Surface tension as a limiting factor for aerobic n-alkane biodegradation

A new mathematical model for n-alkane biodegradation in crude oil, heavy oil and paraffinic mixtures is described. The pattern of n-alkane degradation as a function of the inverse of hydrocarbon chain length reported in this paper can be considered as general behaviour for many aerobic n-alkane biodegradation processes. A new interpretation of n-alkane biodegradation as a function of surface tension, is given. A mathematical expression was obtained starting from the degradation values of n-alkane and relative surface tension, which is a parameter independent of fermentation conditions. An interesting parameter, b, was identified which represented the accelerating conversion factor for n-alkane biodegradation. The findings suggested that the n-alkane biodegradation. The findings suggested that he n-alkane biodegradation rate may be affected by the fermentation condition (agitation, aeration, etc.) and by the strain of microorganism, while the behaviour pattern of n-alkane degradation was essentially linked to the substrate characteristics (molecular structure, molecular weight and density).     

Halogen-free acylation of toluene over FeSBA-1 molecular sieves

Three-dimensional cage type iron substituted mesoporous silica with different iron contents (FeSBA-1) was synthesized in a highly acidic media using cetyltriethylammonium bromide and tetraethylorthosilicate as a template and a silica source, respectively. Acylation of toluene with acetic anhydride (AA) was carried out over FeSBA-1 mesoporous catalysts with different n_Si/n_Fe ratios in the temperature range 80–180 °C for a time-on-stream of 1–6 h under liquid phase conditions. The important factors affecting the conversion and the selectivity of the reaction, such as the reaction temperature, feed ratio, catalyst weight and time-on-stream were studied and the results are discussed in detail. The reaction conditions were optimized and the n_AA/n_Toluene ratio of 2 and catalyst weight of 0.1 g (3.3 wt% of total reaction mixture) were maintained for all catalytic runs. It was found that the catalytic activity is strongly influenced by the amount of tetrahedral iron in the catalysts. Among the catalysts used in the present study, FeSBA-1(36) showed a high toluene conversion and selectivity to p-methylacetophenone (p-MAP) under the optimized reaction conditions. It was also found that the selectivity for p-MAP was always higher than m-MAP and o-MAP for all the catalysts and the activity of the catalysts changes in the following order: FeSBA-1(36) > FeSBA-1(90) > FeSBA-1(120).     

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids, carbohydrates, and lipids, as well as protein synthesis from the consumed food, the liver has many diverse responsibilities and functions that are to be performed. Liver disease may impact the hormonal and nutritional balance in the human body. The earlier diagnosis of such critical conditions may help to treat the patient effectively. A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver. The proposed approach can recognize the abnormalities with better accuracy without training, unlike in supervisory procedures requiring considerable computational efforts for training. In the earlier stages, the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation. Then, the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted–-Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information, which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts. It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%. The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.     

Artificial neural network approach for prediction of stress–strain curve of near b titanium alloy

In the present study, artificial neural network(ANN) approach was used to predict the stress–strain curve of near beta titanium alloy as a function of volume fractions of a and b. This approach is to develop the best possible combination or neural network(NN) to predict the stress–strain curve. In order to achieve this, three different NN architectures(feed-forward back-propagation network,cascade-forward back-propagation network, and layer recurrent network), three different transfer functions(purelin, Log-Sigmoid, and Tan-Sigmoid), number of hidden layers(1 and 2), number of neurons in the hidden layer(s),and different training algorithms were employed. ANN training modules, the load in terms of strain, and volume fraction of a are the inputs and the stress as an output.ANN system was trained using the prepared training set(a,16 % a, 40 % a, and b stress–strain curves). After training process, test data were used to check system accuracy. It is observed that feed-forward back-propagation network is the fastest, and Log-Sigmoid transfer function is giving the best results. Finally, layer recurrent NN with a single hidden layer consists of 11 neurons, and Log-Sigmoid transfer function using trainlm as training algorithm is giving good result, and average relative error is1.27 ± 1.45 %. In two hidden layers, layer recurrent NN consists of 7 neurons in each hidden layer with trainrp as the training algorithm having the transfer function of LogSigmoid which gives better results. As a result, the NN is founded successful for the prediction of stress–strain curve of near b titanium alloy.     

A Constraint-Elimination Technique for Linearly Constrained Array Processing

A new technique is presented for the problem of linearly constrained multi-channel-array processing. The purpose of the array processing is to reject undesired noise, in the minimum-mean-squared-error sense, while responding to any signal coming from a particular direction with a preset, constrained frequency response. In the constraint-elimination technique proposed in this paper, the original constrained-array-processing problem is transformed to the simple unconstrained-Wiener-filtering problem. Transformation of the problem is achieved by introducing a ?compensating? channel to the multichannel processor. Input to the compensating channel is the channel-averaged input. The constraint is then eliminated by expressing the filter weights of the compensating channel in terms of those of the original processor. An adaptive algorithm is derived by applying the stochastic approximation to the simplified Wiener-filtering problem. Simulation experiments verify that the constrained-array-processing problem is properly transformed to the unconstrained one by the proposed technique. Additional experiments show that the adaptive algorithm generally reduces output power while maintaining the constrained frequency response to the desired signal.     

Chip Pulse Shaping in Asynchronous Chaos-Based DS-CDMA

This paper extends and fully formalizes some previous results by developing an analytical method to account for the general chip pulse for DS-CDMA systems in an asynchronous environment with an integrate-and-dump receiver, applying it to commonly used pulses. Given the pulse, such a formal method allows us to define the optimum spreading code autocorrelation to be used and the relative signal-to-interference ratio performance. A chaos-based spreading code is plugged into this model to show that such an optimum performance can be very well approximated by practical sequence generators. This is shown by analyzing some typical bandlimited and substantially bandlimited pulses and determining the optimum spreading for each of them. These results prove that the gain of chaos-based spreading over conventional i.i.d.-like spreading can reach 75% when practical bandlimited pulses are considered.     

Electrodynamically actuated on-chip flow cytometry with low shear stress for electro-osmosis based sorting using low conductive medium

In the proposed paper, we demonstrate on-chip electrodynamically driven actuator flow cytometry, based on negative dielectrophoretic (nDEP) focus and alternating current electro-osmotic flow (ACEOF) sorting technique. This single chip can perform three different functions such as focusing, transportation of beads/cells to detection site and reloading the unsorted ones with two distinctive phenomena. AC EOF is achieved by the design of the asymmetric electrode pair’s array and nDEP is used to focus the beads/cells in-line. The design, simulation and experimental results of the proposed microchip are reported in this paper. The simulation and experimental results reveal well defined stable region for nDEP and ACEOF driving force. The potential severe shear stress damage caused by the sheath flow in conventional flow cytometry is eliminated. In addition, to explore the influence of conductivity of the medium, we have used low conductive formulated medium with conductivity of 81.4 μS/cm. The voltage and the frequency required to manipulate the particles decreased comparatively with the use of this medium.     

Fabrication and morphological control of three-dimensional cage type mesoporous titanosilicate with extremely high Ti content

TiSBA-1 materials with extremely high Ti content, up to silicon to titanium ratio (n_Si/n_Ti) of 2.4, have been successfully prepared through direct synthesis method by controlling the molar ratio of hydrochloric acid to silicon (n_HCl/n_Si). It has been found that the amount of Ti content and the structure of the TiSBA-1 can easily be controlled by the simple adjustment of n_HCl/n_Si ratio. X-ray diffraction pattern (XRD) of the obtained materials revealed that the materials are highly ordered and possess cubic three-dimensional cage type structure with open windows. N₂ adsorption–desorption measurement confirmed the narrow pore size distribution, high specific surface area (1317–1491 m² g⁻¹), and large specific pore volume (0.68–0.75 cm³ g⁻¹) for all the samples. UV–vis DR spectra of the prepared materials confirmed that Ti atoms are exclusively incorporated within silica framework and occupy the tetrahedral position while the presence of isolated bulk titania could be negligible. Morphologies of the TiSBA-1 materials have been also controlled by simply adjusting the n_Si/n_Ti ratio. With the appropriate Ti content, TiSBA-1 materials can be obtained as regular fine spheres. Moreover, the detailed mechanism on the morphological and phase transition control, and the incorporation of high amount of Ti in the framework of TiSBA-1 materials has been also discussed in detail.