Designing Overlapping Networks for Publish-Subscribe Systems

From the publish-subscribe systems of the early days of the Internet to the recent emergence of Web 3.0 and IoT (Internet of Things), new problems arise in the design of networks centered at producers and consumers of constantly evolving information. In a typical problem, each terminal is a source or sink of information and builds a physical network in the form of a tree or an overlay network in the form of a star rooted at itself. Every pair of pub-sub terminals that need to be coordinated (e.g. the source and sink of an important piece of control information) define an edge in a bipartite demand graph; the solution must ensure that the corresponding networks rooted at the endpoints of each demand edge overlap at some node. This simple overlap constraint, and the requirement that each network is a tree or a star, leads to a variety of new questions on the design of overlapping networks. In this paper, for the general demand case of the problem, we show that a natural LP formulation has a non-constant integrality gap; on the positive side, we present a logarithmic approximation for the general demand case. When the demand graph is complete, however, we design approximation algorithms with small constant performance ratios, irrespective of whether the pub networks and sub networks are required to be trees or stars

Ice Shapes on a Tail Rotor

Testing of a thermally-protected helicopter rotor in the Icing Research Tunnel (IRT) was completed. Data included inter-cycle and cold blade ice shapes. Accreted ice shapes were thoroughly documented, including tracing, scanning and photographing. This was the first time this scanning capability was used outside of NASA. This type of data has never been obtained for a rotorcraft before. This data will now be used to validate the latest generation of icing analysis tools

Prospective of study of gestational diabetes mellitus risk in relation to maternal recreation physical activity before and after pregnancy

Background: Gestational diabetes mellitus is common complications of pregnancy. Physical activity is associated with a lower risk of type 2 diabetes mellitus. The present study aimed to know association between physical activity and gestational diabetes mellitus in the first 20 weeks of their pregnancy.Methods: In the current case-control study, 50 pregnant females with gestational diabetes mellitus as the case group and 50 pregnant females as control group were selected. To diagnose gestational diabetes mellitus using diagnostic criteria. Females with abnormal oral glucose challenge test (>140mg/dL) were asked to perform the three-hour 100 g oral glucose tolerance test. The details of physical activity were collected by pregnancy physical activity questionnaire. Anthropometric and other data were recorded for all of the participants.Results: Females with low total physical activity at early pregnancy were at a significantly higher risk of developing gestational diabetes mellitus compared to the ones with higher levels of physical activity. After adjusting for age, body mass index (BMI), gravidity and a family history of diabetes, females with low physical activity during 20 weeks of pregnancy were at a significantly higher risk of developing gestational diabetes mellitus. Females with the low intensity of sedentary, light and moderate physical activity are at a higher risk of developing gestational diabetes mellitus compared to females with a higher intensity of sedentary, light and moderate physical activity.Conclusions: Females should be encouraged to do regular daily physical activity during pregnancy, if there is no specific contraindication to it.

Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints

Efficacy of the multi-robot systems depends on proper sequencing and optimal allocation of robots to the tasks. Focuses on deciding the optimal allocation of set-of-robots to a set-of-tasks with precedence constraints considering multiple objectives. Taguchi’s design of experiments based parameter tuned genetic algorithm (GA) is developed for generalised task allocation of single-task robots to multi-robot tasks. The developed methodology is tested for 16 scenarios by varying the number of robots and number of tasks. The scenarios were tested in a simulated environment with a maximum of 20 robots and 40 multi-robot foraging tasks. The tradeoff between performance measures for the allocations obtained through GA for different task levels was used to decide the optimal number of robots. It is evident that the tradeoffs occur at 20 per cent of performance measures and the optimal number of robot varies between 10 and 15 for almost all the task levels. This method shows good convergence and found that the precedence constraints affect the optimal number of robots required for a particular task level

White Matter Deterioration May Foreshadow Impairment of Emotional Valence Determination in Early-Stage Dementia of the Alzheimer Type

In Alzheimer Disease (AD), non-verbal skills often remain intact for far longer than verbally mediated processes. Four (1 female, 3 males) participants with early-stage Clinically Diagnosed Dementia of the Alzheimer Type (CDDAT) and eight neurotypicals (NTs; 4 females, 4 males) completed the emotional valence determination test (EVDT) while undergoing BOLD functional magnetic resonance imaging (fMRI). We expected CDDAT participants to perform just as well as NTs on the EVDT, and to display increased activity within the bilateral amygdala and right anterior cingulate cortex (r-ACC). We hypothesized that such activity would reflect an increased reliance on these structures to compensate for on-going neuronal loss in frontoparietal regions due to the disease. We used diffusion tensor imaging (DTI) to determine if white matter (WM) damage had occurred in frontoparietal regions as well. CDDAT participants had similar behavioral performance and no differences were observed in brain activity or connectivity patterns within the amygdalae or r-ACC. Decreased fractional anisotropy (FA) values were noted, however, for the bilateral superior longitudinal fasciculi and posterior cingulate cortex (PCC). We interpret these findings to suggest that emotional valence determination and non-verbal skill sets are largely intact at this stage of the disease, but signs foreshadowing future decline were revealed by possible WM deterioration. Understanding how non-verbal skill sets are altered, while remaining largely intact, offers new insights into how non-verbal communication may be more successfully implemented in the care of AD patients and highlights the potential role of DTI as a presymptomatic biomarker

An Approach to Improve Multi objective Path Planning for Mobile Robot Navigation using the Novel Quadrant Selection Method

Currently, automated and semi-automated industries need multiple objective path planning algorithms for mobile robot applications. The multi-objective optimisation algorithm takes more computational effort to provide optimal solutions. The proposed grid-based multi-objective global path planning algorithm [Quadrant selection algorithm (QSA)] plans the path by considering the direction of movements from starting position to the target position with minimum computational effort. Primarily, in this algorithm, the direction of movements is classified into quadrants. Based on the selection of the quadrant, the optimal paths are identified. In obstacle avoidance, the generated feasible paths are evaluated by the cumulative path distance travelled, and the cumulative angle turned to attain an optimal path. Finally, to ease the robot’s navigation, the obtained optimal path is further smoothed to avoid sharp turns and reduce the distance. The proposed QSA in total reduces the unnecessary search for paths in other quadrants. The developed algorithm is tested in different environments and compared with the existing algorithms based on the number of cells examined to obtain the optimal path. Unlike other algorithms, the proposed QSA provides an optimal path by dramatically reducing the number of cells examined. The experimental verification of the proposed QSA shows that the solution is practically implementable

An Evidence based Research on Presence of Carcinogens and Increasing Spurts of Cancer Cases in Vaigai River Basin, India

Water is an inevitable part of living organisms. Water pollution is a serious environmental threat to people who consume, enter, and wash in contaminated water. The aim is to study the quantified levels of carcinogens in the environment, according to IARC Classification such as Arsenic, Benzene, Cadmium, Hexavalent Chromium, Cobalt, Nickel, Lead, Nitrite/Nitrate, and Phosphates and their correlation with increased spikes of cancer cases across districts that lie along Vaigai River Basin, Tamil Nadu, India. A Systematic literature review for cross-sectional studies that provided information about groundwater quality was carried out using six databases, "Researchgate, PubMed, Elsevier Science Direct, Wiley Online Library, Medline, and SpringerLink" from 2012 to 2022. The TNCRP report from 2021 was used as the basis for calculating the proportion of all cancer cases in the relevant district. Based on the Newcastle Ottawa Scale, a quality assessment was conducted. The results show the presence of high concentrations of carcinogens in the groundwater and sediments collected near the industries, commercial zones, and agricultural land. The significant association between exceeding the permissible limit of various heavy metal elements and compounds and the percentage of cancer cases at that particular site has been established in this study. Vaigai River is highly polluted such that the heavy metal concentration has already entered the human food chain. Oral findings commonly associated with chronic toxicity of carcinogenic heavy metals are listed which serves as an alarming signal to adapt to a healthy lifestyle and dietary modifications as required. &nbsp

Validation of Mobile Messages for an mHealth Intervention for Smokeless Tobacco Cessation in India

BACKGROUND: With the growth in use of mobile messages for behaviour change, the need to incorporate personal needs and cultural characteristics of target users has been promoted. The study aimed to describe the findings of content validation of mobile messages designed to promote smokeless tobacco cessation in primary care. METHODS: This study used a concurrent mixed-method approach with 13 patients who were tobacco users at urban primary care clinics. The clarity and appeal of 32 messages were rated on a Likert scale from 1 to 10. A mean clarity and appeal score per message was generated. A 5-item discussion guide was used for in-depth interviews and data was analysed using framework analysis. RESULTS: Participants found the content of the messages useful, and preferred shorter and audio formatted messages. The clarity scores for the messages ranged from 7.9 to 9.4 with an average score of 8.7 (SD 0.5). The appeal scores ranged from 7.3 to 9.2, with an average score of 8.5 (SD 0.6). CONCLUSIONS: Twenty-six from a total of 32 messages were found appropriate and finalised for use. This methodology can be used when developing contextually relevant mobile message interventions in other low resource settings