Development of a low-cost portable colorimeter for the estimation of fluoride in drinking water

People in many countries are affected by fluorosis owing to the high levels of fluoride in drinking water. An inexpensive method for estimating the concentration of the fluoride ion in drinking water would be helpful in identifying safe sources of water and also in monitoring the performance of defluoridation techniques. For this purpose, a simple, inexpensive, and portable colorimeter has been developed in the present work. It is used in conjunction with the SPADNS method, which shows a color change in the visible region on addition of water containing fluoride to a reagent solution. Groundwater samples were collected from different parts of the state of Karnataka, India and analysed for fluoride. The results obtained using the colorimeter and the double beam spectrophotometer agreed fairly well. The costs of the colorimeter and of the chemicals required per test were about Rs. 250 (US$ 5) and Rs. 2.5 (US$ 0.05), respectively. In addition, the cost of the chemicals required for constructing the calibration curve was about Rs. 15 (US$ 0.3). (C) 2010 Elsevier B.V. All rights reserved.

Synthesis of Cost-Optimal Shell-and-Tube Heat Exchangers

Synthesis of cost-optimal shell-and-tube heat exchangers is a difficult task since it involves a large number of parameters. An attempt is made in this article to simplify the process of choosing the parameter values that will minimize the cost of any heat exchanger satisfying a given heat duty and a particular set of constraints. The simplification is based on decoupling of the geometric and the thermal aspects of the problem. The concept of curves for cost-optimal design is introduced and is shown to simplify the synthesis process for shell-and-tube heat exchangers.

Capacity of Gaussian Channels With Energy Harvesting and Processing Cost

Energy harvesting sensor nodes are gaining popularity due to their ability to improve the network life time and are becoming a preferred choice supporting green communication. In this paper, we focus on communicating reliably over an additive white Gaussian noise channel using such an energy harvesting sensor node. An important part of this paper involves appropriate modeling of energy harvesting, as done via various practical architectures. Our main result is the characterization of the Shannon capacity of the communication system. The key technical challenge involves dealing with the dynamic (and stochastic) nature of the (quadratic) cost of the input to the channel. As a corollary, we find close connections between the capacity achieving energy management policies and the queueing theoretic throughput optimal policies.

Low-Cost Cloud-Based Design of Smart Rural Energy Device in Microgrid: Perspective India An Energy-On-Demand Service for Rural India

In this paper we present a combination of technologies to provide an Energy-on-Demand (EoD) service to enable low cost innovation suitable for microgrid networks. The system is designed around the low cost and simple Rural Energy Device (RED) Box which in combination with Short Message Service (SMS) communication methodology serves as an elementary proxy for Smart meters which are typically used in urban settings. Further, customer behavior and familiarity in using such devices based on mobile experience has been incorporated into the design philosophy. Customers are incentivized to interact with the system thus providing valuable behavioral and usage data to the Utility Service Provider (USP). Data that is collected over time can be used by the USP for analytics envisioned by using remote computing services known as cloud computing service. Cloud computing allows for a sharing of computational resources at the virtual level across several networks. The customer-system interaction is facilitated by a third party Telecom Service provider (TSP). The approximate cost of the RED Box is envisaged to be under USD 10 on production scale.

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a `footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by similar to 50% in generator potentials, to similar to 3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

Groups constrain the use of risky habitat by individuals: a new cost to sociality?

Predation risk can strongly constrain how individuals use time and space. Grouping is known to reduce an individual's time investment in costly antipredator behaviours. Whether grouping might similarly provide a spatial release from antipredator behaviour and allow individuals to use risky habitat more and, thus, improve their access to resources is poorly known. We used mosquito larvae, Aedes aegypti, to test the hypothesis that grouping facilitates the use of high-risk habitat. We provided two habitats, one darker, low-risk and one lighter, high-risk, and measured the relative time spent in the latter by solitary larvae versus larvae in small groups. We tested larvae reared under different resource levels, and thus presumed to vary in body condition, because condition is known to influence risk taking. We also varied the degree of contrast in habitat structure. We predicted that individuals in groups should use high-risk habitat more than solitary individuals allowing for influences of body condition and contrast in habitat structure. Grouping strongly influenced the time spent in the high-risk habitat, but, contrary to our expectation, individuals in groups spent less time in the high-risk habitat than solitary individuals. Furthermore, solitary individuals considerably increased the proportion of time spent in the high-risk habitat over time, whereas individuals in groups did not. Both solitary individuals and those in groups showed a small increase over time in their use of riskier locations within each habitat. The differences between solitary individuals and those in groups held across all resource and contrast conditions. Grouping may, thus, carry a poorly understood cost of constraining habitat use. This cost may arise because movement traits important for maintaining group cohesion (a result of strong selection on grouping) can act to exaggerate an individual preference for low-risk habitat. Further research is needed to examine the interplay between grouping, individual movement and habitat use traits in environments heterogeneous in risk and resources. (C) 2015 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Inertial mass of a vortex in cuprate superconductors

We present here a calculation of the inertial mass of a moving vortex in cuprate superconductors. This is a poorly known basic quantity of obvious interest in vortex dynamics. The motion of a vortex causes a dipolar density distortion and an associated electric field which is screened. The energy cost of the density distortion as well as the related screened electric field contributes to the vortex mass, which is small because of efficient screening. As a preliminary, we present a discussion and calculation of the vortex mass using a microscopically derivable phase-only action functional for the far region which shows that the contribution from the far region is negligible and that most of it arises from the (small) core region of the vortex. A calculation based on a phenomenological Ginzburg-Landau functional is performed in the core region. Unfortunately such a calculation is unreliable; the reasons for it are discussed. A credible calculation of the vortex mass thus requires a fully microscopic non-coarse-grained theory. This is developed, and results are presented for an s-wave BCS-like gap, with parameters appropriate to the cuprates. The mass, about 0.5m(e) per layer, for a magnetic field along the c axis arises from deformation of quasiparticle states bound in the core and screening effects mentioned above. We discuss earlier results, possible extensions to d-wave symmetry, and observability of effects dependent on the inertial mass. [S0163-1829(97)05534-3].

Quantum behaved Particle Swarm Optimization (QPSO) for multi-objective design optimization of composite structures

We present a new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi-objective optimization algorithm developed on the basis of the Quantum behaved Particle Swarm Optimization (QPSO) paradigm. QPSO is a co-variant of the popular Particle Swarm Optimization (PSO) and has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; Failure Mechanism based Failure criteria, Maximum stress failure criteria and the Tsai-Wu Failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences as well as fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Also, the performance of QPSO is compared with the conventional PSO.