Elite Triathlete Profiles in Draft-Legal Triathlons as a Basis for Talent Identification

Draft-legal triathlons are the main short-distance races worldwide and are those on which talent-identification programs are usually focused. Performance in these races depends on multiple factors; however, many investigations do not focus on elite triathletes. Therefore, the aim of this narrative review was to carry out a systematic literature search to define the elite female and male triathlete profiles and their competition demands in draft-legal triathlons. This will allow us to summarize the main determinant factors of high-level triathletes as a basis for talent detection. A comprehensive review of Web of Science and Scopus was performed using the search strategy: Triathl* and (performance or competition or profile) and (elite or professional or “high performance” or “high level” or talent). A total of 1325 research documents were obtained, and after screening following the criteria, only 83 articles were selected. After data synthesis, elite triathlete aspects such as age, physiological, anthropometric, and psychosocial profile or competition demands were studied in the scientific literature. Thus, it is essential that when implementing talent identification programs, these factors must be considered. However, constant updating is needed due the continuous regulatory changes and the need of triathletes to adapt to these new competition demands.

Neuromuscular Excercise in Children with Down Syndrome. A Systematic Review

Objective to evaluate the effects of neuromuscular exercise, specifying the parameters and characteristics of effective interventions to improve balance, muscle strength and flexibility in children with DS between the ages of 4 and 18 years. Data Sources: A search was carried out on PubMed, PEDro, EMBASE, SCIELO, Lilacs, Cochrane library. Study Selection: The search yielded 1384 eligible articles. Randomized clinical trials were selected, and that would have reported the effectiveness in the outcomes. Data Extraction: The methodology and results of the studies were critically appraised in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes guidelines. Data Synthesis: Ten studies were included. The interventions included mechanotherapy, vibration, and use of different unstable surfaces. The exercise frequency ranged from three days to five days a week, and the duration of each session was between six and 15 minutes. The frequency was between two and three times a week for 6 and 12 weeks and the intensity was between 60% and 80% of maximum resistance (MR). Conclusion neuromuscular exercise appears to be effective for the improvement of both lower limb and chest muscle strength and balance in children over 8 years of age.

Designing the physical environment for inpatient palliative care: a narrative review

BackgroundIt is essential that the physical environments in which inpatient palliative care is provided support the needs of patients and the facilitate the multidimensional delivery of palliative care. This review aims to identify the features and characteristics of inpatient palliative care environments that enhance or detract from the patient experience; and identify opportunities for progress within this field.MethodThree databases were searched: MEDLINE (1946–2020), PsycINFO (1806–2020) and CINAHL (1937–2020). Articles were screened by title and abstract with included studies read in full for data extraction. Data synthesis involved thematic analysis informed by the findings of the included literature. Inclusion criteria were studies with empirical methodology examining adult palliative care in the hospital, hospice or nursing home environment. Studies that examined palliative care delivered within the emergency department, ICU or within the home were excluded, as were those related to paediatric palliative care.ResultsFour main themes were identified: the provision of privacy, facilitating interactions with family, facilitating comfort through homeliness and connections to nature.ConclusionsThe board acceptance of single rooms as the preeminent design solution for supporting privacy, dignity and family interaction, alongside current conceptions of homeliness that typically focus on matters of interior design, are limiting possibilities for further design innovation within palliative care settings. Research that investigates a broader set of design strategies through which the built environment can support care, alongside enhanced interdisciplinary collaboration, could positively contribute to patient and family experiences of inpatient palliative care.

HeartNet: Self Multi-Head Attention Mechanism via Convolutional Network with Adversarial Data Synthesis for ECG-based Arrhythmia Classification

Cardiovascular disease is now one of the leading causes of morbidity and mortality in humans. Electrocardiogram (ECG) is a reliable tool for monitoring the health of the cardiovascular system. Currently, there has been a lot of focus on accurately categorizing heartbeats. There is a high demand on automatic ECG classification systems to assist medical professionals. In this paper we proposed a new deep learning method called HeartNet for developing an automatic ECG classifier. The proposed deep learning method is compressed by multi-head attention mechanism on top of CNN model. The main challenge of insufficient data label is solved by adversarial data synthesis adopting generative adversarial network (GAN) with generating additional training samples. It drastically improves the overall performance of the proposed method by 5-10% on each insufficient data label category. We evaluated our proposed method utilizing MIT-BIH dataset. Our proposed method has shown 99.67 ± 0.11 accuracy and 89.24 ± 1.71 MCC trained with adversarial data synthesized dataset. However, we have also utilized two individual datasets such as Atrial Fibrillation Detection Database and PTB Diagnostic Database to see the performance of our proposed model on ECG classification. The effectiveness and robustness of proposed method are validated by extensive experiments, comparison and analysis. Later on, we also highlighted some limitations of this work.

Reviews and syntheses: The promise of big soil data, moving current practices towards future potential

In the age of big data, soil data are more available than ever, but -outside of a few large soil survey resources- remain largely unusable for informing soil management and understanding Earth system processes outside of the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for global relevance. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: data discovery, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.