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The advancement of renewable energy resources and their implementation in the power sector poses a serious challenge of maintaining the frequency. In this article, a specified structure-based H $_2$ /H $_\infty$ controller is proposed to stabilise the frequency of the interconnected microgrids system. The norms of the controller are optimized using the teaching-learning-based optimization. A dynamic frequency model of two area microgrids interconnected through a tie-line has been employed to inspect the frequency control of microgrids. Generation using numerous renewable resources and storage sources are considered in suitable combination. The dynamics of dc-link along with measurement unit are also considered in each of the microgrids. In addition, the microgrids are designed with demand response program to damp out the oscillations. A comparative analysis of controllers designed using various existing algorithms namely particle swarm optimization, genetic algorithm, and simulated annealing has been presented. The system response attained is compared to that of other forms of controllers in the literature. Varying input conditions are assumed for wind and solar generation units and their respective frequency responses are studied utilizing two of the best performing algorithms.

The rising global population and worldwide industrialization have led to unprecedented energy demand that is causing fast depletion of fossil reserves. This has led to search for alternative energy sources that are renewable and environment friendly. Use of lignocellulosic biomass for energy generation is considered a promising approach as it does not compete with food supply. However, the lignin component of the biomass acts as a natural barrier that prevents its efficient utilization. In order to remove the lignin and increase the amount of fermentable sugars, the lignocellulosic biomass is pretreated using physical and chemical methods which are costly and hazardous for environment. Moreover, during the traditional pretreatment process, numerous inhibitory compounds are generated that adversely affect the growth of fermentative microbes. Alternatively, biological methods that use microbes and their enzymes disrupt lignin polymers and increase the accessibility of the carbohydrates for the sugar generation. Microbial laccases have been considered as an efficient biocatalyst for delignification and detoxification offering a green initiative for energy generation process. The present review aims to bring together recent studies in bioenergy generation using laccase biocatalyst in the pretreatment processes. The work provides an overview of the sustainable and eco-friendly approach of biological delignification and detoxification through whole-cell and enzymatic methods, use of laccase-mediator system, and immobilized laccases for this purpose. It also summarizes the advantages, associated challenges, and potential prospects to overcome the limitations.

Dyke-Davidoff-Masson Syndrome (DDMS) is a rare neurological condition characterised clinically by recurrent seizures, facial asymmetry, hemiplegia and mental retardation likely due to foetal or early childhood cerebral insult. We describe the MRI findings of DDMS in a 10-year-old male child. MRI brain revealed right cerebral atrophy, ipsilateral thickening of calvarium, right lateral ventricular dilatation, hyper-pneumatisation of frontal sinus, and contralateral cerebellar atrophy which are consistent with DDMS.

Neurofibromatosis is a cancer predisposition syndrome that leads to an increased risk of certain neural tumors. Neurofibromatosis type 1 (NF-1) presents with multiple neurofibromas which may be dermal or plexiform. Neurofibromatosis type 2 is characterized by bilateral vestibular schwannomas. Pituitary masses have been infrequently described in cases of NF-1. We describe the case of an incidentally discovered pituitary macroadenoma in a patient with NF-1. Apart from the macroadenoma, the patient had plexiform neurofibromas of the orbit, Lisch nodules of the iris, and cafe-au-lait spots. The patient was called for medical management but failed to show due to the COVID-19 pandemic.

The structural condition assessment of flexible pavement can be done very conveniently and rapidly using non-destructive testing (NDT). The conventional NDT in-situ pavement evaluation devices require excessive time and resources. Initially, light weight deflectometer (LWD) has been used to measures the deflection and stiffness of bound/unbound pavement layers. Beside LWD produces safe, reliable, rapid and cost-effective in-situ measurements. This paper presents a structural condition assessment model for thin flexible pavement based on LWD and ground penetrating radar (GPR) measurements. An increase in LWD structural index is indicative of the increase in deflection magnitude and scattering through a road section. Case studies were carried out to examine the model and validate by using effective structural number. Result of average surface deflection, 90th percentile surface modulus and pavement thickness reveals good agreement when compared with the prior studies and core samples. The outcome of the structural index model can be said as a quick and simple screening tool at the project or network level to identifying structurally deficient pavements.

Background: Perforated peptic ulcer is the most common cause among all causes of gastrointestinal tract perforationwhich is an emergency condition of the abdomen that requires early recognition and timely surgical management. Peptic ulcer perforation is associated significant morbidity and mortality. The aim of study is to evaluate the incidence, clinical presentation, management and outcomes of the patient with peptic ulcer perforation undergoing emergency laparotomy. Methods: This retrospective study includes 45 patients who were operated for perforated peptic ulcer peritonitis atDepartment of Surgery, Indira Gandhi Institute of Medical Sciences, Patna, Bihar from October 2018 to March 2020. Paediatricpatients of age less than 14 years, patients presenting as recurrent perforation were excluded from the study. A detailed history, clinical presentation and routine investigations were done in all cases. Results: In the present study, most of the patients were male. Most of these patients presents with clinical signs ofperitonitis between 24-48 hours after onset of the pain. Among the patients of peptic ulcer perforation, duodenal perforation (93.3%) is more common and which is the most common cause of perforation peritonitis. The diagnosis is made clinically and confirmed by presence of gas under diaphragm on radiograph. Exploratory laparotomy with simple closure of perforation with omental patch was done in all cases. The most common post-operative complication was wound infection (57.5%). The overall mortality was 11.1%. Conclusions: Late presentation of peptic ulcer perforation is common with high morbidity and mortality. Surgicalintervention with Graham’s omentopexy with broad spectrum antibiotics is still commonly practiced.

Graphene based circular microstrip patch antenna array is presented in this paper. First a single circular patch to resonate at 2.45 GHz is designed in HFSS, then 1 × 2 array and 1 × 4 array are developed in order to improve the gain. The designed patch and arrays are fabricated using copper and graphene and the antenna parameters are measured and compared. This research work mainly focuses on two things; one is to improve the gain by developing array and the other one is to develop graphene antenna array using a simple, low cost printing method. Both are achieved, as the gain is improved by ~ 5 dB for 1 × 4 array when compared to single patch and the graphene antenna is fabricated and tested for its performance and found to be working perfectly as antenna in ISM Band.

Clustering is an effective way to increase network lifetime but it leads to formation of isolated nodes in the wireless sensor network. These isolated sensor nodes forward data directly to sink and consume more energy which significantly reduces the network lifetime. In this article, we present how to maximize the network lifetime through joint routing and resource allocation with isolated nodes technique (JR-IN) between cluster head and isolated nodes in a cognitive based wireless sensor networks. In JR-IN technique the network area is divided into different layers and cluster size is formulated in each layer such that the size of the cluster remains unequal when it moves towards sink. Hence the cluster size is lager in the outermost layer compared to the cluster size in the inner most layer. To avoid inter cluster collision, we proposed different fixed channel to all the cluster heads in the network. For the intra cluster communication, the cluster member (sensor nodes) will lease the spectrum from the cluster head and forward data to their respective cluster head using TDMA technique. The periodical data gathering of cluster heads and forwarding the data to one hop cluster head may tend to lose energy faster and dies out quickly. We also propose in the JR-IN technique, the isolated nodes in the layer will take charge as a cluster head node and utilizes the resource allocated to the respective cluster head and forward the data to next hop cluster head. Simulation result shows that JR-IN outperforms the existing techniques, maximizes network lifetime and throughput and reduces the end to end delay.

Even though degradation and damage to bone and cartilage tissue can be resolved naturally, but there is a great challenge to regenerate functional tissue due to multiple pathological conditions. To treat the diseased/ damaged bone and cartilage tissue as well as to improve or maintain its natural functions and structure, there are different strategies being developed for repair and regeneration of these tissues. Various innovative researches lead to remarkable improvement in clinical outcome of defective bone and cartilage treatments. Biomaterial based scaffolds which are capable of supporting cell growth and applied for replacement of tissue in vivo for both bone and cartilage. The review also delineates about the tissue engineering bioreactors for the recreation of frameworks to recellularise the graft in vitro by presenting them to physiologically significant mechanical or potentially hydrodynamic stimulation condition. This review summarizes and discusses the strategies for regeneration and repair of bone and cartilage tissue, current scenario and application.

Aim To determine the role of scrape cytology in the diagnosis of ovarian neoplasm Material and method This was a prospective study at jlnmc duration of study was from nov 2019 to march 2020 on 100 solid/solid-cystic ovarian neoplasms sent in 10% buffered formalin, then stained with hematoxylin and eosin or Papanicolaou stains. Cytological results were compared with the histological diagnosis taking the latter as the gold standard. Result Among the 100 cases, the standard histopathological diagnosis confirmed 61 as benign, 5 as borderline and 34 as malignant lesion. The diagnostic concordance between cytological and histo pathological study was observed in 97 of the 100 cases. Characteristic cytological pattern was noted in various types of surface epithelial, sex cord stromal and germ cell tumors. The technique had limited value in mucinous tumors to distinguish borderline cases from invasive carcinoma. Conclusions IOC is a good complement to histopathology in the study of ovarian neoplasms, particularly in developing countries like ours, where the facility of frozen sections is often not available. Adequate knowledge on cyto-histological correlation of ovarian scrape cytology may phase out the use of cryostat in intraoperative diagnosis of ovarian neoplasms.

Background: Cholecystectomy is the standard and the only curative treatment for acutecholecystitis. The complications of acute cholecystitis are disastrous to the patients; on the other hand, conservative treatment is associated with recurrence of symptoms and other complications as common bile duct stone. The aim of this study is to weight out the complication of emergency surgery against the complications of conservative treatment in patients with acute cholecystitis. Materials andmethods: A total of 80 patients were included in the study. All Patients underwent early laparoscopiccholecystectomy or interval laparoscopic cholecystectomies for acute calcularcholecystitis from October 2017 to September 2019 were included in the study. Results: The overall complication rate was 15% (6 of 40 in early group and 10% (4 of 40) in the delayed group. One case of delayed group suffering recurrent acute attack and the other one suffering common bile duct stone, there was no major bile duct injury in the delayed group. Conclusion: Laparoscopic cholecystectomy is a safe and cost-effective approach for the treatment of acute cholecystitis within 72 h after the onset of attack.

The soft computing technique, such as an artificial neural network (ANN) is a modelling tool that is used to predict the pavement condition index value. ANN is used to model highly variable non-linear distress available in the pavement. In this paper, the ANN model is trained and tested using three different algorithm Levenberg–Marquardt (LM), Bayesian regularization (BR) and scaled conjugate gradient (SCG) algorithm available in the NN toolbox of MATLAB-2015 version. The flexible pavement distress data collected from the field surveying are used to train and test the ANN model. The algorithms are trained and tested using the 400 data points gathered after the rainy season from four different National Highways (NH) of Bihar, India. The performance of ANN algorithms are determined using the distress density and the calculated pavement condition index (PCI) value. The prediction accuracy of the LM, BR and SCG algorithm was compared using the minimum statistical errors (MSE) and the coefficient of correlation. The LM algorithm has performed better than BR and SCG algorithms. LM algorithm has shown the highest correlation value (89%) compared to BR (76%) and SCG (58%) during training, testing and validation of data points. The models predicted the PCI value with a high correlation coefficient and low MSE value. The five-fold cross-validation has been performed to explain the accuracy of the ANN model which is higher compare to random forest and support vector machine (SVM). The ANN model has shown the highest model accuracy (73%) compared to the SVM model (72%) and RF model (61%).

The suitability of microgrids depends upon the balance between the size, cost-efficiency and reliability of the system. The work involves optimal planning of microgrid taking a case of three locations in the Indian state of Bihar. A combination of Solar/Wind/Bio-generator energy generation units along with diesel generation and the battery is implemented for this purpose. The tradeoff between Cost Of Electricity (COE) and Deficiency of Power Supply Probability (DPSP) has been analysed and an objective function is defined as a combination of the two with a bound of Renewable Factor (RF). A hybrid Particle Swarm Optimisation-Grey Wolf Optimiser (PSO-GWO) is implemented for optimisation. The performance of the algorithm is compared with numerous others using 13 classical benchmark test functions and 10 CEC-06 2019 benchmark functions. The obtained microgrids are analysed to supply at an average Cost of Electricity of 0.17 ( $ / kWh ) meeting at least 93 % of the demand. Besides, an average renewable factor of 0.93 makes the system environmental friendly. The work also includes a sensitivity analysis of Cost of Electricity. The results are compared with those using other previously used algorithms in the literature and the effectiveness of the implemented algorithm is established.

Human Papillomavirus (HPV) is the cause for 90% of cases of Cervical Cancer which can only be cured if diagnosed in early stage. Years of clinical experience in testing the tissue slide and examina...

This paper is presented to observe the conversion of renewable strength resources (RER) into electric power in a standalone hybrid electricity generation system. Recent electricity generation scenarios all over the world are not eco-friendly because the generation systems are by and large depending on fossil fuels that produce greenhouse gasoline (GHG) which contributes to worldwide warming. In this, the aggregate of two electricity resources is taking location i.e. Wind and solar energy. Solar panels are used for converting solar power and wind generators are used for converting wind power into strength. This electrical electricity era can function for numerous purposes. Generation of strength will take place at an affordable cost. This paper provides the Renewable Energy Based Hybrid Technology for Power technology that extracts the renewable energies in Sun and Wind to generate power. System manage relies particularly at the microcontroller. It ensures the optimal utilization of assets and consequently improves the efficiency as related to their person mode of the technology system. Also, it will increase the reliability and decreases the dependence on one unmarried source. This hybrid solarwind energy generating machine is appropriate for industries and additionally for home areas with reasonable price without unfavorable the natural stability like Pollution Free from GHG.

The increase in demand of electricity throughout the world and depleting fossil fuel have proved to be a hurdle in the path of development. In addition environmental aspects of fossil fuel would make the existence of civilisation a difficult task. The design of renewable energy sources have gained much significance in reducing the dependency on fossil fuel. Multiple methods have been utilised for obtaining a feasible combination of renewables. Present work studies one such design optimised by HOMER for a lab facility (at NERIST) Nirjuli, India. The chosen location has sufficient solar energy, trapping off this resource would help in solving power issues. Various cases of interlinking of energy sources are considered and their respective expectancy in terms of meeting up of loads, cost, carbon dioxide emissions and fuel consumption have been observed.

Type 2 diabetic patients show thyroid disorders that may aggravate the metabolic imbalance. In this study, we evaluated the prevalence of abnormal thyroid dysfunction in type 2 diabetes mellitus. This prospective study was conducted among 100 diabetic patients (cases) which were compared with age and sex matched 50 non-diabetic control subjects. TSH (Thyroid Stimulating Hormone), Triiodothyronine (T3) and Thyroxine (T4) were measured. Fasting Plasma glucose and Post Prandial blood glucose is also measured. The result of this prospective study showed, the diabetic patients in the present study although clinically euthyroid show a low level of circulating T3 to which the term “ Low T3 syndrome”given. But there is high prevalence of thyroid disorders in the diabetic population in other studies which indicates that the screening for thyroid disease among diabetic patients should be routinely performed.

With the advent of modern smartphones, AR, VR services and advancement in display resolution of mobile devices coupled with real-time streaming services, the demand for highresolution video has boomed. To fulfill this requirement, a variety of Adaptive Bit-Rate Streaming methods for Video-on-Demand applications are employed. However, the use of multi-pass encoding in the aforementioned methods renders them obsolete when it comes to real-time video streaming due to latency restrictions. In this work, we bypass the conventional multiple-encoding used in Video-on-Demand applications and present a novel machinelearning-based approach that estimates the optimal video resolution for a given content at a particular bit-rate for ultra low latency applications. A new feature that captures temporal as well as spatial correlation in video sequence has been used to train the Deep Neural Network (DNN) model. A python-based testbed is designed to evaluate the proposed scheme. Experiment results corroborate the viability and effectiveness of the proposed method for real-time mobile video streaming applications.

Cascade outbreak is a common phenomenon observed across different social networking platforms. Cascade outbreak might have severe implications in different scenarios like a fake news/rumour can spread across a significant number of people, or a hate news can be propagated, which may incite violence etc. Early prediction of cascade outbreak would help in taking proper remedial action and hence is an important research direction. Most of the existing approaches predicted the popularity of social networking post either by machine learning techniques or using statistical models. Simple machine learning based approaches may miss important features while statistical models use hard-coded functions which might not be suitable in a different scenario. With the availability of huge data, recently deep learning based models have also been applied in the prediction of cascade outbreak. This study identified the limitation of existing deep learning based approaches and proposed a Recurrent Neural Network based Hybrid Model with Feature Concatenation (RNN-HMFC) approach. RNN-HMFC captures important latent features of textual aspect and retweet information respectively by LSTM and GRU and also uses a set of handcrafted features like additional tweet information and user social information for prediction of virality. We achieve 2.7% - 6.45% higher accuracy compared to the state of the art methods on different datasets.

In this contribution, it presents a mechatronics application for automatic color recognition and sorting process performed by the robotic arm. Color sorting is the phenomenon for sorting and analyzing different colors of an object and thereby picking and placing the objects at its desired location, thus enhancing efficiency and minimizing human errors in performing a certain task. The present work discusses the design and development of 3-degree-of-freedom (3-DOF) robotic arm. The system consists of two DC gear motors in order to move the robot in any desired location and four servo motors to control the movement of joints of robotic arm. It includes three joints, an end effector, two rectangular links and a rectangular platform. The type of controller used is Arduino Uno microcontroller which is further interfaced with PIR sensor, color sensor TCS3200 and four servo motors to control the direction of robotic arm. The robotic arms are widely used in industries, but most of them are programmed to follow a previously learned trajectory. Very few robots are able to make real-time decisions, and so they may not be considered smart systems. One example of the smart robotic arm is provided by a device which can sort some objects taking advantage of the information contained in tags glued on the basis of the same objects. These systems can be used in several applications for protecting the environments aimed to automatize the processes of waste stocking and disposal simply differentiating the tag information.

There have been many methods of attaining a suitable combination of renewable energy sources. This work analyses the stability of one such system optimised by HOME-Rquickstart for a small community at Gurmia, India; on the occurrence of faults. The chosen location has a fair potential of solar and wind energy, trapping of these resources efficiently in the form of hybrid microgrid systems could solve major power issues and in the same time supersede the old grids. This work involves simulation of an optimised model obtained from HOMERquickstart package using Simulink. Various cases are considered in interlinking of the energy sources for the microgrid and their respective transient behaviour in the occurrence of faults are observed.

In this paper, we propose a novel strategy for the synthesis of uniformly excited thinned planar antenna (UE-TPA) arrays which renders maximum possible reduction in the peak side lobe level (PSLL) ...

Aim The aim of this study was to compare the cytological features of exudative uids by conventional smear (CS) method and cell block (CB) method and also to assess the utility of the combined approach for cytodiagnosis of these effusions. Materials and Methods: One hundred cases pleural and peritoneal exudative uid samples were subjected to evaluation by both CS and CB methods over a period of 6 months between March 2019 to September 2019. Cellularity, architecture patterns, morphological features and yield for malignancy were compared, using the two methods. Along with the conventional smears, cell blocks were prepared by using 10% alcohol–formalin as xative agent. Result Cellularity and additional yield for malignancy was 5% more by the CB method. Conclusions CB produced signicantly better results while detecting malignant lesions and reducing suspicious results. CB technique denitively increased detection of malignancy in uid effusion when used as an adjunct to CSs. Also, CB provides material suitable for molecular genetic analysis for targeted therapies.

Aim of this paper the infrastructure for the traditional grid & smart grid. Together depend upon management and control system but the main modification is in the security system because it activities the benefits of the cyber world for realizing its objectives, it also faces security attacks. Therefore security of the smart grid becomes foremost concern. Even the best smart grid infrastructure along with best management and control mechanisms will prove to be ineffective if security of the smart grid is not taken care of. In this discusses about the importance of protection in smart grid. It presents a review of progress made by researchers and governments and the technologies used in the area. It identifies the security issues involved with the current infrastructure. It points out about the areas in security where the research is still needed and discusses some observations regarding improvement of security in smart grid.

This research deals with the design and development of Blast and Heavy Impact Simulation mechanism (BHISM) for generating high fidelity data for impact resistant design, testing and validation of reinforced concrete structures experimentally. A commercial finite element software LS-DYNA is used to solve the governing equations, Altair-Hypermesh for meshing and LS-Prepost for pre and post processing. The basic principle used to generate high pressure shock wave is same as the shock tube. The propulsion of shock wave will achieve due to rupture of the diaphragm by accumulation of pressure in high pressure zone (driver section) of BHISM. A missile is placed after diaphragm i.e. low pressure zone (driven section) of BHISM. The Missile is restrained in five degrees of freedom except in the forward surge direction of translation. When the pressure is transferred on to the missile, it will move with a velocity. Analysing the RC members subjected to impact loading due to missile is future target. This research will be useful to find out the necessary parameters required for better construction of RC structures due to impact loading and to modify the existing codes on impact resistant RC structures.

This contribution deals with the design of a wideband 10W power amplifier based on non-distributed approach using 0.25 $\mu$m AlGaN/GaN on SiC substrate. Due to the moderate power density of the process, the power amplifier has been designed using the non-distributed (conventional common source) approach with class AB operation. Thus, Gain flatness and output power and PAE become hard to maintain throughout the frequency bandwidth in non-distributed topology. Fabricated Power amplifier exhibits a power gain of 5dB and greater than 10W of saturated Power.

Very high output power level is achieved at microwave frequencies using Gallium Nitride technologies due to high breakdown voltage, high current density and high carrier mobility in AlGaN/GaN based High Electron Mobility Transistors. The specific 0.45 $\mu$m AlGaN/GaN on SiC HEMT based MMIC technology is developed for this purpose to operate at high DC bias voltage of 50 V to achieve high power at microwave frequencies. This paper demonstrates that a high microwave power exceeding 100 W can be achieved from a single MMIC chip fully matched to 50 Ohm at S-band frequencies. In addition to high power, high power added efficiency greater than 50% is also achieved in this chip. The implemented high-power amplifier chip is a two-stage amplifier achieving output power greater than 50 dBm with power gain better than 22 dB, and power added efficiency exceeding 50% over frequency range of 3.1-3.5 GHz. The MMIC chip layout area is as compact as 5.8 $\times$ 3.3 mm2. The saturated output power density of transistor in this chip reaches value of 7 W/mm, maximum possible in this technology.

Almost from the beginning of mankind, there has been the existence of different kinds of wine. It has also become very important for us to know the quality of the wine, before consuming it. In the last few decades, the food industry has grown enormously and so are the food quality analysis and its “rating” process. We often come across cases in which a consumer falls sick because of consuming low-quality food, so it has become a necessary evil for us to have a quality analysis of a product before selling the product, “evil” because it adds up extra cost to the production of the final product. Similarly, it is also necessary to do a quality analysis of wine and there have been different methods used to determine the quality of the wine, but we often get confused regarding which method to rely on! This paper focuses on the comparative study over different classification algorithms for wine quality analysis which are: SVM, random forest and multilayer perceptron and to know which of the above-mentioned classification algorithms give more accurate result.

Background Chest injuries, accounting for 25% of all trauma-related deaths, are one of the main causes of death in young adults. Our priority is the early identification of life-threatening injuries both immediate and delayed. The role of various biomarkers, such as Clara cell protein 16, von Willebrand factor, interleukin-6, tumor necrosis factor, and angiopoietin, has been studied in trauma-related acute respiratory distress syndrome (ARDS). Serum angiotensin-converting enzyme (ACE) levels have been studied in non-trauma-related ARDS. The aim of this prospective observational study was to evaluate the role of ACE levels as a prognostic marker in thoracic trauma. Methods A prospective observational study was conducted to evaluate serum ACE levels in thoracic trauma patients and to explore its prognostic potential with regard to clinical outcome. A total of 48 thoracic trauma patients were included in the study. Results The mean ACE level in the study population was 66.54+-11.18. A strong positive correlation was found among serum ACE levels and Thoracic Trauma Severity Score (TTSS). Conclusion Our study demonstrates that serum ACE levels are increased in thoracic trauma patients with higher levels, indicating the severe nature of trauma in concordance with increased TTSS scores.

The non-conventional sources of energy like wind, solar and hydro are available everywhere, environmentally friendly and free. The wind energy systems might not generally be used at all locations since of low wind speeds and are additional unpredictable than solar energy. The grouping of renewable energy sources is consequently an area of the researcher to explore and can be broadly used as another to conventional sources energy. In this paper, we initially assessment together with the wind power and photovoltaic power generation procedures and their maximum power point tracking technique. In this paper, we have to design and analyzes a hydropower generation that combination of solar and wind energy conversion techniques

Background: Prescribing patterns provides prescribing behaviors of prescriber. Hypertension is most common cardiac complication among middle and old age population. Thus, study about prescribing trends helps to select appropriate drug for treatment of hypertension. The study aim was to analyze the patterns of antihypertensive drug prescribed in patients diagnosed with hypertension.Methods: The study was cross sectional and observational study. A questionnaire was specifically designed factoring patients’ demographical profile, diagnosis of disease, drug regimen.Results: The totals of 100 patients were analyzed for the prescribing patterns of antihypertensive drug maximum patients belonged to the age group of 61-80. The proportion of male (62%) patients was more as compared to female patients (38%). Total drug prescribed was 246 in 100 prescriptions. Average drug per prescription was 2.46. Among 246 drugs, 97% were antihypertensive prescribed and 3% were other concomitant drugs. 65% single drug prescribed, 25% two drug prescribed and 10% three drug prescribed. Most commonly single antihypertensive drug prescribed was telmisartan. Most commonly two antihypertensive drug prescribed was telmisartan + hydrochlorothiazide. Most commonly three antihypertensive drug prescribed was telmisartan + amlodipine + hydrochlorothiazide. Among total 246 drug prescribed, angiotensin receptor blocker was prescribed (ARB) 28%, calcium channel blocker (CCB) 17%, angiotensin converting enzyme inhibitor (ACEI) 12%, beta blocker 5% followed by ARB + diuretics 13%, ACEI + diuretics 8%, beta blocker + CCB 4%, ARB + CCB + diuretics 7%, ARB + beta blocker + diuretics 3% and 3% other drug prescribed. There was no fixed dose combination prescribed and no injectable prescribed in present study.Conclusions: The most common drug prescribed was ARB as single drug therapy. The most common drug which was used for combination therapy was diuretics.

Wireless networks are gaining popularity to its peak today, as the users want wireless connectivity irrespective of their geographic position. An ad-hoc wireless network is a collection of nodes that come together to dynamically create a network, with no fixed infrastructure or centralized administration. In mobile ad-hoc networks, data transmission is performed within an untrusted wireless environment. The lack of centralized infrastructure in ad-hoc network makes it vulnerable to various attacks. Sybil attack is one of the serious attacks, which form a serious threat in the networks, especially against many ad hoc wireless routing protocols, and location based wireless security system. In the Sybil attack incorporates a malicious device with the ability to illegitimately take on several identities in the same network. The forged identity from a malicious device is called a Sybil node. A malicious device can obtain an identity for a Sybil node in two different ways; (a) generating a new identity; or (b) taking the identity from an existing node (with the cooperation of the node or by developing a spoofing attack). We identify two types of Sybil attacks. In the first type, malicious nodes do not take part in finding routes, meaning that, legitimate nodes do not know their existence. In the second type, malicious nodes do create route advertisements and legitimate nodes are aware of the existence of malicious nodes, just do not know they are malicious. Some of the researchers have proposed many solutions for Sybil attack. In this paper, an efficient method to detect a Sybil attack called modified Sybil detection AODV protocol has been proposed. Detection of Sybil attack is performed using number of hops in different paths from source to destination and delay of each node in different paths from source to destination. The destination is able to detect both kinds of Sybil attacks. The performance of modified Sybil detection AODV protocol is justified by simulations.

specially appointed system (MANET) is a self- designing system that is shaped naturally by means of remote connections by a accumulation of portable hubs without the assistance of a settled base or brought together administration. The versatile hubs forward parcels for one another, permitting correspondence among hubs outside remote transmission extent bounce by jump. Because of dynamic base less nature and absence of brought together observing focuses, the specially appointed systems are powerless against assaults. Assaults on impromptu system directing conventions upset system execution and dependability. This paper endeavors to give a extensive outline of assaults and secure steering. It first breaks down the reason that impromptu system is defenseless against assaults. At that point it introduces the understood assaults and the prevalent secure conventions. KeywordsAODV, SRP

Background: Vildagliptin has multiple beneficial effects reported in isolated studies like anti-diabetic, cardio protective, anti-inflammatory and antioxidant. However, there is no experimental evidence presently available with regard to the possible beneficial effects of vildagliptin on attenuating changes observed in metabolic syndrome co-existing with diabetes in experimental rats. Thus, the present study was designed to evaluate potential effects of vildagliptin on various components of metabolic syndrome. Also to elucidate the underlying mechanisms: DPP-IV, anti-inflammatory, antioxidant pathways were studied. Methods: A combination of high fat diet (HFD) and low dose of streptozotocin (STZ) 40 mg/kg was used to induce metabolic syndrome co-existing with diabetes mellitus in wistar rats. The HFD were fed to rats for 10 weeks to induce metabolic syndrome. At the end of 3 weeks, diabetes was induced by a single STZ injection (40 mg/kg body weight). Vildagliptin (10 mg/kg) was administered to rat from 5th to 10th weeks daily and various parameters of Diabetes and metabolic syndrome were studied. Also to understand the mechanisms; DPP-IV pathway, anti-inflammatory, antioxidant parameters were studied. Biochemical indices of injury (pancreatic, liver and renal function) and histopathological assessment of injury was evaluated in experimental groups. Immunohistochemistry of pancreas was done to assess beta cell mass. Results: The vildagliptin treatment ameliorated the deleterious effects associated with metabolic syndrome and diabetes. The beneficial effects demonstrated by vildagliptin on various parameters include: anti-diabetic (reduced blood glucose, HbA1c, HOMA-IR, increased serum insulin, HOMA-β and restoration of pancreatic function), central obesity (reduced body weight, abdominal circumference (AC), thoracic circumference (TC), AC/TC ratio) and hypolipidemic (favourable lipid profile, artherogenic index) activity. A significant restoration of cardiac injury as indicated by CPK-MB levels was observed. In addition, DPP-IV pathway (reduced serum DPP-IV), anti-inflammatory (reduced hs-CRP levels), and antioxidant (reduced MDA) contributed its beneficial effects in diabetes with metabolic syndrome model. The protective effects on heart, pancreas, liver and kidney were confirmed by histopathological report. The immunohistochemical report of pancreas showed preservation of beta cell mass in vildagliptin treated rats. Conclusions: Vildagliptin treatment ameliorates deleterious changes of diabetes with metabolic syndrome. Beneficial effects of vildagliptin can be attributed to hypoglycemic, hypolipidemic, antioxidant, cardioprotective and anti-inflammatory effects.

Background: Several epidemiological studies have found that in type II diabetic patients, Metformin improves vascular function and reduces cardiovascular events and mortality by mechanisms that are not entirely attributed to its anti- hyperglycemic effects; So far the effect of Metformin on experimentally induced myocardial infarction in setting of type II diabetic rats has not been studied. The aim of the present study was to investigate potential cardioprotective effects and mechanisms of Metformin subsequent to isoproterenol induced myocardial infarction in the setting of diabetes. Methods: Diabetes was induced with single dose of Streptozotocin (STZ): 45mg/kg ip and myocardial infarction was produced by administering isoproterenol (ISP): (85mg/kg, sc) to rats 24 and 48 h prior to sacrification (5th week). After the confirmation of diabetes on 7th day (Glucose>200mg/dl), Metformin (100 mg/kg) was administered and various parameters like anti-diabetic (Glucose, HbA1c), cardioprotective (CPK-MB, hs-CRP), metabolic (lipid profile, artherogenic potential), antioxidant (MDA) safety {pancreatic function (lipase), liver function (SGPT), kidney function (Creatinine) and histopathological indices of injury were evaluated in experimental groups. Results: Administration of STZ-ISP resulted in a significant decrease in body weight (p

Indexing provides fast searching over big data. It is a data structure technique to efficiently retrieve records from the database files based on some attributes on which the indexing has been done. With the help of indexing, queries usually results in much better performance. Hive is batch-oriented data warehouse software. With the help of hive we can perform query processing and data analysis task. Hive is popular because it supports a bulk of the SQL operations in relational database management systems. To improve performance of database systems join has been the focus of several query optimization techniques. As a result the aim of this work is in two folds: Firstly we implement index based join technique and integrated in Hive and secondly performance is estimated, after perform join operation. we run relevant test queries on datasets generated using the industry standard benchmark, TPC-H. Our results indicate significant performance gain over highly selective queries.

The world is progressing towards innovative advancement step by step bringing about an exponential rise in data. This enormous volume of data has presented the possibility of Big data, which has caught the consideration of business and IT researchers as a gift and a source of various opportunities for extensive associations. Securing this enormous measure of information has turned into an extraordinary concern in the field of data and communication technology. Hadoop, as an open-source distributed computing and Big data framework, is progressively utilized as a part of the business world, however the imperfection of security mechanism now ends up noticeably one of the fundamental issues obstructing its improvement. This paper depicts the different attack in detail which is possible on the Hadoop framework. The objective of this paper is to draw out an overview on the security risk and their identification technique in the Hadoop environment.

In this paper, a novel algorithm is devised to reduce the peak side lobe level (PSLL) of the thinned planar antenna (TPA) array at antenna boresight as well as over the desired scan volume without occurrence of grating lobes when the beam is electronically scanned away from the boresight. Randomized symmetrical thinning is incorporated in the proposed algorithm to find the best combination of 'ON' and 'OFF' elements. Modified binary coded genetic algorithm (MBC-GA) is employed in the present study to solve this optimization problem. A 12×12-element TPA array is numerically examined to access the performance of proposed method. Results obtained through this study show that array under consideration renders maximum possible reduction in PSLL and also demonstrate the absence of grating lobes when the beam is scanned to 20 deg. and 40 deg. away from the boresight.