Amygdala activity for the modulation of goal-directed behavior in emotional contexts. by Kazutaka Maeda, Jun Kunimatsu, Okihide Hikosaka

Get full text

Peptide inhibitors of the anaphase promoting-complex that cause sensitivity to microtubule poison. by Scott C Schuyler, Yueh-Fu Olivia Wu, Hsin-Yu Chen, Yi-Shan Ding, Chia-Jung Lin, Yu-Ting Chu, Ting-Chun Chen, Louis Liao, Wei-Wei Tsai, Anna Huang, Lin-Ing Wang, Ting-Wei Liao, Jia-Hua Jhuo, Vivien Cheng

Get full text

Identification of copper metabolism-related subtypes, the development of a prognosis model, and characterization of the immune landscape in colorectal cancer by Geng Peng, Lin Zhong, Nan Lai, Lina Luo, Fu Cheng, Manzhao Ouyang

“…CMGs are effective biomarkers for predicting the prognosis of CRC patient and guiding immunotherapy.…”
Get full text

CD79A and GADD45A as novel immune-related biomarkers for respiratory syncytial virus severity in children: an integrated machine learning analysis and clinical validation by Juan Juan Chen, Zhang Ze Lu, Yu Xin Jing, Xing Mei Nong, Yi Qin, Jin Yang Huang, Na Lin, Jie Wei

“…Potential drug interactions for hug genes were predicted using the Drug-Gene Interaction Database (DGIdb). …”
Get full text

Real-Time Posture Correction of Squat Exercise: A Deep Learning Approach for Performance Analysis and Error Correction by Prashant Rao, C. S. Asha, P. Raghavendra Rao

“…Additionally, we introduce a regression-based approach to predict the correct squat posture. A deep learning-based regressor, trained on a dataset of squat videos, estimates the correct joint angles. …”
Get full text

Assessing the Risk of Natural and Socioeconomic Hazards Caused by Rainfall in the Middle Yellow River Basin by Yufeng Zhao, Shun Xiao, Xinshuang Wu, Shuitao Guo, Yingying Yao

“…In this study, we propose a comprehensive quantification framework and apply it to the Loess Plateau of northern China based on 40 years of climate data, streamflow measurements, and multiple spatial and geographical attribute datasets. A deep learning algorithm of long short-term memory (LSTM) was used to predict runoff, and the analytic hierarchy index was utilized to evaluate the comprehensive spatial risk considering natural and socioeconomic factors. …”
Get full text

Development of intelligent controller for high performance electric drives with hybrid CSA and RERNN technique by J. Prabhakaran, P. Thirumoorthi, M. Mathankumar, S. P. Mangaiyarkarasi

“…The CSA optimizes the voltage source inverter’s control signal, while RERNN predicts the optimal control signal. The system considered the variables of inertia, load torque, and rotor shaft angle. …”
Get full text

Integrative omics analysis reveals the genetic basis of fatty acid composition in Brassica napus seeds by Yuting Zhang, Yunhao Liu, Zhanxiang Zong, Liang Guo, Wenhao Shen, Hu Zhao

“…To elucidate the genetic underpinnings governing fatty acid composition, we then employ a combination of GWAS, TWAS, and dynamic transcriptomic analysis during seed development, along with the POCKET algorithm. We predict six candidate genes that are associated with fatty acid composition. …”
Get full text

Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods. by Mingtao Gao, Minhui Li, Lu Chen, Zihao Guo, Chengyang Guo, Liping Li, Changsen Bu

“…Especially in the rock specimen analysis of prefabricated multi-angle cracks, image quality and algorithm adaptability have emerged as the critical bottlenecks restricting the identification accuracy. …”
Get full text

Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…Furthermore, the modified variational Bayesian Kalman filter (VBKF) that accurately adjusts the measurement noise covariance matrix is proposed, and the Expectation–Maximization (EM) algorithm is employed to refine the prior parameter of the predicted error covariance matrix. …”
Get full text

Development of a New Correlation Model for Heat Transfer in Solar Air Heater with Corrugated Absorber Plates Using Swarm Optimization by Abdulkadir Kocer, Uğur Ercan, Zeki Yetgin, Filiz Karaomerlioglu

“…As the main contribution, two different model equations, namely M1 and M2, for the correlation model of the solar heat transfer were proposed to predict the Nusselt number, where M2 is an original model and M1 is newly established with the fine-tuned coefficients. …”
Get full text

Investigating lightweight and interpretable machine learning models for efficient and explainable stress detection by Debasish Ghose, Ayan Chatterjee, Indika A. M. Balapuwaduge, Yuan Lin, Soumya P. Dash

“…Furthermore, our study has incorporated local interpretable model-agnostic explanations to provide comprehensive insights into the predictions made by the k-NN-based architecture.…”
Get full text

MICROCIRCULATORY DISORDERS IN PATIENTS WITH ACUTE CORONARY SYNDROME by Sergey S. Krutitsky, Georgiy P. Plotnikov, Irina N. Sizova, Damir M. Galimzyanov, Dmitriy L. Shukevich, Evgeniy V. Grigoriev

“…Conclusions: Microcirculation parameters can be included in the diagnostic algorithm for ACS in patients with low cardiac output in order to predict cardiogenic shock and multiple organ failure. …”
Get full text

Crashworthiness and optimization for foam-filled multi-layer composite lattice structures by Jiye Chen, Wangwang He, Hai Fang, Yong Zhuang, Zhixiong Zhang, Yufeng Zhao

“…Additionally, the equivalent compressive modulus and compressive strength of the FMCLSs were predicted using a rule of mixtures.…”
Get full text

APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…In order to classify and predict churning customers, machine learning techniques are required to build the classifier model. …”
Get full text

Corruption through the prism of the theory of national security by S. M. Inshakov

“…Scientific novelty: for the first time, the paper examines the fundamental strategies of social corruption counteraction and their typology, analyzes the algorithm of state corruption counteraction, the factors of corruption counteraction efficiency, and predicts the prospects of anti-corruption activities of state bodies and civil society.Practical significance: the main provisions and conclusions of the article can be used in scientific and educational activities in considering the issues related to corruption counteraction.…”
Get full text

Investigating the Nonlinear Relationship Between the Built Environment and Urban Vitality Based on Multi-Source Data and Interpretable Machine Learning by Wenhao Liu, Zhen Yang, Chen Gui, Gen Li, Hongyi Xu

“…Our findings reveal the following key insights: (1) the distribution of urban vitality exhibits spatial heterogeneity within the main urban area of Shanghai, with high vitality areas concentrated in the Huangpu District and at intersections with neighboring districts, demonstrating a decline from the center to the periphery; (2) the XGBoost model outperforms other comparative models, showcasing superior capabilities in simulating and predicting urban vitality; (3) among the various built environment factors influencing urban vitality, building coverage, population density, and distance to the CBD exert the most significant effects, while the green view index and the number of bus stops contribute relatively less; (4) all built environment factors demonstrate nonlinear impacts and exhibit certain threshold effects on urban vitality. …”
Get full text

Physicochemical profiling and ranking of parkinson’s disease drugs through QSPR and Fuzzy TOPSIS analysis by YuLan Chen, Abdul Rauf, Aqsa Shafique, Fairouz Tchier, Adnan Aslam, Keneni Abera Tola

“…Notably, surface tension (ST) and polar surface area (PSA) showed weaker correlations (R 2 < 0.5, p > 0.05), highlighting limitations in their predictability via Sombor indices. This work demonstrates the utility of combining chemical graph theory, QSPR modeling, and Fuzzy TOPSIS for rational drug evaluation in neurodegenerative disorders. …”
Get full text

Unveiling the immune microenvironment of complex tissues and tumors in transcriptomics through a deconvolution approach by Shu-Hwa Chen, Bo-Yi Yu, Wen-Yu Kuo, Ya-Bo Lin, Sheng-Yao Su, Wei-Hsuan Chuang, I.-Hsuan Lu, Chung-Yen Lin

“…We validated mySORT using synthetic pseudo-bulk data derived from single-cell RNA sequencing (scRNA-seq) datasets. Our predictions exhibit strong concordance with the ground-truth immune cell composition, achieving Pearson’s correlation coefficients of 0.871 in melanoma patients and 0.775 in head and neck cancer patients. …”
Get full text

Pathology in a digital realm: food for thought! by Palzum Sherpa

“…Only time will tell if the predictions of the future of pathology being digital are true. …”
Get full text