UAV detection : a STDP trained deep convolutional spiking neural network retina-neuromorphic approach

The Dynamic Vision Sensor (DVS) has many attributes, such as sub-millisecond response time along with a good low light dy- namic range, that allows it to be well suited to the task for UAV De- tection. This paper proposes a system that exploits the features of an event camera solely for UAV detection while combining it with a Spik- ing Neural Network (SNN) trained using the unsupervised approach of Spike Time-Dependent Plasticity (STDP), to create an asynchronous, low power system with low computational overhead. Utilising the unique features of both the sensor and the network, this result in a system that is robust to a wide variety in lighting conditions, has a high temporal resolution, propagates only the minimal amount of information through the network, while training using the equivalent of 43,000 images. The network returns a 91% detection rate when shown other objects and can detect a UAV with less than 1% of pixels on the sensor being used for processing

Association mapping of spot blotch resistance in wild barley

Spot blotch, caused by Cochliobolus sativus, is an important foliar disease of barley. The disease has been controlled for over 40 years through the deployment of cultivars with durable resistance derived from the line NDB112. Pathotypes of C. sativus with virulence for the NDB112 resistance have been detected in Canada; thus, many commercial cultivars are vulnerable to spot blotch epidemics. To increase the diversity of spot blotch resistance in cultivated barley, we evaluated 318 diverse wild barley accessions comprising the Wild Barley Diversity Collection (WBDC) for reaction to C. sativus at the seedling stage and utilized an association mapping (AM) approach to identify and map resistance loci. A high frequency of resistance was found in the WBDC as 95% (302/318) of the accessions exhibited low infection responses. The WBDC was genotyped with 558 Diversity Array Technology (DArT®) and 2,878 single nucleotide polymorphism (SNP) markers and subjected to structure analysis before running the AM procedure. Thirteen QTL for spot blotch resistance were identified with DArT and SNP markers. These QTL were found on chromosomes 1H, 2H, 3H, 5H, and 7H and explained from 2.3 to 3.9% of the phenotypic variance. Nearly half of the identified QTL mapped to chromosome bins where spot blotch resistance loci were previously reported, offering some validation for the AM approach. The other QTL mapped to unique genomic regions and may represent new spot blotch resistance loci. This study demonstrates that AM is an effective technique for identifying and mapping QTL for disease resistance in a wild crop progenitor

Multicenter evaluation of the clinical utility of laparoscopy-assisted ERCP in patients with Roux-en-Y gastric bypass

Background and Aims The obesity epidemic has led to increased use of Roux-en-Y gastric bypass (RYGB). These patients have an increased incidence of pancreaticobiliary diseases yet standard ERCP is not possible due to surgically altered gastroduodenal anatomy. Laparoscopic-ERCP (LA-ERCP) has been proposed as an option but supporting data are derived from single center small case-series. Therefore, we conducted a large multicenter study to evaluate the feasibility, safety, and outcomes of LA-ERCP. Methods This is retrospective cohort study of adult patients with RYGB who underwent LA-ERCP in 34 centers. Data on demographics, indications, procedure success, and adverse events were collected. Procedure success was defined when all of the following were achieved: reaching the papilla, cannulating the desired duct and providing endoscopic therapy as clinically indicated. Results A total of 579 patients (median age 51, 84% women) were included. Indication for LA-ERCP was biliary in 89%, pancreatic in 8%, and both in 3%. Procedure success was achieved in 98%. Median total procedure time was 152 minutes (IQR 109-210) with median ERCP time 40 minutes (IQR 28-56). Median hospital stay was 2 days (IQR 1-3). Adverse events were 18% (laparoscopy-related 10%, ERCP-related 7%, both 1%) with the clear majority (92%) classified as mild/moderate whereas 8% were severe and 1 death occurred. Conclusion Our large multicenter study indicates that LA-ERCP in patients with RYGB is feasible with a high procedure success rate comparable with that of standard ERCP in patients with normal anatomy. ERCP-related adverse events rate is comparable with conventional ERCP, but the overall adverse event rate was higher due to the added laparoscopy-related events

The risk of esophageal adenocarcinoma associated with Barrett\u27s esophagus and gastroesophageal reflux disease: A retrospective cohort study in U.S. veterans

Patients with Barrett\u27s esophagus (BE) and gastroesophageal reflux disease (GERD) are at a higher risk of developing esophageal adenocarcinoma (EA). We examined this risk in two large national cohorts of patients with BE and GERD alone and provided risk ratios comparing the risk in both cohorts. This was a retrospective cohort study of US veterans with BE and GERD alone diagnosed between 2003 and 2009, identified from a total of 121 Veterans\u27 Affairs facilities nationwide. All cases of EA were verified by detailed medical chart review. We identified 29,536 with BE and 486,676 patients with GERD who met our eligibility criteria. Most patients in both cohorts were men and white, with a mean age of 59.8 and 61.8 years, respectively. The incidence rate of EA in patients with BE was 3.215 per 1,000 person-years, and 0.206 per 1,000 person-years in patients with GERD alone. The incidence of EA in patients with BE increased with age compared to patients with GERD alone. The highest risk of EA in patients with BE when compared to GERD alone was in blacks (incidence rate ratio 52.221, 95%CI 22.412-125.696). BE diagnosis significantly increased the risk of EA when compared to patients with GERD alone. This was most apparent in both black and elderly patients

Detection of antibiotic-producing Actinobacteria in the sediment and water of Ma’in thermal springs (Jordan)

Introduction Detection of new Actinobacteria is significant to discover new antibiotics because development of new antibiotics is connected to the characterization of novel bacterial taxa. This study has focused on the identification and isolation of antibiotic-producing Actinobacteria from the sediment and the water of Ma’in thermal springs (48-59°C) situated in the center area of Jordan. Methods Samples of sediment and water were transferred to glucose yeast malt agar medium and Actinobacteria were cultivated, isolated and identified according to scanning electron microscopy and 16S rRNA gene analysis. Antibacterial activities of the isolates were then tested against different test bacteria by agar well diffusion method. Results Three different species of Actinobacteria were isolated (M1-1, M2-2, M3-2) from sediment samples. Based on 16S rRNA gene analysis, isolate M1-1 was found to have only 90% identity percentage with Nocardiopsis sp., however, isolates M2-2 and M3-2 were found to be closely related Streptomyces sp. (97%) and Nocardioides luteus (99%), respectively. The antibacterial activity showed that strain M1-1 is active against P. aeruginosa ATCC 2785 (inhibition zone, 9 mm). Strain M2-2 was found to be active against S. aureus ATCC 29213 (12 mm), B. cereus ATCC 11778 (11 mm), and E. coli ATCC 25922 (9 mm). In respect to strain M3-2, it was found to be active against S. aureus ATCC 29213 (14 mm) and B. cereus ATCC 11778 (9 mm). There were no actinobacterial isolates obtained from water samples despite their significant diversity revealed by our previous metagenomic analysis, which showed the presence of 13 different species dominated by Arthrobacter (an Actinobacterium belonging to family Actinomycetales). Conclusion There were 17 different Actinobacteria that could be detected in Ma’in thermal springs (13 unculturable species and 3 culturable species). The culturable Actinobacteria were found to have some antimicrobial activity. Further chemical analysis of the bioactive compounds is recommended

Microbial community analysis of the hypersaline water of the Dead Sea using high-throughput amplicon sequencing

Amplicon sequencing using next-generation technology (bTEFAP ) has been utilized in describing the diversity of Dead Sea microbiota. The investigated area is a well-known salt lake in the western part of Jordan found in the lowest geographical location in the world (more than 420 m below sea level) and characterized by extreme salinity (approximately, 34%) in addition to other extreme conditions (low pH, unique ionic composition different from sea water). DNA was extracted from Dead Sea water. A total of 314,310 small subunit RNA (SSU rRNA) sequences were parsed, and 288,452 sequences were then clustered. For alpha diversity analysis, sample was rarefied to 3,000 sequences. The Shannon-Wiener index curve plot reached a plateau at approximately 3,000 sequences indicating that sequencing depth was sufficient to capture the full scope of microbial diversity. Archaea was found to be dominating the sequences (52%), whereas Bacteria constitute 45% of the sequences. Altogether, prokaryotic sequences (which constitute 97% of all sequences) were found to predominate. The findings expand on previous studies by using high-throughput amplicon sequencing to describe the microbial community in an environment which in recent years has been shown to hide some interesting diversity

Mobile-IRS Assisted Next Generation UAV Communication Networks

Prior research on intelligent reflection surface (IRS)-assisted unmanned aerial vehicle (UAV) communications has focused on a fixed location for the IRS or mounted on a UAV. The assumption that the IRS is located at a fixed position will prohibit mobile users from maximizing many wireless network benefits, such as data rate and coverage. Furthermore, assuming that the IRS is placed on a UAV is impractical for various reasons, including the IRS's weight and size and the speed of wind in severe weather. Unlike previous studies, this study assumes a single UAV and an IRS mounted on a mobile ground vehicle (M-IRS) to be deployed in an Internet-of-Things (IoT) 6G wireless network to maximize the average data rate. Such a methodology for providing wireless coverage using an M-IRS assisted UAV system is expected in smart cities. In this paper, we formulate an optimization problem to find an efficient trajectory for the UAV, an efficient path for the M-IRS, and users' power allocation coefficients that maximize the average data rate for mobile ground users. Due to its intractability, we propose efficient techniques that can help in finding the solution to the optimization problem. First, we show that our dynamic power allocation technique outperforms the fixed power allocation technique in terms of network average sum rate. Then we employ the individual movement model (Random Waypoint Model) in order to represent the users' movements inside the coverage area. Finally, we propose an efficient approach using a Genetic Algorithm (GA) for finding an efficient trajectory for the UAV, and an efficient path for the M-IRS to provide wireless connectivity for mobile users during their movement. We demonstrate through simulations that our methodology can enhance the average data rate by 15\% on average compared with the static IRS and by 25\% on average compared without the IRS system.Comment: 11 pages, 8 figure