Optimal Power Flow with Static VAR Compensator Using Galaxy Based Search Algorithm to Minimize Real Power Losses

AbstractIn this paper, Galaxy based search algorithm (GbSA) is used to solve multi-objective problem of optimization in power systems. The proposed GbSA resembles the spiral arms of some galaxies to search for the optimal solutions. The GbSA also uses a modified Hill Climbing algorithm as a local search. Simulation results show that the GbSA finds the optimal or very near optimal values in all runs of the algorithm. The weighted sum technique with equal weights has been chosen to solve the multi-objective function. The functions considered are to minimize the power losses in transmission line, cost of the real power generation and voltage deviation. Static VAR Compensator (SVC) is used for the purpose of optimal power flow. L-index is used to identify the optimal location to place SVC. The results have been compared with Genetic algorithm (GA) for IEEE-14 System

Quasi Switched Capacitor based integrated Boost Series Parallel Fly-back Converter for energy Storage Applications

711-715A quasi-Switched Capacitor technique (QSC) is used to control the switch in Interconnected Boost Series Parallel Fly-Back Converter (IBSPFC). The QSC based IBSPFC does not require any snubber circuits for all the MOSFET switches presented at primary and secondary side and power can also be transferred even if one the winding gets damage. The primary side winding of the fly-back transformer is coupled in series across with bulk capacitor to minimize switch voltage stress and the secondary winding of the 1:1 fly-back transformer is coupled with dc voltage source, three switches and capacitor which forms a Quasi switched capacitor technique. Working techniques of quasi-switched capacitor with IBSPFC have been introduced. A 75v input, 100v output and DC-DC isolated Converter switching at frequency of 100 kHz is modeled using FPGA SPARTAN6LX9 and experimental results have been presented

Ascertaining Along With Taxonomy of Vegetation Folio Ailment Employing CNN besides LVQ Algorithm

In agriculture, early disease detection is crucial for increasing crop yield. The diseases Microbial Blotch, Late Blight, Septoria leaf spot, and yellow twisted leaves all have an impact on tomato crop productivity. Automatic plant illness classification systems can assist in taking action after ascertaining leaf disease symptoms. This paper emphasis on multi-classification of tomato crop illnesses employs Convolution Neural Network (CNN) model and Learning Vector Quantization (LVQ) algorithm-based methodology. The dataset includes 500 photographs of Tomato foliage with four clinical manifestations. CNN paradigm performs feature extraction and categorization in which color information is extensively used in plant leaf disease investigations. The model's filters have been applied to triple conduit similar tendency on RGB hues. The LVQ was fed during training by a yield countenance vector of the convolution component. The experimental results reveal that the proposed method accurately detects four types of solanaceous leaf diseases

Empowering Visually Impaired through the Assistance of SAHAYAK – A Walking Aid for the Blind

To help blind people overcoming difficulty in their movement in the physical environment and even in their home, a study on an engineering concept is very much necessary. So, our research comes out with an aid that will help blind people in their surroundings. It can detect any obstacle that will block the path of the blind. And The motion of the user can be sensed by the bot. Thus, Blind people can comfortably receive the help of our bot in assisting their movement from one place to another. This paper describes about an automated vehicle which can be controlled by an ultrasonic sensor to avoid obstacles when they move in their environment. Our automated robotic system is made up of an ultrasonic sensor and Arduino micro controller controls our automated bot. It is located in the front part of the bot. The ultrasonic sensor retrieves the data from the environment through the sensors attached to the bot. When any obstacle is detected then immediately that path is changed and an obstacle free path is chosen. The bot wheel is moved based on the data received by the controller from the sensor. The direction and wheel movement of the bot and will be decided from the ultrasonic sensor sensing and also using wheel encoder. It is used for detection and avoidance of interference. The controller is also programmed to be used with an android application

Characterisation of atmospheric aerosol by SEM-EDX and Ion-chromatography techniques for eastern Indo-Gangetic plain location, Varanasi, India

Atmospheric aerosol consists of both natural and anthropogenic origin. Studies have shown that continuous exposure to these particles is associated with a high percentage of death from respiratory and cardiovascular disease. In the present study, we have first time used both SEM-EDX analysis as well as chemical analysis to understand the differences in morphology and elemental composition of aerosols sample from a suburban clean and green area of Banaras Hindu University campus and some much polluted urban areas of the Varanasi city situated in the eastern Indo-Gangetic plain. The analysis was done by using scanning electron microscope (SEM) coupled with energy dispersive X-ray microanalyzer (EDX) and ionchromatography (IC). Analyses show that C, Ca, Na, S, Si, Al have dominated the sample

Effectiveness of pegylated erythropoietin in renal anaemia patients on dialysis-a multicentre, cross-sectional, observational outcome study

Background: Low dose of pegylated erythropoietin (PegEPO) is better than conventional erythropoietin stimulating agents (ESAs) in improving hyporesponsiveness and maintaining stable haemoglobin (Hb) levels in renal anaemic patients undergoing hemodialysis. This real-world study aimed to assess effectiveness and safety of low-dose PegEPO (30 µg/0.3 mL), administered at different time-points in renal anaemia patients on dialysis. Methods: HEMEPEG (HEMoglobin outcomE with PegEPO) was a multicentre, retrospective, cross-sectional, observational study of renal anaemia patients receiving PegEPO up to 3 months. The study assessed an increase in Hb, patients achieving Hb 10-12 g/dl, and Hb increase by ≥1 and ≥2 g/dl. Results: Data from 223 out of 273 patients from 19 Indian centers were analyzed. PegEPO was administered weekly to 132 patients (59.19%), with 38.64% being diabetic and 77.27% previously treated with ESAs. Ten day dosing was given to 91 patients (40.81%), including 46.15% diabetic patients and 72.53% previously treated with ESAs. A Significant (p<0.0001) increase in mean Hb levels from baseline to day 30, 60 and 90 were observed for both studied groups, with a target Hb of 10-12 g/dl achieved in 51.08% and 52.85% of patients in the respective groups after 3 months. An increase in Hb by ≥1 and ≥2 g/dl were observed in weekly (68.67% and 45.78%) and 10-day group (77.14% and 50.00%) patients, respectively. Conclusions: PegEPO (30 µg/0.3 mL) was effective treatment of renal anaemia and diabetic chronic kidney disease (CKD) patients on dialysis when administered weekly or every 10 days over a 3-month treatment period

On the Limited Role of Electronic Support Effects in Selective Alkyne Hydrogenation: A Kinetic Study of Au/MO\u3csub\u3ex\u3c/sub\u3e Catalysts Prepared from Oleylamine-Capped Colloidal Nanoparticles

We report a quantitative kinetic evaluation and study of support effects for partial alkyne hydrogenation using oleylaminecapped Au colloids as catalyst precursors. The amine capping agents can be removed under reducing conditions, generating supported Au nanoparticles of ~2.5 nm in diameter. The catalysts showed high alkene selectivity (\u3e90%) at all conversions during alkyne partial hydrogenation. Catalytic activity, observed rate constants, and apparent activation energies (25– 40 kJ/mol) were similar for all Au catalysts, indicating support effects are relatively small. Alkyne adsorption, probed with FTIR and DFT, showed adsorption on the support was associated with hydrogen-bonding interactions. DFT calculations indicate strong alkyne adsorption on Au sites, with the strongest adsorption sites at the metal-support interface (MSI). The catalysts had similar hydrogen reaction orders (0.7–0.9), and 1- octyne reaction orders (~ 0.2), suggesting a common mechanism. The reaction kinetics are most consistent with a mechanism involving the non-competitive activated adsorption of H2 on an alkyne-covered Au surface

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

Macrophage targeted theranostics as personalized nanomedicine strategies for inflammatory diseases

Inflammatory disease management poses challenges due to the complexity of inflammation and inherent patient variability, thereby necessitating patient-specific therapeutic interventions. Theranostics, which integrate therapeutic and imaging functionalities, can be used for simultaneous imaging and treatment of inflammatory diseases. Theranostics could facilitate assessment of safety, toxicity and real-time therapeutic efficacy leading to personalized treatment strategies. Macrophages are an important cellular component of inflammatory diseases, participating in varied roles of disease exacerbation and resolution. The inherent phagocytic nature, abundance and disease homing properties of macrophages can be targeted for imaging and therapeutic purposes. This review discusses the utility of theranostics in macrophage ablation, phenotype modulation and inhibition of their inflammatory activity leading to resolution of inflammation in several diseases