bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the lubrication performance of circular tilting pad thrust bearings for large wind turbines
Authors: Wang Jianlei , Cao Yang , Sun Wenye , Chen Runlin , Jia Qian , Cui Yahui 
Published: February 2024

AbstractIn view of the large temperature rise and impact load of thrust bearings in the main shaft system of large wind turbines, this article takes the circular tilting pad thrust bearings in large wind turbines as the research object, and analyses the basic theory of bearing lubrication. The lubrication performance calculation model established for this bearing includes the Reynolds equation, energy equation, film thickness equation, and elastic deformation equation. Theoretically analysing and calculating the lubrication performance of the circular tilting pad thrust bearing, the key performance parameters have identified such as minimum film thickness (hmin), temperature rise (ΔT), power consumption (W), and flow rate (Q). The calculation results show that the eccentricity ratio has a significant impact on the lubrication performance of the circular tilting pad thrust bearing. When both radial and circumferential eccentricity ratios are around 0.5, the bearing exhibits a high temperature rise, leading to a potential risk of bearing burnout. The results also show that at a radial eccentricity ratio of approximately 0.54, the minimum film thickness reaches its maximum value of 10.34 μm. Similarly, at a circumferential eccentricity ratio of about 0.60, the minimum film thickness reaches its peak value of 21.89 μm. This indicates that the eccentricity ratio plays a crucial role in the lubrication performance. In addition, the lubrication performance of the bearing under varying loads has been calculated at a speed of 9.5 r/min. The results demonstrated that the applied load significantly impacts the thrust bearing's performance. The findings elucidate the critical role of considering the eccentricity ratio and operational external load during the bearing design process. This study validates the potential of replacing rolling bearings with sliding bearings in wind turbine main shafts. It also provides a theoretical reference for the future design of sliding bearings.
Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1–4 over South Africa
Authors: Phakula Steven , Landman Willem A. , Engelbrecht Christien J. 
Published: February 2024

AbstractThe probabilistic forecast skill level of statistically downscaled European Centre for Medium‐Range Weather Forecasts (ECMWF) subseasonal‐to‐seasonal (S2S) forecasts is determined in predicting maximum and minimum temperatures for weeks 1–4 lead times during 20‐year December–January–February (DJF) seasons from 2001 to 2020 over South Africa. Skilful S2S forecasts are vital in assisting decision‐makers in the development of contingency planning for any eventualities that may arise because of weather and climate phenomena. Extreme high‐ and low‐temperature events over a prolonged period can lead to hyperthermia and hypothermia, respectively, and can lead to loss of life. The results from the relative operating characteristic (ROC) and reliability diagrams indicate that the ECMWF S2S model has skill in predicting maximum temperature up to week 3 ahead, particularly over the central and eastern parts of South Africa. The ROC scores indicate that the model has skill in predicting minimum temperature up to week 4 ahead for the above‐normal category, particularly over the central and eastern parts of South Africa. Reliability diagrams indicate that the model has a tendency of overestimating the below‐normal category when predicting both maximum and minimum temperatures for weeks 1–4 lead times over South Africa. Furthermore, canonical correlation analysis (CCA) pattern analysis suggests that when there are anomalously positive and negative predicted 850‐hPa geopotential heights located over South Africa, there are anomalously hot and cold conditions during the DJF seasons over most parts of South Africa, respectively. These results suggests that statistical downscaling of model forecasts can improve forecast skill. Moreover, the results suggest that there is potential for S2S predictions in South Africa, and as such, S2S prediction system for maximum and minimum temperatures can be developed.
Prediction of ultimate tensile strength of Al‐Si alloys based on multimodal fusion learning
Authors: Zhu Longfei , Luo Qun , Chen Qiaochuan , Zhang Yu , Zhang Lijun , Hu Bin , Han Yuexing , Li Qian 
Published: February 2024

AbstractExploring the “composition‐microstructure‐property” relationship is a long‐standing theme in materials science. However, complex interactions make this area of research challenging. Based on the image processing and machine learning techniques, this paper proposes a multimodal fusion learning framework that comprehensively considers both composition and microstructure in prediction of the ultimate tensile strength (UTS) of Al‐Si alloys. Firstly, the composition and image information are collected from the literature and supplementary experiments, followed by the image segmentation and quantitative analysis of eutectic Si images. Subsequently, the quantitative analysis results are combined with other features for three‐step feature screening, and 12 key features are obtained. Finally, four machine‐learning models (i.e., decision tree, random forest, adaptive boosting, and extreme gradient boosting [XGBoost]) are used to predict the UTS of Al‐Si alloys. The results show that the quantitative analysis method proposed in this paper is superior to Image‐Pro Plus (IPP) software in some aspects. The XGBoost model has the best prediction performance with R2 = 0.94. Furthermore, five mixed features and their critical values that significantly affect UTS are identified. Our study provides enlightenment for the prediction of UTS of Al‐Si alloys from composition and microstructure, and would be applicable to other alloys.
Longitudinal examination of borderline personality disorder symptoms and drug use: The influence of negative and positive emotion dysregulation
Authors: Waite Elinor E. , Raudales Alexa M. , Newberger Noam G. , Ferguson Jewelia J. , Denning Dominic M. , Huffman Sarah , Weiss Nicole H. , Dixon‐Gordon Katherine L. 
Published: February 2024

AbstractBorderline personality disorder (BPD) is associated with greater substance use. Emotion dysregulation has been implicated in both BPD and substance use, yet there is limited research examining the role of emotion dysregulation in the BPD–substance use relation. We examined the independent and interactive associations of BPD symptoms and emotion dysregulation in reported drug use over 1 year. Participants (N = 143) were over‐recruited for BPD, assessed via interview, and completed measures of negative and positive emotion dysregulation. Drug use frequency was assessed with monthly surveys over a 1‐year period. Results demonstrated interrelations among BPD symptoms and both negative and positive emotion dysregulation. However, when modeling BPD and emotion dysregulation together, only higher BPD symptoms were associated with more frequent drug use. Findings support the relation of BPD symptoms and emotion dysregulation but suggest that emotion dysregulation may not account for drug use frequency above and beyond BPD in community‐recruited populations.
A sequence‐based model for identifying proteins undergoing liquid–liquid phase separation/forming fibril aggregates via machine learning
Authors: Liao Shaofeng , Zhang Yujun , Han Xinchen , Wang Tinglan , Wang Xi , Yan Qinglin , Li Qian , Qi Yifei , Zhang Zhuqing 
Published: February 2024

AbstractLiquid–liquid phase separation (LLPS) and the solid aggregate (also referred to as amyloid aggregates) formation of proteins, have gained significant attention in recent years due to their associations with various physiological and pathological processes in living organisms. The systematic investigation of the differences and connections between proteins undergoing LLPS and those forming amyloid fibrils at the sequence level has not yet been explored. In this research, we aim to address this gap by comparing the two types of proteins across 36 features using collected data available currently. The statistical comparison results indicate that, 24 of the selected 36 features exhibit significant difference between the two protein groups. A LLPS‐Fibrils binary classification model built on these 24 features using random forest reveals that the fraction of intrinsically disordered residues (FIDR) is identified as the most crucial feature. While, in the further three‐class LLPS‐Fibrils‐Background classification model built on the same screened features, the composition of cysteine and that of leucine show more significant contributions than others. Through feature ablation analysis, we finally constructed a model FLFB (Feature‐based LLPS‐Fibrils‐Background protein predictor) using six refined features, with an average area under the receiver operating characteristics of 0.83. This work indicates using sequence features and a machine learning model, proteins undergoing LLPS or forming amyloid fibrils can be identified.
Challenges of liver transplantation programs in low‐ and middle‐income countries: An experience from Sri Lanka
Authors: Jayarathna M. J. S. , Dassanayake B. K. , Dorji Thinley , Lucero‐Prisno Don Eliseo , Samarasinghe S. , Pinto Vasanthi , Lamawansa M. D. 
Published: February 2024

AbstractLiver diseases lead to 1.3 million deaths per year around the world, the majority of which are secondary to cirrhosis. In the management of liver diseases in chronic and acute conditions, liver transplant (LT) plays a major role in improving the survival and quality of life of patients. LT programmes require the technical capabilities in performing the pre‐transplant evaluation, transplant surgery and post‐transplant care supported by adequate infrastructure and a set of trained teams. Globally, there were 28,000 deceased donor LTs, and 14,000 living donor LTs were performed in 2021. In the South Asia region, India, Pakistan and Sri Lanka conducted 2998 LTs in 2021. Many countries report sociocultural, religious and legislative barriers to acquiring adequate donor livers. We describe the challenges in LT programmes in low‐ and middle‐income countries and experiences from Sri Lanka. Sri Lanka carried out its first LT in 2010, and the service is provided free of charge in the state health sector. In Sri Lanka, the common indications for LT in adults are non‐alcoholic steatohepatitis, cirrhosis, hepatocellular carcinoma and alcoholic liver disease. In children, the indications are biliary atresia, hepatocellular carcinoma and Wilson disease. The common challenges include a lack of an adequate number of doctors and post‐transplant team members, a low number of organ donors and a long waiting list, all of which can be disadvantageous for transplant programmes. To continue providing LT services, there is a need to adopt multimodal strategies in the areas of providing additional skills training to the operating team and promoting organ donation culture in the background of supportive organ donation legislation. With the adoption of the national strategic plan for organ, tissue and cell transplantation, the country hopes to strengthen its capacity of providing transplant services to its people.
The vortex structure and near‐surface winds of Typhoon Faxai (2019) during landfall. Part II: Evaluation of WRF simulations
Authors: Takahashi Takuya , Nolan David S. , McNoldy Brian D. 
Published: February 2024

AbstractThis two‐part study presents a comprehensive analysis of (1) the vortex structure, (2) the inner core planetary boundary layer (PBL) wind profile, and (3) the overland surface winds of Typhoon Faxai(2019) during landfall observationally (Part I) and in high‐resolution Weather Research and Forecasting Model (WRF) simulations (Part II). Part II presents a framework for evaluating the wind field in the WRF simulations of Typhoon Faxai (2019) by comparing them with the observations presented in Part I. First, WRF simulations with two different surface roughness tables are presented. The simulation with the default table in WRF is shown to largely overestimate the surface wind speed. The overestimation is largely mitigated by using larger based on the climatology for urban and forest areas in Japan. Next, using the modified table, WRF simulations with three different PBL parametrizations, namely, Mellor–Yamada–Janjić, Yonsei University, and Mellor–Yamada–Nakanishi–Niino schemes are presented, and their impacts on the simulated vortex structure, inner core PBL wind profile, and overland surface winds are evaluated. In particular, the simulated surface winds are in good agreement with the observations outside the inner core of Typhoon Faxai. However, during the passage of the eyewall, the maximum surface winds are underestimated in the simulations. We show that the underestimation of the inertial stability, associated with the excessively large inner core of Typhoon Faxai in the simulations, led to the overestimation of the eyewall PBL jet height. This, in turn, caused the underestimation of the peak surface winds, as based on the empirical model of the wind reduction factor proposed in Part I.
Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway
Authors: Fakharzadeh Parastoo , Fakoor Saghih Amir Mohammad , Bohlouri Vahid , Motahari Farimani Nasser 
Published: February 2024

AbstractAs one of the most important reasons of irreparable losses at work, human error is still a significant problem in spite of the rapid technological advancement and reduced role of humans in the systems set up and control. Therefore, with the aim of reducing human error, this study presents a new method to improve human reliability using the hybrid approach of SPAR‐H and DSM. For this purpose, the number of 53 tasks was specified for the terminal conductor using Hierarchical Task Analysis (HTA). Then, the error related to each task was calculated utilizing the Standardized Plant Analysis‐Risk Human (SPAR‐H) method, and based on the expert team's opinion. Next, the terminal conductor's tasks were entered into the DSM along with the error numbers and dependencies between tasks, and the most optimal arrangement of tasks was obtained by coding in MATLAB software. Finally, by using the SPAR‐H method, the error of the terminal conductor was calculated based on the new tasks arrangement and compared with the primary state. Based on the obtained results, the 30% increase in reliability shows the significant contribution of the optimal arrangement of tasks in reducing human error. The proposed method of this study helps managers to reviewing the task structure in high‐risk processes as an effective strategy to reduce human error.
Interstitial lung changes and persistent COVID‐19 in a patient with follicular lymphoma: A case report
Authors: Yomota Makiko , Tanaka Masaru , Kobayashi Takayuki , Kitano Masatake , Ikeda Saori , Kanemasa Yusuke , Yanagawa Noriyo , Hosomi Yukio 
Published: February 2024

AbstractWe herein report a case of interstitial lung changes in a patient with prolonged coronavirus disease 2019 (COVID‐19) with follicular lymphoma receiving rituximab and bendamustine who recovered after treatment with a combination therapy consisting of corticosteroids and immunosuppressive agents. There is currently no treatment strategy for prolonged pneumonitis following COVID‐19, which can be life‐threatening for immunocompromised patients. Thus, further investigation is warranted.
Bayesian inference for nonprobability samples with nonignorable missingness
Authors: Liu Zhan , Chen Xuesong , Li Ruohan , Hou Lanbao 
Published: February 2024

AbstractNonprobability samples, especially web survey data, have been available in many different fields. However, nonprobability samples suffer from selection bias, which will yield biased estimates. Moreover, missingness, especially nonignorable missingness, may also be encountered in nonprobability samples. Thus, it is a challenging task to make inference from nonprobability samples with nonignorable missingness. In this article, we propose a Bayesian approach to infer the population based on nonprobability samples with nonignorable missingness. In our method, different Logistic regression models are employed to estimate the selection probabilities and the response probabilities; the superpopulation model is used to explain the relationship between the study variable and covariates. Further, Bayesian and approximate Bayesian methods are proposed to estimate the response model parameters and the superpopulation model parameters, respectively. Specifically, the estimating functions for the response model parameters and superpopulation model parameters are utilized to derive the approximate posterior distribution in superpopulation model estimation. Simulation studies are conducted to investigate the finite sample performance of the proposed method. The data from the Pew Research Center and the Behavioral Risk Factor Surveillance System are used to show better performance of our proposed method over the other approaches.
Synthesis of Imidazo[1,2‐a]pyridine‐Isoquinoline Derivatives as Potent EGFR Inhibiting Anticancer Agents
Authors: Gunuguntla Mahendar Reddy , Hanumantharayappa Manjunatha , Kumar Koppula Shiva 
Published: February 2024

AbstractHerein, we synthesized some new imidazo[1,2‐a]pyridine‐isoquinoline hybrids (8 a–8 x) and investigated their anticancer activity on two human breast cancer cell lines, namely MCF‐7 and MDA‐MB231. Generally, most of them displayed higher activity on both breast cell lines than the reference drug. Specifically, compounds (2,6‐difluorophenyl)(6‐methoxy‐1‐(2‐phenylimidazo[1,2‐a]pyridin‐3‐yl)‐3,4‐dihydroisoquinolin‐2(1H)‐yl)methanone, (6‐methoxy‐1‐(2‐phenyl imidazo[1,2‐a]pyridin‐3‐yl)‐3,4‐dihydroisoquinolin‐2(1H)‐yl)(6‐methoxy pyridin‐3‐yl)methanone, (6‐methoxy‐1‐(2‐phenylimidazo[1,2‐a]pyridin‐3‐yl)‐3,4‐dihydroisoquinolin‐2(1H)‐yl)(pyrimidin‐5‐yl) methanone, 6‐methoxy‐1‐(2‐phenylimidazo[1,2‐a]pyridin‐3‐yl)‐2‐(phenylsulfonyl)‐1,2,3,4‐tetrahydro isoquinoline, 6‐methoxy‐1‐(2‐phenyl imidazo[1,2‐a]pyridin‐3‐yl)‐2‐tosyl‐1,2,3,4‐tetrahydroisoquinoline, and 6‐methoxy‐2‐((4‐methoxyphenyl)sulfonyl)‐1‐(2‐phenylimidazo[1,2‐a] pyridin‐3‐yl)‐1,2,3,4‐tetrahydroisoquinoline showed higher activity against tested cancer cell lines as compared to the erlotinib. The ability of potent compounds to inhibit the tyrosine kinase EGFR was then studied and found that compounds (6‐methoxy‐1‐(2‐phenylimidazo[1,2‐a]pyridin‐3‐yl)‐3,4‐dihydroisoquinolin‐2(1H)‐yl)(pyrimidin‐5‐yl) methanone, 6‐methoxy‐1‐(2‐phenylimidazo[1,2‐a]pyridin‐3‐yl)‐2‐tosyl‐1,2,3,4‐tetra hydroisoquinoline, and 6‐methoxy‐2‐((4‐methoxyphenyl) sulfonyl)‐1‐(2‐phenylimidazo[1,2‐a]pyridin‐3‐yl)‐1,2,3,4‐tetrahydro isoquinoline exhibited promising potency in comparison to the erlotinib. In silico investigations of the most effective compounds were also performed to find interactions with the EGFR receptor that robustly bind to the protein, and energy estimates were in good agreement with the corresponding IC50 values.
Introjected regulation and academic burnout: A moderated mediation model of social comparison and distress overtolerance
Authors: Lee Minyoung 
Published: February 2024

AbstractThe primary purpose of this study is to examine the mediation effect of Contrastive Upward Comparison (CUC) on the relationship between introjected regulation and exhaustion (i.e., introjected regulation—CUC—exhaustion). It is also aimed to examine the moderation effect of distress overtolerance on this mediated relationship. In order to resolve the uncertainty about the causality of cross‐sectional studies, this study worked on the relationship among the variables by setting an alternative model (i.e., CUC—introjected regulation ‐ exhaustion). The participants were 167 (females, 70.7%) undergraduate and graduate students in South Korea. The results of this study indicated that introjected regulation showed indirect and significant effect on exhaustion via CUC. However, in the alternative model, the indirect effect of introjected regulation in the relationship between CUC and exhaustion was not significant. Furthermore, high distress overtolerance buffered the relationship between introjected regulation and CUC, while it strengthened the association of CUC and exhaustion. Lastly, the results of moderated mediation suggested that students with higher distress overtolerance, experienced more CUC, and emotional exhaustion. The implications and limitations were also discussed.
AIBI Modified Mesoporous Copper Sulfide Nanocomposites for Efficient Non‐Oxygen Dependent Free Radicals‐Assisted Photothermal Therapy in Uveal Melanoma
Authors: Huang Pingping , Kong Lingdan , Zhang Feiyu , Chen Linxin , Zhang Yue , Shi Xiaoqian , Lawson Tom , Chou Shulei , Liu Yong , Wu Wencan 
Published: February 2024

AbstractUveal melanoma (UM) is an ocular cancer predominantly affecting adults, characterized by challenging diagnostic outcomes. This research endeavors to develop an innovative multifunctional nanocomposite system sensitive to near‐infrared (NIR) radiation, serving as both a non‐oxygen free‐radical generator and a photothermal agent. The designed system combines azobis isobutyl imidazoline hydrochloride (AIBI) with mesoporous copper sulfide (MCuS) nanoparticles. MCuS harnesses NIR laser energy to induce photothermal therapy, converting light energy into heat to destroy cancer cells. Simultaneously, AIBI is activated by the NIR laser to produce alkyl radicals, which induce DNA damage in remaining cancer cells. This distinctive feature equips the designed system to selectively eliminate cancers in the hypoxic tumor microenvironment. MCuS is also beneficial to scavenge the overexpressed glutathione (GSH) in the tumor microenvironment. GSH generally consumes free radicals and hiders the PDT effect. To enhance control over AIBI release in cancer cells, 1‐tetradecyl alcohol (TD), a phase‐changing material, is introduced onto the surface of MCuS nanoparticles to create the final AMPT nanoparticle system. In vitro and in vivo experiments confirm the remarkable anti‐tumor efficacy of AMPT. Notably, the study introduces an orthotopic tumor model for UM, demonstrating the feasibility of precise and effective targeted treatment within the ocular system.