicase is a member of the superfamily 1 helicase family and possesses multiple enzymatic functions, such as RNA 5’-triphosphatase, RNA unwinding, and NTPase, which are thought to contribute to viral RNA synthesis. However, the helicase interaction with cellular proteins remains less known. Oxysterol binding protein (OSBP) is a lipid regulator that shuffles between the Golgi apparatus and the endoplasmic reticulum (ER) for cholesterol and phosphatidylinositol-4-phosphate (PI4P) exchange and controls the efflux of cholesterol from cells. In this study, the deficiency of OSBP significantly reduced HEV replication. Further studies indicate that the HEV helicase interacted with OSBP, shown by co-immunoprecipitation and co-localization in co-transfected cells. The presence of helicase blocked OSBP preferential translocation to the Golgi apparatus. These results demonstrate that OSBP contributes to HEV replication and enrich our understanding of the HEV-cell interactions.
Emotional responses to climate change, mental health, and climate action: How are they related?
Authors: Mintz Keren Kaplan 
Published: July 2024

Abstract

As climate change becomes a reality, people are becoming increasingly aware of the threats associated with global warming. Many people may experience climate change as an unremitting psychological stressor associated with high levels of concern, worry and anxiety, that can emerge even in the absence of short-term or direct effects. Because emotions are related both to mitigation behavior and to promoting resilience and well-being, studying people’s emotional responses to climate change is important. This study explores the links of different emotional responses to climate change with mental health and pro-environmental behavior, using an online survey of a nationwide representative sample in Israel. An online survey of a nationwide representative sample of Hebrew speakers (N=302) revealed high levels of negative emotions, along with low levels of climate anxiety and moderate levels of positive emotions and indifference. Both climate change anxiety and negative emotions were associated with impairment in mental health. Positive emotions predicted an increase in both private-sphere and collective pro-environmental behavior, whereas indifference predicted a decrease in both types of behavior. Climate change anxiety predicted an increase in collective but not in private-sphere pro-environmental behavior. The research findings extend our understanding of the role played by different emotional responses to climate change in explaining impairment in mental health and adaptive pro-environmental behavior.
The Genomic Architecture of Circulating Cytokine Levels Points to Drug Targets for Immune-Related Diseases
Authors: Konieczny Marek J. , Omarov Murad , Malik Rainer , Richardson Tom G. , Baumeister Sebastian-Edgar , Bernhagen Jürgen , Dichgans Martin , Georgakis Marios K. 
Published: July 2024

Abstract

Circulating cytokines orchestrate immune reactions and are promising drug targets for immune-mediated and inflammatory diseases. Exploring the genetic architecture of circulating cytokine levels could yield key insights into causal mediators of human disease. Here, we performed genome-wide association studies (GWAS) for 40 circulating cytokines in meta-analyses of 74,783 individuals. We detected 359 significant associations between cytokine levels and variants in 169 independent loci, including 150 trans- and 19 cis-acting loci. Integration with transcriptomic data point to key regulatory mechanisms, such as the buffering function of ACKR1 acting as scavenger for multiple chemokines and the role of TRAFD1 in modulating the cytokine storm triggered by TNF signaling. Applying Mendelian randomization (MR), we detected a network of complex cytokine interconnections with TNF-b, VEGF, and IL-1ra exhibiting pleiotropic downstream effects on multiple cytokines. Drug target cis-MR paired with colocalization revealed G-CSF/CSF-3 and CXCL9/MIG as potential causal mediators of asthma and Crohn’s disease, respectively, but also a potentially protective role of TNF-b in multiple sclerosis. Our results provide an overview of the genetic architecture of circulating cytokines and could guide the development of targeted immunotherapies.
Generative-discriminative machine learning models for high-frequency financial regime classification
Authors: KOUKORINIS Andreas , PETERS Gareth W. , GERMANO Guido 
Published: July 2024

Abstract

We combine a hidden Markov model (HMM) and a kernel machine (SVM/MKL) into a hybrid HMM-SVM/MKL generative-discriminative machine learning approach to accurately classify high-frequency financial regimes and predict the direction of trades. The model captures temporal dependencies and key stylized facts in high-frequency financial time series by integrating the HMM to produce model-based generative feature embeddings from microstructure time series data. These generative embeddings then serve as inputs to a SVM with single-and multi-kernel (MKL) formulations for predictive discrimination. Our methodology, which does not require manual feature engineering, improves classification accuracy consistently over six trading regimes, outperforming a logistic classifier, single-kernel SVMs, a feed forward network and kernel target alignment methods. This hybrid HMM-SVM-MKL approach shows high-frequency time-series classification improvements that can significantly benefit applications in finance.
Deep Convolutional Networks for Affective Content Extraction from Textual Sources
Authors: Manda Asha Priyadarshini , Mohan A. Krishna 
Published: July 2024

Abstract

This paper proposes a Convolutional Neural Network (CNN) based system for classifying emotions in text data. The system tackles the challenge of automatically recognizing emotions expressed within textual content. The paper presents a comprehensive approach encompassing data preparation, model building, training, evaluation, saving, and prediction. The data preparation stage involves cleaning, balancing for imbalanced datasets, and pre-processing techniques such as tokenization and padding. The CNN model employs two branches with similar CNN layers for feature extraction. These features are then concatenated to create a richer representation. Dropout techniques are utilized during training to prevent over fitting. The system's performance is evaluated using various metrics like accuracy, precision, and recall. We visualize the learning process through training and validation curves. Additionally, confusion matrix and classification reports are employed to analyze the model's performance. Finally, the trained model and tokenizer are saved for future prediction tasks. This work offers a comprehensive framework for text emotion classification using CNNs, demonstrating its effectiveness in identifying emotions from textual data.
Associations between CAG repeat size, brain and spinal cord volume loss, and motor symptoms in spinocerebellar ataxia type 3: a cohort study
Authors: Ye Zhi-Xian , Chen Xuan-Yu , Li Meng-Cheng , Chen Xin-Yuan , Qiu Yu-Sen , Yuan Ru-Ying , Chen Zhi-Li , Lin Min-Ting , Hu Jian-Ping , Fu Ying , Chen Wan-Jin , Wang Ning , Gan Shi-Rui 
Published: July 2024

Abstract

Background: Spinocerebellar ataxia type 3 (SCA3) is a hereditary polyglutamine disease, caused by abnormally expanded cytosine–adenine–guanine (CAG) repeats in ATXN3 gene. It is classically characterized by cerebellar and spinal cord atrophy and presents with progressive ataxia. we here investigated the associations between expanded CAG repeat size, brain and spinal cord volume loss, and motor functions in SCA3.
Methods: In this prospective cross-observational study, we analyzed 3D T1-weighted MRIs from 92 patients with SCA3 and 42 healthy controls using voxel-based morphometry and region of interest approaches. Associations between CAG repeat size, brain and spinal cord volume loss, and International Cooperative Ataxia Rating Scale (ICARS) score were investigated using partial correlation and mediation analyses. Sample sizes of potential markers were calculated.
Results:Compared with healthy controls, SCA3 patients had lower cerebellar volume and cervical spinal cord area. SCA3 patients evolved along a stage-independent decline that began in the cerebellum, progressed to spinal cord, brainstem, thalami, and basal ganglia, and extensive subcortex. CAG repeat size was associated with right cerebellar lobule IV volume (r = -0.423, P < 0.001) and cervical spinal cord area (r = -0.405, P < 0.001), and higher ICARS (r = 0.416, P < 0.001). Mediation analysis revealed an indirect effect of CAG repeat size on ICARS through spinal cord. Sample sizes estimation revealed that a minimum sample size was achieved with spinal cordmeasures.
Conclusions: CAG repeat size influenced cerebellar lobule IV and cervical spinal cord volume loss. Our results indicated the potential of cervical spinal cord area as a marker for disease progression and sample size estimations in future SCA3 clinical studies.
The influence of ENSO-type on rainfall characteristics over Southern Africa during the austral summer
Authors: Mpheshea Lerato Elizabeth , Blamey Ross C. , Reason Chris J.C. 
Published: July 2024

Abstract

Although the El Niño-Southern Oscillation (ENSO) is the leading mode of climate variability in southern Africa during the austral summer season, the impacts are nonlinear and not all events result in the expected impact. Limited work has been carried out to explore the role ENSO diversity plays in southern African climate, which this study aims to address. Here, the influence of El Niño diversity on rainfall characteristics and whether the impact evolves on sub-seasonal scales are examined. Two broad types of El Niño events, namely Eastern Pacific (EP) and Central Pacific (EP) events, are first determined by the location of the positive SST anomaly in the equatorial Pacific. For the 1950-2022 period, 9 EP El Niño events and 10 CP El Niño events are identified. Results show significant variability in ENSO impacts on a sub-seasonal scale across southern Africa during the summer half of the year (October-March). EP events affect rainfall throughout the summer, with the strongest impacts in the core months (Dec-Jan), characterized by less rainfall, more frequent dry spells and extended dry periods. EP events have a stronger relationship with various rainfall characteristics across most of southern Africa compared to CP events. Consequently, the likelihood of experiencing a significant summer rainfall deficit is higher during EP events. These findings indicate that traditional seasonal definitions, like JFM, or generalizing ENSO as a single type of event, may be inadequate in assessing ENSO-induced rainfall impacts from a seasonal forecasting perspective.
Predictors of massive transfusion in patients with hollow organ injury after blunt abdominal trauma: a cohort of blunt bowel mesenteric injury
Authors: Hsieh Ting-Min , Chuang Po-Chun , Liu Chun-Ting , Wu Bei-Yu , Hsieh Ching-Hua , Cheng Fu-Jen 
Published: July 2024

Abstract

Background
Massive transfusion (MT) is life-saving for patients with exsanguination, especially after blunt abdominopelvic trauma, due to subtle manifestations. Blunt bowel mesenteric injuries (BBMI), besides their potential risk of peritonitis, are still one of the few indications for emergency laparotomy for hemorrhagic shock in the era of non-operative management. Early prediction of the necessity for MT is a critical point in resuscitation.
Methods
This retrospective study reviewed the data of hospitalized patients with trauma between 2009 and 2022, and included 163 adult patients with surgically proven BBMI. The patients were divided based on the presence or absence of MT before emergency laparotomy. Associated injury parameters and bowel mesenteric injury characteristics were used in multivariate regression analysis to identify independent predictors of MT.
Results
The MT (+) group included 30.6% of patients (n = 50). Compared to the MT (-) group, BBMI patients receiving MT had worse clinical injury severity, vital signs, and prognosis; received more units of blood products and more invasive treatments; had more isolated mesenteric injury or combined injury; and had both higher morbidity and mortality rates (94% vs. 55.8%, p < 0.001 and 32% vs. 4.4%, p < 0.001). In multivariate analysis, the presence of traumatic brain injury (TBI) (odds ratio [OR] = 6.7, 95% confidence intervals [CIs]: 1.66–27.02) and pelvic fracture (OR = 6.01, 95% CIs = 1.45–24.89) was identified as an independent predictor of MT after adjusting for confounding factors.
Conclusions
Almost half the patients with BBMI present with shock episodes, and one-third of them require MT before laparotomy, reflecting the critical status for their exsanguination. Patients with associated TBI and pelvic fracture injuries are at increased risk of MT and need to be prioritized for resuscitation.
Development of a Pellet Extruder for Blending Different Materials and Study on the Properties of Eco-friendly Flame Retardant Materials Printed Using a Large-scale 3D Printer
Authors: Jung minsu , Ha Jeong-Ung , Park Jong-kyu 
Published: July 2024

Abstract

This study aims to design and fabricate a pellet extruder capable of blending different materials for the application of flame-retardant building materials in 3D printing and to evaluate the properties of eco-friendly flame-retardant materials printed using a large-scale 3D printer. The main content of the research is as follows: To ensure the printing stability of the large 3D printer, the deflection amount of the axis due to the weight of the pellet extruder was verified through structural analysis. This made it possible to achieve stable printing even on a large bed (1000mm x 1000mm). Next, a pellet extruder capable of blending different materials was developed to quickly collect initial mixing ratios and temperature data, and specimen printing was conducted using this extruder. The flame-retardant performance and mechanical properties of the printed flame-retardant material were evaluated, and PLA specimens mixed with calcium carbonate at various ratios from 5% to 20% were produced to conduct flame-retardant performance tests and tensile tests according to UL-94 standards. As a result, it was found that the flame-retardant performance improved as the calcium carbonate content increased, and the optimal mixing ratio was derived. Finally, to verify the printing stability of the extruder and large 3D printer, a honeycomb composite structure was printed continuously for 1 hour and 30 minutes, and it was confirmed that continuous printing was possible with a maximum error of 1mm. The proposed development systems satisfy both stable printing of large composite structures and excellent flame-retardant performance, confirming the potential for use as eco-friendly building material prints.
The foresight methodology for transitional shale gas reservoirs prediction based on a knowledge graph
Authors: Li Wenyu , Zhao Jingtao , Qiu Zhen , Gao Wanli , Peng Hongjie , Zhang Qin 
Published: July 2024

Abstract

The sedimentary environment in the eastern Ordos area of China is complex and contains a large number of transitional facies environments. Yet, there are many characteristics such as large vertical lithology changes, complex lateral sedimentary environment changes, small monolith thickness and large organic matter content changes, which lead to large uncertainty in the prediction of favorable areas for transitional shale gas. As the intricate reservoirs continue to unfold, the conventional linear prediction methods find themselves facing an arduous path to meet the demands of development. The ever-evolving complexity of these reservoirs has outpaced the capabilities of these traditional approaches. It becomes apparent that a more comprehensive and adaptable approach is necessary to navigate the intricacies of these reservoirs and unlock their hidden potential. Therefore, we put forward a method of introducing knowledge graph into shale gas reservoir prediction by using big data technology. Because artificial intelligence big data relies heavily on data tags, it is particularly important for the construction of tags. Firstly, a top-down knowledge graph in the field of reservoir prediction is constructed to determine the key parameters used in prediction, namely porosity, total organic carbon (TOC) and brittleness index. Secondly, the decision tree knowledge graph optimization label is constructed in a bottom-up way. The key parameter of this prediction is the knowledge graph obtained according to the professional knowledge of reservoir prediction, so as to optimize the school label of U-net and reduce the workload of artificial judgment. The results of the combination of the two methods are applied to 11 wells in Daji area of Ordos, and the experimental results are consistent with the actual situation of the reservoir. Based on the foundation of theoretical knowledge, this method enhances the efficiency and accuracy of interpretation and evaluation. It provides fundamental and technical support for the selection of favorable areas in shale gas exploration and the evaluation of exploration and development prospects, particularly in transitional shale gas areas, which is innovative and advanced in the field.
Three-dimensional stability calculation method and application of intermediate bridge supporting consequent bedding slope in open-pit mine
Authors: Wang Dong , Liang Zuchao , Li guanghe , Xv Yongchao , Zhao lichun , Zhang Jie 
Published: July 2024

Abstract

Solving the dynamic synergistic design challenge of slope and intermediate bridge during parallel stripping of multi-pits is crucial to realizing both safe production and economic benefits of mines. Based on the analysis of the failure mode of the intermediate bridge supporting consequent bedding slope, constructed a 3D mechanical model of the intermediate bridge, and analyzed the 3D supporting effect quantitatively. Combined with Mohr-Coulomb shear strength theory, a 2D equivalent method considering the 3D supporting effect of intermediate bridge under different failure modes is proposed, and a 3D stability calculation method of slope under this effect is established. In addition, the main influencing factors of the intermediate bridge supporting effect are analyzed. The 3D stability coefficient regression model is constructed by using the response surface method, and the validity of the model for solving practical engineering problems is verified by engineering application. The results show that when considering the combined sliding failure mode, the design bottom width d should be given priority in the establishment of supporting structures such as dump bridges, for the intermediate bridge demolition design project, the design bridge length should be given priority b. The interaction between the bottom width d and the bridge height h has a significant effect on the 3D stability of the slope; For the shear dilatancy failure mode, the supporting and demolition engineering should give priority to the design of bridge height h and bottom width d respectively. The interaction between bridge height h and bridge length b has the most significant effect on the 3D stability of the slope. The error rate between the 3D stability calculation results and the predicted value of the regression model is 1.9–3.3%, and the regression model can fully meet the actual needs of the project. This study lays a theoretical and application foundation for the dynamic collaborative design, stability control and engineering implementation of slope and intermediate bridge in multi-pit parallel stripping open-pit coal mine.
Investigation of the Applicability of the Boer Formula for Estimating the Angular Velocity of Rotation of a Small Spacecraft by Measuring the Components of the Induction Vector of the Earth's Magnetic Field in Evaluating Micro-Accelerations and Forming Control Laws
Authors: Sedelnikov Andry , Skidanov Roman , Taneeva Anastasia , Manukyan Luisa , Ivanushkin Maksim , Mordanov Marsel 
Published: July 2024

Abstract

The paper presents studies on the correctness of the application of the simplified Boer formula for estimating the components of the angular velocity vector of the spacecraft using the example of the small ISOI spacecraft (SXC3-219). The simplification consists in neglecting the total derivative of the induction vector of the Earth's magnetic field in time compared to the local derivative. This is due to the fact that measurements are carried out quite often. Therefore, the magnetic induction vector in two adjacent dimensions can be considered unchanged. The aim of the work is to estimate the error in determining the angular velocity due to this simplification. The presented results show the admissibility of neglecting the full derivative, provided that the measurement frequency is sufficient. Reference metrological tests were carried out, in which a gyroscopic angular velocity vector meter was selected as the reference measuring instrument. The errors in the estimates of micro-accelerations and the control moment, which are a consequence of the error in determining the angular velocity, are calculated.
Reliability Research of Thyristors for HVDC Transmission System
Authors: XU Yang , Pang Lei , Xie Tianxi , Chen Zhengguang , Guo Jun 
Published: July 2024

Abstract

The long-term operation performance of HVDC transmission systems is significantly influenced by the reliability of thyristors. However, the current reliability research of thyristors is mainly based on the leakage current and there is no comprehensive degradation characteristics of thyristors. In this article, the degradation characteristics of thyristors under voltage and temperature accelerated ageing tests are obtained, including the reverse recovery characteristic, on-state characteristic, blocking characteristic and gate characteristic. The reverse recovery characteristic obviously degrades under the voltage accelerated ageing tests. The reverse recovery charge and reverse recovery time decrease by over 10% after the tests. Seven thyristors operating for a certain number of years from two HVDC stations are tested, and the results verify the thyristor degradation characteristics obtained from the ageing tests. Moreover, the mechanisms of the leakage current and reverse recovery characteristic are analyzed in detail.