Results of clinical developments of early triple negative breast cancer drug treatment: ASCO-2022 by D. A. Andreev, A. A. Zavyalov

“…The results presented in this article once again substantiate the prospects for further determination of algorithms for biomarker-personalized immunotherapy (in particular, pembrolizumab) as part of the combined antitumor treatment of RMZHER–/PR–/HER2– at early stages. …”
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Public and mental health professionals’ perspectives on social media and suicide exposure by Jo Bell, Christopher Westoby

“…Results Four key themes emerged: (1) The communicative ecology of social media (where the public act as content purveyors, rapidly disseminating varied and often unregulated narratives); (2) Harmful effects (including the copycat effect and toxic discourse); (3) Positive effects (where protective discourse and moderation offer harm reduction opportunities); and (4) Challenges in intervention (including content moderation difficulties and algorithmic biases that amplify harmful narratives). …”
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Hand gestures classification of sEMG signals based on BiLSTM-metaheuristic optimization and hybrid U-Net-MobileNetV2 encoder architecture by Khosro Rezaee, Safoura Farsi Khavari, Mojtaba Ansari, Fatemeh Zare, Mohammad Hossein Alizadeh Roknabadi

“…Abstract Surface electromyography (sEMG) data has been extensively utilized in deep learning algorithms for hand movement classification. This paper aims to introduce a novel method for hand gesture classification using sEMG data, addressing accuracy challenges seen in previous studies. …”
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Enhancing Reliability in Redundant Homogeneous Sensor Arrays with Self-X and Multidimensional Mapping by Elena Gerken, Andreas König

“…This demonstrates the concrete benefit of sensor redundancy and DR algorithms for creating robust, fault-tolerant measurement systems.…”
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An automation monitoring system for the production facility work by Артем Бронніков, Альона Коломієць, Олег Юрченко

“… The subject of research in the article is the application of technology and control algorithms in the automation system for monitoring the operation of the instrument building room. …”
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Properties of the SURE Estimates When Using Continuous Thresholding Functions for Wavelet Shrinkage by Alexey Kudryavtsev, Oleg Shestakov

“…Wavelet analysis algorithms in combination with thresholding procedures are widely used in nonparametric regression problems when estimating a signal function from noisy data. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…Exactly, traditional matrix-factorization-based algorithms often result in the loss of cubic structure knowledge in hyperspectral data, while deep neural networks are susceptible to noise accumulation and lack of large-scale labeled data. …”
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Advanced Multiplier Architecture Optimization for Accelerated Arithmetic Operations and its Integration in Wireless Sensor Network Applications by Nirmal Kumar R., Valarmathi R. S., Kalamani M.

“…Due to power efficiency, latency reduction, and resource use, optimum designs are required. …”
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Simulating Future Land Use/Land Cover of Tigris River Basin Assuming the Continuation of the Conditions During 2018 and 2023. by Abolfazl Ghanbari, Ayat Khaleel-Gharibawi, Hala Abdulkareem-Rubaiee, Mehrdad Jeihouni

“…Notably, LULC changes in TRB were critical, including a reduction in water resources, wetlands and croplands. …”
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Performance Estimation of Low Power and Area-Efficient Parallel Pipelined FFT by Surya P, Arunachalaperumal C, Dhilipkumar S

“…It is also used in image and video processing and is critical for algorithms that manipulate pixels, scale, and compress data when many multiplications need to be performed quickly. …”
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Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers by Ruslan Abdulkadirov, Pavel Lyakhov, Denis Butusov, Nikolay Nagornov, Dmitry Reznikov, Anatoly Bobrov, Diana Kalita

“…The advanced optimization algorithms achieve the global minimum of loss functions, which makes the precision and recall metrics superior to the ones for their known counterparts. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This fusion of deep learning innovation with the principles of randomization-based algorithms opens new avenues for developing accessible, accurate diagnostic tools, potentially alleviating the global impact of diabetic vision loss.…”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Compared to the baseline YOLOv8n model, YOLORM achieved a 7.43% increase in detection accuracy and a 15.21% reduction in computational complexity. Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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Contributon-Informed Approach to RPV Irradiation Study Using Hybrid Shielding Methodology by Mario Matijević, Krešimir Trontl, Dubravko Pevec

“…The complex design of a typical PWR is posing a deep penetration shielding problem for which an elaborate simulation model is needed, not only in geometrical aspects but also in efficient computational algorithms for solving particle transport. This paper presents such a hybrid shielding approach of FW-CADIS for characterization of the reactor pressure vessel (RPV) irradiation using SCALE6.2.4 code package. …”
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Decentralized multi-agent federated and reinforcement learning for smart water management and disaster response by H. Mancy, Naglaa E. Ghannam, Amr Abozeid, Ahmed I. Taloba

“…The new feature is a Decentralized Cooperation environment in which intelligent and self-managing agents learn utilizing Reinforcement Learning (RL) and Federated Learning (FL) algorithms for enhancing smart water management and real-time disaster relief. …”
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Detection of Defects in Polyethylene and Polyamide Flat Panels Using Airborne Ultrasound-Traditional and Machine Learning Approach by Artur Krolik, Radosław Drelich, Michał Pakuła, Dariusz Mikołajewski, Izabela Rojek

“…Furthermore, ML models are adaptable, allowing the same trained algorithms to work on various material batches or panel types with minimal retraining. …”
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Modelling soil prokaryotic traits across environments with the trait sequence database ampliconTraits and the R package MicEnvMod by Jonathan Donhauser, Anna Doménech-Pascual, Xingguo Han, Karen Jordaan, Jean-Baptiste Ramond, Aline Frossard, Anna M. Romaní, Anders Priemé

“…We created the trait sequence database ampliconTraits, constructed by cross-mapping species from a phenotypic trait database to the SILVA sequence database and formatted to enable seamless classification of environmental sequences using the SINAPS algorithm. The R package MicEnvMod enables modelling of trait – environment relationships, combining the strengths of different model types and integrating an approach to evaluate the models' predictive performance in a single framework. …”
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Machine Learning Prognostic Model for Post-Radical Resection Hepatocellular Carcinoma in Hepatitis B Patients by Zhu D, Tulahong A, Abuduhelili A, Liu C, Aierken A, Lin Y, Jiang T, Lin R, Shao Y, Aji T

“…A prognostic model was developed using a machine learning algorithm and evaluated for predictive performance using the concordance index (C-index), calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves.Results: Key predictors for constructing the best model included body mass index (BMI), albumin (ALB) levels, surgical resection method (SRM), and the American Joint Committee on Cancer (AJCC) stage. …”
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Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches by Suleiman Ibrahim Mohammad, Hamza Abu Owida, Asokan Vasudevan, Suhas Ballal, Shaker Al-Hasnaawei, Subhashree Ray, Naveen Chandra Talniya, Aashna Sinha, Vatsal Jain, Ahmad Abumalek

“…A range of sophisticated artificial intelligence methods, including One-Dimensional Convolutional Neural Network (1D-CNN), Artificial Neural Networks (ANN), Decision Tree (DT), Ensemble Learning (EL), Adaptive Boosting (AdaBoost), Random Forest (RF), and Least Squares Support Vector Machine (LSSVM), were utilized to model and predict pH variations with high accuracy. The Coupled Simulated Annealing (CSA) algorithm was employed to optimize the hyperparameters of these models, enhancing their predictive performance. …”
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Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…The objective was to apply a classification method to predict WQI using Kinta River data in Malaysia and improve on existing models&#x2019; <inline-formula> <tex-math notation="LaTeX">$70-95\%$ </tex-math></inline-formula> accuracy range. …”
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