Acquisition and correlation of cryogenic nitrogen mass flow data through a multiple orifice Joule-Thomson device

Liquid nitrogen mass flow rate, pressure drop, and temperature drop data were obtained for a series of multiple orifice Joule-Thomson devices, known as Visco Jets, over a wide range of flow resistance. The test rig used to acquire the data was designed to minimize heat transfer so that fluid expansion through the Visco Jets would be isenthalpic. The data include a range of fluid inlet pressures from 30 to 60 psia, fluid inlet temperatures from 118 to 164 R, outlet pressures from 2.8 to 55.8 psia, outlet temperatures from 117 to 162 R and flow rate from 0.04 to 4.0 lbm/hr of nitrogen. A flow rate equation supplied by the manufacturer was found to accurately predict single-phase (noncavitating) liquid nitrogen flow through the Visco Jets. For cavitating flow, the manufacturer's equation was found to be inaccurate. Greatly improved results were achieved with a modified version of the single-phase equation. The modification consists of a multiplication factor to the manufacturer's equation equal to one minus the downstream quality on an isenthalpic expansion of the fluid across the Visco Jet. For a range of flow resistances represented by Visco Jet Lohm ratings between 17,600 and 80,000, 100 percent of the single-phase data and 85 percent of the two-phase data fall within + or - 10 percent of predicted values

An Investigation on Disease Diagnosis and Prediction by Using Modified K-Mean clustering and Combined CNN and ELM Classification Techniques

Data analysis is important for managing a lot of knowledge in the healthcare industry. The older medical study favored prediction over processing and assimilating a massive volume of hospital data. The precise research of health data becomes advantageous for early disease identification and patient treatment as a result of the tremendous knowledge expansion in the biological and healthcare fields. But when there are gaps in the medical data, the accuracy suffers. The use of K-means algorithm is modest and efficient to perform. It is appropriate for processing vast quantities of continuous, high-dimensional numerical data. However, the number of clusters in the given dataset must be predetermined for this technique, and choosing the right K is frequently challenging. The cluster centers chosen in the first phase have an impact on the clustering results as well. To overcome this drawback in k-means to modify the initialization and centroid steps in classification technique with combining (Convolutional neural network) CNN and ELM (extreme learning machine) technique is used. To increase this work, disease risk prediction using repository dataset is proposed. We use different types of machine learning algorithm for predicting disease using structured data. The prediction accuracy of using proposed hybrid model is 99.8% which is more than SVM (support vector machine), KNN (k-nearest neighbors), AB (AdaBoost algorithm) and CKN-CNN (consensus K-nearest neighbor algorithm and convolution neural network)

Introduction to Analyzing and Evaluating Medical Terminology

Illinois CTE Endorsement Area: Health Science Technology & Human Services Teacher and Student Editionshttps://digitalcommons.imsa.edu/books/1001/thumbnail.jp

Trust Deficit in Surgical Systems in an Urban Slum in India Under Universal Health Coverage: A Mixed Method Study

Objectives: We carried out a mixed method study to understand why patients did not avail of surgical care in an urban slum in India. Methods: In our earlier study, we found that out of 10,330 people, 3.46% needed surgery; 42% did not avail of surgery (unmet needs). We conducted a follow-up study to understand reasons for not availing surgery, 141 in met needs, 91 in unmet needs. We administered 2 instruments, 16 in-depth interviews and 1 focused group discussion. Results: Responses from the 2 groups for “the Socio-culturally Competent Trust in Physician Scale for a Developing Country Setting” scale did not have significant difference except for, prescription of medicines, patients with unmet needs were less likely to agree (p = 0.076). Results between 2 groups regarding “Patient perceptions of quality” did not show significant difference except for doctors answering questions where a higher proportion of unmet need group agreed (p = 0.064). Similar observations were made in the in depth interviews and focus group. Conclusion: There is a need for understanding trust issues with health service delivery related to surgical care for marginalized populations

Integrated multisectoral strategy to improve girls' and women's nutrition before conception, during pregnancy and after birth in India (Swabhimaan): protocol for a prospective, non-randomised controlled evaluation

INTRODUCTION: Swabhimaan is a community-based programme to improve adolescent girls’ and women’s nutrition in the rural areas of three Indian states—Bihar, Chhattisgarh and Odisha with high prevalence of undernutrition. METHODS AND ANALYSIS: Swabhimaan has a nested prospective, non-randomised controlled evaluation. Since 2017, five intervention sites receive community-led interventions through national government’s livelihood mission supported women’s self-help group federations and five control sites will initiate these activities 36 months later, in 2020. Community-led activities aim to improve coverage of 18 interventions including adequacy of food consumed, prevention of micronutrient deficiencies, access to basic health services and special care of nutritionally ‘at risk’ girls and women, improving hygiene and access to water and sanitation services and access to family planning services. The evaluation includes baseline (2016–2017), midline (2018–2019) and endline (2020–2021) surveys covering 6638 adolescent girls, 2992 pregnant women and 8755 mothers of children under 2. The final impact analysis will be by intention to treat, comparing primary and secondary outcomes in five intervention areas and five control areas. The primary outcomes are: (1) a 15% reduction in the proportion of adolescent girls with a body mass index (BMI) <18.5 kg/m2; (2) a 15% reduction in the proportion of mothers of children under two with a BMI <18.5 kg/m2 and (3) and a 0.4 cm improvement in mean mid-upper arm circumference among pregnant women. ETHICS AND DISSEMINATION: All procedures involving human subjects were approved by the Institutional Ethics Committee of the All India Institute of Medical Sciences, Bihar, Chhattisgarh and Odisha and in compliance with guidelines laid down in the Declaration of Helsinki. Evidence will inform maternal and preconception nutrition policy at national and state level. TRIAL REGISTRATION NUMBER: 58261b2f46876 and CTRI/2016/11/007482; Pre-results

Immunomagnetic microbeads for screening with flow cytometry and identification with nano-liquid chromatography mass spectrometry of ochratoxins in wheat and cereal

Multi-analyte binding assays for rapid screening of food contaminants require mass spectrometric identification of compound(s) in suspect samples. An optimal combination is obtained when the same bioreagents are used in both methods; moreover, miniaturisation is important because of the high costs of bioreagents. A concept is demonstrated using superparamagnetic microbeads coated with monoclonal antibodies (Mabs) in a novel direct inhibition flow cytometric immunoassay (FCIA) plus immunoaffinity isolation prior to identification by nano-liquid chromatography–quadrupole time-of-flight-mass spectrometry (nano-LC-Q-ToF-MS). As a model system, the mycotoxin ochratoxin A (OTA) and cross-reacting mycotoxin analogues were analysed in wheat and cereal samples, after a simple extraction, using the FCIA with anti-OTA Mabs. The limit of detection for OTA was 0.15 ng/g, which is far below the lowest maximum level of 3 ng/g established by the European Union. In the immunomagnetic isolation method, a 350-times-higher amount of beads was used to trap ochratoxins from sample extracts. Following a wash step, bound ochratoxins were dissociated from the Mabs using a small volume of acidified acetonitrile/water (2/8 v/v) prior to separation plus identification with nano-LC-Q-ToF-MS. In screened suspect naturally contaminated samples, OTA and its non-chlorinated analogue ochratoxin B were successfully identified by full scan accurate mass spectrometry as a proof of concept for identification of unknown but cross-reacting emerging mycotoxins. Due to the miniaturisation and bioaffinity isolation, this concept might be applicable for the use of other and more expensive bioreagents such as transport proteins and receptors for screening and identification of known and unknown (or masked) emerging food contaminants