Isolation and characterization of Pseudomonas phage HJ01 and its therapeutic efficacy in canine pyoderma by Yixian Wei, Ziyong Li, Jianlong Lao, Jijie Huang, Hailin Chen, Jiajia Li, Yayu Deng, Xinyu Mao, Runwen Ma, Yuxing Wu, Yizhou Tan, Xun Li, Yangqing Lu, Shunjin Jiang, Xiaoye Wang

“…Results The host strain GDPA-01 exhibited multidrug resistance, with a 75% resistance gene detection rate, and harbored virulence genes such as exoU and exoT. …”
Get full text

Polyhydramnios at Term in Gestational Diabetes: Should We Be Concerned? by Mercedes Horcas-Martín, Tania Luque-Patiño, Claudia Usandizaga-Prat, Elena Díaz-Fernández, Victoria Melero-Jiménez, Luis Vázquez-Fonseca, Francisco Visiedo, José Román Broullón-Molanes, Rocío Quintero-Prado, Fernando Bugatto

“…We aim to study the implications of polyhydramnios in term pregnancies complicated with gestational diabetes mellitus (GDM). <b>Methods:</b> A prospective cohort study including 340 GDM cases was conducted. …”
Get full text

High-throughput screening of monoclonal antibodies against carbapenemases using a multiplex protein microarray platform by Sascha D. Braun, Sascha D. Braun, Martin Reinicke, Martin Reinicke, Celia Diezel, Celia Diezel, Elke Müller, Elke Müller, Katrin Frankenfeld, Thomas Schumacher, Hugo Arends, Stefan Monecke, Stefan Monecke, Ralf Ehricht, Ralf Ehricht, Ralf Ehricht

“…Given the urgent clinical need for rapid diagnostics, immunochromatographic assays represent a promising and urgently needed approach for economic and available point-of-care detection. However, the development of such assays is often hindered by the time-consuming process of identifying high-affinity antibody pairs.MethodsTo accelerate this process, we evaluated a protein microarray platform as a high-throughput screening tool to identify optimal monoclonal antibody (mAb) pairs targeting the most clinically relevant carbapenemases. …”
Get full text

Acoustic virtual sensors for industrial process monitoring using non-negative matrix factorization by Clara Luzon-Alvarez, Maximo Cobos, Jesus Lopez-Ballester, Ana M. Torres-Aranda, Francesc J. Ferri

“…By decomposing acoustic signals captured from machinery into distinct spectral components, the proposed method enables the detection of specific operational phases and potential anomalies. …”
Get full text

A Microplate-Based Nonradioactive Protein Synthesis Assay: Application to TRAIL Sensitization by Protein Synthesis Inhibitors. by Curtis J Henrich

“…Non-radioactive assays based on incorporation of puromycin into newly synthesized proteins and subsequent detection using anti-puromycin antibodies have been previously reported and well-validated. …”
Get full text

Use of UAVs to assess fire hazard of areas adjacent to trunk pipelines by Sharafutdinov Azat, Abdullin Nail, Balyklov Alexander, Akhmetkhafizov Aydar

“…The relevance and importance of the problem of environmental monitoring through innovative methods, including the use of unmanned aerial vehicles, is beyond doubt. …”
Get full text

A Developed Colorimetric Assay Using Unmodified Gold Nanoparticles for the Identification of Acinetobacter baumannii Isolates from Different Clinical Samples by Mohamed M. Sehree, Amani M. Al-Kaysi, Hanaa N. Abdullah

“…Detection and optimization of A. baumannii amplicons using unmodified AuNPs were performed based on species-specific DNA oligonucleotide. …”
Get full text

Porous cobalt oxide nanorods-like-based material as an effective electrochemical glucose sensor by Trung-Tan Tran, Gia-Tuyen Phan, Tan-Dat Nguyen, Hoang-Phat Nguyen, Ha-Nhat-Nghi Pham, Van Hoang Luan, Minh-Vien Le

“…The shape and morphology of nanostructures play a crucial role in determining their electrochemical performance, offering a promising strategy for enhancing glucose sensing capabilities through structural optimization. In this study, a novel three-dimensional porous cobalt oxide (Co₃O₄) nanorod-like structure was synthesized via a facile hydrothermal method and investigated as an efficient catalyst for glucose detection. …”
Get full text

Composite fault feature extraction for gears based on MCKD-EWT adaptive wavelet threshold noise reduction by Yanchang LV, Jingyue Wang, Chengqiang Zhang, Jianming Ding

“…Aiming at fault feature extraction and separation, an adaptive threshold denoising fault detection method based on Maximum correlated kurtosis deconvolution (MCKD) and Empirical wavelet transform (EWT) is proposed. …”
Get full text

Challenges and Opportunities for Atrial Fibrillation Management by Minsi Cai, Jordi Heijman, Hanjia Gao

“…However, numerous challenges in AF management remain at the disease, patient, and population levels, including an incomplete understanding of basic mechanisms that can be clinically targeted; heterogenous progressive natural history; poor correlation between rhythm and symptoms/outcomes; as well as suboptimal detection methods and treatment options. Recent advances in disease perception in combination with modern monitoring devices, state-of-the art computational models, and novel antiarrhythmic drugs and ablation strategies can contribute to addressing these issues, ultimately leading to a paradigm shift in AF diagnosis, classification, and treatment. …”
Get full text

Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…The dataset was preprocessed using the Standard Scaler to standardize it, ensuring each feature has a mean of zero and a standard deviation of one, followed by outlier detection with Cook’s distance. Hyperparameter optimization made using the Differential Evolution (DE) method improved the performance of models. …”
Get full text

Frequency hopping modulation recognition based on time-frequency energy spectrum texture feature by Hongguang LI, Ying GUO, Ping SUI, Zisen QI

“…For frequency hopping modulation identification,a novel method based on time-frequency energy spectrum texture feature was proposed.Firstly,the time-frequency diagram of the frequency hopping signal was obtained by smoothed pseudo Wigner-Ville distribution,and the background noise of the time-frequency diagram was removed by two-dimensional Wiener filtering to improve the resolution of the time-frequency diagram under low SNR conditions.Then,the connected-domain detection algorithm was used to extract the time-frequency energy spectrum of each hop signal and convert it into a time-frequency gray-scale image.The histogram statistical features and the gray-scale co-occurrence matrix feature were combined to form a 22-dimensional eigenvector.Finally,the feature set was trained,classified and identified by optimized support vector machine classifier.Simulation experiments show that the multi-dimensional feature vector extracted by the algorithm has strong representation ability and avoids the misjudgment caused by the similarity of single features.The average recognition accuracy of the six modulation methods of frequency hopping signals BPSK,QPSK,SDPSK,QASK,64QAM and GMSK is 91.4% under the condition of -4 dB SNR.…”
Get full text

Clinical Application of Artificial Intelligence in Breast MRI by Jong-Min Kim, Su Min Ha

“…AI-based segmentation methods enable accurate tumor detection and characterization, thereby aiding personalized treatment planning. …”
Get full text

Classification of Oil Loss Levels in Palm Oil Processing Using Near-Infrared Spectroscopy with Machine Learning by Muhamad Ilham Fauzan, Jaka Adi Baskara, Wahyuningdiah Trisari Harsanti Putri, Quintin Kurnia Dikara

“…The results of the study indicate that applying machine learning methods to FOSS-NIRS data can enhance the accuracy of oil loss classification, making it a potential solution for broader implementation in the palm oil processing industry to optimize production efficiency.   …”
Get full text

Synergistic Multi-Granularity Rough Attention UNet for Polyp Segmentation by Jing Wang, Chia S. Lim

“…To address these issues, we propose the Synergistic Multi-Granularity Rough Attention U-Net (S-MGRAUNet), which integrates three key modules: the Multi-Granularity Hybrid Filtering (MGHF) module for extracting multi-scale contextual information, the Dynamic Granularity Partition Synergy (DGPS) module for enhancing polyp-background differentiation through adaptive feature interaction, and the Multi-Granularity Rough Attention (MGRA) mechanism for further optimizing boundary recognition. Extensive experiments on the ColonDB and CVC-300 datasets demonstrate that S-MGRAUNet significantly outperforms existing methods while achieving competitive results on the Kvasir-SEG and ClinicDB datasets, validating its segmentation accuracy, robustness, and generalization capability, all while effectively reducing computational complexity. …”
Get full text

Automatic motion recognition technology based on fuzzy clustering algorithm and VR video image by Ganbin Xu, Jianwei Lin

“…Current dynamic video segmentation methods emphasize iterative pixel-level classification based on fuzzy membership levels. …”
Get full text

Study of the survival of patients with head and neck cancer in relation to Circulating Tumor Cells (CTCs). by Romina Mastronicola, Elise Kayser, Pauline Le Roux, Agathe Barrat, Alexandre Aubertin, Aurore Casse, Léa Nominé, Hélèna Villard, Sophie Cortese, Emilie Beulque, Jean-Louis Merlin, Gilles Dolivet

“…This study aimed at comparing two methods (Reverse Transcription-Polymerase Chain Reaction and CellSearch) to detect circulating tumor cells (CTC) as a prognosticator. …”
Get full text

Autoregressive Neural Network for Cloud Concentration Forecast from Hemispheric Sky Images by Cristian Crisosto

“…Secondly, a new image-processing algorithm is suggested to optimize the cloud detection process starting with the Haze Index. …”
Get full text

Effective and fair cognitive terminal assignment scheme for cooperative spectrum sensing by WU Zhiqiang, LIU Qianli, LIU Jiabin, FENG Qing, XIAO Shanpeng, LIU Shang

“…The node allocation strategy during the spectrum detection process was directly determined by the results of joint spectrum sensing. …”
Get full text

OCTAVA: An open-source toolbox for quantitative analysis of optical coherence tomography angiography images. by Gavrielle R Untracht, Rolando S Matos, Nikolaos Dikaios, Mariam Bapir, Abdullah K Durrani, Teemapron Butsabong, Paola Campagnolo, David D Sampson, Christian Heiss, Danuta M Sampson

“…We present each analysis step, including optimization of filtering and choice of segmentation algorithm, and definition of metrics. …”
Get full text