Browse Articles

Enhancing concealed object detection in active THz security images with adaptation-YOLO

Abstract The terahertz (THz) security scanner offers advantages such as non-contact inspection and the ability to detect various types of dangerous goods, playing an important role in preventing terrorist attacks. We aim to accurately and quickly detect concealed objects in THz security images. However, current object detection algorithms face many challenges when applied to THz images. The main reasons for the detection difficulty are that the concealed objects are small, the image resolution is low, and there is back-ground noise. Many methods often ignore the contextual dependency of the objects, hindering the effective capture of the object’s features. To address this task, this paper first proposes an adaptive context-aware attention network (ACAN), which models global contextual association features in both spatial and channel dimensions. By dynamically combining local features and their global relationships, contextual association information can be obtained from the input features, and enhanced attention features can be achieved through feature fusion to enable precise detection of concealed objects. Secondly, we improved the adaptive convolution and developed the dynamic adaptive convolution block (DACB). DACB can adaptively adjust convolution filter parameters and allocate the filters to the corresponding spatial regions, then filter the feature maps to suppress interference information. Finally, we integrated these two components to YOLOv8, resulting in Adaptation-YOLO. Through wide-ranging experiments on the active THz image dataset, the results demonstrate that the suggested method effectively improves the accuracy and efficiency of object detectors.

Sleep and cardiorespiratory function assessed by a smart bed over 10 weeks post COVID-19 infection

CuTCP: Custom Text Generation-based Class-aware Prompt Tuning for visual-language models

A biomechanical study of locking spongious screws and failure rates are higher than expected in plate fixation

PLK3 weakens antioxidant defense and inhibits proliferation of porcine Leydig cells under oxidative stress

Sustainable application of waste gangue mortar in coal mine tunnel support

Community science as a potential tool to monitor animal demography and human-animal interactions

Renal anemia and hyporesponsiveness to ESA for preservation of residual kidney function in patients undergoing peritoneal dialysis

Comprehensive evaluation of pure and hybrid collaborative filtering in drug repurposing

Abstract Drug development is known to be a costly and time-consuming process, which is prone to high failure rates. Drug repurposing allows drug discovery by reusing already approved compounds. The outcomes of past clinical trials can be used to predict novel drug-disease associations by leveraging drug- and disease-related similarities. To tackle this classification problem, collaborative filtering with implicit feedback (and potentially additional data on drugs and diseases) has become popular. It can handle large imbalances between negative and positive known associations and known and unknown associations. However, properly evaluating the improvement over the state of the art is challenging, as there is no consensus approach to compare models. We propose a reproducible methodology for comparing collaborative filtering-based drug repurposing. We illustrate this method by comparing 11 models from the literature on eight diverse drug repurposing datasets. Based on this benchmark, we derive guidelines to ensure a fair and comprehensive evaluation of the performance of those models. In particular, an uncontrolled bias on unknown associations might lead to severe data leakage and a misestimation of the model’s true performance. Moreover, in drug repurposing, the ability of a model to extrapolate beyond its training distribution is crucial and should also be assessed. Finally, we identified a subcategory of collaborative filtering that seems efficient and robust to distribution shifts. Benchmarks constitute an essential step towards increased reproducibility and more accessible development of competitive drug repurposing methods.

Retraction Note: Novel magnetic organic–inorganic hybrids based on aromatic polyamides and ZnFe2O4 nanoparticles with biological activity

Time series forecasting of bed occupancy in mental health facilities in India using machine learning

Assessment of walnut (Juglans regia L.) cultivation land suitability using a multiple-criteria decision-making method in Southeastern Turkey

Liquid crystal torons in Poiseuille-like flows

Retraction Note: Enhancing MPPT performance for partially shaded photovoltaic arrays through backstepping control with Genetic Algorithm-optimized gains

A hybrid human fall detection method based on modified YOLOv8s and AlphaPose

The value of increasing sequencing depth for noninvasive prenatal screening for whole chromosomal aneuploidy

First principles design of multifunctional spintronic devices based on super narrow borophene nanoribbons

College students’ entrepreneurship education path and management strategy of start-up enterprises using causal attribution theory

Association between extracellular DNA levels, markers of inflammation and left ventricular mass index in children with chronic kidney disease

Abstract Chronic kidney disease (CKD) is associated with chronic low-grade inflammation, but the primary factors triggering this inflammation remain unclear. Extracellular or cell-free DNA (exDNA) originates from virtually all tissues, being released during cell death, and stimulates the innate immune system. Our study was designed as an observational, cross-sectional cohort study of children with CKD (both before and after kidney transplantation) and controls to analyze associations between exDNA, markers of inflammation, and cardiovascular health. Extracellular DNA (total, nuclear, and mitochondrial) was analyzed in plasma using fluorometry and real-time PCR. We found that children with CKD after kidney transplantation had higher concentrations of total and nuclear extracellular DNA (total exDNA and nc_exDNA) in plasma compared to controls. In univariate analysis, levels of interleukin-6 (IL-6), antimicrobial peptide cathelicidin (LL-37), soluble vascular cell adhesion molecule-1 (VCAM-1) and left ventricular mass index (LVMI) were positively correlated with total exDNA and nc_exDNA concentrations. Multivariate analysis revealed LVMI as the only independent variable associated with high levels of both total exDNA and nc_exDNA. We believe that our results contribute new knowledge to the pathogenesis of CKD and its complications and may help identify new treatment targets.

The impact of major congenital anomalies on obstetric outcomes in the United Arab Emirates: the Mutaba’ah Study