Modelling of structural, mechanical, electronic, and optical properties of Rb2TlXF6 (X = Ir, Rh) double perovskite compounds through density functional theory by Wasi Ullah, Nasir Rahman, Mudasser Husain, Wafa Mohammed Almalki, Khamael M. Abualnaja, Ghaida Alosaimi, Soufyane Belhachi, Bashar.M. Al-Khamiseh, Vineet Tirth, Ahmed Azzouz-Rached, Hanan A. Althobaiti, Farooq Ali

“…This study utilizes density functional theory (DFT) with the Tran–Blaha modified Becke–Johnson (TB-mBJ) exchange potential in the WIEN2k framework to comprehensively investigate the structural, electronic, elastic, and optical properties of Rb2TlIrF6 and Rb2TlRhF6 double perovskite compounds. …”
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An Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning by Xue Wang, Shiyuan Zhou, Zijia Wang, Xiaoyun Xia, Yaolong Duan

“…Furthermore, in the loser update strategy, an adaptive <i>t</i>-distribution perturbation strategy is utilized for its small mutation amplitude, which enhances the local search capability and robustness of the algorithm. …”
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Versatile graceful degradation framework for bio-inspired proprioception with redundant soft sensors by Taku Sugiyama, Kyo Kutsuzawa, Dai Owaki, Elijah Almanzor, Fumiya Iida, Mitsuhiro Hayashibe

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Improved Coulomb collision operator for kinetic ion transport with EMC3-EIRENE simulating Nitrogen seeding in medium density ITER L-mode scenario by D. Harting, D. Reiser, S. Rode, J. Romazanov, P. Börner, Y. Feng, H. Frerichs, A. Knieps

“…We have now implemented a new Coulomb collision operator in EIRENE, where the Coulomb collisions are described by a linear kinetic equation in Fokker-Planck form utilizing the Trubnikov-Rosenbluth potential functions, which includes scattering of the kinetic ions as well as friction with the background plasma. …”
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Short-Term Power Load Forecasting Based on DPSO-LSSVM Model by Shujun Ji, Linhao Zhang, Jinteng Wang, Tao Wei, Jiadong Li, Bu Ling, Jinglong Xu, Zuoping Wu

“…The dynamic particle swarm optimization algorithm is utilized to dynamically adjust the parameters to achieve higher accuracy in load forecasting. …”
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Reconfigurable Three-Switch Leg Multi-Port Boost Inverters With Novel Modulation Schemes for Hybrid DC/AC Microgrid Systems by M. Rama Narayana Reddy, B. Dastagiri Reddy, Prajof Prabhakaran, Andrii Chub, Samir Kouro

“…A hybrid modulation scheme was proposed, dynamically adapted to the configuration of DC and AC ports, facilitating seamless boost and dual inversion operations or combined boost, buck, and inversion functionalities within a single converter. …”
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Testing the Psychometric Properties of the Turkish Version of the LGBT Community Connectedness Scale by Yusuf Barburoğlu, S. Burcu Özgülük Üçok, Eda Çürükvelioğlu Köksal, Yuvamathi Gandhi, Pamela J. Lannutti

“…Thus, the current study adapted Frost and Meyer’s (2012) LGBT Community Connectedness Scale to Turkish. …”
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Provably secure quantum resistance two-server password-authenticated key exchange protocol by Anqi YIN, Yuanbo GUO, Ding WANG, Tongzhou QU, Lin CHEN

“…Aiming at the problem that the lattice-based single-sever password-authenticated key exchange (PAKE) protocols are not resistant to server compromise attack, while the existing lattice-based multi-server PAKE protocols are inefficient and incompatible with two-server scenarios.The first lattice-based two-party smooth projective hash function (SPHF) was proposed by utilizing the learning with errors (LWE), which was indistinguishability under adaptive chosen-ciphertext attack(IND-CCA2) secure.The parameters of the based public key encryption (PKE) scheme were also identified.On this basis, pertinent two-server PAKE protocols from lattices were designed countering both passive and active attackers.The two quantum resistance protocols were able to achieve password-only settings and the expensive cryptographic primitives were not used, including signature/verification, fully homomorphic encryption and secret sharing.The utilization of zero knowledge proofs were avoided by the protocol under the passive attackers.In the standard model, rigorous security proofs were provided for the two proposed protocols.Experimental results show that the proposed SPHF and PAKE protocols exhibit higher execution efficiency.…”
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An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system by Md. Naiem-Ur-Rahman, Md. Mahmudul Hasan, Afsana Mimi Raka, Md. Fayzur Rahman, Md. Masud Rana, Ahmed Al Mansur, Md. Abdur Razzak

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Altitude-Driven Variations in Nutritional, Bioactive, and Mineral Profiles of Hawthorn (<i>Crataegus</i> spp.) by Yanyan Liu, Lu Chen, Guohui Shen, Yanting Gu, Yanzhi Guo, Juan Han

“…By leveraging these insights, the functional and nutritional properties of hawthorn can be optimized, supporting its sustainable application in the food and health industries.…”
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Overexpression MsJAR1 gene increased lateral branches and plant height in alfalfa (Medicago sativa L.) by Rui Dai, Qi Chen, Xiao-yu Wang, Xiao-wei Huo, Jian-wei Li, Jiang-bo An, Fu-gui Mi, Feng-ling Shi, Zhi-qiang Zhang

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Assessment of the Integrated Communicable Disease Surveillance and Response System in Thamar Governorate, Yemen by Basem F. Abdel-Aziz, Saddam A.H. Al-Nahari, Ali A. Al-Waleedi, Shymaa M. Elshoura

“…Objectives: This study aimed to assess the IDSR system core and support functions in Thamar Governorate, Yemen. Methods: The study utilized a cross-sectional design. …”

Advanced DFE, MLD, and RDE Equalization Techniques for Enhanced 5G mm-Wave A-RoF Performance at 60 GHz by Umar Farooq, Amalia Miliou

“…Lastly, RDE is implemented as an alternative algorithm to the CMA-based equalizer, utilizing the idea of adjusting the amplitude of the received distorted symbol so that its modulus is closer to the ideal value for that symbol. …”
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A novel feature selection algorithm using decomposition based multi-objective guided honey badger algorithm (MO-GHBA) and NSGA-III by Anusha Papasani, Nagaraju Devarakonda

“…Classification accuracy improvement and removal of redundant features are considered to be the multi-objective optimization functions of the proposed multi-objective feature selection technique. …”
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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

“…This article presents deep learning frameworks for predicting electricity demand in the Western region of Bangladesh, utilizing Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithms. …”
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Design and Basic Performance Analysis of a Bionic Finger Soft Actuator with a Dual-Chamber Composite Structure by Yu Cai, Sheng Liu, Dazhong Wang, Shuai Huang, Dong Zhang, Mengyao Shi, Wenqing Dai, Shang Wang

“…The soft manipulator that has been developed at present still has problems with single function and poor load-bearing capacity. This paper designs a composite soft finger inspired by the human middle finger, featuring a dual-chamber pneumatic drive and embedded steel sheet structure. …”
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Analysis on gut microbiota diversity of wild Asian elephants (Elephas maximus) from three regions of Yunnan Province by Zeya Yang, Yixuan Wang, Yuhan Wang, Jiuxuan Zhou, Ruimei Wang, Mingfei Shi, Mingwei Bao, Binghui Wang, Ruiling Yuan

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Intelligent trajectory tracking algorithm for autonomous robots under membrane computing by YAO Jiangyun, WU Fangyuan

“…Finally, based on the multi-step parallel membrane structure, a feasible autonomous robot trajectory path was found, and a sliding mode variable structure function was used to design the control rate. The position error was adjusted by the control rate to achieve autonomous robot trajectory tracking. …”
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Fault-Tolerant Control of Steer-by-Wire System Based on Sliding Mode Observer With Neural Network by Rongji Yang, Daozheng Liao

“…Secondly, a sliding mode observer with neural network is designed, which utilizes an adaptive radial basis function (RBF) neural network to reconstruct the internal and external uncertainties, as well as the fault-induced uncertainty, and employs the terminal sliding mode algorithm to ensure fast convergence of observation errors. …”
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BCDCNN: breast cancer deep convolutional neural network for breast cancer detection using MRI images by D. E. Martina Jaincy, V. Pattabiraman

“…Afterwards, feature extraction is done and finally, BCD is conducted employing BCDCNN, wherein the loss function is newly designed based on an adaptive error similarity. …”
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