Enhanced Room Temperature Coefficient of Resistance and Magneto-resistance of Ag-added La0.7Ca0.3-xBaxMnO3 Composites

In this paper we report an enhanced temperature coefficient of resistance (TCR) close to room temperature in La0.7Ca0.3-xBaxMnO3 + Agy (x = 0.10, 0.15 and y = 0.0 to 0.40) (LCBMO+Ag) composite manganites. The observed enhancement of TCR is attributed to the grain growth and opening of new conducting channels in the composites. Ag addition has also been found to enhance intra-granular magneto-resistance. Inter-granular MR, however, is seen to decrease with Ag addition. The enhanced TCR and MR at / near room temperature open up the possibility of the use of such materials as infrared bolometric and magnetic field sensors respectively.Comment: 22 pages of Text + Figs:comments/suggestions([email protected]

Soil Invertebrates of \u3cem\u3eLasiurus sindicus\u3c/em\u3e Based Grazing Lands: Impact of Management and Grazing Intensity

Arid Western plains of India are dominated by pasture and grazing lands. Lasiurus sindicus (LS) is the dominant na-tive grass species growing on sandy plains and low dunes under the low rainfall extreme desert climate. Palatability and higher crude protein (8-14% in early vegetative growth, 4-6% in 80-120 days of growth) make this grass a highly preferred grazing species. Since drought is frequent (47%) in this part of the country the LS grasslands are under tremendous grazing pressures and classified under poor or very poor condition for livestock. It is imperative to re-store the natural resources on which this grassland depends. Soil invertebrates especially soil collembola and mites are an integral part of this grassland ecosystem. Their community structure changes in response to the changes in management and other factors, and may serve as a tool for rapid impact assessment of restoration measures. With this background, Lasiurus sindicus grazing lands in Jaisalmer District of Western Rajasthan of India were evaluated, to understand the impact of grazing intensity and management practices on the community structure of the soil invertebrates

Young Stellar Population of the Bright-Rimmed Clouds BRC 5, BRC 7 and BRC 39

Bright-rimmed clouds (BRCs), illuminated and shaped by nearby OB stars, are potential sites of recent/ongoing star formation. Here we present an optical and infrared photometric study of three BRCs: BRC 5, BRC 7 and BRC 39 to obtain a census of the young stellar population, thereby inferring the star formation scenario, in these regions. In each BRC, the Class I sources are found to be located mostly near the bright rim or inside the cloud, whereas the Class II sources are preferentially outside, with younger sources closer to the rim. This provides strong support to sequential star formation triggered by radiation driven implosion due to the UV radiation. Moreover, each BRC contains a small group of young stars being revealed at its head, as the next-generation stars. In particular, the young stars at the heads of BRC 5 and BRC 7 are found to be intermediate/high mass stars, which, under proper conditions, may themselves trigger further star birth, thereby propagating star formation out to long distances.Comment: 30 pages, 7 Figures, 6 Tables, accepted for publication in Monthly Notices of the Royal Astronomical Societ

Comparative clinical profile of patients of Benign Prostatic Hyperplasia (BPH) with and without Metabolic Syndrome: a prospective observational study

Background: Benign Prostatic Hyperplasia (BPH) is one of common disorder in men of old age group. The pathogenesis of BPH is multi-factorial and still not been fully elucidated. There are numerous reports which suggest possible link between several metabolic alterations known as Metabolic Syndrome. In the present study, the aim was to establish relation between Benign Prostatic Hyperplasia and Metabolic Syndrome and to find out effects of therapeutic intervention of Metabolic Syndrome on prostatic parameters.Methods: 93 patients of Benign Prostatic Hyperplasia enrolled who met qualifying criteria for inclusion in study and divided into three groups on the basis of Metabolic Syndrome and its treatment administered. Administration of alpha adrenergic blocker was common to all patients of all groups. Metabolic parameters including Fasting blood glucose, High-density lipoprotein (HDL), Triglycerides (TGs), waist circumference and prostatic parameters that is prostate volume, prostate specific antigen (PSA), uroflometry, International prostate symptom score (IPSS) were assessed at baseline, after 3 and 6 months follow-up. Further appropriate statistical tests were applied for comparison of parameters among groups.Results: Patients receiving no treatment for Metabolic Syndrome were having most deranged prostatic parameters as compared to patients without Metabolic Syndrome or patients with Metabolic Syndrome receiving treatment for same. Further patients receiving treatment for Metabolic Syndrome and alpha adrenergic blocker were having better clinical profile than patients of alpha adrenergic blocker alone.Conclusions: These findings show probable link between Metabolic Syndrome and worse prostatic profile. Metabolic Syndrome must be looked for and treated in patients of Benign Prostatic Hyperplasia. Metabolic derangements must not be overlooked and must be treated accordingly

Ground-based optical transmission spectrum of the hot Jupiter HAT-P-1b

Time-series spectrophotometric studies of exoplanets during transit using ground-based facilities are a promising approach to characterize their atmospheric compositions. We aim to investigate the transit spectrum of the hot Jupiter HAT-P-1b. We compare our results to those obtained at similar wavelengths by previous space-based observations. We observed two transits of HAT-P-1b with the Gemini Multi-Object Spectrograph (GMOS) instrument on the Gemini North telescope using two instrument modes covering the 320 - 800 nm and 520 - 950 nm wavelength ranges. We used time-series spectrophotometry to construct transit light curves in individual wavelength bins and measure the transit depths in each bin. We accounted for systematic effects. We addressed potential photometric variability due to magnetic spots in the planet's host star with long-term photometric monitoring. We find that the resulting transit spectrum is consistent with previous Hubble Space Telescope (HST) observations. We compare our observations to transit spectroscopy models that marginally favor a clear atmosphere. However, the observations are also consistent with a flat spectrum, indicating high-altitude clouds. We do not detect the Na resonance absorption line (589 nm), and our observations do not have sufficient precision to study the resonance line of K at 770 nm. We show that even a single Gemini/GMOS transit can provide constraining power on the properties of the atmosphere of HAT-P-1b to a level comparable to that of HST transit studies in the optical when the observing conditions and target and reference star combination are suitable. Our 520 - 950 nm observations reach a precision comparable to that of HST transit spectra in a similar wavelength range of the same hot Jupiter, HAT-P-1b. However, our GMOS transit between 320 - 800 nm suffers from strong systematic effects and yields larger uncertainties.Comment: A&A, accepted, 16 pages, 8 figures, 5 table

KNN-Based ML Model for the Symbol Prediction in TCM Trellis Coded Modulation TCM Decoder

Machine Learning is a booming technology today. In a machine learning set of training, data is to be provided to the model for training and that model predicts the output. Machine Learning models are trained using a computer program known as ML algorithms.The new machine learning-based Transition Metric Unit (TMU) of 4D- 8PSK Trellis coded Modulation TCM Decoder is presented in this work. The classic Viterbi decoder's branch metric unit, or TMU, takes on a complex structure. Trellis coded Modulation (TCM) is a combination of 8 PSK modulations and Error Correcting Code (ECC). TMU is one of the complex units of the TCM decoder, which is essentially a Viterbi decoder. Similar to how the first Branch metric is determined in the straightforward Viterbi decoder, the TCM decoder performs this BM computation via the TMU unit. The TMU becomes challenging and uses more dynamic power as a result of the enormous constraint length and the vast number of encoder states.In the proposed algorithm innovative KNN (K nearest neighbours) based ML model is developed. It is a supervised learning model in which input and output both are provided to the model, training data also called the labels, when a new set of data will come the model will give output based on its previous set experience and data.Here we are using this ML model for the symbol prediction at the receiver end of the TCM decoder based on the previous learning. Using the proposed innovation, the paper perceives the optimization of the TCM Decoder which will further reduce the H/W requirements and low latency which results in less power consumption

Growth of dense CNT on the multilayer graphene film by the microwave plasma enhanced chemical vapor deposition technique and their field emission properties

Catalyst assisted carbon nanotubes (CNTs) were grown on multilayer graphene (MLG) on copper and silicon substrates by the microwave plasma enhanced chemical vapor deposition technique. The transmission of the MLG was found to vary between 82 to 91.8% with the increase of deposition time. Scanning electron microscopy depicted that the MLG film survived at the deposition condition of CNTs with the appearance of the damaged structure due to the plasma. Growth of CNTs was controlled by adjusting the flow rates of methane gas. The density of carbon nanotubes was observed to increase with a higher supply of methane gas. It was observed that the field emission properties were improved with the increased density of CNTs on MLG. The lowest turn-on field was found to be 1.6 V mu m(-1) 1 accompanied with the highest current density of 2.8 mA cm(-2) for the CNTs with the highest density. The findings suggested that the field emission properties can be tuned by changing the density of CNTs

A Survey of Practitioner’s Knowledge of Psychiatric Medication Costs

Introduction. Escalating medical costs continue to be an issue facing contemporary medicine. One factor contributing to this escalation may be physicians’ knowledge of medication costs. As physicians increasingly face opportunities to treat a variety of symptoms and conditions in a single patient, including co-morbid psychiatric disorders or complications, accurate knowledge of medication costs becomes increasingly important. Methods. Resident and attending physicians (N = 16) across the disciplines of internal medicine, psychiatry, and combined internal medicine/psychiatry from a large, mid-western medical school were surveyed on the costs of several medications that are used to manage physical and psychiatric symptoms. Results. Differences were found in the perceived estimated cost of medications among practitioners particularly with specialty internal medicine training as compared to those with additional psychiatric training/experience. Trends also were noted across practitioners with psychiatric and internal medicine/psychiatry training. Conclusions. The breadth of training and experience can affect accuracy in estimating anticipated costs of medication regimens

The impact of lean practices on operational performance - an empirical investigation of Indian process industries

In deciding to adopt lean manufacturing, it is imperative to investigate where and how lean practices are most needed to influence manufacturing and business performance. Such an investigation becomes indispensable when lean thinking is to be considered in a production arrangement different to the conventional, repetitive, high-volume, stable-demand and discrete-manufacturing environment. This study provides explanations of how performance is improved through the adoption of lean practices in process industries. This is a relatively under-researched area compared to the performance effects associated with the introduction and implementation of lean principles in traditional, discrete manufacturing. Based on a survey of Indian process industries, this study attempts to develop an empirical relationship between lean practices and performance improvement through the use of multivariate statistical analysis. The findings have led to the conclusion that lean practices are positively associated with timely deliveries, productivity, first-pass yield, elimination of waste, reduction in inventory, reduction in costs, reduction in defects and improved demand management. However, within a process-industry context, lean practices related to pull production were found to have a marginal impact on performance improvement. A detailed discussion of the findings along with their theoretical and managerial implications is provided in the paper