Effects of Temperature and <i>Bacillus velezensis</i> on the Development, Longevity, and Reproduction of <i>Culex quinquefasciatus</i> by Abdullah A. Alomar

“…Temperature is a key environmental factor that influences mosquito phenotypic traits and the effectiveness of vector control strategies. <i>Bacillus velezensis</i> (<i>Bv</i>) has shown promise as a microbial biocontrol agent due to its insecticidal properties; however, its effects on mosquitoes under different environmental conditions are still unexplored. …”
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Using text embeddings for deductive qualitative research at scale in physics education by Tor Ole B. Odden, Halvor Tyseng, Jonas Timmann Mjaaland, Markus Fleten Kreutzer, Anders Malthe-Sørenssen

“…Using a natural language processing technique known as text embeddings, we create vector-based representations of texts in a high-dimensional meaning space within which it is possible to quantify differences in meaning as vector distances. …”
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Firefly Algorithm based Feature Selection for Arabic Text Classification by Souad Larabi Marie-Sainte, Nada Alalyani

“…Keywords: Arabic Natural Language Processing, Feature Selection, Firefly optimization method, Text Classification…”
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Tensor Calculus in Digital Colorimetry by Y. N. Saukova, M. A. Hundzina

“…From the point of view of measurement, a digital image can be represented by a combinatorial model of an information and measurement channel with the appearance of the phenomenon of a color covariance hypercube requiring a significant amount of memory for data storage and processing. The transition from the covariance hypercube to high-dimensional matrices and tensors of the first, second and higher ranks provides the prospect of optimizing the color parameters of a digital image by the criterion of information entropy.Tensor calculus provides opportunities for expanding the dynamic range in color measurements describing multidimensional vector fields and quantized spaces with indexing tensors and decomposing them into matrices of low orders.The proposed complex approach based on tensor calculus. …”
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Spectral Feature Extraction Using Partial and General Method by Bin Jiang, Xi Fang, Yang Liu, Xingzhu Wang, Jie Liu

“…With the rapid growth in astronomical spectra produced by large sky survey telescopes, traditional manual classification processes can no longer fulfill the requirements of precision and efficiency of spectral classification. …”
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Leveraging machine learning and open accessed remote sensing data for precise rainfall forecasting by Bambang Kun Cahyono, Muhammad Hidayatul Ummah, Ruli Andaru, Neil Andika, Adjie Pamungkas, Hepi Hapsari Handayani, Paramita Atmodiwirjo, Rory Nathan

“…Machine learning methods, including Support Vector Regression, Gradient Boosting Regression, Random Forest, and Deep Neural Networks, were applied. …”
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Automatic Extraction Method of Phenotypic Parameters for <i>Phoebe zhennan</i> Seedlings Based on 3D Point Cloud by Yang Zhou, Yikai Qi, Longbin Xiang

“…The stem point cloud was extracted from the model using the median normalized growth vector-based search (MNVG) method, with the current growth vector refined based on previous growth points and vectors. …”
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Synthesis and properties of 3-(ethylthio)-9-methyl-6-(alkylthio)pyrazolo[1,5-d][1,2,4]triazolo[3,4-f][1,2,4]triazines by S. O. Fedotov, A. S. Hotsulia

“…Various factors contribute to this process. Among them, we can note the significant possibilities of chemical transformation involving these cycles, the simplicity, and reliability of methods, the creation of molecules with a certain level of bioavailability and the ability to influence a number of biochemical processes. …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Through a multistep selection process, a refined subset of 15 optimal radiomic features was identified for model training. …”
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SELF-EDUCATION AS A PEDAGOGICAL PROBLEM by Oleksandr L. Shums’kyi, Ol’ha O. Shums’ka

“…It has been shown that the state regulations and international documents on education define lifelong learning as the main vector of educational development in the 21st century. …”
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Experimental evaluation of polymer construction materials: effects of acrylic resin and a fiberglass-based composite upon cytokine production by A. P. Godovalov, A. B. Astashina, A. A. Bazhin, T. A. Drokina

“…It makes sense to evaluate probable hazards of inflammatory process which could be activated when using structural polymer materials and composites in dental practice. …”
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THE "LARGE BARYON PUMP OF THE EARTH" AS A NATURAL IMAGE OF THE "TREE OF LIFE" AND AN OBJECT OF ENVIRONMENTAL LAW, WHICH IS INTEGRATED WITH THE NATURAL ENVIRONMENT OF MAN by Mykhaylo O. Baymuratov, Volodymyr P. Ozhereliev

“…Currently, the world structure that has emerged can be imagined as a complex global-regional legal system, in the regulatory field of which there is a process of deep integration of international public law and municipal law. …”
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Mechanism Analysis of an Abrupt Torrential Rain Event under Weak Synoptic Forcing by Mingjuan LI, Damei GUO, Dian FENG, Kuifeng ZHAO, Jiahuimin LIU, Liwei QU

“…On July 18， 2021， abrupt rainstorms， torrential rain and local torrential rain occurred in areas of northeastern Xi'an and southern Weinan.The global numerical model and multiple Meso-scale numerical models failed to predict this torrential rain process.Based on data of aerological sounding， surface observation， ERA5 reanalysis， TBB data of FY-2G satellite， lidar wind vector data of Lintong station， radar data of Jinghe station， and microwave radiometer data， circulation patterns， environmental conditions and Meso-scale convective system evolution are investigated in this paper to enhance the understanding of mechanisms of this type of torrential rain and improve its predicting accuracy.Results show that the abrupt torrential rain process occurred under the forcing of a weak synoptic system， on the edge of the continental high at 500 hPa.There were no shear lines， warm advections and high-speed wind transporting water vapor at 700 hPa and 850 hPa， and neither cold front nor warm front on surface.Before the torrential rain process， on environmental fields， vertical wind shear was weak from 0 to 6 km on T-lnP chart， and 0 ℃-level was high， which was conducive to formation of deep warm clouds.A light rain appeared on surface， increasing atmospheric humidity near ground and lowering atmospheric lifting condensation level and lower cloud base， which was favorable for developing Meso-scale convective systems and improving precipitating efficiency.On radar wind profile map and wind lidar map， the low-level easterly wind was increased to 6~10 m·s-1， transferring abundant water vapor and energy to the rainstorm area， giving the atmosphere a certain amount of convective available potential energy（CAPE）.Satellite image， ERA5 reanalysis data and microwave radiometer data show a weak ascent was found in the middle and low levels which produced a deep wet layer and a large value of total atmospheric precipitable water.TBB data indicates that quasi-stationary isolated Meso-β-scale convective systems caused the abrupt torrential rain.On radar composite reflectivity factor map， the heavy rainfall was induced by a Meso-γ-scale and Meso-β-scale convective cell or a Meso-β-scale convective system.The Meso-γ-scale convective cell developed near Lishan Mountain with loose structure and organization.The maximum center of reflectivity factor demonstrates a consistently vertical structure from top to bottom with a low centroid， showing characteristics of highly efficient warm cloud precipitation.The abrupt torrential rain was caused by convections triggered by interaction of the ground convergence line induced by weak cold air on surface， topographic uplift of the Lishan Mountain and funneling effect of Bahe Valley collectively.The initial heavy rainfall formed a cold pool， then， the outflow of the cold pool generated new convergence lines around， triggering new convective systems.The Meso-β-scale convective system on the northeast side of the Jinghe River propagated backwards and moved slowly southwestwards.In the Meso-β-scale convective system， multiple new Meso-γ-scale convective cells developed and created a “train effect” over Jinghe River， resulting in this torrential rain process.For prediction under the forcing of weak synoptic systems， it is necessary to strengthen the understanding of its formation mechanism and the use of new observation data， pay close attention to the influence of early weak precipitation on near-surface humidification and lifting condensation level， water vapor and unstable energy transport to rainstorm areas by increased low-level wind， and the triggering effect of weak cold air on the ground and terrain， combined with maximum values predicted by a number of Meso-scale numerical models， comprehensively consider the possibility of abrupt torrential rain.…”
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Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images by Mahsa Raisi-Nafchi, Mahnoosh Tajmirriahi, Hossein Rabbani, Zahra Amini

“…The method is implemented in both 1D and 2D processing modes, with customized preprocessing for each. …”
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Terahertz‐Wave Polarization Space‐Division Multiplexing Meta‐Devices based on Spin‐Decoupled Phase Control by Yuehong Xu, Yuma Takida, Tetsu Suzuki, Hiroaki Minamide

“…Additionally, the advanced meta‐devices M‐2B and M‐4B are designed to generate two‐vector and four‐vector Bessel beams with tunable spatial polarization distributions. …”
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Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

“…Hyperspectral monitoring models for winter wheat ChD were constructed using 8 machine learning algorithms, including partial least squares regression, support vector regression, multi-layer perceptron regression, random forest regression, extra-trees regression (ETsR), decision tree regression, K-nearest neighbors regression, and gaussian process regression, based on the full spectrum band and the band selected by competitive adaptive reweighted sampling (CARS). …”
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Integrating LiDAR Point Cloud Classification and Building Footprints for Enhanced 3D LOD Building Modeling: A Deep Learning Approach by L. Lakshmanan, S. Nagarajan

“…Once the building points are classified and improvised with Building Footprint vector layer, they are utilized to reconstruct detailed 3D geometric models. …”
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MIMD Programs Execution Support on SIMD Machines: A Holistic Survey by Dheya Mustafa, Ruba Alkhasawneh, Fadi Obeidat, Ahmed S. Shatnawi

“…The SIMD model is used in traditional CPUs, dedicated vector systems, and accelerators such as GPUs, vector extensions, and Xeon Phi. …”
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Approximate power flow solutions‐based forecasting‐aided state estimation for power distribution networks by Zhenyu Wang, Zhao Xu, Donglian Qi, Yunfeng Yan, Jianliang Zhang

“…Abstract This paper presents an approximate power flow model‐based forecasting‐aided state estimation estimator for power distribution networks subject to naive forecasting methods and nonlinear filtering processes. To this end, this estimator designs a voltage perturbation vector around the priori‐determined nominal value as the dynamic state variable, which enables more detailed depictions of voltage changes. …”
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INVARIANTS OF GENERALIZED RAPOPORT-LEAS EQUATIONS by E. N. Kushner

“…Therefore, following the approach of Sophus Lie, we restrict ourselves to the search for infinitesimal transformations which are generated by translations along the trajectories of vector fields. The problem of finding these vector fields reduces to the redefined system decision of linear differential equations with respect to their coefficients. …”
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