Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes by Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Roberto Henriques, Daniele Ramazzotti

“…One of the most challenging tasks when adopting Bayesian networks (BNs) is the one of learning their structure from data. This task is complicated by the huge search space of possible solutions and by the fact that the problem is NP-hard. …”
Get full text

Experience of Semantic-Cognitive Modeling of Religious Worldview in Languages of Different Structure (HARAM Concept) by P. A. Magomedova

Get full text

The structural effects of evaluation types in the implementation process of the independent learning program in higher education by Bambang Budi Wiyono, Aan Komariah, Hendra Hidayat, Desi Eri Kusumaningrum

“…Questionnaires, interviews, and documentation were used as data collection techniques. Descriptive statistics, Structural Equation Modeling, and qualitative data analysis were used to process the data. …”
Get full text

Entropy-Based Block Scrambling Image Encryption Using DES Structure and Chaotic Systems by Xuncai Zhang, Lingfei Wang, Guangzhao Cui, Ying Niu

Get full text

Design and Development of Multi-Parameter Long-Term Monitoring Cable Tube Structure in Underground by ZOU Qi, XIN Ye, LIU Zhilong, DING Pengfei, LIU Fengxun, QIAO Dekang, YUAN Weijie

“…The cable tube has a three-layer pipe structure. The data of DTS and distributed acoustic sensing technology (DAS) can be collected and transmitted simultaneously in the high-temperature wellbore environment. …”
Get full text

Resolving Subsurface Structure with Magnetotelluric Method in the Urban Area of Pingtung County, Southwestern Taiwan by Haiyina Hasbia Amania, Ping-Yu Chang, Ding-Jiun Lin, Jordi Mahardika Puntu, Yekti Widyaningrum

“…This study presents the results of the Magnetotelluric (MT) survey aimed at resolving the subsurface structures in the northern part of the Pingtung Plain. …”
Get full text

RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning by Juan G. Carvajal-Patiño, Vincent Mallet, David Becerra, Luis Fernando Niño Vasquez, Carlos Oliver, Jérôme Waldispühl

“…Abstract RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. …”
Get full text

Causal signals between codon bias, mRNA structure, and the efficiency of translation and elongation by Cristina Pop, Silvi Rouskin, Nicholas T Ingolia, Lu Han, Eric M Phizicky, Jonathan S Weissman, Daphne Koller

“…We also show a correlation between efficiency and RNA structure calculated both computationally and from recent structure probing data, as well as the Kozak initiation motif, which may comprise a mechanism to regulate initiation.…”
Get full text

A study of Electronic Structure in W–Cu Alloys by using RFA and FE models by Fareed M. Mohammed, Shalash A. Mohammed, Abdul Qader A. Hussein, Sameh H. Saleh

Get full text

Viral escape-inspired framework for structure-guided dual bait protein biosensor design. by Yee Chuen Teoh, Mohammed Sakib Noor, Sina Aghakhani, Jack Girton, Guiping Hu, Ratul Chowdhury

“…CTRL-V successfully identifies ~70% (five out of seven) single point mutations (371F, 373P, 440K, 445H, 456L) in the latest circulating KP.2 variant and offers detailed structural insights to the escape mechanism. While other data-driven viral escape variant predictor tools have shown promise in predicting potential future viral variants, they require massive amounts of data to bypass the need for physics of explicit biochemical interactions. …”
Get full text

Structural changes in China's flow of funds (1992–2022): A Who-to-Whom model by Nan Zhang, Li Zhu

“…Our objective was to analyze structural changes in China's flow of funds and macroeconomic regulation. …”
Get full text

Human Height’s Development in Midwestern Spain, 1856-2000: Health, Nutrition, and Economic Structure by Antonio M. Linares-Luján, Francisco M. Parejo-Moruno

“…Data show important anthropometric growth in men recruited between 1856 and 2000 because of three major advances: the epidemiological transition, the nutritional transition, and structural change. …”
Get full text

The Influence of Cash Turnover, Accounts Receivable Turnover, Capital Structure, and Profit Growth on Profitability by Azizah Nasya Ziyadatul, Dewi Siska, Rokhman Nur

“…In this empirical study of manufacturing businesses in the consumer products industrial sector listed on the IDX in 2019–2023, the impact of cash turnover, receivables turnover, capital structure, and profit growth on profitability is the main goal. …”
Get full text

Financial Risk and Capital Structure: Does it Contribute to Increasing the Company Value of Islamic Banking? by Satrio Fajar Putra, Ulfi Kartika Oktaviana

“…This study aimed to determine the effect of financial risk and capital structure on the company value of Islamic commercial banks in 2016-2020. …”
Get full text

Understanding Newton's Third Law: A Study of Prospective Physics Teachers' Knowledge Structure by Wulan Anna Pertiwi, Revnika Faizah, Astrini Dewi Kusumawati, Nadiyah Nadiyah, Agus Setyo Budi, Luh Sukariasih

“…In contrast, the qualitative data source comes from students' reasons for choosing answers, which are used to see the characteristics of knowledge structures. …”
Get full text

SPECIFIC VELOCITY STRUCTURE OF THE UPPER MANTLE IN THE TRANSBAIKALIA SEGMENT OF THE MONGOLIA-OKHOTSK OROGENIC BELT by V. M. Soloviev, V. V. Chechelnitsky, A. S. Salnikov, V. S. Seleznev, A. V. Liseikin, N. A. Galyova

“…The seismic data was used to contour an area with high velocity values in the mantle in the central part of the Mongolia-Okhotsk orogenic belt and the neighboring fold structures of Transbaikalia. …”
Get full text

Relationship between serum Cystatin C and cardiac structure and function in peritoneal dialysis patients by LI Feng, AI Quan-ling, SHENGMei-xiao

“…Objective To evaluate the relationship between serum Cystatin C(Cys-C) and the structure and function of the heart in peritoneal dialysis(PD) patients.Methods Forty-four patients subject to PD treatment for 3 months or more were included from March 2012 to February 2013 in Department of Nephrology,Jiangsu Provincial Hospital of TCM in the end stage of chronic kidney disease and in a stable condition.According to serum Cys-C levels,44 patients were divided into two groups:high Cys-C group(Cys-C>7.0 mg/L) and low Cys-C group(Cys-C≤7.0 mg/L).The clinical data(total Ccr,total Kt/V,serum creatinine,hemoglobin,serum albumin,total cholesterol,and triglycerides) were collected,serum Cys-C level was determined by latex-enhanced immunoturbidimetry,and left atrial diameter,left ventricular end-diastolic diameter,left ventricular end-systolic diameter,left ventricular posterior wall thickness,interventricular septal thickness,stroke volume and ejection fractions were measured by color Doppler ultrasound.The differences in the clinical data and the indexes of the heart between two groups were observed,and the relationship between Cys-C and clinical data or the indexes of the heart was analyzed.Results There was no significant difference in LAD,LVDd,LVDs and SV between two groups(P>0.05).LVPWT,IVST and LVMI were higher in high Cys-C group,but LVEF was higher in low Cys-C group(P<0.05),prompting high Cys-C patients had elevated left ventricular hypertrophy and decreased heart function.Pearson correlation analysis revealed that serum Cys-C levels were positively correlated with LVMI,and negatively with LVEF.Serum Cys-C levels were positively correlated with serum creatinine and dialysis age,but negatively with total Ccr.Conclusions The increase of Cys-C in PD patients can result in left ventricular systolic dysfunction and make left ventricular hypertrophy and ventricular remodeling.We can predict cardiovascular complications by assessing cardiac function and structural changes in PD patients.…”
Get full text

Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination by Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie

“…Here, we address this issue by employing a physics-informed deep learning (PIDL) approach that quantifies uncertainty in two-dimensional seismic velocity structure modeling and its propagation to hypocenter determination by introducing neural network ensembles trained on active seismic survey data, earthquake observation data, and the physical equation of wavefront movement. …”
Get full text

Study of structural stability of a concrete gravity dam using a reliability approach� by Mohamed Essaddik Kerkar, Mustapha Kamel Mihoubi

“…Dam safety is a priority at the international level, it requires a large amount of data that allows analysts to make optimization on its structural stability, the latter is based on the estimation of the probability of failure from the effects of stress and resistance acting on the dam-reservoir system. …”
Get full text

Structural Reliability Analysis Based on IPSO-SVR for High-speed EMU Motor Hanger by Yonghua LI, Yue XU, Fuyu ZHAO, Yue WU

Get full text