Impact of Environmental Degradation on Human Health

Degradation of environment is one of the most serious challenges before the mankind in today's world. Mankind has been facing a wide range of problem arising out of the degradation of environment. Not only the areas under human inhabitation, but the areas of the planet without human population have also been suffering from these problems. As the population increase day by day, the amenities are not improved simultaneously. With the advancement of science and technologies the needs of human beings has been changing rapidly. As a result different types of environmental problems have been rising. Environmental degradation is a wide- reaching problem and it is likely to influence the health of human population is great. It may be defined the deterioration of the environment through depletion of resources such as air, water, and soil. The destruction of ecosystem and extinction of wildlife. Environmental degradation has occurred due to the recent activities in the field of socio-economic, institute and technology. Poverty still remains a problem as the root of several environmental problems to create awareness among the people about the ill effect of environmental pollution. In the whole research it is clear that all factors of environmental degradation may be reduced through- Framing the new laws on environmental degradation, Environment friend policy, Controlling all the ways and means of noise, air, soil and water pollution, Through growing more and more trees and by adapting the proper sanitation policy.&nbsp

Reaction Time of a Group of Physics Students

The reaction time of a group of students majoring in Physics is reported here. Strong co-relation between fatigue, reaction time and performance have been seen and may be useful for academicians and administrators responsible of working out time-tables, course structures, students counsellings etc.Comment: 10 pages, 4 figure

Level of dietary protein intake affects glucose turnover in endurance-trained men

<p>Abstract</p> <p>Background</p> <p>To examine the effects of higher-protein diets on endogenous glucose metabolism in healthy, physically active adults, glucose turnover was assessed in five endurance-trained men (age 21.3 ± 0.3 y, VO_2peak70.6 ± 0.1 mL kg^-1min^-1) who consumed dietary protein intakes spanning the current dietary reference intakes.</p> <p>Findings</p> <p>Using a randomized, crossover design, volunteers consumed 4 week eucaloric diets providing either a low (0.8 g kg^-1d^-1; LP), moderate (1.8 g kg^-1d^-1; MP), or high (3.6 g kg^-1d^-1; HP) level of dietary protein. Glucose turnover (Ra, glucose rate of appearance; and Rd glucose rate of disappearance) was assessed under fasted, resting conditions using primed, constant infusions of [6,6-²H₂] glucose. Glucose Ra and Rd (mg kg^-1min^-1) were higher for MP (2.8 ± 0.1 and 2.7 ± 0.1) compared to HP (2.4 ± 0.1 and 2.3 ± 0.2, <it>P </it>< 0.05) and LP (2.3 ± 0.1 and 2.2 ± 0.1, <it>P </it>< 0.01) diets. Glucose levels (mmol/L) were not different (<it>P </it>> 0.05) between LP (4.6 ± 0.1), MP (4.8 ± 0.1), and HP (4.7 ± 0.1) diets.</p> <p>Conclusions</p> <p>Level of protein consumption influenced resting glucose turnover in endurance athletes in a state of energy balance with a higher rate of turnover noted for a protein intake of 1.8 g kg^-1d^-1. Findings suggest that consumption of protein in excess of the recommended dietary allowance but within the current acceptable macronutrient distribution range may contribute to the regulation of blood glucose when carbohydrate intake is reduced by serving as a gluconeogenic substrate in endurance-trained men.</p

The Dispersion Velocity of Galactic Dark Matter Particles

The self-consistent spatial distribution of particles of Galactic dark matter is derived including their own gravitational potential, as also that of the visible matter of the Galaxy. In order to reproduce the observed rotation curve of the Galaxy the value of the dispersion velocity of the dark matter particles, \rmsveldm, should be \sim 600\kmps or larger.Comment: RevTex, 4 pages, 1 ps figure, accepted for publication in Physical Review Letter

Trust and Reputation Modelling for Tourism Recommendations Supported by Crowdsourcing

Tourism crowdsourcing platforms have a profound influence on the tourist behaviour particularly in terms of travel planning. Not only they hold the opinions shared by other tourists concerning tourism resources, but, with the help of recommendation engines, are the pillar of personalised resource recommendation. However, since prospective tourists are unaware of the trustworthiness or reputation of crowd publishers, they are in fact taking a leap of faith when then rely on the crowd wisdom. In this paper, we argue that modelling publisher Trust & Reputation improves the quality of the tourism recommendations supported by crowdsourced information. Therefore, we present a tourism recommendation system which integrates: (i) user profiling using the multi-criteria ratings; (ii) k-Nearest Neighbours (k-NN) prediction of the user ratings; (iii) Trust & Reputation modelling; and (iv) incremental model update, i.e., providing near real-time recommendations. In terms of contributions, this paper provides two different Trust & Reputation approaches: (i) general reputation employing the pairwise trust values using all users; and (ii) neighbour-based reputation employing the pairwise trust values of the common neighbours. The proposed method was experimented using crowdsourced datasets from Expedia and TripAdvisor platforms.info:eu-repo/semantics/publishedVersio

Towards Better Integration of Surrogate Models and Optimizers

Surrogate-Assisted Evolutionary Algorithms (SAEAs) have been proven to be very effective in solving (synthetic and real-world) computationally expensive optimization problems with a limited number of function evaluations. The two main components of SAEAs are: the surrogate model and the evolutionary optimizer, both of which use parameters to control their respective behavior. These parameters are likely to interact closely, and hence the exploitation of any such relationships may lead to the design of an enhanced SAEA. In this chapter, as a first step, we focus on Kriging and the Efficient Global Optimization (EGO) framework. We discuss potentially profitable ways of a better integration of model and optimizer. Furthermore, we investigate in depth how different parameters of the model and the optimizer impact optimization results. In particular, we determine whether there are any interactions between these parameters, and how the problem characteristics impact optimization results. In the experimental study, we use the popular Black-Box Optimization Benchmarking (BBOB) testbed. Interestingly, the analysis finds no evidence for significant interactions between model and optimizer parameters, but independently their performance has a significant interaction with the objective function. Based on our results, we make recommendations on how best to configure EGO

Overlapping SETBP1 gain-of-function mutations in Schinzel-Giedion syndrome and hematologic malignancies

Schinzel-Giedion syndrome (SGS) is a rare developmental disorder characterized by multiple malformations, severe neurological alterations and increased risk of malignancy. SGS is caused by de novo germline mutations clustering to a 12bp hotspot in exon 4 of SETBP1. Mutations in this hotspot disrupt a degron, a signal for the regulation of protein degradation, and lead to the accumulation of SETBP1 protein. Overlapping SETBP1 hotspot mutations have been observed recurrently as somatic events in leukemia. We collected clinical information of 47 SGS patients (including 26 novel cases) with germline SETBP1 mutations and of four individuals with a milder phenotype caused by de novo germline mutations adjacent to the SETBP1 hotspot. Different mutations within and around the SETBP1 hotspot have varying effects on SETBP1 stability and protein levels in vitro and in in silico modeling. Substitutions in SETBP1 residue I871 result in a weak increase in protein levels and mutations affecting this residue are significantly more frequent in SGS than in leukemia. On the other hand, substitutions in residue D868 lead to the largest increase in protein levels. Individuals with germline mutations affecting D868 have enhanced cell proliferation in vitro and higher incidence of cancer compared to patients with other germline SETBP1 mutations. Our findings substantiate that, despite their overlap, somatic SETBP1 mutations driving malignancy are more disruptive to the degron than germline SETBP1 mutations causing SGS. Additionally, this suggests that the functional threshold for the development of cancer driven by the disruption of the SETBP1 degron is higher than for the alteration in prenatal development in SGS. Drawing on previous studies of somatic SETBP1 mutations in leukemia, our results reveal a genotype-phenotype correlation in germline SETBP1 mutations spanning a molecular, cellular and clinical phenotype

Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study

Background: Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries. Methods and Findings: We obtained weekly virology and underlying cause-of-death mortality time series for 2005–2009 for 20 countries covering ~35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%–85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in person