Segmentation and object-oriented processing of single-season and multi-season Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data was utilized for the classification of wetlands in a 1560 km² study ...area of north central Florida. This segmentation and object-oriented classification outperformed the traditional maximum likelihood algorithm (MLC) in accurately mapping wetlands, with overall accuracies of 90.2% (single-season imagery) and 90.8% (multi-season imagery), compared to overall accuracies for the MLC classifiers of 78.4 and 79.0%, respectively. Kappa coefficients were over 1.5-times greater for the segmentation/object-oriented classifications than for the MLC classifications, and producer and user accuracies were also higher. The producer accuracies of the segmentation/object-oriented classifications were 90.8% (single-season) and 91.6% (multi-season), compared to 70.6 and 74.4%, respectively, for the MLC classifications. User accuracies were 73.9 and 73.5% for the single-season and multi-season segmentation/object-oriented classifications, respectively, compared to 54.1% (single-season) and 55.0% (multi-season) for the MLC classifications. The use of multi-seasonal data resulted in only a slight increase in overall accuracy over the single-season imagery. This small increase was primarily due to better discrimination of riparian wetlands in the multi-season data. Segmentation and object-oriented processing provides a low-cost, high-accuracy method for classification of wetlands on a local, regional, or national basis.
Image omitted - see PDF Methods The current PVI model integrates multiple data streams into an overall score derived from 12 key indicators—including well-established, general vulnerability factors ...for public health, plus emerging factors relevant to the pandemic—distributed across four domains: current infection rates, baseline population concentration, current interventions, and health and environmental vulnerabilities. Data sources in the current model (version 11.2.1) include the Social Vulnerability Index (SVI) of the Centers for Disease Control and Prevention (CDC) for emergency response and hazard mitigation planning (Horney et al. 2017), testing rates from the COVID Tracking Project (Atlantic Monthly Group 2020), social distancing metrics from mobile device data ( https://www.unacast.com/covid19/social-distancing-scoreboard), and dynamic measures of disease spread and case numbers ( https://usafacts.org/issues/coronavirus/). Acknowledgments We thank the information technology and web services staff at the National Institute of Environmental Health Sciences (NIEHS)/National Institutes of Health (NIH) for their help and support, as well as J.K. Cetina and D.J. Reif for their useful technical input and advice.
European countries have been the key destination for many Syrians since the beginning of the civil war in 2011. In this new context, refugees have faced various challenges, including negative public ...attitudes and pressure of assimilation that might negatively influence psychophysical adaptation. This indicates the necessity of exploring the factors associated with the adaptation of refugees in their new society. Using a multidimensional individual difference acculturation (MIDA) model as a theoretical framework, the present study investigated the psychophysical adaptation of Syrian refugees (N = 265, Mage = 33.03 years) in Germany. The MIDA model is a theoretical model on immigrants’ adaptation that takes into account the role of psychosocial resources (e.g., psychological strength), co-national connectedness (e.g., ingroup support), hassles, and acculturation orientations in predicting adaptation of immigrants. Using structural equation modelling, specific hypotheses drawn from the MIDA model were tested. It was found that Syrian refugees with high psychological strength and cultural competence reported high levels of adjustment as indicated by low levels of distress. On the other hand, refugees with high levels of perceived hassles reported low levels of adjustment as indicated by high level of distress. The results highlight the importance of psychological strength, cultural competence, and hassles in refugees’ adaption. The study’s findings have the potential to inform host country policymakers regarding the positive integration of refugees into German society, and specific recommendations have been made.
The need for holistic molecular measurements to better understand disease initiation, development, diagnosis, and therapy has led to an increasing number of multiomic analyses. The wealth of ...information available from multiomic assessments, however, requires both the evaluation and interpretation of extremely large data sets, limiting analysis throughput and ease of adoption. Computational methods utilizing artificial intelligence (AI) provide the most promising way to address these challenges, yet despite the conceptual benefits of AI and its successful application in singular omic studies, the widespread use of AI in multiomic studies remains limited. Here, we discuss present and future capabilities of AI techniques in multiomic studies while introducing analytical checks and balances to validate the computational conclusions.
Presenting a comprehensive picture of geographic data comprising multiple factors is an inherently integrative undertaking. Visualizing such data in an interactive form is essential for public ...sharing and geographic information systems (GIS) analysis. The Toxicological Prioritization Index (ToxPi) framework offers a visual analytic integrating data that is compatible with geographic data. ArcGIS is a predominant geospatial software available for presenting and communicating geographic data, yet to our knowledge there is no methodology for integrating ToxPi profiles into ArcGIS maps.
We introduce an actively developed suite of software, the ToxPi*GIS Toolkit, for creating, viewing, sharing, and analyzing interactive ToxPi profiles in ArcGIS to allow for new GIS analysis and an avenue for providing geospatial results to the public.
The ToxPi*GIS Toolkit is a collection of methods for creating interactive feature layers that contain ToxPi profiles. It currently includes an ArcGIS Toolbox (ToxPiToolbox.tbx) for drawing location-specific ToxPi profiles in a single feature layer, a collection of modular Python scripts that create predesigned layer files containing ToxPi feature layers from the command line, and a collection of Python routines for useful data manipulation and preprocessing. We present workflows documenting ToxPi feature layer creation, sharing, and embedding for both novice and advanced users looking for additional customizability.
Map visualizations created with the ToxPi*GIS Toolkit can be made freely available on public URLs, allowing users without ArcGIS Pro access or expertise to view and interact with them. Novice users with ArcGIS Pro access can create de novo custom maps, and advanced users can exploit additional customization options. The ArcGIS Toolbox provides a simple means for generating ToxPi feature layers. We illustrate its usage with current COVID-19 data to compare drivers of pandemic vulnerability in counties across the United States.
The integration of ToxPi profiles with ArcGIS provides new avenues for geospatial analysis, visualization, and public sharing of multi-factor data. This allows for comparison of data across a region, which can support decisions that help address issues such as disease prevention, environmental health, natural disaster prevention, chemical risk, and many others. Development of new features, which will advance the interests of the scientific community in many fields, is ongoing for the ToxPi*GIS Toolkit, which can be accessed from www.toxpi.org .
There are tens of thousands of man-made chemicals in the environment; the inherent safety of most of these chemicals is not known. Relevant biological platforms and new computational tools are needed ...to prioritize testing of chemicals with limited human health hazard information. We describe an experimental design for high-throughput characterization of multidimensional in vivo effects with the power to evaluate trends relating to commonly cited chemical predictors. We evaluated all 1060 unique U.S. EPA ToxCast phase 1 and 2 compounds using the embryonic zebrafish and found that 487 induced significant adverse biological responses. The utilization of 18 simultaneously measured endpoints means that the entire system serves as a robust biological sensor for chemical hazard. The experimental design enabled us to describe global patterns of variation across tested compounds, evaluate the concordance of the available in vitro and in vivo phase 1 data with this study, highlight specific mechanisms/value-added/novel biology related to notochord development, and demonstrate that the developmental zebrafish detects adverse responses that would be missed by less comprehensive testing strategies.
Currently, assessment of the potential immunotoxicity of a given agent involves a tiered approach for hazard identification and mechanistic studies, including observational studies, evaluation of ...immune function, and measurement of susceptibility to infectious and neoplastic diseases. These studies generally use costly low-throughput mammalian models. Zebrafish, however, offer an excellent alternative due to their rapid development, ease of maintenance, and homology to mammalian immune system function and development. Larval zebrafish also are a convenient model to study the innate immune system with no interference from the adaptive immune system. In this study, a respiratory burst assay (RBA) was utilized to measure reactive oxygen species (ROS) production after developmental xenobiotic exposure. Embryos were exposed to non-teratogenic doses of chemicals and at 96 h post-fertilization, the ability to produce ROS was measured. Using the RBA, 12 compounds with varying immune-suppressive properties were screened. Seven compounds neither suppressed nor enhanced the respiratory burst; five reproducibly suppressed global ROS production, but with varying potencies: benzoapyrene, 17β-estradiol, lead acetate, methoxychlor, and phenanthrene. These five compounds have all previously been reported as immunosuppressive in mammalian innate immunity assays. To evaluate whether the suppression of ROS by these compounds was a result of decreased immune cell numbers, flow cytometry with transgenic zebrafish larvae was used to count the numbers of neutrophils and macrophages after chemical exposure. With this assay, benzoapyrene was found to be the only chemical that induced a change in the number of immune cells by increasing macrophage but not neutrophil numbers. Taken together, this work demonstrates the utility of zebrafish larvae as a vertebrate model for identifying compounds that impact innate immune function at non-teratogenic levels and validates measuring ROS production and phagocyte numbers as metrics for monitoring how xenobiotic exposure alters the innate immune system.
Exposure to endocrine-disrupting chemicals (EDCs) is linked to myriad disorders, characterized by the disruption of the complex endocrine signaling pathways that govern development, physiology, and ...even behavior across the entire body. The mechanisms of endocrine disruption involve a complex system of pathways that communicate across the body to stimulate specific receptors that bind DNA and regulate the expression of a suite of genes. These mechanisms, including gene regulation, DNA binding, and protein binding, can be tied to differences in individual susceptibility across a genetically diverse population. In this review, we posit that EDCs causing such differential responses may be identified by looking for a signal of population variability after exposure. We begin by summarizing how the biology of EDCs has implications for genetically diverse populations. We then describe how gene-environment interactions (GxE) across the complex pathways of endocrine signaling could lead to differences in susceptibility. We survey examples in the literature of individual susceptibility differences to EDCs, pointing to a need for research in this area, especially regarding the exceedingly complex thyroid pathway. Following a discussion of experimental designs to better identify and study GxE across EDCs, we present a case study of a high-throughput screening signal of putative GxE within known endocrine disruptors. We conclude with a call for further, deeper analysis of the EDCs, particularly the thyroid disruptors, to identify if these chemicals participate in GxE leading to differences in susceptibility.
Abstract
Interdisciplinary engineering of cyber physical production systems (CPPS) are often subject to delay, cost overrun and quality problems or may even fail due to the lack of efficient ...information exchange between multiple interdisciplinary teams working in complex networks within and across companies. We propose a direct integration of multiteam and organisational aspects into the graphical notation of the systems engineering workflow. BPMN++, with eight new notational elements and two subdiagrams, enables the modelling of the required cooperation aspects. BPMN++ provides an improved overview, uniform notation, more compact presentation and easier modifiability from an engineering point of view. We also included a first set of empirical studies and historical qualitative and quantitative data in addition to subjective expert-based ratings to increase validity. The use case introduced to explain the procedure and the notation is derived from surveys in plant manufacturing focussing on the start-up phase and decision support at site. This, in particular, is one of the most complex and critical phases with potentially high economic impact. For evaluation purposes, we compare two alternative solutions for a short-term management decision in the start-up phase of CPPS using the BPMN++ approach.
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