Machine learning projection of climate and technology impacts on crops key to food security by Dan Li, Vassili Kitsios, David Newth, Terence John O’Kane

“…Here we introduce a multivariate autoregressive econometrics model that includes a time-varying non-linear variable to account for the decreasing impact of technology on crop yields. …”
Get full text

Investigating wave solutions in coupled nonlinear Schrödinger equation: insights into bifurcation, chaos, and sensitivity by Adil Jhangeer, Abdallah M. Talafha, Ariana Abdul Rahimzai, Lubomír Říha

“…The transformation of the coupled partial differential equation into ordinary differential equation is achieved by utilizing a complex wave variable. Exponential function combinations are applied to construct the wave solutions. …”
Get full text

Research on multi-UAV autonomous obstacle avoidance algorithm integrating improved dynamic window approach and ORCA by Xucheng Chang, Jingyu Wang, Kang Li, Xinhui Zhang, Qian Tang

“…Confronted with the difficulty of balancing calculation speed and accuracy in the DWA algorithm, a dynamic time step adjusted according to the environment was designed to weigh the computational efficiency. Aiming at the poor environmental adaptability of the DWA algorithm, a trajectory evaluation function with variable weights was put forward to improve environmental fitness. …”
Get full text

An Intelligent Inspection and Scheduling Algorithm for Integrated Pipe Gallery Based on Cloud Robot by ZHOU Xiwei, SHANG Xiao, SHANG Xinjuan, YAN Maode, WANG Fafa

“…The algorithm has very strong exploring precision and variable function, which makes this algorithm of fewer iterations, and can effectively improve the real-time detection of pipeline leakage source in pipeline corridor. …”
Get full text

Evaluasi Kinerja Aplikasi Penelusuran Online Cerah Informasi Pustaka (CIP) Perpustakaan Universitas Tridinanti Palembang Berdasarkan Persepsi Pustakwan by Rusmiatiningsih Rusmiatiningsih, Indah Solehati, Sagiman Sagiman, Marleni Marleni

“…The evaluation model used is the PIECES evaluation model by making a questionnaire based on 6 variables, namely Performance, Information, Economy, Control, Efficiency and Service and each variable is made into indicators. …”
Get full text

Modelling Geographically Weighted Truncated Spline Regression Using Maximum Likelihood Estimation for Human Development Disparities by Laode Muhammad Saris, Henny Pramoedyo, Adji Achmad Rinaldo Fernandes

“…Among these, the Bi-Square weighting function performed the best, achieving a coefficient of determination of 99.999%, demonstrating the model’s capability to explain nearly all data variability effectively. …”
Get full text

Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis-Study of Treatment’s Echocardiographic Mechanisms (CLOVERS-STEM) by Michael J. Lanspa, MD, Akram Khan, MD, Patrick G. Lyons, MD, Michelle N. Gong, MD, Ali A. Naqvi, MD, Siddharth Dugar, MD, Abhijit Duggal, MD, Nicholas J. Johnson, MD, Jacob H. Schoeneck, MD, Lane Smith, MD, PhD, Somnath Bose, MD, MPH, Nathan I. Shapiro, MD, Tatyana Shvilkina, DO, Danielle Groat, MStat, Jason R. Jacobs, PhD, Troy D. Olsen, RCDS, Steven Cannavina, RCDS, Daniel B. Knox, MD, Eliotte L. Hirshberg, MD, Wesley H. Self, MD, Samuel M. Brown, MD

“…Receipt of fluid and vasopressors, common treatments in septic shock, may affect cardiac function. OBJECTIVES:. We sought to determine whether a liberal or restrictive fluid resuscitation strategy was associated with changes in cardiac function. …”
Get full text

Process engineering by Ahmed Mohamed Farid Shaaban, Azza Ibrahim Hafez, Mona Amin Abdel-Fatah, Nabil Mahmoud Abdel-Monem, Mohamed Hanafy Mahmoud

“…The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number. …”
Get full text

The performance of 76 kHz positional acoustic telemetry is challenged by acoustic conditions in the tailrace of a hydroelectric dam by C. Ryan Hill, Antóin M. O’Sullivan, R. Allen Curry, Tommi Linnansaari, Philip M. Harrison

“…Performance improved marginally for the second array (i.e., 200–500 m downstream), but position efficiency was ultimately low (1%), variable across transmitter locations, and negatively correlated with discharge. …”
Get full text

Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
Get full text

Locomotive Syndrome Digital Therapeutics Provided via a Smartphone App: Protocol for a Single-Group Trial by Tatsuru Sonobe, Yoshihiro Matsumoto

“…We evaluated the participants’ objective motor function using the timed up and go (TUG) test, and we compare the results using a 3-way ANOVA with the TUG test at the 3 evaluation time points as the dependent variable. …”
Get full text

Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm by Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak

“…The resulting objective function is highly nonlinear and complex. To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. …”
Get full text

Association between Oral Health Status and Diabetic Nephropathy-Related Indices in Japanese Middle-Aged Men by Masami Yoshioka, Yoshifumi Okamoto, Masahiro Murata, Makoto Fukui, Shizuko Yanagisawa, Yasuhiko Shirayama, Kojiro Nagai, Daisuke Hinode

“…Logistic regression analysis using eGFR as a dependent variable and age, CPI score, body mass index, HbA1c, and neutral fat as independent variables suggested that low eGFR (<60) could be attributed to CPI score (OR=3.169, 95% CI: 1.031–9.742, p=0.044). …”
Get full text

EM Algorithm in the Modified Slash Power Maxwell Distribution with an Application by Francisco A. Segovia, Yolanda M. Gómez, Héctor J. Gómez, Inmaculada Barranco-Chamorro, Héctor W. Gómez

“…We study its probability density function and some properties, such as moments, asymmetry and kurtosis coefficient. …”
Get full text

Path following control of underground mining articulated vehicle based on the preview control method by MENG Yu, GAN Xin, BAI Guo-xing

“…The path following control system is a multi-variable, multi-constraint system. There are optimization problems under multiple constraints as well as challenges such as actuator saturation during the control process. …”
Get full text

Root‐Zone Water‐Storage Capacity and Uncertainty: An Intrinsic Factor Affecting Agroecosystem Resilience to Drought by Nunzio Romano, Caterina Mazzitelli, Paolo Nasta

“…Root‐zone water‐storage capacity (SR) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. …”
Get full text

Optimization of Material Flow and Product Allocation in Inter-Unit Operations: A Case Study of a Refrigerator Manufacturing Facility by Selman Karagoz, Yasin Karagoz

“…<i>Background</i>: Logistics operations are integral to manufacturing systems, particularly in the transportation processes that occur not only between facilities and stakeholders but also between warehouses and workstations within a facility. The design of functional areas and allocating goods to appropriate zones within the warehouse management system (WMS) are critical activities that substantially influence the efficiency of manufacturing logistics operations. …”
Get full text

Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

“…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
Get full text

Fast Möbius transform: An algebraic approach to information decomposition by Abel Jansma, Pedro A. M. Mediano, Fernando E. Rosas

“…The partial information decomposition (PID) and its extension integrated information decomposition (ΦID) are promising frameworks to investigate information phenomena involving multiple variables. An important limitation of these approaches is the high computational cost involved in their calculation. …”
Get full text

Utilizing a Transient Electromagnetic Inversion Method with Lateral Constraints in the Goaf of Xiaolong Coal Mine, Xinjiang by Yingying Zhang, Bin Xie, Xinyu Wu

“…Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. …”
Get full text