Efficiency Improvement of Rotary Compressor by Improving the Discharge path through Simulation

To help raise consumer awareness on saving energy and create more energy efficient appliances, the government is upgrading the requirements of star rating of air conditioners. The enhanced star rating in air conditioners will significantly support the energy conservation and protect the environment by reducing greenhouse gas emissions in the fight against climate change. The increasing demand for star rated air-conditioners is compelling the compressor designers to develop & optimize more energy-efficient components. This paper deals with discharge port optimization in a rotary compressor, which is heart of an air-conditioner. The existing discharge port is studied & analyzed for the performance in the aspect of its capacity, EER, mass flow rate, over pressure power, area of PV diagram, motor power, valve functioning & stability. The port is redesigned to obtain improved performance, by analyzing the compressor performance parameters. Analysis is performed to study the stresses on the discharge valve and valve lift. Computational fluid dynamics is used to observe the flow behavior & pressure phenomenon in the rotary compressor, since the compressor shell accumulates the discharge gas pressure. The results are validated with the test and improved EER is observed

A Sensitive and Simple HPLC-UV Method for Trace Level Quantification of Ethyl p-Toluenesulfonate and Methyl p-Toluenesulfonate, Two Potential Genotoxins in Active Pharmaceutical Ingredients

A sensitive and simple HPLC/UV method has been developed and validated for the determination of two potential genotoxic impurities, namely methyl p-toluenesulfonate (MPTS) and ethyl p-toluenesulfonate (EPTS) at trace levels in Pemetrexed sodium API. Applying the concept of threshold of toxicological concern (TTC), a limit of 3 ppm each for both genotoxins was calculated based on the maximum daily dose of API. A reversed phase LC method using UV detection was developed and validated. The method was found to be specific and selective for the application. The limit of detection (LOD) and limit of quantitation (LOQ) for both MPTS and EPTS was found to be 0.15 ppm (0.009 μg mL−1) and 0.5 ppm (0.03 μg mL−1), respectively, with respect to sample concentration. The calibration curves of MPTS and EPTS were linear over the concentration range from LOQ to 6 μg/mL. The method was found to be specific, precise, linear and accurate and has been successfully applied to determine the two genotoxins in commercial batches of the API

Zinc oxide nanowire modified flexible plastic platform for immunosensing

In this work, we demonstrate a novel, label-free flexible plastic based platform for immunosensing application. This nanobiosensor platform comprises of mercaptopropionic acid functionalized electrospun zinc oxide nanofiber modified flexible plastic film for covalent conjugation of protein. The highly oriented zinc oxide nanowires were synthesized by simple, low cost electrospinning technique and electrophoretically deposited on the ITO coated flexible plastic sheet. The performance of nanobiosensor platform is validated by using BSA-Anti BSA interaction as a model system. The zinc oxide nanowire modified flexible biosensing platforms have been characterized using scanning electron microscopy and atomic force microscopy. The fabricated flexible plastic based immunosensor shows a remarkable detection limit of 100fg/mL in the wider detection range of 100 fg/mL–100 μg/mL. To the best of our knowledge, this is the first time that zinc oxide nanofiber modified flexible plastic substrate have been used to develop immunosensing application and efforts should be made to explore this flexible immunosensor platform for the detection of several important biomarkers for point of care (POC) diagnostics

Low complexity underdetermined blind source separation system architecture for emerging remote healthcare applications

In this paper, we have proposed a low complexity architecture for the Under-determined Blind Source Separation (UBSS) algorithm targeting remote healthcare applications. UBSS algorithm, departing from the typical BSS convention-equal number of the sources and sensors present, which is of tremendous interest in the field of Biomedical signal processing especially for remote health care applications. Since such applications are constrained by the on-chip area and power consumption limitation due to the battery backup, a low complexity architecture needs to be formulated. In this paper, firstly we have introduced UBSS architecture, followed by the identification of the most computationally intensive module N-point Discrete Hilbert Transform (DHT) and finally proposed a low complexity DHT architecture design to make the entire UBSS architecture suitable for such resource constrained applications. The proposed DHT architecture implementation and experimental comparison results show that the proposed design saves 50.28%, 48.40% and 46.27% on-chip area and 53.25%, 48.01% and 45.95% power consumption when compared to the state of the art method for N=32, 64 and 128 respectively. Furthermore the proposed DHT architecture works for N=2m point, but the state of art architecture works for N=4m point, where m is an integer

A Step Towards Miniaturized Milk Adulteration Detection System: Smartphone-Based Accurate pH Sensing Using Electrospun Halochromic Nanofibers

Development of an economical miniaturized platform for monitoring inherent biophysical properties of milk is imperative for tamper-proof milk adulteration detection. Towards this, herein, we demonstrate synthesis and evaluation of a paper-based scalable pH sensor derived from electrospun halochromic nanofibers. The sensor manifests into three unique color-signatures corresponding to pure (6.6 ≤ pH ≤ 6.9), acidic (pH  6.9) milk samples, enabling a colorimetric detection mechanism. In a practical prototype, color transitions on the sensor strips are captured using smartphone camera and subsequently assigned to one of the three pH ranges using an image-based classifier. Specifically, we implemented three well-known machine learning algorithms and compared their classification performances. For a standard training-to-test ratio of 80:20, support vector machines achieved nearly perfect classification with average accuracy of 99.71%

Measurements of surface ozone at semi-arid site Anantapur (14.62 degrees N, 77.65 degrees E, 331 m asl) in India

Abstract In the present study, an attempt has been made to examine the governing photochemical processes of surface ozone (O3) formation in rural site. For this purpose, measurements of surface ozone and selected meteorological parameters have been made at Anantapur (14.62°N, 77.65°E, 331 m asl), a semi-arid zone in India from January 2002 to December 2003. The annual average diurnal variation of O3 shows maximum concentration 46 ppbv at noon and minimum 25 ppbv in the morning with 1σ standard deviation. The average seasonal variation of ozone mixing ratios are observed to be maximum (about 60 ppbv) during summer and minimum (about 22 ppbv) in the monsoon period. The monthly daytime and nighttime average surface ozone concentration shows a maximum (55±7 ppbv; 37±7.3 ppbv) in March and minimum (28±3.4 ppbv; 22±2.3 ppbv) in August during the study period. The monthly average high (low) O3 48.9±7.7 ppbv (26.2± 3.5 ppbv) observed at noon in March (August) is due to the possible increase in precursor gas concentration by anthropogenic activity and the influence of meteorological parameters. The rate of increase of surface ozone is high (1.52 ppbv/h) in March and lower (0.40 ppbv/h) in July. The average rate of increase of O3 from midnight to midday is 1 ppbv/h. Surface temperature is highest (43–44°C) during March and April months leading to higher photochemical production. On the other hand, relative humidity, which is higher during the rainy season, shows negative correlation with temperature and ozone mixing ratio. It can be seen that among the two parameters are measured, correlation of surface ozone with wind speed is better (R2=0.84) in compare with relative humidity (R2=0.66)

Providing Consistent State to Distributed Storage System

In cloud storage systems, users must be able to shut down the application when not in use and restart it from the last consistent state when required. BlobSeer is a data storage application, specially designed for distributed systems, that was built as an alternative solution for the existing popular open-source storage system-Hadoop Distributed File System (HDFS). In a cloud model, all the components need to stop and restart from a consistent state when the user requires it. One of the limitations of BlobSeer DFS is the possibility of data loss when the system restarts. As such, it is important to provide a consistent start and stop state to BlobSeer components when used in a Cloud environment to prevent any data loss. In this paper, we investigate the possibility of BlobSeer providing a consistent state distributed data storage system with the integration of checkpointing restart functionality. To demonstrate the availability of a consistent state, we set up a cluster with multiple machines and deploy BlobSeer entities with checkpointing functionality on various machines. We consider uncoordinated checkpoint algorithms for their associated benefits over other alternatives while integrating the functionality to various BlobSeer components such as the Version Manager (VM) and the Data Provider. The experimental results show that with the integration of the checkpointing functionality, a consistent state can be ensured for a distributed storage system even when the system restarts, preventing any possible data loss after the system has encountered various system errors and failures