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Introduction: Hemoglobinopathies and thalassemias are the most common single gene disorders in the world. World Health Organization figures estimate that 5% of the world populations are carriers of a potentially pathological hemoglobin (Hb) gene. The general incidence of thalassemia trait and sickle cell anaemia in India varies between 3-17% and 1-44% respectively3 but because of consanguinity, caste and area endogamy, some communities show a very high incidence, making the disease a major public health problem in our country. Cation exchange high-performance liquid chromatography (CE-HPLC) is one of the best methods for screening, detection, and identification of various hemoglobinopathies. Material &Method: A retrospective study was carried out from period of 2017 to 2019 with 106277 cases evaluated with an aim to identify various hemoglobinopathies seen in Indian population by high-performance liquid chromatography. Cases outside Indian geographical location were excluded from the study Result: A total of 18,936(17.82%) cases with abnormal haemoglobin variants was reported in the study with 35 difference variants across India. Northeast India reported maximum abnormal hemoglobinopathies (50.16%). Beta Thalassemia Trait was the most common abnormal variant found.Such a high incidence emphasises premarital and prenatal screening for prevention of dangerous effects of hemoglobinopathies in the population. Conclusion: CE-HPLC should be used for early detection and proper management of these haemoglobinopathies. The most common hemoglobinopathy observed in our study was Beta thalassemia trait followed by Sickle cell trait and then sickle cell disease. It was also observed that Northeast India had maximum abnormal hemoglobinopathies.

One of the most important topics of intelligent transportation system is the License Plate Recognition (LPR). LPR systems have many potential applications in intelligent traffic systems, such as the payment of parking fee, highway toll fee, traffic data collection, traffic monitoring systems, traffic law enforcement, security control of restricted areas and so on. LPR was developed to identify vehicles by the contents of their license plates. The LPR system consists of three major modules: license plate extraction, segmentation and recognition of individual characters. This paper presents a study of applying the neural network approach for character image recognition. The new approach is tested on 400 samples of extracted license plate images captured in outdoor environment. The result yield 99.2% recognition accuracy, the method takes 1.6 seconds to perform the car plate recognition from vehicle's image. In order to decrease problems such as low quality and low contrast in the vehicle images, image recognition is done by the two different methods first is feed forward method and another is Radial Basis function and the best one is selected. The algorithm based on neural network which can quickly and correctly detect the region of license plate and the license plate detecting rate of success is 99.2%.

Introduction: Covid 19 pandemic has affected the world deeply and continues to affect even after 2 years of its outbreak. As the signs and symptoms of coronavirus disease 2019 overlap with those of other respiratory pathogens it necessitated laboratory testing to specically identify individuals infected with Covid 19. The initial testing began by using the standard RT-PCR method. In certain situations, individuals without obvious signs and symptoms of SARS-COV 2 also require RT PCR testing. Once detected positive, these patients get triaged on the basis of their symptoms and the abnormalities in their laboratory ndings as per their age and comorbidities. The testing rate has been ramped up signicantly over the last two years and continues to rise till date. With the variety of laboratory diagnostic tests available an informed prognosis can be made. In this study we performed a retrospective analysis of laboratory investigations in COVID RTPCR positive patients in India including all age groups and gender. The Aim of this study was to correlate the ndings of covid monitoring tests such as IL-6, D-Dimer that were performed in Covid RT PCR positive patients at our center and report the variations noted when analyzed with parameters i.e. Age and Gender. Materials and Methodology: This retrospective study was performed at GRL Laboratory, Metropolis, Mumbai. Data of covid st th RT PCR positive patients who underwent covid allied tests was retrieved for the period starting from 1 June 2020 till 30 June 2021. The laboratory values of covid monitoring proles which included tests-- CBC with Neutrophil to lymphocyte ratio, IL6, cardiac troponin, D Dimer, ferritin, CRP, PT, LDH, Albumin, liver enzymes (SGPT), creatinine & ESR, were collected and were correlated with Age and Gender of the COVID 19 positive patients. Results: The study included 1141 conrmed Covid 19 patients in the cohort group of which 524(45.9%) were female and 617(54.08%) were male. 43.9% < 45 years of age and 56% > 45 years of age. C-reactive protein (CRP) was elevated in 41.4%, Ddimer in 20.2% with signicant variation noted in age and gender along with erythrocyte sedimentation rate (ESR). In majority patients, increased neutrophils and decreased lymphocytes were observed. Patients above 45 years of age showed higher neutrophil (p = 0.002) and lower absolute lymphocyte (p = 0.022) counts than adults below 45 years of age. Conclusion: Following biomarkers were found to be mostly elevated in patient with COVID-19: High Sensitive Troponin, NLR, Absolute Basophil Count, Ferritin, CRP, Hemoglobin and IL6. Biomarkers abnormality tends to vary with gender and age group. The analysis illustrates the value of laboratory parameters can be rapid and cost-effective biomarkers for prognostication in patients with COVID-19.