Donor-acceptor-donor type conjugated polymers for electrochromic applications: benzimidazole as the acceptor unit

Donor-acceptor-donor (DAD) type benzimidazole (BIm) and 3,4 ethylenedioxythiophene (EDOT) bearing monomers were synthesized and electrochemically polymerized. Pendant group at 2-C position of the imidazole ring was functionalized with phenyl (P1), EDOT (P2) and ferrocene (P3) in order to observe substituent effect on electrochemical and electrochromic properties of corresponding polymers. Spectroelectrochemical results showed that different pendant groups resulted in polymers with slightly different optical band gaps (1.75, 1.69 and 1.77 eV respectively) and different number of achievable colored states. Optoelectronic performance and comparison of results with other well known π-accepting benzazole bearing DAD type polymers were reported in detail.     

Signal‐to‐noise ratios for measuring saliency of features extracted by eigenvector methods from ophthalmic arterial Doppler signals

Abstract: Features are used to represent patterns with minimal loss of important information. The feature vector, which is composed of the set of all features used to describe a pattern, is a reduced‐dimensional representation of that pattern. Medical diagnostic accuracies can be improved when the pattern is simplified through representation by important features. By identifying a set of salient features, the noise in a classification model can be reduced, resulting in more accurate classification. In this study, a signal‐to‐noise ratio saliency measure was employed to determine the saliency of input features of recurrent neural networks (RNNs) used in classification of ophthalmic arterial Doppler signals. Eigenvector methods were used to extract features representing the ophthalmic arterial Doppler signals. The RNNs used in the ophthalmic arterial Doppler signal classification were trained for the signal‐to‐noise ratio screening method. The application results of the signal‐to‐noise ratio screening method to the ophthalmic arterial Doppler signals demonstrated that classification accuracies of RNNs with salient input features are higher than those of RNNs with salient and non‐salient input features.     

A GIS-Based Optimization Framework for Competitive Multi-Facility Location-Routing Problem

In a dynamic market setting, firms need to quickly respond to shifting demographics and economic conditions. In this paper, we investigate the problem of determining the optimum set of locations for a firm, which operates a chain of facilities under competition. We consider the objective of maximizing profit, defined as gross profit margin minus logistics costs. We propose a location-routing model where revenue is realized according to probabilistic patronization of customers and routing costs are incurred due to vehicles serving the open facilities from a central depot. We propose a hybrid heuristic optimization methodology for solving this model. The optimal locations are searched for by a Genetic Algorithm while an integrated Tabu Search algorithm is employed for solving the underlying vehicle routing problem. The solution approach is tested on a real dataset of a supermarket chain. The results show that the location decisions made by the proposed methodology lead to increased market share and profit margin, while keeping logistics costs virtually unchanged. Finally, we present a GIS-based framework that can be used to store, analyze and visualize all data as well as model solutions in geographic format.     

Equilibrium studies for the sorption of zinc and copper from aqueous solutions using sugar beet pulp and fly ash

In the present work, the abilities of native sugar beet pulp (SBP) and fly ash (FA) to remove copper (Cu(2+)) and zinc (Zn(2+)) ions from aqueous solutions were compared. The SBP and FA, an industrial by-product and solid waste of sugar industry, were used for the removal of copper and zinc from aqueous water. Batch adsorption experiments were performed in order to evaluate the removal efficiency of SBP and lignite-based FA. The effect of various operating variables, i.e. initial pH, adsorbent dose, initial metal ion concentration, and time on adsorption of copper and zinc onto the SBP and FA, has been studied. The sorption process was relatively fast and equilibrium was reached after about 60 min of contact. As much as 60-97% removal of copper and zinc for SBP and FA are possible in about 60 min, respectively, under the batch test conditions. Uptake showed a pH-dependent profile. The overall uptake for the SBP is at a maximum at pH 5.5 and gives up to 30.9 mg g(-1) for copper and at pH 6.0 and gives 35.6 mg g(-1) for zinc for SBP, which seems to be removed exclusively by ion exchange and physical sorption. Maximum adsorption of copper and zinc occurred 7.0 and 7.84 mg g(-1) at a pH value of 5.0 and 4.0 for FA, respectively. A dose of 8 g l(-1) of SBP and 8 g l(-1) FA were sufficient for the optimum removal of both the metal ions. The sorption data were represented by the Freundlich for SBP and the Langmuir and Freundlich for FA. The sorption data were better represented by the Langmuir isotherm than by the Freundlich one for FA in the adsorption of zinc ion, suggesting that the monolayer sorption, mainly due to ion exchange. The presence of low ionic strength or low concentration of Na and Cl ions does not have a significant effect on the adsorption of these metals by SBP and FA. The SBP and FA are shown to be effective metal adsorbents for these two metals.     

Performance evaluation of a submerged membrane bioreactor for the treatment of brackish oil and natural gas field produced water

Produced water, which is co-produced during oil and gas manufacturing, represents one of the largest sources of oily wastewaters. Therefore, treatment of this produced water may improve the economic viability and lead to a new source of water for beneficial use. In this study a submerged hollow fiber membrane bioreactor (MBR) has been studied experimentally for the treatment of brackish oil and natural gas field produced water. This type of wastewater is also characterized with relatively moderate to high amount of salt, oil and total petroleum hydrocarbons (TPH). However, the bacteria which are growing in conventional activated sludge and MBR cannot survive at these strict conditions, therefore acclimation of the bacteria is of vital importance. The performance of the biological system, membrane permeability, the rate and extent of TPH biodegradability have been investigated under different sludge age and F/M ratios. The results obtained by gas chromatography analyses showed that the MBR system could be very effective in the removal of TPH from produced water and a significant improvement in the effluent quality was achieved.     

Estimating Construction Material Indices with ARIMA and Optimized NARNETs

Construction Industry operates relying on various key economic indicators. One of these indicators is material prices. On the other hand, cost is a key concern in all operations of the construction industry. In the uncertain conditions, reliable cost forecasts become an important source of information. Material cost is one of the key components of the overall cost of construction. In addition, cost overrun is a common problem in the construction industry, where nine out of ten construction projects face cost overrun. In order to carry out a successful cost management strategy and prevent cost overruns, it is very important to find reliable methods for the estimation of construction material prices. Material prices have a time dependent nature. In order to increase the foreseeability of the costs of construction materials, this study focuses on estimation of construction material indices through time series analysis. Two different types of analysis are implemented for estimation of the future values of construction material indices. The first method implemented was Autoregressive Integrated Moving Average (ARIMA), which is known to be successful in estimation of time series having a linear nature. The second method implemented was Non-Linear Autoregressive Neural Network (NARNET) which is known to be successful in modeling and estimating of series with non-linear components. The results have shown that depending on the nature of the series, both these methods can successfully and accurately estimate the future values of the indices. In addition, we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.     

Detection of seizures from small samples using nonlinear dynamicsystem theory

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D₂) of EEG time series data. In this paper, D₂ of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D₂ computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D₂ computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies     

Telepresence feedback and input systems for a twin armed mobilerobot

Complex tasks in unstructured/hazardous environments often require teleoperation. The telepresence robot featured here has “user friendly” limb linked output and feedback systems. The mechanism design and sensory feedback of visual, audio and multi-functional tactile (pressure, texture/slip and thermal parameters) are described     

IPM: A computer Interactive Project Management teaching tool

Project management deals with all phases of a project, from the initiation of the planning procedure to the physical completion of the entire effort. The process of teaching the quantitative approaches to project management (i.e. Critical-Path Method and Program Evaluation and Review Technique) is a fairly straightforward task that has been performed for many years. However, teaching the principles of project management is a different task altogether. The project management process involves a sequence of planning, decision making, follow-up activities and reevaluation followed by a repeat of the sequence. That is, in order to truly examine and teach the process of project management (i.e. not just the tools), it is necessary to view the activities in a dynamic projectlike environment. With this idea in mind, the Interactive Project Management game (IPM) was developed. IPM was created with the intent of teaching project management principles in a simulated project environment using the computer. This paper describes IPM, its characteristics and its capabilities, and includes an IPM gaming session.     

Repeated hydrolysis process is effective for enrichment of omega 3 polyunsaturated fatty acids in salmon oil by Candida rugosa lipase

Enrichment of omega 3 polyunsaturated fatty acids (PUFA) in the glyceride fraction of salmon oil was performed by Candida rugosa lipase (CRL)-catalysed hydrolysis. Total omega 3 PUFA content in the product was 38.71% (mol.%), more than double of the initial level. The hydrolysis reaction was scaled up to 1 l in a stirred tank reactor without any decrease in the selectivity of the reaction. Moreover, non-steroselectivity and acyl chain specificity of CRL-catalysed hydrolysis, as well as CRL’s recognition of the whole triacylglycerol molecule, were proved. The product was purified by short path distillation, which was also shown to contribute to the recovery of omega 3 PUFA in residue. After the removal of free fatty acids, the final product was subjected to a second round of hydrolysis to concentrate omega 3 PUFA further to 50.58%. Recoveries of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) decreased slightly after the second round of hydrolysis, while oleic acid (OA) content was not affected.