ASCRClu: an adaptive subspace combination and reduction algorithm for clustering of high-dimensional data

Pattern Analysis and Applications - The curse of dimensionality in high-dimensional data is one of the major challenges in data clustering. Recently, a considerable amount of literature has been...     

Topological surrogates for computationally efficient seismic robustness optimization of water pipe networks

The criticality of seismic robustness of the water pipe networks cannot be overstated. Current methodologies for optimizing seismic robustness of city‐scale water pipe networks are scarce. A very few studies that can be found are also prone to long optimization runtimes due to the requirement of repeated hydraulic analysis. Hence, there is a critical need for the identification of computationally efficient surrogate optimization methods for maximizing seismic robustness of water pipe networks. To address this need, this research was conducted to identify, for the first time, computationally efficient topological surrogates for hydraulic simulation‐based optimization. The computational efficiency of surrogate optimization was measured in terms of solution quality (i.e., post‐earthquake serviceability) and computational runtime. Ten different topological connectivity metrics were evaluated out of which five were considered computationally infeasible due to their prohibitive optimization runtime. Five remaining metrics were then used to formulate five surrogate objective functions for seismic robustness of water pipe networks. Each of these functions was optimized using a simulated annealing‐based algorithm. Application of the proposed approach to city‐level benchmark networks helped to identify two metrics out of ten that offered a substantial reduction in optimization runtime with a minimal loss in solution quality. These findings will be highly valuable to water distribution network managers for identifying economical rehabilitation policies for enhancing the seismic robustness at a city‐scale within a reasonable amount of time.     

Estimating the distribution of external causes in hospital data from injury diagnosis

Hospital discharge datasets are a key source for estimating the incidence of non-fatal injuries. While hospital records usually document injury diagnosis (e.g. traumatic brain injury, femur fracture, etc.) accurately, they often contain poor quality information on external causes (e.g. road traffic crashes, falls, fires, etc.), if such data is recorded at all. However, estimating incidence by external causes is essential for designing effective prevention strategies. Thus, we developed a method for estimating the number of hospital admissions due to each external cause based on injury diagnosis. We start with a prior probability distribution of external causes for each case (based on victim age and sex) and use Bayesian inference to update the probabilities based on the victim's injury diagnoses. We validate the method on a trial dataset in which both external causes and injury diagnoses are known and demonstrate application to two problems: redistribution of cases classified to ill-defined external causes in one hospital data system; and, estimation of external causes in another hospital data system that only records nature of injuries. In comparison with age–sex proportional distribution (the method usually employed), we found the Bayesian method to be a significant improvement for generating estimates of incidence for many external causes (e.g. fires, drownings, poisonings). But the method, performed poorly in distinguishing between falls and road traffic injuries, both of which are characterized by similar injury codes in our datasets. While such stop gap methods can help derive additional information, hospitals need to incorporate accurate external cause coding in routine record keeping.     

Electrocatalytic activities of gold-5-amino-2-mercaptobenzimidazole-M self-assembled monolayer complexes (M: Ag, Cu) for hydroquinone oxidation investigated by CV and EIS

Electrocatalytic activity of a new catalyst toward the oxidation reaction of hydroquinone as a model compound is described. The catalyst was formed by immobilizing metal cations on the topside of a gold-5-amino-2-mercaptobenzimidazole, self-assembled monolayer (Au-5A2MBI-Mⁿ⁺ SAM, Mⁿ⁺: Cu²⁺, Ag⁺) electrode. Preparation steps and the electrocatalytic activity of the catalyst were studied by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The EIS data were approximated by appropriate electronic equivalent circuit models from which kinetic parameters, such as charge transfer resistance, double layer capacitance, and apparent rate constant (k_app), were estimated. Excellent activity was observed for Au-5A2MBI-Ag⁺ SAM with the following order: Au-5A2MBI-Ag⁺ > Au-5A2MBI-Cu²⁺ > Au-5A2MBI, after testing many modified electrodes. The increased activity originates from a modification of the Au-5A2MBI structure by mediating the effect of Ag⁺. This behavior was understood from significant increases in the k_app without significant changes in the double layer capacitance.     

CFD modeling of the effect of absorbent size on absorption performance of a packed bed column

This paper reports a study on the ability of the computational fluid dynamics (CFD) modeling for analyzing the fluid flow hydrodynamics and absorption in a packed bed column. The water absorption by silica gel absorbents in an experimental packed bed was investigated, and the absorption performance of two different sizes of absorbent was studied. A series of experiments were carried out for five setups which are different in the weight ratio of the employed big to small absorbents. The CFD modeling was carried out for all five experimental setups. The predicted results show that by more replacing of the big absorbents with the small ones the water absorption increased. On the other hand, a greater pressure drop was observed as more small absorbents were used. The predicted absorption rates were compared with the measured values and on average a consistency within 11.6% was observed.     

Resolution of near-infrared spectral data from distillation of binary mixtures and calculation of band boundaries of feasible solutions for species profiles

In this work, mean centering, ordinary and incomplete rank annihilation based methods were applied to estimate concentration profiles (g/mL) and pure spectra of components from an evolutionary near infrared spectral data for successive condensates from distillation process of binary mixtures. Constraints such as non-negativity, selectivity of some spectral regions and density of condensates were applied during the resolution of some series of data. Fixed size moving window evolving factor analysis (FSMWEFA) and orthogonal projection analysis (OPA) were the applied chemometrics methods for assigning the selective regions. No pure spectrum from any of components or calibration samples was necessary for performing the analysis. Three binary mixtures containing toluene:n-hexane, toluene:cyclohexene and toluene:ethanol were investigated using the proposed method. Band boundaries of feasible solutions for pure absorption spectra and species concentration profiles for the mixture of components were successfully estimated in presence of high spectral overlap. In the first case the solution was unique, but in the second and third distillations a number of acceptable solutions were obtained as band boundaries.     

Modeling Groundwater Flow and Seawater Intrusion in the Coastal Aquifer of Wadi Ham,UAE

Groundwater pumping from Kalbha and Fujairah coastal aquifer of the United Arab Emirates (UAE) has increased significantly during the last two decades to meet the agriculture water demands. Due to the lack of natural replenishment from rainfall and the excessive pumping, groundwater levels have declined significantly causing an intrusion of seawater in the coastal aquifer of Wadi Ham. As a result, many pumping wells in the coastal zone have been terminated and a number of farms have been abandoned. In this paper, MODFLOW was used to simulate the groundwater flow and assess the seawater intrusion in the coastal aquifer of Wadi Ham. The model was calibrated against a five-year dataset of historical groundwater levels and validated against another eleven-year dataset. The effects of pumping on groundwater levels and seawater intrusion were investigated. Results showed that reducing the pumping from Khalbha well field will help to reduce the seawater intrusion into the southeastern part of the aquifer. Under the current groundwater pumping rates, the seawater will continue to migrate inland.     

Influence of dietary vitamin E,selenium and age on regional distribution of α-tocopherol in the rat brain

Concentrations of α-tocopherol (α-T) in plasma, cerebrum, cerebellum, midbrain and brain stem and activity of selenium (Se)-dependent glutathione peroxidase (GSH-Px) in plasma were measured in 1- and 15-month-old male F344 rats fed diets containing vitamin E (E, IU/kg) and Se (ppm) in the following combinations: 30 E, 0.1 Se (control diet, minimum requirements); 200E, 0.2 Se; 0.0 E, 0.2 Se; 200 E, 0.0 Se; 0.0 E, 0.0 Se for 8 or 20 weeks. α-T and GSH-Px levels in plasma were reflective of dietary treatment in young rats in which an interaction of the two nutrients was noted. A longer period of dietary vitamin E deficiency was necessary to deplete plasma α-T and depress GSP-Px activity significantly in the old rats. Among the brain regions of all ages, cerebrum and midbrain had the highest concentrations of α-T while cerebellum showed the lowest. However, cerebellum of young rats and cerebellum and brain stem of old rats had a greater α-T accumulation with doubly supplemented diets, whereas only cerebellum of young and old rats showed a marked increased of α-T with vitamin E supplementation. In old rats, vitamin E deficiency resulted in greater depletion of α-T in cerebellum and brain stem than cerebrum and midbrain regions. Se deficiency in brain stem of young and old rats significantly decreased α-T accumulation by vitamin E supplementation. Se supplementation marginally alleviates vitamin E depletion in brain. Cerebellum and brain stem of old rats fed the minimum requirements of vitamin E and Se for 20 weeks showed a significant decline in α-T. Therefore, cerebellum and brain stem appear, to have a higher turnover of α-T than cerebrum and midbrain, and older rats may require a higher level, of vitamin E in the diet to maintain steady state levels of α-T in these regions.     

The Integrated Approach of Simulation and Optimization in Determining the Optimum Dimensions of Canal for Seepage Control

Water Resources Management - The appropriate management of water resources in the world is a policy that can be used in the line of optimum water consumption. One of these management instructions...     

Nested Augmentation of Rainfall Monitoring Network: Proposing a Hybrid Implementation of Block Kriging and Entropy Theory

One of the most influential environmental variables is rainfall which has significant effect on water resources management, agricultural development, hydrology, and climate change studies. Due to high spatiotemporal variability of rainfall, its monitoring network design can be considered as a useful tool to improve the efficiency of recorded rain gauge stations within the study area. In this study, a new methodology of augmentation of rain gauge network is developed using coupled Block Kriging (BK) and entropy theory methods. In the proposed method, a nested approach of a two-stage positioning of rain gauge stations has been demonstrated. In the first stage, large-scale or fast positioning was done in which the optimal number of candidate blocks was identified. Then, local scale or fine-tuned positioning was done in the second stage. In this stage, to develop the network, accurate locations of rain gauge stations in each block are determined. Besides the main point of this paper, the effect of two kriging estimators, BK and Ordinary Kriging (OK), on the developed network has been investigated and compared. The study area is the Namak Lake watershed with various climates and altitudes. To assess the performance of the optimal rainfall network, three diagnostics were utilized; spatial distribution of annual precipitation, Estimation Error Variance (EEV) maps and histograms. Based on the results, 30 (more than 30% percent of the current stations) rain gauge stations have been proposed scattered over the watershed. Evaluation of the results has shown that the augmented rain gauge network proposed by the BK method outperformed dramatically that of the OK method. EEV maps and also statistical analysis of EEV values confirms the EEV value reduction of almost 25% in augmented network, as well.