Environmental mycology in public health: fungi and mycotoxins risk assessment and management

Fungi are essential to the survival of our global ecology, but they might pose a significant threat to the health of occupants when they grow in our buildings. The exposure to fungi in homes is a significant risk factor for a number of respiratory symptoms. Well-known illnesses caused by fungi include allergy and hypersensitivity pneumonitis. Environmental monitoring for fungi and their disease agents are important aspects of exposure assessment, but few guidelines exist for interpreting their health impacts. This book answers the questions: How does one detect and measure the presence of indoor fungi? What is an acceptable level of indoor fungi? How do we relate this information to human health problems?

An environmental atlas of Albania

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Changing environmental behaviors through smartphone-based augmented experiences

Dissertação para obtenção do Grau de Mestrado em Engenharia de Informática

Health survey on the Ilha da Conceição, state of Rio de Janeiro: I. Study design and report of selected demographic and environmental characteristics

During July and August of 1968, a Health survey was conducted on the Ilha da Conceição, an area of Niterói containing approximately one thousand households. The survey was conducted by students from the Universidade Federal Fluminense and the University of Maryland, and was under the supervision of faculty of the Department of Tropical Medicine at U.F.F. and from the Department of Preventive Medicine at the University of Maryland, Baltimore, Maryland, U.S.A. The survey was focused on a 25 percent random sample of the households on the island. Information was obtained from a responsible adult at each Household for completion of a Health questionnaire. Physical measurements, as well as laboratory study information were obtained from, all children in these households. A number of environmental sanitation problems were identified on the Ilha da Conceição. In addition, the survey indicated that approximately half the children had not been adequately immunized against diphteria, pertussis and typhoid. Preventable communicable diseases were the major cause of reported deaths which had occurred in infants ou Household members. The Health of the population on the Ilha da Conceição could well be enhanced by the development of an intelligence system indicating the immunization status of all children in the area. In addition a Health education program for the residents could well be beneficial for improvement of sanitary conditions on the island, as well as maternity and well baby care.

The Appraisal of projects with environmental impacts. Efficiency and Sustainability

It is usually assumed that the appraisal of the impacts experienced by present generations does not entail any difficulty. However, this is not true. Moreover, there is not a widely accepted methodology for taking these impacts into account. Some of the controversial issues are: the appropriate value for the discount rate, the choice of the units for expressing the impacts, physical or monetary units -income, consumption or investment- and the valuation of tangible and intangible goods. When approaching the problem of very long term impacts, there is also the problem of valuing the impacts experienced by future generations, through e.g., the use of an intergenerational discount rate. However, if this were the case, the present generation perspective would prevail, as if all the property rights on the resources were owned by them. Therefore, the sustainability requirement should also be incorporated into the analysis. We will analyze these problems in this article and show some possible solutions.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Using environmental niche modeling to understand biological invasions in a changing world

L'activité humaine affecte particulièrement la biodiversité, qui décline à une vitesse préoccupante. Parmi les facteurs réduisant la biodiversité, on trouve les espèces envahissantes. Symptomatiques d'un monde globalisé où l'échange se fait à l'échelle de la planète, certaines espèces, animales ou végétales, sont introduites, volontairement ou accidentellement par l'activité humaine (par exemple lors des échanges commerciaux ou par les voyageurs). Ainsi, ces espèces atteignent des régions qu'elles n'auraient jamais pu coloniser naturellement. Une fois introduites, l'absence de compétiteur peut les rendre particulièrement nuisibles. Ces nuisances sont plus ou moins directes, allant de problèmes sanitaires (p. ex. les piqûres très aigües des fourmis de feu, originaires d'Amérique du Sud et colonisant à une vitesse fulgurante les USA, l'Australie ou la Chine) à des nuisances sur la biodiversité (p. ex. les ravages de la perche du Nil sur la diversité unique des poissons Cichlidés du Lac Victoria). Il est donc important de pouvoir prévenir de telles introductions. De plus, pour le biologiste, ces espèces représentent une rare occasion de pouvoir comprendre les mécanismes évolutifs et écologiques qui expliquent le succès des envahissantes dans un monde où les équilibres sont bouleversés. Les modèles de niche environnementale sont un outil particulièrement utile dans le cadre de cette problématique. En reliant des observations d'espèces aux conditions environnementales où elles se trouvent, ils peuvent prédire la distribution potentielle des envahissantes, permettant d'anticiper et de mieux limiter leur impact. Toutefois, ils reposent sur des hypothèses pas évidentes à démontrer. L'une d'entre elle étant que la niche d'une espèce reste constante dans le temps, et dans l'espace. Le premier objectif de mon travail est de comparer si la niche d'une espèce envahissante diffère entre sa distribution d'origine native et celle d'origine introduite. En étudiant 50 espèces de plantes et 168 espèces de Mammifères, je démontre que c'est le cas et que par corolaire, il est possible de prédire leurs distributions. La deuxième partie de mon travail consiste à comprendre quelles seront les interactions entre le changement climatiques et les envahissantes, afin d'estimer leur impact sous un climat réchauffé. En étudiant la distribution de 49 espèces de plantes envahissantes, je démontre que les montagnes, régions relativement préservée par ce problème, deviendront bien plus exposées aux risques d'invasions biologiques. J'expose aussi comment les interactions entre l'activité humaine, le réchauffement climatique et les espèces envahissantes menacent la vigne sauvage en Europe et propose des zones géographiques particulièrement adaptée pour sa conservation. Enfin, à une échelle beaucoup plus locale, je montre qu'il est possible d'utiliser ces modèles de niches le long d'une rivière à une échelle extrêmement fine (1 mètre), potentiellement utile pour rationnaliser des mesures de conservations sur le terrain. - Biodiversity is significantly negatively affected by human activity. Invasive species are one of the most important factors causing biodiversity's decline. Intimately linked to the era of global trade, some plant or animal species can be accidentally or casually introduced with human activity (e.g. trade or travel). In this way, these species reach areas they could never reach through natural dispersal. Once naturalized, the lack of competitors can make these species highly noxious. Their effect is more or less direct, from sanitary problems (e.g. the harmful sting of Fire Ants, originating from South America and now spreading throughout USA, China and Australia) or can affect biodiversity (e.g. the Nile perch, devastating the one of the richest hotspot of Cichlid fishes diversity in Lake Victoria). It is thus important to prevent such harmful introductions. Moreover, invasive species represent for biologists one of the rare occasions to understand the evolutionary and ecological mechanisms behind the success of invaders in a world where natural equilibrium is already disturbed. Environmental niche models are particularly useful to tackle this problematic. By relating species observation to the environmental conditions where they occur, they can predict the potential distribution of invasive species, allowing a better anticipation and thus limiting their impact. However, they rely on strong assumption, one of the most important being that the modeled niche remains constant through space and time. The first aim of my thesis is to quantify the difference between the native and the invaded niche. By investigating 50 plant and 168 mammal species, I show that the niche is at least partially conserved, supporting for reliable predictions of invasive' s potential distributions. The second aim of my thesis is to understand the possible interactions between climate change and invasive species, such as to assess their impact under a warmer climate. By studying 49 invasive plant species, I show that mountain areas, which were relatively preserved, will become more suitable for biological invasions. Additionally, I show how interactions between human activity, global warming and invasive species are threatening the wild grapevine in Europe and propose geographical areas particularly adapted for conservation measures. Finally, at a much finer scale where conservation plannings ultimately take place, I show that it is possible to model the niche at very high resolution (1 meter) in an alluvial area allowing better prioritizations for conservation.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Parental post-traumatic reactions after premature birth: implications for sleeping and eating problems in the infant.

BACKGROUND: Progress in perinatal medicine has made it possible to increase the survival of very or extremely low birthweight infants. Developmental outcomes of surviving preterm infants have been analysed at the paediatric, neurological, cognitive, and behavioural levels, and a series of perinatal and environmental risk factors have been identified. The threat to the child's survival and invasive medical procedures can be very traumatic for the parents. Few empirical reports have considered post-traumatic stress reactions of the parents as a possible variable affecting a child's outcome. Some studies have described sleeping and eating problems as related to prematurity; these problems are especially critical for the parents. OBJECTIVE: To examine the effects of post-traumatic reactions of the parents on sleeping and eating problems of the children. DESIGN: Fifty families with a premature infant (25-33 gestation weeks) and a control group of 25 families with a full term infant participated in the study. Perinatal risks were evaluated during the hospital stay. Mothers and fathers were interviewed when their children were 18 months old about the child's problems and filled in a perinatal post-traumatic stress disorder questionnaire (PPQ). RESULTS: The severity of the perinatal risks only partly predicts a child's problems. Independently of the perinatal risks, the intensity of the post-traumatic reactions of the parents is an important predictor of these problems. CONCLUSIONS: These findings suggest that the parental response to premature birth mediates the risks of later adverse outcomes. Preventive intervention should be promoted.

Council Bluffs Interstate System Improvement Project Tier 2, Segment 3 Pottawatomie County, Iowa Environmental Assessment, March 2011

This Tier 2 Environmental Assessment (EA) presents the results of studies and analyses conducted to determine the potential impacts of proposed improvements in Segment 3 of the Council Bluffs Interstate System (CBIS) in the Council Bluffs metropolitan area. This document is tiered to the Tier 1 Draft and Final Environmental Impact Statements (EIS) that evaluated impacts of the overall CBIS Improvements Project, which includes five segments of independent utility1 This EA on Segment 3 of the Project is divided into the following sections: and encompasses 18 mainline miles of Interstate and 14 interchanges along Interstate 80 (I-80), Interstate 29 (I-29), and Interstate 480 (I-480). More information about the tiering process is found below under Project Background. • Section 1 provides background information on the Project and discusses the relationship between the earlier Tier 1 EIS and this Tier 2 EA. It also discusses the proposed action and the area studied, the purpose of the Project, and the need for the Project based on transportation problems that currently exist or are expected in the future. • Section 2, Alternatives, identifies the range of alternatives considered for Segment 3 to address the transportation problems identified in Section 1. It also identifies the alternatives retained for further study in this EA and the preferred Segment 3 alternative. • Section 3, Affected Environment and Environmental Consequences, describes the general environment for each resource affected by the proposed improvements. It also describes the potential environmental impacts of the Segment 3 Project and methods to avoid, minimize, and mitigate impacts. • Section 4, Disposition, lists the agencies and organizations that will receive copies of this EA and the locations at which this EA will be available for public review. • Section 5, Comments and Coordination, summarizes the agency coordination and public involvement efforts in conjunction with the Segment 3 Project. • Section 6, Conclusion and Recommendation, summarizes resource impacts. • Section 7, References, lists the sources cited in this EA. For Segment 3, the Federal Highway Administration (FHWA) and Iowa Department of Transportation (Iowa DOT) determined that an EA is the appropriate level of Tier 2 study to comply with the National Environmental Policy Act (NEPA) requirements. The primary purpose of an EA is to clearly establish the significance of a project’s environmental impacts. That analysis is included in this document.

Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

Retrofit Methods for Distortion Cracking Problems in Plate Girder Bridges, TR-436, 2003

This report is formatted to independently present four individual investigations related to similar web gap fatigue problems. Multiple steel girder bridges commonly exhibit fatigue cracking due to out-of-plane displacement of the web near the diaphragm connections. This fatigue-prone web gap area is typically located in negative moment regions of the girders where the diaphragm stiffener is not attached to the top flange. In the past, the Iowa Department of Transportation has attempted to stop fatigue crack propagation in these steel girder bridges by drilling holes at the crack tips. Other nondestructive retrofits have been tried; in a particular case on a two-girder bridge with floor beams, angles were bolted between the stiffener and top flange. The bolted angle retrofit has failed in the past and may not be a viable solution for diaphragm bridges. The drilled hole retrofit is often only a temporary solution, so a more permanent and effective retrofit is required. A new field retrofit has been developed that involves loosening the bolts in the connection between the diaphragm and the girders. Research on the retrofit has been initiated; however, no long-term studies of the effects of bolt loosening have been performed. The intent of this research is to study the short-term effects of the bolt loosening retrofit on I-beam and channel diaphragm bridges. The research also addressed the development of a continuous remote monitoring system to investigate the bolt loosening retrofit on an X-type diaphragm bridge over a number of months, ensuring that the measured strain and displacement reductions are not affected by time and continuous traffic loading on the bridge. The testing for the first three investigations is based on instrumentation of web gaps in a negative moment region on Iowa Department of Transportation bridges with I-beam, channel, and X-type diaphragms. One bridge of each type was instrumented with strain gages and deflection transducers. Field tests, using loaded trucks of known weight and configuration, were conducted on the bridges with the bolts in the tight condition and after implementing the bolt loosening retrofit to measure the effects of loosening the diaphragm bolts. Long-term data were also collected on the X-diaphragm bridge by a data acquisition system that collected the data continuously under ambient truck loading. The collected data were retrievable by an off-site modem connection to the remote data acquisition system. The data collection features and ruggedness of this system for remote bridge monitoring make it viable as a pilot system for future monitoring projects in Iowa. Results indicate that loosening the diaphragm bolts reduces strain and out-of-plane displacement in the web gap, and that the reduction is not affected over time by traffic or environmental loading on the bridge. Reducing the strain in the web gap allows the bridge to support more cycles of loading before experiencing fatigue, thus increase the service life of the bridge. Two-girder floor beam bridges may also exhibit fatigue cracking in girder webs.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Genetic origin of the relationship between parental negativity and behavior problems from early childhood to adolescence: A longitudinal genetically sensitive study.

Little is known about how genetic and environmental factors contribute to the association between parental negativity and behavior problems from early childhood to adolescence. The current study fitted a cross-lagged model in a sample consisting of 4,075 twin pairs to explore (a) the role of genetic and environmental factors in the relationship between parental negativity and behavior problems from age 4 to age 12, (b) whether parent-driven and child-driven processes independently explain the association, and (c) whether there are sex differences in this relationship. Both phenotypes showed substantial genetic influence at both ages. The concurrent overlap between them was mainly accounted for by genetic factors. Causal pathways representing stability of the phenotypes and parent-driven and child-driven effects significantly and independently account for the association. Significant but slight differences were found between males and females for parent-driven effects. These results were highly similar when general cognitive ability was added as a covariate. In summary, the longitudinal association between parental negativity and behavior problems seems to be bidirectional and mainly accounted for by genetic factors. Furthermore, child-driven effects were mainly genetically mediated, and parent-driven effects were a function of both genetic and shared-environmental factors.