Processing of Synthetic Aperture Radar Images by the Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to two large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. Finally, a diffusive filling-in operation within the segmented regions produces coherent visible structures. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.Air Force Office of Scientific Research (90-0175); Defense Advanced Research Projects Agency (90-0083

Using Educational Data Mining to Identify and Analyze Student Learning Strategies

This paper explores student learning strategies in an introductory spreadsheets course. Student study habits were tracked at a level of detail not available in previous research. Detailed data were collected regarding reading, video watching, actions in practice assignments, references to assignment instructions, and actions in graded assignments. The analysis indicates that student strategies cluster into four primary learning groups. The study provides insight into how instructors can develop their courses and lectures in ways that better match the learning strategies of their students

Spatial scaling properties of coral reef benthic communities

The spatial structure of ecological communities on tropical coral reefs across seascapes and geographies have historically been poorly understood. Here we addressed this for the first time using spatially expansive and thematically resolved benthic community data collected around five uninhabited central Pacific oceanic islands, spanning 6° latitude and 17° longitude. Using towed-diver digital image surveys over ~140 linear km of shallow (8–20 m depth) tropical reef, we highlight the autocorrelated nature of coral reef seascapes. Benthic functional groups and hard coral morphologies displayed significant spatial clustering (positive autocorrelation) up to kilometre-scales around all islands, in some instances dominating entire sections of coastline. The scale and strength of these autocorrelation patterns showed differences across geographies, but patterns were more similar between islands in closer proximity and of a similar size. For example, crustose coralline algae (CCA) were clustered up to scales of 0.3 km at neighbouring Howland and Baker Islands and macroalgae were spatially clustered at scales up to ~3 km at both neighbouring Kingman Reef and Palmyra Atoll. Of all the functional groups, macroalgae had the highest levels of spatial clustering across geographies at the finest resolution of our data (100 m). There were several cases where the upper scale at which benthic community members showed evidence of spatial clustering correlated highly with the upper scales at which concurrent gradients in physical environmental drivers were spatially clustered. These correlations were stronger for surface wave energy than subsurface temperature (regardless of benthic group) and turf algae and CCA had the closest alignments in scale with wave energy across functional groups and geographies. Our findings suggest such physical drivers not only limit or promote the abundance of various benthic competitors on coral reefs, but also play a key role in governing their spatial scaling properties across seascapes

Parsing human and biophysical drivers of coral reef regimes

Coral reefs worldwide face unprecedented cumulative anthropogenic effects of interacting local human pressures, global climate change and distal social processes. Reefs are also bound by the natural biophysical environment within which they exist. In this context, a key challenge for effective management is understanding how anthropogenic and biophysical conditions interact to drive distinct coral reef configurations. Here, we use machine learning to conduct explanatory predictions on reef ecosystems defined by both fish and benthic communities. Drawing on the most spatially extensive dataset available across the Hawaiian archipelago-20 anthropogenic and biophysical predictors over 620 survey sites-we model the occurrence of four distinct reef regimes and provide a novel approach to quantify the relative influence of human and environmental variables in shaping reef ecosystems. Our findings highlight the nuances of what underpins different coral reef regimes, the overwhelming importance of biophysical predictors and how a reef's natural setting may either expand or narrow the opportunity space for management interventions. The methods developed through this study can help inform reef practitioners and hold promises for replication across a broad range of ecosystems. © 2019 The Author(s

Digital endpoints in clinical trials of Alzheimer's disease and other neurodegenerative diseases: challenges and opportunities.

Alzheimer's disease (AD) and other neurodegenerative diseases such as Parkinson's disease (PD) and Huntington's disease (HD) are associated with progressive cognitive, motor, affective and consequently functional decline considerably affecting Activities of Daily Living (ADL) and quality of life. Standard assessments, such as questionnaires and interviews, cognitive testing, and mobility assessments, lack sensitivity, especially in early stages of neurodegenerative diseases and in the disease progression, and have therefore a limited utility as outcome measurements in clinical trials. Major advances in the last decade in digital technologies have opened a window of opportunity to introduce digital endpoints into clinical trials that can reform the assessment and tracking of neurodegenerative symptoms. The Innovative Health Initiative (IMI)-funded projects RADAR-AD (Remote assessment of disease and relapse-Alzheimer's disease), IDEA-FAST (Identifying digital endpoints to assess fatigue, sleep and ADL in neurodegenerative disorders and immune-mediated inflammatory diseases) and Mobilise-D (Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement) aim to identify digital endpoints relevant for neurodegenerative diseases that provide reliable, objective, and sensitive evaluation of disability and health-related quality of life. In this article, we will draw from the findings and experiences of the different IMI projects in discussing (1) the value of remote technologies to assess neurodegenerative diseases; (2) feasibility, acceptability and usability of digital assessments; (3) challenges related to the use of digital tools; (4) public involvement and the implementation of patient advisory boards; (5) regulatory learnings; and (6) the significance of inter-project exchange and data- and algorithm-sharing

Combining fish and benthic communities into multiple regimes reveals complex reef dynamics

Abstract Coral reefs worldwide face an uncertain future with many reefs reported to transition from being dominated by corals to macroalgae. However, given the complexity and diversity of the ecosystem, research on how regimes vary spatially and temporally is needed. Reef regimes are most often characterised by their benthic components; however, complex dynamics are associated with losses and gains in both fish and benthic assemblages. To capture this complexity, we synthesised 3,345 surveys from Hawai‘i to define reef regimes in terms of both fish and benthic assemblages. Model-based clustering revealed five distinct regimes that varied ecologically, and were spatially heterogeneous by island, depth and exposure. We identified a regime characteristic of a degraded state with low coral cover and fish biomass, one that had low coral but high fish biomass, as well as three other regimes that varied significantly in their ecology but were previously considered a single coral dominated regime. Analyses of time series data reflected complex system dynamics, with multiple transitions among regimes that were a function of both local and global stressors. Coupling fish and benthic communities into reef regimes to capture complex dynamics holds promise for monitoring reef change and guiding ecosystem-based management of coral reefs

Determinants and impact of role-related time use allocation on self-reported health among married men and women: a cross-national comparative study

Background Research on the effects of marriage on health maintains that there is a gender-specific gradient, with men deriving far greater benefits than women. One reason provided for this difference is the disproportionate amount of time spent by women on housework and childcare. However, this hypothesis has yet to be explicitly tested for these role-related time use activities. This study provides empirical evidence on the association between role-related time use activities (i.e. housework, childcare and paid work) and self-reported health among married men and women. Methods Data from the Multinational Time Use Study (MTUS) on 32,881 men and 26,915 women from Germany, Italy, Spain, the UK and the US were analyzed. Seemingly unrelated regression (SUR) models and multivariable logistic regression were used to estimate the association between role-related time use activities and self-reported health among married men and women. Results The findings showed that education, occupation and number of children under 18 years old in the household were the most consistent predictors of time allocation among married men and women. Significant gender differences were also found in time allocation, with women sacrificing paid working time or reducing time devoted to housework for childcare. Men, in contrast, were less likely to reduce paid working hours to increase time spent on childcare, but instead reduced time allocation to housework. Allocating more time to paid work and childcare was associated with good health, whereas time spent on housework was associated with poor health, especially among women. Conclusions Time allocation to role-related activities have differential associations on health, and the effects vary by gender and across countries. To reduce the gender health gap among married men and women, public policies need to take social and gender roles into account

A global database of ant species abundances

What forces structure ecological assemblages? A key limitation to general insights about assemblage structure is the availability of data that are collected at a small spatial grain (local assemblages) and a large spatial extent (global coverage). Here, we present published and unpublished data from 51, 388 ant abundance and occurrence records of more than 2,693 species and 7,953 morphospecies from local assemblages collected at 4,212 locations around the world. Ants were selected because they are diverse and abundant globally, comprise a large fraction of animal biomass in most terrestrial communities, and are key contributors to a range of ecosystem functions. Data were collected between 1949 and 2014, and include, for each geo-referenced sampling site, both the identity of the ants collected and details of sampling design, habitat type, and degree of disturbance. The aim of compiling this data set was to provide comprehensive species abundance data in order to test relationships between assemblage structure and environmental and biogeographic factors. Data were collected using a variety of standardized methods, such as pitfall and Winkler traps, and will be valuable for studies investigating large-scale forces structuring local assemblages. Understanding such relationships is particularly critical under current rates of global change. We encourage authors holding additional data on systematically collected ant assemblages, especially those in dry and cold, and remote areas, to contact us and contribute their data to this growing data set

Time spent on work-related activities, social activities and time pressure as intermediary determinants of health disparities among elderly women and men in 5 European countries: a structural equation model

Background Psychosocial factors shape the health of older adults through complex inter-relating pathways. Besides socioeconomic factors, time use activities may explain gender inequality in self-reported health. This study investigated the role of work-related and social time use activities as determinants of health in old age. Specifically, we analysed whether the impact of stress in terms of time pressure on health mediated the relationship between work-related time use activities (i.e. housework and paid work) on self-reported health. Methods We applied structural equation models and a maximum-likelihood function to estimate the direct and indirect effects of psychosocial factors on health using pooled data from the Multinational Time Use Study on 11,168 men and 14,295 women aged 65+ from Italy, Spain, UK, France and the Netherlands. Results The fit indices for the conceptual model indicated an acceptable fit for both men and women. The results showed that socioeconomic status (SES), demographic factors, stress and work-related time use activities after retirement had a significant direct influence on self-reported health among the elderly, but the magnitude of the effects varied by gender. Social activities had a positive impact on self-reported health but had no significant impact on stress among older men and women. The indirect standardized effects of work-related activities on self-reported health was statistically significant for housework (β = − 0.006; P  0.05 among women), which implied that the paths from paid work and housework on self-reported health via stress (mediator) was very weak because their indirect effects were close to zero. Conclusions Our findings suggest that although stress in terms of time pressure has a direct negative effect on health, it does not indirectly influence the positive effects of work-related time use activities on self-reported health among elderly men and women. The results support the time availability hypothesis that the elderly may not have the same time pressure as younger adults after retirement

Digital endpoints in clinical trials of Alzheimer’s disease and other neurodegenerative diseases: challenges and opportunities

Alzheimer’s disease (AD) and other neurodegenerative diseases such as Parkinson’s disease (PD) and Huntington’s disease (HD) are associated with progressive cognitive, motor, affective and consequently functional decline considerably affecting Activities of Daily Living (ADL) and quality of life. Standard assessments, such as questionnaires and interviews, cognitive testing, and mobility assessments, lack sensitivity, especially in early stages of neurodegenerative diseases and in the disease progression, and have therefore a limited utility as outcome measurements in clinical trials. Major advances in the last decade in digital technologies have opened a window of opportunity to introduce digital endpoints into clinical trials that can reform the assessment and tracking of neurodegenerative symptoms. The Innovative Health Initiative (IMI)-funded projects RADAR-AD (Remote assessment of disease and relapse—Alzheimer’s disease), IDEA-FAST (Identifying digital endpoints to assess fatigue, sleep and ADL in neurodegenerative disorders and immune-mediated inflammatory diseases) and Mobilise-D (Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement) aim to identify digital endpoints relevant for neurodegenerative diseases that provide reliable, objective, and sensitive evaluation of disability and health-related quality of life. In this article, we will draw from the findings and experiences of the different IMI projects in discussing (1) the value of remote technologies to assess neurodegenerative diseases; (2) feasibility, acceptability and usability of digital assessments; (3) challenges related to the use of digital tools; (4) public involvement and the implementation of patient advisory boards; (5) regulatory learnings; and (6) the significance of inter-project exchange and data- and algorithm-sharing