A Cross-Sectional Study of Aggression among School Adolescents in Karnataka, India

Introduction: Adolescents are placed in critical stage of human development when they are stepping from childhood to adulthood. Worldwide, it is seen that aggression is one of the most common features in this group.Aims and Objectives: (1) To identify aggression among school-going adolescents and (2) To assess different sociodemographic characteristics associated with aggression among these studentsMethodology: A cross-sectional descriptive study was conducted in one of the private schools in Karnataka from 1st September to 1st December, 2015 (3 months). Study population comprised of high school children studying in classes VIII–X. A pre-tested, semi-structured, self-administered questionnaire was distributed to the study subjects. For assessing aggression, a modified version of direct and indirect aggression scale (DIAS) was used. School authority permitted the study. An information sheet and consent form was givento each student. The consent form was to be signed by a parent or guardian and returned to the school. Data was entered in MS-Excel. Data was analyzed by using frequency tables and significant association was established by chi-square test.Results: A total of 187 students participated in the present study. A significant proportion of adolescents scored very high on aggression scale. Males were found to be more aggressive than females and as the age of school children advanced, aggression scores also increased. And these results were statisticallysignificant (p<0.05).Conclusion: Overall, prevalence of aggression was high in adolescents, especially among males, late adolescents and Hindus and whose mothers were less educated. Understanding sex and age differences in the development of various types of aggressions during adolescence can guide the development ofviolence prevention programs. Such intervention programs should be started early in life to have the most impact on aggression during adolescence

Comparison of oral nifedipine and oral labetalol as a single drug therapy for control of blood pressure in preeclampsia

Background: Worldwide hypertension during pregnancy is a common cause of maternal and fetal morbidity and mortality. Effective control of blood pressure is one of the important steps in management of preeclampsia. Few drugs like nifedipine, labetalol, methyldopa, and hydralazine have acceptable high safety profile during pregnancy.Methods: In this study 120 antenatal women with non-severe preeclampsia were compared by giving either nifedipine or labetalol as a single drug therapy for control of blood pressure. Various parameters like control of blood pressure, side effects of drugs, gestational age at the time of delivery, mode of delivery, any complication and perinatal outcome were assessed.Results: In this study authors found that in both group, adequate control of blood pressure was achieved. This study shows slightly higher rate of pre term delivery and LSCS with labetalol and minimal side effects with nifedipine but difference in each group is insignificant.Conclusions: Labetalol and nifedipine both the drugs are equally effective in reducing blood pressure and any of it can safely be used as a first choice of drug for management of hypertension in preeclampsia and it can be decided as per clinician’s experience and familiarity with drug

Flexible Deep Learning in Edge Computing for Internet of Things

Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Traditional edge computing models have rigid characteristics. Flexible edge computing architecture solves rigidity in IoT edge computing. Proposed model combines deep learning into edge computing and flexible edge computing architecture using multiple agents. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. FEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. In the performance evaluation, we test the performance of executing deep learning tasks in FEC architecture for edge computing environment. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT

Flexible Deep Learning in Edge Computing for Internet of Things

Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Traditional edge computing models have rigid characteristics. Flexible edge computing architecture solves rigidity in IoT edge computing. Proposed model combines deep learning into edge computing and flexible edge computing architecture using multiple agents. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. FEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. In the performance evaluation, we test the performance of executing deep learning tasks in FEC architecture for edge computing environment. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT

Effect of nurse culture on inducing division of isolated pollen protoplasts of Hevea brasiliensis

Haploids are of great relevance in crop improvement of Hevea, a highly heterozygous tree species with a long breeding cycle. The isolation and culture of pollen protoplasts may be a viable proposition for raising haploid plants/ homozygous lines in Hevea. The present work envisages the development of a method for the isolation and culture of pollen protoplasts of Hevea. Effect of different nurse cultures on the development of cultured protoplasts has been studied. Intact pollen grains were isolated from mature male flowers of Hevea prior to opening. Viable protoplasts in high yield could be isolated from these pollen grains when exposed to a mixture of 0.5 per cent cellulase and 0.05 per cent pectolyase in the presence of the osmotic stabilizers 0.6 M mannitol and 0.3 M sorbitol. These protoplasts were partially purified and cultured in the nutrient medium with three different nurse cultures namely embryogenic calli from Hevea, tobacco and carrot. Division of the cultured protoplasts leading to the formation of a few micro-colonies was observed in the medium containing 0.8 mg l-1 2, 4-D and 0.5 mg l-1 BA and enriched with Hevea nurse culture. Cultures with micro-colonies are dark incubated for further development. This is the first report of division of pollen protoplasts and micro-colony formation in Hevea brasiliensis

Toll like receptors play a role in general immunity, eye infection and inflammation : TLRs for nanodelivery

Dendritic cells [DCs] are potent antigen presenting cells [APC], which plays a vital role in immune system by detecting and capturing pathogens in the body. DCs perform a pivotal role in induction of T cell response. Regulation of immune response can be achieved by specific antigen [Ag] delivery to DCs. A delivery system that can efficiently target and present Ags to DCs for the purpose of anti-tumour activity is currently a topic of significant research interest. DCs are receiving attention due to their key role in anti cancer host response and due to their adjuvanic property in tumour vaccines. Role of toll like receptors [TLR] in innate immune system and their part in eventual stimulation of adaptive immunity is exploited to develop vaccines. TLR agonists in conjugation with vaccines are shown to increase therapeutic efficacy in some cases. TLRs also play a vital role in protecting the cornea from invading pathogens. Due to adverse effects in the treatment of ocular inflammations, cancer and in viral infections, an alternate approach such as the use of TLRs will solve the inquisitive question regarding side effects. The intended delivery is attained by the use of nanoparticles which in turn leads to prolonged half-life in the body. Co-delivery of Ags, TLRs and immunomodulators using nanoparticles has been demonstrated to elicit potent cellular immune responses and are currently under development of clinically applicable immunisations and vaccines

A facile one pot synthetic approach for C3N4-ZnS composite interfaces as heterojunctions for sunlight-induced multifunctional photocatalytic applications

Herein, we report a facile one pot synthetic protocol for the creation of C3N4-ZnS composite interfaces by the co-pyrolysis of a precursor mix containing zinc nitrate, melamine, and thiourea at 550°C in air. The organic-inorganic semiconductor heterojunctions thus formed displayed increased absorbance in the longer wavelength region and facilitated broad absorption of visible light compared to pure ZnS, C3N4 and conventionally synthesized hybrid samples. The decreased emission intensity, increased photocurrent generation and decreased fluorescence lifetime revealed reduced exciton recombinations in the co-pyrolysed sample containing C3N4-ZnS heterostructures. The samples displayed sunlight driven photocatalytic reduction of nitrophenol as well as hydrogen generation (4 mmol g-1 h-1) by water splitting. © The Royal Society of Chemistry 2016