bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling academic adjustment: Modeling structural equations mediated by emotional fatigue in students
Authors: Wang Zhaozhi , Wang Huanjun 
Published: November 2024

Abstract

Background:
Academic achievement is a complex construct that results from myriad personal, environmental and institutional factors. Where those two variables meet, each student will have their probable academic success. The aim of the present study was to examine the associations of academic adjustment with emotional exhaustion among 467 Chinese college students. The current study aims to elucidate the role of emotional exhaustion as a mediator between academic adjustment and, on the other hand, academic performance, and second in terms of its impact on life satisfaction.
Methods:
This present study was a cross-sectional survey study that was conducted on university students of all years. The current study indicates that these questionnaires are highly reliable with low inversion. Objective: The present study utilized the structural equation model (SEM) to examine the role of emotional fatigue and academic adjustment on three principal constructs of students' university success.
Results: Correlational analysis showed that academic adjustment and satisfaction with life were positively correlated (r = 0.497, p < 0.01): students who adjusted well to study found themselves more satisfied with their lives overall format than those not doing so. The academic adjustment was also significantly associated with the academic performance (r = 0.451, p < 0.05), suggesting that those who sought support from faculty were more likely to perform well in academics and vice versa. The negative relationship was found in emotional burnout and academic adjustment (r = −0.392, p < 0.01), which suggested that higher level of emotional fatigue might result in poorer adaptation to campus life as well lower satisfaction with their lives (r = −0.424, p < 0) Mediation analysis revealed that a lower level of emotional fatigue among academically successful students mediated the association between academic adjustment and low achievement.
Conclusion:
Identifying pathways for predicting academic adjustment in students can guide the educators and/or local educational system to identify student with high risk of academic maladjustment.
Short-chain fatty acids are a key mediator of gut microbial regulation of T cell trafficking and differentiation after traumatic brain injury
Authors: Celorrio Marta , Shumilov Kirill , Ni Allen , Self Wade K. , Vitorino Francisca N. L. , Rodgers Rachel , Schriefer Lawrence A. , Garcia Ben , Layden Brian T. , Egervari Gabor , Baldridge Megan T. , Friess Stuart H. 
Published: November 2024

Abstract

The gut microbiota has emerged as a pivotal regulator of host inflammatory processes after traumatic brain injury (TBI). However, the mechanisms by which the gut microbiota communicates to the brain in TBI are still under investigation. We previously reported that gut microbiota depletion (GMD) using antibiotics after TBI resulted in increased microglial activation, reduced neurogenesis, and reduced T cell infiltration. In the present study, we have demonstrated that intestinal T cells contribute to the pool of cells infiltrating the brain after TBI. Depletion or genetic deletion of T cells before injury reversed GMD induced reductions in post-TBI neurogenesis. Short-chain fatty acid supplementation increased T regulatory and T helper1 cell infiltration to the brain along with restoring neurogenesis and microglia activation after TBI with GMD. These data suggest that T cell subsets are essential cellular mediators by which the gut microbiota modulates TBI pathogenesis, a finding with important therapeutic implications.
AutoRNet: Automatically Optimizing Heuristics for Robust Network Design via Large Language Models
Authors: Yu He , Liu Jing 
Published: November 2024

Abstract

Achieving robust networks is a challenging problem due to its NP-hard nature and the vast, complex, high-dimensional solution space. Current methods, from handcrafted feature extraction to deep learning approaches, have made certain advancements but remain rigid and complex, often requiring manual design, trial and error, and large amounts of labeled data. To deal with these problems, we propose AutoRNet, a novel framework that integrates large language models (LLMs) with evolutionary algorithms to automatically generate complete heuristics for robust network design. With the intrinsic properties of robust network structure in mind, effective network optimization strategy-based variation operations are designed to provide domain specific prompts for LLMs to help them make use of domain knowledge to generate advanced complete heuristics. Moreover, to deal with the difficulty brought by the hard constraint of maintaining degree distributions, an adaptive fitness function, which can progressively strengthening constraints to balance convergence and diversity, is designed. We evaluate the robustness of networks generated by AutoRNet’s heuristics on both sparse and dense initial scale-free networks. These solutions outperform those from current methods. AutoRNet reduces the need for manual design and large datasets, offering a more flexible and adaptive approach for generating robust network structures
Toward Online Personalization of Continuous Impedance Control for Powered Knee Prostheses
Authors: Hong Woolim , Naseri Amirreza , Huang He (Helen) 
Published: November 2024

Abstract

Humans perform locomotion by continuously modulating lower-limb joint impedance to ensure safe and adaptive interactions with the environment. This principle makes continuous impedance control promising for robotic prostheses to assist individuals with lower-limb amputations in locomotion. However, a significant challenge remains in control personalization to accommodate each user’s unique physiological traits. This study proposes a novel approach to enable personalization of continuous impedance prosthesis control. Kinematics-informed optimization was used to capture continuous knee impedance values in walking. Principal Component Analysis (PCA) was then used to characterize the impedance curves with a reduced number of parameters, enabling tuning for each user's desired control impedance. Experimental evaluations with human participants demonstrate the feasibility of our personalization method to adjust continuous impedance to achieve the desired gait pattern. The findings inform a promising solution for delivering tailored prosthetic control, enhancing the experience, function, and quality of life of each user with lower-limb amputation.
An orally available Mpro/TMPRSS2 bispecific inhibitor with potent anti-coronavirus efficacy in vivo
Authors: Chu Hin , Shuai Huiping , Qiao Jingxin , Yoon Chaemin , Zhang Guo , Hou Yuxin , Xia Xiaoyan , Wang Lei , Deng Xinyue , Wang Yifei , Li Qingquan , Du Lianzhao , Liu Yuanchen , Zhou Minmin , Wong Hoi Ting , Liu Huan , Hu Bingjie , Chen Yan , Fang Zhen , Xia Ziyi , Chai Yue , Shi Jialu , Wang Yang , Zhu Tianrenzheng , Zhang Honglei , Yuan Shuofeng , Zhou Jie , Chan Jasper , Yuen Kwok-Yung , Xu Chunfu , Lei Jian , Yang Shengyong 
Published: November 2024

Abstract

Coronaviruses have caused three major endemics in the past two decades. Alarmingly, recent identification of novel zoonotic coronaviruses that caused human infections suggests the risk of future coronavirus outbreak caused by spillover infection from animal reservoirs remains high1,2. Therefore, development of novel therapeutic options with broad-spectrum anti-coronavirus activities are urgently needed. Here, we develop an orally-available bispecific inhibitor, TMP1, which simultaneously targets key coronavirus replication protease Mpro and the essential airway protease TMPRSS23,4. TMP1 shows broad-spectrum protection not only against different SARS-CoV-2 variants but also against multiple human-pathogenic coronaviruses in vitro. By using the K18-hACE2 transgenic mouse, hDPP4 knock-in mouse and golden Syrian hamster models, we demonstrate TMP1 cross-protects against highly-pathogenic coronaviruses (SARS-CoV-1, SARS-CoV-2 and MERS-CoV) in vivo and efficiently abrogates SARS-CoV-2 transmission. Through structural and mutagenesis studies, we confirmed the direct interaction of TMP1 with Mpro and TMPRSS2, and pinpoint the key sites of interactions. Importantly, TMP1 inhibits the infection of nirmatrelvir-resistant SARS-CoV-2 escape mutants. Together, our findings demonstrate the antiviral potential of the novel bispecific Mpro/TMPRSS2 antiviral design against human-pathogenic coronaviruses and other emerging coronaviruses.
Change of opioid prescribing before and after the COVID pandemic in California, 2017-2022
Authors: Wang Yun , Wang Hao , Watson Drake , Jose Kabir Snell , Stofer Ryan , Ng Quinton Ding Quan , Chang Chih-Hung , Miotto Karen A. , Heshmatipour Matthew , Chan Alexandre 
Published: November 2024

Abstract

Background The coronavirus disease pandemic 2019 (COVID-19) has profoundly affected healthcare access, but its impact on high-risk opioid prescribing patterns remains unclear. The study aimed to investigate the changes in high-risk opioid prescribing in California during the pre-pandemic and during-pandemic phases.
Methods: This retrospective observational study utilized data from California’s prescription drug monitoring program (PDMP) to analyze high-risk opioid prescribing patterns. The study included California residents who received at least one oral opioid prescription during the study period, spanning a 33-month pre-pandemic phase (June 2017 to March 2020) and a 33-month pandemic phase (March 2020 to December 2022). We assessed four high-risk opioid prescribing patterns: (1) multiple provider episodes, (2) overlapping opioid prescriptions for seven or more days, (3) concurrent opioid and benzodiazepine prescriptions for seven or more days, and (4) high standardized dosage of opioid prescriptions. To evaluate the impact of COVID-19 on these prescribing patterns, we applied interrupted time series analyses to assess trends before and after the onset of the pandemic in March 2020.
Results: Our analysis included 73 236 002 opioid prescriptions filled by 19 048 455 patients in California. Segmented regression analysis revealed declining trends in high-risk opioid prescribing behaviors before March 2020. However, since the onset of the COVID-19 pandemic, the declining trends in overlapping opioid prescriptions, multiple provider episodes, concurrent use of opioids and benzodiazepine, and high-dose opioid prescriptions have been mitigated.
Conclusions: The pandemic likely influenced the decline in high-risk opioid prescribing patterns observed before its onset.
Revamping Road Tax Compliance: Unveiling Insights from Fiscal Psychology and Planned Behavior
Authors: Koerniawan Koenta Adji , Putri Andita Lusiana 
Published: November 2024

Abstract

This research explores the effects of road tax socialization, tax service quality, and tax sanctions on taxpayer compliance in Depok City’s Samsat (One-Stop Integrated Administration System). Data were collected through surveys of 44 tax authorities. Although Samsat employees have a positive view of tax socialization and service quality, road tax revenue remains low, suggesting a disconnect between perception and reality. The findings indicate a significant positive relationship among tax socialization, service quality, tax sanctions, and compliance, yet the revenue gap implies other influencing factors. The study suggests enhancing compliance through outreach, improved services, and stricter enforcement while integrating fiscal psychology and planned behavior theories with local socio-economic contexts. This approach offers tax authorities and policymakers valuable insights to improve road tax revenue.
Traffic Prediction and Network Load Forecasting in Mobile Networks Using Machine Learning
Authors: K SURESH KUMAR 
Published: November 2024

Abstract

Precisely, the accuracy in predicting network traffic with precise forecasting of load at the right time are very important because they contribute directly towards the optimal distribution of resources and prevention of future congestion in mobile networks. This work is based on predicting future network traffic patterns and load through the implementation of machine learning methods applied based on supervised algorithms, like Random Forests and Support Vector Machines (SVM). The proposed models use historical network data, environmental factors, and user behaviour to make real-time predictions about the traffic demand under which network resources can proactively be adjusted in advance. The experiments show that the machine learning-based models have better performance than the traditional ones, which means a higher accuracy in traffic demand prediction and better effectiveness in network management. This study shows how powerful machine learning is in making mobile networks offer better performance and reliability through effective ensuring optimal resource distribution and resisting congestion.
Neuroscreen-1 Cell Line – a Model for Parkinson’s Disease Neuronal Cell Death but not Alpha-Synucleinopathy
Authors: Chua PinFen , Lim William K. , Seruji Nurr Maria Ulfa , Lizazman Mas Atikah , Mian Vivien Jong Yi 
Published: November 2024

Abstract

Parkinson’s disease (PD) is characterised by the loss of dopaminergic neurons in the substantia nigra and the presence of Lewy bodies containing α-synuclein (α-syn). PC12 cells are commonly used in cellular PD models. Neurocreen-1 cells (NS-1, a variant of PC12 cells) have a reduced doubling time and exhibit an enhanced neuronal phenotype compared to its parental PC12 cell line. This study aimed to develop a PD model with NS-1 cells based on the neurotoxin 6-hydroxydopamine (6-OHDA). Firstly, we investigated the expression of (endogenous) wild-type α-syn and pathological phosphorylated α-syn (pSer129-α-syn) in 6-OHDA-treated NS-1 cells via western blotting. However, wild type or pSer129-α-syn could not be immunodetected. Next, we examined the caspase-dependent apoptotic pathway in NS-1 cells treated with 6-OHDA. Cell viability was reduced, with significant activation of caspase-3 and -7. We validated this model by testing the effects of xanthones, a class of phytochemicals with reported neuroprotective properties. Gamma-mangostin at 10 nM increased cell viability with significant inhibition of caspase 3/7 activity, while beta-mangostin gave a lower effect. Lastly, we investigated the antiparkinsonian properties of lesser-studied xanthones: brasixanthone B, ananixanthone, thwaitesixanthone, trapezifolixanthone, and beta-mangostin.
NS-1 cells replicated the effects of the neurotoxin 6-OHDA seen in parental PC12 cells. Of the lesser-studied xanthones, brasixanthone B and ananixanthone gave the greatest antiapoptotic activity in the PD model. We make the first report that brasixanthone B and thwaitesixanthone are neuroprotective. NS-1 is a fast-growing and adherent cell line with neuronal characteristics useful as an in vitro PD model in screening compounds for antiapoptotic effects, but unsuitable for modelling α-synucleinopathy.
Analyzing Variability of Rainfall and Meteorological Drought Over Wolaita Zone, Ethiopia
Authors: Arba Adugna , Kebede Abebe 
Published: November 2024

Abstract

Rainfall variability is one of the most significant climate variables for global agricultural productivity. It has also effect on the agricultural activities, water and food security over the Wolaita Zone. Station and merged satellite data from 1990 to 2020 and also the two stages of the Coupled Model Intercomparison Project (CMIP6) data to analyze historical (1985 to 2014) and future projected meteorological drought changes from (2041–2100) using two Shared Socioeconomic Pathway (SSP) under SSP2-4.5 and SSP5-8.5 emission scenarios were used in this study. The variability of rainfall at the annual, seasonal, and monthly scales was analyzed by using the coefficient of variation (CV) and standardized rainfall anomalies (SRA) over the study area. The modified Mann-Kendall test was used to determine the upward or downward trend and Sen’s slope estimator was used to determine increasing or decreasing in the magnitude. In this study, the power transformation (PT) bias correction method was used to correct the GCM (CMIP6) model data with the observed rainfall dataset serving as a reference. The SPI is the drought index, which indicates historical and future projected meteorological drought conditions at different severity levels that range from normal to extreme drought conditions. Future projected meteorological drought will be more affected by extreme and severe drought during the middle and far future under SSP2-4.5 and SSP5-8.5 scenarios, which is more frequent and intense than historical time over the study area. This study provides important guidance for identifying causes, minimizing impacts, and enhancing resilience to droughts over the Wolaita Zone.
Advanced Lung Disease Detection: CBAM-Augmented, Lightweight EfficientNetB2 with Visual Insights
Authors: Godbin A. Beena , Jasmine S. Graceline 
Published: November 2024

Introduction:
This paper presents a multichannel deep-learning method for detecting lung diseases using chest X-ray images. Using EfficientNetB0 through
EfficientNetB7 pretrained models, the methodology offers improved performance in classifying COVID-19, viral pneumonia, and normal chest Xrays.

Methods:
The EfficientNetB2 model was customized by incorporating Squeeze-and-Excitation (SE) blocks and the Convolutional Block Attention Module
(CBAM) to improve the model's attention mechanisms. Additional convolutional layers were added for improved feature extraction, and multiscale
feature fusion was implemented to capture features at different scales.

Results:
In this study, 99.3% of the unseen chest X-ray images were identified using the proposed model. It demonstrated superior performance, surpassing
existing techniques and highlighting its robustness and generalizability on unseen data samples.

Conclusion:
Moreover, visualization techniques were used to inspect the intermediate layers of the model, providing deeper insights into its processing and
interpretation of medical images. The proposed method offers healthcare radiologists a valuable tool for rapid and accurate point-of-care diagnoses.
Features of hemostasis in patients with hemophilic arthropathy of the knee joint in the perioperative period
Authors: Averianov Ye.V. , Shkrebko V.O. 
Published: November 2024

Background. Today, hemophilia is considered a hematological-orthopedic disease that develops as a result of damage to various anatomical structures of the musculoskeletal system among which the synovial joints, the so-called target joints, dominate in almost all patients with hemophilia. The aim of our study was to analyze the influence of the level of coagulation factors in patients with hemophilic arthropathies of the knee joint in different periods of surgical treatment. Materials and methods. To carry out our research, we analyzed data from 77 patients with hemophilia who underwent inpatient and outpatient treatment at the MNPE “Kyiv City Clinical Hospital 9” from 2008 to 2022. The first group included 43 (55.8 %) patients who underwent surgical synovectomy. The second group comprised 34 (44.2 %) patients who underwent total knee arthroplasty. Results. In our study, the coagulation factor level in the preoperative period was 1.66 ± 0.15 IU/ml in the first group, and 1.83 ± 0.15 IU/dl in the second group. Before surgery, all patients were administered coagulation factor VIII at a dose of 50 IU/kg of body weight. As a result, during surgery, the coagulation factor level was 92.6 ± 2.0 IU/dL in the first group, and 98.5 ± 2.2 IU/dL in the second group. These mean levels of factor VIII deficiency are a typical predicted response to administration of recombinant factor VIII concentrate. Such content of coagulation factor VIII corresponded to the normal level of coagulation factor VIII during surgery and did not require intraoperative correction. In the postoperative period, there was a significant decrease in the level of coagulation factor VIII to 69.3 ± 1.4 IU/dl in patients of the first group and 75.3 ± 1.5 IU/dl in the second group. Such a drop in the postoperative period is natural, taking into account the typical pharmacokinetics of coagulation factor VIII preparations in patients with hemophilia. Conclusions. Given the obtained indicators of coagulation factor VIII, as well as the peculiarities of the pharmacokinetics of its recombinant drug, patients of both observation groups were administered a maintenance dose of 25 IU/kg in the postoperative period.
PEMERTAHANAN NILAI KEKERABATAN MELALUI TRADISI MERENDENG-ENDENG PAMINGKE LABUHANBATU UTARA
Authors: Ritonga Syafriyana , Wuriyani Elly Prihasti , Harahap Rosmawaty 
Published: November 2024

AbstrakTujuan penulis dalam artikel ini adalah untuk melestarikan nilai-nilai pemertahanan antar kerabat dan lingkungan melalui tradisi marendeng-endeng. Secara empiris kajian penulis dalam tradisi ini mencakup syair nyanyian yang sering digunakan dalam merendeng-endeng berdasarkan pendekatan kualitatif dengan metode deskripsi secara makna simbolik dalam budaya etnis mandailing. Tradisi ini sudah mulai hilang di daerah Pamingke Labuhanbatu Utara. Oleh sebab itu penulis membuat penelitian guna untuk melestarikan kembali tradisi lokal di daerah tersebut agar tidak punah. Nilai-nilai yang didapat dalam tradisi marendeng-endeng yaitu menggambarkan keakraban terhadap sanak saudara melalui metode tradisi merendeng-endeng sekaligus untuk menghibur masyarakat dalam acara pernikahan, aqiqah, dan mengayunkan anak. Tradisi marendeng-endeng memiliki makna nasehat dalam bentuk syair nyanyian yang disajikan mulai nyanyian endeng-endeng, reremanarere, marudan marlasniari, dllKata kunci : tradisi merendeng-endeng, nilai-nilai, pemertahanan kekerabatan
GAYA BAHASA PERBANDINGAN DALAM SINANDONG MELAYU TANJUNG BALAI
Authors: Maida Hida Al , Marsella Emma , Widayati Dwi 
Published: November 2024

AbstrakPenelitian ini bertujuan untuk mengetahui makna dari gaya Bahasa dan diksi-diksi yang terkandung dalam Sinandong Melayu Tanjung Balai dengan menggunakan kajian stilistika yang bermanfaat untuk mengembangkan dan melestarikan seni kebudayaan Sinandong Melayu Tanjung Balai. Pradopo (2020: 2) menjelaskan bahwa stilistika adalah ilmu tentang gaya (bahasa). Gaya Bahasa dibagi menjadi gaya Bahasa perulangan, gaya Bahasa perbandingan, gaya Bahasa pertentangan, dan gaya Bahasa pertautan. Metode yang digunakan dalam penelitian ini adalah metode deskriptif kualitatif dengan pendekatan analisis isi. Sumber dari penelitian ini adalah Sinandong Melayu Tanjung Balai dengan data berupa kata-kata atau kalimat yang ditemukan melalui teknik telaah pustaka, analisisi data, dan pengolahan data. Hasil penelitian ditemukan banyak sekali gaya Bahasa dan diksi dalam Sinandong Melayu Tanjung Balai yang mengandung makna sarat akan nasehat, pelajaran hidup, petuah-petuah orang tua, dan lain-lain.Kata kunci: analisis, gaya bahasa, sinandong Melayu, Stilistika AbstrackThis study aims to determine the meaning of the language style and dictions contained in the Tanjung Balai Malay Sinandong by using stylistic studies that are useful for developing and preserving the Tanjung Balai Malay Sinandong cultural arts. Pradopo (2020: 2) explains that stylistics is the science of style (language). Language style is divided into repetition language style, comparative language style, contradicting language style, and linking language style. The method used in this study is a qualitative descriptive method with a content analysis approach. The source of this research is the Tanjung Balai Malay Sinandong with data in the form of words or sentences found through literature review techniques, data analysis, and data processing. The results of the study found that there are many styles of language and diction in Tanjung Balai Malay Sinandong which contain meanings full of advice, life lessons, advice from parents, and others.Keywords: analysis, language style, sinandong Melayu, Stylistics