High dimensional land cover inference using remotely sensed MODIS data

Image segmentation persists as a major statistical problem, with the volume and complexity of data expanding alongside new technologies. Land cover classification, one of the most studied problems in Remote Sensing, provides an important example of image segmentation whose needs transcend the choice of a particular classification method. That is, the challenges associated with land cover classification pervade the analysis process from data pre-processing to estimation of a final land cover map. Many of the same challenges also plague the task of land cover change detection. Multispectral, multitemporal data with inherent spatial relationships have hardly received adequate treatment due to the large size of the data and the presence of missing values. In this work we propose a novel, concerted application of methods which provide a unified way to estimate model parameters, impute missing data, reduce dimensionality, classify land cover, and detect land cover changes. This comprehensive analysis adopts a Bayesian approach which incorporates prior knowledge to improve the interpretability, efficiency, and versatility of land cover classification and change detection. We explore a parsimonious, parametric model that allows for a natural application of principal components analysis to isolate important spectral characteristics while preserving temporal information. Moreover, it allows us to impute missing data and estimate parameters via expectation-maximization (EM). A significant byproduct of our framework includes a suite of training data assessment tools. To classify land cover, we employ a spanning tree approximation to a lattice Potts prior to incorporate spatial relationships in a judicious way and more efficiently access the posterior distribution of pixel labels. We then achieve exact inference of the labels via the centroid estimator. To detect land cover changes, we develop a new EM algorithm based on the same parametric model. We perform simulation studies to validate our models and methods, and conduct an extensive continental scale case study using MODIS data. The results show that we successfully classify land cover and recover the spatial patterns present in large scale data. Application of our change point method to an area in the Amazon successfully identifies the progression of deforestation through portions of the region

IFRS für KMU

Mit der Publikation des International Financial Reporting Standard for Small and Medium-Sized Entities – kurz: IFRS for SMEs – im Juli 2009 ging das bisher langwierigste Projekt des International Accounting Standards Board (IASB) zu Ende: ein einziges Regelwerk weltweit für Finanzberichte privater Unternehmen! Während die „vollen“ IFRS (full IFRS) und US GAAP immer komplexer werden, wird mit dem IFRS for SMEs eine Variante light in den Markt gebracht. Der vorliegende Beitrag erläutert Geltungsbereich, Werdegang und Wesensmerkmale des neuen Standards, dessen wesentliche Unterschiede zu den „vollen“ IFRS sowie den Swiss GAAP FER und beleuchtet das Marktpotenzial in der Schweiz

Neural Network Model for Apparent Deterministic Chaos in Spontaneously Bursting Hippocampal Slices

A neural network model that exhibits stochastic population bursting is studied by simulation. First return maps of inter-burst intervals exhibit recurrent unstable periodic orbit (UPO)-like trajectories similar to those found in experiments on hippocampal slices. Applications of various control methods and surrogate analysis for UPO-detection also yield results similar to those of experiments. Our results question the interpretation of the experimental data as evidence for deterministic chaos and suggest caution in the use of UPO-based methods for detecting determinism in time-series data.Comment: 4 pages, 5 .eps figures (included), requires psfrag.sty (included

Heart Rate Variability During Physical Exercise Is Associated With Improved Cognitive Performance in Alzheimer's Dementia Patients-A Longitudinal Feasibility Study

Heart rate variability (HRV) rapidly gains attention as an important marker of cardiovascular autonomic modulation. Moreover, there is evidence for a link between the autonomic deficit measurable by reduced HRV and the hypoactivity of the cholinergic system, which is prominently affected in Alzheimer's disease (AD). Despite the positive influence of physical exercise on cognition and its promising association with HRV, previous studies did not explore the effect of long-term physical exercise in older adults with AD. Taking advantage of a longitudinal study we analyzed the effect of a 20-week dual task training regime (3 × 15-min per week) on the vagal mediated HRV index RMSSD (root mean square of successive RR interval differences) during physical exercise and the short-term memory performance in a AD cohort (N = 14). Each training contained physical exercise on a bicycle ergometer while memorizing 30 successively presented pictures as well as the associated post-exercise picture recognition memory test. Linear-mixed modeling revealed that HRV-RMSSD significantly increased over the intervention time. Moreover, the reaction time in the picture recognition task decreased while the accuracy remained stable. Furthermore, a significantly negative relationship between increased fitness measured by HRV-RMSSD and decreased reaction time was observed. This feasibility study points to the positive effects of a dual task regime on physical and cognitive fitness in a sample with impaired cognitive performance. Beyond this, the results show that the responsiveness of parasympathetic system as measured with HRV can be improved in patients with dementia

Ghost of invasion past: legacy effects on community disassembly following eradication of an invasive ecosystem engineer

By changing ecosystem processes and altering the physical landscape, invasive ecosystem engineers can have substantial impacts on ecosystem functions and human economies and may facilitate other non-native species. Eradication programs in terrestrial and aquatic systems aim to reverse the impacts of invasive species and return the system to its pre-invasion conditions. Despite an extensive focus on the impacts of both native and non-native ecosystem engineers, the consequences of removing invasive ecosystem engineers, particularly in coastal ecosystems, are largely unknown. In this study, we quantified changes in a benthic community following the eradication of the invasive ecosystem engineer, hybrid cordgrass Spartina, in San Francisco Bay, California. We used field experimental manipulations to test for persistent effects of both aboveground and belowground structural modifications of the invasive plant on the benthic community. We found significant effects of the invasive plant more than four years following eradication. Experimental modification of the above- vs. belowground structure of this ecosystem engineer revealed taxonomic specific effects resulting in hysteresis in the recovery of the benthic food webs. We found that these legacy effects resulted from two specific mechanisms: (1) delayed breakdown of belowground structures (stems, roots) and (2) persistence of other invasive species whose invasion was facilitated by the ecosystem engineer. Both of these mechanisms are likely to occur in similar systems where belowground structures breakdown more slowly or where other associated long-lived invaders persist. Our work is among the first to quantify the slow rate of change in food web and community processes and the persistent legacy effects of an invasive ecosystem engineer in a coastal ecosystem. We suggest that this delayed transition to pre-invasion conditions could resemble an alternate state that would be misidentified without a sufficient monitoring interval or recovery duration, with consequences for future management and restoration activity planning

Cellular Structures for Computation in the Quantum Regime

We present a new cellular data processing scheme, a hybrid of existing cellular automata (CA) and gate array architectures, which is optimized for realization at the quantum scale. For conventional computing, the CA-like external clocking avoids the time-scale problems associated with ground-state relaxation schemes. For quantum computing, the architecture constitutes a novel paradigm whereby the algorithm is embedded in spatial, as opposed to temporal, structure. The architecture can be exploited to produce highly efficient algorithms: for example, a list of length N can be searched in time of order cube root N.Comment: 11 pages (LaTeX), 3 figure

Individual and setting level predictors of the implementation of a skin cancer prevention program: a multilevel analysis

<p>Abstract</p> <p>Background</p> <p>To achieve widespread cancer control, a better understanding is needed of the factors that contribute to successful implementation of effective skin cancer prevention interventions. This study assessed the relative contributions of individual- and setting-level characteristics to implementation of a widely disseminated skin cancer prevention program.</p> <p>Methods</p> <p>A multilevel analysis was conducted using data from the Pool Cool Diffusion Trial from 2004 and replicated with data from 2005. Implementation of Pool Cool by lifeguards was measured using a composite score (implementation variable, range 0 to 10) that assessed whether the lifeguard performed different components of the intervention. Predictors included lifeguard background characteristics, lifeguard sun protection-related attitudes and behaviors, pool characteristics, and enhanced (<it>i.e</it>., more technical assistance, tailored materials, and incentives are provided) versus basic treatment group.</p> <p>Results</p> <p>The mean value of the implementation variable was 4 in both years (2004 and 2005; SD = 2 in 2004 and SD = 3 in 2005) indicating a moderate implementation for most lifeguards. Several individual-level (lifeguard characteristics) and setting-level (pool characteristics and treatment group) factors were found to be significantly associated with implementation of Pool Cool by lifeguards. All three lifeguard-level domains (lifeguard background characteristics, lifeguard sun protection-related attitudes and behaviors) and six pool-level predictors (number of weekly pool visitors, intervention intensity, geographic latitude, pool location, sun safety and/or skin cancer prevention programs, and sun safety programs and policies) were included in the final model. The most important predictors of implementation were the number of weekly pool visitors (inverse association) and enhanced treatment group (positive association). That is, pools with fewer weekly visitors and pools in the enhanced treatment group had significantly higher program implementation in both 2004 and 2005.</p> <p>Conclusions</p> <p>More intense, theory-driven dissemination strategies led to higher levels of implementation of this effective skin cancer prevention program. Issues to be considered by practitioners seeking to implement evidence-based programs in community settings, include taking into account both individual-level and setting-level factors, using active implementation approaches, and assessing local needs to adapt intervention materials.</p

The roles of dispositional coping style and social support in helping people with respiratory disease cope with a breathlessness crisis

© 2019 John Wiley & Sons Ltd Aim: To explore the role of coping moderators in self-management of breathlessness crises by people with advanced respiratory disease. Design: A secondary analysis of semi-structured interview data. Methods: Interviews with patients who had advanced respiratory disease, chronic breathlessness and at least one experience where they considered presenting to Emergency but self-managed instead (a “near miss”). Participants were recruited from New South Wales, Queensland, Victoria, South Australia or Tasmania. Eligible caregivers were those who contributed to Emergency-related decision-making. Interviews were coded inductively and then deductively against the coping moderators social support and dispositional coping style, defined by the Transactional Model of Stress and Coping. Results: Interviews were conducted between October 2015 - April 2016 with 20 patients and three caregivers. Social networks offered emotional and practical support but also had potential for conflict with patients' ‘hardy’ coping style. Patient hardiness (characterized by a sense of ‘commitment’ and ‘challenge’) promoted a proactive approach to self-management but made some patients less willing to accept support. Information-seeking tendencies varied between patients and were sometimes shared with caregivers. An optimistic coping style appeared to be less equivocally beneficial. Conclusion: This study shows that social support and coping style may influence how people self-manage through their breathlessness crises and identified ways coping moderators can facilitate or hinder effective self-management. Impact: This study confers insights into how social-support and coping style can be supported and optimized to facilitate breathlessness self-management. Acknowledging coping moderator interactions is beneficial for developing resources and strategies that recognise patient mastery

Lagrangian description of the fluid flow with vorticity in the relativistic cosmology

We develop the Lagrangian perturbation theory in the general relativistic cosmology, which enables us to take into account the vortical effect of the dust matter. Under the Lagrangian representation of the fluid flow, the propagation equation for the vorticity as well as the density is exactly solved. Based on this, the coupling between the density and vorticity is clarified in a non-perturbative way. The relativistic correspondence to the Lagrangian perturbation theory in the Newtonian cosmology is also emphasized.Comment: 14 pages (RevTeX); accepted for publication in Phys. Rev.

Gravitational Microlensing Evidence for a Planet Orbiting a Binary Star System

The study of extra-solar planetary systems has emerged as a new discipline of observational astronomy in the past few years with the discovery of a number of extra-solar planets. The properties of most of these extra-solar planets were not anticipated by theoretical work on the formation of planetary systems. Here we report observations and light curve modeling of gravitational microlensing event MACHO-97-BLG-41, which indicates that the lens system consists of a planet orbiting a binary star system. According to this model, the mass ratio of the binary star system is 3.8:1 and the stars are most likely to be a late K dwarf and an M dwarf with a separation of about 1.8 AU. A planet of about 3 Jupiter masses orbits this system at a distance of about 7 AU. If our interpretation of this light curve is correct, it represents the first discovery of a planet orbiting a binary star system and the first detection of a Jovian planet via the gravitational microlensing technique. It suggests that giant planets may be common in short period binary star systems.Comment: 11 pages, with 1 color and 2 b/w Figures included (published version