Chemical characteristics of aerosols in MABL of bay of Bengal and Arabian sea during spring inter-monsoon: a comparative study

The chemical composition of aerosols in the Marine Atmospheric Boundary Layer (MABL) of Bay of Bengal (BoB) and Arabian Sea (AS) has been studied during the spring and inter-monsoon (March-May 2006) based on the analysis of water soluble constituents (Na+, NH4+, K+, Mg2+, Ca2+, Cl-, NO3- and SO42-), crustal elements (Al, Fe, and Ca) and carbonaceous species (EC, OC). The total suspended particulates (TSP) ranged from 5.2 to 46.6 μg m-3 and 8.2 to 46.9 μg m-3 during the sampling transects in the BoB and AS respectively. The water-soluble species, on average, accounted for 44% and 33% of TSP over BoB and AS respectively, with dominant contribution of SO42- over both the oceanic regions. However, distinct differences with respect to elevated abundances of NH4+ in the MABL of BoB and that of Na+ and Ca2+ in AS are clearly evident. The non-sea-salt component of SO42- ranging from 82 to 98% over BoB and 35 to 98% over AS; together with nss-Ca2+/nss-SO42- equivalent ratios 0.12 to 0.5 and 0.2 to 1.16, respectively, provide evidence for the predominance of anthropogenic constituents and chemical transformation processes occurring within MABL. The concentrations of OC and EC average around 1.9 and 0.4 μg m-3 in BoB and exhibit a decreasing trend from north to south; however, abundance of these carbonaceous species are not significantly pronounced over AS. The abundance of Al, used as a proxy for mineral aerosols, varied from 0.2 to 1.9 μg m-3 over BoB and AS, with a distinctly different spatial pattern - decreasing north to south in BoB in contrast to an increasing pattern in the Arabian Sea

Event by Event Analysis of High Multiplicity Events Produced in 158 A GeV/c 208 Pb- 208 Pb Collisions

An extensive analysis of individual high multiplicity events produced in 158 A GeV /c 208Pb- 208Pb collisions is carried by adopting different methods to examine the anomalous behavior of these rare events. A method of selecting the events with densely populated narrow regions or spikes out of a given sample of collision events is discussed.Employing this approach two events with large spikes in their eta- and phi- distributions are selected for further analysis. For the sake of comparison, another two events which do not exhibit such spikes are simultaneously analyzed. The findings suggest that the systematic studies of particle density fluctuations in one- and two-dimensional phase-spaces and comparison with those obtained from the studies of correlation free Monte Carlo events, would be useful for identifying the events with large dynamical fluctuations. Formation of clusters or jet like phenomena in multihadronic final states in individual events is also discussed and the experimental findings are compared with the independent particle emission hypothesis by carrying out Monte Carlo simulations

Tree Based Boosting Algorithm to Tackle the Overfitting in Healthcare Data

Healthcare data refers to information about an individual's or population's health issues, reproductive results, causes of mortality, and quality of life. When people interact with healthcare systems, a variety of health data is collected and used. However, these healthcare data are noisy as well as it prone to over-fitting. Over-fitting is a modeling error in statistics that occurs when a function is too closely aligned to a limited set of data points. As a result, the model learns the information and noise in the training data to the point where it degrades the model's performance on fresh data. The tree-based boosting approach works well on over-fitted data and is well suited for healthcare data. Improved Paloboost performs trimmed gradient and updated learning rate using Out-of-Bag mistakes collected from Out-of-Bag data. Out-of-Bag data are the data that are not present in In-Bag data. Improved Paloboost's outcome will protect against over-fitting in noisy healthcare data and outperform all tree baseline models. The Improved Paloboost is better at avoiding over-fitting of data and is less sensitive, according to experimental results on health-care datasets

A SIMPLE AND A CHEAP UV ASSAY METHOD DEVELOPMENT AND VALIDATION FOR THE ESTIMATION OF EPLERENONE IN TABLETS

Objective: To develop a simple and a cheap UV spectrophotometric assay method for the estimation of Eplerenone in tablets and validate as per ICH guidelines.Methods: The optimized method uses 100% potassium dihydrogen orthophosphate, pH 2.0 as a solvent for the estimation of assay of Eplerenone in tablets at a detection wavelength of 245 nm.Results: The developed method resulted in Eplerenone exhibiting linearity in the range 5-15μg/ml. System precision and intra-day precision are exemplified by relative standard deviation of 1.17% and 0.94% respectively. Method was found to be rugged as precision was found to be 1.52%. Percentage Mean recovery was found to be in the range of 98â€102 by percentage method during accuracy studies. Conclusion: A simple and a cheap UV spectrophotometric assay method were developed and validated for the estimation of Eplerenone in tablets as per ICH guidelines and hence it can be used for routine analysis in various pharmaceutical industries.Â

ROLE OF PANCHAKARMA IN MYASTHENIA GRAVIS - A CASE STUDY

Myasthenia Gravis (MG) is a long-term neuromuscular disease that leads to varying degrees of skeletal muscle weakness. The underlying defect is a decrease in the number of available acetylcholine receptors (AChRs) at neuromuscular junctions due to an antibody mediated autoimmune attack. The most commonly affected muscles are those of the eyes, face and swallowing. The cause of this disease can be understood in view of Upahata Dhatu Ushma, Srotas and Marutha respectively. The present observation was conducted with an objective to find out the efficacy of Ayurvedic management in Myasthenia gravis. Here is a case of 50years old Hindu female who was diagnosed as myasthenia gravis (MG) reported with complaining of slurred speech, low pitch of voice, difficulty to open the mouth and to swallow food and weakness in the both upper limbs since 4months was registered in OPD of SKAMCH&RC, Bengaluru. Considering the signs and symptoms patient was treated on the line of Ardita Vata chikitsa, Sarvanga Abhyanga with Moorchita tila taila, Nasya with Yashtimadhu taila, Gandusha with Erimedadi taila, Jihwa nirlekhana with Vacha churna were done. Treatment shows significant improvement in the symptoms without any side effects

Bifidobacterium longum subsp. infantis in experimental necrotizing enterocolitis: alterations in inflammation, innate immune response, and the microbiota.

BackgroundProbiotics decrease the risk of necrotizing enterocolitis (NEC). We sought to determine the impact of Bifidobacterium longum subsp. infantis (B. infantis) in the established rat model of NEC.MethodsRat pups delivered 1 d prior to term gestation were assigned to one of three groups: dam fed (DF), formula fed (FF), or fed with formula supplemented with 5 × 10(6) CFU B. infantis per day (FF+Binf). Experimental pups were exposed to hypoxia and cold stress. Ileal tissue was examined for pathology and expression of inflammatory mediators, antimicrobial peptides, and goblet-cell products. Ceca were assessed for bacterial composition by analysis of the 16S rRNA sequence.ResultsAdministration of B. infantis significantly reduced the incidence of NEC, decreased expression of Il6, Cxcl1, Tnfa, Il23, and iNOS, and decreased expression of the antimicrobial peptides Reg3b and Reg3g. There was significant microbial heterogeneity both within groups and between experiments. The cecal microbiota was not significantly different between the FF and FF+Binf groups. Bifidobacteria were not detected in the cecum in significant numbers.ConclusionIn the rat model, the inflammation associated with NEC was attenuated by administration of probiotic B. infantis. Dysbiosis was highly variable, precluding determination of the precise role of the microbiota in experimental NEC

Implementation of Ac Power Stand by Switch-Off Outlets using Arduino mega2560

As more and more domestic appliances and consumer electronics are installed, house usage electronic devices tends to grow rapidly. A large number of electronic devices increase power consumption in two features, standby power and normal operation power. These two types of power consumption are proportional to the number of domestic devices. As a result, operational cost in household areas is also increasing. To achieve efficient domestic energy management in addition to the technology of standby power reduction

Detection of incorrect and inappropriateImagefrom Tweets in Social Network

Digital imaging has grown to become the prevalent technology for creating, processing, and storing digital memory and proof. Though this technology brings many leverage, it can be used as a ambiguous tool for covering details and evidences. This is because today digital images can be tampered in such supremacy that forgery cannot be find visually. In fact, the immunity concern of digital content has arisen a long time ago and different methods to verify the efficiency of digital images have been developed. Digital images offer many features for forgery detection algorithm to take precedence of specifically the color and brightness of individual pixels as well as an image�s resolution and format. These properties grant for analysis and similarity between the significance of digital forgeries in an attempt to develop an algorithm for detecting image tampering. This paper presents a technique for image copy or move image forgery detection using Radix Sort, FasterK-means clustering algorithm & DCT

Production of Biodiesel using waste temple oil from Shani Shingnapur temple (Dist. Ahmednagar), Maharashtra, India using chemical and biological methods

In India, due to various mythological and religious reasons hundreds of devotees pour oil over the idols in Hanuman or Maruti and Shani temples. The oil once poured cannot be reutilized and was ultimately wasted. These waste temple oil from Shani Shingnapurwas used to produce biodiesel. Immobilized Pseudomonas aeruginosa was used to catalyze transesterification of waste temple oil. The cells of P.aeruginosa were immobilized within the sodium alginate. Biodiesel production and its applications were gaining popularity in recent years due to decreased petroleum based reserves. Biodiesel cost formed from waste temple oil was higher than that of fossil fuel, because of high raw material cost.To decrease the cost of biofuel, waste temple oil was used as alternative as feedstock. It has lower emission of pollutants; it is biodegradable and enhances engine lubricity. Waste temple oil contains triglycerides that were used for biodiesel production by chemical and biological method.Transesterification reaction of oil produces methyl esters that are substitutes for fatty acid alkyl biodiesel fuel. Characteristics of oil were studied such as specific gravity, viscosity, acid number, saponification number.Parameters such as temperature,oil: methanol ratio were studied and 88%, 96% of biodiesel yield was obtained with effect of temperature and oil: methanol ratio on transesterification reaction. Withaddition ofNaOH or KOH to fatty acids which formed salt known as soap,which is excellent emulsifying and cleaning agents

A Grey Wolf Optimization-Based Clustering Approach for Energy Efficiency in Wireless Sensor Networks

In the realm of Wireless Sensor Networks, the longevity of a sensor node's battery is pivotal, especially since these nodes are often deployed in locations where battery replacement is not feasible. Heterogeneous networks introduce additional challenges due to varying buffer capacities among nodes, necessitating timely data transmission to prevent loss from buffer overflows. Despite numerous attempts to address these issues, previous solutions have been deficient in significant respects. Our innovative strategy employs Grey Wolf Optimization for Cluster Head selection within heterogeneous networks, aiming to concurrently optimise energy efficiency and buffer capacity. We conducted comprehensive simulations using Network Simulator 2, with results analysed in MATLAB, focusing on metrics such as energy depletion rates, remaining energy, node-to-node distance, node count, packet delivery, and average energy in the cluster head selection process. Our approach was benchmarked against leading protocols like LEACH and PEGASIS, considering five key performance indicators: energy usage, network lifespan, the survival rate of nodes over time, data throughput, and remaining network energy. The simulations demonstrate that our Grey Wolf Optimisation method outperforms conventional protocols, showing a 9% reduction in energy usage, a 12% increase in node longevity, a 9.8% improvement in data packet delivery, and a 12.2% boost in data throughput