A RANDOMISED CONTROL STUDY TO COMPARE THE EFFICACY OF CEFUROXIME, CLARITHROMYCIN, AND LEVOFLOXACIN IN THE MANAGEMENT OF PAEDIATRIC UPPER RESPIRATORY TRACT INFECTION

Background: The upper respiratory infections cause considerable morbidity mainly in children due to the fact that they mainly affect children. Accordingly, a study was conducted on antibiotics to compare the effectiveness of clarithromycin, cefuroxime, and levofloxacin for treating upper respiratory tract infections (URTI) in children. Methods: A prospective observational study for a period of 6 months was conducted in the pediatrics department of RVM hospital. Outpatients under the age of 14 years given antibiotics for the treatment of URTI were included in the study. A total of 99 study subjects were included in the study, divided into three groups each containing 33 sample sizes (clarithromycin, cefuroxime, and levofloxacin). Patient data was collected using a form and verbal consent was obtained from patients/patient representatives, and drugs were given using the lottery method. Follow-up was done and noted for the 3rd, 5th, 7th day through telephonic calls, and the collected data were evaluated using statistical analysis. Results: Pool data from 99 patients shows that many patients belong to 0–5 years age groups (age distribution), and males were more than female (gender distribution). Clarithromycin (cure rate 3 days) and cefuroxime (cure rate 5 days) showed an equal rate of cure percentage (94%), while levofloxacin for 3–5 days with a 3% failure rate. A significant difference of p<0.05 (p=0.000) was observed and no adverse events were noted. Conclusion: The study findings showed, out of 3 drugs, clarithromycin and cefuroxime showed an equal efficacy rate of 94%, but clarithromycin showed shorter duration of outcome, i.e., 3 days. Hence, clarithromycin is effective than the other two drugs in the treatment of URTI

EFFECT OF DATA QUALITY ON WATER BODY SEGMENTATION WITH DEEPLABV3+ ALGORITHM

Training Deep Learning (DL) algorithms for segmenting features require hundreds to thousands of input data and corresponding labels. Generating thousands of input images and labels requires considerable resources and time. Hence, it is common practice to use opensource imagery data and labels available online. Most of these open-source data have little or no metadata describing their quality or suitability making it problematic for training or evaluating DL models. This study evaluated the effect of data quality on training DeepLabV3+, using Sentinel 2 A/B RGB images and labels obtained from Kaggle. We generated subsets of 256 × 256 pixels, and 10% of these images (802) were set aside for testing. First, we trained and validated the DeepLabV3+ model with the remaining images. Second, we removed images with incorrect labels and trained another DeepLabV3+ network. Finally, we trained the third DeepLabV3+ network after removing images with turbid water or with floating vegetation. All three trained models were evaluated with test images and then we calculated accuracy metrics. As the quality of the input images improved, accuracy of the predicted masks generated from the first model increased from 92.8% to 94.3% in the second model. The third model’s accuracy was 96.4%, demonstrating the network’s ability to better learn and predict water bodies when the input data had fewer class variations. Based on the results we recommend assessing the quality of open-source data for incorrect labels and variations in the target class prior to training DeepLabV3+ or any other DL network

Review on Various Applications of Visible Light Communication

In the current scenario, there is an increased usage of Radio Frequency (RF) for wireless communication, that there is a major problem of bandwidth allocation. In order to overcome this problem a new technology called Visible Light Communication (VLC) is introduced which uses visible light whose data rates are higher than radio waves. Visible Light requires fewer components than radio technology, hence cost effective. Data transmission requires LED light sources which consumes less power. The data transmitted is more secure and can be used in electromagnetic sensitive areas. This transmission technique can also be used in aircraft cabins, hospitals and nuclear power plants without causing electromagnetic interference

Immunohistochemical Expression of Anaplastic Lymphoma Kinase in Invasive Breast Carcinomas- A Retrospective Study

Introduction: Breast carcinoma remains one of the most common causes of mortality among female cancer patients inspite of improvements in treatment modalities. Increased survival rate can be achieved by identification of new targeted therapies. Anaplastic Lymphoma Kinase (ALK) alterations are present in many solid and haematological tumours indicating its role in pathogenesis and treatment. There are studies regarding the expression of ALK in few breast cancers but its importance was not clearly mentioned. Hence, identification of ALK overexpression in breast cancers, particularly in Triple Negative Breast Cancers (TNBC) might play a role in their chemotherapy with the help of ALK inhibitors. Aim: To study the ALK expression in different subtypes of invasive carcinomas of breast. Materials and Methods: This was a retrospective cross-sectional study conducted in the Department of Pathology at Great Eastern Medical School (GEMS) and Hospital, Srikakulam, Andhra Pradesh, India, from January 2022 to July 2022. The data of 60 patients, from January 2021 to December 2021 was retrieved using Hospital Information Management System (HIMS) and the Haematoxylin and Eosin (H&E)-stained slides and formalin fixed paraffin embedded tissue blocks of breast tumour were retrieved and reviewed. Estrogen receptor (ER), Progesterone receptor (PR) and Human Epidermal growth factor Receptor 2 (HER2) immunostains were performed and categorised based on molecular classification as Luminal, Her2 and Triple negative. ALK Staining was performed on all cases and its expression was studied. Statistical Package for Social Sciences (SPSS) software version 2.0 was used for analysis of data. Mean with standard deviation is used for quantitative variables and prevalence, ratio is used for quantitative variables. Chi-square test and Fischer exact test were used for detecting significance. The p-value <0.05 was considered as significant. Results: Out of 60 cases, majority (N=22; 36.66%) of patients were in the age group of 51-60 years. The mean tumour size was 3.2±0.5 cm. The most common histological type was invasive breast carcinoma, No Special Type (N=44; 73.34%). Majority of the tumours showed grade 1 and 2 with 24 (40%) and 25 (41.67%) cases, respectively. A total of 30 cases (50%) of tumours belonged to stage T2. Luminal molecular subtype was the most common 31 (51.67%) cases followed by TNBC, 16 (26.67%) cases and Her2neu 13 (21.67%) cases. Among all the cases, ALK overexpression was seen in 17 (28.33%) cases and among different molecular subtypes, its expression was seen in 5 (8.33%) cases of Luminal type, 3 (5.0%) cases of HER2 type and in 9 (15.0%) cases of TNBC cases. Conclusion: Immunohistochemical analysis showed ALK over expression in a substantial proportion of cases and possibly plays a significant role in aggressive behaviour of breast cancer. ALK inhibitors offer an opportunity to treat aggressive subtypes of breast cancer

HYPERSTAGE: AN ENHANCED APPROACH FOR HYPER ETL TO DELIVER A SELF-MANAGED ENVIRONMENT FOR OPTIMIZED AND ANALYTICS

A straightforward, painless to use and systematic process, rooted in Hyper ETL (Extraction, Transformation and Load) is put forward to assist in the selection among choices, with more than a few decision criteria. In order to expand significant selling reward, it is necessary to study the application of decision support system based on data mart. Hereby, we discuss the various decision analysis methods to take efficient decision making in data mart which hike revenue in the business. We construct ideas on how to put into action, and demonstrate them with sales records examples. The purpose of a vital sales data mart using Hyper ETL is to offer decision-makers entree to steady, trustworthy, and apt data for systematic forecast and planning

Agritourism as a preferred travelling trend in boosting rural economies in the post-COVID-19 period: Nexus between agriculture, tourism, art and culture

The COVID-19 global pandemic has caused a massive disruption in the global economy, especially the tourism and hospitality industry. The unpleasant experience of the COVID-19 pandemic and it’s post effects and the fear of a new wave of infections has thrown the tourism industry of many countries in limbo. Due to the growing interest in agritourism, it has become a preferred travelling trend in boosting the tourism revenues of countries, especially, those in the rural regions where the harsh economic impacts of the COVID-19 pandemic is greatly experienced. This mini-review of existing theoretical and empirical studies on agritourism aimed at discussing how agritourism as a tourism option for countries, could boost rural economies, promote cultural education and local traditional craft enterprises in this post-COVID-19 period. The study concludes that when skilfully managed with strict observation to the COVID-19 safety protocols, agritourism could be a preferred tourism resort for especially domestic visitors to generate tourism revenue for impoverished farmers and rural community members in the present post-COVID-19 era

Genetic diversity analysis using shoot and root morphological markers in castor (Ricinus communis L.)

The morphological variation and genetic diversity in 15 root and shoot characters was studied in 27 castor accessions sown in an elevated temporary root study structure. Variation in characters accounted to 3.05 to 50.29%. Characters were subjected to Shannon Weaver diversity index (H`) to know the genetic diversity. Eleven traits recorded high H` indicating suitability in breeding programmes. Their regression coefficients indicated positive change for six traits in dependent variable seed yield. Phenotypic correlation studies revealed that seed yield was significantly correlated to root dry weight, root diameter, plant height, node number, effective spike length and 100 seed weight. Principal component analysis (PCA) revealed that PC1, 2 and 3 accounted for 44.52, 15.93 and 10.54% variation. High loadings in the first three PCs were recorded for nine traits viz., root dry weight, shoot dry weight, root length, total root length, root diameter at crown region, SCMR, effective spike length, node number to primary spike. Hence, present studies gains importance in understanding the root related traits and their role in quantifying the genotypes in terms of divergence

Atrial septal defects: Pattern, clinical profile, surgical techniques and outcome at Innova heart hospital: A 4-year review

Background: Atrial septal defect (ASD) is a congenital heart defect that leads to shunting of blood between left and right atria. It may be asymptomatic and sometimes may present with heart failure. Surgical repair is definitive, but currently non-surgical procedure is used to close the defect. Materials and Methods: It is a retrospective study of patients who underwent transcatheter closure of ASD at Innova Heart Hospital, Hyderabad, India. Echocardiography was repeated at intervals of 24 hours, then at 1, 3 and 6 months after the procedure to assess complications. The morphological characteristics of the ASD, including its diameter, location, shape and the width of surrounding septal margins, were also evaluated. Results: From April 2007 to June 2011, 69 consecutive children (29 males, 40 females) with a median age of 9.0 years (range = 3.2-19 years) registered with diagnosis of ASD. The median weight was 31.5 kg (range = 7.5-39.0 kg). Five patients (7.2%) were young children aged 3-5 years. Forty-four (63.8%) of these children presented with symptoms of heart failure, whereas 47 (68.1%) of the cases repaired with device were large-sized ASD. The most common interventional procedures done were Searcare Heart® and Amplatzer® technique with a highest success rate obtained in 2010. Conclusions: ASD is a common congenital heart disease with a high success rate for those who undergo intervention