Surface characterization of sol-gel derived indium tin oxide films on glass

Indium tin oxide (ITO) films containing different In : Sn atomic ratios, viz. 90 :10, 70 :30, 50 : 50, 30 :70, were deposited on two types of glass substrates by sol-gel spinning technique. XPS analysis of the films was done under as-received and after-sputtering conditions. The narrow spectra obtained for the Na1s, In3d, Sn3d and O1s have been discussed. Oxygen was found to exist in three chemical environments in as-received samples due to the existence of (i) environmental hydroxyl (-OH) group, (ii) crystalline ITO and (iii) amorphous ITO; but it was in two chemical environments, (ii) and (iii), after surface cleaning by sputtering. The presence of both tin metal and tin oxides was confirmed by the peak analysis of Sn3d. The In : Sn atomic ratio taken in the precursor sols did not change considerably in the case of developed films of low Sn content, but considerable change was observed in the films having high Sn content.     

Parallel 3D Mortar Element Method for Adaptive Nonconforming Meshes

We present a new two-step “intermediate mortar” approach that efficiently extends the Mortar Element Method (MEM) to 3D meshes with nonconforming discretizations. The technique utilizes projection matrices derived in 2D, thereby avoiding the need to explicitly form large matrices for the 3D cases. The method also allows more flexibility for both h- and p-type adaptation. Parallel implementations with OpenMP and multithreading compiler directives are used to solve a moving heat source problem on SGI Origin and Cray MTA machines. Numerical results demonstrate the advantages of adaptive nonconforming meshes with MEM over uniformly fine meshes.     

Responses of the autonomic nervous system during acclimatization tp high altitude in man

A study has been conducted on 20 sojourners, between the ages of 20-30 years, to evaluate responses of the autonomic nervous system during acclimatization to high altitude. The responses measured consisted of heart rate (HR), blood pressure (BP), oral temperature (Tor), mean skin temperature (Tsk), cold pressor response (CPR), orthostatic tolerance to tilt, and urinary catecholamines. The subjects were tested initially at Delhi (altitude 260 m) and thereafter, on acute induction to an altitude of 3500 m periodically for 3 weeks. For comparison, the same responses were studied on 10 acclimatized lowlanders (AL) who had been staying at the same altitude for more than a year and on 10 high-altitude natives (HAN). The studies showed a rise in HR, BP, Tor, and urinary catecholamines, and a fall in Tsk, CPR, and orthostatic tolerance immediately on arrival at HA, indicating a relative hyperactivity of the sympathetic system. After a stay of 1 week, there was a gradual recovery in all the responses, though sympathetic hyperactivity was still maintained throughout the 3 weeks of stay. In AL also there was a preponderance of sympathetic activity, though of relatively lesser magnitude than that seen in sojourners. In HAN, on the other hand, there was a relative parasympathetic predomination. It has been concluded that in lowlanders it takes more than a year of stay at altitude for complete recovery of autonomic balance.     

Field studies on the mosquito repellent action of neem oil

Repellent action of neem oil was evaluated against different mosquito species. 2% neem oil mixed in coconut oil provided 96-100% protection from anophelines, 85% from Aedes, 37.5% from Armigeres whereas it showed wide range of efficacy from 61-94% against Culex spp. Therefore, neem oil can be applied as a personal protection measure against mosquito bites.     

ReIDD: reliability-aware intelligent data dissemination protocol for broadcast storm problem in vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) have emerged as fast growing networks with aims to provide safety, and comfort to the onboard passengers. But, in this environment reliable data dissemination to the destination nodes is one of the biggest challenges as there may be a congestion in the network due to blind flooding of messages to their final destination, called as broadcast storm which may lead to the performance degradation with respect to the metric such as-message delivery, reliability and response time. To address this issue, in this paper, we propose a reliability-aware intelligent data dissemination protocol for broadcast storm problem in VANETs. We have solved the above specified problem using game theory concepts in which players, strategy space and decisions with respect to the current state of the system. To reduce the message overhead with respect to the communication cost among the players of the game, in the proposed scheme, messages are routed to the next destination by selecting the most reliable path in an intelligent manner. A coalition game is formulated among the vehicles by considering vehicles as the players in the game. Each player in the game has an initial payoff value based upon the parameters such as-communication range, storage requirements, and computation power. Based upon the payoff value of the players in the game, different coalitions/clusters are formulated among the players in the proposed scheme. Then, the players send the messages to the other vehicles/players within the same coalition which increases the reliability of transmission. In the proposed scheme, messages are unicasted to their final destination in an intelligent manner. Different algorithms are designed for coalition formation, maintenance, and reliability-aware data dissemination. The performance of the proposed scheme is evaluated using various evaluation metrics such as-service time, packet delivery ration, and throughput. The results obtained prove the effectiveness of the proposed scheme as compared to the other state-of-the-art existing schemes.     

Seasonal influence on urban dust PAH profile and toxicity in Sydney, Australia

Road dust is one of the major threats to the urban environment due to wash-off of dust to the surrounding catchments during wet weather period. The dust contains wide range of toxic contaminants such as heavy metals, polycyclic aromatic hydrocarbons (PAHS) and endocrine disrupting chemicals. Among the toxic contaminants, PAHs are of environmental concern due to their potential carcinogenic and mutagenic effect besides endocrine disruptive behaviour. Eighteen road dust samples from Sydney were collected in different time periods for a year and analysed for 16 US EPA PAHS. Total PAHs content range in the dust was 9-105 pg/g. Total and individual PAH contents were highest in the finest size fraction (<75 microm) and in winter compared to the other seasons. The PAH profiles in the different particle sizes were similar but different between the four seasons. The concentrations of higher molecular weight PAHS (4- and 5-rings) were much greater than the concentrations of lower molecular weight PAHs (2- and 3-rings). Toxicity equivalency factor application showed that the longer the dry weather period the higher the total PAHs content and toxicity in the dust.     

Fuzzy R&D portfolio selection of interdependent projects

Global competition of markets has forced firms to invest in targeted R&D projects so that resources can be focused on successful outcomes. A number of options are encountered to select the most appropriate projects in an R&D project portfolio selection problem. The selection is complicated by many factors, such as uncertainty, interdependences between projects, risk and long lead time, that are difficult to measure. Our main concern is how to deal with the uncertainty and interdependences in project portfolio selection when evaluating or estimating future cash flows. This paper presents a fuzzy multi-objective programming approach to facilitate decision making in the selection of R&D projects. Here, we present a fuzzy tri-objective R&D portfolio selection problem which maximizes the outcome and minimizes the cost and risk involved in the problem under the constraints on resources, budget, interdependences, outcome, projects occurring only once, and discuss how our methodology can be used to make decision support tools for optimal R&D project selection in a corporate environment. A case study is provided to illustrate the proposed method where the solution is done by genetic algorithm (GA) as well as by multiple objective genetic algorithm (MOGA).     

Dynamic hierarchical reactive controller synthesis

In the formal approach to reactive controller synthesis, a symbolic controller for a possibly hybrid system is obtained by algorithmically computing a winning strategy in a two-player game. Such game-solving algorithms scale poorly as the size of the game graph increases. However, in many applications, the game graph has a natural hierarchical structure. In this paper, we propose a modeling formalism and a synthesis algorithm that exploits this hierarchical structure for more scalable synthesis. We define local games on hierarchical graphs as a modeling formalism that decomposes a large-scale reactive synthesis problem in two dimensions. First, the construction of a hierarchical game graph introduces abstraction layers, where each layer is again a two-player game graph. Second, every such layer is decomposed into multiple local game graphs, each corresponding to a node in the higher level game graph. While local games have the potential to reduce the state space for controller synthesis, they lead to more complex synthesis problems where strategies computed for one local game can impose additional requirements on lower-level local games. Our second contribution is a procedure to construct a dynamic controller for local game graphs over hierarchies. The controller computes assume-admissible winning strategies that satisfy local specifications in the presence of environment assumptions, and dynamically updates specifications and strategies due to interactions between games at different abstraction layers at each step of the play. We show that our synthesis procedure is sound: the controller constructs a play that satisfies all local specifications. We illustrate our results through an example controlling an autonomous robot in a building with known floor plan and provide simulation results using an implementation of our algorithm on top of LTLMoP.     

PLUM : Parallel Load Balancing for Adaptive Unstructured Meshes

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method calledPLUMto dynamically balance the processor workloads with a global view. This paper describes the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate thatPLUMis an effective dynamic load balancing strategy which remains viable on a large number of processors.