An Adiabatic-Expansion-Induced Perturbation Study on Gas–Aerosol Partitioning in Ambient Air—Formation of NH₄NO₃ and Microdroplet Nitrogen Fixation (2) by Yating Gao, Qinchu Fan, Yujiao Zhu, Hengqing Shen, Qi Yuan, Yang Gao, Huiwang Gao, Xiaohong Yao

“…Our results indicate the adiabatic-expansion-induced generation of NH₃ + HNO₃ at ultrafast formation rates, with campaign-dependent stable stoichiometric ratios of HNO₃ to NH₃, as well as highly variable occurrence frequencies and efficiencies. These findings suggest that microdroplet redox reactions are more likely responsible for the generation of NH₃ + HNO₃ than conventional atmospheric NH₃ chemistry. …”
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The Design and Analysis of a Lightweight Robotic Arm Based on a Load-Adaptive Hoisting Mechanism by Ruchao Wang, Zhiguo Lu, Yiru Wang, Zhongqing Li

“…The proposed design integrates a spring-loaded rope and a variable radius reel into the gripper, enabling efficient load adaptability with minimal structural complexity. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…In the end, using an attention function, Vision Transformer-based models classify vehicles seen from above. …”
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Integration of indigenous and formal knowledge in the assessment of soil quality performance assessment using multiple factor analysis in Alborz central mountains by Niloufar Izadi, Fateme Aghamir

“…The current study uses Multiple Factor Analysis (MFA) to propose efficiency indicators based on the weighting of familiar, organizational, or productive variables in groups evaluating indigenous, scientific, and data variability. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The Lasso function is used for elastic net regression analysis to evaluate the impact of design variables on the objective functions. …”
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Elastostatic analysis of tapered FGM beams with spatially varying material properties by Justín Murín, Stephan Kugler, Juraj Paulech, Juraj Hrabovský, Vladimír Kutiš, Herbert Mang, Mehdi Aminbaghai

“…In this article an effective method for elastostatic analysis of tapered beams made of functionally-graded material (FGM) is presented. The spatially variable stiffness of the beam is the consequence of the continuous longitudinal variability of the cross-sectional dimension, accompanied by the variability of the material properties in three orthogonal directions. …”
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Quantitative comparison between single-photon emission computed tomography and positron emission tomography imaging of lung ventilation with 99mTc-technegas and 68Ga-gallgas in pat... by Enrique Gustavo Cuna, Juan Pablo Gambini, Liliana Servente, Eduardo Savio, Henry William Engler, Gabriel Adrián González, Omar Alonso

“…The aim of this study was quantitative comparison between 68Ga-Gallgas positron emission tomography (PET) and 99mTc-Technegas single photon emission computed tomography (SPECT) for lung ventilation function assessment in patients with moderate-to-severe obstructive pulmonary disease and to identify image-derived texture features correlating to the physiologic parameters. …”
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FORMAL REPRESENTATION OF THE PIXEL-BY-PIXEL CLASSIFICATION PROCESS USING A MODIFIED WANG-MENDEL NEURAL NETWORK by Oleksii Kolomiitsev, Volodymyr Pustovarov

“…The following results were obtained: the use of a fuzzy Wang-Mendel neural network as a classifier of a modified U-Net decoder based on the representation of membership functions in IFST2 and the implementation of phasing, aggregation and activation operations using operations on IFST2; introduction of an additional operation of type reduction in the phase of dephasification of the original variable based on the classical method of the center of gravity (centroid); introduction of several outputs of the network to recognize the appropriate number of classes (subclasses) of the subject area. …”
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A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems by Harun Gezici

“…It is deprived of a stochastic variable and is not able to generate an applicable balance between exploration and exploitation. …”
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Establishment of an evaluation system for conversion to laparotomy in laparoscopic cholecystectomy and exploration of surgical grading management by ZHANG Nannan, GUO Jinxing, WU Gang, YI Hui, ZHOU Yuanhang, LIAO Zhiwei, HUANG Qi, DONG Jian

“…Then, the risk factors were analyzed by multiple Logistic regression, and the pre-coefficient of each variable of the risk factors was assigned according to the established conversion to laparotomy possibility function. …”
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Revisiting the Group Classification of the General Nonlinear Heat Equation <i>u_t</i> = (<i>K</i>(<i>u</i>)<i>u_x</i>)<i>_x</i> by Winter Sinkala

“…In this paper, we revisit the group classification of the general nonlinear heat (or diffusion) equation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>u</mi><mi>t</mi></msub><mo>=</mo><msub><mfenced separators="" open="(" close=")"><mi>K</mi><mrow><mo>(</mo><mi>u</mi><mo>)</mo></mrow><mspace width="0.166667em"></mspace><msub><mi>u</mi><mi>x</mi></msub></mfenced><mi>x</mi></msub><mo>,</mo></mrow></semantics></math></inline-formula> where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula> is a non-constant function of the dependent variable. We present the group classification framework, derive the determining equations for the coefficients of the infinitesimal generators of the admitted symmetry groups, and systematically solve for admissible forms of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula>. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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Designing a supply chain resilience assessment model with the approach of NDEA(case of study: government hospitals of Yazd province) by Mohsen Shafiei Nikabadi, Fereshteh Bahrami

“…Therefore, in order to maintain the basic functions and quickly return the hospital to its original state, the resilience of the hospital is important (Mohammed Hosseini Issini, 2019), which calls attention to the necessity of availability and efficiency of hospitals. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Variation in Likert scale of the mathematics usefulness test by Facundo Juan Pablo Abal, Sofía Esmeralda Auné, Horacio Félix Attorresi

“…Likert scales with more categories increased test reliability at the extreme levels of the trait, but at the expense of compromising the internal structure validity evidences (Confirmatory Factor Analysis and Partial Credit Model of the Item Response Theory). The relative efficiency function revealed that similar information is obtained for all levels of the trait when using 5 or 6-point scales. …”
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Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

“…SCR model estimates of abundance, the density-covariate coefficient β and the movement-related scale parameter of the detection function σ were robust to ignoring temporal variation in detection, with relative bias, CV and RMSE of the two models generally being within 4% of each other. …”
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Reference Intervals for Echocardiography Parameters of Children Living in the Arkhangelsk Region and a Digital Application for Their Assessment by Aleksey A Karyakin, Igor’ S. Chub, Ol’ga E. Karyakina, Andrey M. Grjibovski, Aleksey V. Artemov, Ul’yana R. Zakharchenko

“…Reference intervals of echocardiography parameters were determined using body surface area as the dependent variable. The values were automatically calculated in our digital application that allows one to increase the accuracy and efficiency of interpretation of cardiac ultrasound parameters. …”
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Effect of settling time, velocity gradient, and camp number on turbidity removal for oilfield produced water by Thamer J. Mohammed, Eman Shakir

“…The experimental results of this study are used to develop an empirical correlation for turbidity removal efficiency as a function of multi variables poly-aluminum chloride dosage; polyelectrolyte dosage; and Ferric chloride dosage. …”
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Gut health modulation through phytogenics in poultry: mechanisms, benefits, and applications by Aderanti Ifeoluwa Oni, Oyegunle Emmanuel Oke

“…These plant-derived compounds, such as polyphenols, alkaloids, flavonoids, and essential oils exhibit various bioactive properties that improve gut microbiota composition, support immune function, and improve nutrient absorption by influencing gut morphology and digestive enzyme activity. …”
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