Synergetic effects of organic and inorganic additives on improvement in hydrophilicity and performance of PVDF antifouling ultrafiltration membrane for removal of natural organic material from water

Surrounding vegetation, animal, human and microbiological decomposition are the strong source of humic acid (HA) falling into the surface water bodies through rain runoff in the monsoon. HA contains various functional groups, such as carboxylic, phenolic, hydroxyl, and quinine, which are the major foulant. Contact of HA may have an adversarial health issue to human beings namely goiter, black foot, and cancer disease. The maximum permissible limit of HA in drinking water should be less than 2 ppm as per the Environmental Protection Agency (EPA). The membrane technology has prevailed a prominent place worldwide in chemical, water and wastewater treatment technologies. The proposed work is focused on the blending of organic-water soluble polymer polyethylene glycol 6000 as a pore-forming agent and inorganic salt lithium bromide (LiBr) as membrane morphology modifier with polyvinylidene fluoride host polymer in the N,N-Dimethylacetamide solvent. All fabricated membranes were characterized for functional groups and morphology. The total number of pores per unit surface area of membrane for membranes M-LiBr-0, M-LiBr-1, M-LiBr-2, and M-LiBr-3 are 2 × 10¹³, 2.3 × 10¹⁴, 2.7 × 10¹⁴ and 2.82 × 10¹⁴, respectively. The static water contact angle was decreased from 68.2° to 50.6° with an increase in the content of LiBr from 0 to 3 wt%. The order of pure water flux and hydraulic permeability of the membrane was M-LiBr-0 < M-LiBr-1 < M-LiBr-2 < M-LiBr-3. The HA rejection of the membrane was also increased from 90.13% to 96.24% with LiBr content due to a decrease in pore size of the membrane with the addition of LiBr content.     

Insights into the Genetic Variations of Human Cytochrome P450 2C9: Structural Analysis,Characterization and Comparison

Cytochromes P450 (CYP) are one of the major xenobiotic metabolizing enzymes with increasing importance in pharmacogenetics. The CYP2C9 enzyme is responsible for the metabolism of a wide range of clinical drugs. More than sixty genetic variations have been identified in CYP2C9 with many demonstrating reduced activity compared to the wild-type (WT) enzyme. The CYP2C9*8 allele is predominantly found in persons of African ancestry and results in altered clearance of several drug substrates of CYP2C9. The X-ray crystal structure of CYP2C9*8, which represents an amino acid variation from arginine to histidine at position 150 (R150H), was solved in complex with losartan. The overall conformation of the CYP2C9*8-losartan complex was similar to the previously solved complex with wild type (WT) protein, but it differs in the occupancy of losartan. One molecule of losartan was bound in the active site and another on the surface in an identical orientation to that observed in the WT complex. However, unlike the WT structure, the losartan in the access channel was not observed in the *8 complex. Furthermore, isothermal titration calorimetry studies illustrated weaker binding of losartan to *8 compared to WT. Interestingly, the CYP2C9*8 interaction with losartan was not as weak as the CYP2C9*3 variant, which showed up to three-fold weaker average dissociation constant compared to the WT. Taken together, the structural and solution characterization yields insights into the similarities and differences of losartan binding to CYP2C9 variants and provides a useful framework for probing the role of amino acid substitution and substrate dependent activity.     

Nitro Derivatives of 1,3,5-Triazepine as Potential High-Energy Materials

Structure optimization and frequency calculation of six nitro derivatives of 1,3,5-triazepine were performed using a MP2(FULL)/6-311G(d,p) method. In order to obtain reliable energy data, single-point energy and subsequently thermodynamic properties of the species considered were calculated at a fairly high level of theory, CCSD(T)/6-311G(d,p). Solid-phase heats of formation and crystal density were determined using an electrostatic potential (ESP) method utilizing wave function analysis-surface analysis suite (WFA-SAS) code. The result shows that all nitro derivatives possess high positive heats of formation that increase with an increase in the number of nitro groups attached to the ring moiety. The crystal density was found to be in the range of 1.67–1.90 g/cm³. Detonation properties of the compounds were estimated using the Kamlet-Jacobs equation. The results showed that detonation velocity (D) and detonation pressure (P) increased with an increase in the number of nitro groups attached at the ring moiety. It was found that all six nitro derivatives of the title compound had better or comparable performance characteristics than the most widely used commercial explosives, such as TNT, research and development explosives (RDX), and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX). The trinitro derivative (1,3,5-trinitro-1,3,5-triazepine, F) yielded detonation pressure (P) and detonation velocity (D) of 45.5 GPa and 9.23 km/s, respectively, at a loading density of 1.90 g/cm³, which are superior to the most powerful available explosive HMX (P = 39.00 GPa and D = 9.11 km/s). The results obtained during the present study show that the title compounds can be used as promising futuristic high-energy-density materials (HEDMs).     

Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules

Optimal use of scarce water resources is the prime objective for water resources development projects in the developing country like India. Optimal releases have been generally expressed as a function of reservoir state variables and hydrologic inputs by a relationship which ultimately allows the policy/water managers to determine the water to be released as a function of available information. Optimal releases were obtained by using optimal control theory with inflow series and revised reservoir characteristics such as elevation area capacity table, zero elevation level as input in this study. Operating rules for reservoir were developed as a function of demand, water level and inflow. Artificial Neural Network (ANN) with back propagation algorithm, Fuzzy Logic and decision tree algorithms such as M5 and REPTree were used for deriving the operating rules using the optimal releases for an irrigation and power supply reservoir, located in northern India. It was found that fuzzy logic model performed well compared to other soft computing techniques such as ANN, M5P and REPTree investigated in this study.     

Statistical Analysis of Long Term Trends of Rainfall During 1901–2002 at Assam,India

Rainfall is a principal element of the hydrological cycle and its variability is important from both the scientific as well as socio-economic point of view. This study presents an analysis based on the precipitation variation in Assam, India over 102 years from 1901 to 2002. Precipitation data from 21 stations have been collected. These data have been analyzed for both annual and seasonal variation. For trend analysis, Mann-Kendell and Sen’s slope estimator test were used. To compare seasonal variations, three seasons of winter, summer and monsoon have been considered. Mean annual precipitation varied from 2,074 mm (at Tinsukia) to 3,538 mm (at North Chahar Hills). The most probable year of change was 1959 in annual precipitation. Time series of the Standardized Precipitation Index (SPI) depict that near normal occurs in about 68 years out 102 years, and in 2.48 years out of 102 years there was an extreme wet. All these findings can help provide rational regulatory and policy in relation to water resources to maintain the health of the various ecosystems that make up Assam, India.     

Linked Simulation-Optimization based Dedicated Monitoring Network Design for Unknown Pollutant Source Identification using Dynamic Time Warping Distance

Implementation of monitoring strategy for increasing the efficiency of groundwater pollutant source characterization is often necessary, especially when only inadequate and arbitrary concentration measurement data are initially available. Two main parameters that need to be estimated for efficient and accurate characterization of groundwater pollution sources are: location of the source and the time when the source became active. Complexities involved with the explicit estimation of the time of start and source activity have not been addressed so far in previous studies. The main complexity arises due to the fact that the spatial location and time of activity are inter-related. Therefore, specifying one and solving for the other simplifies the source characterization problem. Hence, in this study, both the source location and time of initiation are treated as unknowns. The developed methodology uses dynamic time warping distance in the linked simulation-optimization model to address some complex issues in designing a monitoring network to efficiently estimate source characteristics including the time of first activity of unknown groundwater source. Performance of the developed methodology is evaluated on illustrative contaminated aquifer. These evaluation results demonstrate the potential use of the developed methodology.     

Addressing spatiotemporal and computational heterogeneity in structured adaptive mesh refinement

Structured adaptive mesh refinement (SAMR) techniques can provide accurate and cost- effective solutions to realistic scientific and engineering simulations modeling complex physical phenomena. However, the adaptive nature and inherent space–time heterogeneity of SAMR applications result in significant runtime management challenges. Moreover, certain SAMR applications involving reactive flows exhibit pointwise varying workloads and cannot be addressed by traditional parallelization approaches, which assume homogeneous loads. This paper presents hierarchical partitioning, bin-packing based load balancing, and Dispatch structured partitioning strategies to manage the spatiotemporal and computational heterogeneity in SAMR applications. Experimental evaluation of these schemes using 3-D Richtmyer–Meshkov compressible turbulence and 2-D reactive-diffusion kernels demonstrates the improvement in overall performance.     

Socket Buffer Auto-Sizing for High-Performance Data Transfers

It is often claimed that TCP is not a suitable transport protocol for data intensive Grid applications in high-performance networks. We argue that this is not necessarily the case. Without changing the TCP protocol, congestion control, or implementation, we show that an appropriately tuned TCP bulk transfer can saturate the available bandwidth of a network path. The proposed technique, called SOBAS, is based on automatic socket buffer sizing at the application layer. In non-congested paths, SOBAS limits the socket buffer size based on direct measurements of the received throughput and of the corresponding round-trip time. The key idea is that the send window should be limited, after the transfer has saturated the available bandwidth in the path, so that the transfer does not cause buffer overflows (self-induced losses). A difference with other socket buffer sizing schemes is that SOBAS does not require prior knowledge of the path characteristics, and it can be performed while the transfer is in progress. Experimental results in several high bandwidth-delay product paths show that SOBAS provides consistently a significant throughput increase (20% to 80%) compared to TCP transfers that use the maximum possible socket buffer size. We expect that SOBAS will be mostly useful for applications such as GridFTP in non-congested wide-area networks.     

A Probabilistic and Decision Attitude Aggregation Operator for Intuitionistic Fuzzy Environment

In this paper, a new operator for aggregation of uncertain information under intuitionistic fuzzy environment is proposed. A novel approach is proposed for the selection of best alternative action in the face of the imprecise probabilities and the complex attitudinal character of the decision makers (DMs). This approach is distinguished with its capacity to accommodate the linguistic specification of probabilities as provided by human experts directly without the need to determine the fuzzy membership grades. The focus is to compute the net payoff for each alternative in the face of uncertain states of nature and DM's attitude. The proposed operator and the approach are illustrated through two real case studies.     

A technique for generating natural colour images from false colour composite images

Colour is widely used in remote sensing work. In many instances, the use of colour conveys additional information both visually and scientifically. Remote sensing satellites view the earth in different spectral bands, viz. near infrared (NIR), red, green, and blue bands, in a conventional multispectral imaging system. In the absence of a blue channel, colour images can be generated using near infrared, red, and green bands in what is known as a false colour composite (FCC) and does not look natural, like the image we see with the naked eye. For a trained interpreter, this does not pose any problems. However, when the intended use is a fly‐through of a draped terrain, visual interpretation, or a display, meant for the non‐remote sensing professional, this becomes a handicap. To overcome this, there is a requirement to generate natural colour composites (NCC) from the given false colour composite, which demands the simulation of a blue band to be combined with green and red bands. This paper describes a unique method of generating a blue band to form natural colour images from a given false colour image set. We use a spectral transformation method to establish a relationship between the false colour and true colour image pairs provided by a sensor with all the four bands, which has a broader spectral coverage. A transformation function is fitted by selecting radiometric control points along the line of geometric registration to find a set of coefficients to be used for simulating a blue band. This blue band, along with the green and red bands, provides a near true colour or ‘natural colour’ on the display. In this paper, we present a set of adjustable radiometric transformation coefficients to accommodate variation in spatial and dynamic range offered by sensors to generate natural colour. These coefficients seem to work on a large number of images of different seasons, provided similar spectral bands and terrain are used. The proposed ‘natural colour generator’ can be used in changing false colour images to natural colour images with the aim of ‘what you get is what you would have seen’.