Medical assistance as a decision-taking process. Pedagogical implications for the formation of the treatment hability by Luis Alberto Corona Martínez

“…In a general way, the exhibition of the elements is guided to the recognition of the taking of decisions, like an implicit feature in the way of the doctor's professional performance, in her/his curative assistance function, that which has important implications in the formation of the treatment ability.…”
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Liryka konwersacyjna w funkcji narratywu – ideologem by Dimitar Pandev

“… CONVERSATIONAL LYRICYSM AS A NARRATIVE FUNCTION – IDEOLOGEME The conversational lyric (an expression that we take from the Makjej Kavka’s study on the poetry of Aco Shopov and adapt it to poetry with an emphasized communicative function) opens new multimedia forms of public performance in front of a wide auditorium with a clearly emphasized contact (phatic), but also has a propaganda function, most often for political purposes. …”
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Accelerated Sarcopenia Phenotype in the DJ-1/<i>Park7</i>-Knockout Zebrafish by Kristine O. Rostad, Tobias Trognitz, Ann Kristin Frøyset, Ersilia Bifulco, Kari E. Fladmark

“…A total of 68 proteins, mainly associated with inflammation and mitochondrial function, were dysregulated in the young DJ-1-null adults, with Annexin A3, Sphingomyelin phosphodiesterase acid-like 3B, Complement C3a, and 2,4-dienoyl CoA reductase 1 being the most affected. …”
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Modulation of Hippocampal Neural Plasticity by Glucose-Related Signaling by Marco Mainardi, Salvatore Fusco, Claudio Grassi

“…In this regard, increasing evidence shows that molecules such as insulin, insulin-like growth factor-I, glucagon-like peptide-1, and ghrelin impact on the function of the hippocampus, which is a key area for learning and memory. …”
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CNTFET-Based Design of a High-Efficient Full Adder Using XOR Logic by Seyedehsomayeh Hatefinasab

“…This proposed full adder is based on a XOR logic function using 32 nm CNTFET technology. The MOSFET-like CNTFET is applied in this paper to use CMOS (Complementary Metal Oxide Semiconductor) logic gate. …”
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COVID-19 detection using federated machine learning. by Mustafa Abdul Salam, Sanaa Taha, Mohamed Ramadan

“…During the model training stage, we tried to identify which factors affect model prediction accuracy and loss like activation function, model optimizer, learning rate, number of rounds, and data Size, we kept recording and plotting the model loss and prediction accuracy per each training round, to identify which factors affect the model performance, and we found that softmax activation function and SGD optimizer give better prediction accuracy and loss, changing the number of rounds and learning rate has slightly effect on model prediction accuracy and prediction loss but increasing the data size did not have any effect on model prediction accuracy and prediction loss. finally, we build a comparison between the proposed models' loss, accuracy, and performance speed, the results demonstrate that the federated machine learning model has a better prediction accuracy and loss but higher performance time than the traditional machine learning model.…”
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A thermodynamic inspired AI based search algorithm for solving ordinary differential equations by V. Murugesh, M. Priyadharshini, T. R. Mahesh, Esmael Adem Esleman

“…Abstract Solving Ordinary Differential Equations (ODEs) is an essential and very challenging computational problem in many areas of science and engineering like physics, biology, control system, and economics. …”
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Distortion-Tolerant 3-Dimensional Object Recognition Using Hybrid Joint Transform Correlator by Jyoti Bikash Mohapatra, Ram Kumar, Naveen K. Nishchal

“…The method has been tested with standard performance measuring parameters like correlation peak intensity and signal-to-noise ratio.…”
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Stabilization of a Class of Fractional-Order Nonlinear Systems Subject to Actuator Saturation and Time Delay by Esmat Sadat Alaviyan Shahri, Naser Pariz, Yangquan Chen

“…Two primary methodologies are employed: the vector Lyapunov function method, integrated with the <i>M</i>-matrix approach, and the second one is the Lyapunov-like function method, which incorporates diffusive realization and the Lipchitz condition. …”
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Excitation-Dependent Fluorescence Quantum Yield for Freshwater Chromophoric Dissolved Organic Matter from Northern Russian Lakes by Svetlana Patsaeva, Daria Khundzhua, Oleg A. Trubetskoj, Olga E. Trubetskaya

“…This technique revealed “hidden” protein-like fluorophores for some CDOM fractions, in spite of the absence of protein-like fluorescence in the initial CDOM samples. …”
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An Adaptive Neural Network Fuzzy Sliding Mode Controller for Tracking Control of Deep-Sea Mining Vehicles by Shidong Wang, Zida Shan, Jialuan Xiao, Junjun Cao, He Zhang, Nan Sun

“…The algorithm, named the Adaptive Radial Basis Function Neural Network Fuzzy Sliding Mode Controller (ARFSMC), replaces modeled vehicle dynamics with a radial basis function neural network (RBFNN). …”
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Robust Smooth Sliding-Mode-Based Controller with Fixed-Time Convergence for Missiles considering Aerodynamic Uncertainty by Yuhang Yun, Jie Guo, Shengjing Tang

“…Unlike previous terminal sliding mode approaches, not only is the bound of settling time independent of initial state, indicating that performance metrics like convergence rate can be predicted beforehand, but the control input is designed to be smooth based on adaptive estimations and some mathematical results without introducing any discontinuous items like the signum function, which avoids the problem of chattering consequently. …”
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A Queueing Model for an Automatic Manufacturing System with Disasters, Breakdowns and Vacations. Optimal Design and Analysis by Nada Riheb Yatim, Amina Angelika Bouchentouf, Pikkala Vijaya Laxmi

“…We use matrix methods to find the system's steady state along with performance measures like the expected number of customers lost, the expected waiting time, and system reliability. …”
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Research on a Target Detection Algorithm for Common Pests Based on an Improved YOLOv7-Tiny Model by He Gong, Xiaodan Ma, Ying Guo

“…Additionally, compared to algorithms like Faster R-CNN, SSD, and RetinaNet, the improved model delivers superior detection performance. …”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…Understanding and forecasting energy consumption patterns is crucial for improving energy efficiency and human well-being, especially in diverse infrastructures like Spain. This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. …”
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Gut metagenomic features of frailty by Zharkyn Jarmukhanov, Nurislam Mukhanbetzhanov, Elizaveta Vinogradova, Samat Kozhakhmetov, Almagul Kushugulova

“…Frailty was significantly correlated with age, weight, and functional measures like walking speed and grip strength. …”
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A Computational Offloading Method for Edge Server Computing and Resource Allocation Management by Muna Al-Razgan, Taha Alfakih, Mohammad Mehedi Hassan

“…The HVV is a mapping function based on the features of the edge server like the workload and performance. …”
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A Novel Multiobjective Control of DVR to Enhance Power Quality of Sensitive Load by Sathish Babu Pandu, Kamaraj Nagappan

“…A novel multiobjective function is formulated to express the control performance of the system, which is quantified using three power quality indices such as Total Harmonic Distortion (THD), voltage sag index, and RMS voltage variation. …”
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A CNN-Based Approach for Classical Music Recognition and Style Emotion Classification by Yawen Shi

“…Meanwhile, in this study, a novel loss function has been devised to more effectively assess the model&#x2019;s performance. …”
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Navigating Data Corruption in Machine Learning: Balancing Quality, Quantity, and Imputation Strategies by Qi Liu, Wanjing Ma

“…The results indicate that performance degradation follows a diminishing-return pattern, well modeled by an exponential function. …”
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