Variational Quantum Monte Carlo Solution of the Many-Electron Schrödinger Equation Based on Deep Neural Networks by Huiping Su, Hongbo Gao, Xinmiao Wang, Xi He, Da Shen

“…Therefore, it is crucial to find an effective numerical method. To solve this problem, this paper present a deep learning architecture, VMCNet, using the powerful computational efficiency of neural networks to improve the speed of numerical computation. …”
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Biochemical Oxygen Demand Prediction Based on Three-Dimensional Fluorescence Spectroscopy and Machine Learning by Xu Zhang, Yihao Zhang, Xuanyi Yang, Zhiyun Wang, Xianhua Liu

“…Biochemical oxygen demand (BOD) is an important indicator of the degree of organic pollution in water bodies. Traditional methods for BOD₅ determination, although widely used, are complicated and dependent on accurate chemical measurements of dissolved oxygen. …”
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Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning by Łukasz Jeleń, Izabela Stankiewicz-Antosz, Maria Chosia, Michał Jeleń

“…The main purpose of cervical cancer diagnosis is a correct and rapid detection of the disease and the determination of its histological type. This study investigates the effectiveness of combining handcrafted feature-based methods with convolutional neural networks for the determination of cancer histological type, emphasizing the role of feature selection in enhancing classification accuracy. …”
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Development of a mathematical model for the formation of a semi-convex helicoid shape of the knife of the executive body of the geokhod by Efremenkov A.B., Nikitin E.I., Pashkov D.A., Nozirzoda Sh.S.

“…Mathematical modeling and 3D modeling methods were used to achieve the goal. Based on the specified parameters of the cross-section of a semi-convex knife, a system of equations has been developed that makes it possible, depending on the rational geometric characteristics of the cutting edge, to determine the trajectory of points on it. …”
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Buckling Analysis and Stability of Compressed Low-Carbon Steel Rods in the Elastoplastic Region of Materials by Gaioz Partskhaladze, Ingusha Mshvenieradze, Elguja Medzmariashvili, Gocha Chavleshvili, Victor Yepes, Julian Alcala

“…A new approach for the determination of critical stresses in the elastoplastic region was developed through which the structural reliability and economic efficiency was increased by almost 12% compared to the existing approaches.…”
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A Novel Integrated Path Planning and Mode Decision Algorithm for Wheel–Leg Vehicles in Unstructured Environment by Kui Wang, Xitao Wu, Shaoyang Shi, Mingfan Xu, Yifei Han, Zhewei Zhu, Yechen Qin

“…The simulation results show that the proposed method demonstrates significant advantages in terms of fewer mode-switching occurrences compared to existing methods.…”
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Natural Frequency Analysis of a Stepped Drill String in Vertical Oil Wells Subjected to Coupled Axial–Torsional–Lateral Vibrations by Mohamed Zinelabidine Doghmane

“…These findings contribute to drilling systems’ reliability and efficiency in the oil and gas energy sector.…”
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LOW LEVEL OF ANTITHROMBIN III AS A WARNING SIGN FOR DEVELOPING THROMBOTIC COMPLICATIONS IN SURGICAL PATIENTS by K. N. Zolotukhin, Ph. Krüger, A. V. Samorodov

“…The functional activity of platelets was studied using a Biola 230LA laser platelet aggregation analyser (Russia). The determination of circulating aggregates was conducted using the Wu — Hoak method. …”
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Green synthesis of titanium dioxide photocatalyst using Lactobacillus bulgaricus for processing palm oil mill effluent by L. Agustina, M. Romli, P. Suryadarma, S. Suprihatin

“…The effectiveness of titanium dioxide as a photocatalyst depends on the synthesis method used. The method affect the particle size, crystallinity and phase composition of the produced catalyst. …”
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Using trauma video review to search for the Goldilocks pre-activation time by Eric Klein, Ella Rose Rastegar, Sophia Görgens, Manuel Beltran del Rio, Elizabeth Nilsson Sjolander, Joseph Landers, Cristy Meyer, Daniel Rolston, Maria Sfakianos, Matthew Bank, Daniel Jafari

“…Objectives We sought to determine the optimal time to pre-activation for trauma team activation that resulted in maximum team efficiency, measured by the time to complete critical actions (TCCAs) during resuscitation. …”
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Research on nitrogen transformation pathways of a thermophilic heterotrophic nitrifying bacterial consortium GW7 by Yongqi Ma, Jiali Wang, Yindi Zhang, Wenping Guan, Wenrui Qi, Xisheng Tai, Dong Lin, Rong He, Likun Sun, Aiwen Zhang

“…Under these conditions, the NH₄+-N utilization efficiency increased to 87.80%. Enzymatic assays showed that the specific activities of GS, GDH, and GOGAT were 0.392 U/mg, 0.926 U/mg, and 0.195 U/mg, respectively. …”
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Effect of transcriptional coactivator with PDZ-binding motif on proliferation and migration of breast cancer cells and its mechanism by WANG Lin, ZHAO Gaoxiang

“…Colony-forming assay (CFA) and Transwell assay were used to determine plating efficiency and migration rate in groups A-F and a-f. …”
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Enhanced transdermal delivery of lidocaine cream via ultrasound and microneedle rollers by Jiaxiao Sun, Yang Yang, Yang Yang, Juanjuan Zheng, Hao Liang, Feng Yan, Wensheng Zhang, Wensheng Zhang, Wenqin Xie

“…ObjectiveThe aim of this study is to determine the most effective physical parameters for optimizing the transdermal delivery of lidocaine cream.MethodsPreliminary experiments were conducted to optimize ultrasound settings while ensuring safety, guided by visual and histopathological evaluations following observations of skin burns in rats. …”
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Induction Machine Bearing Fault Detection Using Empirical Wavelet Transform by Ricardo Lopez-Gutierrez, Jose de Jesus Rangel-Magdaleno, Carlos Javier Morales-Perez, Arturo García-Perez

“…Then, three types of goodness-of-fit tests are used, Kuiper, Kolmogorov–Smirnov, and Pearson chi-square, to classify the signals and determine which ones belong to a damaged engine. Finally, the experimental results show that the EWT in conjunction with the proposed goodness tests achieves competitive precision and efficiency in diagnosing induction motor-bearing faults.…”
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Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer by Ming Cai, Yifan Yao, Haibo Wang

“…Two efficiency experiments are implemented. One experiment involves comparing the expansibility of the parallel algorithm with various numbers of compute nodes and various computing scales to determine the expansibility. …”
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Research on online inspection of pantograph and catenary based on deep learning by ZHOU Zhaoan, LI Shuzhi

“…The pantograph-catenary system is a key part of power supply for electric locomotive, and its operating status determines the current receiving quality of electric locomotive, as well as safety and efficiency of trains. …”
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Theoretical Analysis of a Novel Rock Wall to Limit Heating Demands in Historical Buildings by Roberto Bruno, Antonio Cristaudo

“…The system was investigated preliminarily using a transient Finite Difference Method (FDM) code to analyse the temperature field inside the rock wall. …”
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Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks by Mohammad M. Hasan, Jason P. Jue

“…We present an easy-to-implement method named DED (distributed, energy-efficient, and dual-homed clustering) which provides robustness for WSNs without relying on the redundancy of dedicated sensors, that is, without depending on node density. …”
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Optimizing the Electrode Geometry of an In-Plane Unimorph Piezoelectric Microactuator for Maximum Deflection by Parker Megginson, Jason Clark, Ryan Clarson

“…After validating the finite element modeling method against experimental data, the geometric parameters of the proposed unimorph model are manipulated to explore the effect of different electrode geometries and layer thicknesses on actuation efficiency. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…With advancements in technology, more sophisticated techniques—such as reinforcement learning methods (e.g., DQN, Q-Learning, DDPG, and Meta-Learning)—could enhance the accuracy and efficiency of operational risk prediction models.…”
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