On The Finite-Sample Performance Of The Nearest-Neighbor Classifier

The finite sample performance of a nearest neighbor classifier is analyzed for a two-class pattern recognition problem. An exact integral expression is derived for the m-sample risk R(m) given that a reference m-sample of labeled points is available to the classifier. The statistical setup assumes that the pattern classes arise in nature with fixed a priori probabilities and that points representing the classes are drawn from Euclidean n-space according to fixed class-conditional probability distributions. The sample is assumed to consist of m independently generated class-labeled points. For a family of smooth class-conditional distributions characterized by asymptotic expansions in general form, it is shown that the m-sample risk R(m) has a complete asymptotic series expansio

Conservation and divergence of protein pathways in the vertebrate heart

Heart disease is the leading cause of death in the western world. Attaining a mechanistic understanding of human heart development and homeostasis and the molecular basis of associated disease states relies on the use of animal models. Here, we present the cardiac proteomes of 4 model vertebrates with dual circulatory systems: the pig (Sus scrofa), the mouse (Mus musculus), and 2 frogs (Xenopus laevis and Xenopus tropicalis). Determination of which proteins and protein pathways are conserved and which have diverged within these species will aid in our ability to choose the appropriate models for determining protein function and to model human disease. We uncover mammalian- and amphibian-specific, as well as species-specific, enriched proteins and protein pathways. Among these, we find and validate an enrichment in cell-cycle–associated proteins within Xenopus laevis. To further investigate functional units within cardiac proteomes, we develop a computational approach to profile the abundance of protein complexes across species. Finally, we demonstrate the utility of these data sets for predicting appropriate model systems for studying given cardiac conditions by testing the role of Kielin/chordin-like protein (Kcp), a protein found as enriched in frog hearts compared to mammals. We establish that germ-line mutations in Kcp in Xenopus lead to valve defects and, ultimately, cardiac failure and death. Thus, integrating these findings with data on proteins responsible for cardiac disease should lead to the development of refined, species-specific models for protein function and disease states

Acceptance and Use of E-Learning Based on Cloud Computing: The Role of Consumer Innovativeness

Cloud computing and E-learning are the inevitable trend of computational science in general, and information systems and technologies in specific.However, there are not many studies on the adoption of cloud-based E-learning systems. Moreover, while there are many papers on information system adoption as well as customer innovativeness, the innovativeness and adoption in the same model seems to be rare in the literature. The study combines the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and consumer innovativeness on the adoption of E-learning systems based on cloud computing. A survey was conducted among 282 cloud-based E-learning participants and analyzed by structural equation modeling (SEM). The findings indicate that the adoption of cloud-based E-learning is influenced by performance expectancy, social influence, hedonic motivation, and habit. Interestingly, although innovativeness is not significant to use intention, it has a positive effect on E-learning usage which is relatively new in Vietnam

Examining Contextual Factors and Individual Value Dimensions of Healthcare Providers Intention to Adopt Electronic Health Technologies in Developing Countries

Part 5: Research in ProgressInternational audienceDespite substantial research on electronic health (e-Health) adoption, there still exist vast differences between resource-rich and resource-poor populations regarding Information Technology adoption. To help bridge the technological gulf between developed and developing countries, this research-in-progress paper examines healthcare providers’ intention to adopt e-health technologies from two perspectives 1) contextual factors (i.e. specific to developing world settings) and 2) individual value dimensions (i.e. cultural, utilitarian, social and personal). The primary output of this paper is a theoretical model merging both the contextual factors and value dimensions; this forms a strong baseline to examine and help ensure the successful adoption of e-Health technologies within developing countries. Future research will be performed to validate the model developed in this paper, with a specific focus on mobile Health in Malawi, Africa

Loss-of-function mutations in UDP-Glucose 6-Dehydrogenase cause recessive developmental epileptic encephalopathy

Developmental epileptic encephalopathies are devastating disorders characterized by intractable epileptic seizures and developmental delay. Here, we report an allelic series of germline recessive mutations in UGDH in 36 cases from 25 families presenting with epileptic encephalopathy with developmental delay and hypotonia. UGDH encodes an oxidoreductase that converts UDP-glucose to UDP-glucuronic acid, a key component of specific proteoglycans and glycolipids. Consistent with being loss-of-function alleles, we show using patients’ primary fibroblasts and biochemical assays, that these mutations either impair UGDH stability, oligomerization, or enzymatic activity. In vitro, patient-derived cerebral organoids are smaller with a reduced number of proliferating neuronal progenitors while mutant ugdh zebrafish do not phenocopy the human disease. Our study defines UGDH as a key player for the production of extracellular matrix components that are essential for human brain development. Based on the incidence of variants observed, UGDH mutations are likely to be a frequent cause of recessive epileptic encephalopathy

The burden of unintentional drowning: Global, regional and national estimates of mortality from the Global Burden of Disease 2017 Study

__Background:__ Drowning is a leading cause of injury-related mortality globally. Unintentional drowning (International Classification of Diseases (ICD) 10 codes W65-74 and ICD9 E910) is one of the 30 mutually exclusive and collectively exhaustive causes of injury-related mortality in the Global Burden of Disease (GBD) study. This study's objective is to describe unintentional drowning using GBD estimates from 1990 to 2017. __Methods:__ Unintentional drowning from GBD 2017 was estimated for cause-specific mortality and years of life lost (YLLs), age, sex, country, region, Socio-demographic Index (SDI) quintile, and trends from 1990 to 2017. GBD 2017 used standard GBD methods for estimating mortality from drowning. __Results:__ Globally, unintentional drowning mortality decreased by 44.5% between 1990 and 2017, from 531 956 (uncertainty interval (UI): 484 107 to 572 854) to 295 210 (284 493 to 306 187) deaths. Global age-standardised mortality rates decreased 57.4%, from 9.3 (8.5 to 10.0) in 1990 to 4.0 (3.8 to 4.1) per 100 000 per annum in 2017. Unintentional drowning-associated mortality was generally higher in children, males and in low-SDI to middle-SDI countries. China, India, Pakistan and Bangladesh accounted for 51.2% of all drowning deaths in 2017. Oceania was the region with the highest rate of age-standardised YLLs in 2017, with 45 434 (40 850 to 50 539) YLLs per 100 000 across both sexes. __Conclusions:__ There has been a decline in global drowning rates. This study shows that the decline was not consistent across countries. The results reinforce the need for continued and improved policy, prevention and research efforts, with a focus on low-and middle-income countries