Prevention and Management of Spinal Cord Ischemia After Aortic Surgery: An Umbrella Review by Alexandros G. Brotis, Adamantios Kalogeras, Metaxia Bareka, Eleni Arnaoutoglou, Kostas Spanos, Miltiadis Matsagkas, Kostas N. Fountas

“…The prompt management of spinal cord complications is crucial to optimizing outcomes. No clear treatment algorithm has been universally adopted. …”
Get full text

Evaluating the impact of deep learning approaches on solar and photovoltaic power forecasting: A systematic review by Oussama Khouili, Mohamed Hanine, Mohamed Louzazni, Miguel Angel López Flores, Eduardo García Villena, Imran Ashraf

“…Accurate solar and photovoltaic (PV) power forecasting is essential for optimizing grid integration, managing energy storage, and maximizing the efficiency of solar power systems. …”
Get full text

Capabilities of BIOMASS Three-Baseline PolInSAR Mode for the Characterization of Tropical Forests by Yanzhou Xie, Laurent Ferro-Famil, Yue Huang, Thuy Le Toan, Jianjun Zhu, Haiqiang Fu, Peng Shen

“…Second, the forest height was retrieved using a three-baseline algorithm based on polarimetric coherence optimization with multi-baseline joint diagonalization. …”
Get full text

Ultra-Low Dose Computed Tomography Imaging in Quantifying Bone Trauma and Disorders: A Cross-Sectional Study by Fariba Zarei, Seyedeh Marzieh Ahmadi, Saber Dehbani-Zadeh, Anahita Jafari, Vyas Akondi, Sabyasachi Chatterjee, Seyed Alireza Mirhosseini, Rezvan Ravanfar Haghighi

“…Background: X-ray computed tomography (CT) is a standard tool for diagnosing bone abnormalities. CT dose optimization is strongly recommended, due to the stochastic effects of x-ray. …”
Get full text

Gap-filling of land surface temperature in arid regions by combining Landsat 8 and 9 imageries by Fahime Arabi Aliabad, Ebrahim Ghaderpour, Ahmad Mazidi, Fatemeh Houshmandzade

“…The aims of this research are to determine the optimal parameters for the reconstruction of Landsat-LST images, required in many applications, by the harmonic analysis of time series algorithm (HANTS) and to investigate the possibility of improving LST reconstruction accuracy using Landsat 8 and 9 images simultaneously. …”
Get full text

Unsupervised Learning for Distributed Downlink Power Allocation in Cell-Free mMIMO Networks by Mattia Fabiani, Asmaa Abdallah, Abdulkadir Celik, Omer Haliloglu, Ahmed M. Eltawil

“…The proposed unsupervised learning approach circumvents the arduous task of training data computations, typically required in supervised learning methods, bypassing the use of conventional complex optimization methods and heuristic methodologies. Furthermore, an LSF-based radio unit (RU) selection algorithm is employed to activate only the contributing RUs, allowing efficient utilization of network resources. …”
Get full text

An Enhanced Deep Neural Network Approach for WiFi Fingerprinting-Based Multi-Floor Indoor Localization by Shehu Lukman Ayinla, Azrina Abd Aziz, Micheal Drieberg, Misfa Susanto, Afidalina Tumian, Mazlaini Yahya

“…The CV process is repeated multiple times to assess the RFE’s generalization ability for optimal feature selection, and the BN algorithm is integrated into each layer of the DNN to ensure consistent activation value distribution and stabilization of the training process. …”
Get full text

Evaluation of Shelf Life Prediction for Broccoli Based on Multispectral Imaging and Multi-Feature Data Fusion by Xiaoshuo Cui, Xiaoxue Sun, Shuxin Xuan, Jinyu Liu, Dongfang Zhang, Jun Zhang, Xiaofei Fan, Xuesong Suo

“…Savitzky–Golay (SG) convolution smoothing and standard normal variate (SNV) and normalization (Norm) preprocessing methods were employed to preprocess the original spectral data and textural features, while a successive projection algorithm (SPA) was used to extract relevant feature bands. …”
Get full text

Deepfake Face Detection and Adversarial Attack Defense Method Based on Multi-Feature Decision Fusion by Shanzhong Lei, Junfang Song, Feiyang Feng, Zhuyang Yan, Aixin Wang

“…Ultimately, the model’s robustness was validated by generating adversarial samples using the I-FGSM algorithm and optimizing model performance through adversarial training. …”
Get full text

A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
Get full text

Photovoltaic Farm Power Generation Forecast Using Photovoltaic Battery Model with Machine Learning Capabilities by Agboola Benjamin Alao, Olatunji Matthew Adeyanju, Manohar Chamana, Stephen Bayne, Argenis Bilbao

“…To address these limitations, the proposed model integrates an Adaptive Neuro-Fuzzy Inference System (ANFIS) with a multi-input multi-output (MIMO) prediction algorithm, utilizing historical temperature and irradiance data for accurate and efficient forecasting. …”
Get full text

Characterization of Irrigated Rice Cultivation Cycles and Classification in Brazil Using Time Series Similarity and Machine Learning Models with Sentinel Imagery by Andre Dalla Bernardina Garcia, Ieda Del’Arco Sanches, Victor Hugo Rohden Prudente, Kleber Trabaquini

“…The processing of input data and exploratory analysis were performed using a clustering algorithm based on Dynamic Time Warping (DTW), with K-means applied to the time series. …”
Get full text

Variable-Rate Nitrogen Application in Wheat Based on UAV-Derived Fertilizer Maps and Precision Agriculture Technologies by Alexandros Tsitouras, Christos Noulas, Vasilios Liakos, Stamatis Stamatiadis, Miltiadis Tziouvalekas, Ruijun Qin, Eleftherios Evangelou

“…Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. …”
Get full text

Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Ablation studies confirm LDSNet-ELA integration reduces false positives by 27.6%, while the enhanced loss function system improves small-object recall by 19.4%. …”
Get full text

Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis by Zhengxiao Wei, Jinyu Chen, Xue Mei, Yi Yu

“…Preliminary logistic regression identified three PFAS compounds (perfluorooctanoic acid [PFOA], perfluorooctane sulfonic acid [PFOS], and 2-(N-methyl-PFOSA) acetate acid [MPAH]) as significantly associated with mortality in the diabetic population. The optimal cut-off values for PFOS, PFOA, and MPAH were determined using the X-tile algorithm, and participants were categorized into high- and low-exposure groups. …”
Get full text

Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…The review method includes an in-depth analysis of algorithm performance using key metrics such as accuracy, precision, recall, and F1 score across various datasets. …”
Get full text

Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…While our model is built on a typical CNN architecture, we make significant advances by using preprocessing techniques and hyperparameter tuning. …”
Get full text

High-Quality Short-Range Radar Imaging with Coprime Sampling by Yaping Wang, Tianjiao Zeng, Xu Zhan, Xiangdong Ma, Mou Wang, Jun Shi, Shunjun Wei, Xiaoling Zhang

“…Our approach is built upon three core perspectives: (1) physical sampling: we adopt a coprime pattern to form an extended sampling aperture with a structured layout, enabling effective utilization of limited channels and minimizing aperture loss; (2) signal measurement: we utilize the second-order statistics of the measured data to generate additional equivalent measurements, thus enhancing the system’s capability to capture diverse spatial information; and (3) scene reconstruction: we establish a novel forward measurement model, linking these equivalent measurements to the scene, and then formulate a sparsity-regularized optimization problem. We design a background-texture-preserving, target-enhanced resolving method based on the first-order proximal gradient algorithm to achieve robust and high-quality imaging results. …”
Get full text

Outcomes among children and adults at risk of severe dengue in Sri Lanka: Opportunity for outpatient case management in countries with high disease burden. by Champica K Bodinayake, Ajith DeS Nagahawatte, Vasantha Devasiri, Niroshana J Dahanayake, Gaya B Wijayaratne, Nayani P Weerasinghe, Madureka Premamali, Tianchen Sheng, Bradly P Nicholson, Harshanie A Ubeysekera, Ruvini Mp Kurukulasooriya, Aruna D de Silva, Truls Østbye, Christopher W Woods, L Gayani Tillekeratne

“…<h4>Conclusions</h4>One-half of patients hospitalized with acute dengue progressed to develop DHF and a very small number developed DSS or severe dengue. Developing an algorithm for triaging patients to ambulatory versus inpatient management should be the future goal to optimize utilization of healthcare resources in dengue-endemic countries.…”
Get full text

Research on ecological management zoning in Jilin Province based on a human well-being framework by Baihao Zhang, Jiafu Liu, Zhenyu Zhang, Yu Zhu

“…To further delineate ecological management zones, the SC K-means clustering algorithm and the coupling coordination degree model are employed. …”
Get full text