Integrative Analysis of Transcriptomic and Metabolomic Profiles Uncovers the Mechanism of Color Variation in the Tea Plant Callus by Mengna Xiao, Yingju Tian, Ya Wang, Yunfang Guan, Ying Zhang, Yuan Zhang, Yanlan Tao, Zengquan Lan, Dexin Wang

“…Tissue culture serves as a crucial method in commercial breeding by facilitating the rapid propagation of valuable genotypes and the generation of disease-free clones. …”
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Green Synthesis and Characterization of Carbon Dots Nanosensors Using Pumpkin Seed Shell for Spectrofluorimetric Determination of L-cysteine by Afsaneh Zarei Manujan, Alireza Bazmandegan-shamili, Mohammad Sabet, Masoud Rohani Moghadam

“…In this research, carbon dots with high luminescence intensity were synthesized using pumpkin seed shell as a new and green source with hydrothermal method. The prepared carbon dots were characterized using X-ray diffraction, Fourier transform infrared spectroscopy and Scanning electron microscopy. …”
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Benchmarking <i>K</i>_DP in rainfall: a quantitative assessment of estimation algorithms using C-band weather radar observations by M. Aldana, M. Aldana, S. Pulkkinen, A. von Lerber, M. R. Kumjian, D. Moisseev, D. Moisseev

“…Most of these methods showed a significant reduction in the estimation errors after the optimization, with respect to the default settings. …”
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Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling. by Burak Alakent, Erkan Isikli, Cigdem Kadaifci, Tonguc S Taspinar

“…Since a model is constructed separately for each test point, the proposed method is, indeed, an example of JITL. The JITL-GPR method is easy to use and optimize, and offers a reduction in forecast errors compared to traditional time series methods and a state-of-the-art combination model; therefore, it is a promising tool for NGD forecasting in similar settings.…”
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Qualitative and quantitative HPLC-ELSD-ESI-MS analysis of steroidal saponins in fenugreek seed by Król-Kogus Barbara, Głód Daniel, Krauze-Baranowska Mirosława

“…Therefore, the steroidal saponin complex in the seeds of T. foenum-graecum cultivated in Poland was qualitatively and quantitatively analyzed by the HPLC-ELSDESI-MS method. Two C-18 columns connected in series were used for the first time in analysis of fenugreek saponins and ELS detector parameters were optimized. …”
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Energy Management Considering Energy Storage and Demand Response for Smart Energy Hub in Internet of Things by Jinyong Lei, Changcheng Zhou, Xiaolin Li, Andi Huang, Hao Bai, Zhiyong Yuan, Linjie Zhou

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An overview of ahead geological detection technologies in tunnels by Dingchao Chen, Xiangyu Wang, Jianbiao Bai, Yuan Chu, Xian Wang, Jiaxin Zhao, Menglong Li

“…This paper underscores the need for multi-source, cooperative detection approaches and transparent geological models to improve the safety and efficiency of tunneling operations, ultimately contributing to the optimization of tunnel design and construction strategies.…”
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HiGoReg: A Hierarchical Grouping Strategy for Point Cloud Registration by Tengfei Zhou, Jianxiang Gu, Zhen Dong

“…To address the persistent computational bottlenecks in point cloud registration, this paper proposes a hierarchical grouping strategy named HiGoReg. This method incrementally updates the pose of the source point cloud via a hierarchical mechanism, while adopting a grouping strategy to efficiently conduct recursive parameter estimation. …”
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Investigation and analysis of the impact of historical contexts on urban tourism development by Ali Morvati

“…The research sample consists of 150 people who will be selected using random sampling method. In this research, a mixed method (qualitative and quantitative) is used, and the research tools include questionnaires designed to collect statistical data and semi-structured interviews with tourism experts and experts. …”
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Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models by Jian-An Chen, Wu-Chun Chung, Che-Lun Hung, Chun-Ying Wu

“…ObjectiveThis study aims to develop a robust and generalizable deep learning framework for detecting misinformation related to the prolonged impacts of COVID-19 by integrating pretrained language models (PLMs) with an innovative fuzzy rank-based ensemble approach. MethodsA comprehensive dataset comprising 566 genuine and 2361 fake samples was curated from reliable open sources and processed using advanced techniques. …”
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Numerical analysis on heat and mass transfer of immiscible fluids in a vertical channel with diffusion effects by P. Kumaraswamy, T Ramakrishna Goud, B. Suresh Babu, Vanaja Gosty, G. Srinivas, T. Haripriya, O.D. Makinde

“…The study further incorporates the effects of an internal heat source, adding complexity to the analysis of transfer processes. …”
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From Simulation to Implementation: A Systems Model for Electric Bus Fleet Deployment in Metropolitan Areas by Ludger Heide, Shuyao Guo, Dietmar Göhlich

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Precise Design of Solid Rocket Motor Heat Insulation Layer Thickness under Nonuniform Dynamic Burning Rate by Ran Wei, Futing Bao, Yang Liu, Weihua Hui

“…The proposed method is compatible with solid rocket motors that have any shape and any manner of erosion. …”
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Life cycle inventory dataset for energy production and storage technologies: Standardized metrics for environmental modelingZenodo by Elena Rozzi, Paolo Marocco, Marta Gandiglio

“…Unlike existing LCA databases, which are often paywalls, and can have highly detailed but less accessible data, this method provides aggregated and user-friendly parameters that are ready for direct use. …”
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Modular Design and Layout Planning of Tooling Structures for Aircraft Assembly by Zhanghu Shi, Chengyu Li, Junshan Hu, Xingtao Su, Hancheng Wang, Wei Tian

“…A parametric representation of the multi-source information of tooling modules is proposed, and optimization methods for the layout and configuration of locators and platforms are developed using their parametric information. …”
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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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Integration of interior design strategies and computer-aided design technology guided by morphogenetic theory by Jie Zhang, Zhongxian Ren

“…Among them, this study adopts a method based on an open-source computer vision library to identify double line walls and windows in the drawings. …”
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Smooth Guided Adversarial Fully Test-Time Adaptation by Dong Li, Panfei Yang

“…Fully test-time adaptation (FTTA) refers to a specific type of domain adaptation that involves adjusting a pre-trained machine learning model to work with a new target domain, without accessing any data from the source domain. The lack of access to source data makes it more difficult to adjust to the target domain. …”
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Feasibility of a Sustainable On-Site Paper Recycling Process by Karl Jakob Levin, David dos Santos Costa, Lii Urb, Anna-Liisa Peikolainen, Tanel Venderström, Tarmo Tamm

“…Several EU initiatives and directives emphasize waste reduction and immediate reuse at the source. This study introduces a novel on-site recycling method for transforming printing house paper waste into high-quality, eco-friendly cardboard without mixing it with lower-quality or heterogeneous waste streams. …”
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A novel twin time series network for building energy consumption predicting. by Zhixin Sun, Han Cui, Xiangxiang Mei, Hailei Yuan

“…The model was evaluated on datasets from university dormitories, office buildings, and school classrooms, showing significant improvements over the optimal baseline method. For instance, on the university classroom dataset, T2SNET reduced MAE by 4.56%, RMSE by 9.45%, and MAPE by 3.16% compared to the CEEMDAN-RF-LSTM model. …”
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