A pragmatic mixing model for the evaluation of powder flow properties of multicomponent pharmaceutical blends by Daniel Yanes, Rachael Shinebaum, Georgios Papakostas, Gavin K. Reynolds, Sadie M.E. Swainson

“…Traditionally, understanding flow properties has required testing large amounts of material, particularly when evaluating formulation options. This has led to research into developing predictive flow models to reduce experimental burden. …”
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Evaluating the strength of industrial wastesbased concrete reinforced with steel fiber using advanced machine learning by Kennedy C. Onyelowe, Viroon Kamchoom, Ahmed M. Ebid, Shadi Hanandeh, Susana Monserrat Zurita Polo, Vilma Fernanda Noboa Silva, Rodney Orlando Santillán Murillo, Rolando Fabián Zabala Vizuete, Paul Awoyera, Siva Avudaiappan

“…Also, accuracies of developed models were evaluated by comparing sum of squared error (SSE), mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), Error (%), Accuracy (%) and coefficient of determination (R2), correlation coefficient (R), willmott index (WI), Nash–Sutcliffe efficiency (NSE), Kling–Gupta efficiency (KGE) and symmetric mean absolute percentage error (SMAPE) between predicted and calculated values of the output. …”
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Development of a stand for measuring thrust of micro-jet thrusters based on machine vision by V. V. Fedyanin, V. V. Shalay, P. S. Yachmenev, I. S. Vavilov

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Investigating the Effect of Different Concentrations of Organic Acids (Ascorbic, Citric, Malic, and Tartaric) on the Viscosity and Rheological Properties of Balangu Seed Gum by Fakhreddin Salehi, Maryam Tashakori, Kimia Samary

“…The Power law model had a good performance with the highest correlation coefficient (>0.9406) and least sum of squared error (<0.0090) and root mean square error (<0.0275) for all samples. …”
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A neural network-based model for assessing 3D printable concrete performance in robotic fabrication by Weijiu Cui, Dongsheng Ji, Liang Shen, Shiyong Su, Xinyu Shi, Jidong Liu, Zirui Bai, Yubo Sun, Jian Gong, Yaxin Tao

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Improved Power Budget of 112 Gb/s/<inline-formula><tex-math notation="LaTeX">$\lambda$</tex-math></inline-formula> Intra-Datacentre Links Using a Split-Carrier Transmitter Architec... by Thomas Gerard, Zhixin Liu, M. Sezer Erkilinc, Lidia Galdino, Polina Bayvel, Benn Thomsen, Domanic Lavery

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Physics-informed machine learning to predict solvatochromic parameters of designer solvents with case studies in CO2 and lignin dissolution by Mood Mohan, Nikhitha Gugulothu, Sreelekha Guggilam, T. Rajitha Rajeshwar, Michelle K. Kidder, Jeremy C. Smith

“…The polarity of solvents plays a critical role in various research applications, particularly in their solubilities. …”
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Machine learning assisted design of low-carbon aluminosilicate cementitious composites with diverse raw materials and target mechanical strength by Jinyang Jiang, Yi Liu, Junlin Lin, Tao Yang, Fengjuan Wang

“…Furthermore, the influences of various factors on the strength of composites are systematically analyzed through detailed interpretation of machine learning model. This research provides an effective alternative for the development of cementitious composites with diverse calcium/silicon/aluminum-rich materials and multi-objective performances.…”
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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

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The effect of training data size on real-time respiration prediction using long short-term memory model by Wenzheng Sun, Jun Dang, Lei Zhang, Qichun Wei, Chao Li, Ye Liu, Huang Jing, Kanghua Huang, Yuanpeng Zhang, Bing Li

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Remotely sensed estimation and mapping of soil moisture by eliminating the effect of vegetation cover by Cheng-yong WU, Guang-chao CAO, Ke-long CHEN, Chong-yi E, Ya-hui MAO, Shuang-kai ZHAO, Qi WANG, Xiao-yi SU, Ya-lan WEI

“…The accuracy of the bare soil albedo model (root mean square error=4.20, mean absolute percent error=22.75%, and theil inequality coefficient=0.67) was higher than that of the existing surface albedo model (root mean square error=4.66, mean absolute percent error=25.46% and theil inequality coefficient=0.74). …”
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Cosmic Chronometers, Pantheon+ Supernovae, and Quasars Favor Coasting Cosmologies over the Flat ΛCDM Model by Peter Raffai, Adrienn Pataki, Rebeka L. Böttger, Alexandra Karsai, Gergely Dálya

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Online Monitoring Method for Opening and Closing Time of 10 kV Spring Energy Storage Circuit Breaker Based on Transient Electrical Signal Characteristic Point Marking and Self-Cali... by Liting Weng, Jiangtao Xiao, Zhaochuang Zhang, Jingang Wang, Yuchuan Wen, Fan Zhang, Xingyu Zhang, Lingyi Ma, Pengcheng Zhao

“…The comparison results show that this method has good stability, and the calculation error is controlled within 1% after self-calibration, which provides a new idea for the online monitoring research of the mechanical characteristics of spring energy storage vacuum circuit breakers.…”
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Unraveling overestimated exposure risks through hourly ozone retrievals from next-generation geostationary satellites by Siwei Li, Ge Song, Jia Xing, Jiaxin Dong, Maolin Zhang, Chunying Fan, Shiyao Meng, Jie Yang, Lechao Dong, Wei Gong

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A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors by Ahmad Aminzadeh, Sasan Sattarpanah Karganroudi, Soheil Majidi, Colin Dabompre, Khalil Azaiez, Christopher Mitride, Eric Sénéchal

“…This paper presents the deployment of such an integration on an industrial air compressor unit. This research combines updated concepts from the Internet of Things, machine learning, multi-sensor data collection, structured data mining, and cloud-based data analysis. …”
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Real-Time High-Resolution Global PWV Retrieval Based on Weather Forecast Foundation Models and Cross-Validation With Radiosonde, GNSS, and ERA5 by Junsheng Ding, Wu Chen, Junping Chen, Jungang Wang, Yize Zhang, Lei Bai

“…High-quality precipitable water vapor (PWV) plays a vital role in climate change and weather prediction studies. This research introduces a novel scheme for retrieving high-resolution surface-domain PWV with real-time and forecasting capabilities with global coverage, utilizing weather forecast foundation models represented by Huawei Cloud Pangu-Weather, Google DeepMind GraphCast, and Shanghai AI Lab FengWu. …”
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Role of Visual Saliency in Video Quality Assessments by Syeda Eesha-Tir-Razia, Qaisar Abbas, Imran Fareed Nizami, Adil Ali Raja, Mutlaq B. Aldajani, Mudasir Wahab, Tallha Akram, Sadiq Ahmad

“…With the growing reliance on video-based applications such as streaming, virtual reality, and video conferencing, video quality assessment (VQA) has become crucial. This research investigates the role of Global Contrast-Based Visual Saliency in VQA and proposes two methodologies: 1) feature extraction using Visual Saliency, 2) Visual Saliency combined with Feature Extraction and Feature Selection. …”
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Deep Learning Python-Based Time-Series Model for Oil Palm Yield Prediction by Yuhao Ang, Helmi Zulhaidi Mohd Shafri, Yang Ping Lee, Shahrul Azman Bakar, Haryati Abidin, Mohd Umar Ubaydah Mohd Junaidi, Hwee San Lim, Rosni Abdullah, Yusri Yusup, Syahidah Akmal Muhammad, Teh Sin Yin

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Quantitative Analysis of 3-Monochloropropane-1,2-diol in Fried Oil Using Convolutional Neural Networks Optimizing with a Stepwise Hybrid Preprocessing Strategy Based on Fourier Tra... by Xi Wang, Siyi Wang, Shibing Zhang, Jiping Yin, Qi Zhao

“…As one kind of ‘probable human carcinogen’ (Group 2B) compound classified by the International Agency for Research on Cancer, 3-MCPD is mainly formed during the thermal processing of food. …”
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A novel reconstruction-based video anomaly detection with idempotent generative network by Wenmin Dong, Lifeng Zhang, Wenjuan Shi, Xiangwei Zheng, Yuang Zhang

“…Reconstruction-based VAD has received increasing research attention, but faces challenges such as missing anomalies for the reconstruction error as a criterion, and information loss when suppressing anomalous data, existing methods also struggle to detect unseen anomalies. …”
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