Development of Non-Invasive Continuous Glucose Prediction Models Using Multi-Modal Wearable Sensors in Free-Living Conditions by Thilini S. Karunarathna, Zilu Liang

“…We used the BIG IDEAs Lab Glycemic Variability and Wearable Device Data (BIGIDEAs) dataset, which includes approximately 26,000 CGM readings, simultaneous ly collected wearable data, and demographic information. …”
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A Novel Electromagnetic Induction-Based Approach to Identify the State of Shallow Groundwater in the Oasis Group of the Tarim Basin in Xinjiang During 2000–2022 by Fei Wang, Yang Wei, Rongrong Li, Hongjiang Hu, Xiaojing Li

“…Our understanding of water and salt changes in the context of declining groundwater levels in the Tarim Basin remains limited, largely due to the scarcity of hydrological monitoring stations and field observation data. This study utilizes water and salt monitoring data from 474 apparent electromagnetic induction (ECa, measured by EM38-MK2 device) sites across seven oases, combined with groundwater level observation data from representative areas, to analyze the spatiotemporal changes in ECa within the oases of the Tarim Basin from 2000 to 2022. …”
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Clinicopathological spectrum of central nervous system germ cell tumors: A single-institution retrospective study by Sreelekha Appasani, Neelima Radhakrishnan, Anitha Mathews

“…Statistical Analysis: Data on categorical variables were analyzed as percentages, and data on continuous variables calculated as mean. …”
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A method for short-term wind power forecasting under extreme weather conditions based on meteorological factor interpretability and hybrid deep learning algorithms by Bo Wang, Shu Wang, Zheng Wang, Yingying Zheng, Xin Li

“…This model combines the CNN and BiLSTM network to capture local features and long-term temporal trends complementarily and further enhances the learning of key temporal features through an AM, finally outputting the forecasting results. Through case analysis on a wind power dataset in Liaoning, China, the experimental results show that compared with traditional forecasting methods, the proposed framework reduces the mean absolute error (MAE) by 52.29% and increases R2 by 0.0625 under windy conditions, and reduces the MAE by 64.29% and increases R2 by 0.0462 under low-temperature weather. …”
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Implications of Self-Potential Distribution for Groundwater Flow System in a Nonvolcanic Mountain Slope by Tada-nori Goto, Kazuya Kondo, Rina Ito, Keisuke Esaki, Yasuo Oouchi, Yutaka Abe, Maki Tsujimura

“…Survey routes were set around the northern slope, and the reliability of observed SP anomaly was checked by using SP values along parallel survey routes; the error was almost within 10 mV. The FFT analysis of the spatial SP distribution allows us a separation of raw data into two components with shorter and longer wavelength. …”
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An Improved Short-Term Electricity Load Forecasting Method: The VMD–KPCA–xLSTM–Informer Model by Jiawen You, Huafeng Cai, Dadian Shi, Liwei Guo

“…Finally, the Informer model processes long-sequence data to improve prediction efficiency. Experimental results demonstrate that the VMD–KPCA–xLSTM–Informer model achieves an average absolute percentage error (MAPE) as low as 2.432% and a coefficient of determination (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>) of 0.9532 on dataset I, while, on dataset II, it attains a MAPE of 4.940% and an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> of 0.8897. …”
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Evaluation and modeling of traffic noise in an urban area of Chhattisgarh, India by Vishal Kumar, Ajay Vikram Ahirwar, A. D. Prasad

“…Six models best suited to our location were selected after performing the literature review in brief. Traffic data was collected, and models were tested. Results: On comparing the data, it was found that out of six models, the Burgess model was found to be the most accurate, as its predicted noise levels are consistently closest to the measured noise levels across all ten locations. …”
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Blood Glucose Concentration Prediction Based on Double Decomposition and Deep Extreme Learning Machine Optimized by Nonlinear Marine Predator Algorithm by Yang Shen, Deyi Li, Wenbo Wang, Xu Dong

“…Using actual collected blood glucose concentration data for predictive analysis, the results of three patients show the following: (i) The double decomposition strategy effectively reduces the complexity and volatility of the original sequence and the residual component. …”
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Strategy of satellite monitoring of organic carbon content in arable soil horizons in Russia by I. Yu. Savin, E. Yu. Prudnikova, G. V. Windecker, N. S. Sobolev

“…The strategy is based on the analysis of Landsat 8-9 OLI satellite data archives. …”
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Anesthesia depth prediction from drug infusion history using hybrid AI by Liang Wang, Yiqi Weng, Wenli Yu

“…The model was trained and evaluated on patient data from a publicly available anesthesia monitoring database. …”
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Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…Finally, a simulation experiment platform is established based on MATLAB to verify the temperature rise of high-speed bearings in gearboxes of wind turbines by example calculation and comparative analysis. The results show that the model established in this paper is effective, the prediction results are accurate and the performance is stable, and then compared with the algorithms such as PSO-SVM, SVM, BP, etc, the coefficient of determination of the algorithm is greater than 0.994 in both the training set and the test set, and the average decision percentage error is around 1.88% in both.…”
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Tunable All-Optical Pattern Recognition System Based on Nonlinear Optical Loop Mirror for Bit-Flip BPSK Targets by Ying Tang, Ziyi Kang, Xin Li, Ningjing Liang, Jinyong Chang, Genqing Bian

“…To improve the security of optical networks, optoelectronic firewalls primarily leverage all-optical pattern recognition to perform direct detection and analysis of data transmitted through the optical network at the optical layer. …”
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Index or illusion: The case of frailty indices in the Health and Retirement Study. by Yi-Sheng Chao, Hsing-Chien Wu, Chao-Jung Wu, Wei-Chih Chen

“…We are concerned the processing of frailty data may introduce measurement error and bias. We aim to review the assumptions, interpretability and predictive power of FIs regarding mortality.…”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…Two feature reduction techniques were used to reduce data dimensions and improve model performance: Pearson correlation and principal component analysis. …”
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Physiologically Based Pharmacokinetic Simulation of Tofacitinib in Humans Using Extrapolation from Single-Species Renal Failure Model by Sung Hun Bae, So Yeon Park, Hyeon Gyeom Choi, So Hee Kim

“…This was because the Dedrick plot relied solely on preclinical plasma concentration data without incorporating drug physicochemical properties, in vitro data, or physiological and pathophysiological variables. …”
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Negative control-calibrated difference-in-difference analyses: addressing unmeasured confounding in RWD with application to racial/ethnic differences by Dazheng Zhang, Bingyu Zhang, Huiyuan Wang, Yiwen Lu, Charles J. Wolock, Wenjie Hu, Linbo Wang, George Hripcsak, Yong Chen

“…Abstract Real-world data (RWD) from electronic health records and digital health databases present unique opportunities to study causal effects in healthcare. …”
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FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…Manual grading of DR is time-consuming and prone to human error. It is also crucial to securely exchange patients’ fundus image data with hospitals worldwide while maintaining confidentiality in real time. …”
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Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea by Sara Pensieri, Roberto Bozzano, Jeffrey A. Nystuen, Emmanouil N. Anagnostou, Marios N. Anagnostou, Renzo Bechini

“…., buoy mounted rain gauge and anemometer and weather radar) to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. …”
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Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model by Lingyi Hou, Xiao Wang, Bo Yang, Zhiyuan Wei, Yuwen Sun, Yuxiang Ma

“…The model’s performance is evaluated through error analysis, comparisons of wave number spectra, and differences in wave surface reconstructions using a dedicated test set. …”
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Assessing and Forecasting Natural Regeneration in Mediterranean Landscapes After Wildfires by Paraskevi Oikonomou, Vassilia Karathanassi, Vassilis Andronis, Ioannis Papoutsis

“…Their performance was evaluated by comparing the predicted and actual numerical values, calculating error metrics (RMSE, MAPE), and analyzing how the predicted patterns align with the observed ones. …”
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