Impact of heterologous expression of Cannabis sativa tetraketide synthase on Phaeodactylum tricornutum metabolic profile by Nicolas Sene, Karen Cristine Gonçalves dos Santos, Natacha Merindol, Sarah-Eve Gélinas, Alexandre Custeau, Fatima Awwad, Elisa Fantino, Fatma Meddeb-Mouelhi, Hugo Germain, Isabel Desgagné-Penix

“…These findings underscore the complexity of metabolic engineering in diatoms and suggest the need for further pathway optimization and metabolic flux analysis to achieve efficient cannabinoid biosynthesis. …”
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Novel Cerium‐Based p‐Dopants with Low Parasitic Absorption for Improved Organic Devices by Stephanie A. Buchholtz, L. Conrad Winkler, Maximilian F. X. Dorfner, Fred Kretschmer, Anncharlott Kusber, Léonard Y. M. Eymann, Theresa Schmidt, Hans Kleemann, Johannes Benduhn, Frank Ortmann, Karl Leo

“…Abstract High electrical conductivity and improved charge carrier injection enabled by molecular doping are pivotal for high‐performance, energy‐efficient, and stable organic optoelectronic devices. …”
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Sub-pA dark current infrared photodetection enabled by polarized water-intercalated heterojunctions by Chang Liu, Lin Tang, Yawei Lv, Long Chen, Yilu Qin, Sen Zhang, Shihao Zhao, Shuimei Ding, Xin Zhang, Pan Xu, Chao Ma, Xingqiang Liu, Fang Wang, Peng Wang, Xudong Wang, Yuan Liu, En-Ge Wang, Lei Liao, Xuming Zou

“…The confined water layer forms a clean, well-ordered interface and further generates a precisely oriented polarization field that depletes electrons in WSe2, significantly suppressing dark current to sub-pA levels across all biases, while enabling efficient tunneling of photogenerated holes. The device shows broadband photoresponse from the ultraviolet to mid-wave infrared (MWIR), with a room-temperature average detectivity exceeding 10¹⁰ cm Hz¹/² W⁻¹ in the MWIR. …”
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Identification of strengths and weaknesses of the healthcare system for persons living with rare diseases in Catalonia (Spain), and recommendations to improve its comprehensive att... by José Hernández-Rodríguez, Fernando Martínez-Valle, Xènia Acebes, Carmen Alerany, Jordi Antón, Gonzalo Calvo, Marian Corral, Jordi Cruz, M. Antònia Mangues-Bafalluy, José Mateo, Josefa Rivera, Albert Salazar, Roser Francisco, Cristina Mallol, Rita Reig-Viader, Ariadna Tigri-Santiña, Assumpta Ricart, Francesc Palau

“…Abstract Background Rare diseases (RDs) are a heterogeneous group of complex and low-prevalence conditions in which the time to establish a definitive diagnosis is often too long. …”
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An azo substituted quinoline‐malononitrile enzyme‐activable aggregation‐induced emission nanoprobe for hypoxia imaging by Zhirong Zhu, Shichang Liu, Xupeng Wu, Qianqian Yu, Yi Duan, Shanshan Hu, Wei‐Hong Zhu, Qi Wang

“…Abstract The development of efficient aggregation‐induced emission (AIE) active probes is crucial for disease diagnosis, particularly for tumors and cardiovascular diseases. …”
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Enhancing the FFT-LSTM Time-Series Forecasting Model via a Novel FFT-Based Feature Extraction–Extension Scheme by Kyrylo Yemets, Ivan Izonin, Ivanna Dronyuk

“…These approaches have already shown considerable advantages over traditional methods, especially due to their capacity to efficiently process large datasets and detect complex patterns. …”
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Isolation and identification of a matrine-producing fungal strain from petroleum-contaminated soil by Mao Dongxia, Guo Dandan, Wu Lingling, Tian Xiaoxue, Zhang Shengxiang, Liu Tao, Ma Xiaokui

“…In addition, the production efficiency is not high enough, and the product has many impurities. …”
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Identification of tRF-29-79MP9P9NH525 as a biomarker and tumor suppressor of gastric cancer via regulating KIF14/AKT pathway by Jiaxin Ge, Ji Dai, Haoqiang Ji, Jie Guo, Xiaoban Shen, Desen Sun, Qiang Chen, Pan Chen, Guoliang Ye, Junming Guo, Shuangshuang Zhang

“…It was found that tissue tRF-29 showed effective diagnostic efficiency in GC and could discriminate different gastric mucosa. …”
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Blessing of dimensionality in spiking neural networks: the by-chance functional learning by Valeri A. Makarov, Sergey A. Lobov, Sergey A. Lobov

“…Spiking neural networks (SNNs) have significant potential for a power-efficient neuromorphic AI. However, their training is challenging since most of the learning principles known from artificial neural networks are hardly applicable. …”
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Graph cut-based segmentation for intervertebral disc in human MRI by Leena Silvoster, R. Mathusoothan S. Kumar

“…Validation of the algorithm on a dataset of 15 patients demonstrates its efficient segmentation performance, achieving a Dice Similarity Coefficient (DSC) of 89%.…”
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Chemotactic response and adaptation dynamics in Escherichia coli. by Diana Clausznitzer, Olga Oleksiuk, Linda Løvdok, Victor Sourjik, Robert G Endres

“…Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. …”
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Optimization with Time and Frequency Constraints Using Automatic Differentiation: Application to an Aircraft Electrical Power Channel by Lucas Agobert, Laurent Gerbaud, Benoit Delinchant

“…Optimal sizing, on top of developing such a model, is a significant challenge for designers, particularly due to the complexity of incorporating efficiently both time-domain and frequency-domain constraints and objectives. …”
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U-Net-based VGG19 model for improved facial expression recognition by Xiaohu ZHAO, Jingyi ZHANG, Mingzhi JIAO, Lixun XIE, Lanfei WANG, Weiqing SUN, Di ZHANG

“…The use of feature cropping and stitching techniques allows the model to efficiently integrate multi-scale features, thereby enhancing the robustness and effectiveness of facial expression recognition tasks. …”
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Identification of Metabolites of Ferulic Acid in Human after Oral Administration by Qian PAN, Wei LI, Yang YANG, Yong-qiang ZHAO, Li LIAN, Qing-qing CONG, Li-hong WANG, Yue-lin SONG, Qian HONG

“…Liquid chromatography coupled with mass spectrometry (LC-MS) combines the high-efficiency separation capabilities of LC with the powerful qualitative analysis advantage of MS, playing a vital and irreplaceable role in the in-depth study of chemical profiles in complex systems. …”
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Metallurgical Waste for Sustainable Agriculture: Converter Slag and Blast-Furnace Sludge Increase Oat Yield in Acidic Soils by Olga V. Zakharova, Peter A. Baranchikov, Svetlana P. Chebotaryova, Gregory V. Grigoriev, Nataliya S. Strekalova, Tatiana A. Grodetskaya, Igor N. Burmistrov, Sergey V. Volokhov, Denis V. Kuznetsov, Alexander A. Gusev

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Quantitative and Qualitative Evaluation of Microplastic Contamination of Shrimp Using Visible Near-Infrared Multispectral Imaging Technology Combined with Supervised Self-Organizin... by Sureerat Makmuang, Abderrahmane Aït-Kaddour

“…However, accurately detecting and characterizing MPs in biological samples remains a challenge due to the complexity of biological matrices and analytical limitations. …”
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Systems monitoring platform integrating artificial intelligence for incident response in servers by Bruno Hiroshi Espinosa-Luna, Johann Castillo-Oliva, Willy Francisco García-Gutiérrez, Alberto Carlos Mendoza-de-los-Santos

“… The increasing complexity of IT management and the need to monitor critical infrastructure metrics, such as CPU usage, memory, storage, and service logs, detect failures, and respond quickly to alerts, imply the adoption of advanced technologies that enable comprehensive monitoring and efficient response. …”
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Robust Network Traffic Classification Based on Information Bottleneck Neural Network by Wei Lin, Yu Chen

“…Recent advances in machine learning have improved NTC but often struggle with data labeling, encrypted traffic, and model complexity. This paper introduces a novel Information Bottleneck Neural Network (IBNN) to address these challenges by efficiently extracting essential features from raw traffic data while minimizing irrelevant information. …”
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A Hybrid Approach to Enhanced Signal Denoising Using Data-Driven Multiresolution Analysis with Detrended-Fluctuation-Analysis-Based Thresholding and Stationary Wavelet Transform by Fatima Kozhamkulova, Muhammad Tahir Akhtar

“…It is demonstrated that the proposed method outperforms the state-of-the-art denoising methods and with a comparable computational complexity.…”
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Unravelling single-cell DNA replication timing dynamics using machine learning reveals heterogeneity in cancer progression by Joseph M. Josephides, Chun-Long Chen

“…Here, we develop MnM, an efficient machine learning-based tool that allows disentangling scRT profiles from heterogenous samples. …”
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