bluuebunny/crossref_metadata_2025_split huggingface dataset:
Precipitation Microphysics in Tropical Cyclones: A Global Perspective Using the NASA Global Precipitation Measurement Mission Dual‐Frequency Precipitation Radar
Authors: Brauer Noah S. , Kirstetter Pierre E. , Basara Jeffrey B. , Hristova‐Veleva Svetla , Tanelli Simone , Joseph Turk F. 
Published: December 2023

AbstractPrecipitation microphysics in tropical cyclones (TCs) are often poorly represented in numerical simulations, which ultimately affects TC structure, evolution, and prediction. This provides a large incentive to better observe and understand the underlying microphysical processes in TCs in order to improve precipitation forecasts and warning operations. 112 TCs from 2014 to 2020 were matched up with overpasses from the NASA Global Precipitation Measurement (GPM) mission Dual‐Frequency Precipitation Radar (DPR) on a global scale to identify cloud properties and associated precipitation processes by quantifying vertical slopes of reflectivity in the liquid and ice phase. Further, vertical profiles of reflectivity were partitioned into different 850–200 hPa shear‐relative quadrants of each storm, different annuli from the storm center, and 5 TC ocean basins globally. Preliminary results showed the highest echo top heights occurred in the Northwest Pacific and Indian Ocean basins, with all basins and quadrants exhibiting median negative slopes of KuPR in the liquid phase. Additionally, all shear‐relative quadrants revealed negative slopes of reflectivity in the ice phase implying ice hydrometeor growth. These findings can potentially be used to improve the representation of cloud properties and the accuracy of the DPR particle size distribution algorithm in TCs.
A Variational LSTM Emulator of Sea Level Contribution From the Antarctic Ice Sheet
Authors: Van Katwyk Peter , Fox‐Kemper Baylor , Seroussi Hélène , Nowicki Sophie , Bergen Karianne J. 
Published: December 2023

AbstractThe Antarctic ice sheet (AIS) will be a dominant contributor to global mean sea level rise in the 21st century but remains a major source of uncertainty. The Ice Sheet Model Intercomparison for CMIP6 (ISMIP6) is an ensemble of continental‐scale models for studying the evolution of the AIS and projecting its future contribution to sea level. Due to their complexity and computational cost, ISMIP6 simulations are sparse and generated infrequently. Emulators are smaller‐scale models that approximate ISMs and enable experimentation and exploration into the drivers of sea level change. We introduce a neural network (NN) emulator to approximate the ISMIP6 ensemble, using a variational Long Short‐Term Memory (LSTM) with Monte Carlo dropout to quantify single‐projection uncertainty. The proposed NN emulator is compared to a Gaussian Process (GP) emulator on four criteria: accuracy of point estimates and predictive distributions of individual model projections, approximation of the ensemble projections, and model training time. The NN predicts more accurately on single projections, with a mean absolute error of 0.46 mm Sea Level Equivalent (SLE) versus 0.73 mm SLE for the GP, and has more accurate uncertainty estimates. The NN emulator also better approximates the ensemble distribution of ISMIP6 model projections, with a Kullback‐Leibler divergence of 18.26 versus 199.14 for GP at the projection year 2100. The NN enables more accurate experimentation with a reduced runtime, offering a new tool for understanding the important role of regional precipitation, ice sheet drainage systems, and interannual and longer timescale dynamics.
Study on the microcrystal cellulose and the derived 2D graphene and relative carbon materials
Authors: Long Si-Yu , Liu Jin-Lei , Zhou Ling-Qiang , Lv Wen-Da , Xian Xue-Quan , Tang Pei-Duo , Du Qi-Shi 
Published: December 2023

AbstractMicrocrystal cellulose (MCC) is a green and sustainable resource that widely exists in various lignocellulose species in percentage 10% to 30%. The fine powder of MCC is often discarded in industrial productions that use lignocellulose as feedstock. The crystal structure of two types of MCC (sugarcane pith and bamboo pith) and their derived carbon materials are studied, and the key findings are summarized as follows. (1) In the MCC refined from sugarcane pith, there are large amount of cellulose 2D crystal, which can be converted to valuable 2D graphene crystal. (2) In the MCC refined from bamboo pith there are large amount of cluster microcrystal cellulose, which can be converted to soft and elastic graphene microcrystal (GMC). (3) The 2D cellulose in MCC of sugarcane pith has large surface area and is easily to be degraded to sugars by acid–base hydrolysis reaction, which can be carbonized to Fullerenes-like carbon spheres. (4) The crystal structures of MCC derived carbon materials are strongly impacted by the crystal structures of MCC, and the carbonization reaction of MCC follows “in situ carbonization” and “nearby recombination” mechanism. In general, the results from this study may open a new way for value-added applications of microcrystal cellulose.
Copper pyrithione and zinc pyrithione induce cytotoxicity and neurotoxicity in neuronal/astrocytic co-cultured cells via oxidative stress
Authors: Oh Ha-Na , Kim Woo-Keun 
Published: December 2023

AbstractPrevious studies on copper pyrithione (CPT) and zinc pyrithione (ZPT) as antifouling agents have mainly focused on marine organisms. Even though CPT and ZPT pose a risk of human exposure, their neurotoxic effects remain to be elucidated. Therefore, in this study, the cytotoxicity and neurotoxicity of CPT and ZPT were evaluated after the exposure of human SH-SY5Y/astrocytic co-cultured cells to them. The results showed that, in a co-culture model, CPT and ZPT induced cytotoxicity in a dose-dependent manner (~ 400 nM). Exposure to CPT and ZPT suppressed all parameters in the neurite outgrowth assays, including neurite length. In particular, exposure led to neurotoxicity at concentrations with low or no cytotoxicity (~ 200 nM). It also downregulated the expression of genes involved in neurodevelopment and maturation and upregulated astrocyte markers. Moreover, CPT and ZPT induced mitochondrial dysfunction and promoted the generation of reactive oxygen species. Notably, N-acetylcysteine treatment showed neuroprotective effects against CPT- and ZPT-mediated toxicity. We concluded that oxidative stress was the major mechanism underlying CPT- and ZPT-induced toxicity in the co-cultured cells.
Microfluidic devices for precise measurements of cell directionality reveal a role for glutamine during cell migration
Authors: Gural Nil , Irimia Daniel 
Published: December 2023

AbstractCancer cells that migrate from tumors into surrounding tissues are responsible for cancer dissemination through the body. Microfluidic devices have been instrumental in discovering unexpected features of cancer cell migration, including the migration in self-generated gradients and the contributions of cell–cell contact during collective migration. Here, we design microfluidic channels with five successive bifurcations to characterize the directionality of cancer cell migration with high precision. We uncover an unexpected role for glutamine in epithelial cancer cell orientation, which could be replaced by alfa-keto glutarate but not glucose.
Transformer fault diagnosis method based on TLR-ADASYN balanced dataset
Authors: Guan Shan , Yang Haiqi , Wu Tongyu 
Published: December 2023

AbstractAs the cornerstone of transmission and distribution equipment, power transformer plays a very important role in ensuring the safe operation of power system. At present, the technology of dissolved gas analysis (DGA) has been widely used in fault diagnosis of oil-immersed transformer. However, in the actual scene, the limited number of transformer fault samples and the uneven distribution of different fault types often lead to low overall fault detection accuracy or a few types of fault misjudgment. Therefore, a transformer fault diagnosis method based on TLR-ADASYN balanced data set is presented. This method effectively addresses the issue of samples imbalance, reducing the impact on misjudgment caused by a few samples. It delves deeply into the correlation between the ratio of dissolved gas content in oil and fault type, eliminating redundant informations and reducing characteristic dimensions. The diagnostic model SO-RF (Snake Optimization-Random Forest) is established, achieving a diagnostic accuracy rate of 97.06%. This enables online diagnosis of transformers. Comparative analyses using different sampling methods, various features, and diverse diagnostic models were conducted to validate the effectiveness of the proposed method. In conclusion, validation was conducted using a public dataset, and the results demonstrate that the proposed method in this paper exhibits strong generalization capabilities.
White shark optimizer with optimal deep learning based effective unmanned aerial vehicles communication and scene classification
Authors: Nadana Ravishankar T. , Ramprasath M. , Daniel A. , Selvarajan Shitharth , Subbiah Priyanga , Balusamy Balamurugan 
Published: December 2023

AbstractUnmanned aerial vehicles (UAVs) become a promising enabler for the next generation of wireless networks with the tremendous growth in electronics and communications. The application of UAV communications comprises messages relying on coverage extension for transmission networks after disasters, Internet of Things (IoT) devices, and dispatching distress messages from the device positioned within the coverage hole to the emergency centre. But there are some problems in enhancing UAV clustering and scene classification using deep learning approaches for enhancing performance. This article presents a new White Shark Optimizer with Optimal Deep Learning based Effective Unmanned Aerial Vehicles Communication and Scene Classification (WSOODL-UAVCSC) technique. UAV clustering and scene categorization present many deep learning challenges in disaster management: scene understanding complexity, data variability and abundance, visual data feature extraction, nonlinear and high-dimensional data, adaptability and generalization, real-time decision making, UAV clustering optimization, sparse and incomplete data. the need to handle complex, high-dimensional data, adapt to changing environments, and make quick, correct decisions in critical situations drives deep learning in UAV clustering and scene categorization. The purpose of the WSOODL-UAVCSC technique is to cluster the UAVs for effective communication and scene classification. The WSO algorithm is utilized for the optimization of the UAV clustering process and enables to accomplish effective communication and interaction in the network. With dynamic adjustment of the clustering, the WSO algorithm improves the performance and robustness of the UAV system. For the scene classification process, the WSOODL-UAVCSC technique involves capsule network (CapsNet) feature extraction, marine predators algorithm (MPA) based hyperparameter tuning, and echo state network (ESN) classification. A wide-ranging simulation analysis was conducted to validate the enriched performance of the WSOODL-UAVCSC approach. Extensive result analysis pointed out the enhanced performance of the WSOODL-UAVCSC method over other existing techniques. The WSOODL-UAVCSC method achieved an accuracy of 99.12%, precision of 97.45%, recall of 98.90%, and F1-score of 98.10% when compared to other existing techniques.
A rapid and reference-free imputation method for low-cost genotyping platforms
Authors: Chi Duong Vinh , Minh Vu Giang , Khac Nguyen Thien , Tran The Nguyen Hung , Luong Pham Thang , S. Vo Nam , Hong Hoang Tham 
Published: December 2023

AbstractMost current genotype imputation methods are reference-based, which posed several challenges to users, such as high computational costs and reference panel inaccessibility. Thus, deep learning models are expected to create reference-free imputation methods performing with higher accuracy and shortening the running time. We proposed a imputation method using recurrent neural networks integrating with an additional discriminator network, namely GRUD. This method was applied to datasets from genotyping chips and Low-Pass Whole Genome Sequencing (LP-WGS) with the reference panels from The 1000 Genomes Project (1KGP) phase 3, the dataset of 4810 Singaporeans (SG10K), and The 1000 Vietnamese Genome Project (VN1K). Our model performed more accurately than other existing methods on multiple datasets, especially with common variants with large minor allele frequency, and shrank running time and memory usage. In summary, these results indicated that GRUD can be implemented in genomic analyses to improve the accuracy and running-time of genotype imputation.
Whole-genome sequencing provides novel insights into the evolutionary history and genetic adaptation of reindeer populations in northern Eurasia
Authors: Pokharel Kisun , Weldenegodguad Melak , Dudeck Stephan , Honkatukia Mervi , Lindeberg Heli , Mazzullo Nuccio , Paasivaara Antti , Peippo Jaana , Soppela Päivi , Stammler Florian , Kantanen Juha 
Published: December 2023

AbstractDomestic reindeer (Rangifer tarandus) play a vital role in the culture and livelihoods of indigenous people across northern Eurasia. These animals are well adapted to harsh environmental conditions, such as extreme cold, limited feed availability and long migration distances. Therefore, understanding the genomics of reindeer is crucial for improving their management, conservation and utilisation. In this study, we have generated a new genome assembly for the Fennoscandian domestic reindeer with high contiguity, making it the most complete reference genome for reindeer to date. The new genome assembly was utilised to explore genetic diversity, population structure and selective sweeps in Eurasian Rangifer tarandus populations which was based on the largest population genomic dataset for reindeer, encompassing 58 individuals from diverse populations. Phylogenetic analyses revealed distinct genetic clusters, with the Finnish wild forest reindeer (Rangifer tarandus fennicus) standing out as a unique subspecies. Divergence time estimates suggested a separation of ~ 52 thousand years ago (Kya) between the northern European Rangifer tarandus fennicus and Rangifer tarandus tarandus. Our study identified four main genetic clusters: Fennoscandian, the eastern/northern Russian and Alaskan group, the Finnish forest reindeer, and the Svalbard reindeer. Furthermore, two independent reindeer domestication processes were inferred, suggesting separate origins for the domestic Fennoscandian and eastern/northern Russian reindeer. Notably, shared genes under selection, including retroviral genes, point towards molecular domestication processes that aided adaptation of this species to diverse environments.
Acute smartphone use impairs vigilance and inhibition capacities
Authors: Jacquet Thomas , Lepers Romuald , Pageaux Benjamin , Poulin-Charronnat Bénédicte 
Published: December 2023

AbstractSmartphones are now in very widespread use, and concerns have arisen about potential detrimental effects, even with acute use. These adverse consequences are often linked to the emergence of mental fatigue. While the cognitive implications of fatigue are well-documented, knowledge about the specific influence of acute smartphone use on cognitive performance remains scarce. The aim of this study was therefore to investigate the impact of acute smartphone use on cognitive performance. It included two experiments: one designed to assess the impact of smartphone use on vigilance, and the other focusing on evaluating inhibition capacities. In Experiment 1, two groups of 40 participants completed a Psychomotor Vigilance Task (PVT) before and after using a smartphone for 45 min (experimental group), or before and after watching a documentary (control group). In Experiment 2, two groups of 40 participants were subjected to a similar experimental design but had to perform a Go/NoGo task instead of a PVT. Mental fatigue and drowsiness were evaluated with visual analog scales before and after smartphone use and watching a documentary. Results suggested that both watching a documentary and using a smartphone for 45 min increased subjective mental fatigue and drowsiness. Watching the documentary did not impair cognitive performance. Reaction times on the PVT and number of errors on NoGo trials in the Go/NoGo task were higher among the participants in the smartphone condition. These results indicate reduced vigilance and impaired inhibition capacities only after smartphone use. We conclude that acute smartphone use induces mental fatigue and decreases cognitive performance. Further research is needed to understand the mechanisms underlying this decline in cognitive performance.
Identification of CD38, CD97, and CD278 on the HIV surface using a novel flow virometry screening assay
Authors: Burnie Jonathan , Fernandes Claire , Chaphekar Deepa , Wei Danlan , Ahmed Shubeen , Persaud Arvin Tejnarine , Khader Nawrah , Cicala Claudia , Arthos James , Tang Vera A. , Guzzo Christina 
Published: December 2023

AbstractWhile numerous cellular proteins in the HIV envelope are known to alter virus infection, methodology to rapidly phenotype the virion surface in a high throughput, single virion manner is lacking. Thus, many human proteins may exist on the virion surface that remain undescribed. Herein, we developed a novel flow virometry screening assay to discover new proteins on the surface of HIV particles. By screening a CD4+ T cell line and its progeny virions, along with four HIV isolates produced in primary cells, we discovered 59 new candidate proteins in the HIV envelope that were consistently detected across diverse HIV isolates. Among these discoveries, CD38, CD97, and CD278 were consistently present at high levels on virions when using orthogonal techniques to corroborate flow virometry results. This study yields new discoveries about virus biology and demonstrates the utility and feasibility of a novel flow virometry assay to phenotype individual virions.
Trajectory modeling of cannabis use over 30 years identifies five unique longitudinal patterns
Authors: Mahar Amy R. , Bancks Michael P. , Sidney Stephen , Reis Jared , Kinney Gregory L. 
Published: December 2023

AbstractCannabis is the most prevalently used psychoactive substance in the United States. Cannabis has conflicting federal and state legal status in the US, however medical and recreational cannabis use are increasing. When assessing health outcomes, cannabis use classification has been modeled largely as current use status (never/former/current) or cumulative use (joint-years). These methods do not describe longitudinal patterns of use which may have unique relationships with health outcomes. We used cannabis use data spanning 30 years from the Coronary Artery Risk Development in Young Adults Cohort (CARDIA) to create trajectories of current cannabis use during young and middle adulthood. We identified 5 unique patterns of the probability of cannabis use during young and middle adulthood in the CARDIA Cohort. To support the cannabis probability trajectories, we qualitatively examined cumulative cannabis use as joint-years for each trajectory group. Trajectory group 5 had high probability of consistent cannabis use (0.8–0.9% probability of use) and had the highest number of joint-years (0.6 +/− 0.4). Trajectory group 1 who had a lower probability of cannabis use (0.05–0% probability of use) with the lowest number of joint-years (0.1 +/− 0.1).
Excess mortality in adults from Sao Paulo during the COVID-19 pandemic in 2020: analyses of all-cause and noncommunicable diseases mortality
Authors: Resende Bruna de Souza , Dias Rayara Mozer , Ferrari Gerson , Rezende Leandro F. M. 
Published: December 2023

AbstractIn this study, we estimated the excess mortality from all-causes of death and noncommunicable diseases (NCDs) in adults living in the state of São Paulo during the COVID-19 pandemic in 2020. Number of deaths were retrieved from the Mortality Information System before (2017–2019) and during (2020) the COVID-19 pandemic, considering the following underlying causes of death: Neoplasms; Diabetes Mellitus; Circulatory System Diseases, and Respiratory System Diseases. Standardized Mortality Ratio (SMR) were calculated by dividing the mortality rates in 2020 by average mortality rates in 2017–2019, according to sex, age group, geographic location (state, capital, and Regional Health Departments). In 2020, occurred 341,704 deaths in the state of São Paulo vs 290,679 deaths in 2017–2019, representing an 18% increase in all-cause mortality (SMR 1.18) or 51,025 excess deaths during the first year of COVID-19 pandemic. The excess mortality was higher in men (186,741 deaths in 2020 vs 156,371 deaths in 2017–2019; SMR 1.18; 30,370 excess deaths) compared to women (154,963 deaths in 2020 vs 134,308 deaths in 2017–2019; SMR 1.15; 20,655 excess deaths). Regarding NCDs mortality, we observed a reduction in cancer mortality (SMR 0.98; −1,354 deaths), diseases of the circulatory system (SMR 0.95; −4,277 deaths), and respiratory system (SMR 0.88; −1,945). We found a 26% increase in Diabetes Mellitus mortality (SMR 1.26; 2885 deaths) during the pandemic year. Our findings corroborate the need to create and strengthen policies aimed at the prevention and control of NCDs, in order to mitigate the impact of future infectious disease pandemics.
Material aspects of sintering of EAC-1A lunar regolith simulant
Authors: Ginés-Palomares Juan-Carlos , Fateri Miranda , Schubert Tim , de Peindray d’Ambelle Lilou , Simon Sebastian , Gluth Gregor J. G. , Günster Jens , Zocca Andrea 
Published: December 2023

AbstractFuture lunar exploration will be based on in-situ resource utilization (ISRU) techniques. The most abundant raw material on the Moon is lunar regolith, which, however, is very scarce on Earth, making the study of simulants a necessity. The objective of this study is to characterize and investigate the sintering behavior of EAC-1A lunar regolith simulant. The characterization of the simulant included the determination of the phase assemblage, characteristic temperatures determination and water content analysis. The results are discussed in the context of sintering experiments of EAC-1A simulant, which showed that the material can be sintered to a relative density close to 90%, but only within a very narrow range of temperatures (20–30 °C). Sintering experiments were performed for sieved and unsieved, as well as for dried and non-dried specimens of EAC-1A. In addition, an analysis of the densification and mechanical properties of the sintered specimens was done. The sintering experiments at different temperatures showed that the finest fraction of sieved simulant can reach a higher maximum sintering temperature, and consequently a higher densification and biaxial strength. The non-dried powder exhibited higher densification and biaxial strength after sintering compared to the dried specimen. This difference was explained with a higher green density of the non-dried powder during pressing, rather than due to an actual influence on the sintering mechanism. Nevertheless, drying the powder prior to sintering is important to avoid the overestimation of the strength of specimens to be fabricated on the Moon.