Learning to classify software defects from crowds: a novel approach

In software engineering, associating each reported defect with a cate- gory allows, among many other things, for the appropriate allocation of resources. Although this classification task can be automated using stan- dard machine learning techniques, the categorization of defects for model training requires expert knowledge, which is not always available. To cir- cumvent this dependency, we propose to apply the learning from crowds paradigm, where training categories are obtained from multiple non-expert annotators (and so may be incomplete, noisy or erroneous) and, dealing with this subjective class information, classifiers are efficiently learnt. To illustrate our proposal, we present two real applications of the IBM’s or- thogonal defect classification working on the issue tracking systems from two different real domains. Bayesian network classifiers learnt using two state-of-the-art methodologies from data labeled by a crowd of annotators are used to predict the category (impact) of reported software defects. The considered methodologies show enhanced performance regarding the straightforward solution (majority voting) according to different metrics. This shows the possibilities of using non-expert knowledge aggregation techniques when expert knowledge is unavailable

Electrical properties of individual tin oxide nanowires contacted to platinum electrodes

A simple and useful experimental alternative to field-effect transistors for measuring electrical properties free electron concentration nd, electrical mobility , and conductivity in individual nanowires has been developed. A combined model involving thermionic emission and tunneling through interface states is proposed to describe the electrical conduction through the platinum-nanowire contacts, fabricated by focused ion beam techniques. Current-voltage I-V plots of single nanowires measured in both two- and four-probe configurations revealed high contact resistances and rectifying characteristics. The observed electrical behavior was modeled using an equivalent circuit constituted by a resistance placed between two back-to-back Schottky barriers, arising from the metal-semiconductor-metal M-S-M junctions. Temperature-dependent I-V measurements revealed effective Schottky barrier heights up to BE= 0.4 eV

Design and psychometric evaluation of the 'Clinical Communication Self-Efficacy Toolkit'

Nursing students experience difficulties when communicating in clinical practice. Their self-efficacy in clinical communication should be explored as part of their competence assessment before they are exposed to real human interactions in the clinical setting. The aim of this study was to design and psychometrically evaluate a toolkit to comprehensively assess nursing students’ self-efficacy in clinical communication. The study followed an observational cross-sectional design. A sample of 365 nursing students participated in the study. The ‘Clinical Communication Self-Efficacy Toolkit’ (CC-SET) was comprised of three tools: the ‘Patient-Centered Communication Self-efficacy Scale’ (PCC-SES), the ‘Patient clinical Information Exchange and interprofessional communication Self-Efficacy Scale’ (PIE-SES), and the ‘Intrapersonal communication and Self-Reflection Self-Efficacy Scale’ (ISR-SES). The tools’ reliability, validity (content, criterion, and construct) and usability were rigorously tested. The Cronbach’s alpha coefficient of the three tools comprising the CC-SET was very high and demonstrated their excellent reliability (PCC-SES = 0.93; PIE-SES = 0.87; ISR-SES = 0.86). The three tools evidenced to have excellent content validity (scales’ content validity index > 0.95) and very good criterion validity. Construct validity analysis demonstrated that the PCC-SES, PIE-SES, and ISR-SES have a clear and theoretically-congruent structure. The CC-SET is a comprehensive toolkit that allows the assessment of nursing students’ self-efficacy in interpersonal, interprofessional, and intrapersonal communication

Influenza vaccination among multiple sclerosis patients during the COVID-19 pandemic

In the context of the COVID-19 pandemic, the co-circulation of influenza and SARS-CoV-2 viruses may have severe complications for vulnerable populations. For this reason, the World Health Organization pointed to the 2020–2021 anti-influenza campaign as being of special relevance. Our aim was to assess the 2020–2021 influenza vaccination coverage, and its associated factors, among patients in a Spanish multiple sclerosis (MS) unit. A cross–sectional study was conducted. People attending the MS unit of the Clinical Hospital of Zaragoza during 2020 were included. Variables were obtained by reviewing records. Associations with 2020–2021 influenza vaccination were analyzed using bivariate analysis and a multiple logistic regression model. A total of 302 patients were studied; 62.6% were women, whose mean age (standard deviation) was 47.3 (11.5) years. The 2020–2021 influenza vaccination coverage was 55.3% (59.8% in women and 47.8% in men). A total of 89.7% had at least one other indication for vaccination (e.g., immunosuppressive treatment in 225 patients). The variables associated with getting vaccinated were being female (adjusted odds ratio (95% confidence interval) (aOR (95%CI) = 2.12 (1.12–3.99)), having received the 2019–2020 influenza vaccine (aOR (95%CI) = 31.82 (14.71–68.86)) and being born in Spain (aOR (95%CI) = 12.91 (1.07–156.28)). Coverage is moderate compared to other countries. It is necessary to develop strategies to improve it, especially in men and those born outside Spain

Experiences of mothers of extremely preterm infants after hospital discharge

The purpose of this study was to describe and understand the experiences of mothers of extremely preterm infants during the first twelve months at home following discharge from a neonatal intensive care unit. A qualitative, interpretative approach using Gadamer's philosophical hermeneutics was carried out. One focus group and fifteen in-depth, semi-structured interviews were conducted twelve months after hospital discharge. Responses were recorded, transcribed and analyzed using computer-assisted qualitative data analysis. The study´s participants were twenty women. The following themes emerged from the data analysis: 1) 'The journey home: the discharge process', which included the sub-themes 'escaping the hospital environment: between desire and fear' and 'preparing parents for hospital discharge: practice and formal support'; and 2) 'The difficulty of living with an extremely preterm infant', including the sub-themes 'the challenge of an unexpected form of childcare', 'overprotection of and bond with a child with special needs' and 'disturbance in the social/familiar setting: when a mother becomes a nurse'. The process of hospital discharge and the first months at home are difficult. The birth and care of an extremely preterm infant affect the mothers' quality of life as well as their family and social life. Practice and early discharge programmes can make the discharge process easier. The knowledge and understanding of the experience of mothers of extremely preterm infants in the first months at home after hospital discharge could help healthcare professionals to develop educational strategies and counselling interventions in accordance with the mothers' needs. [Abstract copyright: Copyright © 2018 Elsevier Inc. All rights reserved.

Influenza vaccination coverage among multiple sclerosis patients: evolution over time and associated factors

Our objective was to determine the influenza vaccination rate in a Spanish cohort of multiple sclerosis (MS) patients. A retrospective cohort study was carried out. Patients who attended the MS unit of the Lozano Blesa Hospital of Zaragoza between January 2015 and 2020 were included. The variables were obtained by reviewing the specialized and primary care records. Associations between receiving the vaccine in each flu season and the other variables were analyzed using bivariate analysis and multiple logistic regression models. A total of 260 patients were studied, with a median age of 31 years at the time of diagnosis. A total of 62.3% (162/260) were women. Vaccination coverage ranged from 20.4% in the 2015–2016 and 2016–2017 seasons to 41.5% in the 2019–2020 season (p = 0.000). Having been vaccinated in the previous season (ORa: 16.47–390.22; p = 0.000) and receiving a vaccination recommendation from the hospital vaccination unit (ORa: 2.44–3.96; p < 0.009) were associated with being vaccinated. The coverage is in an intermediate position compared to other countries. It is necessary to improve the referral system of these patients to the hospital vaccination unit because the information obtained by this service contributed to higher vaccination rates

Examination of the Feynman-Hibbs Approach in the Study of NeN_N-Coronene Clusters at Low Temperatures

Feynman-Hibbs (FH) effective potentials constitute an appealing approach for investigations of many-body systems at thermal equilibrium since they allow us to easily include quantum corrections within standard classical simulations. In this work we apply the FH formulation to the study of Ne$_N$-coronene clusters ($N=$ 1-4, 14) in the 2-14 K temperature range. Quadratic (FH2) and quartic (FH4) contributions to the effective potentials are built upon Ne-Ne and Ne-coronene analytical potentials. In particular, a new corrected expression for the FH4 effective potential is reported. FH2 and FH4 cluster energies and structures -obtained from energy optimization through a basin-hoping algorithm as well as classical Monte Carlo simulations- are reported and compared with reference path integral Monte Carlo calculations. For temperatures $T> 4$ K, both FH2 and FH4 potentials are able to correct the purely classical calculations in a consistent way. However, the FH approach fails at lower temperatures, especially the quartic correction. It is thus crucial to assess the range of applicability of this formulation and, in particular, to apply the FH4 potentials with great caution. A simple model of $N$ isotropic harmonic oscillators allows us to propose a means of estimating the cut-off temperature for the validity of the method, which is found to increase with the number of atoms adsorbed on the coronene molecule

Design and psychometric analysis of the COVID-19 prevention, recognition and home-management self-efficacy scale

In order to control the spread of COVID-19, people must adopt preventive behaviours that can affect their day-to-day life. People’s self-efficacy to adopt preventive behaviours to avoid COVID-19 contagion and spread should be studied. The aim of this study was to develop and psychometrically test the COVID-19 prevention, detection, and home-management self-efficacy scale (COVID-19-SES). We conducted an observational cross-sectional study. Six-hundred and seventy-eight people participated in the study. Data were collected between March and May 2020. The COVID-19-SES’ validity (content, criterion, and construct), reliability (internal consistency and test-retest reliability), and legibility were studied. The COVID-19-SES’ reliability was high (Cronbach’s alpha = 0.906; intraclass correlation coefficient = 0.754). The COVID-19-SES showed good content validity (scale’s content validity index = 0.92) and good criterion validity when the participants’ results on the COVID-19-SES were compared to their general self-efficacy (r = 0.38; p 0.001). Construct validity analysis revealed that the COVID-19-SES’ three-factor structure explained 52.12% of the variance found and it was congruent with the World Health Organisation’s recommendations to prevent COVID-19 contagion and spread. Legibility analysis showed that the COVID-19-SES is easy to read and understand by laypeople. The COVID-19-SES is a psychometrically robust instrument that allows for a valid and reliable assessment of people’s self-efficacy in preventing, detecting symptoms, and home-managing COVID-19