Model Development and Validation of Personal Exposure to Volatile Organic Compound Concentrations

Background: Direct measurement of exposure to volatile organic compounds (VOCs) via personal monitoring is the most accurate exposure assessment method available. However, its wide-scale application to evaluating exposures at the population level is prohibitive in terms of both cost and time. Consequently, indirect measurements via a combination of microenvironment concentrations and personal activity diaries represent a potentially useful alternative. Objective: The aim of this study was to optimize a model of personal exposures (PEs) based on microenvironment concentrations and time/activity diaries and to compare modeled with measured exposures in an independent data set. Materials: VOC PEs and a range of microenvironment concentrations were collected with active samplers and sorbent tubes. Data were supplemented with information collected through questionnaires. Seven models were tested to predict PE to VOCs in 75% (n = 370) of the measured PE data set, whereas the other 25% (n = 120) was used for validation purposes. Results: The best model able to predict PE with independence of measurements was based upon stratified microenvironment concentrations, lifestyle factors, and individual-level activities. The proposed model accounts for 40–85% of the variance for individual VOCs and was validated for almost all VOCs, showing normalized mean bias and mean fractional bias below 25% and predicting 60% of the values within a factor of 2. Conclusions: The models proposed identify the most important non-weather-related variables for VOC exposures; highlight the effect of personal activities, use of solvents, and exposure to environmental tobacco smoke on PE levels; and may assist in the development of specific models for other locations.peer-reviewe

Transition between child and adult services for young people with ADHD: findings from a British national surveillance study

This is the author accepted manuscript. The final version is available from Cambridge University Press via the DOI in this record.Data Availability: Data is currently stored securely by the University of Exeter Medical School, under embargo until the end of the CATCh-uS project (2019).Background: Optimal transition involves continuity, joint care, planning meetings and information transfer. To plan services, commissioners and service providers need data on how many people require that service. Although Attention-Deficit/Hyperactivity Disorder (ADHD) frequently persists into adulthood, evidence is limited on transitions between child and adult services. Aims: To estimate the national incidence of young people taking medication for ADHD that require and complete transition, and describe the proportion that experienced optimal transition. Methods: Surveillance over twelve months using the British Paediatric Surveillance Unit and the Child and Adolescent Psychiatry Surveillance System, including baseline notification and follow up questionnaires. Results: Questionnaire response was 79% at baseline and 82% at follow up. For cases aged 17-19, incident rate (range adjusted for non-response) of transition need was 202-511 per 100,000 people aged 17-19 per year, with successful transition of 38-96 per 100,000 people aged 17-19 per year. Cases were mostly male (77%) with a comorbid condition (62%). Half were referred to specialist adult ADHD and 25% to general adult mental health services; 64% had referral accepted but only 22% attended a first appointment. Only 6% met optimal transition criteria. Conclusions: As inclusion criteria required eligible cases to be on medication, these estimates will represent the lower limit of the need for transition. Two critical points were apparent; referral acceptance and first appointment attendance. The low rate of successful transition and limited guideline adherence indicates significant need for commissioners and service providers to improve service transition experiences.National Institute for Health Research (NIHR

Prediction of the yield of grains through artificial intelligence

Grass turns out to be an appropriate food for cattle, mainly in tropical climate countries such as Latin American countries. This is due to the high number of species that can be used, the possibility of growing them year-round, the ability of the ruminant to use fibrous supplies and be an economic source (Sánchez et al., Data mining and big data. DMBD 2018. Lecture notes in computer science, vol 10943. Springer, Cham, 2018, [1]). In this work, an application of neural networks was carried out in the forecasting of more accurate values of production and quality of grasslands

Using zeta-potential measurements to quantify peptide partition to lipid membranes

© The Author(s) 2011. This article is published with open access at Springerlink.com.Open Access: This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.Many cellular phenomena occur on the biomembranes. There are plenty of molecules (natural or xenobiotics) that interact directly or partially with the cell membrane. Biomolecules, such as several peptides (e.g., antimicrobial peptides) and proteins, exert their effects at the cell membrane level. This feature makes necessary investigating their interactions with lipids to clarify their mechanisms of action and side effects necessary. The determination of molecular lipid/water partition constants (Kp) is frequently used to quantify the extension of the interaction. The determination of this parameter has been achieved by using different methodologies, such as UV-Vis absorption spectrophotometry, fluorescence spectroscopy and ζ-potential measurements. In this work, we derived and tested a mathematical model to determine the Kp from ζ-potential data. The values obtained with this method were compared with those obtained by fluorescence spectroscopy, which is a regular technique used to quantify the interaction of intrinsically fluorescent peptides with selected biomembrane model systems. Two antimicrobial peptides (BP100 and pepR) were evaluated by this new method. The results obtained by this new methodology show that ζ-potential is a powerful technique to quantify peptide/lipid interactions of a wide variety of charged molecules, overcoming some of the limitations inherent to other techniques, such as the need for fluorescent labeling.This work was partially supported by project PTDC/QUI/ 69937/2006 from Fundação para a Ciência e Tecnologia-Ministério da Ciência, Tecnologia e Ensino Superior (FCT-MCTES, Portugal), and by Fundação Calouste Gulbenkian (Portugal). JMF and MMD also thank FCT-MCTES for grants IMM/BT/37-2010 and SFRH/BD/41750/2007, respectively

An Assessment of Students’ Satisfaction in Higher Education

Student’s Satisfaction (SS) with a particular subject may impact the learning process, being the figure of attentiveness of the utmost importance over time, and also a very difficult undertaking to accomplish. To go forward with such exercise, a workable methodology for problem solving had to be built and tested. It is based on a thermodynamic approach to Knowledge Representation and Reasoning, which is the ultimate goal of SS assessment when working on a particular topic

A precision study of the fine tuning in the DiracNMSSM

Recently the DiracNMSSM has been proposed as a possible solution to reduce the fine tuning in supersymmetry. We determine the degree of fine tuning needed in the DiracNMSSM with and without non-universal gaugino masses and compare it with the fine tuning in the GNMSSM. To apply reasonable cuts on the allowed parameter regions we perform a precise calculation of the Higgs mass. In addition, we include the limits from direct SUSY searches and dark matter abundance. We find that both models are comparable in terms of fine tuning, with the minimal fine tuning in the GNMSSM slightly smaller.Comment: 20 pages + appendices, 10 figure

Extending colonic mucosal microbiome analysis - Assessment of colonic lavage as a proxy for endoscopic colonic biopsies

This study was supported through GI Research funds and MRC Grant Ref: MR/M00533X/1 to GH.Peer reviewedPublisher PD

Design and validation of a three-instrument toolkit for the assessment of competence in electrocardiogram rhythm recognition

Background: Rapid and accurate interpretation of cardiac arrhythmias by nurses has been linked with safe practice and positive patient outcomes. Although training in electrocardiogram (ECG) rhythm recognition is part of most undergraduate nursing programmes, research continues to suggest that nurses and nursing students lack competence in recognising cardiac rhythms. In order to promote patient safety, nursing educators must develop valid and reliable assessment tools that allow the rigorous assessment of this competence before nursing students are allowed to practise without supervision. Aim: To develop and psychometrically evaluate a toolkit to holistically assess competence in ECG rhythm recognition. Methods: Following a convenience sampling technique, 293 nursing students from a nursing faculty in a Spanish university were recruited for the study. The following three instruments were developed and psychometrically tested: a knowledge assessment tool (ECG-KAT), a skills assessment tool (ECG-SAT) and a self-efficacy assessment tool (ECG-SES). Reliability and validity (content, criterion and construct) of these tools were meticulously examined. Results: A high Cronbach’s alpha coefficient demonstrated the excellent reliability of the instruments (ECG-KAT=0.89; ECG-SAT=0.93; ECG-SES=0.98). An excellent context validity index (S-CVI/Ave>0.94) and very good criterion validity were evidenced for all the tools. Regarding construct validity, principal component analysis revealed that all items comprising the instruments contributed to measure knowledge, skills or self-efficacy in ECG rhythm recognition. Moreover, known-groups analysis showed the tools’ ability to detect expected differences in competence between groups with different training experiences. Conclusion: The three-instrument toolkit developed showed excellent psychometric properties for measuring competence in ECG rhythm recognition

The Goal Programming as a Tool for Measuring the Sustainability of Agricultural Production Chains of Rice

Agricultural activity is characterized by an intensive use of capital and a considerable dependence on external financing. Access to credit is often limited by the scarcity of resources and lack of guarantees, seriously affecting the productivity and economic performance of agricultural exploitations. The objective of this paper is to assess the sustainability of agricultural production chain of rice in Latin America using multi-criteria analysis tools to facilitate decision-making through a benchmarking process to contribute to their economic sustainability. The implementation of the model in an exploitation typy depending on financing sources (conservative, intermediate, and innovative) has revealed the conflict between the goals, being the intermediate exploitation, which gets the best results. The conclusions show that the flexibilization of financing options positively affects the economic performance