Toward reliable fluorescence imaging: Optical prior-guided probabilistic reconstruction for structured illumination microscopy by Kun Lin, Junkang Dai, Huaian Chen, Yi Jin

“…Fluorescence microscopy is expected to be a reliable technique for bioprocess analysis, but the current single, deterministic imaging cannot objectively reflect the inherent observation errors caused by instruments and algorithms. For structured illumination microscopy (SIM) used for fast and long-term imaging at low excitation levels, the risk of unreliable misconceptions will be more non-negligible due to severe noise and super-resolution reconstruction. …”
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Development of New Radar and Pyroelectric Sensors for Road Safety Increase in Cloud-Based Multi-Agent Control Application by Leslie Robert Adrian, Ansis Avotins, Donato Repole, Olegs Tetervenoks

“…The work is based on previous developments by the authors in the production and design of close and long-range hybrid Pyroelectric Infrared (PIR) motion detection sensors. It also introduces the advances in radar-type sensors used in smart SLC (street lighting control) application systems. …”
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Phylogenetic Analysis of the North American Beetle Genus Trichiotinus (Coleoptera: Scarabaeidae: Trichiinae) by T. Keith Philips, Mark Callahan, Jesús Orozco, Naomi Rowland

“…Data from nineteen morphological traits and CO1 and 28S gene sequences were used to construct phylogenies using both parsimony and Bayesian algorithms. All results show that Trichiotinus is monophyletic. …”
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Deep and Machine Learning for Acute Lymphoblastic Leukemia Diagnosis: A Comprehensive Review by Mohammad Faiz, Bakkanarappa Gari Mounika, Mohd Akbar, Swapnita Srivastava

“…This analysis covers both machine learning models (ML), such as support vector machine (SVM) & random forest (RF), as well as deep learning algorithms (DL), including convolution neural network (CNN), AlexNet, ResNet50, ShuffleNet, MobileNet, RNN. …”
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Blockchain-enabled efficient distributed attribute-based access control framework with privacy-preserving in IoV by Ye Zhang, Leyou Zhang, Qing Wu, Yi Mu

“…Numeral experiments to show the proposed scheme has many advantages of over others such as the storage cost, the whole time consume of the proposed algorithms and the proxy computation cost.…”
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Research on Seismic Signal Denoising Model Based on DnCNN Network by Li Duan, Jianxian Cai, Li Wang, Yan Shi

“…Addressing the noise in seismic signals, a prevalent challenge within seismic signal processing, has been the focus of extensive research. Conventional algorithms for seismic signal denoising often fall short due to their reliance on manually determined feature functions and threshold parameters. …”
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The influence of partisanship on the roots of anti-vaccine attitudes in the context of the COVID-19 pandemic by Sylvia Iasulaitis, Alan Demetrius Baria Valejo, Leonardo Ribeiro dos Santos

“…We created a partisanship score using supervised machine learning algorithms with the random forest method to assess the influence of political orientations on the roots of COVID-19 vaccine rejection attitudes. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…LightGBM-GWO and CatBoost-GWO also demonstrated improvements, scoring up to 89 %. …”
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Ultrafast neuromorphic computing driven by polariton nonlinearities by Yusong Gan, Ying Shi, Sanjib Ghosh, Haiyun Liu, Huawen Xu, Qihua Xiong

“…Notably, we also show that the system is dynamically nonlinear, further enhancing the potential to improve classification efficiency and address more complex tasks. …”
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Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…Our findings ultimately inform practitioners about system efficiencies and limitations, but also the recent advances in hardware accelerators and algorithmic improvements aimed at shaping the new graph processing frontier in diverse technology domains.…”
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A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…Additionally, parameters such as $$\sigma ,\textrm{n} ,d,\gamma$$ in the hybrid kernel function, and the penalty coefficient C, were also optimized to improve classification accuracy. …”
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Development of a composite index for the assessment of food systems in the Philippines by Maria Julia Golloso-Gubat, Angelina Felix, Nancy A. Tandang, Cecilia Cristina S. Acuin, Prudenciano U. Gordoncillo

“…The robustness of the model was also tested by uncertainty and sensitivity tests. …”
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Environmental sustainability indicators applied to bioprocesses: a bibliometric analysis (2005–2024) by Anibal Alviz-Meza, Segundo Rojas-Flores, Ángel Darío González-Delgado

“…Their collaborative networks were also visualized using VOSviewer. The need to incorporate quantitative, qualitative, and descriptive indicators that comprehensively capture the environmental impacts of biotechnological processes led us to compile thirty diversified indices. …”
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Multi-Sensing Monitoring of the Microalgae Biomass Cultivation Systems for Biofuels and Added Value Products Synthesis—Challenges and Opportunities by Marcin Dębowski, Joanna Kazimierowicz, Marcin Zieliński

“…The integration of artificial intelligence (AI), the Internet of Things (IoT) and metaheuristic algorithms into monitoring systems is also discussed as a promising way to optimise key ecological, physicochemical, and biological parameters in real time. …”
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Machine Learning-Based Methodologies for Cyber-Attacks and Network Traffic Monitoring: A Review and Insights by Filippo Genuario, Giuseppe Santoro, Michele Giliberti, Stefania Bello, Elvira Zazzera, Donato Impedovo

“…Also, the ensembles are tested. The algorithms are evaluated on the KDD-99, NSL-KDD, UNSW-NB15, IoT-23, and UNB-CIC IoT 2023 datasets. …”
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Systematic Review: Malware Detection and Classification in Cybersecurity by Sebastian Berrios, Dante Leiva, Bastian Olivares, Héctor Allende-Cid, Pamela Hermosilla

“…The digital era, marked by the proliferation of connected devices, cloud services, and the advancement of machine learning, has brought numerous benefits; however, it has also exacerbated exposure to cyber threats, affecting both individuals and corporations. …”
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Advancements in artificial intelligence for atopic dermatitis: diagnosis, treatment, and patient management by Fang Cao, Yujie Yang, Cui Guo, Hui Zhang, Qianying Yu, Jing Guo

“…In addition, artificial intelligence has also shown promise in creating personalized treatment plans, simplifying drug development processes, and managing clinical trials. …”
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A Comparative Study of Continual, Lifelong, and Online Supervised Learning Libraries by Nicholas Cummins, Brad Killen, Somayeh Bakhtiari Ramezani, Shahram Rahimi, Maria Seale, Sudip Mittal

“…Our comparison as developers takes maintenance, documentation, and offerings of state-of-the-art algorithms into account. As this is not necessarily free of bias, we also use benchmarks known to online learning to gather power usage, RAM usage, speed, and accuracy of these libraries to get an objective view. …”
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Routing Protocols in Underwater Acoustic Sensor Networks: A Quantitative Comparison by Guangjie Han, Na Bao, Li Liu, Daqiang Zhang, Lei Shu

“…The impact of water currents on the routing algorithms is also analyzed in our simulation. Experimental results demonstrate that E-PULRP provides high data delivery ratio at the cost of end-to-end delay. …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Despite these promises, machine learning applications are not widely adapted in clinical care due to many issues including ethical concerns, patient privacy, informed consent, algorithmic biases, data quality and availability, and education and training of health care professionals. …”
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