1,720,972 research outputs found
Resilience dimensions in health system performance assessments, European Union
Full text linkObjective: To explore the definition and operationalization of resilience in health system performance assessments in European Union countries. Methods: We conducted multiple empirical case study analyses. We identified relevant cases through a literature review from 2014 to 2023 using Google Scholar and through a snowball technique to retrieve additional information. We included only documents that explicitly mentioned resilience in health system performance assessments. We performed a content analysis to identify common patterns in defining resilience. Findings: The final sample consisted of six countries: Belgium, Croatia, Czechia, Estonia, Ireland and Italy. Each country adopted a distinct approach to conceptualizing resilience, with countries prioritizing specific aspects based on lessons learnt from the coronavirus disease 2019 (COVID-19) pandemic. Some countries focused on maintaining essential health-care services and protecting vulnerable groups. Other countries prioritized management capacity, staff preparedness, digital health utilization and strengthening of primary health care. Content analysis revealed six resilience definitions derived from the key performance indicators: addressing unmet needs and maintaining outcomes; protecting vulnerable groups; acquiring and using resources; having trained and prepared staff in place; using digital health; and strengthening primary health care. Conclusion: Integration of resilience into the health profiles of European Union countries preceded its inclusion in national health system performance assessments, the latter of which became more prominent after the COVID-19 pandemic. Variations in interpretations within health system performance assessments reflect differences in indicators and policy responses
SwimmerNET: Underwater 2D Swimmer Pose Estimation Exploiting Fully Convolutional Neural Networks
Full text linkProfessional swimming coaches make use of videos to evaluate their athletes’ performances. Specifically, the videos are manually analyzed in order to observe the movements of all parts of the swimmer’s body during the exercise and to give indications for improving swimming technique. This operation is time-consuming, laborious and error prone. In recent years, alternative technologies have been introduced in the literature, but they still have severe limitations that make their correct and effective use impossible. In fact, the currently available techniques based on image analysis only apply to certain swimming styles; moreover, they are strongly influenced by disturbing elements (i.e., the presence of bubbles, splashes and reflections), resulting in poor measurement accuracy. The use of wearable sensors (accelerometers or photoplethysmographic sensors) or optical markers, although they can guarantee high reliability and accuracy, disturb the performance of the athletes, who tend to dislike these solutions. In this work we introduce swimmerNET, a new marker-less 2D swimmer pose estimation approach based on the combined use of computer vision algorithms and fully convolutional neural networks. By using a single 8 Mpixel wide-angle camera, the proposed system is able to estimate the pose of a swimmer during exercise while guaranteeing adequate measurement accuracy. The method has been successfully tested on several athletes (i.e., different physical characteristics and different swimming technique), obtaining an average error and a standard deviation (worst case scenario for the dataset analyzed) of approximately 1 mm and 10 mm, respectively
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Detection of microplastics in fish using computed tomography and deep learning
No full textMarine organisms have been observed ingesting microplastic particles, with field analyses indicating fibers and fragments as prevalent forms. Current microplastic detection methods are mainly time-consuming, susceptible to cross-contamination, and expensive. Furthermore, these techniques, being disruptive, do not allow for the exact localization of the microplastic in the sample. This study proposes a new approach using Computed Tomography (CT scan) and Artificial Intelligence for the automatic and non-destructive detection of microplastics in fishes and other species based on the combination of several factors, such as density and shape. The advantages of this methodology include accurate identification of plastic localization, a low risk of cross-contamination, rapid processing, automatic tomographic measurement, efficient data processing, cost-effectiveness, and a high cost-benefit ratio. The herein results highlight how artificial intelligence applied to conventional techniques can significantly improve precision and efficiency in microplastic research. Indeed, the semantic segmentation model clearly recognized the presence of 100 % of the plastic particles, both in their location and in their volume, accelerating the identification process and surpassing the limitations of traditional spectral analysis methodologies
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Risk and protective factors for pregnancy‐related urinary incontinence until 1 year postpartum: A cohort study using patient‐reported outcome measures in Italy
Full text linkObjective: To investigate the epidemiology of pregnancy-related urinary incontinence (UI) and the related risk factors, focusing also on women's characteristics related to maternity pathway utilization. Methods: In this prospective cohort study, we used patient-reported data obtained from the systematic survey on the maternity pathway that all pregnant women in Tuscany, Italy, can join. We selected 8410 women who completed-between March 2019 and November 2022-all five follow-up questionnaires from the first trimester until 12 months postpartum, each including a UI-specific patient-reported outcome measure. We performed panel regression models to explore the related risk factors. Results: Prevalence of UI was 4.4% at the first trimester, 23.7% at the third trimester, and 15.6%, 12.6%, and 12.4% at 3, 6, and 12 months postpartum. UI occurrence and severity were higher in older, overweight/obese, and unemployed women. High-risk pregnancy and discomfort during pregnancy were risk factors. Receiving a cesarean section reduced the risk, while spontaneous tears, episiotomy, and high birth weight increased it. Women who experienced delays in pregnancy examinations because of long waiting times and women who had planned pregnancy had a higher risk, while performing during-pregnancy pelvic-floor-muscle training was protective. Conclusion: Besides confirming the classic risk and protective factors for UI, we also found novel determinants related to the proper maternity pathway utilization
Design and Experimental Validation of a Cardiac Simulator for Prosthetic Heart Valve Evaluation
No full textContinuous innovation in medical technologies is important to address the complexities of cardiovascular diseases. This research aimed to design and experimentally validate an innovative cardiac valve simulator specifically designed to evaluate prosthetic heart valve (PHV) behavior. The simulator incorporates 3D-printed left ventricle and aorta real models, providing a controlled environment to assess PHV s. A hydraulic circuit, connected to a linear actuator, simulates the dynamic environment of the systemic circulation. The cardiac simulator allows personalized testing based on individual anatomical and physiological characteristics. Lab VIEW-based control systems ensure controlled replication of cardiac parameters. Experimen-tal results, conducted at a 1: 1 scale under resting conditions (70 bpm, 70 ml stroke volume), demonstrate the simulator's ability to replicate physiological conditions, as evidenced by pressure and flow signals at varying heart rates. Frequency analysis confirms the consistency of experimental data with theoretical predictions. Moreover, a unique feature of the realized simulator is its compact design, reducing footprint and components for improved accessibilit
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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