Ameliorative effect of vitamin E on potassium dichromate-induced hepatotoxicity in rats

AbstractHexavalent chromium [Cr (VI)]-mediated oxidative stress causes severe hepatic toxicity. This study aims to investigate the protective role of oral vitamin E administration against potassium dichromate (K2Cr2O7)-induced hepatotoxicity. Adult male rats (Rattus norvegicus, n=24) weighing 150–180g were used and divided into 4 groups (n=6 per group): the control group received distilled water; control+vitamin E group received vitamin E (100mg/kg b.w.); Cr group received K2Cr2O7 (8mg/kg b.w.), and Cr+vitamin E group received K2Cr2O7+vitamin E. All treatments were administered orally on a daily basis for 6weeks.There was a significant accumulation of Cr in the livers of the Cr group compared with the control group. In addition, exposure to K2Cr2O7 induced significant increases in the level of thiobarbituric-reactive substances (TBARS) and significant decreases in glutathione (GSH) content and superoxide dismutase (SOD) activity in the Cr group compared with the control group. Moreover, livers of the Cr group showed major histological alterations, such as severe necrosis, increased lymphocytic infiltration, and a significant decrease in the DNA content. Oral vitamin E administration concomitant with K2Cr2O7 ameliorated all these changes and resulted in normal hepatic histological and cellular contents. In conclusion, oral vitamin E administration has a hepatoprotective role against K2Cr2O7-induced hepatotoxicity in rats

Description of a new species of Megastigmus Dalman (Hymenoptera: Chalcidoidea: Torymidae) from Saudi Arabia

A new species, Megastigmus asir, sp. nov. (Hymenoptera: Torymidae) which emerged from seeds of Juniperus procera (Cupressaceae) collected from Jabel Al sodah, Asir region, Saudi Arabia is described and illustrated. The genus, Megasitigmus Dalman, is recorded for the first time from Saudi Arabia.Key words: Megastigmus, Torymidae, new records, new species, Juniperus procera, Saudi Arabia

COVID-19 Detection System: A Comparative Analysis of System Performance Based on Acoustic Features of Cough Audio Signals

A wide range of respiratory diseases, such as cold and flu, asthma, and COVID-19, affect people's daily lives worldwide. In medical practice, respiratory sounds are widely used in medical services to diagnose various respiratory illnesses and lung disorders. The traditional diagnosis of such sounds requires specialized knowledge, which can be costly and reliant on human expertise. Recently, cough audio recordings have been used to automate the process of detecting respiratory conditions. This research aims to examine various acoustic features that enhance the performance of machine learning (ML) models in detecting COVID-19 from cough signals. This study investigates the efficacy of three feature extraction techniques, including Mel Frequency Cepstral Coefficients (MFCC), Chroma, and Spectral Contrast features, on two ML algorithms, Support Vector Machine (SVM) and Multilayer Perceptron (MLP), and thus proposes an efficient COVID-19 detection system. The proposed system produces a practical solution and demonstrates higher state-of-the-art classification performance on COUGHVID and Virufy datasets for COVID-19 detection.Comment: 8 pages, 3 figure

Phytoprotective and Antioxidant Effects of German Chamomile Extract against Dimpylate-Induced Hepato-Nephrotoxicity in Rats

Dimpylate is one of the most organophosphorus widely used insecticides in agriculture. This study aims to investigate the ameliorative effect of German chamomile (Matricaria recutita) on the hepato-nephrotoxicity induced by Dimpylate in male Wistar rats.  Rats  were divided into 4 groups: Control group, received  corn oil alone; Chamomile group, orally given water extract of Chamomile (300 mg/kg b.wt./day for 30 days); Dimpylate group, orally given 15 mg/kg b.wt./day for 30 days of Dimpylate; and Dimpylate and chamomile group,  orally given Dimpylate (15 mg/kg b.wt./day) with Chamomile extract (300 mg/kg b.wt./day) for 30 days. Oxidative stress and antioxidant status were estimated in the liver and kidney of all groups. In the liver and kidney of the Dimpylate-intoxicated rats, there was an increase in malondialdehyde (MDA) concentration and a significant decrease in the activities of superoxide dismutase (SOD), total antioxidant capacity (TCA), glutathione-peroxidase (GPx), glutathione reductase (GSH-R) and Glutathione–S-transferase (GST). In addition, significant increases in serum liver function marker enzymes (AST, ALT, ALP) were recorded in Dimpylate intoxicated rats as compared to control group. Moreover, significant increase in serum total lipid, triglyceride and total cholesterol levels was observed in Dimpylate group as compared to control group. Serum total protein was decreased significantly in Dimpylate intoxicated rats as compared to the control group. Renal products; urea and creatinine were significantly elevated in in Dimpylate group compared to the control group. Dimpylate treated animals also revealed a significant increase in serum biochemical parameters as well as hepatic and renal lipid peroxidation but caused an inhibition in antioxidant biomarkers. normalized the elevated serum levels of AST, ALT, APL, uric acid, urea and creatinine. Furthermore, it reduced dimpylate-induced lipid peroxidation and oxidative stress in a dose dependent manner. Therefore, it could be concluded that Chomomile extract administration able to minimize the toxic effects of dimpylate by its free radical-scavenging and potent antioxidant activity. Co-administration of the Chamomile aqueous extract with Dimpylate could attenuate the all the disrupted measured parameters in liver and kidney tissued. Therefore, it could be concluded that the chamomile aqueous extract has antioxidant and protective property againsit Dimpylate hepato-nephrotoxicity Keywords: Dimpylate, Chamomile, hepato-nephrotoxicity, Antioxidant

Texture features extraction based on GLCM for face retrieval system

Texture features play an important role in most image retrieval techniques to obtain results of high accuracy. In this work, the face image retrieval method considering texture analysis and statistical features has been proposed. Textile features can also be extracted using the GLCM tool. In this research, the GLCM calculation method involves two phases, first: some of the previous image processing techniques work together to get the best results to determine the big object of the face image (center of face image) then, the gray level co-occurrence matrix GLCM is computed for gray face image and then some statistical texture features with second-order are extracted. In the second phase, the facial texture features are retrieved by finding the minimum distance between texture features of an unknown face image with the texture features of face images that are stored in the database system. The experimental results show that the proposed method is capable to achieve high accuracy degree in face image retrieval

SAT-Based Approach for Learning Optimal Decision Trees with Non-Binary Features

Decision trees are a popular classification model in machine learning due to their interpretability and performance. Traditionally, decision-tree classifiers are constructed using greedy heuristic algorithms, however these algorithms do not provide guarantees on the quality of the resultant trees. Instead, a recent line of work has studied the use of exact optimization approaches for constructing optimal decision trees. Most of the recent approaches that employ exact optimization are designed for datasets with binary features. While numeric and categorical features can be transformed to binary features, this transformation can introduce a large number of binary features and may not be efficient in practice. In this work, we present a novel SAT-based encoding for decision trees that supports non-binary features and demonstrate how it can be used to solve two well-studied variants of the optimal decision tree problem. We perform an extensive empirical analysis that shows our approach obtains superior performance and is often an order of magnitude faster than the current state-of-the-art exact techniques on non-binary datasets

The influence of COVID-19 on online shopping behaviour in South Africa

The traditional brick-and-mortar stores have had to endure competition in the recent past from the arrival of various shopping channels, particularly the online shopping. Despite the competition enhanced by a proliferation of technology, brick-and-mortar is still the preferred shopping channel. This is largely due to the shopping behaviour, which is generally stable and slow to change unless it is distorted by a catastrophic event. The advent of the corona virus pandemic has seen nations imposing restrictions on gatherings and encouraging moving to online platforms for both social and business interactions as a way to curb transmission of the deadly virus. This major life event has the potential to distort traditional shopping behaviour. Therefore, this study seeks to investigate whether the pandemic has had an influence on online shopping in South Africa. The research aims to examine the different shopping channels and factors that lure customers to those channels paying particular attention to online shopping during the pandemic. Communication, technology, product variety, payment method, delivery, shopping behaviour, COVID-19 and demographics were identified during a literature review as independent factors that influence online shopping. A positivism paradigm, which informed the selection of a quantitative method, was adopted for this research in order to achieve the study’s research objectives. An online questionnaire was designed to collect data and was distributed by the university’s first-year MBA students. The collected data were analysed with the assistance of the university’s statistician. The ethics approval for the study was obtained from the Nelson Mandela University’s Ethics Committee, reference number H21-BES-BS-003. The study draws from the Technology Acceptance Model, Theory of Planned Behaviour and Diffusion of Innovation theories to gain a better understanding on the acceptance of technologies’ influence on online shopping. The study identified that the biographic variables, namely age, income, education, gender and employment status have an influence on online shopping. The relationship between the different independent factors and online shopping was tested using the Exploratory Factor Analysis, Pearson correlations and Chi2 Tests. The factors Payment method, Shopping behaviour, Current impact of COVID-19, Acceptance of technologies and Product variety were found to have a significant influence on online shopping.Based on the research findings, the study formulated recommendations for online businesses in South Africa. The research findings will allow businesses to promptly implement strategies that meet the consumers’ needs and gain competitive advantage. Based on the findings, businesses are urged to improve security on payment methods, leverage technology to offer improved customer experience and primarily market to the 18-39 years employed cohort. These recommendations will assist businesses to retain these online shopping customers post the pandemic.Thesis (MBA) -- Faculty of Business and Economic Sciences, 202

An oxygen isotope record of lacustrine opal from a European Maar indicates climatic stability during the Last Interglacial

The penultimate temperate period, 127–110 ka before present (BP), bracketed by abrupt shifts of the global climate system initiating and terminating it, is considered as an analogue of the Holocene because of a similar low global ice‐volume. Ice core records as well as continental and marine records exhibit conflicting evidence concerning the climate variability within this period, the Last Interglacial. We present, for the first time, a high‐resolution record of oxygen isotopes in diatom opal of the Last Interglacial obtained from the Ribains Maar in France (44°50′09″N 3°49′16″E). Our results indicate that the Last Interglacial in southwestern Europe was generally a period of climatic stability. The record shows that the temperate period was initiated by an abrupt warm event followed midway by a minor climatic transition to a colder climate. An abrupt isotopic depletion that occurs simultaneously with abrupt changes in pollen and diatom assemblages marks the end of the temperate period, and is correlative with the Melisey I stadial. Variations in the isotopic composition of lake‐water related to the isotopic composition of precipitation and evaporation dominate the biogenic opal oxygen isotope record

Assessment of Differences between Near-Surface Air and Soil Temperatures for Reliable Detection of High-Latitude Freeze and Thaw States

Near-surface air temperature and the underlying soil temperature are among the key components of the Earth’s surface energy budget, and they are important variables for the comprehensive assessment of global climate change. Better understanding of the difference in magnitude between these two variables over high-latitude regions is also crucial for accurate detections of freeze and thaw (FT) states. However, these differences are not usually considered and included in current remote sensing-based FT detection algorithms. In this study, the difference between near-surface air temperature at the 2-meter height and soil temperature at the 5-centimeter depth is assessed using ground-based observations that span a three-year period from 2013 to 2015. Results show noticeable differences between air and soil temperatures over temporal scales that range from diurnal to seasonal. The study also suggests that the ground-based upper layer soil temperature may be a better surrogate than the near-surface air temperature for the reliable detection of FT states at high-latitudes. Furthermore, the results from this study are particularly useful for better understanding the surface energy budget that ultimately drives the land surface processes that are embedded within weather and climate models