A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists’ demonstrations by David Martínez-Pascual, José M. Catalán, Luís D. Lledó, Andrea Blanco-Ivorra, Nicolás García-Aracil

“…The architecture of the Deep Learning model is conceived to perform time-series classification. It consists of diverse one-dimensional convolutional layers, a convolutional attention mechanism, and a Global Average Pooling layer. …”
Get full text

The effects of magnitude of calcium decline at the onset of lactation on serotonin dynamics and the serotonin-calcium axis by M.K. Connelly, R.M. Rodney, J. Kuehnl, J.P.N. Andrade, F. Sonnewend Andrade, S. Henschel, E. Block, I.J. Lean, L.L. Hernandez

“…Cows fed a −DCAD diet prepartum had greater circulating serotonin concentrations pre- and postpartum. Time series analyses demonstrated that the pooled mean effect size (ES) of the relationship between ionized Ca and serotonin 36 h before parturition was significantly positive (ES = 0.164) prepartum. …”
Get full text

Vegetation growth improvement Inadequately represents the ecological restoration of the Populus euphratica forests in Xinjiang, China by Xuefei Guo, Junli Li, Jiudan Zhang, Chunxia Wei, Zhijun Li

“…Monitoring the health of these forests is crucial for understanding forest succession and ecosystem restoration. This study used time-series NDVI data from Landsat imagery and fieldwork investigations to monitor vegetation growth and stand age structures of P. euphratica forests in Xinjiang and explore the driving factors of these changes. …”
Get full text

Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days by Brook L. Nunn, Emma Timmins-Schiffman, Miranda C. Mudge, Deanna L. Plubell, Gabriella Chebli, Julia Kubanek, Michael Riffle, William S. Noble, Elizabeth Harvey, Tasman A. Nunn, Tatiana Rynearson, Marcel Huntemann, Kurt LaButti, Brian Foster, Bryce Foster, Simon Roux, Krishnaveni Palaniappan, Supratim Mukherjee, T. B. K. Reddy, Chris Daum, Alex Copeland, I-Min A. Chen, Natalia N. Ivanova, Nikos C. Kyrpides, Tijana Glavina del Rio, Emiley A. Eloe-Fadrosh

“…Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. …”
Get full text

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study by Xin Xiong, Linghui Xiang, Litao Chang, Irene XY Wu, Shuzhen Deng

“…MethodsWe analyzed mumps incidence in Yunnan Province from 2014 to 2023, and used time series data, including mumps incidence, Baidu search index, and environmental factors, from 2016 to 2023, to develop predictive models based on long short-term memory networks. …”
Get full text

Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions by Jin-Hyun Park, Yu-Bin Shin, Dooyoung Jung, Ji-Won Hur, Seung Pil Pack, Heon-Jeong Lee, Hwamin Lee, Chul-Hyun Cho, Chul-Hyun Cho

“…This study employed extended Geneva minimalistic acoustic parameter set for acoustic feature extraction and extracted statistical attributes from time series-based physiological responses. We developed ML models that predict the upper tertile group for various anxiety symptoms in SAD using Random Forest, extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost) models. …”
Get full text

Macroecological predictors to determine future refuges of Luciobarbus species in the Tigris–Euphrates basin: Rethinking conservation strategies and management by Hadi Khoshnamvand, Seyed Mohsen Mousavi, Asef Darvishi, Kourosh Ahmadi, Amir Naghibi, Karel Janko, Asghar Abdoli, Faraham Ahmadzadeh

“…We employed a generalized linear model (GLM) with a quasi-Poisson distribution to create a map depicting the richness of Luciobarbus fish species.Our projections indicate that suitable habitats will decline in both time series under climate change SSP126 and SSP585 scenarios, resulting in the loss of certain habitat patches in the Southwest of Iran, Syria and Iraq. …”
Get full text

The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins by H. M. M. Hasan, P. Döll, P. Döll, S.-M. Hosseini-Moghari, F. Papa, A. Güntner, A. Güntner

“…This indicates an overfitting to the singular observation time series by the calibration algorithm. We therefore propose a transparent algorithm to identify high-performing Pareto solutions under consideration of observational uncertainties of the calibration data.…”
Get full text

Construction and application of optimized model for mine water inflow prediction based on neural network and ARIMA model by Xiaoyu Gong, Bo Li, Yu Yang, MengHua Li, Tao Li, Beibei Zhang, Lulin Zheng, Hongfei Duan, Pu Liu, Xin Hu, Xin Xiang, Xinju Zhou

“…In order to better predict the amount of water surging in mines and to provide an important basis for mine water damage prevention work, based on the time series data of mine water influx from January 2020 to February 2023 in Northern Guizhou Province Longfeng Coal Mine, the BP-ARIMA prediction model was established by combining the BP neural network model and ARIMA autoregressive sliding average model, It also predicted the mine influx for a total of 6 months from July 2022 to February 2023, and compared the prediction results with four models, namely, BP neural network model, ARIMA autoregressive sliding average model, traditional method of Large well method, and GM(1,1) grey model, and used the absolute relative error as the calculation of model accuracy. …”
Get full text

Variability of plankton communities in relation to the lunar cycle in oceanic waters by Santiago Hernández-León, M. Loreto Torreblanca, M. Loreto Torreblanca, Inma Herrera, Inma Herrera, Laia Armengol, Gara Franchy, Alejandro Ariza, Juan Carlos Garijo, María Couret

“…The short-term variability of plankton communities in the oceanic realm is still poorly known due to the paucity of high-resolution time-series in the open ocean. Among these few studies, there is compelling evidence of a lunar cycle of epipelagic zooplankton biomass in subtropical waters during the late winter bloom. …”
Get full text

Tobacco control research in South Africa from 1978 to 2022: A scoping review by C O Egbe, C Dare, S Gwambe, C van Walbeek

“…A total of 79% of the studies used cross-sectional survey design, followed by randomised controlled trials (3.6%; n=8), time series studies (3.1%; n=7) and longitudinal and qualitative studies (2.2%; n=5 each), while costs and benefits analysis (0.4%; n=1) was used much less. …”
Get full text

Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques by Mohammad Shakiul Islam, Padmanava Dash, Abduselam M. Nur, Hafez Ahmad, Rajendra M. Panda, Jessica S. Wolfe, Gray Turnage, Lee Hathcock, Gary D. Chesser, Jr, Robert J. Moorhead

“…The XGB algorithm was subsequently applied to a time series of UAS imagery to generate Chl-a concentration maps, which revealed the spatiotemporal distribution of Chl-a across the study area. …”
Get full text

Temporal segmentation method for 30-meter long-term mapping of abandoned and reclaimed croplands in Inner Mongolia, China by Deji Wuyun, Liang Sun, Zhongxin Chen, Luís Guilherme Teixeira Crusiol, Jinwei Dong, Nitu Wu, Junwei Bao, Ruiqing Chen, Zheng Sun, Hasituya, Hongwei Zhao

“…The Temporal Segmentation of Abandoned and Reclaimed Cropland (TSARC) method created time series maps of abandoned and reclaimed cropland at a 30-meter resolution, achieving an overall accuracy of 87.61%. …”
Get full text

Impacts of drought on respiratory mortality in the upper midwest United States: a population subgroup assessment by Yeongjin Gwon, Yuanyuan Ji, Jesse D Berman, Azar M Abadi, Ronald D Leeper, Jared Rennie, Jesse E Bell

“…A Bayesian two-stage time-series modeling approach was applied to estimate the county-level and overall risk along with the 95% Credible Intervals (Cr). …”
Get full text

Needs Assessment and Tailored Training Pilot for Emergency Care Clinicians in the Prehospital Setting in Rwanda by Naz Karim, Jeanne D’Arc Nyinawankusi, Mikaela S. Belsky, Pascal Mugemangango, Zeta Mutabazi, Catalina Gonzalez Marques, Angela Y. Zhang, Janette Baird, Jean Marie Uwitonze, Adam C. Levine

“…A prospective, nonrandomized, interrupted time-series approach was used. Data collected through closed- and open-ended questionnaires included age, sex, training, and knowledge assessment. …”
Get full text

An observational, multigenerational platform for health systems and population health interventions to minimise intergenerational transmission of non-communicable diseases in India... by Vaman Khadilkar, Tarun Reddy Katapally, Jasmin Bhawra, Neha Kajale, Rubina Mandlik, Vivek Patwardhan, Demi Miriam, Dipali Ladkat, Chidvilas More, Ketan Gondhalekar, Anuradha Vaman Khadilkar

“…The long-term data analysis plan includes longitudinal modelling, time-series analyses, structural equation modelling, multilevel modelling and sex-based analyses to investigate growth trajectories and intergenerational patterns of health risks. …”
Get full text

Excess Sensitivity and Financial Development in the Iranian Households by Amineh Mahmoudzadeh, Kamyab Rajabizadeh, Majid Einian

“…Second, it mitigates the issues arising from the short time series data, which can lead to estimation errors. …”
Get full text

The impact of the live broadcast of Stromae’s song L’enfer on social media publications, calls to the national helpline, and suicide attempt rates in France by Charles-Edouard Notredame, Chloé Saint-Dizier, Antoine Lamer, Erika Nogue, Emile Fares, Mohamed Lemdani, Guillauma Vaiva, Philippe Courtet, Emilie Olié

“…We employed the Gombay test to identify change points within each time series. We identified a significant increase in mean SA rates among women aged 20–24 years 6 days after the singer’s performance. …”
Get full text

Explore the evolution of winter wheat production and its response to climate change under varying precipitation years in the Loess Plateau of China by Donglin Wang, Yanbin Li, Binbin Zhang, Tengcong Jiang, Siyu Wu, Wenjie Wu, Yi Li, Jianqiang He, Deli Liu, Qinge Dong, Hao Feng

“…In this study, parameters of APSIM-Wheat model were refined based on experimental data. Time series analysis showed that the winter wheat yields in the Loess Plateau exhibit periodic fluctuation, with a shorter fluctuation period under the SSP245 scenario compared to the SSP585 scenario, indicating an overall upward trend. …”
Get full text

Automatic GPR detection of grouting defects behind the tunnel shield segments based on wavelet coherence analysis combined with modified Res-RCNN by Dengyi Wang, Ming Peng, Liu Liu, Xiongyao Xie, Zhenming Shi, Yaoying Liang, Jian Shen, Qiyu Wu

“…The approach employs wavelet coherence to transform the time-series GPR profile into the time-frequency images and reveal the weak defect reflections. …”
Get full text