Prevalence of Ocular Morbidity Among School Adolescents of Gandhinagar District, Gujarat

Objective: To study the prevalence of ocular morbidity (abnormal condition) and various factors affecting it among school attending adolescents. Methods: A cross-sectional study was conducted to study abnormal ocular conditions like refractive errors, vitamin A deficiency, conjunctivitis, trachoma, ocular trauma, blephritis, stye, color blindness and pterygium among school adolescents of 10-19 years age in rural and urban areas of Gandhinagar district from January to July, 2009. Systematic sampling was done to select 20 schools having 6th to 12th standard education including 12 schools from rural and 8 from urban areas. Six adolescents from each age year (10-19) were selected randomly to achieve sample size of 60 from each school. In total, 1206 adolescents including 691 boys and 515 girls were selected. Information was collected from selected adolescents by using proforma. Visual acuity was assessed using a Snellen’s chart and all participants underwent an ophthalmic examination carried out by a trained doctor. Results: Prevalence of ocular morbidity among school adolescents was reported 13% (7.8% in boys, 5.6% in girls); with 5.2% have moderate visual impairment. Refractive error was most common ocular morbidity (40%) both among boys and girls. Almost 30% of boys and girls reported vitamin A deficiency in various forms of xerophthalmia. Prevalence of night blindness was 0.91% and of Bitot`s spot 1.74%. Various factors like, illiterate or lower parents’ education, lower socio-economic class and malnutrition were significantly associated with ocular morbidity. Conclusion: Ocular morbidity in adolescents is mainly due to refractive error, moderate visual impairment and xerophthalmia

Spin-Hall effect and circular birefringence of a uniaxial crystal plate

The linear birefringence of uniaxial crystal plates is known since the 17th century, and it is widely used in numerous optical setups and devices. Here we demonstrate, both theoretically and experimentally, a fine lateral circular birefringence of such crystal plates. This effect is a novel example of the spin-Hall effect of light, i.e., a transverse spin-dependent shift of the paraxial light beam transmitted through the plate. The well-known linear birefringence and the new circular birefringence form an interesting analogy with the Goos-H\"anchen and Imbert-Fedorov beam shifts that appear in the light reflection at a dielectric interface. We report the experimental observation of the effect in a remarkably simple system of a tilted half-wave plate and polarizers using polarimetric and quantum-weak-measurement techniques for the beam-shift measurements. In view of great recent interest in spin-orbit interaction phenomena, our results could find applications in modern polarization optics and nano-photonics.Comment: 16 pages, 8 figures, to appear in Optic

Spread of Malicious Objects in Computer Network: A Fuzzy Approach

We propose an e-epidemic fuzzy SEIQRS (Susceptible-Exposed-Infectious-Quarantine- Recovered-Susceptible) model for the transmission of malicious codes in a computer network. We have simulated the result for various parameters and analyzed the stability of the model. The efficiency of antivirus software and crashing of the nodes due to attack of malicious code is analyzed. Furthermore, initial simulation results illustrate the behavior of different classes for minimizing the infection in a computer network. It also reflects the positive impact of anti-virus software on malicious code propagation in a computer network. The basic reproduction number R0 f and its formulation is also discussed

Performance Analysis of LEACH with Deep Learning in Wireless Sensor Networks

Thousands of low-power micro sensors make up Wireless Sensor Networks, and its principal role is to detect and report specified events to a base station. Due to bounded battery power these nodes are having very limited memory and processing capacity. Since battery replacement or recharge in sensor nodes is nearly impossible, power consumption becomes one of the most important design considerations in WSN. So one of the most important requirements in WSN is to increase battery life and network life time. Seeing as data transmission and reception consume the most energy, it’s critical to develop a routing protocol that addresses the WSN’s major problem. When it comes to sending aggregated data to the sink, hierarchical routing is critical. This research concentrates on a cluster head election system that rotates the cluster head role among nodes with greater energy levels than the others.  We used a combination of LEACH and deep learning to extend the network life of the WSN in this study.  In this proposed method, cluster head selection has been performed by Convolutional Neural Network (CNN). The comparison has been done between the proposed solution and LEACH, which shows the proposed solution increases the network lifetime and throughput

Performance Analysis of LEACH with Deep Learning in Wireless Sensor Networks

Thousands of low-power micro sensors make up Wireless Sensor Networks, and its principal role is to detect and report specified events to a base station. Due to bounded battery power these nodes are having very limited memory and processing capacity. Since battery replacement or recharge in sensor nodes is nearly impossible, power consumption becomes one of the most important design considerations in WSN. So one of the most important requirements in WSN is to increase battery life and network life time. Seeing as data transmission and reception consume the most energy, it’s critical to develop a routing protocol that addresses the WSN’s major problem. When it comes to sending aggregated data to the sink, hierarchical routing is critical. This research concentrates on a cluster head election system that rotates the cluster head role among nodes with greater energy levels than the others.  We used a combination of LEACH and deep learning to extend the network life of the WSN in this study.  In this proposed method, cluster head selection has been performed by Convolutional Neural Network (CNN). The comparison has been done between the proposed solution and LEACH, which shows the proposed solution increases the network lifetime and throughput

A study of cesarean section rate by using modified Robson's ten group classification system

Background: High caesarean section rate worldwide including India is matter of concern. The Robson’s Ten-group classification system allows critical analysis of caesarean deliveries according to characteristics of pregnancy. The objective was to analyze caesarean section rates in a tertiary care centre according to Modified Robson’s ten groups classification.Methods: This retrospective study was conducted at GMERS Gotri Medical College, Vadodara, Gujarat, India. All patients who delivered between August 2018 and March 2019, were included in the study. Women were classified in 10 groups according to modified Robson’s classification using their maternal characteristics and obstetric history. For each group, authors calculated the caesarean section rate within the group and its absolute and relative contribution to the overall caesarean rate.Results: Total number of delivery in my study institute in 8 months was 1531 out of them 456 was cesarean section, so the overall caesarean section rate was 29.78%. The main contributions to overall caesarean rate was 40.78% by group 5 (previous CS, singleton, cephalic, >37weeks) followed by 14.25% by group 1 (nullipara, singleton, cephalic, >37 weeks, spontaneous labour), 11.40% by group 2 (nullipara, singleton, cephalic,>37 weeks, induced or CS before labour). CS rates among various group ranges from 100% among women with abnormal lie (group 9) to 98.4% in previous CS (group 5), 84% in nulliparous breech (group 6), 58% in multiparous breech (group 7) and least 8.2% in multipara spontaneous labour (group 3).Conclusions: The Robson’s classification is easy to use. It is time to implement obstetric audit to lower the overall CS rates

Impact of industrial wastes on the water quality of tropical river, Ami (India)

Industries discharge their effluents which are rich in solids, may it be in the form of TSS or TDS. These solids affect the other physicochemical parameters of the water body. Present study deals with the investigation of seasonal variation and statistical analyses of the selected parameters, in river Ami, in light of the industrial effluents. The study records that summer season, appears to be the most polluted, that is during the period when the river carries little amount of water. Statistical analysis showed that all the physicochemical parameters were positively correlated except TDS and temperature

Study the accuracy of salivary ferning test as a predictor of ovulation

Background: Women probably spent much of their adult life avoiding getting pregnant but when they are actively trying for a baby, it may be taking a little longer time than they hoped. So it is important for the women to know when they are ovulating. Recently, a small hand held microscope (KNOWHEN ovulation microscope) has been developed for the purpose of self-observing ferning patterns in saliva during female fertile period. The purpose of our study is to evaluate the accuracy of salivary ferning test by KNOWHEN ovulation microscope to predict the ovulation and to detect sensitivity and specificity of salivary ferning test and to correlate the salivary ferning with cervical mucus and Trans vaginal sonographic findings (TVS).Methods: This was a prospective observational type of study conducted on all healthy married women volunteers age between 21–40 years attending gynec OPD in sola civil hospital, Ahmedabad, with regular menstrual cycle From April 2016 to September 2016.Results: Salivary ferning test by KNOWHEN ovulation microscope is accurate method of detecting ovulation. Its accuracy was 86.5%.Conclusions: Salivary ferning test is a reliable test to detect fertile period of menstrual cycle. Hence can be use for monitoring ovulation instead of ultrasonography where facility of ultrasonography will not available. Detection of salivary ferning by KNOWHEN microscope has same accuracy as laboratory microscope. KNOWHEN microscope can be use by patient herself to detect fertile period

A study of efficacy of oral iron and intravenous iron sucrose in the treatment of moderate anemia in pregnancy

Background: Iron deficiency anaemia in pregnancy is a common medical problem throughout India with the burden of disease impacting on both mother and the newborn. It is also responsible for increased incidence of premature births, low birth weight babies and high perinatal mortality. Intravenous iron sucrose and oral iron therapy are the primary therapeutic modalities for management of iron deficiency anaemia during pregnancy, but its efficacy during pregnancy is still a matter of argument among healthcare personnel. Therefore the objective of this study is to compare the effect of oral iron and intravenous iron sucrose on hemoglobin and other blood indices among pregnant females with iron deficiency anemia.Methods: Randomized clinical trial was conducted among 400 females between 20 to 34 weeks gestation with iron deficiency anemia who were managed either with oral ferrous sulphate or intravenous iron sucrose therapy. Z test was used for statistical analysis for significance with 95% confidence interval. The hemoglobin and blood indices levels before and after initiating treatment in both groups were compared.Results: Intravenous and oral; both the treatments were associated with increment in hemoglobin but this rise was significantly more in the intravenous group than in oral. Comparing participants with low pretreatment hemoglobin among both groups, participants in the intravenous group were better benefited than oral due to respective treatment.Conclusions: Intravenous iron therapy is much effective in correcting iron deficiency anemia in pregnancy than oral iron therapy. It restores iron stores more promptly. Also intravenous iron is better tolerated compared to oral iron