RAPD analysis revealing polymorphism in egg parasitoids of soybean stink bugs (Hemiptera: Pentatomidae).

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Naïve Bayesian Classification Based Glioma Brain Tumor Segmentation Using Grey Level Co-occurrence Matrix Method

Brain tumors vary widely in size and form, making detection and diagnosis difficult. This study's main aim is to identify abnormal brain images., classify them from normal brain images, and then segment the tumor areas from the categorised brain images. In this study, we offer a technique based on the Nave Bayesian classification approach that can efficiently identify and segment brain tumors. Noises are identified and filtered out during the preprocessing phase of tumor identification. After preprocessing the brain image, GLCM and probabilistic properties are extracted. Naive Bayesian classifier is then used to train and label the retrieved features. When the tumors in a brain picture have been categorised, the watershed segmentation approach is used to isolate the tumors. This paper's brain pictures are from the BRATS 2015 data collection. The suggested approach has a classification rate of 99.2% for MR pictures of normal brain tissue and a rate of 97.3% for MR images of aberrant Glioma brain tissue. In this study, we provide a strategy for detecting and segmenting tumors that has a 97.54% Probability of Detection (POD), a 92.18% Probability of False Detection (POFD), a 98.17% Critical Success Index (CSI), and a 98.55% Percentage of Corrects (PC). The recommended Glioma brain tumour detection technique outperforms existing state-of-the-art approaches in POD, POFD, CSI, and PC because it can identify tumour locations in abnormal brain images

A COMPARATIVE STUDY BETWEEN THE PRESENCE OR ABSENCE OF SUPPORT FOR FARMERS OF THE CORN CROP IN IRAQ FOR THE YEAR 2019

Using the policy of price has a significant impact to developing the production of a particular crop by increasing productivity, which is eventually reflected in achieving high rates of self-sufficiency of the crops. The research objective is to identify the most important economic and social effects that will result from cancelling or reducing this subsidy Using the Cost-Benefit Analysis. The results showed that the ratio of return to cost in the case of reducing subsidies for corn farmers about 0.92%, which indicates that the one dinar invested in the cultivation of the corn under the subsidy policy achieves about 0.92 dinar, which is higher than the ratio of return to costs In the absence of this policy, that reached 0.65%. This indicates that the subsidy policy, even in reducing it, will lead to a reduction in farmers' losses by 27%. This is an incentive for the government to continue providing support to farmers to continue the production process. The study recommended that there is necessarily need to reorganize the strategy of providing support to farmers and find appropriate mechanisms for implementing the government policy to ensure that all corn farmers benefit from this support

DETECTION AND CHARACTERISATION OF SUGARCANE YELLOWS PHYTOPLASMA

Abstract A study was carried out to assess the distribution and association of sugarcane yellows phytoplasma-ScYP in sugarcane affected by yellow leaf syndrome (YLS) in Mauritius. The polymerase chain reaction was used to detect and characterise the phytoplasma. Samples were collected from clones undergoing quarantine, in a variety collection plot, in mature commercial fields and from 6 month old commercial fields. A 1.25 kb DNA fragment encoding for the phytoplasma 16s rRNA was consistently amplified by nested-PCR. Of the 204 samples with and without symptoms derived from 166 varieties, 95 (57%) tested positive for ScYP by PCR. Restriction fragment length polymorphism analysis of the phytoplasma 16s rDNA amplified product indicated that 3 phytoplasma groups are present in sugarcane in Mauritius. The results indicated that detection of YLS based on symptoms only is not reliable, since many asymptomatic varieties were positive for the phytoplasma early in the growing season

Application of the Jaya algorithm to solve the optimal reliability allocation for reduction oxygen supply system of a spacecraft

In this paper the reliability of reduction oxygen supply system (ROSS) of a spacecraft which was calculated as a complex system using minimal cut method. The reliability of each component of system was calculated as well as the reliability importance of the system. The cost of each component of the system was possible approaches of the allocation values of reliability based the minimization of the overall cost in this system. The advantage of this algorithm can be used to allocate the optimization of reliability for simple or complex system. This optimization is achieved using the Jaya algorithm. The proposed technique is based on the notion that a conclusion reached on a particular problem should pass near the best results and avoid the worst outcomes. The original findings of this paper are: I) the system used in this paper is a spacecraft's reduced oxygen supply system with the logarithmic cost function; and ii) the results obtained were by using the Jaya algorithm to solve specific system reliability optimization problems

An evaluation of the SureID 23comp Human Identification Kit for kinship testing

Short tandem repeat (STR) profiling has been routinely used in kinship testing since the introduction of commercial kits in the mid-1990s. While 15 to 23 STR loci normally give definitive results in simple kinship testing, additional loci are sometimes required to resolve complex cases. The SureID 23comp Human Identification Kit, recently released by Health Gene Technologies (China), multiplexes amelogenin and 22 autosomal STRs, 17 of which are non-CODIS STRs. This enables the profiling of 38–40 loci when used in conjunction with widely used commercial kits. In this study, the kit was evaluated for kinship applications as a supplementary STR kit following the minimum criteria for validation recommended by the European Network of Forensic Science Institutes (ENFSI) and the Scientific Working Group on DNA Analysis Methods (SWGDAM) using 500 samples. Performance was comparable with other commercial kits demonstrating: repeatability and reproducibility; precision (maximum s.d. 0.1048 nt); accuracy, all alleles were within ±0.41 nt compared to the actual sizes; heterozygous peak balances at all loci >68%; stutter ratios ranged from 3.8% to 16.15%; full profiles were generated with 125 pg DNA (95.12% of alleles at 62 pg),; and we found 100% concordance over 5 common STRs with the GlobalFiler kit

Bacterial co-infections with SARS-CoV-2

The pandemic coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has affected millions of people worldwide. To date, there are no proven effective therapies for this virus. Efforts made to develop antiviral strategies for the treatment of COVID-19 are underway. Respiratory viral infections, such as influenza, predispose patients to co-infections and these lead to increased disease severity and mortality. Numerous types of antibiotics such as azithromycin have been employed for the prevention and treatment of bacterial co-infection and secondary bacterial infections in patients with a viral respiratory infection (e.g., SARS-CoV-2). Although antibiotics do not directly affect SARS-CoV-2, viral respiratory infections often result in bacterial pneumonia. It is possible that some patients die from bacterial co-infection rather than virus itself. To date, a considerable number of bacterial strains have been resistant to various antibiotics such as azithromycin, and the overuse could render those or other antibiotics even less effective. Therefore, bacterial co-infection and secondary bacterial infection are considered critical risk factors for the severity and mortality rates of COVID-19. Also, the antibiotic-resistant as a result of overusing must be considered. In this review, we will summarize the bacterial co-infection and secondary bacterial infection in some featured respiratory viral infections, especially COVID-19. © 2020 International Union of Biochemistry and Molecular Biolog

Evaluation of Five Methods for Total DNA Extraction from Western Corn Rootworm Beetles

Background: DNA extraction is a routine step in many insect molecular studies. A variety of methods have been used to isolate DNA molecules from insects, and many commercial kits are available. Extraction methods need to be evaluated for their efficiency, cost, and side effects such as DNA degradation during extraction. Methodology/Principal Findings: From individual western corn rootworm beetles, Diabrotica virgifera virgifera, DNA extractions by the SDS method, CTAB method, DNAzol reagent, Puregene solutions and DNeasy column were compared in terms of DNA quantity and quality, cost of materials, and time consumed. Although all five methods resulted in acceptable DNA concentrations and absorbance ratios, the SDS and CTAB methods resulted in higher DNA yield (ng DNA vs. mg tissue) at much lower cost and less degradation as revealed on agarose gels. The DNeasy kit was most time-efficient but was the costliest among the methods tested. The effects of ethanol volume, temperature and incubation time on precipitation of DNA were also investigated. The DNA samples obtained by the five methods were tested in PCR for six microsatellites located in various positions of the beetle’s genome, and all samples showed successful amplifications. Conclusion/Significance: These evaluations provide a guide for choosing methods of DNA extraction from western corn rootworm beetles based on expected DNA yield and quality, extraction time, cost, and waste control. The extraction conditions for this mid-size insect were optimized. The DNA extracted by the five methods was suitable for further molecular applications such as PCR and sequencing by synthesis

Expression of a rice chitinase gene in transgenic banana ('Gros Michel', AAA genome group) confers resistance to black leaf streak disease

Peer reviewe