Integration Of Environmental Information Research Articles

Co-developing frameworks towards environmentally directed pharmaceutical prescribing in Scotland – A mixed methods study

The presence of human pharmaceuticals in the aquatic environment is recognised internationally as an important public health and environmental issue. In Scotland, healthcare sustainability targets call for improvements to medicine prescribing and use to reduce healthcare's impact on the environment. This proof-of-concept study aimed to develop a framework on the environmental impact of pharmaceuticals to use as a knowledge support tool for healthcare professionals, focussing on pharmaceutical pollution. Nominal Group Technique was applied to achieve consensus on pharmaceuticals and modelling factors for the framework, working with a panel of cross-sector stakeholders. Bayesian Belief Network modelling was applied to predict the environmental impact (calculated from hazard and exposure factors) of selected pharmaceuticals, with Scotland-wide mapping for visualisation in freshwater catchments. The model calculated the pollution risk score of the individual pharmaceuticals, using the ratio of prescribed mass vs. mass that would not exceed the predicted no-effect concentration in the freshwater environment. The pharmaceuticals exhibited different risk patterns, and spatial variation of risk was evident (generally related to population density), with the most catchments predicted to exceed the pollution risk score for clarithromycin (probability >80 % in 35 of 40 modelled catchments). Simulated risk scores were compared against observed risk calculated as the ratio of measured environmental concentrations from national regulatory and research monitoring and predicted no-effect concentrations. The model generally overpredicted risk, likely due to missing factors (e.g. solid-phase sorption, temporal variation), low spatial resolution, and low temporal resolution of the monitoring data. This work demonstrates a novel, trans-disciplinary approach to develop tools aiding collation and integration of environmental information into healthcare decision-making, through application of public health, environmental science, and health services research methods. Future work will refine the framework with additional clinical and environmental factors to improve model performance, and develop electronic interfaces to communicate environmental information to healthcare professionals.

Enhancing winter wheat prediction with genomics, phenomics and environmental data

In the realm of multi-environment prediction, when the goal is to predict a complete environment using the others as a training set, the efficiency of genomic selection (GS) falls short of expectations. Genotype by environment interaction poses a challenge in achieving high prediction accuracies. Consequently, current efforts are focused on enhancing efficiency by integrating various types of inputs, such as phenomics data, environmental information, and other omics data. In this study, we sought to evaluate the impact of incorporating environmental information into the modeling process, in addition to genomic and phenomics information. Our evaluation encompassed five data sets of soft white winter wheat, and the results revealed a significant improvement in prediction accuracy, as measured by the normalized root mean square error (NRMSE), through the integration of environmental information. Notably, there was an average gain in prediction accuracy of 49.19% in terms of NRMSE across the data sets. Moreover, the observed prediction accuracy ranged from 5.68% (data set 3) to 60.36% (data set 4), underscoring the substantial effect of integrating environmental information. By including genomic, phenomic, and environmental data in prediction models, plant breeding programs can improve selection efficiency across locations.

Do feature selection methods for selecting environmental covariables enhance genomic prediction accuracy?

Genomic selection (GS) is transforming plant and animal breeding, but its practical implementation for complex traits and multi-environmental trials remains challenging. To address this issue, this study investigates the integration of environmental information with genotypic information in GS. The study proposes the use of two feature selection methods (Pearson's correlation and Boruta) for the integration of environmental information. Results indicate that the simple incorporation of environmental covariates may increase or decrease prediction accuracy depending on the case. However, optimal incorporation of environmental covariates using feature selection significantly improves prediction accuracy in four out of six datasets between 14.25% and 218.71% under a leave one environment out cross validation scenario in terms of Normalized Root Mean Squared Error, but not relevant gain was observed in terms of Pearson´s correlation. In two datasets where environmental covariates are unrelated to the response variable, feature selection is unable to enhance prediction accuracy. Therefore, the study provides empirical evidence supporting the use of feature selection to improve the prediction power of GS.

Green reporting in the perception of reports preparers. Evidence from Poland

Purpose: The main purpose of the paper is to assess the perception of environmental reports preparers related to the obligation towards disclosing environmental information from the perspective of the company interests. The auxiliary aim of the article is to propose integrated green reporting in the context of theoretical foundations, in particular the theory of legitimacy, stakeholders and agencies. Design/methodology/approach: Surveys were used to assess the perception of preparers of environmental reports. The empirical data was collected in a non-exhaustive survey. In the statistical analysis of the survey data, contingency tables and association measures for categorical variables were used (examination of correlations between pairs of survey questions) as well as logistic regression models and odds ratios (examination of the impact of explanatory variables on the selected survey questions with dichotomous values). Findings: In the opinion of the respondents, the disclosure of environmental information is useful for stakeholders. They partly agree to extend the mandatory subjective and objective scope of the disclosure of environmental information. However, their opinion depends on some features of the enterprise, capital connections and the type of information shaping the enterprise image. The disclosed environmental information is an important element of influencing the company image, but it is not the most important one. Research limitations/implications: This research is the first, pilot stage of the overall research. In the next stages, the research sample will be enlarged. The second limitation is the focus on Polish enterprises. As part of the research continuation, we intend to cover other countries. Practical implications: Appropriate legal arrangements are needed to adequately enforce the scope and quality of reporting focused on environmental information. The author's definition of green reporting refers to a comprehensive, integrated environmental report combining financial and non-financial information arranged according to the substantively separated areas. Social implications: Our proposed integration of environmental information in one report – green report - that emphasizes the importance of the environmental protection problem, which will increase the transparency and availability of information, and ensure its comprehensiveness for stakeholders, and as a result have a positive impact on environmental awareness in the business operations of enterprises. Originality/value: The research was conducted from the perspective of preparers and managers that disclose environmental information. Our research is the broadening and deepening of knowledge on environmental information reporting in Poland, as well as participation in the discussion on the desired directions of its development. Keywords: green accounting, green reporting, environmental disclosures, non-financial statement, CSR. Category of the paper: research paper.

Improved Indoor Positioning by Means of Occupancy Grid Maps Automatically Generated from OSM Indoor Data

In recent years, there is a growing interest in indoor positioning due to the increasing amount of applications that employ position data. Current approaches determining the location of objects in indoor environments are facing problems with the accuracy of the sensor data used for positioning. A solution to compensate inaccurate and unreliable sensor data is to include further information about the objects to be positioned and about the environment into the positioning algorithm. For this purpose, occupancy grid maps (OGMs) can be used to correct such noisy data by modelling the occupancy probability of objects being at a certain location in a specific environment. In that way, improbable sensor measurements can be corrected. Previous approaches, however, have focussed only on OGM generation for outdoor environments or require manual steps. There remains need for research examining the automatic generation of OGMs from detailed indoor map data. Therefore, our study proposes an algorithm for automated OGM generation using crowd-sourced OpenStreetMap indoor data. Subsequently, we propose an algorithm to improve positioning results by means of the generated OGM data. In our study, we used positioning data from an Ultra-wideband (UWB) system. Our experiments with nine different building map datasets showed that the proposed method provides reliable OGM outputs. Furthermore, taking one of these generated OGMs as an example, we demonstrated that integrating OGMs in the positioning algorithm increases the positioning accuracy. Consequently, the proposed algorithms now enable the integration of environmental information into positioning algorithms to finally increase the accuracy of indoor positioning applications.

Forest Fire Smoke Recognition Based on Anchor Box Adaptive Generation Method

There are major problems in the field of image-based forest fire smoke detection, including the low recognition rate caused by the changeable and complex state of smoke in the forest environment and the high false alarm rate caused by various interferential objects in the recognition process. Here, a forest fire smoke identification method based on the integration of environmental information is proposed. The model uses (1) the Faster R-CNN as the basic framework, (2) a component perception module to generate a receptive field of integrated environmental information through separable convolution to improve recognition accuracy, and (3) a multi-level Region of Interest (ROI)pooling structure to reduce the deviation caused by rounding in the ROI pooling process. The results showed that the model achieved a recognition accuracy rate of 96.72%, an Intersection Over Union (IOU) of 78.96%, and an average recognition speed for each picture of 1.5 ms; the false alarm rate was 2.35% and the false-negative rate was 3.28%. Compared with other models, the proposed model can effectively enhance the recognition accuracy and recognition speed of forest fire smoke, which provides a technical basis for the real-time and accurate detection of forest fires.

Integration of Environmental Information in a Mining Region Using a Geoportal

At present, the complex nature of the impact on the ecosystem in regions with intensive mining creates a multidimensional information “plume” consisting of data on mineral reserves, the state of mining operations, accumulated, current and future environmental pollution. The transition to the lean use of the subsoil and the reasonable disposal of mining waste requires fundamentally new forms of environmental information accumulation and processing during designing new enterprises and regulating the activities of existing ones. The most promising form of information support for the greening of mining is a geoportal. It is a complex of software and technological support for working with spatial data. Its key task is to provide the users with tools and services for storing and cataloging, publishing and loading spatial and environmental data, searching and filtering by metadata, interactive web visualization, direct access to geodata based on map web services.

Flexibility in the integration of environmental information by Dinoponera quadriceps Kempf during foraging

Flexibility in the integration of environmental information by Dinoponera quadriceps Kempf during foraging

Current Opportunities and Challenges in the Incorporation of the LCA Method in BIM

Background: In the last years, Building Information Modelling (BIM) and Life Cycle Assessment (LCA) have been integrated to support the pursuit of sustainability in the built environment. However, the integration of environmental information with different specificity and reliability requirements on distinct Levels of Development (LOD) of BIM objects was not yet exploited considering several environmental impact categories. Objective: The objective of this paper is to discuss the complexity and depth of LCA information needed for BIM objects, considering different LOD, and to propose a parametrisation of environmental information be included in BIM objects according to their LODs. Methods: A literature review on LCA methodology, sources of LCA information, integration of LCA in BIM, and LOD of BIM objects was initially performed, followed by a detailed characterisation of the different types of sources of LCA information to include in BIM models. These steps contributed to the development of the proposed parametrisation of environmental data. Results: A parametrisation of environmental information to be included in BIM objects was developed. This parametrisation considered the degree at which the element’s information has been specified (LOD) and the respective detail and reliability of the environmental information to include. Conclusion: A new approach is proposed that allows an evolutive integration of environmental information in BIM objects according to their growing LODs.

Task-specific prioritization of reward and effort information: Novel insights from behavior and computational modeling.

Efficient integration of environmental information is critical in goal-directed behavior. Motivational information regarding potential rewards and costs (such as required effort) affects performance and decisions whether to engage in a task. While it is generally acknowledged that costs and benefits are integrated to determine the level of effort to be exerted, how this integration occurs remains an open question. Computational models of high-level cognition postulate serial processing of task-relevant features and demonstrate that prioritizing the processing of one feature over the other can affect performance. We investigated the hypothesis that motivationally relevant task features also may be processed serially, that people may prioritize either benefit or cost information, and that artificially controlling prioritization may be beneficial for performance (by improving task-accuracy) and decision-making (by boosting the willingness to engage in effortful trials). We manipulated prioritization by altering order of presentation of effort and reward cues in two experiments involving preparation for effortful performance and effort-based decision-making. We simulated the tasks with a recent model of prefrontal cortex (Alexander & Brown in Neural Computation, 27(11), 2354-2410, 2015). Human behavior was in line with model predictions: prioritizing reward vs. effort differentially affected performance vs. decision. Prioritizing reward was beneficial for performance, showing striking increase in accuracy, especially when a large reward was offered for a difficult task. Counterintuitively (yet predicted by the model), prioritizing reward resulted in a blunted reward effect on decisions. Conversely, prioritizing effort increased reward impact on decision to engage. These results highlight the importance of controlling prioritization of motivational cues in neuroimaging studies.

Temperature-dependent vitamin D signaling regulates developmental trajectory associated with diapause in an annual killifish

The mechanisms that integrate environmental signals into developmental programs remain largely uncharacterized. Nuclear receptors (NRs) are ligand-regulated transcription factors that orchestrate the expression of complex phenotypes. The vitamin D receptor (VDR) is an NR activated by 1α,25-dihydroxyvitamin D3 [1,25(OH)2D3], a hormone derived from 7-dehydrocholesterol (7-DHC). VDR signaling is best known for regulating calcium homeostasis in mammals, but recent evidence suggests a diversity of uncharacterized roles. In response to incubation temperature, embryos of the annual killifish Austrofundulus limnaeus can develop along two alternative trajectories: active development and diapause. These trajectories diverge early in development, from a biochemical, morphological, and physiological perspective. We manipulated incubation temperature to induce the two trajectories and profiled changes in gene expression using RNA sequencing and weighted gene coexpression network analysis. We report that transcripts involved in 1,25(OH)2D3 synthesis and signaling are expressed in a trajectory-specific manner. Furthermore, exposure of embryos to vitamin D3 analogs and Δ4-dafachronic acid directs continuous development under diapause-inducing conditions. Conversely, blocking synthesis of 1,25(OH)2D3 induces diapause in A. limnaeus and a diapause-like state in zebrafish, suggesting vitamin D signaling is critical for normal vertebrate development. These data support vitamin D signaling as a molecular pathway that can regulate developmental trajectory and metabolic dormancy in a vertebrate. Interestingly, the VDR is homologous to the daf-12 and ecdysone NRs that regulate dormancy in Caenorhabditis elegans and Drosophila We suggest that 7-DHC-derived hormones and their associated NRs represent a conserved pathway for the integration of environmental information into developmental programs associated with life history transitions in animals.

The Drosophila TRPA1 Channel and Neuronal Circuits Controlling Rhythmic Behaviours and Sleep in Response to Environmental Temperature.

trpA1 encodes a thermosensitive transient receptor potential channel (TRP channel) that functions in selection of preferred temperatures and noxious heat avoidance. In this review, we discuss the evidence for a role of TRPA1 in the control of rhythmic behaviours in Drosophila melanogaster. Activity levels during the afternoon and rhythmic temperature preference are both regulated by TRPA1. In contrast, TRPA1 is dispensable for temperature synchronisation of circadian clocks. We discuss the neuronal basis of TRPA1-mediated temperature effects on rhythmic behaviours, and conclude that they are mediated by partly overlapping but distinct neuronal circuits. We have previously shown that TRPA1 is required to maintain siesta sleep under warm temperature cycles. Here, we present new data investigating the neuronal circuit responsible for this regulation. First, we discuss the difficulties that remain in identifying the responsible neurons. Second, we discuss the role of clock neurons (s-LNv/DN1 network) in temperature-driven regulation of siesta sleep, and highlight the role of TRPA1 therein. Finally, we discuss the sexual dimorphic nature of siesta sleep and propose that the s-LNv/DN1 clock network could play a role in the integration of environmental information, mating status and other internal drives, to appropriately drive adaptive sleep/wake behaviour.

Integration of Administrative, Clinical, and Environmental Data to Support the Management of Type 2 Diabetes Mellitus: From Satellites to Clinical Care.

A very interesting perspective of "big data" in diabetes management stands in the integration of environmental information with data gathered for clinical and administrative purposes, to increase the capability of understanding spatial and temporal patterns of diseases. Within the MOSAIC project, funded by the European Union with the goal to design new diabetes analytics, we have jointly analyzed a clinical-administrative dataset of nearly 1.000 type 2 diabetes patients with environmental information derived from air quality maps acquired from remote sensing (satellite) data. Within this context we have adopted a general analysis framework able to deal with a large variety of temporal, geo-localized data. Thanks to the exploitation of time series analysis and satellite images processing, we studied whether glycemic control showed seasonal variations and if they have a spatiotemporal correlation with air pollution maps. We observed a link between the seasonal trends of glycated hemoglobin and air pollution in some of the considered geographic areas. Such findings will need future investigations for further confirmation. This work shows that it is possible to successfully deal with big data by implementing new analytics and how their exploration may provide new scenarios to better understand clinical phenomena.

Multicriterial optimization of liquid food packaging systems

The food industry is in the crossfire of increasing pressure of competition, consumer demands, and growing importance of ecological sustainability considerations. Life cycle analysis is one of the most important methods for evaluation of environmental effects of food industrial technologies and packaging systems. During the last decades there have been an intense work to collect pieces of information on different environmental aspects of food packaging systems all over the world, but there is a considerable gap between the amount of knowledge and its practical application in decision making on the level of enterprises as well as in the process of determination of environmental protection fee. Application of modern, freely available software frameworks for life cycle analysis offers a favourable possibility for integration of environmental information into managerial and governmental decision making processes. Based on case studies, the article demonstrates the possibilities of utilisation of cumulative en...

Predictive modeling of microhabitats for endemic birds in South Chilean temperate forests using Maximum entropy (Maxent)

Temperate forests of Chile exhibit high biodiversity, which generates a wide range of habitats for wildlife. These valuable natural ecosystems have been affected by major natural and anthropogenic processes that have reduced habitats, resulting in serious ecological problems, given both the high endemism of certain avian groups in these forests and the complexity of their habitat selection. Continued degradation and ecosystem problems could lead to the extinction of such groups. In spite of this possibility, ecologically valuable wildlife conservation is seldom integrated into forest management decision-making processes. This study aims to integrate wildlife into forest management, identifying potential habitats for two endemic birds of high ecological value, the Black throated Huet-Huet ( Pteroptochos tarnii), and the Ochre-flanked Tapaculo ( Eugralla paradoxa). Both species inhabit an ecotonal area between evergreen and sclerophyllous forests, making them high-quality bio-indicator species for the degree of conservation of temperate forest. The integration of environmental information and a geostatistical model based on the criterion of maximum entropy (Maxent model) identifies the most important variables that explain the presence of each species. Pteroptochos tarnii is less restrictive in its choice of habitat than Eugralla paradoxa, requiring merely certain topographical condition (elevation, ground slope and aspect). However Eugralla paradoxa requires not only the same topographical features, but also eco-geographical characteristics such as distance to trails, waterways and ecotones. Maxent analysis showed that for both species, the model most capable of predicting their choice of microhabitat was not random based, but rather one based on topographical and environmental variables. The integration of Maxent and Geographic Information Systems (GIS) tools could help to solve problems of wildlife habitat conservation and forest planning.

Gentle supervisory system based on integration of environmental information and social knowledge

PurposeReal‐time multimedia supervisory systems generally include a distributed system that delivers live video input captured with cameras at the watched person's site, using a PC or hand‐held device at the distant supervisor's site. The system comprises many entities such as cameras for image capture, transmission software, network connections, receiver software, a display device, multimedia processing software and hardware, control software, etc. The purpose of this paper is to realize a safe and convenient supervisory system that autonomously provides users with services that fulfill users' requirements related to quality and privacy in a ubiquitous information environment.Design/methodology/approachA system is designed by integrating environmental information acquired from the real world and knowledge related to human social activities. A real space understanding mechanism is proposed to infer the situations and relationships of users by combining sensing information and social knowledge. Social knowledge related to human relationships, the life style of the watched person, home structure, etc. is used with ontology to infer the situations of users.FindingsAn early prototype was implemented for supervising elderly people and some experiments were performed based on several scenarios. Results obtained from some experiments confirmed that this supervisory system can provide real‐time multimedia supervisory services for elderly people, with reasonable quality‐of‐service and privacy that meet the users' requirements.Originality/valueThe system described in this paper assesses the situation of users and surrounding environmental information to provide appropriate supervisory services. This paper provides insight into the design and development of ubiquitous application systems to realize comfortable and safe services using a combination of environmental information and social knowledge.

A multi-agent system for the integration of distributed environmental information

This paper describes a multi-agent platform to be used for the integration of environmental information that may be distributed over a network. The system is designed to work as a collection of collaborating agents. Information sources are encapsulated as data source agents (DSAs) that accept messages in an agent communication language. Here we describe how queries can be entered into the system and information collected from multiple sources. A key component of the query module is the planner agent, which takes a query and transforms it first to a calculus, then to an algebraic expression in order to break it into subqueries which an executor agent can send to the DSAs. As part of this process, the query is translated from user-level ontologies to lower level ontologies relevant to the DSAs. Query results need not be returned within an ACL message, but may instead be represented by a Common Object Request Broker Architecture (CORBA) object reference which may be used to obtain the result set. The architecture and operation of these agent components is described and an example is presented of how environmental information can be queried.

Melatonin and 5-methoxytryptophol (5-ML) in nervous and/or neurosensory structures of a gastropod mollusc ( Helix aspersa maxima): synthesis and diurnal rhythms

Daily patterns of melatonin and 5-methoxytryptophol (5-ML) concentrations and of aryl alkylamine N-acetyltransferase (AA-NAT) and hydroxyindole- O-methyltransferase (HIOMT) activities have been measured in the cerebroid ganglions, visceral ganglions, and ocular tentacles of the gastropod mollusc Helix aspersa maxima. Melatonin concentrations are very low in all the studied structures, except a small peak at the end of the night in the cerebroid ganglions. 5-ML, which is quite undetectable in the cerebroid and visceral ganglions, shows clear daily variations in the ocular tentacles with low values in the middle of the light period and high values during the night. These results are opposite to what is known on daily variations of 5-ML in vertebrates. AA-NAT activity was not detected, while the presence of an HIOMT-like activity supports the hypothesis that 5-ML is synthesized in the ocular tentacles. The temporal relationships existing between the 5-ML rhythm in the ocular tentacles and the hemolymph suggest that 5-ML could be released in the general circulation. These preliminary results suggest that 5-ML could be an informative molecule involved in adaptative processes in the snail and they reinforce the hypothesis that the different 5-methoxyindoles could be implicated in the integration of environmental information.

1A1-B08 移動ロボットのオペレーションのための環境情報の統合

移動ロボットが未知の環境において活動するためには, 周辺環境を得ることが必要不可欠である。しかしながらミッションを行うための重要な情報だけを選別していくようなシステムは存在しない。そこで, データベースを用いて計測情報や地形情報などを一元的に管理する手法を提案する。本研究では, 仮想DEMを用いた地形のモデリングとともに, 環境情報のサンプルを用いた情報の統合手法について検討する。

Environmental information systems based on enterprise resource planning

This paper describes the consequences of the integration of environmental information within enterprise resource planning (ERP) systems. The state‐of‐the art of dedicated environmental information systems is briefly discussed. Essentials and peculiarities of environmental information are highlighted. The role of environmental management systems and their relationship with other dedicated management systems is positioned within this field. The need for information following from this is compared with the information available in current ERP systems. The common features of both information systems are discussed and the importance of physical relationships within them is demonstrated. A physical approach is argued as the very base of future extended ERP systems. An outline of the special character of physical information is presented for this purpose. Subsequently, some restrictions connected to the current approach in ERP are analysed. This results in a number of recommendations. The most crucial aspects are the integration of the process and discrete manufacturing orientation by applying a multiple‐input multiple‐output approach to all processes, and a similar consideration of co‐products, by‐products, wastes and emissions.