Design of a PD like Fuzzy Logic Controller for Precise Positioning of a Stepper Motor

Designing of controllers for control of various motors has been an exciting field for the researchers. Talking of controllers, PID controllers are the most popular among the various industries. Nowadays Fuzzy Logic Controllers (FLC) and PID like FLCs are very famous due to its robust design, faster response and accuracy. In this paper we have proposed a novel method to control a stepper motor with PD like FLC that can handle one sided errors like those in tracking problem such as tracking the Sun and maximum power point in PV array system. During simulation it is seen that the controller can easily handle different errors without much of oscillations. The speed of response mainly depends on the step size of the stepper motor.Keywords: Tracking problem, PD like Fuzzy Logic Controller, Stepper motor control. Matlab/Simulink, Fuzzy Logic toolbox.*Cite as: Jyoti Kumar Barman, Pushpanjalee Konwar, Gitu Das, “Design of a PD like Fuzzy Logic Controller for Precise Positioning of a Stepper Motor†ADBU J.Engg.Tech., 1(2014) 0011407(4pp

Comparative studies on haemato-biochemical changes following pre-emptive analgesia with tramadol, pentazocine lactate and meloxicam inpain management of canine ovariohysterectomy

The present study was conducted to evaluate the effects of tramadol, pentazocine lactate and meloxicam as pre- emptive analgesics in dogs premedicated with glycopyrrolate, inducted with propofol and maintained with propofol continuous rate infusion (CRI) for certain haematological and biochemical parameters. The animals were randomly divided into three equal groups,viz. Group-T, Group-P and Group-M comprising six animals in each group and all the animals were premedicated with glycopyrrolate. After 10 min of pre-anaesthetic administration, pre-emptive analgesia was given. Blood was collected from cephalic or saphenous vein at intervals 0 (baseline) min before premedication, thereafter at 10 min, 30 min, 1 h, 2 h and 3 h after pre-emptive analgesic administration and haemato- biochemical parameters were recorded. Hb, PCV and TEC were significantly decreased at 30 min and 1 h interval in all the three groups. TLC and glucose concentration were significantly higher in group-M as compared to group-T and group-P at different time intervals. GGT level increased significantly at 30 min in all the three groups. CRP concentration was significantly higher in group-M as compared to group-T. Total protein was significantly decreased at 1 h interval in group-T and group-P, but in group-M such finding was noticed at 2 h interval. Cortisol was significantly lower in group-T in entire study period. The alterations in physiological and haematological parameters caused by tramadol, pentazocine lactate and meloxicam were found to be minimal and within the physiological limits. Tramadol produced less significant rise in CRP and cortisol concentrations which indicated better pain management. Based on the findings of the present study, it is concluded that tramadol is more effective as compared to pentazocine lactate and meloxicam in the management of post-operative pain due to canine ovariohysterectomy

New biomass derived carbon catalysts for biomass valorization

Due to diminishing petroleum reserves, unsteady market situation and the environmental concerns associated with utilization of fossil resources, the utilization of renewables for production of energy and chemicals (biorefining) has gained considerable attention. Biomass is the only sustainable source of organic compounds that has been proposed as petroleum equivalent for the production of fuels, chemicals and materials. In fact, it would not be wrong to say that the only viable answer to sustainably convene our future energy and material requirements remain with a bio-based economy with biomass based industries and products. This has prompted biomass valorization (biorefining) to become an important area of industrial research. While many disciplines of science are involved in the realization of this effort, catalysis and knowledge of chemical technology are considered to be particularly important to eventually render this dream to come true. Traditionally, the catalyst research for biomass conversion has been focused primarily on commercially available catalysts like zeolites, silica and various metals (Pt, Pd, Au, Ni) supported on zeolites, silica etc. Nevertheless, the main drawbacks of these catalysts are coupled with high material cost, low activity, limited reusability etc. – all facts that render them less attractive in industrial scale applications (poor activity for the price). Thus, there is a particular need to develop active, robust and cost efficient catalytic systems capable of converting complex biomass molecules. Saccharification, esterification, transesterification and acetylation are important chemical processes in the valorization chain of biomasses (and several biomass components) for production of platform chemicals, transportation fuels, food additives and materials. In the current work, various novel acidic carbons were synthesized from wastes generated from biodiesel and allied industries, and employed as catalysts in the aforementioned reactions. The structure and surface properties of the novel materials were investigated by XRD, XPS, elemental analysis, SEM, TEM, TPD and N2-physisorption techniques. The agro-industrial waste derived sulfonic acid functionalized novel carbons exhibit excellent catalytic activity in the aforementioned reactions and easily outperformed liquid H2SO4 and conventional solid acids (zeolites, ion-exchange resins etc). The experimental results indicated strong influence of catalyst pore-structure (pore size, pore-volume), concentration of –SO3H groups and surface properties in terms of the activity and selectivity of these catalysts. Here, a large pore catalyst with high –SO3H density exhibited the highest esterification and transesterification activity, and was successfully employed in biodiesel production from fatty acids and low grade acidic oils. Also, a catalyst decay model was proposed upon biodiesel production and could explain that the catalyst loses its activity mainly due to active site blocking by adsorption of impurities and by-products. The large pore sulfonated catalyst also exhibited good catalytic performance in the selective synthesis of triacetin via acetylation of glycerol with acetic anhydride and out-performed the best zeolite H-Y with respect to reusability. It also demonstrated equally good activity in acetylation of cellulose to soluble cellulose acetates, with the possibility to control cellulose acetate yield and quality (degree of substitution, DS) by a simple adjustment of reaction time and acetic anhydride concentration. In contrast, the small pore and highly functionalized catalysts obtained by hydrothermal method and from protein rich waste (Jatropha de-oiled waste cake, DOWC), were active and selective in the esterification of glycerol with fatty acids to monoglycerides and saccharification of cellulosic materials, respectively. The operational stability and reusability of the catalyst was found to depend on the stability of –SO3H function (leaching) as well as active site blocking due to adsorption of impurities during the reaction. Thus, our results corroborate the potential of DOWC derived sulfated mesoporous active carbons as efficient integrated solid acid catalysts for valorization of biomass to platform chemicals, biofuel, bio-additive, surfactants and celluloseesters

Assessing the Effectiveness of Climate-Resilient Rice Varieties in Building Adaptive Capacity for Small-Scale Farming Communities in Assam

Rice crop in Assam constitutes a significant portion of the cultivated area, covering around sixty percent of the total area. The state, like many others, confronts the repercussions of climate change, notably evident in recurrent floods that impact agricultural lands. The shifting climate, marked by rising temperatures and increased rainy days, poses threats to crop production. Despite witnessing overall productivity growth, the state grapples with persistent challenges related to flood-induced losses. In response to this, climate-resilient rice varieties were developed to withstand submergence. This study delves into the assessment of the impact of these climate-resilient rice varieties on yield, income, and adoption among farmers. Concentrating on Golaghat and Sivasagar districts, where 106 farmers were interviewed, the research addresses the prevalent challenges in rice cultivation due to changing rainfall patterns. The introduced varieties underwent demonstration in plots, and their effects on yield, income, and adoption were comprehensively evaluated. The study additionally scrutinized the technology and extension gaps in the area, utilizing various indices such as the technology gap, extension gap, technology index, and benefit-cost ratio to measure the efficacy of the introduced varieties. The findings of the study highlight disparities between recommended agricultural practices and the actual methods employed by farmers. Despite these challenges, the introduction of climate-resilient varieties resulted in a noteworthy increase in yield. Economic analysis revealed enhanced profitability from B:C ratio of 0.43 to1.06 and positive changes in economic indicators. The adoption and horizontal spread of these varieties were substantial, with a significant rise from 106 to 378 in the number of adopters and expanded cultivation areas. Overall, the study emphasizes the success of climate-resilient rice varieties in augmenting yield, income, and adoption among farmers. The positive economic changes, coupled with heightened awareness, underscore the importance of promoting such varieties. The study advocates for sustained efforts in disseminating climate-resilient varieties, emphasizing their pivotal role in enhancing farmers' climate resilience. Addressing the identified discrepancies in agricultural practices emerges as a crucial step toward fostering sustainability and optimizing crop yield in the region

Switching to quetiapine for risperidone-induced amenorrhea: Report of two cases

Almost all the antipsychotics can cause hyperprolactinemia-related side-effects like amenorrhea. Quetiapine has been reported to have minimal propensity to cause hyperprolactinemia. We report here two cases of risperidone-induced amenorrhea, who resumed their normal cycle on switching over the medication to quetiapine

Deep Neural Network-Based Smart Grid Stability Analysis: Enhancing Grid Resilience and Performance

With the surge in population growth, the demand for electricity has escalated, necessitating efficient solutions to enhance the reliability and security of electrical systems. Smart grids, functioning as self-sufficient systems, offer a promising avenue by facilitating bi-directional communication between producers and consumers. Ensuring the stability and predictability of smart grid operations is paramount to evaluating their efficacy and usability. Machine learning emerges as a crucial tool for decision-making amidst fluctuating consumer demand and power supplies, thereby bolstering the stability and reliability of smart grids. This study explores the performance of various machine learning classifiers in predicting the stability of smart grid systems. Utilizing a smart grid dataset obtained from the University of California’s machine learning repository, classifiers such as logistic regression (LR), XGBoost, linear support vector machine (Linear SVM), and SVM with radial basis function (SVM-RBF) were evaluated. Evaluation metrics, including accuracy, precision, recall, and F1 score, were employed to assess classifier performance. The results demonstrate high accuracy across all models, with the Deep Neural Network (DNN) model achieving the highest accuracy of 99.5%. Additionally, LR, linear SVM, and SVM-RBF exhibited comparable accuracy levels of 98.9%, highlighting their efficacy in smart grid stability prediction. These findings underscore the utility of machine learning techniques in enhancing the reliability and efficiency of smart grid systems

Efficient hydrothermal deoxygenation of tall oil fatty acids into n-paraffinic hydrocarbons and alcohols in the presence of aqueous formic acid

Hydrothermal deoxygenation of tall oil fatty acids (TOFA) was investigated in the presence of aqueous formic acid (0.5–7.5 wt%) as a H2 donor in the presence of subcritical H2O pressure (569–599 K). Pd and Ru nanoparticles supported on carbon (5% Pd/CSigma, 5% Ru/CSigma, 10% Pd/CO850_DP, and 5% Ru/COPcomm_DP) were found to be efficient catalysts for deoxygenation of TOFA. The reaction pathway was mainly influenced by the concentration of formic acid and the catalyst. In case of Pd catalysts, in the presence of 0–2.5 wt% formic acid, decarboxylation was the dominant pathway producing n-paraffinic hydrocarbons with one less carbon atom (heptadecane yield up to 94 wt%), while with 5–7.5% formic acid, a hydrodeoxygenation/hydrogenation mechanism was favored producing C18 deoxygenation products octadecanol and octadecane as the main products (yields up to 70 wt%). In contrast, Ru catalysts produced a mixture of C5-C20 (n-and iso-paraffinic) hydrocarbons via decarboxylation, cracking and isomerization (up to 58 wt% C17 yield and total hydrocarbon yield up to 95 wt%) irrespective of formic acid concentration. Kinetic studies showed that the rates of deoxygenation displayed Arrhenius type behavior with apparent activation energies of 134.44 ± 31.36 kJ/mol and 148.92 ± 3.66 kJ/mol, for the 5% Pd/CSigma and 5% Ru/CSigma catalyst, respectively. Furthermore, the experiments with glycerol tristearate, rapeseed oil, sunflower oil, rapeseed biodiesel, and hydrolyzed rapeseed oil produced identical products confirming the versatility of the aforementioned catalytic systems for deoxygenation of C18 feedstocks.Bio4Energ