bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fluid‐Mantle Interaction Along the Mariana Convergent Margin
Authors: Miladinova Irena , Kurz Walter , Hilmbauer‐Hofmarcher Thomas 
Published: September 2023

AbstractActive serpentinite mud volcanoes in the forearc region of the Izu‐Bonin‐Mariana system represent an excellent natural laboratory for studying the geochemical processes along convergent plate margins and the associated forearc. During IODP Expedition 366, serpentinite mud with lithic clasts from the underlying forearc crust and mantle as well as from the subducting Pacific Plate was recovered. Ultramafic clasts from Fantangisña Seamount reveal very high degrees of serpentinization with mesh and bastite textures as well as development of late lizardite and chrysotile veins, which suggests serpentinization temperatures below 200°C. On the other hand, recovered harzburgites and, on occasion, dunites from Asùt Tesoru Seamount show a well‐preserved primary assemblage with low degrees of serpentinization and forearc peridotite characteristics. Fine‐grained antigorite associating with lizardite has been identified throughout the serpentine mud matrix, suggesting an alteration temperature of c. 340°C. Furthermore, alteration conditions during rodingitization point to temperatures of at least 228°C, estimated via chlorite geothermometry. Additionally, a rare ophicarbonate clast containing andraditic as well as Cr‐rich hydrogarnets from Asút Tesoru Seamount indicates crystallization temperatures of at least 230°C. Hence, a trend of lower temperature of serpentinization and higher degree of alteration closer to the trench. The detailed characterization of the fluid‐rock alteration conditions as well as fluids composition and transport permits a better constraining of the fluid–rock interactions and related mass transfers within subduction zones and during ascent of serpentinite fault gouge within mud volcano conduits and in mudflows after their emplacement on the flanks of the edifices.
Active Deformation Constraints on the Nubia‐Somalia Plate Boundary Through Heterogenous Lithosphere of the Turkana Depression
Authors: Musila M. , Ebinger C. J. , Bastow I. D. , Sullivan G. , Oliva S. J. , Knappe E. , Perry M. , Kounoudis R. , Ogden C. S. , Bendick R. , Mwangi S. , Mariita N. , Kianji G. , Kraus E. , Illsley‐Kemp F. 
Published: September 2023

AbstractThe role of lithospheric heterogeneities, presence or absence of melt, local and regional stresses, and gravitational potential energy in strain localization in continental rifts remains debated. We use new seismic and geodetic data to identify the location and orientation of the modern Nubia‐Somalia plate boundary in the 300‐km‐wide zone between the southern Main Ethiopian Rift (MER) and Eastern Rift (ER) across the Mesozoic Anza rift in the Turkana Depression. This region exhibits lithospheric heterogeneity, 45 Ma‐Recent magmatism, and more than 1,500 m of base‐level elevation change, enabling the assessment of strain localization mechanisms. We relocate 1716 earthquakes using a new 1‐D velocity model. Using a new local magnitude scaling with station corrections, we find 1 ≤ ML ≤ 4.5, and a b‐value of 1.22 ± 0.06. We present 59 first motion and 3 full moment tensor inversions, and invert for opening directions. We use complementary geodetic displacement vectors and strain rates to describe the geodetic strain field. Our seismic and geodetic strain zones demonstrate that only a small part of the 300 km‐wide region is currently active; low elevation and high‐elevation regions are active, as are areas with and without Holocene magmatism. Variations in the active plate boundary's location, orientation and strain rate appear to correspond to lithospheric heterogeneities. In the MER‐ER linkage zone, a belt of seismically fast mantle lithosphere generally lacking Recent magmatism is coincident with diffuse crustal deformation, whereas seismically slow mantle lithosphere and Recent magmatism are characterized by localized crustal strain; lithospheric heterogeneity drives strain localization.
Influence of Asian Topography on the Arctic Stratospheric Ozone
Authors: Wang Qilu , Duan Anmin , Pan Zhulei 
Published: September 2023

AbstractEvaluating the impact of topography on stratospheric ozone is a crucial step toward achieving a deeper comprehension of the role of topography uplift in driving paleoclimatic evolution and stratospheric dynamics and chemistry. This paper quantitatively estimates the contribution of Asian topography to Arctic stratospheric ozone by topography experiments in the Whole Atmosphere Community Climate Model version 6. The results indicate that Asian topography exerts an especially robust influence on Arctic stratospheric ozone during winter. Compared to the flattened topography, Asian topography significantly increases the ozone by 15% in the lower Arctic stratosphere, accompanied by the highest accumulation of total ozone appearing in the polar region north to the North American continent. The intensified residual mean circulation transport is principally responsible for the increase in ozone, and Asian topography has a stronger impact on the vertical residual mean transport than on the meridional residual mean transport. Further examination demonstrates that the robust strengthening of planetary waves caused by Asian topography significantly contributes to the enhancement of the residual mean circulation. Specifically, the upper Arctic stratosphere experiences a 42.7% increase in the amplitude of planetary waves with wavenumber 1, which means the weakened polar vortex. The diagnosis of the mean Lorenz energy cycle further indicates that Asian topography decreases the zonal mean kinetic energy and increases the eddy kinetic energy in the stratosphere. Therefore, the enhancement of residual mean circulation transport and the weakening of the polar vortex both work together to promote the accumulation of Arctic ozone.
Subdaily Extreme Precipitation and Its Linkage to Global Warming Over the Tibetan Plateau
Authors: Ma Mengnan , Tang Jianping , Ou Tinghai , Chen Deliang 
Published: September 2023

AbstractThe spatiotemporal characteristics of subdaily extreme precipitation over the Tibetan Plateau (TP) have undergone significant changes due to global warming. In this study, we employed the high‐resolution Weather Research and Forecasting regional climate model to conduct a series of historical and projection simulations under representative concentration pathways (RCPs), especially RCP4.5 and RCP8.5. The aim was to investigate the past and future climatologies and spatiotemporal evolution of subdaily precipitation extremes using newly proposed subdaily extreme precipitation indices (EPIs). The results show that projected changes in precipitation amount, particularly during wet hours, exhibit spatial disparaties. Notably, there are significant decreases along the southern border of the TP and over the western TP, while obvious increases are observed over the inner TP. The southeastern TP, western TP, and southern border of the TP are expected to experience less frequent, shorter duration, and more intense precipitation on an hourly basis. The TP, as a whole, has demonstrated significantly increasing trends in moderate‐to‐heavy precipitation frequencies, along with consistent decreasing trends in precipitation events with short, medium, and long durations. Furthermore, it is predicted that the relationship between extreme precipitation and temperature will deviate from the Clausius‐Clapeyron (C‐C) relationship toward the double C‐C relationship in the far‐future under RCP8.5, particularly over the southeastern TP. Additionally, there are robust correlations between the intensity‐related EPIs and elevation. This indicates that, at the local scale, the complex topography of the region may play a crucial role in shaping the nonuniform distribution of precipitation extremes by modulating associated upward motion.
Investigating the Interhemispheric Asymmetry in Joule Heating During the 2013 St. Patrick's Day Geomagnetic Storm
Authors: Smith A. R. , Ozturk D. S. , Delamere P. , Lu G. , Kim H. 
Published: September 2023

AbstractSudden changes in energy input from the magnetosphere during geomagnetic storms could drive extreme variability in the ionosphere‐thermosphere system, which in turn affect satellite operations and other modern infrastructure. Joule heating is the main form of magnetospheric energy dissipation in the ionosphere‐thermosphere system, so it is important to know when and where Joule heating will occur. While Joule heating occurs all the time, it can increase rapidly during geomagnetic storms. We investigated the Joule heating profile of the 2013 St Patrick's day storm using the University of Michigan Global Ionosphere‐Thermosphere Model (GITM). Using empirical and data‐assimilated drivers we analyzed when and where intense Joule heating occurred. The timing, location, and sources of interhemispheric asymmetry during this geomagnetic storm are of key interest due to near equinox conditions. Hemispheric comparisons are made between parameters, including solar insolation, total electron content profiles, and Pedersen and Hall conductance profiles, obtained from GITM driven with empirical driven input, versus those driven with data‐assimilated patterns. Further comparisons are made during periods of peak hemispheric Joule heating asymmetry in an effort to investigate their potential sources. Additionally, we compare the consistency of the interhemispheric asymmetry between empirical‐ and data‐assimilated driven simulations to further analyze the role of data‐assimilated drivers on the IT system.
Interoceptive regulation of skeletal tissue homeostasis and repair
Authors: Xiao Yao , Han Changhao , Wang Yunhao , Zhang Xinshu , Bao Rong , Li Yuange , Chen Huajiang , Hu Bo , Liu Shen 
Published: September 2023

AbstractRecent studies have determined that the nervous system can sense and respond to signals from skeletal tissue, a process known as skeletal interoception, which is crucial for maintaining bone homeostasis. The hypothalamus, located in the central nervous system (CNS), plays a key role in processing interoceptive signals and regulating bone homeostasis through the autonomic nervous system, neuropeptide release, and neuroendocrine mechanisms. These mechanisms control the differentiation of mesenchymal stem cells into osteoblasts (OBs), the activation of osteoclasts (OCs), and the functional activities of bone cells. Sensory nerves extensively innervate skeletal tissues, facilitating the transmission of interoceptive signals to the CNS. This review provides a comprehensive overview of current research on the generation and coordination of skeletal interoceptive signals by the CNS to maintain bone homeostasis and their potential role in pathological conditions. The findings expand our understanding of intersystem communication in bone biology and may have implications for developing novel therapeutic strategies for bone diseases.
Osimertinib induces paraptosis and TRIP13 confers resistance in glioblastoma cells
Authors: Hu Lulu , Shi Ji , Shen Dachuan , Zhai Xingyue , Liang Dapeng , Wang Jing , Xie Chunrui , Xia Zhiyu , Cui Jing , Liu Feng , Du Sha , Meng Songshu , Piao Haozhe 
Published: September 2023

AbstractThe efficacy of osimertinib, a third-generation epidermal growth factor receptor tyrosine kinase inhibitor, has been evaluated in glioblastoma (GBM) through preclinical and clinical trials. However, the underlying mechanism of osimertinib-induced GBM cell death and the underlying resistance mechanism to osimertinib remains unclear. Here, we demonstrate that Osimertinib induces paraptosis in GBM cells, as evidenced by the formation of cytoplasmic vacuoles, accumulation of ubiquitinated proteins, and upregulation of endoplasmic reticulum (ER) stress markers like CHOP. Additionally, neither apoptosis nor autophagy was involved in the osimertinib-induced cell death. RNAseq analysis revealed ER stress was the most significantly downregulated pathway upon exposure to osimertinib. Consistently, pharmacologically targeting the PERK-eIF2α axis impaired osimertinib-induced paraptosis. Notably, we show that the expression of thyroid receptor-interacting protein 13 (TRIP13), an AAA+ATPase, alleviated osimertinib-triggered paraptosis, thus conferring resistance. Intriguingly, MK-2206, an AKT inhibitor, downregulated TRIP13 levels and synergized with Osimertinib to suppress TRIP13-induced high GBM cell growth in vitro and in vivo. Together, our findings reveal a novel mechanism of action associated with the anti-GBM effects of osimertinib involving ER stress-regulated paraptosis. Furthermore, we identify a TRIP13-driven resistance mechanism against Osimertinib in GBM and offer a combination strategy using MK-2206 to overcome such resistance.
Identification of the bacteriophage nucleus protein interaction network
Authors: Enustun Eray , Deep Amar , Gu Yajie , Nguyen Katrina T. , Chaikeeratisak Vorrapon , Armbruster Emily , Ghassemian Majid , Villa Elizabeth , Pogliano Joe , Corbett Kevin D. 
Published: September 2023

AbstractIn the arms race between bacteria and bacteriophages (phages), some large-genome jumbo phages have evolved a protein shell that encloses their replicating genome to protect it against host immune factors. By segregating the genome from the host cytoplasm, however, the ‘phage nucleus’ introduces the need to specifically translocate messenger RNA and proteins through the nuclear shell and to dock capsids on the shell for genome packaging. Here, we use proximity labeling and localization mapping to systematically identify proteins associated with the major nuclear shell protein chimallin (ChmA) and other distinctive structures assembled by these phages. We identify six uncharacterized nuclear-shell-associated proteins, one of which directly interacts with self-assembled ChmA. The structure and protein–protein interaction network of this protein, which we term ChmB, suggest that it forms pores in the ChmA lattice that serve as docking sites for capsid genome packaging and may also participate in messenger RNA and/or protein translocation.
Creativity and productivity during the COVID-19 pandemic
Authors: Görlich Yvonne 
Published: September 2023

AbstractThis study explored impacts of the COVID-19 pandemic on creativity and productivity and how personality variables moderated these impacts. Two online self-report surveys were conducted. 863 (spring 2020) and 421 (spring 2021) participants were asked how the corona crisis affected their creativity and productivity. In addition, personality variables, namely the Big Five (openness, conscientiousness, extraversion, agreeableness, neuroticism), as well as interpersonal trust, need for cognition, risk-taking, and life satisfaction, were assessed. As a result of the crisis, the group of participants appeared more creative in 2020, while no significant group effect of the pandemic was found for productivity. In 2021, however, the crisis had a negative impact on creativity and productivity. In 2020, predictors for an improved creativity were openness, conscientiousness, neuroticism, and life satisfaction; predictors for improved productivity were conscientiousness, negative interpersonal trust, and life satisfaction. In 2021, only life satisfaction predicted improved creativity, while improved productivity was predicted by conscientiousness, negative neuroticism, and life satisfaction. At its beginning, the COVID-19 pandemic had, on average, a positive effect on creativity and a neutral one on productivity. Later, the impact turned negative on both creativity and productivity. Here, lower life satisfaction was particularly relevant.
Power system low delay resource scheduling model based on edge computing node
Authors: Zhao Ying , Ye Hua 
Published: September 2023

AbstractAs more and more intelligent devices are put into the field of power system, the number of connected nodes in the power network is increasing exponentially. Under the background of smart grid cooperation across power areas and voltage levels, how to effectively process the massive data generated by smart grid has become a difficult problem to ensure the stable operation of power system. In the complex calculation process of power system, the operation time of complex calculation can not be shortened to the greatest extent, and the execution efficiency can not be improved. Therefore, this paper proposes a two-phase heuristic algorithm based on edge computing. In solving the virtual machine sequence problem, for the main partition and the coordination partition, the critical path algorithm is used to sort the virtual machines to minimize the computing time. For other sub-partitions, the minimum cut algorithm is used to reduce the traffic interaction of each sub-partition. In the second stage of the virtual machine placement process, an improved best fit algorithm is used to avoid poor placement of virtual machines across physical machine configurations, resulting in increased computing time. Through the experiment on the test system, it is proved that the calculation efficiency is improved when the coordinated partition calculation belongs to the target partition. Because the edge computing is closer to the data source, it can save more data transmission time than cloud computing. This paper provides an effective algorithm for power system distributed computing in virtual machine configuration in edge computing, which can effectively reduce the computing time of power system and improve the efficiency of system resource utilization.
Inferring linear-B cell epitopes using 2-step metaheuristic variant-feature selection using genetic algorithm
Authors: Angaitkar Pratik , Aljrees Turki , Kumar Pandey Saroj , Kumar Ankit , Janghel Rekh Ram , Sahu Tirath Prasad , Singh Kamred Udham , Singh Teekam 
Published: September 2023

AbstractLinear-B cell epitopes (LBCE) play a vital role in vaccine design; thus, efficiently detecting them from protein sequences is of primary importance. These epitopes consist of amino acids arranged in continuous or discontinuous patterns. Vaccines employ attenuated viruses and purified antigens. LBCE stimulate humoral immunity in the body, where B and T cells target circulating infections. To predict LBCE, the underlying protein sequences undergo a process of feature extraction, feature selection, and classification. Various system models have been proposed for this purpose, but their classification accuracy is only moderate. In order to enhance the accuracy of LBCE classification, this paper presents a novel 2-step metaheuristic variant-feature selection method that combines a linear support vector classifier (LSVC) with a Modified Genetic Algorithm (MGA). The feature selection model employs mono-peptide, dipeptide, and tripeptide features, focusing on the most diverse ones. These selected features are fed into a machine learning (ML)-based parallel ensemble classifier. The ensemble classifier combines correctly classified instances from various classifiers, including k-Nearest Neighbor (kNN), random forest (RF), logistic regression (LR), and support vector machine (SVM). The ensemble classifier came up with an impressively high accuracy of 99.3% as a result of its work. This accuracy is superior to the most recent models that are considered to be state-of-the-art for linear B-cell classification. As a direct consequence of this, the entire system model can now be utilised effectively in real-time clinical settings.
RETRACTED ARTICLE: Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson’s disease
Authors: Lilhore Umesh Kumar , Dalal Surjeet , Faujdar Neetu , Margala Martin , Chakrabarti Prasun , Chakrabarti Tulika , Simaiya Sarita , Kumar Pawan , Thangaraju Pugazhenthan , Velmurugan Hemasri 
Published: September 2023

AbstractThe patients’ vocal Parkinson’s disease (PD) changes could be identified early on, allowing for management before physically incapacitating symptoms appear. In this work, static as well as dynamic speech characteristics that are relevant to PD identification are examined. Speech changes or communication issues are among the challenges that Parkinson’s individuals may encounter. As a result, avoiding the potential consequences of speech difficulties brought on by the condition depends on getting the appropriate diagnosis early. PD patients’ speech signals change significantly from those of healthy individuals. This research presents a hybrid model utilizing improved speech signals with dynamic feature breakdown using CNN and LSTM. The proposed hybrid model employs a new, pre-trained CNN with LSTM to recognize PD in linguistic features utilizing Mel-spectrograms derived from normalized voice signal and dynamic mode decomposition. The proposed Hybrid model works in various phases, which include Noise removal, extraction of Mel-spectrograms, feature extraction using pre-trained CNN model ResNet-50, and the final stage is applied for classification. An experimental analysis was performed using the PC-GITA disease dataset. The proposed hybrid model is compared with traditional NN and well-known machine learning-based CART and SVM & XGBoost models. The accuracy level achieved in Neural Network, CART, SVM, and XGBoost models is 72.69%, 84.21%, 73.51%, and 90.81%. The results show that under these four machine approaches of tenfold cross-validation and dataset splitting without samples overlapping one individual, the proposed hybrid model achieves an accuracy of 93.51%, significantly outperforming traditional ML models utilizing static features in detecting Parkinson’s disease.
Immuno-physiological effects of dietary reishi mushroom powder as a source of beta-glucan on Rohu, Labeo rohita challenged with Aeromonas veronii
Authors: Saha Tutul Kumar , Mariom  , Rahman Tanvir , Moniruzzaman Mohammad , Min Taesun , Hossain Zakir 
Published: September 2023

AbstractBeta-glucans have immense potential to stimulate immune modulation in fish by being injected intramuscularly, supplemented with feed or immersion routes of administration. We studied how supplementing Labeo rohita’s diet with reishi mushroom powder containing beta-glucan influenced immunological function. A supplemented diet containing 10% reishi mushroom powder was administered for 120 days. Afterwards, analyses were conducted on different immunological parameters such as antioxidants, respiratory burst, reactive oxygen species (ROS), alternative complement activity, and serum immunoglobulin, which resulted significant increases (p < 0.05; p < 0.01) for the reishi mushroom-fed immune primed L. rohita. Additionally, analyzing various hematological parameters such as erythrocytes and leukocytes count were assessed to elucidate the immunomodulatory effects, indicating positive effects of dietary reishi mushroom powder on overall fish health. Furthermore, the bacterial challenge-test with 1.92 × 104 CFU/ml intramuscular dose of Aeromonas veronii showed enhanced disease-defending system as total serum protein and lysozyme activity levels accelerated significantly (p < 0.01). Nevertheless, reishi mushroom powder contained with beta-glucan ameliorated the stress indicating parameters like acetylcholinesterase (AChE), serum-glutamic pyruvic transaminase (SGPT) and serum-glutamic oxaloacetic transaminase (SGOT) enzyme activities results suggested the fish’s physiology was unaffected. Therefore, the results indicated that adding dietary reishi mushroom as a source of beta-glucan could significantly boost the immune responses in Rohu.