Response surface and artificial neural network simulation for process design to produce L-lysine by Corynebacterium glutamicum NCIM 2168

269-279The L-lysine is one of the most important essential amino acid used in food and pharmaceutical industries. The present investigation was conducted to optimize the L-lysine production by Corynebacterium glutamicum (NCIM 2168). The production parameters such as the temperature, pH and glucose concentration (g/l) were optimised and evaluated by simulation method to develop a suitable model. The experimental design was done using central composite design (CCD). Total 20 set of experiments were performed according to the CCD. The factors and their responses were analysed by using the statistical tools: response surface methodology (RSM) and artificial neural network (ANN) linked with genetic algorithm (GA). The predicted optimum production of L-lysine was 19.003 g/l and 28.363 g/l by CCD-RSM and ANN-GA respectively. During validation by GA under optimized conditions, the L-lysine production was found to be 27.25 ± 1.15 g/l, which was significantly high than that obtained using CCD-RSM optimization method. The ANN coupled with GA was found to be a powerful tool for optimizing production parameters with high level of accuracy. This technique may be used for other fermentation products to optimize the important process parameters before scaling up the process to industrial level

Spectral Characterization of Himalayan Near-Fault Ground Motion

Near-Fault Ground Motion (NFGM) spectral characteristics of three moderate-sized Himalayan earthquakes, viz., the 1986 Dharamsala earthquake (Mw = 5:5), the 1991 Uttarkashi earthquake (Mw = 6:8), and the 1999 Chamoli earthquake (Mw = 6:5) have been studied from the 33 available strong ground motion recordings. Pulse characteristics of fault-normal components in terms of pulse-periods and pulse-indicators have been extracted adopting wavelet analysis. Seven mother wavelets were used in the analysis, and it was found that db4 and db7 mother wavelets were more efficient in extracting the pulse-type characteristics. NFGM spectra, at Bhatwari and Gopeshwar stations, showed higher spectral amplitudes in the velocity-sensitive and acceleration-sensitive regions compared to Indian codal response spectra. This is attributed to high PGV/PGA ratios. The study shows that NFGM leads to widening of acceleration-sensitive region, and the structures that are designed according to the Indian seismic code as flexible structures shall behave as stiff structures when subjected to NFGM

Tunnelling Characteristics of Stone-Wales Defects in Monolayers of Sn and Group-V Elements

Topological defects in ultrathin layers are often formed during synthesis and processing, thereby, strongly influencing their electronic properties . In this paper, we investigate the role of Stone-Wales (SW) defects in modifying the electronic properties of the monolayers of Sn and group-V elements. The calculated results find the electronic properties of stanene (monolayer of Sn atoms) to be strongly dependent on the concentration of SW-defects e.g., defective stanene has nearly zero band gap (~ 0.03 eV) for the defect concentration of 2.2 x 10^13 cm^-2 which opens up to 0.2 eV for the defect concentration of 3.7 x 10^13 cm^-2. In contrast, SW-defects appear to induce conduction states in the semiconducting monolayers of group-V elements. These conduction states act as channels for electron tunnelling, and the calculated tunnelling characteristics show the highest differential conductance for the negative bias with the asymmetric current-voltage characteristics. On the other hand, the highest differential conductance was found for the positive bias in stanene. Simulated STM topographical images of stanene and group-V monolayers show distinctly different features in terms of their cross-sectional views and distance-height profiles which can serve as fingerprints to identify the topological defects in the monolayers of group-IV and group-V elements in experiments.Comment: 18 pages, 5 figures, 1 tabl

Hydrodynamic forces in non-uniform cantilever beam resonator

In this paper, we developed two dimensional and three dimensional boundary element method (BEM) to compute hydrodynamic forces due to the oscillation of non-uniform beam (NUB) in a quiescent incompressible fluid with linear and quartic varying widths. To model the fluid flow under small amplitude oscillation of thin NUB in its first mode, the linearized unsteady Stokes equation is solved using BEM. After finding the converged structural and fluid nodes in all the cases, we compute real and imaginary components of hydrodynamic function. Subsequently, damping ratio or quality factor is found from energy dissipation due to drag forces mainly because of stress jumps across the thin beam thickness. Similarly, the frequency shift is found due to virtual added mass obtained from the mean hydrodynamic thrust force. The results are validated with existing literature and further analysis is done in terms of tapering parameter and index of non-uniform beam, and the corresponding aspect ratio and frequency parameters. Based on the analysis presented, it is found that quartic converging beam provides better quality factor and least added mass effect and it can be explored to design a cantilever based resonator operating in fluid with improved performance such as AFM probes. Thus, the new model developed for non-uniform beam can be useful to drag forces in other types of 2D and 3D beams

Unraveling the mysteries of moyamoya: a rare case report of stroke in young

Moyamoya disease is a unique cerebrovascular disease that is characterized by chronic progressive stenosis of distal part of internal carotid artery with consequent development of a network of collateral vessels in response to brain ischemia. It is mainly seen in individuals of Asian descent and is the most common cause of stroke in Asian children. However, it is rare in Indian subcontinent. Here we report a case of young adult who manifested with moyamoya disease, evident from acute onset ischemic stroke. The patient underwent a diagnostic cerebral angiogram that showed bilateral posterior cerebral artery stenosis with pathognomonic collateral moyamoya vessels. The patient subsequently underwent elective surgical intervention procedures to prevent further complications

Correlation of Ahlback grading and knee society score in patients with moderate to severe osteoarthritis of the knee

Background: Knee osteoarthritis (OA) is a most common rheumatological disorder that causes functional limitation and disability. The most common problem in knee OA are joint pain and stiffness. It will lead to decreased quality of life and it have a serious economic burden on any country due to effect of disability and treatment.Methods: A correlational study was conducted to find out correlation between Ahlback grading and knee society score (KSS) on a sample of 100 moderate to severe knee OA patients and 142 OA knees. Data was collected at orthopedics OPD, for a period of 3 months by purposive sampling.Results: On evaluation, mean age of the participants was 60.19±1.01. Out of 100 patients, 42 patients had bilateral knee OA, therefore total 142 knees included in the analysis. More than half (51%) participants were overweight. Only 34% subjects had compliament to physiotherapy. Around 76% subjects taking analgesics and massage therapy to reduce knee pain. Maximum 82.4% subjects had a poor knee condition in KSS and mean score is 49.07±1.06. Ahlback grading in X-ray had negative correlation -0.610 with KSS. Hence it is evaluated, both the scales have approximately same result as it is analyzed that both scales are moderately correlated. There is significant association of age, occupation and physiotherapy with Ahlback grading followed with KSS significant associated with BMI, occupation and physiotherapy.Conclusions: The study concluded that there is a moderate correlation found between Ahlback X-ray grading and knee society scoring. X-ray and knee society scoring (clinical evaluation) both are essential for effective treatment of OA

Pull-in analysis of non-uniform microcantilever beams under large deflection

Cantilever beams under the influence of electrostatic force form an important subclass of microelectromechanical system(MEMS) and nanoelectromechanical system. Most of the studies concerning these micro-nano resonators are centered around uniform cantilever beams. In this paper, we have investigated another class of micro-resonators consisting of non-uniform cantilever beams. The study is focused around investigating pull-in voltage and resonance frequency of non-uniform cantilever beams when they operate in the linear regime about different static equilibriums. In this paper, we term this frequency as “linear frequency.” Calculation of the linear frequency is done at different static equilibriums corresponding to different DC voltages. We have studied two classes of beams, one with increasing cross sectional area from the clamped edge (diverging beam) and other with decreasing cross sectional area from the clamped edge (converging beam). Within each class, we have investigated beams with linear as well as quartic variation in width. We start by obtaining Euler beam equation for non-uniform cantilever beams considering large deflection and their corresponding exact mode shapes from the linear equation. Subsequently, using the Galerkin method based on single mode approximation, we obtain static and dynamic modal equations for finding pull-in voltage and resonance frequency as a function of DC voltage, respectively. We found that the linear frequency of converging beams increases with increase in non-uniform parameter (α) while those of diverging beams decreases with α. A similar trend is observed for pull-in voltage. Within the converging class, beams with quartic variation in width show significant increase in both frequency and pull-in voltage as compared to corresponding linearly tapered beams. In quantitative terms, converging beams with quartic variation in width and α=−0.6 showed an increase in linear frequency by a factor of 2.5 times and pull-in voltage by 2 times as compared to commonly used uniform beams. Our investigation can prove to be a step forward in designing highly sensitive MEMS sensors and actuators

Analysis of Linear and Non-Linear Stress-Strain Properties for Graphene and Single Walled Carbon Nanotubes

Carbon Nanotube (CNT) has revolutionized the world of nanotechnology with several novel applications in the field of sensors and actuators. Such popularity of CNT is due to its excellent mechanical and electrical properties. There are several studies done on understanding the modeling of mechanical and electrical properties using different approaches ranging from molecular to continuum based method. In this thesis, we focus on estimating the mechanical properties of single walled carbon nanotube (SWCNT) mainly based on stress-strain relationship. There are several approaches such as molecular mechanics, molecular dynamics, coupled molecular-structural mechanics, exponential Cauchy born based continuum method, etc, for estimating the linear and nonlinear stress-strain relationship in order to find elastic modulus of SWCNT. In this thesis, we first find the analytical model using molecular mechanics approach to study the variation of elasticity with the diameter of SWNT under different configurations. It is found that the elasticity becomes size independent if the diameter is above 1 nm. Moreover this approach does not help us to get accurate nonlinear stress-strain relationship. Therefore, we used coupled molecular-structural approach to study the nonlinear variation of stress-strain relationship for different configurations. Then, we come up with compact formulas in order to predict the nonlinear stress-strain relationship. Capitalizing on this approach, we find the equivalent mechanical properties of a beam element for the corresponding C-C bond that exists in CNT. Thereafter, we use these properties to do structural modeling in ANSYS which drastically reduces the modeling effort as compared to molecular dynamics approach. In order to standardize this approach, we do several comparisons and tests with existing results based on other methods. It is found that the results are in good agreement with the literature. After validating the stress-strain properties of SWCNT under different configurations, we do modal analysis to find the first few frequencies for fixed-fixed and cantilever kinds of support. On comparing the results with analytical model based from continuum theory, we get relatively good match for cantilever under vii wider range of aspect ratio- a ratio of length to diameter of SWNT. However, analytical result for the fixed-fixed condition matches well only for larger length to diameter ratio. Furthermore, we investigate different modes of graphene and SWCNT under different configurations to demonstrate the capabilities of this method

Grey-Fuzzy Hybrid Optimization and Cascade Neural Network Modelling in Hard Turning of AISI D2 Steel

Nowadays hard turning is noticed to be the most dominating machining activity especially for difficult to cut metallic alloys. Attributes of dry hard turning are highly influenced by the amount of heat generation during cutting. Some major challenges are rapid tool wear, lower tool-life span, and poor surface finish but simultaneously generated heat is enough to provide thermal softening of hard work material and facilitates easier shear deformation thus easy cutting. Also, plenty of works reported the utilization of various cooling methods as well as coolants which successfully retard the intensity of cutting heat but this leads to additional cost as well as environmental and health issues. However, still, there is scope to select proper cutting tool materials, its geometry, and appropriate values of cutting parameters to get favorable machining outcomes under dry hard turning and avoid the cooling cost, environmental and health issue. Considering these challenges, current work utilizes PVD-coated (TiAlN) carbide insert in dry hard turning of AISI D2 steel. The multi-responses like tool-flank wear, chip morphology and chip reduction coefficient are considered. Further, to get the best combination of input cutting terms, grey-fuzzy hybrid optimization (Type I and Type II) is utilized considering the Gaussian membership function. Type II grey-fuzzy system attributed to 15 % less error (between GRG and GFG) compared to Type I. Hence, Type II grey-fuzzy system is utilized to get the optimal set of input terms. The optimal combination of input terms is found as t-1 (0.15 mm), s-4 (0.25 mm/rev) and is Vc-2 (100 m/min) which is comparable to the results obtained under spray impingement cooling using CVD tool in the literature. However, hard turning can be assessed under the dry condition with a PVD tool at the obtained optimal input condition for industrial uses. Further, six different types of cascade-forward-back propagation neural network modelling are accomplished. Among all models, CFBNN-4 model exhibited the best prediction results with a mean absolute error of 2.278% for flank wear (VBc) and 0.112% for the chip reduction coefficient (CRC). However, this model can be recommended for other engineering modelling problems