Digital Health Technology Interventions for Improving Medication Safety: Systematic Review of Economic Evaluations by Widya Norma Insani, Neily Zakiyah, Irma Melyani Puspitasari, Muhammad Yorga Permana, Kankan Parmikanti, Endang Rusyaman, Auliya Abdurrohim Suwantika

“…We adopted recommendations from the Panel on Cost-Effectiveness in Health and Medicine for data extraction. A narrative analysis was conducted to synthesize clinical and economic outcomes. …”
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Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels by Gökalp Tulum, Sajjad Nematzadeh, İlke Taşçıoğlu, Şemsettin Altındal, Fahrettin Yakuphanoğlu

“…LSTM shows on Diode 2 consistently lower errors, achieving a minimum RMSE of 6.22 mA at 100 W (R²=0.993). …”
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Light use efficiency (LUE) based bimonthly gross primary productivity (GPP) for global grasslands at 30 m spatial resolution (2000–2022) by Mustafa Serkan Isik, Leandro Parente, Davide Consoli, Lindsey Sloat, Vinicius Vieira Mesquita, Laerte Guimaraes Ferreira, Simone Sabbatini, Radost Stanimirova, Nathalia Monteiro Teles, Nathaniel Robinson, Ciniro Costa Junior, Tomislav Hengl

“…The final time-series of maps (uncalibrated and grassland GPP) are available as bimonthly (daily estimates in units of gCm−2d−1) and annual (daily average accumulated by 365 days in units of gCm−2yr−1) in Cloud-Optimized GeoTIFF (~23TB in size) as open data (CC-BY license). The recommended uses of data include: trend analysis e.g., to determine where are the largest losses in GPP and which could be an indicator of potential land degradation, crop yield mapping and for modeling GHG fluxes at finer spatial resolution. …”
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A deep learning-orchestrated garlic routing architecture for secure telesurgery operations in healthcare 4.0 by Kavit Shah, Nilesh Kumar Jadav, Rajesh Gupta, Sucheta Gupta, Sudeep Tanwar, Joel J.P.C. Rodrigues, Fayez Alqahtani, Amr Tolba

“…The proposed architecture is evaluated using different evaluation metrics, such as statistical analysis (training accuracy, training loss, optimizer performance, activation function performance), data compromisation rate (0.346), network throughput (1.44 Mbps), error rate, and latency comparison.…”
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New multifactor spatial prediction method based on Bayesian maximum entropy by YANG Yong, ZHANG Chutian, HE Liyuan

“…The main objective is to incorporate the results of classical geostatistics and quantitative soil-landscape model in the BME framework.The result of ordinary Kriging was taken as the priori probability density function (pdf), as well as the sampling data as hard data, and the results of environmental correlation as soft data. …”
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Sample intensity in ombrophilous open forest at Verde Para Sempre Extractive Reserve, Porto de Moz, PA by Fábio Miranda Leão, Luiz Fernandes Silva Dionisio, Loirena do Carmo Moura Sousa, Marlon Costa de Menezes, Marcelo Henrique Silva de Oliveira, Raphael Lobato Prado Neves

“…Determining the ideal sampling intensity is important to guarantee data closer to reality with less cost and time in the forest inventory. …”
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Abnormal link detection algorithm based on semi-local structure by Haoran SHI, Lixin JI, Shuxin LIU, Gengrun WANG

“…With the research in network science, real networks involved are becoming more and more extensive.Redundant error relationships in complex systems, or behaviors that occur deliberately for unusual purposes, such as wrong clicks on webpages, telecommunication network spying calls, have a significant impact on the analysis work based on network structure.As an important branch of graph anomaly detection, anomalous edge recognition in complex networks aims to identify abnormal edges in network structures caused by human fabrication or data collection errors.Existing methods mainly start from the perspective of structural similarity, and use the connected structure between nodes to evaluate the abnormal degree of edge connection, which easily leads to the decomposition of the network structure, and the detection accuracy is greatly affected by the network type.In response to this problem, a CNSCL algorithm was proposed, which calculated the node importance at the semi-local structure scale, analyzed different types of local structures, and quantified the contribution of edges to the overall network connectivity according to the semi-local centrality in different structures, and quantified the reliability of the edge connection by combining with the difference of node structure similarity.Since the connected edges need to be removed in the calculation process to measure the impact on the overall connectivity of the network, there was a problem that the importance of nodes needed to be repeatedly calculated.Therefore, in the calculation process, the proposed algorithm also designs a dynamic update method to reduce the computational complexity of the algorithm, so that it could be applied to large-scale networks.Compared with the existing methods on 7 real networks with different structural tightness, the experimental results show that the method has higher detection accuracy than the benchmark method under the AUC measure, and under the condition of network sparse or missing, It can still maintain a relatively stable recognition accuracy.…”
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Development and Application of an Intelligent Meterless Electricity Charging Analyzer by CHEN Xing, MAO Heng, CHEN Yawen, WANG Jia, MA Chuang, SHU Shiyu, WENG Jiaming

“…Finally, the developed analyzer was applied to multiple sites and one of them was analyzed. The analysis of the application showed that the error of the traditional metering was 11.7%, and the practical value of the developed meterless electricity charging analyzer was verified by field data.…”
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On nonlinear coupled differential equations for corrugated backward facing step (CBFS) with circular obstacle: AI-neural networking by Khalil Ur Rehman, Wasfi Shatanawi, Weam G. Alharbi

“…ANN has 10 neurons in the hidden layer and is trained with the Levenberg-Marquardt algorithm. Mean square error and regression analysis are performed to validate the model. …”
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A New Method for Measuring Higgs Mass by Berger Thomas, Tian Junping

“…The Higgs mass as one of the fundamental parameters in the Standard Model has been already measured with a precision of 110 MeV with the data collected so far at the LHC. However in some cases of looking for small deviations from the SM, current precision or projection of the Higgs mass measurement at the LHC or HL-LHC may not be enough. …”
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Country governance nexus with the financial stability of banks: The moderating effect of country’s income level by Protap K. GHOSH, Saira B. KHARUDDIN, Fakarudin B. KAMARUDIN

“…To ensure robustness in the estimation, this study uses panel corrected standard error (PCSE) estimation model for the direct and moderating effect analysis. …”
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In Situ Calculation of Spaceflight Magnetometer Coupling Coefficients for Interference Removal Using the Reduction Algorithm for Magnetometer Electromagnetic Noise (RAMEN) by Alex P. Hoffmann, Mark B. Moldwin

“…This process is time‐intensive, costly, and prone to error due to the changing nature of a spacecraft magnetic field environment in operation. …”
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In-situ stress evaluation of coal measures based on logging parameters-A case study of Xishanyao formation in the Southern margin of Junggar basin by Shuai Yang, Xinxin Fang, Yunhong Wang, Fengling Li

“…Abstract Based on acoustic and density logging data, the in-situ stress calculation model is established. …”
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The importance of group-wise registration in tract based spatial statistics study of neurodegeneration: a simulation study in Alzheimer's disease. by Shiva Keihaninejad, Natalie S Ryan, Ian B Malone, Marc Modat, David Cash, Gerard R Ridgway, Hui Zhang, Nick C Fox, Sebastien Ourselin

“…Tract-based spatial statistics (TBSS) is a popular method for the analysis of diffusion tensor imaging data. TBSS focuses on differences in white matter voxels with high fractional anisotropy (FA), representing the major fibre tracts, through registering all subjects to a common reference and the creation of a FA skeleton. …”
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How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…Time series data from 10 subjects walking under 13 conditions, with and without hip exoskeletons, were analyzed. …”
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Trajectory Prediction and Intention Recognition Based on CNN-GRU by Jinghao Du, Dongdong Lu, Fei Li, Ke Liu, Xiaolan Qiu

“…The proposed multi-channel parallel GRU-CNN neural network combines the temporal analysis capabilities of GRU with the spatial feature extraction strengths of CNN through a weight allocation strategy. …”
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Predicting Oil Price Trends During Conflict With Hybrid Machine Learning Techniques by Hicham Boussatta, Marouane Chihab, Mohamed Chiny, Younes Chihab

“…Prior to the war, the models showed strong predictive capabilities, evidenced by low mean-squared error (MSE) values and high coefficients of determination (R2). …”
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Technological Disruption, Ease of Doing Business, and Manufacturing Resilience: A Study of Competitiveness and Efficiency in Developing Countries by Dwi Budi Santoso, Ferry Prasetyia, Trinh Thi Chung, Axellina Muara Setyanti, Nayaka Artha Wicesa, Al Muizzudin Fazaalloh

“…Competitiveness in this study is measured using the concept of Revealed Comparative Advantages (RCA) introduced by Balassa (1965) employing Panel Corrected Standard Error (PCSE) estimation technique. Simultaneously, manufacturing efficiency is gauged utilizing the Data Envelopment Analysis (DEA) method, a nonparametric approach applied to compute the efficiency of a group of decision-making units (DMU). …”
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THE IMPACT OF EXTERNAL SHOCKS ON THE RUSSIAN ECONOMY by M. G. Tiunova

“…The study uses statistical data on the real and financial sectors of the Russian economy, as well as foreign markets for the period 2002–2018. …”
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Inclusion of maintenance energy improves the intracellular flux predictions of CHO. by Diana Széliová, Jerneja Štor, Isabella Thiel, Marcus Weinguny, Michael Hanscho, Gabriele Lhota, Nicole Borth, Jürgen Zanghellini, David E Ruckerbauer, Isabel Rocha

“…In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. …”
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