bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anthropogenic Weakening of the Atmospheric Circulation During the Satellite Era
Authors: Shrestha Sisam , Soden Brian J. 
Published: November 2023

AbstractClimate models predict a slowing of the atmospheric overturning circulation with warming. In models, this slowing manifests primarily as a weakening of the Walker Circulation (WC). However, observational studies indicate a strengthened Pacific WC over the past several decades, raising questions about the models' ability to represent critical energetic and hydrologic constraints responsible for the predicted weakening. This discrepancy is closely tied to differences in the warming pattern over the Pacific during this period. We show that model simulations with either observed or model‐projected warming patterns predict a robust weakening of atmospheric overturning circulation, despite having opposing changes in the Pacific WC strength. This weakening occurs in the zonally asymmetric circulation, rather than in the zonal‐mean Hadley cell. Weakening inferred from satellite observations is reproduced in coupled models only when anthropogenic forcing is included, suggesting that a human‐induced weakening of the global atmospheric circulation is already detectable in observations.
Arctic Warming and Eurasian Cooling: Weakening and Reemergence
Authors: Xu Xinping , He Shengping , Zhou Botao , Wang Huijun , Sun Bo 
Published: November 2023

AbstractThe observed Eurasian winter surface cooling from the 1990s to the early 2010s, which is contrary to global warming, has been extensively studied. Previous studies revealed that the surface cooling trend has significantly weakened in the past decade. Based on large‐ensemble simulations, this study reveals that the weakening of Eurasian surface cooling is primarily driven by the atmospheric internal variability, which coincides with the weakening of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. Negative Arctic Oscillation (−AO) and Ural blocking (UB) in combination dominate the intensity of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. In the future, there is a possibility that the severe Eurasian cooling trend with comparable magnitude to that during 1990–2013 may reemerge accompanied with Arctic mid‐tropospheric warming, in response to the decadal strengthening of −AO and UB. This may occur before the 2050s, when the atmospheric internal variability is able to overwhelm the effects of greenhouse gases.
Electron Heating Associated With Magnetic Reconnection in Foreshock Waves: Particle‐In‐Cell Simulation Analysis
Authors: Wang Shan , Yang Yan 
Published: November 2023

AbstractMagnetic reconnection occurs in turbulent plasmas like shock transition regions, while its role in energy dissipation therein is not yet clear. We perform a 2D particle‐in‐cell simulation of foreshock waves and study electron heating associated with reconnection. The probability distribution of Te exhibits a shift to higher values near reconnection X‐lines compared to elsewhere. By examining the Te evolution using the superposed epoch analysis, we find that Te is higher in reconnection than in non‐reconnecting current sheets, and Te increases over the ion cyclotron time scale. The heating rate of Te is 10%–40% miVA2, where VA is the average ion Alfvén speed in reconnection regions, which demonstrates the importance of reconnection in heating electrons. We further investigate the bulk electron energization mechanisms by decomposing je · E under guiding center approximations. Around the reconnection onset, E|| dominates the total energization partly contributed by electron holes, and the perpendicular energization is dominated by the magnetization term associated with the gyro‐motion in inhomogeneous fields. The Fermi mechanism contributes negative energization at early time mainly due to Hall effects, and later the outflow in the reconnection plane contributes more dominant positive values. After a couple of ion cyclotron periods from reconnection onset, the Fermi mechanism dominates the energization. A critical factor for initiating reconnection is to drive current sheets to the de‐scale thickness. The reconnection structures can be complicated due to flows originated from the ion‐scale waves, and interactions between multiple reconnection sites. Visualizing such complicated features in simulations may assist future analysis of observation data.
Investigation of Added Value in Regional Climate Models for East Asian Storm Track Analysis
Authors: Byun Ui‐Yong , Chang Eun‐Chul , Kim Joowan , Ahn Joong‐Bae , Cha Dong‐Hyun , Min Seung‐Ki , Byun Young‐Hwa 
Published: November 2023

AbstractStudies have shown that regional climate models (RCMs) can simulate local climates at a higher resolution for specific regions compared to global climate models (GCMs), making dynamic downscaling using RCMs a more effective approach. Therefore, RCMs have become valuable tools for evaluating the potential impacts of climate change on specific regions and for informing local adaptation strategies. To fully understand the added value (AV) of RCMs, it is essential to understand how the characteristics differ between land and ocean. The complex topography of East Asia, including land and sea, makes it a suitable region for evaluating the AV of RCMs. In this study, we compared two regional simulations that integrated the same RCMs but employed different GCMs from the Coordinated Regional Climate Downscaling Experiment for their ability to simulate storm tracks in East Asia. The results of the RCMs for the period from 1982 to 2005 were compared with their host Coupled Model Intercomparison Project GCM projections and high‐resolution reanalysis. In mountainous regions, the AV of the RCMs weakened the bias of the GCM and improved its agreement with the reanalysis due to the dynamical process near the high‐resolution topography. In plains and coastal areas, owing to the increase in horizontal resolution and clearly determined coastline in RCMs, small‐scale phenomena are well represented, and the storm track of RCMs shows similar values to that of the GCM in maritime regions. This study demonstrates the value of RCMs for improving the accuracy of climate projections in East Asia, informing adaptation strategies, and enhancing climate research.
Experimental mining plumes and ocean warming trigger stress in a deep pelagic jellyfish
Authors: Stenvers Vanessa I. , Hauss Helena , Bayer Till , Havermans Charlotte , Hentschel Ute , Schmittmann Lara , Sweetman Andrew K. , Hoving Henk-Jan T. 
Published: November 2023

AbstractThe deep pelagic ocean is increasingly subjected to human-induced environmental change. While pelagic animals provide important ecosystem functions including climate regulation, species-specific responses to stressors remain poorly documented. Here, we investigate the effects of simulated ocean warming and sediment plumes on the cosmopolitan deep-sea jellyfish Periphylla periphylla, combining insights gained from physiology, gene expression and changes in associated microbiota. Metabolic demand was elevated following a 4 °C rise in temperature, promoting genes related to innate immunity but suppressing aerobic respiration. Suspended sediment plumes provoked the most acute and energetically costly response through the production of excess mucus (at ≥17 mg L−1), while inducing genes related to aerobic respiration and wound repair (at ≥167 mg L−1). Microbial symbionts appeared to be unaffected by both stressors, with mucus production maintaining microbial community composition. If these responses are representative for other gelatinous fauna, an abundant component of pelagic ecosystems, the effects of planned exploitation of seafloor resources may impair deep pelagic biodiversity and ecosystem functioning.
SETD2 deficiency accelerates sphingomyelin accumulation and promotes the development of renal cancer
Authors: Rao Hanyu , Liu Changwei , Wang Aiting , Ma Chunxiao , Xu Yue , Ye Tianbao , Su Wenqiong , Zhou Peijun , Gao Wei-Qiang , Li Li , Ding Xianting 
Published: November 2023

AbstractPatients with polycystic kidney disease (PKD) encounter a high risk of clear cell renal cell carcinoma (ccRCC), a malignant tumor with dysregulated lipid metabolism. SET domain–containing 2 (SETD2) has been identified as an important tumor suppressor and an immunosuppressor in ccRCC. However, the role of SETD2 in ccRCC generation in PKD remains largely unexplored. Herein, we perform metabolomics, lipidomics, transcriptomics and proteomics within SETD2 loss induced PKD-ccRCC transition mouse model. Our analyses show that SETD2 loss causes extensive metabolic reprogramming events that eventually results in enhanced sphingomyelin biosynthesis and tumorigenesis. Clinical ccRCC patient specimens further confirm the abnormal metabolic reprogramming and sphingomyelin accumulation. Tumor symptom caused by Setd2 knockout is relieved by myriocin, a selective inhibitor of serine-palmitoyl-transferase and sphingomyelin biosynthesis. Our results reveal that SETD2 deficiency promotes large-scale metabolic reprogramming and sphingomyelin biosynthesis during PKD-ccRCC transition. This study introduces high-quality multi-omics resources and uncovers a regulatory mechanism of SETD2 on lipid metabolism during tumorigenesis.
Surrounding greenness is associated with lower risk and burden of low birth weight in Iran
Authors: Luo Siqi , Wang Yaqi , Mayvaneh Fatemeh , Relvas Helder , Baaghideh Mohammad , Wang Kai , Yuan Yang , Yin Zhouxin , Zhang Yunquan 
Published: November 2023

AbstractThe nexus between prenatal greenspace exposure and low birth weight (LBW) remains largely unstudied in low- and middle-income countries (LMICs). We investigated a nationwide retrospective cohort of 4,021,741 live births (263,728 LBW births) across 31 provinces in Iran during 2013–2018. Greenness exposure during pregnancy was assessed using satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). We estimated greenness-LBW associations using multiple logistic models, and quantified avoidable LBW cases under scenarios of improved greenspace through counterfactual analyses. Association analyses provide consistent evidence for approximately L-shaped exposure-response functions, linking 7.0–11.5% declines in the odds of LBW to each 0.1-unit rise in NDVI/EVI with multiple buffers. Assuming causality, 3931–5099 LBW births can be avoided by achieving greenness targets of mean NDVI/EVI, amounting to 4.4–5.6% of total LBW births in 2015. Our findings suggest potential health benefits of improved greenspace in lowering LBW risk and burden in LMICs.
Pertuzumab plus high-dose trastuzumab for HER2-positive breast cancer with brain metastases: PATRICIA final efficacy data
Authors: Lin Nancy U. , Kumthekar Priya , Sahebjam Solmaz , Ibrahim Nuhad , Fung Anita , Cheng Anna , Nicholas Alan , Sussell Jesse , Pegram Mark 
Published: November 2023

AbstractThe PATRICIA study (NCT02536339) examined the efficacy and safety of pertuzumab plus high-dose trastuzumab in patients with HER2-positive metastatic breast cancer (MBC) with progressive central nervous system (CNS) metastases following radiotherapy. Primary analysis confirmed CNS objective response rate (ORR) was 11% (95% confidence interval [CI]: 3–25); clinical benefit rate (CBR) was 68% (4 months) and 51% (6 months). We report final efficacy data after a further 21-months of follow-up, updated safety, survival, and patient-reported outcomes (PROs). Patients received standard-dose pertuzumab plus high-dose trastuzumab (6 mg/kg weekly) until CNS or systemic disease progression or unacceptable toxicity. Primary endpoint: confirmed ORR (CNS) per Response Assessment in Neuro-Oncology Brain Metastases criteria. Secondary endpoints were response duration, CBR, progression-free survival (PFS), overall survival (OS), safety, and PROs. By clinical cut-off, 39 patients had completed or discontinued treatment. Confirmed ORR (CNS) was 11% (95% CI: 3.0–25.4). Median CNS-PFS was 4.6 months (95% CI: 4.0–8.9), as was median CNS-PFS or systemic PFS (95% CI: 4.0–8.9); median OS was 27.2 months (95% CI: 16.1–not reached). CBR in the CNS was 51% (19 patients, 95% CI: 34.4–68.1) at 6 months. Two patients remained on treatment until study closure, achieving stable disease for 4.1 and 4.8 years. Treatment-related grade 3/4 adverse events occurred in 7.7% of patients. Patients with confirmed partial response or stable disease (≥4 months) in the CNS had stable PROs over time. Pertuzumab plus high-dose trastuzumab represents a reasonable non-chemotherapeutic treatment option for selected patients with HER2-positive MBC with CNS metastases.
Predicting water quality through daily concentration of dissolved oxygen using improved artificial intelligence
Authors: Yang Jiahao 
Published: November 2023

AbstractAs an important hydrological parameter, dissolved oxygen (DO) concentration is a well-accepted indicator of water quality. This study deals with introducing and evaluating four novel integrative methods for the prediction of DO. To this end, teaching–learning-based optimization (TLBO), sine cosine algorithm, water cycle algorithm (WCA), and electromagnetic field optimization (EFO) are appointed to train a commonly-used predictive system, namely multi-layer perceptron neural network (MLPNN). The records of a USGS station called Klamath River (Klamath County, Oregon) are used. First, the networks are fed by the data between October 01, 2014, and September 30, 2018. Later, their competency is assessed using the data belonging to the subsequent year (i.e., from October 01, 2018 to September 30, 2019). The reliability of all four models, as well as the superiority of the WCA-MLPNN, was revealed by mean absolute errors (MAEs of 0.9800, 1.1113, 0.9624, and 0.9783) in the training phase. The calculated Pearson correlation coefficients (RPs of 0.8785, 0.8587, 0.8762, and 0.8815) plus root mean square errors (RMSEs of 1.2980, 1.4493, 1.3096, and 1.2903) showed that the EFO-MLPNN and TLBO-MLPNN perform slightly better than WCA-MLPNN in the testing phase. Besides, analyzing the complexity and the optimization time pointed out the EFO-MLPNN as the most efficient tool for predicting the DO. In the end, a comparison with relevant previous literature indicated that the suggested models of this study provide accuracy improvement in machine learning-based DO modeling.
Speech emotion analysis using convolutional neural network (CNN) and gamma classifier-based error correcting output codes (ECOC)
Authors: Zhao Yunhao , Shu Xiaoqing 
Published: November 2023

AbstractSpeech emotion analysis is one of the most basic requirements for the evolution of Artificial Intelligence (AI) in the field of human–machine interaction. Accurate emotion recognition in speech can be effective in applications such as online support, lie detection systems and customer feedback analysis. However, the existing techniques for this field have not yet met sufficient development. This paper presents a new method to improve the performance of emotion analysis in speech. The proposed method includes the following steps: pre-processing, feature description, feature extraction, and classification. The initial description of speech features in the proposed method is done by using the combination of spectro-temporal modulation (STM) and entropy features. Also, a Convolutional Neural Network (CNN) is utilized to reduce the dimensions of these features and extract the features of each signal. Finally, the combination of gamma classifier (GC) and Error-Correcting Output Codes (ECOC) is applied to classify features and extract emotions in speech. The performance of the proposed method has been evaluated using two datasets, Berlin and ShEMO. The results show that the proposed method can recognize speech emotions in the Berlin and ShEMO datasets with an average accuracy of 93.33 and 85.73%, respectively, which is at least 6.67% better than compared methods.
Moderate intensity walking exercises reduce the body mass index and vascular inflammatory factors in postmenopausal women with obesity: a randomized controlled trial
Authors: Son Woo-Hyeon , Park Hyun-Tae , Jeon Byeong Hwan , Ha Min-Seong 
Published: November 2023

AbstractPostmenopause, the secretion of female hormones changes, causing excessive fat accumulation in the body and leading to chronic inflammation, which increases the incidence of cardiovascular diseases (CVD). Walking is an easily accessible daily exercise and effective non-pharmacological treatment for reducing obesity and the incidence of CVD. The aim of this study was to investigate the effect of moderate intensity walking exercises on body composition, vascular inflammatory factors, and vascular endothelial growth factor (VEGF) in postmenopausal women with obesity. Twenty-six older postmenopausal women with obesity (ages 68–72) were randomly assigned to control (n = 12, BMI 26.06 ± 1.37) or exercise (n = 14, BMI 26.04 ± 1.94) groups. Following a 12-week moderate intensity walking exercise program, we measured the participants’ body composition with an InBody S10 analyzer and assessed blood sera using enzyme-linked immunosorbent assays. There was a significant clustering by weight (p < 0.01), body mass index (p < 0.01), percentage body fat (p < 0.001), high-sensitivity C-reactive protein (p < 0.05), interleukin-6, and tumor necrosis factor-α (p < 0.05) being significantly decreased in the exercise group. Although VEGF levels did not change significantly, a tendency to increase was observed in participants that exercised. Our results indicate that walking exercise may help prevent CVD in postmenopausal women with obesity by reducing obesity and vascular inflammatory factors.
Additive manufacturing of poly (lactic acid)/hydroxyapatite/carbon nanotubes biocomposites for fibroblast cell proliferation
Authors: da Luz Belo Francilene , Vasconcelos Esleane Vilela , Pinheiro Miriane Alexandrino , da Cruz Barbosa Nascimento Damares , Passos Marcele Fonseca , da Silva Alisson Clay Rios , dos Reis Marcos Allan Leite , Monteiro Sérgio Neves , Brígida Rebecca Thereza Silva Santa , Rodrigues Ana Paula Drummond , Candido Verônica Scarpini 
Published: November 2023

AbstractBone tissue is one of the most important in the human body. In this study, scaffolds of poly (lactic acid) PLA reinforced with hydroxyapatite (HA) and carbon nanotubes (CNT) were manufactured, evaluating their mechanical and biological properties. HA was synthesized by wet method and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The scaffolds were produced using additive manufacturing and characterized by optical microscopy, SEM, thermogravimetric analysis (TGA), Raman spectroscopy and biological tests. The SEM results showed that the PLA surface was affected by the incorporation of CNT. TG showed that the incorporation of HA into the polymer matrix compromised the thermal stability of PLA. On the other hand, the incorporation of CNT to the polymer and the impregnation with HA on the surface by thermal effect increased the stability of PLA/CNT scaffolds. Raman spectra indicated that HA impregnation on the surface did not modify the polymer or the ceramic. In the compression tests, PLA and PLA/CNT scaffolds displayed the best compressive strength. In the biological tests, more than 85% of the cells remained viable after 48 h of incubation with all tested scaffolds and groups with CNT in the composition disclosing the best results.
Evaluating automatic sentence alignment approaches on English-Slovak sentences
Authors: Forgac Frantisek , Munkova Dasa , Munk Michal , Kelebercova Livia 
Published: November 2023

AbstractParallel texts represent a very valuable resource in many applications of natural language processing. The fundamental step in creating parallel corpus is the alignment. Sentence alignment is the issue of finding correspondence between source sentences and their equivalent translations in the target text. A number of automatic sentence alignment approaches were proposed including neural networks, which can be divided into length-based, lexicon-based, and translation-based. In our study, we used five different aligners, namely Bilingual sentence aligner (BSA), Hunalign, Bleualign, Vecalign, and Bertalign. We evaluated both, the performance of the Bertalign in terms of accuracy against the up to now employed aligners as well as among each other in the language pair English-Sovak. We created our custom corpus consisting of texts collected in 2021 and 2022. Vecalign and Bertalign performed statistically significantly best and BSA the worst. Hunalign and Bleualign achieved the same performance in terms of F1 score. However, Bleualign achieved the most diverse results in terms of performance.
The combination of Ephedrae herba and coixol from Coicis semen attenuate adiposity via glucocorticoid receptor regulation
Authors: Yu Ga-Ram , Kim Jai-Eun , Lim Dong-Woo , Park Won-Hwan 
Published: November 2023

AbstractThe enhanced therapeutic effects and mechanisms of certain herbal combination in various herbal prescriptions are mostly unclear. A combination of two herbs, namely Ephedrae herba (EH) and Coicis semen (CS), has been commonly prescribed for obesity. In our previous work, the combination of EH and CS was studied using network pharmacological approach to predict its pharmacological targets and in vitro experiments to evaluate its efficacy on obesity. Although we demonstrated enhanced anti-adiposity effects of the combination on matured adipocytes, the molecular mechanisms and contributing compounds underlying the effects of EH-CS combination on adiposity or adipogenesis were not fully elucidated. The current study adopted integrated bioinformatics analysis to precisely validate potential targets of EH-CS by screening differentially expressed genes (DEGs) of morbid obesity patients from NCBI gene expression omnibus (GEO). Based on the functional cluster analysis of down-regulated DEGs, the anti-adipogenesis mechanism of EH-CS combination was speculated with KEGG enrichment analysis. Furthermore, we investigated the combinational effects of EH and coixol, or stigmasterol, the two compounds in CS which were expected to have main beneficial effects in metabolic diseases. Moreover, distinct effect of the combination on transcriptional activity of glucocorticoid receptor (GR) was investigated using electrophoretic mobility shift assay (EMSA). The EH-CS combination was predicted to modulate down-regulated genes which are involved in KEGG pathways crucial to metabolic disease in morbidly obese individuals. The combination of EH with CS compounds significantly increased the phosphorylation of acetyl-coA carboxylase (ACC), AMP-activated protein kinase (AMPK), and protein kinase B (AKT) in 3T3-L1 cells and decreased intracellular lipid accumulation. The two CS compounds significantly increased the anti-adipogenesis/lipogenesis effects of EH by inhibiting the gene expression levels. Finally, the combination of EH and coixol inhibited dexamethasone-induced GR translocation to the nucleus and transcriptional binding activity in adipocytes. The combination of EH and CS could be considered a therapeutic strategy for treating metabolic diseases, including obesity.