On the Efficacy of Fine-Grained Traffic Splitting Protocols in Data Center Networks

Multi-rooted tree topologies are commonly used to construct high-bandwidth data center network fabrics. In these networks, switches typically rely on equal-cost multipath (ECMP) routing techniques to split traffic across multiple paths, such that packets within a flow traverse the same end-to-end path. Unfortunately, since ECMP splits traffic based on flow-granularity, it can cause load imbalance across paths resulting in poor utilization of network resources. More finegrained traffic splitting techniques are typically not preferred because they can cause packet reordering that can, according to conventional wisdom, lead to severe TCP throughput degradation. In this work, we revisit this fact in the context of regular data center topologies such as fat-tree architectures. We argue that packet-level traffic splitting, where packets of a flow are sprayed through all available paths, would lead to a better load-balanced network, which in turn leads to significantly more balanced queues and much higher throughput compared to ECMP

Genetic analysis of agronomic and biochemical variables among different tomato (Solanum lycopersicum L.) accessions

In the present study, thirty accessions of tomato were evaluated for estimation of correlation and path analysis among various quantitative and qualitative characters related to fruit yield. There were highly significant differences among the accessions for all the characters studied as per the analysis of variance. Genotypic correlation coefficients were generally similar in nature and higher in magnitude than the corresponding phenotypic correlation coefficients. The results revealed that the fruit yield plant-1 was significantly and positively correlated with number of fruits plant-1 (0.3119 and 0.3184) followed by fruit set percentage (0.2434 and 0.2499), fruit weight (0.6766 and 0.6731), polar diameter of fruit (0.4687 and 0.4635) at genotypic and phenotypic level, respectively, indicating that effective improvement in fruit yield plant-1 through these characters could be achieved. Fruit weight showed positive and significant genotypic and phenotypic correlation with fruit yield plant-1 by having greatest positive direct effect (1.1298 and 1.1116) on fruit yield plant-1 at both levels, indicating the true relationship between them and the feasibility to exploit the potentiality of this trait for effective direct selection to improve fruit yield plant-1

Study of Thyroid Function Tests in Patients with Metabolic Syndrome

Background: The metabolic syndrome is a constellation of clinical and metabolic abnormalities including abdominal obesity, hypertension, dyslipidemia and impaired fasting glucose or impaired glucose tolerance. Metabolic syndrome and thyroid dysfunction are independent risk factors for cardiovascular disease. Aims and objectives: To study the prevalence, symptomatology of thyroid dysfunction and fine needle aspiration cytology (FNAC) findings of thyroidin the patients having metabolic syndrome. Material and methods: The study was carried out in 60 cases of metabolic syndrome (according to NCEP ATP III criteria) selected from the medicine outdoor clinic (including diabetic clinics, thyroid clinics) and medicine indoor wards in Post Graduate Department of Medicine, SN Medical College and Hospital, Agra. Diagnosis of thyroid dysfunction was made by history, examination and serum FT4 and TSH. Resultand observations: Out of 60 patients of metabolic syndrome, 30 patients (50%) were euthyroid, 13 patients (21.66%) had subclinical hypothyroid and 12 patients (20%) had overt hypothyroid. Five patients (8.33%) of metabolic syndrome had hyperthyroidism. Truncal obesity was most prevalent (80.0%) component of metabolic syndrome, followed by hypertriglyceridemia (70%). Diabetes mellitus was equally prevalent in both males as well as females and was presentin about 40.0% patients and 53% of patients with metabolic syndrome were hypertensive. Conclusion: This study shows that 50% metabolic syndrome patients had thyroid dysfunction. About 21.66% had subclinical hypothyroidism, 20% had overt hypothyroidism and 8.33% were having hyperthyroidism. The most common symptom in metabolic syndrome patients with hypothyroidism was lethargy/sleepiness followed by dry and coarse skin. The most commonsymptom in hyperthyroid patients was nervousness (100%) followed by sweating, heat intolerance and palpitation in 80% of the patients

Study of Thyroid Function Tests in Patients with Metabolic Syndrome

Background: The metabolic syndrome is a constellation of clinical and metabolic abnormalities including abdominal obesity, hypertension, dyslipidemia and impaired fasting glucose or impaired glucose tolerance. Metabolic syndrome and thyroid dysfunction are independent risk factors for cardiovascular disease. Aims and objectives: To study the prevalence, symptomatology of thyroid dysfunction and fine needle aspiration cytology (FNAC) findings of thyroid in thepatients having metabolic syndrome. Material and methods: The study was carried out in 60 cases of metabolic syndrome (according to NCEP ATP III criteria) selected from the medicine outdoor clinic (including diabetic clinics, thyroid clinics) and medicine indoor wards in Post Graduate Department of Medicine, SN Medical College and Hospital, Agra. Diagnosis of thyroid dysfunction was made by history, examination and serum FT4 and TSH. Result and observations: Out of 60 patients of metabolic syndrome, 30 patients (50%) were euthyroid, 13 patients (21.66%) had subclinical hypothyroid and 12 patients (20%) had overt hypothyroid. Five patients (8.33%) of metabolic syndrome had hyperthyroidism. Truncal obesity was most prevalent (80.0%) component of metabolic syndrome, followed by hypertriglyceridemia (70%). Diabetes mellitus was equally prevalent in both males as well as females and was present in about 40.0% patients and 53% of patients with metabolic syndrome were hypertensive. Conclusion: This study shows that 50% metabolic syndrome patients had thyroid dysfunction. About 21.66% had subclinical hypothyroidism, 20% had overt hypothyroidism and 8.33% were having hyperthyroidism. The most common symptom in metabolic syndrome patients with hypothyroidism was lethargy/ sleepiness followed by dry and coarse skin. The most common symptom in hyperthyroid patients was nervousness (100%) followed by sweating, heat intolerance and palpitation in 80% of th

Role of Organochlorine Pesticides in Chronic Kidney Diseases of Unknown Etiology

Chronic kidney disease (CKD) contributes to a significant burden on the healthcare system and economy worldwide. In the last two decades, a new form of CKD: chronic kidney disease of unknown etiology (CKDu) in which the disease is not attributed to known causes has emerged as a major health issue in different geographical areas over the world mainly from farming community and has become a global concern today. Despite intense and numerous research works dedicated to CKDu, very little is known with certainty regarding its etiology and the pathophysiology behind its development. Recent evidences are emerging in favor of possible role of agrochemicals and pesticides in the pathogenesis of CKDu. Organochlorine pesticides (OCPs) due to their longer half-life and lipophilic nature persist long in the environment and are known to be biomagnified through food chain. Some study reports by the authors and a few others constitute the important body of evidences depicting the association between chronic exposures to OCPs and occurrence of CKDu through environmental contamination in farming as well as non-farming communities in different geographical areas around the globe

In situ intercalation dynamics in inorganic-organic layered perovskite thin films.

The properties of layered inorganic semiconductors can be manipulated by the insertion of foreign molecular species via a process known as intercalation. In the present study, we investigate the phenomenon of organic moiety (R-NH3I) intercalation in layered metal-halide (PbI2)-based inorganic semiconductors, leading to the formation of inorganic-organic (IO) perovskites [(R-NH3)2PbI4]. During this intercalation strong resonant exciton optical transitions are created, enabling study of the dynamics of this process. Simultaneous in situ photoluminescence (PL) and transmission measurements are used to track the structural and exciton evolution. On the basis of the experimental observations, a model is proposed which explains the process of IO perovskite formation during intercalation of the organic moiety through the inorganic semiconductor layers. The interplay between precursor film thickness and organic solution concentration/solvent highlights the role of van der Waals interactions between the layers, as well as the need for maintaining stoichiometry during intercalation. Nucleation and growth occurring during intercalation matches a Johnson-Mehl-Avrami-Kolmogorov model, with results fitting both ideal and nonideal cases.This work is part of High-Impact Research scheme of IIT Delhi, Nano Research Facility (MCIT, Govt. Of India), UK-India Education and Research Initiative (UKIERI) programme, and part funded by EPSRC grant EP/G060649/1, and ERC LINASS 320503.This material is excerpted from a work that was published in ACS Applied Materials and Interfaces, copyright © American Chemical Society after peer review. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/am501568

Investigation of DNA damage response and apoptotic gene methylation pattern in sporadic breast tumors using high throughput quantitative DNA methylation analysis technology

<p>Abstract</p> <p>Background-</p> <p>Sporadic breast cancer like many other cancers is proposed to be a manifestation of abnormal genetic and epigenetic changes. For the past decade our laboratory has identified genes involved in DNA damage response (DDR), apoptosis and immunesurvelliance pathways to influence sporadic breast cancer risk in north Indian population. Further to enhance our knowledge at the epigenetic level, we performed DNA methylation study involving 17 gene promoter regions belonging to DNA damage response (DDR) and death receptor apoptotic pathway in 162 paired normal and cancerous breast tissues from 81 sporadic breast cancer patients, using a high throughput quantitative DNA methylation analysis technology.</p> <p>Results-</p> <p>The study identified five genes with statistically significant difference between normal and tumor tissues. Hypermethylation of <it>DR5 </it>(P = 0.001)<it>, DCR1 </it>(P = 0.00001)<it>, DCR2 </it>(P = 0.0000000005) and <it>BRCA2 </it>(P = 0.007) and hypomethylation of <it>DR4 </it>(P = 0.011) in sporadic breast tumor tissues suggested a weak/aberrant activation of the DDR/apoptotic pathway in breast tumorigenesis. Negative correlation was observed between methylation status and transcript expression levels for <it>TRAIL</it>, <it>DR4</it>, <it>CASP8</it>, <it>ATM</it>, <it>CHEK2</it>, <it>BRCA1 </it>and <it>BRCA2 </it>CpG sites. Categorization of the gene methylation with respect to the clinicopathological parameters showed an increase in aberrant methylation pattern in advanced tumors. These uncharacteristic methylation patterns corresponded with decreased death receptor apoptosis (P = 0.047) and DNA damage repair potential (P = 0.004) in advanced tumors. The observation of BRCA2 -26 G/A 5'UTR polymorphism concomitant with the presence of methylation in the promoter region was novel and emerged as a strong candidate for susceptibility to sporadic breast tumors.</p> <p>Conclusion-</p> <p>Our study indicates that methylation of DDR-apoptotic gene promoters in sporadic breast cancer is not a random phenomenon. Progressive epigenetic alterations in advancing tumors result in aberrant DDR-apoptotic pathway thereby promoting tumor development. We propose, since pathological epigenetic changes of the DDR-apoptotic genes are reversible modifications, these could further be targeted for therapeutic interventions.</p

DEEP LEARNING-BASED INTRUSION DETECTION AND PREVENTION IN WIRELESS COMMUNICATION

Wireless sensor networks (WSNs) are made up of a large number of sensor nodes which collect data and send it to a centralized location. Nevertheless, the WSN has several security difficulties because of resource-constrained nodes, deployment methodologies, and communication channels. So, it is very necessary to identify illegal access in order to strengthen the safety measures of WSN. The use of network intrusion detection systems (IDS) to safeguard the network is now standard procedure for any communication system. While deep learning (DL) methods are often utilized in IDS, their efficacy falls short when faced with imbalanced attacks. An IDS based on a novel transfer deep multicolumn convolution neural network (TDMCNN) technique was presented in this study to address this problem and boost performance. The most significant features of the dataset are chosen using a cross-correlation procedure and then included into the suggested methods for detecting intrusions. The accuracy, precision, sensitivity, and specificity are used to conduct the analysis and comparison. The experimental findings verified the effectiveness of the suggested method over the status quo of deep learning models for attack detection