Effect of carbon dioxide and bicarbonate as inorganic carbon sources on growth and adaptation of autohydrogenotrophic denitrifying bacteria

Acclimation of autohydrogenotrophic denitrifying bacteria using inorganic carbon source (CO(2) and bicarbonate) and hydrogen gas as electron donor was performed in this study. In this regard, activated sludge was used as the seed source and sequencing batch reactor (SBR) technique was applied for accomplishing the acclimatization. Three distinct strategies in feeding of carbon sources were applied: (I) continuous sparging of CO(2), (II) bicarbonate plus continuous sparging of CO(2), and (III) only bicarbonate. The pH-reducing nature of CO(2) showed an unfavorable impact on denitrification rate; however bicarbonate resulted in a buffered environment in the mixed liquor and provided a suitable mean to maintain the pH in the desirable range of 7-8.2. As a result, bicarbonate as the only carbon source showed a faster adaptation, while carbon dioxide as the only carbon source as well as a complementary carbon source added to bicarbonate resulted in longer acclimation period. Adapted hydrogenotrophic denitrifying bacteria, using bicarbonate and hydrogen gas in the aforementioned pH range, caused denitrification at a rate of 13.33 mg NO(3)(-)-N/g MLVSS/h for degrading 20 and 30 mg NO(3)(-)-N/L and 9.09 mg NO(3)(-)-N/g MLVSS/h for degrading 50mg NO(3)(-)-N/L.     

Effect of spatial variation of thermal conductivity on non-fourier heat conduction in a finite slab

The non-Fourier heat conduction problem in a finite slab is studied analytically. Dependence of thermal conductivity on space has been considered. The Laplace transform method is used to remove the time-dependent terms in the governing equation and the boundary conditions. The hyperbolic heat conduction (HHC) equation has been solved by employing trial solution method and collocation optimization criterion. Results show that the space-dependent thermal conductivity strongly affects the temperature distribution. A temperature peak on the insulated wall of the slab has been observed due to linear variation of thermal conductivity. It has been shown that the magnitude of the temperature peak increases with increasing the dimensionless relaxation time. To validate the approach, the results have been compared with the analytical solution obtained for a special case which shows a good agreement.     

The effect of Al2O3 nano additions on failure of GFRP plate with two parallel pin loaded holes

Journal of Mechanical Science and Technology - The aim of this study is to scrutinize the effect of nano-additions on failure modes and loads of glass-epoxy laminate subjected two parallel...     

Real-time monitoring of color variations of apple slices and effects of pre-treatment and drying air temperature

An attempt was made to quantify the contribution of chemical pre-treatment on the color changes of apple slices during hot air drying. The monitored color attributes of apple slices were computed real time at drying air temperatures of 50, 60, and 70 °C. The apple slices dried in a computer vision system (CVS) assisted-hot air dryer both with and without pre-treatment. The quantities of measured color parameters for pre-treated (P.T.) samples were subtracted from the values obtained for untreated (U.T.) samples at the same water content. For this purpose, an artificial neural network was developed and used satisfactorily for mapping out the color parameters of P.T. samples at calculated moisture ratio for U.T. sample to compute the physio-chemically significant difference. From the results, it can be derived that a CVS seems to be a promising tool when it comes to detecting and monitoring the effects of various pre-treatments on being-processed foodstuffs .     

Compact Navigation and Distance Oracles for Graphs with Small Treewidth

Given an unlabeled, unweighted, and undirected graph with n vertices and small (but not necessarily constant) treewidth k, we consider the problem of preprocessing the graph to build space-efficient encodings (oracles) to perform various queries efficiently. We assume the word RAM model where the size of a word is Ω(logn) bits. The first oracle, we present, is the navigation oracle which facilitates primitive navigation operations of adjacency, neighborhood, and degree queries. By way of an enumeration argument, which is of interest in its own right, we show the space requirement of the oracle is optimal to within lower order terms for all graphs with n vertices and treewidth k. The oracle supports the mentioned queries all in constant worst-case time. The second oracle, we present, is an exact distance oracle which facilitates distance queries between any pair of vertices (i.e., an all-pairs shortest-path oracle). The space requirement of the oracle is also optimal to within lower order terms. Moreover, the distance queries perform in O(k ³log³ k) time. Particularly, for the class of graphs of popular interest, graphs of bounded treewidth (where k is constant), the distances are reported in constant worst-case time.     

Speaker Identification in a Shouted Talking Environment Based on Novel Third-Order Circular Suprasegmental Hidden Markov Models

It is well known that speaker identification yields very high performance in a neutral talking environment; on the other hand, the performance has been sharply declined in a shouted talking environment. This work aims at proposing, implementing, and evaluating novel third-order circular suprasegmental hidden Markov models (CSPHMM3s) to improve the low performance of text-independent speaker identification in a shouted talking environment. CSPHMM3s possess combined characteristics of: Circular Hidden Markov models, third-order hidden Markov models (HMM3s), and suprasegmental hidden Markov models (SPHMMs). Our results show that CSPHMM3s are superior to each of: first-order left-to-right suprasegmental hidden Markov models (LTRSPHMM1s), second-order left-to-right suprasegmental hidden Markov models (LTRSPHMM2s), third-order left-to-right suprasegmental hidden Markov models (LTRSPHMM3s), first-order circular suprasegmental hidden Markov models (CSPHMM1s), and second-order circular suprasegmental hidden Markov models (CSPHMM2s) in a shouted talking environment. Using our collected speech database, average speaker identification performance in a shouted talking environment based on LTRSPHMM1s, LTRSPHMM2s, LTRSPHMM3s, CSPHMM1s, CSPHMM2s, and CSPHMM3s is 74.6, 78.4, 81.7, 78.7, 83.4, and 85.8 %, respectively. Speaker identification performance that has been achieved based on CSPHMM3s is close to that attained based on subjective assessment by human listeners.     

Numerical results achieved with an inverse computational method for determining the constitutive parameters using the hot torsion test results

It was demonstrated in a previous paper that to obtain a unique set of parameters for a constitutive relationship from the hot torsion test, two separate objective or error functions must be considered. They are based on the load-displacement and load-displacement rate data respectively. The algorithm described earlier, has been implemented in a rigid viscoplastic FE code. The best set of the constitutive parameters that minimizes the objective functions is determined by using an optimization scheme. To demonstrate the predictive capabilities of the analytical approximation described in the previous part and to simulate the problem of identification of material parameters, a set of pseudo-experimental load-displacement/displacement rate data has been used for calculating the objective functions. The results confirm the inadequacy of using only the load-displacement results for the identification of the constitutive parameters from the hot torsion results. This is in agreement with the theoretical results in the previous paper. It is shown subsequently that the newly proposed inverse computational method can be used successfully to determine a unique set of the constitutive parameters.     

Heteroscedastic linear feature extraction based on sufficiency conditions

Classification of high-dimensional data typically requires extraction of discriminant features. This paper proposes a linear feature extractor, called whitened linear sufficient statistic (WLSS), which is based on the sufficiency conditions for heteroscedastic Gaussian distributions. WLSS approximates, in the least squares sense, an operator providing a sufficient statistic. The proposed method retains covariance discriminance in heteroscedastic data, while it reduces to the commonly used linear discriminant analysis (LDA) in the homoscedastic case. Compared to similar heteroscedastic methods, WLSS imposes a low computational complexity, and is highly generalizable as confirmed by its consistent competence over various data sets.