Computer vision plays a big role in pipeline leakage detection systems and is one of the latest techniques. Still, it requires a powerful image-processing algorithm to detect objects. The purpose of ...this work is to develop and implement spill detection in oil pipes caused by leakage using images taken by a drone equipped with a Raspberry Pi 4. The acquired images are sent to the base station along with the global positioning system (GPS) location of the captured images via the message queuing telemetry transport Internet of Things (MQTT IoT) protocol. At the base station, images are processed to identify contours by dense extreme inception networks for edge detection(DexiNed) deep learning techniques based on holistically-nested edge detection(HED) and extreme inception (Xception) networks. This algorithm is capable of finding many contours in images. To find a contour with black color, the CIELAB color space (LAB) has been used. The proposed algorithm removes small contours and computes the area of the remaining contours. If the contour is above the threshold value, it is considered a spill; otherwise, it will be saved in a database for further inspection. For testing purposes, three different spill areas were implemented with spill sizes of (1 m^2,2 m^2 ,and 3 m^2). Images have been captured at three different heights (5 m, 10 m, and 15 m) by the drone used to capture the images. The result shows that effective detection has been obtained at 10 meters high. To monitor the entire system, a web application has been integrated into the base station.
Given the role that pipelines play in transporting crude oil, which is considered the basis of the global economy and across different environments, hundreds of studies revolve around providing the ...necessary protection for it. Various technologies have been employed in this pursuit, differing in terms of cost, reliability, and efficiency, among other factors. Computer vision has emerged as a prominent technique in this field, albeit requiring a robust image-processing algorithm for spill detection. This study employs image segmentation techniques to enable the computer to interpret visual information and images effectively. The research focuses on detecting spills in oil pipes caused by leakage, utilizing images captured by a drone equipped with a Raspberry Pi and Pi camera. These images, along with their global positioning system (GPS) location, are transmitted to the base station using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol. At the base station, deep learning techniques, specifically Holistically-Nested Edge Detection (HED) and extreme inception (Xception) networks, are employed for image processing to identify contours. The proposed algorithm can detect multiple contours in the images. To pinpoint a contour with a black color, representative of an oil spill, the CIELAB color space (LAB) algorithm effectively removes shadow effects. If a contour is detected, its area and perimeter are calculated to determine whether it exceeds a certain threshold. The effectiveness of the proposed system was tested on Iraqi oil pipeline systems, demonstrating its capability to detect spills of different sizes.
The goal of this research was to investigate the echotextural parameters, numerical pixel values (NPVs), and pixel heterogeneity (PSDs) of the lymph node and udder parenchyma, as well as the ...correlation between echotextural parameters and electrical conductivity (EC), in order to develop it as an alternative to laboratory testing for mastitic animal diagnosis and prognosis. The ultrasonographic images of each quarter were processed using digital image analyses to obtain mean NPVs and mean PSDs of mammary gland and lymph node parenchyma. The mean EC increased with the progression of infection. The mean NPVs of lymph node parenchyma decreased, whereas the mean NPVs of udder parenchyma increased from healthy to subclinical and clinical cows, respectively. The mean PSDs of lymph node and udder parenchyma increased with the progression and severity of infection from healthy to subclinical and clinical cows, respectively. It was concluded that, in dairy cattle, the variation in echotextural variables (NPVs and PSDs) of mammary gland and supramammary lymph node parenchyma and electrical conductivity appeared to be good indicators for the diagnostic and prognostic evaluation of sub-clinical and clinical mastitis in animals and simultaneously assists in the evaluation of udder health status.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Outbreaks of Middle East respiratory syndrome (MERS) raise questions about the prevalence and evolution of the MERS coronavirus (CoV) in its animal reservoir. Our surveillance in Saudi Arabia in 2014 ...and 2015 showed that viruses of the MERS-CoV species and a human CoV 229E–related lineage co-circulated at high prevalence, with frequent co-infections in the upper respiratory tract of dromedary camels. Including a betacoronavirus 1 species, we found that dromedary camels share three CoV species with humans. Several MERS-CoV lineages were present in camels, including a recombinant lineage that has been dominant since December 2014 and that subsequently led to the human outbreaks in 2015. Camels therefore serve as an important reservoir for the maintenance and diversification of the MERS-CoVs and are the source of human infections with this virus.
Globally, Food security main threaten by abiotic stress like salinity and levels amongst the majority serious environmental stressors which reduce crop yield mass production. Biochar application has ...received much attention in agricultural practices as it enhances crop quality and production. The present study was carried out to analyze the role of lysine zinc and biochar on growth enhancement of wheat (
L. cv. PU-2011) under saline stress (EC 7.17 dSm
). Seeds were sown in pots containing saline soil with and without 2% biochar, and foliar application of Zn-lysine (0, 1.0, and 2.0 mM) was made at different time intervals during plant growth. A combined application of biochar and Zn-lysine 2.0 mM highly improved the physiological attributes such as chlorophyll a (37%), chlorophyll b (60%), total chlorophyll (37%), carotenoids (16%), photosynthesis rate (
) 45%, stomatal conductance (
) 53%, transpiration rate (
) 56%, and water use efficiency (
) 55%. The levels of malondialdehyde (MDA) 38%, hydrogen peroxide (H
O
) 62%, and electrolyte leakage (EL) 48% were decreased with the combined application of biochar and Zn-lysine 2.0 mM as compared with other treatments. The activities of catalase (CAT) 67%, superoxide dismutase (SOD) 70%, and ascorbate peroxidase (APX) 61% as well as catalase (CAT) 67% were regulated with the combined biochar and Zn-lysine 2.0 mM treatment. Similarly, the combined application of biochar and zinc-lysine (2.0 mM) enhanced the growth and yield attributes such as shoot length (79%), root fresh weight (62%), shoot fresh weight (36%), root dry weight (86%), shoot dry weight (39%), grain weight (57%), and spike length (43%) as compared with untreated control. The concentrations of sodium (Na) decreased whereas potassium (K), iron (Fe), and zinc (Zn) concentrations were enhanced in plants with the combined application of Zn-lysine and biochar. Overall, results showed that the combined application of Zn-lysine (2.0 mM) and biochar significantly inhibited the negative effect of salinity and improved the growth and physiological performance of wheat plants. The combined use of Zn-lysine and biochar might be a practical solution to tackle salt stress in plants, but field studies by growing various crops under varied environmental conditions are needed before any recommendation to farmers.
Renewable energy-based distributed generators (DGs) are gaining more penetration in modern grids to meet the growing demand for electrical energy. The anticipated techno-economic benefits of these ...eco-friendly resources require their judicious and properly sized allocation in distribution networks (DNs). The preeminent objective of this research is to determine the sizing and optimal placing of DGs in the condensed DN of a smart city. The placing and sizing problem is modeled as an optimization problem to reduce the distribution loss without violating the technical constraints. The formulated model is solved for a radial distribution system with a non-uniformly distributed load utilizing the selective particle swarm optimization (SPSO) algorithm. The intended technique decreases the power loss and perfects the voltage profile at the system’s nodes. MATLAB is used for the simulation, and the obtained results are also validated by the Electrical Transient Analysis Program (ETAP). Results show that placing optimally sized DGs at optimal system nodes offers a considerable decline in power loss with an improved voltage profile at the network’s nodes. Distribution system operators can utilize the proposed technique to realize the reliable operation of overloaded urban networks.
Globally, Food security main threaten by abiotic stress like salinity and levels amongst the majority serious environmental stressors which reduce crop yield mass production. Biochar application has ...received much attention in agricultural practices as it enhances crop quality and production. The present study was carried out to analyze the role of lysine zinc and biochar on growth enhancement of wheat ( Triticum aestivum L. cv. PU-2011) under saline stress (EC 7.17 dSm -1 ). Seeds were sown in pots containing saline soil with and without 2% biochar, and foliar application of Zn-lysine (0, 1.0, and 2.0 mM) was made at different time intervals during plant growth. A combined application of biochar and Zn-lysine 2.0 mM highly improved the physiological attributes such as chlorophyll a (37%), chlorophyll b (60%), total chlorophyll (37%), carotenoids (16%), photosynthesis rate ( Pn ) 45%, stomatal conductance ( gs ) 53%, transpiration rate ( Tr ) 56%, and water use efficiency ( WUE ) 55%. The levels of malondialdehyde (MDA) 38%, hydrogen peroxide (H 2 O 2 ) 62%, and electrolyte leakage (EL) 48% were decreased with the combined application of biochar and Zn-lysine 2.0 mM as compared with other treatments. The activities of catalase (CAT) 67%, superoxide dismutase (SOD) 70%, and ascorbate peroxidase (APX) 61% as well as catalase (CAT) 67% were regulated with the combined biochar and Zn-lysine 2.0 mM treatment. Similarly, the combined application of biochar and zinc-lysine (2.0 mM) enhanced the growth and yield attributes such as shoot length (79%), root fresh weight (62%), shoot fresh weight (36%), root dry weight (86%), shoot dry weight (39%), grain weight (57%), and spike length (43%) as compared with untreated control. The concentrations of sodium (Na) decreased whereas potassium (K), iron (Fe), and zinc (Zn) concentrations were enhanced in plants with the combined application of Zn-lysine and biochar. Overall, results showed that the combined application of Zn-lysine (2.0 mM) and biochar significantly inhibited the negative effect of salinity and improved the growth and physiological performance of wheat plants. The combined use of Zn-lysine and biochar might be a practical solution to tackle salt stress in plants, but field studies by growing various crops under varied environmental conditions are needed before any recommendation to farmers.
Coronavirus Disease 2019 (COVID-19) is a current pandemic infection of the human respiratory system, which is caused by which caused by Sever Acute respiratory syndrome virus 2 (SARS-CoV-2). The ...infection was classified by World Health Organization (WHO) as a universal pandemic in February 2020; there have been 494.587.638 confirmed cases and 6.170.283 deaths. The present study investigated the molecular genetics of the Angiotensin Converting Enzyme 2 (
) gene in correlation to COVID-19 patients in the Kurdish population. Eighty-six individuals were clinically diagnosed with COVID-19 and control groups. After the genomic DNA extraction these participants the target 1, 2 and 8 exons of the ACE2 gene were amplified using the PCR technique, and then the Sanger sequencing technique was performed to analyze genetic variants of the
gene in 70 DNA samples of COVID-19 hospital patients at Emergency Hospital in Erbil city, Sarchnar Hospital in Sulaymaniyah city, Lalav Hospital in Duhok city and Wafa Hospital in Halabja city from Kurdistan Region of Iraq. The current study was designed into two groups control group and a patient group. The patient group was divided into two subgroups, severe and mild patients of different ages and genders. As a result, there were no mutations at the positions 1, 2 and 8 exons sequences, while single nucleotide polymorphisms (SNPs) were detected and identified three different types of mutation at intron position: twenty-six of c.12405 del T, two of c.12407 T>G, and two of c.12406 G>A in a total 86 participants. This result shows that genetic difference does not impact the COVID-19 infection severity among the Kurdish population regarding
gene polymorphism.
PDF
