Thermal Conductivity Performance of Silica Aerogel after Exposition on Different Heating under Ambient Pressure by Israa F. Al-sharuee

“…The varied thermal conductivity (insulation) of silica aerogel with heating for different pH has been investigated, it has been depended on ambient pressure drying method in the preparing silica aerogel samples, also six different pH of samples (1, 2, 3, 7, 8 and 9) were treated under five degree of heating with (50,100,150,200 and 250) ᴼC. …”
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A Crystallization-Induced Asymmetric Transformation using Racemic Phenyl Alanine Methyl Ester Derivatives as Versatile Precursors to Prepare Amino Acids by Samira Rahmani-Nezhad, Shima Dianat, Abbas Hadjiakhoondi

“…For some substrates such as amino acids, resolution by the formation of diastereomers offers an attractive alternative. Among different methods in this case, crystallization-induced asymmetric transformation (CIAT) that is in situ racemization and selective crystallization of a reaction product can be a good choice. …”
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CdZnTe- and TlBr-detectors response simulation for registration of the mixed beta- and gamma-radiation by A. I. Skrypnyk

“…Firstly, DFT properties are accurate, have their own specificity and significantly differ from the properties of the Fourier transform of continuous signals. …”
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Construction of several plant expression vectors using multiple cell wall degrading enzyme genes from Trichoderma harzianum and rice transformation by LIU Mei, SUN Zong-xiu, XU Tong

“…Three kinds of methods was used to solve different problems in the process of vector construction: (1) Restriction solution was used directly to ligation reaction for recovered DNA fragment usually influenced ligation frequency; (2) Using one cohensive end and one blunted end to carry out the ligation reaction was more effective than two blunted ends when restriction ends must be modified; (3) Choosing appro-priate mediated plasmid to introduce new restriction sites around certain DNA fragment and avoid linear ends modification. …”
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3D medical image segmentation using the serial–parallel convolutional neural network and transformer based on cross‐window self‐attention by Bin Yu, Quan Zhou, Li Yuan, Huageng Liang, Pavel Shcherbakov, Xuming Zhang

“…The core components of the proposed method include the cross window self‐attention based transformer (CWST) and multi‐scale local enhanced (MLE) modules. …”
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Trajectoires d’adaptation face au changement climatique : analyse et transformation du système de gouvernance du massif ardennais by Jon Marco Church

“…In this article, we are particularly interested in the Ardennes governance system. We first use transformational sustainability research methods through a methodological framework that combines different methods. …”
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Evaluating Cognitive Function and Brain Activity Patterns via Blood Oxygen Level-Dependent Transformer in N-Back Working Memory Tasks by Zhenming Zhang, Yaojing Chen, Aidong Men, Zhuqing Jiang

“…This study aimed to evaluate brain activation patterns by analyzing functional magnetic resonance imaging (fMRI) time-series data collected during a designed N-back working memory task with varying cognitive demands. (2) Methods: We utilized a novel transformer model, blood oxygen level-dependent transformer (BolT), to extract the activation level features of brain regions in the cognitive process, thereby obtaining the influence weights of regions of interest (ROIs) on the corresponding tasks. (3) Results: Compared with previous studies, our work reached similar conclusions in major brain region performance and provides a more precise analysis for identifying brain activation patterns. …”
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Thermal dynamics of nanofluids with aggregating nanoparticles and magnetic heating: Utilization of Maxwell-Bruggeman and Kreiger-Dougherty models by Muhammad Idrees Afridi, Abdullah Alhushaybari, Ali J. Chamkha

“…Furthermore, it is found that as the values of the transformed stream-wise coordinate, Hartman number and temperature difference parameter grew, Bejan's number profile diminished.…”
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Enhancement of Thermal Stability of Ultra-high Temperature-Sterilized Yak Milk by Different Pretreatment Techniques by CAO Hongyu, ZHAO Xiaoxuan, WANG Yunna, XIE Ning, LI Xu, PANG Xiaoyang, LÜ Jiaping, YU Jinghua, LI Hongjuan, ZHANG Shuwen

“…The enhancing effects of different pre-treatment techniques (addition of emulsifying salts, electrodialysis, and resin adsorption) on the stability of ultra-high temperature (UHT)-sterilized yak milk with standardized protein content was investigated by measurement of ethanol stability, protein precipitation rate, whey protein denaturation rate and turbidity stability index (TSI) as well as by using Fourier transform infrared spectroscopy (FTIR) and inductively coupled plasma mass spectrometry (ICP-MS). …”
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Kombinasi Intent Classification dan Named Entity Recognition pada Data Berbahasa Indonesia dengan Metode Dual Intent and Entity Transformer by Zahra Asma Annisa, Rizal Setya Perdana, Putra Pandu Adikara

“…One application of artificial intelligence for service excellence is the use of a chatbot, which requires an appropriate method for the classification of user intent and Named Entity Recognition (NER). …”
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Coupling relationship between land use transition and rural transformation development: A case study of county-level regions in Jiangsu Province by GE Dazhuan, WANG Rumin, LU Xiaoxue

“…[Objective] The coupling level between land use transition and rural transformation development shows obvious gradient differentiation characteristics at different stages of socio-economic development or in different regions, and clarifying the coupling relationship between the two systems creates conditions for promoting sustainable rural revitalization. …”
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IDEAS FOR TRANSFORMING THE STATE STRUCTURE OF THE RUSSIAN EMPIRE DURING THE REIGN OF ALEXANDER I (DEDICATED TO THE 200TH ANNIVERSARY OF THE DECEMBRIST REVOLT OF 1825) by PETROV Alexander Vasilievich

“…Methods: theoretical (dialectical logic), empirical (comparisons, descriptions), specific scientific (historical-legal). …”
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Expression and Characterization of Alkaline Phosphatase from <i>Cobetia amphilecti</i> KMM 296 in Transiently Transformed Tobacco Leaves and Transgenic Calli by Peter Adeolu Adedibu, Yulia Aleksandrovna Noskova, Yulia Anatolievna Yugay, Daria Mikhailovna Ovsiannikova, Elena Anatolievna Vasyutkina, Olesya Dmitrievna Kudinova, Valeria Petrovna Grigorchuk, Yury Nikolaevich Shkryl, Liudmila Aleksandrovna Tekutyeva, Larissa Anatolievna Balabanova

“…The <i>alp</i> gene encoding for CmAP was cloned into the binary vectors pEff and pHREAC and transformed into <i>N. tabacum</i> leaves through agroinfiltration and the leaf disc method for callus induction using <i>Agrobacterium tumefaciens</i> strain EHA105. …”
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Mathematical and Machine Learning Innovations for Power Systems: Predicting Transformer Oil Temperature with Beluga Whale Optimization-Based Hybrid Neural Networks by Jingrui Liu, Zhiwen Hou, Bowei Liu, Xinhui Zhou

“…Power transformers are vital in power systems, where oil temperature is a key operational indicator. …”
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Hydrolysis Patterns of Different Crystalline Raw Starches by a Novel Cold-adapted α-Amylase by Hongbo HUANG, Miao SHAO, Xiangze JIA, Bin ZHANG, Xiong FU, Qiang HUANG

“…The hydrolytic behavior of low-temperature α-amylase on A-type crystalline starch (waxy maize starch, WMS) and B-type crystalline starch (potato starch, PS) was investigated in this study, using porcine pancreatic α-amylase (PPA) as a control. Methods: Hydrolysis products were analyzed using anionic high-performance liquid chromatography (HPAEC), and the physicochemical properties of starch granules were examined through scanning electron microscopy (SEM), X-ray diffraction (XRD), fourier transform infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC). …”
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Rep-MobileViT: Texture and Color Classification of Solid Wood Floors Based on a Re-Parameterized CNN-Transformer Hybrid Model by Anning Duanmu, Sheng Xue, Zhenye Li, Yajun Zhang, Chao Ni

“…However, most current research does not address the simultaneous classification of both texture and color in solid wood floors, and there is a notable gap in studies focusing on the classification of color-difference wood floors and white-edge wood floors. This paper proposes a re-parameterized CNN-Transformer hybrid architecture based on the MobileViT model, named Rep-MobileViT. …”
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A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence by Emrah Aslan, Yildirim Ozupak, Feyyaz Alpsalaz, Zakaria M. S. Elbarbary

“…Power transformers are critical components in ensuring the continuous and stable operation of power systems. …”
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Visual explainability of 250 skin diseases viewed through the eyes of an AI‐based, self‐supervised vision transformer—A clinical perspective by Ramy Abdel Mawgoud, Christian Posch

“…Objectives This study aimed to form the basis for an inexpensive and explainable AI system, targeted at the vastness of clinical skin diagnoses by comparing so‐called ‘self‐attention maps’ of an SS and a supervised ViT on 250 skin diseases—visualizations showing areas of interest for each skin disease. Methods Using a public data set containing images of 250 different skin diseases, one small ViT was pretrained S) for 300 epochs (=ViT‐SS), and two were fine‐tuned supervised from ImageNet‐weights for 300 epochs (=ViT‐300) and for 78 epochs due to heavier regularization (=ViT‐78), respectively. …”
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A Visualization of Ultrasonic Beam from a Medical Transducer using a Combination of Background-Oriented Schlieren Imaging with Hilbert Transformation by Margi Sasono, Apik Rusdiarna IP

“…The ultrasonic waves in water displace the patterns relative to the reference. A Hilbert Transform (HT) has been used to estimate the displacement of patterns proportional to the phase difference. …”
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Radio Frequency Sensing&#x2013;Based Human Emotion Identification by Leveraging 2D Transformation Techniques and Deep Learning Models by Najah AbuAli, Ihtesham Jadoon, Farman Ullah, Mohammad Hayajneh, Shayma Alkobaisi

“…The core objective is to evaluate the effectiveness of deep learning models from transformed time-frequency features, comparing their performance with different transformation techniques and training conditions. …”
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