Reduction capability of soil humic substances from the Rio Negro basin, Brazil, towards Hg(II) studied by a multimethod approach and principal component analysis (PCA)

This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro, AM, Brazil. (c) 2007 Published by Elsevier B.V.

Direct determination of Cu, Cd, Ni and Pb in aquatic humic substances by graphite furnace atomic absorption spectrometry

A method has been developed for the direct determination of Cu, Cd, Ni and Pb in aquatic humic substances (AHS) by graphite furnace atomic absorption spectrometry. AHS were isolated from water samples rich in organic matter, collected in the Brazilian Ecological Parks. All analytical curves presented good linear correlation coefficient. The limits of detection and quantification were in the ranges 2.5-16.7 mu g g(-1) and 8.5-50.0 mu g g(-1), respectively. The accuracy was determined using recovery tests, and for all analytes recovery percentages ranged from 93 - 98 %, with a relative standard deviation less than 4 %. The results indicated that the proposed method is a suitable alternative for the direct determination of metals in AHS.

Characterization of the Interactions between Endocrine Disruptors and Aquatic Humic Substances from Tropical Rivers

Interactions between two endocrine disruptors (ED) and aquatic humic substances (AHS) from tropical rivers were studied using an ultrafiltration system equipped with a 1 kDa cut-off cellulose membrane to separate free ED from the fraction bound in the AHS. Quantification of 17 alpha-ethynylestradiol and bisphenol A was performed using gas chromatography-mass spectrometry (GC-MS). The times required for establishment of equilibrium between the AHS and the ED were ca. 30 min, and complexation capacities for 17 alpha-ethynylestradiol and bisphenol A were 18.53 and 2.07 mg g(-1) TOC, respectively. The greater interaction of AHS with 17 alpha-ethynylestradiol, compared to bisphenol A, was due to the presence of hydrogen in the structure of 17 alpha-ethynylestradiol, which could interact with ionized oxygenated groups of the AHS. The results indicate that AHS can strongly influence the transport and reactivity of endocrine disruptors in aquatic systems.

Thermal Decomposition Kinetics of Humic Substances Extracted from Mid-Rio Negro (Amazon Basin) Soil Samples

In this work humic substances (HS) extracted from non-flooded (Araca) and flooded (Iara) soils were characterized through the calculation of stability and activation energies associated with the dehydration and thermal decomposition of HS using TGA and DTA, electronic paramagnetic resonance and C/H, C/N and C/O atomic ratios. For HS extracted from flooded soils, there was evidence for the influence of humidity on the organic matter humification process. Observations of thermal behaviour, with elemental analysis, indicated the presence of fossilized organic carbon within clay particles, which only decomposed above 800 C. This characteristic could explain the different thermal stability and pyrolysis activation energies for Iara HS compared to Araca HS.

Peat humic substances enriched with nutrients for agricultural applications: Competition between nutrients and non-essential metals present in tropical soils

Improved agricultural productivity, and reduction of environmental impacts, require studies of the interactions between different soil components. Fertilizers marketed as "organic" or "natural", such as peats or humic substances (HS) extracted from peats, are enriched with macro and micronutrients that, according to the manufacturers, are released to the plant in accordance with its needs. This work investigates the complexation capacity of HS for macro and micronutrient metal species, considering the competition, for HS complexation sites, between non-essential metals (aluminium and lead), present in the soil, and the nutrients. Humic substances were found to possess strong affinities for Pb(II) and Al(III), forming stable complexes, with concomitant release of complexed nutrients. Although HS are already used commercially as organic fertilizers, further studies of methods of HS enrichment, aimed at avoiding losses, are highly desirable from environmental and economic perspectives. (C) 2009 Elsevier B.V. All rights reserved.

Ontology-Based Workflow Design for the Coordination of Homecare Interventions

Part 20: Health and Care Networks

Building an Ontology of Product/Service-Systems: Using a Maritime Case Study to Elicit Classifications and Characteristics

Part 4: Transition Towards Product-Service Systems

Ontology forecasting in scientific literature:semantic concepts prediction based on innovation-adoption priors

The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t + 1, using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.

Potential valorization as fertilizers of Humic Substances extracted from landfill leachate

In this study, four leachates samples from 3 different landfills localized in the north of Portugal were characterized and fractionated, to understand the decomposition degree and to evaluate their potential as an agent for fertilization. Humic substances (HS) were extracted, quantified, chemical characterized and further fractionated in humic acid (HA) and fulvic acid (FA). Keeping in mind the purpose to use these fractions as fertilizers, the phytotoxicity of HS, HA and FA solutions was evaluated on cress seed germination. The HS concentration was similar for all the leachates evaluated and was higher than 780 mg/L of total organic carbon. All the leachates analysed registered higher FA concentration than HA. The chemical characterization indicated that HA had a relatively higher aromatic character than the FA obtained from same sources. These results suggest that the HS from landfill leachates were in an early stage of humification, once the degree of humification increase as the landfilling age increase. Overall, the HS extracts showed absence of phytotoxicity, with germination index greater than 80% for samples treated to achieve low electric conductivity values. This suggests that the HS from the leachate may be used to produce liquid organic fertilizers.

Forms, Foundations, and the Ethos of Foremost: Zen Practice, Epistemology, and Ontology in Reflective Knowledge Organization

In reflecting on the practice of knowledge organization, we tacitly or explicitly root our conceptions of work and its value in some epistemic and ontological foundation. Zen Buddhist philosophy offers a unique set of conceptions vis-à-vis organizing, indexing, and describing documents.When we engage in knowledge organization, we are setting our mind to work with an intention. We intend to make some sort of intervention. We then create a form a realization of an abstraction (like classes or terms) [1], we do this from a foundation of some set of beliefs (epistemology, ontology, and ethics), and because we have to make decisions about what to privilege, we need to decide what is foremost in our minds. We must ask what is the most important thing?Form, foundation, and the ethos of foremost require evoke in our reflection on work number of ethical, epistemic, and ontological concerns that ripple throughout our conceptions of space, “good work”, aesthetics, and moral mandate [2,3]. We reflect on this.

Assessing the risk of groundwater contamination from organic substances in sewage sludge.

In this work, the risk of groundwater contamination from organic substances in sewage sludge from wastewater treatment stations was evaluated in its worst case. The sewage sludge was applied as fertilizer in corn culture, prioritizing the substances for monitoring. The assessing risk took place in a Typic Distrophic Red Latossol (TDRL) area, in the county district of Jaguariúna, SP. The simulators CMLS-94 and WGEN were used to evaluate the risk of twenty-eight organic substances in sewage sludge to leach to groundwater. The risk of groundwater contamination was accomplished for a single sludge dose application in a thousand independent and equally probable years, simulated to esteem the substances leaching in one year after the application date of the sludge. It is presented the substances that should be priorly monitored in groundwater.

Synergies among safety and security in the prevention of major accidents related to dangerous substances

Historical evidence shows that chemical, process, and Oil&Gas facilities where dangerous substances are stored or handled are target of deliberate malicious attacks (security attacks) aiming at interfering with normal operations. Physical attacks and cyber-attacks may generate events with consequences on people, property, and the surrounding environment that are comparable to those of major accidents caused by safety-related causes. The security aspects of these facilities are commonly addressed using Security Vulnerability/Risk Assessment (SVA/SRA) methodologies. Most of these methodologies are semi-quantitative and non-systematic approaches that strongly rely on expert judgment, leading to security assessments that are not reproducible. Moreover, they do not consider the synergies with the safety domain. The present 3-year research is aimed at filling the gap outlined by providing knowledge on security attacks, as well as rigorous and systematic methods supporting existing SVA/SRA studies suitable for the chemical, process, and Oil&Gas industry. The different nature of cyber and physical attacks resulted in the development of different methods for the two domains. The first part of the research was devoted to the development and statistical analysis of security databases that allowed to develop new knowledge and lessons learnt on security threats. Based on the obtained background, a Bow-Tie based procedure and two reverse-HazOp based methodologies were developed as hazard identification approaches for physical and cyber threats respectively. To support the quantitative estimation of the security risk, a quantitative procedure based on the Bayesian Network was developed allowing to calculate the probability of success of physical security attacks. All the developed methods have been applied to case studies addressing chemical, process and Oil&Gas facilities (offshore and onshore) proving the quality of the results that can be achieved in improving site security. Furthermore, the outcomes achieved allow to step forward in developing synergies and promoting integration among safety and security management.

Empirical ontology design patterns

Knowledge graphs (KGs) and ontologies have been widely adopted for modelling numerous domains. However, understanding the content of an ontology/KG is far from straightforward: existing methods partially address this issue. This thesis is based on the assumption that identifying the Ontology Design Patterns (ODPs) in an ontology or a KG contributes to address this problem. Most times, the reused ODPs are not explicitly annotated, or their reuse is unintentional. Therefore, there is a challenge to automatically identify ODPs in existing ontologies and KGs, which is the main focus of this research work. This thesis analyses the role of ODPs in ontology engineering, through experiences in actual ontology projects, placing this analysis in the context of existing ontology reuse approaches. Moreover, this thesis introduces a novel method for extracting empirical ODPs (EODPs) from ontologies, and a novel method for extracting EODPs from knowledge graphs, whose schemas are implicit. The first method groups the extracted EODPs in clusters: conceptual components. Each conceptual component represents a modelling problem, e.g. representing collections. As EODPs are fragments possibly extracted from different ontologies, some of them will fall in the same cluster, meaning that they are implemented solutions to the same modelling problem. EODPs and conceptual components enable the empirical observation and comparison of modelling solutions to common modelling problems in different ontologies. The second method extracts EODPs from a KG as sets of probabilistic axioms/constraints involving the ontological entities instantiated. These EODPs may support KG inspection and comparison, providing insights on how certain entities are described in a KG. An additional contribution of this thesis is an ontology for annotating ODPs in ontologies and KGs.

Monitoring of New Psychoactive Substances in the hair of patients with a history of addiction. Evaluation of the public health impact.

Introduction. The term New Psychoactive Substances (NPS) encompasses a broad category of drugs which have become available on the market in recent years and whose illicit use for recreational purposes has recently exploded. The analysis of NPS usually requires mass spectrometry based techniques. The aim of our study was to define the preva-lence of NPS consumption in patients with a history of drug addiction followed by Public Services for Pathological Addictions, with the purpose of highlighting the effective presence of NPS within the area of Bologna and evaluating their association with classical drugs of abuse (DOA). Materials and methods. Sustained by literature, a multi-analyte UHPLC-MS/MS method for the identification of 127 NPS (phenethylamines, arylcyclohexylamines, synthetic opioids, tryptamines, synthetic cannabinoids, synthetic cathinones, designer benzodiazepines) and 15 classic drugs of abuse (DOA) in hair samples was developed and validated according to International Guidelines [112]. Samples pretreatment consisted of washing steps and overnight incubation at 45°C in an acid mixture of methanol and water. After cooling, supernatant were injected into the chromatographic system coupled with a tandem mass spectrometry detector. Results. Successful validation was achieved for almost all of the compounds. The method met all the required technical parameters. LOQ was set from 4 to 80 pg/mg The developed method was applied to 107 cases (85 males and 22 females) of clinical interest. Out of 85 hair samples resulting positive to classical drugs of abuse, NPS were found in twelve (8 male and 4 female). Conclusion. The present methodology represents an easy, low cost, wide-panel method for the de-tection of 127 NPS and 15 DOA in hair samples. Such multi-analyte methods facilitates the study of the prevalence of drugs abused that will enable the competent control authorities to obtain evi-dence-based reports regarding the critical spread of the threat represented by NPS.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.