Analysis of Hydrological and Meteorological Conditions in the Southern Baltic Sea for the Purpose of Using LNG as Bunkering Fuel by Ewelina Orysiak, Jakub Figas, Maciej Prygiel, Maksymilian Ziółek, Bartosz Ryłko

“…The southern Baltic Sea is characterized by highly variable weather conditions, particularly in autumn and winter, when storms, strong westerly winds, and temporary sea ice formation disrupt maritime operations. …”
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Smart technique for calculating fault current model parameters using short circuit current measurements by R. A. Mahmoud, O. P. Malik, W. M. Fayek

“…The difference concept can be utilized to obtain precise mathematical formulas for evaluating the parameters of the fault current model. This is for efficient implementation of multiple functions that include digital protective relay, fault locator, digital filter, CT saturation detector and compensator. …”
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A toolkit for facilitating markerless integration of expression cassettes in Komagataella phaffii via CRISPR/Cas9 by Laura García-Calvo, Charlotte Kummen, Solvor Rustad, Sissel Beate Rønning, Annette Fagerlund

“…Abstract Background The yeast Komagataella phaffii (formerly known as Pichia pastoris) has been widely used for functional expression of recombinant proteins, including plant and animal food proteins. …”
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Machine learning projection of climate and technology impacts on crops key to food security by Dan Li, Vassili Kitsios, David Newth, Terence John O’Kane

“…Our model is designed to capture the relationships between technology, climate variables and the annual growth rate in crop yield across the world’s producing regions. …”
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On the Modular Design Application for the Gas Turbine Sector: A Performance Optimization Approach in the Context of Industry 4.0 by Lucas Chavanel-Precloux, Roland Maranzana, Lucas A. Hof

“…Indeed, this study presents the functioning of the novel application, the different deployed components and their variables, such as the compressor efficiency, heat exchangers, or turbine stages, and the decision variable, e.g., the costs of generated energy. …”
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Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…Coefficient of determination (R2), mean absolute error (MAE), and mean relative error (MRE) were used as error indicators to evaluate the potential of the six machine learning algorithms for predicting NDVI changes. …”
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An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning by Wenyuan Cong, Hao Yi, Feifan Yu, Jiajie Chen, Xinmin Chen, Fengrui Xu

“…Subsequently, a path planning objective function was constructed based on trajectory cost and threat cost to simulate a 3D space for UAV maritime rescue missions, and the IPKO algorithm was applied to address the UAV path planning problem. …”
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U-rich elements drive pervasive cryptic splicing in 3’ UTR massively parallel reporter assays by Khoa Dao, Courtney F. Jungers, Sergej Djuranovic, Anthony M. Mustoe

“…Splicing is activated by U-rich sequences, which function as potent position-dependent regulators of 5’ and 3’ splice site choice and overall splicing efficiency. …”
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Multi-camera association tracking algorithm for pedestrian target based on difference image by Shuai Ren

“…The pedestrian target obeys the Laplacian random variable probability density function, and moves according to the center position of the bounding box to ensure that the target tends to move around the starting position, and realizes the multi-camera association tracking. …”
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Estimation of Above-Ground Biomass for <italic>Dendrocalamus Giganteus</italic> Utilizing Spaceborne LiDAR GEDI Data by Huanfen Yang, Zhen Qin, Qingtai Shu, Li Xu, Jinge Yu, Shaolong Luo, Zaikun Wu, Cuifen Xia, Zhengdao Yang

“…The outcomes reveal that 1) the results showed that the power function emerged as the most efficacious model, with coefficient of determination (<italic>R</italic>²) &#x003D; 0.87 and root mean square error (RMSE) &#x003D; 0.00051 Mg, in estimating the AGB of <italic>Dendrocalamus giganteus</italic>. 2) Based on the feature importance ranking of Random Forest, five variables were selected from the 40 extracted from GEDI, achieving RMSE &#x003D; 8.21 Mg&#x002F;ha and mean absolute error (MAE) &#x003D; 6.12 Mg&#x002F;ha. …”
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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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Preoperative Anteroposterior and Lateral Assessment of Sagittal Spinopelvic Parameters Show High Positional Correlation and Measurement Reliability Preceding Both Hip Preservation... by Benjamin D. Kuhns, M.D., M.S., Tyler R. McCarroll, M.D., Roger Quesada-Jimenez, M.D., Ady H. Kahana-Rojkind, M.D., Drashti Sikligar, M.Eng., Meredith F. Cohen, B.A., Benjamin G. Domb, M.D.

“…Interobserver reliability for each measure was evaluated through the intraclass correlation coefficient (ICC). Bivariate linear correlations between AP and lateral standing, supine, and sitting images were obtained. …”
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Early Predictive Value of the Glucose‐to‐Lymphocyte Ratio for the Occurrence of Stroke‐Associated Pneumonia by Fuqiang Zhou, Liju Ma, Min Li, Haijiang Li, Heying Yang, Ye Xu, Kuankuan Dang, Fengchen Gao, Haimei Sun

“…The GLR was converted into a categorical variable for trend testing, and compared the predictive efficiency of GLR through the receiver operating characteristic (ROC) curve and Bonferroni correction analysis. …”
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A 3D mixed frame element with multi-axial coupling for thin-walled structures with damage by D. Addessi, P. Di Re

“…The beam formulation is derived on the basis of the Hu-Washizu variational principle, expressed as function of four independent fields: the standard displacements, strains and stresses and the additional warping displacement. …”
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Pedestrian detection method based on improved YOLOv5 by Shangtao You, Zhenchao Gu, Kai Zhu

“…We optimize the regression prediction of the anchor using the Efficient IOU Loss (EIOU) function. Experimental data show that the mean average precision (mAP) of the HOD-YOLOv5 model achieves 83.5%, compared to YOLOv5, which is 4.4% higher than original YOLOv5, and the recognition speed of the HOD-YOLOV5 reaches 106.7 frames per second (FPS). …”
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Cross-sectional associations between physical activity and sedentary time with cardiovascular health in children from the ALSPAC study using compositional data analysis by K. M. Sansum, B. Bond, R. M. Pulsford, A. McManus, A. O. Agbaje, A. M. Skinner, A. R. Barker

“…Cardiovascular outcomes included flow mediated dilation, distensibility coefficient, pulse wave velocity and a clustered CVD risk factor score. …”
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Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder by Muzher Saleem, Ghada A. Khouqeer, Fazal Haq, Naglaa AbdelAll, Arshad Hussain, Mohammed Sallah

“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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Evaluating the Effectiveness of Quality Control Measures in Project Management: A Study of Construction Companies in Lusaka by Mwanza Jacob, Chimbomba Kelvin

“…A solid positive relationship appeared between how well technology supports quality control and general quality control practices (Pearson coefficient = 0.893). Quality control measures improve the efficiency of construction projects, but they should be further improved as many projects still get delayed as a result of quality issues. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…Dehui City in Jilin Province, China, was selected as the case study area, where multidimensional data including vegetation indices, ecological function parameters, and environmental variables were collected, covering seven key growth stages of rice. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…The fused dataset demonstrates significant improvements over the original MERRA-2 AOD, with an increase in the coefficient of determination (R²) by 0.1065 and a reduction in root mean square error (RMSE) by 0.0369. …”
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