The detection of objects concealed under people's clothing is a very challenging task, which has crucial applications for security.  https://www.selleckchem.com/PI3K.html  When testing the human body for metal contraband, the concealed targets are usually small in size and are required to be detected within a few seconds. Focusing on weapon detection, this paper proposes using a real-time detection method for detecting concealed metallic weapons on the human body applied to passive millimeter wave (PMMW) imagery based on the You Only Look Once (YOLO) algorithm, YOLOv3, and a small sample dataset. The experimental results from YOLOv3-13, YOLOv3-53, and Single Shot MultiBox Detector (SSD) algorithm, SSD-VGG16, are compared ultimately, using the same PMMW dataset. For the perspective of detection accuracy, detection speed, and computation resource, it shows that the YOLOv3-53 model had a detection speed of 36 frames per second (FPS) and a mean average precision (mAP) of 95% on a GPU-1080Ti computer, more effective and feasible for the real-time detection of weapon contraband on human body for PMMW images, even with small sample data.A variety of deep learning techniques are actively employed for advanced driver assistance systems, which in turn require gathering lots of heterogeneous driving data, such as traffic conditions, driver behavior, vehicle status and location information. However, these different types of driving data easily become more than tens of GB per day, forming a significant hurdle due to the storage and network cost. To address this problem, this paper proposes a novel scheme, called CoDR, which can reduce data volume by considering the correlations among heterogeneous driving data. Among heterogeneous datasets, CoDR first chooses one set as a pivot data. Then, according to the objective of data collection, it identifies data ranges relevant to the objective from the pivot dataset. Finally, it investigates correlations among sets, and reduces data volume by eliminating irrelevant data from not only the pivot set but also other remaining datasets. CoDR gathers four heterogeneous driving datasets two videos for front view and driver behavior, OBD-II and GPS data. We show that CoDR decreases data volume by up to 91%. We also present diverse analytical results that reveal the correlations among the four datasets, which can be exploited usefully for edge computing to reduce data volume on the spot.Parathyroid hormone (PTH) has an important role in the maintenance of serum calcium levels. It activates renal 1α-hydroxylase and increases the synthesis of the active form of vitamin D (1,25[OH]2D3). PTH promotes calcium release from the bone and enhances tubular calcium resorption through direct action on these sites. Hallmarks of secondary hyperparathyroidism associated with chronic kidney disease (CKD) include increase in serum fibroblast growth factor 23 (FGF-23), reduction in renal 1,25[OH]2D3 production with a decline in its serum levels, decrease in intestinal calcium absorption, and, at later stages, hyperphosphatemia and high levels of PTH. In this paper, we aim to critically discuss severe CKD-related hyperparathyroidism, in which PTH, through calcium-dependent and -independent mechanisms, leads to harmful effects and manifestations of the uremic syndrome, such as bone loss, skin and soft tissue calcification, cardiomyopathy, immunodeficiency, impairment of erythropoiesis, increase of energy expenditure, and muscle weakness.To understand and manipulate the interactions between plants and microorganisms, sterile seeds are a necessity. The seed microbiome (inside and surface microorganisms) is unknown for most plant species and seed-borne microorganisms can persist and transfer to the seedling and rhizosphere, thereby obscuring the effects that purposely introduced microorganisms have on plants. This necessitates that these unidentified, seed-borne microorganisms are removed before seeds are used for studies on plant-microbiome interactions. Unfortunately, there is no single, standardized protocol for seed sterilization, hampering progress in experimental plant growth promotion and our study shows that commonly applied sterilization protocols for barley grains using H2O2, NaClO, and AgNO3 yielded insufficient sterilization. We therefore developed a sterilization protocol with AgNO3 by testing several concentrations of AgNO3 and added two additional steps Soaking the grains in water before the sterilization and rinsing with salt water (1% (w/w) NaCl) after the sterilization. The most efficient sterilization protocol was to soak the grains, sterilize with 10% (w/w) AgNO3, and to rinse with salt water. By following those three steps, 97% of the grains had no culturable, viable microorganism after 21 days based on microscopic inspection. The protocol left small quantities of AgNO3 residue on the grain, maintained germination percentage similar to unsterilized grains, and plant biomass was unaltered. Hence, our protocol using AgNO3 can be used successfully for experiments on plant-microbiome interactions.BACKGROUND Autism spectrum disorder (ASD) is a public health problem and has a prevalence of 0.6%-1.7% in children. As well as psychiatric symptoms, dysbiosis and gastrointestinal comorbidities are also frequently reported. The gut-brain microbiota axis suggests that there is a form of communication between microbiota and the brain underlying some neurological disabilities. The aim of this study is to describe and compare the composition of gut microbiota in children with and without ASD. METHODS Electronic databases were searched as far as February 2020. Meta-analyses were performed using RevMan5.3 to estimate the overall relative abundance of gut bacteria belonging to 8 phyla and 17 genera in children with ASD and controls. RESULTS We included 18 studies assessing a total of 493 ASD children and 404 controls. The microbiota was mainly composed of the phyla Bacteroidetes, Firmicutes, and Actinobacteria, all of which were more abundant in the ASD children than in the controls. Children with ASD showed a significantly higher abundance of the genera Bacteroides, Parabacteroides, Clostridium, Faecalibacterium, and Phascolarctobacterium and a lower percentage of Coprococcus and Bifidobacterium. DISCUSSION This meta-analysis suggests that there is a dysbiosis in ASD children which may influence the development and severity of ASD symptomatology. Further studies are required in order to obtain stronger evidence of the effectiveness of pre- or probiotics in reducing autistic behaviors.