Study on serum iron profile in COVID-19 associated mucormycosis patients

Background: Mucormycosis is an angio-invasive disease caused by fungi prevalence of which in India is approximately 0.14 cases per 1000 population. The incidence of mucor in COVID 19 patients has increased to greater extent. Probable cause of which is increased serum ferritin among these patients and Iron is required by virtually all microbial pathogens for growth and virulence. Hence, we had conducted a study to estimate serum iron profile and association of iron profile with mucor mycosis in covid-19 associated mucormycosis.Methods: Cross sectional study conducted from May 2021 to July 2021 by the department of general medicine, Banglore medical college and research centre, Karnataka. The data collected was analyzed statistically using descriptive statistics.Results: We observed increased prevalence of mucor cases among the patients aged between 41 to 60 years and those who were not vaccinated. Hyperglycaemia had strong correlation with development of mucor. There was lower UIBC, lower TIBC, high ferritin and serum Iron levels among those who had developed mucormycosis.Conclusions: By our observations, we concluded that the increased serum iron, ferritin, transferrin and reduced TIBC and UIBC are the associated risk factor in the development of COVID 19 associated invasive mucor mycosis. Patients with HbA1c >7 are at higher risk of developing COVID 19 associated mucor mycosis

Evaluation and Analysis of Rate Control Methods for H.264/AVC and MPEG-4 Video Codec

Audio, image and video signals produce a vast amount of data. The only solution of this problem is to compress data before storage and transmission. In general there is the three crucial terms as, Bit Rate Reduction, Fast Data Transfer and Reduction in Storage. Rate control is a vigorous factor in video coding. In video communications, rate control must ensure the coded bitstream can be transmitted effectively and make full use of the narrow bandwidth. There are various test models usually suggested by a standard during the development of video codes models in order to video coding which should be suffienciently be efficient based on H.264 at very low bit rate. These models are Test Model Number 5 (TMN5), Test Model Number 8 for H.263, and Verification Model 8 (VM8) for MPEG-4 and H.264 etc. In this work, Rate control analysis for H.264, MPEG-4 performed. For Rate control analysis test model verification model version 8.0 is adopted

A Preliminary Study on Phytoplankton in Fresh Water-Lake of Gogi, Yadgir District, Karnataka

The present study was conducted in a semi arid region of Karnataka. The study discusses the phytoplankton diversity of the Gogi lake ecosystem. A standard methodology was followed in conducting to complete this study and samples were collected at different points from the lake ecosystem located at the core area of the proposed uranium mining site. Through a field survey, twenty one species of phytoplankton were recorded coming under four classes viz., Bacillariophyceae(8), Chlorophyceae(7),Cyanophyceae (5) Charophyceae (1) and twelve families and Fragilariaceae (4), Bacillariaceae (3), Zygnemataceae(3), Desmidiaceae (2), Oscillatoriaceae (2), Melosiraceae (1), Cladophoraceae (1), Scenedesmaceae (1), Microcystaceae (1), Nostocaceae (1), Phormidiaceae (1), Characeae (1). The data were collected over two seasons- March to May and September to November -2012. A total of 21 species were recorded from the study region of which 10 species were recorded during March to May, while 02 species from September to November, nine species were recorde

Numerical and experimental investigation of the effect of process parameters on sheet deformation during the electromagnetic forming of AA6061-T6 alloy.

Electromagnetic forming is a high-speed sheet metal forming technique to form metallic sheets by applying magnetic forces. In comparison to the conventional sheet metal forming process, electromagnetic forming is a process with an extremely high velocity and strain rate, which can be effectively used for the forming of certain difficult-to-form metals. During electromagnetic forming, it is important to recognise the effects of process parameters on the deformation and sheet thickness variation of the sheet metal. This research focuses on the development of a numerical model for aluminium alloy (AA6061-T6) to analyse the effects of three process parameters, namely voltage, sheet thickness and number turns of the coils, on the deformation and thickness variation of the sheet. A two-dimensional fully coupled finite-element (FE) model consisting of an electrical circuit, magnetic field and solid mechanics was developed and used to determine the effect of changing magnetic flux and system inductance on sheet deformation. Experiment validation of the results was performed on a 28 KJ electromagnetic forming system. The Taguchi orthogonal array approach was used for the design of experiments using the three input parameters (voltage, sheet thickness and number of turns of the coil). The maximum error between numerical and experimental values for sheet thickness variation was observed to be 4.9 %. Analysis of variance (ANOVA) was performed on the experimental results. Applied voltage and sheet thickness were the significant parameters, while the number of turns of the coil had an insignificant effect on sheet deformation. The contribution ratio of voltage and sheet thickness was 46.21 % and 45.12 % respectively. The sheet deformation from simulations was found to be in good agreement with the experimental results

Progressive Class-Wise Attention (PCA) Approach for Diagnosing Skin Lesions

Skin cancer holds the highest incidence rate among all cancers globally. The importance of early detection cannot be overstated, as late-stage cases can be lethal. Classifying skin lesions, however, presents several challenges due to the many variations they can exhibit, such as differences in colour, shape, and size, significant variation within the same class, and notable similarities between different classes. This paper introduces a novel class-wise attention technique that equally regards each class while unearthing more specific details about skin lesions. This attention mechanism is progressively used to amalgamate discriminative feature details from multiple scales. The introduced technique demonstrated impressive performance, surpassing more than 15 cutting-edge methods including the winners of HAM1000 and ISIC 2019 leaderboards. It achieved an impressive accuracy rate of 97.40% on the HAM10000 dataset and 94.9% on the ISIC 2019 dataset

Towards Automated Weed Detection Through Two-Stage Semantic Segmentation of Tobacco and Weed Pixels in Aerial Imagery

In precision farming, weed detection is required for precise weedicide application, and the detection of tobacco crops is necessary for pesticide application on tobacco leaves. Automated accurate detection of tobacco and weeds through aerial visual cues holds promise. Precise weed detection in crop field imagery can be treated as a semantic segmentation problem. Many image processing, classical machine learning, and deep learning-based approaches have been devised in the past, out of which deep learning-based techniques promise better accuracies for semantic segmentation, i.e., pixel-level classification. We present a new method that improves the precision of pixel-level inter-class classification of the crop and the weed pixels. The technique applies semantic segmentation in two stages. In stage I, a binary pixel-level classifier is developed to segment background and vegetation. In stage II, a three-class pixel-level classifier is designed to classify background, weeds, and tobacco. The output of the first stage is the input of the second stage. To test our designed classifier, a new tobacco crop aerial dataset was captured and manually labeled pixel-wise. The two-stage semantic segmentation architecture has shown better tobacco and weeds pixel-level classification precision. The intersection over union (IOU) for the tobacco crop was improved from 0.67 to 0.85, and IOU for weeds enhanced from 0.76 to 0.91 with the new approach compared to the traditional one-stage semantic segmentation application. We observe that in stage I shallower, a smaller semantic segmentation model is enough compared to stage II, where a segmentation network with more neurons serves the purpose of good detection

Internet-of-Video Things Based Real-Time Traffic Flow Characterization

Real-world traffic flow parameters are fundamental for devising smart mobility solutions. Though numerous solutions (intrusive and non-intrusive sensors) have been proposed, however, these have serious limitations under heterogeneous and congested traffic conditions. To overcome these limitations, a low-cost real-time Internet-of-Video-Things solution has been proposed. The sensor node (fabricated using Raspberry Pi 3B, Pi cameral and power bank) has the capability to stream 2 Mbps MJPEG video of 640x480 resolution and 20 frames per second (fps). The Camlytics traffic analysis software installed on a Dell desktop is employed for traffic flow characterization. The proposed solution was field-tested with vehicle detection rate of 85.3%. The novelty of the proposed system is that in addition to vehicle count, it has the capability to measure speed, density, time headway, time-space diagram and trajectories. Obtained results can be employed for road network planning, designing and management

Involvement of Inflammatory Cytokines in Antiarrhythmic Effects of Clofibrate in Ouabain-Induced Arrhythmia in Isolated Rat Atria

Considering the cardioprotective and anti-inflammatory properties of clofibrate, the aim of the present experiment was to investigate the involvement of local and systemic inflammatory cytokines in possible antiarrhythmic effects of clofibrate in ouabain-induced arrhythmia in rats. Rats were orally treated with clofibrate (300 mg/kg), and ouabain (0.56 mg/kg) was administered to animals intraperitoneally. After induction of anesthesia, the atria were isolated and the onset of arrhythmia and asystole was recorded. The levels of inflammatory cytokines in atria were also measured. Clofibrate significantly postponed the onset of arrhythmia and asystole when compared to control group (P � 0.05 and P � 0.01, resp.). While ouabain significantly increased the atrial beating rate in control group (P � 0.05), same treatment did not show similar effect in clofibrate-treated group (P > 0.05). Injection of ouabain significantly increased the atrial and systemic levels of all studied inflammatory cytokines (P � 0.05). Pretreatment with clofibrate could attenuate the ouabain-induced elevation of IL-6 and TNF-α in atria (P � 0.01 and P � 0.05, resp.), as well as ouabain-induced increase in IL-6 in plasma (P � 0.05). Based on our findings, clofibrate may possess antiarrhythmic properties through mitigating the local and systemic inflammatory factors including IL-6 and TNF-α. Copyright © 2016 Somayeh Moradi et al

Degradation assessment of nuclear power plant extraction steam piping after long term service

Degradation due to ageing in a Nuclear Power Plant’s Extraction Steam Piping has been assessed. Samples of twelve years old seamless carbon steel SA 106B pipe have been taken and subjected to metallographic examination, hardness testing, radiographic examination and ultrasonic thickness measurement to investigate and analyze ageing in piping material. Metallographic examination of aged sample revealed irregularly distributed graphite nodules in ferrite grains and on grain boundaries as well, the reduction in pearlite phase has also been observed from 40% to 25%. This Transformation in microstructure has reduced hardness of steel. Reduction in hardness has found 20.4% and 0.7% on inner and outer layer of the pipe material respectively. Corrosion pits having average depth of 0.07 mm have been found on external surface. Radiograph of aged pipe revealed material removal and wall thinning due to erosion on inner surface of pipe. The extent of erosion had been checked, which has found 8.7%