Two-colour QCD phases and the topology at low temperature and high density by Kei Iida, Etsuko Itou, Tong-Gyu Lee

“…In addition, we newly find that around the boundary between the hadronic and BEC phases, nonzero quark number density occurs even in the hadronic phase in contrast to the prediction of the chiral perturbation theory (ChPT), while the diquark condensate approaches zero in a manner that is consistent with the ChPT prediction. …”
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The theses for PhD degree by article Editorial

“…Bystrovskaya – Postcholecystectomy syndrome: clinical variants, prediction and prophylaxis.N.I. Zhernakova – Clinical neuroimmunoendocrinology of peptic ulcer in elderly patients. …”
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Optimalisasi Prediksi Harga Ihsg Menggunakan Hybrid Weighted Fuzzy Time Series Hidden Markov Model Dengan Algoritma Evolusi Differensial by Alya Fitri Syalsabilla, Suci Astutik, Agus Fachrur Rozy

“…This research aims to enhance the prediction of IHSG price through hybrid model optimization and performance evaluation. …”
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Research on cutting mechanism and process optimization method of gear skiving by Peng Wang, Yuanchao Ni, Xiaoqiang Wu, Jiaxue Ji, Geng Li, Jiahao Wu

“…This prediction model allows for the construction of a multi-objective optimization model for the process parameters. …”
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UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data by Shiyang Zhou, Qingyong Zhang, Peng Xiao, Bingrong Xu, Geshuai Luo

“…Experiments conducted on three load datasets from Australia, Panama and Austria show that UniLF achieves superior forecasting accuracy with competitive practical efficiency under different prediction lengths, providing a new solution for STLF.…”
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Study some two loop contribution to muon anomalous MDM in the N-B-LSSM by Xing-Yu Han, Shu-Min Zhao, Long Ruan, Xi Wang, Xing-Xing Dong

“…From the data obtained in all the figures of the numerical results, most of the values of $$a_{\mu }^{NBL}$$ a μ NBL are in 2 $$\sigma $$ σ interval, which can compensate the departure between the experiment data and the SM prediction.…”
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Discovering emergent connections in quantum physics research via dynamic word embeddings by Felix Frohnert, Xuemei Gu, Mario Krenn, Evert van Nieuwenburg

“…We demonstrate that this representation enables accurate predictions about the co-occurrence of concepts within research abstracts over time. …”
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Deciphering CSU pathogenesis: Network toxicologyand molecular dynamics of DOTP exposure by Fang Cao, Cui Guo, Jing Guo

“…Methods: The structural analysis of DOTP was conducted in PubChem, with target prediction executed via Swiss Target Prediction and SuperPred, and target identification standardized using UniProt. …”
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Nonthermal Signatures of Radiative Supernova Remnants. II. The Impact of Cosmic Rays and Magnetic Fields by Rebecca Diesing, Siddhartha Gupta

“…Understanding SNR evolution at this stage is crucial for estimating feedback in galaxies, as SNRs are expected to release energy and momentum into the interstellar medium near the ends of their lives. A standard prediction of SNR evolutionary models is that the onset of the radiative stage precipitates the formation of a dense shell behind the forward shock. …”
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Options of conservative treatment at acute adhesive smallintestinal obstruction by S. G. Shapovalyants, S. Ye. Larichev, M. Ye. Timofeyev, I. V. Babkova, Z. A. Zhemukhova, O. I. Seryogina

“…In 92 patients results of conservative treatment prediction were determined at ASIAO (forecast effectiveness was 98,9%).Conclusions. …”
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Devaluing memories of reward: a case for dopamine by Benjamin R. Fry, Nicolette Russell, Victoria Fex, Bing Mo, Nathan Pence, Joseph A. Beatty, Fredric P. Manfredsson, Brandon A. Toth, Christian R. Burgess, Samuel Gershman, Alexander W. Johnson

“…Abstract Midbrain dopamine cells encode differences in predictive and expected value to support learning through reward prediction error. …”
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Comparison of different models to describe the lactation curve of Holstein cows in a small-scale dairy system by Luis Javier Montiel-Olguín, Felipe de Jesús Ruiz-López, Sergio Gómez-Rosales, Germinal Jorge Cantó-Alarcón, Eliab Estrada-Cortés, Héctor Raymundo Vera-Ávila

“…The Bayesian information criterion (BIC) and mean square prediction error (MSPE) were used to assess the fit of the models to the observed data, and the root mean square prediction error as a percentage of the observed mean (%RMSPE) was used to evaluate the accuracy of the models. …”
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Defect modeling in semiconductors: the role of first principles simulations and machine learning by Md Habibur Rahman, Arun Mannodi-Kanakkithodi

“…ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. …”
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Analysing COVID-19 Verified, Recuperate and Death Cases in Ethiopia Using ARIMA Models by Birhanu Betela Warssamo

“… Applying a successful prediction of the confirmed, recovered and deaths is thought to be the basic requirement to successfully control the spreading rate of diseases. …”
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Organoid models: applications and research advances in colorectal cancer by Yijie Wu, Yijie Wu, Yu Sha, Xingpo Guo, Ling Gao, Jian Huang, Song-Bai Liu, Song-Bai Liu

“…In conclusion, this review systematically explains the applications of organoids in colorectal cancer research, highlighting their tremendous potential and promising prospects in basic research, drug research and development, personalized treatment evaluation and prediction, and regenerative medicine.…”
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Identifying relevant EEG channels for subject-independent emotion recognition using attention network layers by Camilo E. Valderrama, Camilo E. Valderrama, Anshul Sheoran

“…BackgroundElectrical activity recorded with electroencephalography (EEG) enables the development of predictive models for emotion recognition. These models can be built using two approaches: subject-dependent and subject-independent. …”
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ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple allel... by Thinh Tuan Chu, Thinh Tuan Chu, Just Jensen

“…We found that genomic models using dense bi-allelic markers could effectively predicted breeding values of individuals in a well-structure population despite the presence of multi-allelic QTL. …”
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Impact of morphological traits and irrigation levels on fresh herbage yield of sorghum x sudangrass hybrid: Modelling data mining techniques. by Halit Tutar, Senol Celik, Hasan Er, Erdal Gönülal

“…For this purpose, Artificial Neural Networks (ANN), Automatic Linear Model (ALM), Random Forest (RF) Algorithm and Multivariate Adaptive Regression Spline (MARS) Algorithm were used, and the prediction performances of these methods were compared. …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…The study explores the potential of machine learning for improved diabetes prediction using microarray gene expression data and PIMA data set. …”
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Assessing Driving Risk Level: Harnessing Deep Learning Hybrid Model With Intercity Bus Naturalistic Driving Data by Wei-Hsun Lee, Che-Yu Chang

“…Additionally, the high-risk level prediction F1-score reaches 0.728 for the proposed model, which is up to 9.3 times better than the performance of the machine learning baseline model. …”
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