Unveiling Theranostics: Nanocomplex-Assisted Photodynamic Eradication of Aggressive Cancer Cells and Modulation of Tumor-Associated Macrophages by Butkute A, Kazlauske E, Mlynska A, Peciukaityte E, Karabanovas V, Rotomskis R, Steponkiene S

“…The nanocomplex accumulated efficiently and uniformly across all CRC cell lines, regardless of their aggressiveness or drug sensitivity. …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…The DL model exhibited high accuracy in tissue quantification and TP53 status prediction, outperforming traditional methods in terms of precision and efficiency. DL-based approaches offer significant promise for enhancing biomarker testing and precision oncology by reducing intra- and inter-observer variability, but further validation is required to optimize their integration into real-world clinical workflows. …”
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Global dynamics and time-optimal control studies for additional food provided holling type-III mutually interfering prey-predator systems with applications to pest management by D. Bhanu Prakash, D. K. K. Vamsi

“…Abstract In this study, we derive and analyze an additional food provided prey-predator model with Holling type-III functional response, incorporating mutual interference among predators. …”
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Exploring Purpose-Driven Methods and a Multifaceted Approach in Dam Health Monitoring Data Utilization by Zhanchao Li, Ebrahim Yahya Khailah, Xingyang Liu, Jiaming Liang

“…Dam monitoring tracks environmental variables (water level, temperature) and structural responses (deformation, seepage, and stress) to assess safety and performance. …”
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Comparison of Numerical Results With Experiment Using Digital Image Correlation System of Multiobjective Structural Optimised Wind Turbine Blade by Ramazan Özkan, Mustafa Serdar Genç

“…ABSTRACT This paper presents a novel approach to the structural design of small‐scale turbine blades using the Artificial Bee Colony (ABC) Algorithm to optimise both mass and cost (objective functions), with a comparison to experimental results obtained using a Digital Image Correlation (DIC) system. …”
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Barriers in Proliferating Digital Technologies at Russian Companies: Causes and Effects by A. S. Melnikov, E. G. Kalabina

“…As a result a systematized picture of enterprise functioning was developed in the context of overcoming barriers in introducing digital technologies and identification of situational and contextual variables influencing the effect of their introduction. …”
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Parallel Primal-Dual Method with Linearization for Structured Convex Optimization by Xiayang Zhang, Weiye Tang, Jiayue Wang, Shiyu Zhang, Kangqun Zhang

“…This paper presents the Parallel Primal-Dual (PPD3) algorithm, an innovative approach to solving optimization problems characterized by the minimization of the sum of three convex functions, including a Lipschitz continuous term. The proposed algorithm operates in a parallel framework, simultaneously updating primal and dual variables, and offers potential computational advantages. …”
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The Brain Behind the Grid: A Comprehensive Review on Advanced Control Strategies for Smart Energy Management Systems by Gowthamraj Rajendran, Reiko Raute, Cedric Caruana

“…This paper presents a systematic review of key digital technologies—such as artificial intelligence, the Internet of Things, blockchain, and digital twins—employed in AES, providing a critical assessment of their individual functionalities, interdependencies, and collective contributions to the energy sector. …”
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VARX Granger analysis: Models for neuroscience, physiology, sociology and econometrics. by Lucas C Parra, Aimar Silvan, Maximilian Nentwich, Jens Madsen, Vera E Parra, Behtash Babadi

“…We also provide methods for enhancing model efficiency, such as L2 regularization for limited data and basis functions to cope with extended delays. …”
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Optimized Blade Design of Counter-Rotating-Type Pump-Turbine Unit Operating in Pump and Turbine Modes by Jin-Woo Kim, Jun-Won Suh, Young-Seok Choi, Kyoung-Yong Lee, Toshiaki Kanemoto, Jin-Hyuk Kim

“…The pump and turbine mode efficiencies of the unit were selected as the objective functions and they combined into a single specific objective function with the weighting factors. …”
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MAGNETOHYDRODYNAMICS NANOFERRO FLUID FLOWS PASSING THROUGH A MAGNETIC POROUS SPHERE UNDER THERMAL RADIATION EFFECT by Basuki Widodo, Eirene Juwita Ningtyas Pamela, Dieky Adzkiya, Chairul Imron, Tri Rahayuningsih

“…The dimensional mathematical model is further transformed into non-dimensional mathematical model by using non-dimensional variables. The non-dimensional mathematical model is simplified using the similarity equation by utilizing the stream function. …”
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Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

“…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Based on the spectral principal components, three classifiers were built to classify the maturity level: support vector machine, backpropagation neural network, and radial basis function neural network. Excellent results with a classification accuracy of 100% were obtained. …”
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Approximation by interpolation spectral subspaces of operators with discrete spectrum by M.I. Dmytryshyn

“…Applications to spectral approximations of the regular elliptic operators with variable smooth coefficients in the space $L_q(\Omega)$ over an open bounded set $\Omega\subset\mathbb{R}^n$ and some self-adjoint ordinary elliptic differential operators in a bounded interval $\Omega=(a,b)$ are shown.…”
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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
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Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data. by Neda Aminnejad, Michelle Greiver, Huaxiong Huang

“…This research focuses on developing a predictive model to classify diabetic patients showing signs of kidney function impairment based on their CKD development risk. …”
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A Mimetic Assay of Neutrophil Extracellular Trap Degradation Using YOYO-1-Stained DNA-Histone Surface Webs by Katherine H. Nguyen, Midori L. Wasielewski, Srilakshmi Yalavarthi, Xianggui Qu, Jason S. Knight, Shuichi Takayama

“…This paper describes a simplified, lower variability mimetic assay with DNA–histone structures, referred to as surface webs, that performs functionally similarly to traditional NET degradation assays with increased scalability, ease of use, shorter preparation time, and lowered costs. …”
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Cardiometabolic risk factors in predicting obstructive coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, E. D. Emtseva, A. A. Vishnevskiy

“…The predictors of this model were 7 categorical (total cholesterol (CS) ≥5,9 mmol/L, low-density lipoprotein cholesterol >3,5 mmol/L, waist-to-hip ratio ≥0,9, waist-to-height ratio ≥0,69, atherogenic index ≥3,4, lipid accumulation product index ≥38,5 cm*mmol/L, uric acid ≥356 pmol/L) and 2 continuous (high density lipoprotein cholesterol and insulin resistance index) variables.Conclusion. The developed algorithm for selecting predictors made it possible to determine their significant predictive threshold values and weighting coefficients characterizing the degree of influence on endpoints. …”
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Family Resilience and Its Influencing Factors Among Patients With Lung Cancer Based on Double ABC‐X Theoretical Framework by Ziyi Shen, Yan Fang, Chengcheng Li, Xin Luo, Junling Cui, Yanchang Liu, Jingfang Hong

“…Relationships between variables and pathways were also explored based on the Double ABC‐X as the theoretical framework. …”
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Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms by Nicolás Faedo, Giordano Scarciotti, Alessandro Astolfi, John V. Ringwood

“…The authors develop a framework under which the objective function (and system variables) can be mapped to a finite‐dimensional tractable quadratic program (QP), which can be efficiently solved using state‐of‐the‐art solvers. …”
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