Alignment Studies for Tungsten Near L3 Sub-Shell Threshold Via Theoretical, Experimental and Empirical Methods

Alignment studies are made for tungsten near L3 sub-shell threshold using theoretical, experimental and empirical approaches. Experimentally to measure alignment parameter, the angular distribution of L x-rays of tungsten (W-74) is measured in the angular range 0° to 120°, where maximum anisotropy is expected. The experimental measurements are performed in XRF laboratories of Raja Ramanna Center for Advanced Technology (RRCAT), Indore, India using a three-dimensional double reflection set-up. The weighted average of alignment values with 10% error comes 0.155 ± 0.009. Theoretically, the value of alignment parameter A20 is calculated using non-relativistic dipole approximation in a point Coulomb potential and is found 0.151 at L3 threshold energy (10.676 keV). For empirical A20 evaluations, IGELCS interpolated experimental LXRF cross-section σ*Lg (g = α, ℓ) values of Mann et al with 8% reported errorsare used along with the radiative decay rates. The comparison among theoretical, experimental and empirical values are similar and values being >0.1 at L3 threshold energy are certainly higher than the 5 to 8 percent uncertainties quoted in earlier experimental results

Analytic perturbation theory to study the effect of screening on alignment of atomic inner shell vacancies

An analytic perturbation theory has been developed for screened Coulomb radial wave functions by interpolating the screened Coulomb potential of McEnnan for elements lanthanum to uranium and was used to calculate alignment of vacancies in L3 sub shell. To check the authenticity of the present method of calculation, the intermediate steps are compared with our earlier formulation of point Coulomb potential for the calculations. A close agreement has been obtained among the values of intermediate steps involved in both the formulations that proved the reliability of present calculations and prompted us to extend the calculations for the elements lanthanum to uranium in the energy region threshold to 60 keV

2D Unsteady Routing and Flood Inundation Mapping for Lower Region of Brazos River Watershed

Present study uses two dimensional flow routing capabilities of hydrologic engineering center\u27s river analysis system (HEC-RAS) for flood inundation mapping in lower region of Brazo River watershed subjected to frequent flooding. For analysis, river reach length of 20 km located at Richmond, Texas, was considered. Detailed underlying terrain information available from digital elevation model of 1/9-arc second resolution was used to generate the two-dimensional (2D) flow area and flow geometrics. Streamflow data available from gauging station USGS08114000 was used for the full unsteady flow hydraulic modeling along the reach. Developed hydraulic model was then calibrated based on the manning\u27s roughness coefficient for the river reach by comparison with the downstream rating curve. Corresponding water surface elevation and velocity distribution obtained after 2D hydraulic simulation were used to determine the extent of flooding. For this, RAS mapper\u27s capabilities of inundation mapping in HEC-RAS itself were used. Mapping of the flooded areas based on inflow hydrograph on each time step were done in RAS mapper, which provided the spatial distribution of flow. The results from this study can be used for flood management as well as for making land use and infrastructure development decisions

A study on pattern of adverse drug reaction in an adverse drug reaction monitoring centre of a tertiary care hospital in South Kerala, India

Background: Adverse drug reactions (ADR) are rated as fifth leading cause of death and accounts for approximately 5% of all hospital admissions. Under reporting of ADR from healthcare professional is considered as the contributing factor for increased morbidity and mortality. India has taken well appreciated step to launch Pharmacovigilance Programme of India (PvPI) to safeguard heath care of Indian population. This study looks into the detailed analysis of ADR reported to adverse drug reaction monitoring centre (AMC), Government Medical College, Trivandrum to assess its pattern, causality, severity and seriousness of ADR. Primary objectives of this study are the pattern of adverse drug reactions reported to ADR monitoring centre (AMC) and secondary objective is to assess causality, severity.Methods: A record based descriptive study was conducted in the ADR monitoring centre of government medical college, Trivandrum, Kerala from September 1st  2016 to February 2017(6 months). The data were collected from the all reported case records/ ADR report form of CDSCO. The details of the various adverse drug reactions were identified and analysed to find the pattern of adverse drug reactions including distribution of age, gender, causal drug group, system organ class. Also, an attempt is made to do causality assessment using WHO UMC scale and severity by using Heart wig Seigel Scale.Results: Out of 320 ADR cases, majority of reports were due to cutaneous manifestations. Most common ADRs were erythema, induration, and rash, itching. Females were 56% and males were 44%. Majority cases were of adult age group. Causality 91.88% were probably related, 75.6% were mild reaction. 25% of cases were serious. 77.5% were recovered. Antibacterial implicated 25(7.8%) followed by anti-epileptics 24 (7.5%) ADR.Conclusions: The pattern of adverse drug reactions reported to this AMC is comparable to the studies done in other parts of country. A strong need for streamlining of ADR monitoring system and reporting reemphasized by this study, which will promote the ADR reporting in healthcare professionals

Global Reactions to COVID-19 on Twitter: A Labelled Dataset with Latent Topic, Sentiment and Emotion Attributes

This paper presents a large, labelled dataset on people's responses and expressions related to the COVID-19 pandemic over the Twitter platform. From 28 January 2020 to 1 Jan 2021, we retrieved over 132 million public Twitter posts (i.e., tweets) from more than 20 million unique users using four keywords: "corona", "wuhan", "nCov" and "covid". Leveraging natural language processing techniques and pre-trained machine learning-based emotion analytic algorithms, we labelled each tweet with seventeen latent semantic attributes, including a) ten binary attributes indicating the tweet's relevance or irrelevance to the top ten detected topics, b) five quantitative emotion intensity attributes indicating the degree of intensity of the valence or sentiment (from extremely negative to extremely positive), and the degree of intensity of fear, of anger, of sadness and of joy emotions (from barely noticeable to extremely high intensity), and c) two qualitative attributes indicating the sentiment category and the dominant emotion category the tweet is mainly expressing. We report the descriptive statistics around the topic, sentiment and emotion attributes, and their temporal distributions, and discuss the dataset's possible usage in communication, psychology, public health, economics, and epidemiology research.Comment: Updated with the complete 2020 data (28 Jan 2020-1 Jan 2021

Estimation of Standby Power Consumption for Typical Appliances

In the past days, many consumers could simply unplug their appliances and go on holidays, assuming that their electricitymeter would just stop. Standby power is a power consumed by an appliance when switched off or not performing its primaryfunctions. Standby power consumption provides good opportunity for reducing both energy consumption and green housegas emissions. Through co-operation among governments, industry and consumers and the co-ordination of internationalpolicies, standby modes can be made more efficient, thereby reducing the overall demand for power.In this paper, standby power consumption of various domestic appliances was determined using an energy cost meter. Theexperimental results shows that the standby power of various house hold electrical appliances is consuming more electricityduring standby mod

Study of prevalence of thyroid dysfunction in type 2 diabetes mellitus

Background: Type 2 diabetes mellitus (T2DM) is associated with increased incidence of thyroid dysfunction (TD). The coexistence of thyroid dysfunction in T2DM patient is an important barrier in achieving treatment goal. The study regarding prevalence of TD in T2DM has not been done in patients of Eastern Uttar Pradesh. The present study was aimed to know the prevalence of thyroid dysfunction in T2DM in patients of Eastern Uttar Pradesh.Methods: This is an observational cross sectional prevalence study of thyroid dysfunction in 250 diagnosed T2DM patients deleat diagnosed based on ADA criteria attending the department of medicine Baba Raghav Das Medical College, Gorakhpur, Uttar Pradesh, Study was India, done over a period of 1 year. Thyroid dysfunction was classified on the basis of ATA criteria. All subjects underwent a detailed history, clinical examination and relevant biochemical tests.Results: The prevalence of thyroid dysfunction in T2DM patients was found to be 20.4% in this study.Conclusions: The prevalence of thyroid dysfunction was found to be higher in type 2 diabetes mellitus patients in comparison to general population as mentioned in different literature

A Conceptual Framework to Predict Mental Health Patients' Zoning Classification.

Zoning classification is a rating mechanism, which uses a three-tier color coding to indicate perceived risk from the patients' conditions. It is a widely adopted manual system used across mental health settings, however it is time consuming and costly. We propose to automate classification, by adopting a hybrid approach, which combines Temporal Abstraction to capture the temporal relationship between symptoms and patients' behaviors, Natural Language Processing to quantify statistical information from patient notes, and Supervised Machine Learning Models to make a final prediction of zoning classification for mental health patients

Role of closed subcutaneous drain in prevention of surgical site infection in perforation peritonitis

Background: Surgery for perforation peritonitis is associated with the highest rates of infective complications, especially surgical site infection. SSI occurs due to failure of obliteration of dead space during abdominal wound closure resulting in formation of hematoma and seroma collection in the surgical wound viz. abdominal wound in cases of perforation peritonitis. This acts as a good culture medium for bacterial organisms to grow and cause wound infection. The bacterial pathogens can be either from intra-abdominal sepsis or nosocomial in origin. Closed suction drains can be used effectively to eliminate dead space in the wound and evacuates the seroma or hematoma collection, thereby reducing chances of SSI and also helps in early detection of SSI by inspecting the nature of drain output. Aim was to evaluate the role of closed suction drains in prevention of SSI in cases of perforation peritonitis. Methods: Comparative study of 60 cases of perforation peritonitis divided into two equal groups (Group A patient with closed suction drain in subcutaneous space vs. Group B patient without closed suction drain). Outcomes of SSI were compared. Results: The incidence of SSI in Group A was 33% whereas in Group B was 70%. 40% cases in SSI in Group A whereas 76% cases of SSI in Group B developed wound dehiscence. Most cases of SSI was diagnosed on POD 2 for Group A and on POD 4 for Group B. Conclusions: The study supports use of closed suction drain in perforation peritonitis for prevention, early detection and appropriate management of SSI