EZ-AG: Structure-free data aggregation in MANETs using push-assisted self-repelling random walks

This paper describes EZ-AG, a structure-free protocol for duplicate insensitive data aggregation in MANETs. The key idea in EZ-AG is to introduce a token that performs a self-repelling random walk in the network and aggregates information from nodes when they are visited for the first time. A self-repelling random walk of a token on a graph is one in which at each step, the token moves to a neighbor that has been visited least often. While self-repelling random walks visit all nodes in the network much faster than plain random walks, they tend to slow down when most of the nodes are already visited. In this paper, we show that a single step push phase at each node can significantly speed up the aggregation and eliminate this slow down. By doing so, EZ-AG achieves aggregation in only O(N) time and messages. In terms of overhead, EZ-AG outperforms existing structure-free data aggregation by a factor of at least log(N) and achieves the lower bound for aggregation message overhead. We demonstrate the scalability and robustness of EZ-AG using ns-3 simulations in networks ranging from 100 to 4000 nodes under different mobility models and node speeds. We also describe a hierarchical extension for EZ-AG that can produce multi-resolution aggregates at each node using only O(NlogN) messages, which is a poly-logarithmic factor improvement over existing techniques

Quadfinder: server for identification and analysis of quadruplex-forming motifs in nucleotide sequences

G-quadruplex secondary structures, which play a structural role in repetitive DNA such as telomeres, may also play a functional role at other genomic locations as targetable regulatory elements which control gene expression. The recent interest in application of quadruplexes in biological systems prompted us to develop a tool for the identification and analysis of quadruplex-forming nucleotide sequences especially in the RNA. Here we present Quadfinder, an online server for prediction and bioinformatics of uni-molecular quadruplex-forming nucleotide sequences. The server is designed to be user-friendly and needs minimal intervention by the user, while providing flexibility of defining the variants of the motif. The server is freely available at URL

Good Girls Don’t Go Online: Unpacking the Quotidian Playful Resilience Influencing Girls’ Social and Digital Engagements

In this study, we examine the ways in which young girls from low-income communities exercise their autonomy and agency in their engagement with digital technologies and, at times, show compliance with social norms when online. Based on our findings from our ethnographic fieldwork, we argue that young girls’ engagement with digital technologies reflects both submission to the dominant gender, class realities, and a sustained desire to create a fraying around the edges of systems for gendered surveillance-discipline. We develop the concept of “quotidian playful resilience” (QPR) to unpack the influence of gender norms and class-based experiences on young girls’ everyday digital practices. We define QPR as a meta practice that informs how girls access, use, and navigate digital technologies—including the infrastructural affordances and limitations and the realm of the digitalscape. The study explores the productive associations between gender, class, and technology in young girls’ digital encounters in India

To study the association of high sensitivity C-reactive protein with metabolic syndrome

Background: Metabolic Syndrome is a constellation of dyslipidemia (elevated triglycerides, low high-density lipoproteins (HDL)), elevation of arterial blood pressure (BP), dysregulated glucose homeostasis, and increased abdominal obesity.Methods: We studied the association of high sensitivity C-reactive protein with metabolic syndrome by case-control method in our tertiary care hospital in West U.P.Results: The mean age of cases and controls was 52.6 ± 7.7 and 51.4±7.0 years, respectively. There were 25 (50%) male and 25 (50%) female in case groups, and 27 (54%) males and 23 (46%) females in control group. Our analysis revelaed that there was a significant association between hs-CRP and the central obesity when compared in case-control group (3.57 vs 0.96 mg/L) (p value <0.001). There was no significant association between hs-CRP and high triglycerides, hypertension, diabetes, and reduced high density lipoprotein cholesterol.Conclusions: Raised hsCRP level can be considered as a surrogate marker of chronic inflammation in patients with metabolic syndrome

Breastfeeding counselling and support: is it adequate? a descriptive study from Rohtak, India

Background: Antenatal breastfeeding education and motivation along with postnatal encouragement and lactation support are likely to improve rates of early initiation and exclusive breastfeeding. This study was done to know whether antenatal and postnatal visits were utilized for promotion of optimum breastfeeding in addition to the routine obstetric services.Methods: This descriptive cross-sectional type of community based epidemiological study was conducted in rural and urban field practice area attached to Department of Community Medicine, Pt. B. D. Sharma PGIMS, Rohtak. A total of 500 mothers were studied. A pre-tested semi-structured interview schedule was used for interviewing the study subjects and house to house visits were carried out to collect the information.Results: Health functionaries were the source of information in 49.6% mothers in urban area as compared to only 29.2% in rural areas. Breastfeeding related information was better in the mothers counseled by health functionaries than not counseled group.Conclusions: Health functionaries should be instructed to inform all pregnant women about the benefits and management of breastfeeding during antenatal as well as postnatal visits. Existing breastfeeding education and postnatal support is not adequate in the population studied and needs to be strengthened

UNIQUE BENCHMARKING TOOL TO MEASURE RELATIVE CARDHOLDER CARBON FOOTPRINT COMPARED TO IN-MARKET AND GLOBAL PEERS

The present disclosure relates to a method and system for calculating Carbon (CO2) emission scores from customer purchase data and creating a score-based numerical representation to represent the carbon footprint with respect to the cardholder’s green-score benchmark. The present disclosure suggests mapping the MCCs to purchased item-level information to obtain CO2 intensity multipliers. Thereafter, the net carbon emission value is calculated based on the transaction data associated with the purchased items. Further, a visual representation of the numerical scale score is created to represent the user green score/carbon footprint