Chlorinated hydrocarbons in Coastal Lagoon of the Pacific Coast of Nicaragua

A screening for persistent chlorinated hydrocarbons was carried out in December 1995 in the main coastal lagoons on the Pacific side of Nicaragua, where most of the country’s agriculture and pesticide use has been taking place for decades. Results for a wide range of organochlorine pesticides in lagoon sediments show levels that generally were very low in Estero Real, Estero Padre Ramos, and estuary of San Juan del Sur. For example, total DDTs in these lagoons averaged 4.5 6 3.4 ng g21 dry weight, which may be considered a baseline level for the region. Other compounds such as HCHs, BHC, endosulfan, heptachlor, endrin, toxaphene, and aroclors were present in concentrations even lower, generally below 1 ng g21 dry weight. However, sediments of the Esteros Naranjo–Paso Caballos system at Chinandega district contained pesticide residues in much higher levels, attaining maximum values of 1,420 ng g21 and 270 ng g21 dry weight, respectively, for toxaphene and total DDTs. Other compounds such as aroclors, chlordane, endosulfan, and dieldrin were also present in the sediments of this lagoon system, but in lower concentrations. The very high concentrations of toxaphene and DDTs in this lagoon are a result of the intensive use of these pesticides in cotton growing in the district of Chinandega. Due to the long environmental half-lives of these compounds (t1⁄2 . 10 years in temperate soils), their concentrations in lagoon sediments will likely remain high for years to come. Based on these results, the development of the new shrimp farming activities in the Pacific coastal lagoons should be restricted to selected areas. The intensive use of pesticides in Nicaragua, which for decades has been one of the biggest pesticide importers and users in Central America (Appel 1991; Castillo et al. 1997), is likely to cause severe contamination of aquatic systems. In particular halogenated hydrocarbons, including chlorinated pesticides and industrial chemicals such as the polychlorinated biphenyls (PCBs), are lipophilic toxic compounds that bioaccumulate and transfer in the food chain. Introduced in aquatic environments these chemicals may compromise the health of the ecosystems (Tardiff 1991). This is the case for the coastal lagoons of the Pacific coast of Nicaragua, where most of the country’s agriculture and population have been concentrated. In particular, cotton growing, a pesticide intensive agriculture started in the 1950s, was developed in this region of Nicaragua (Appel 1991). The degradation of these coastal lagoon systems, especially the reduction of mangrove forest and overexploitation of fishery resources, has received focused attention from national authorities. Agrochemical residues are suspected in the degradation of these lagoons, but have not been investigated. Furthermore, with the plans for developing shrimp rearing farms in these coastal lagoons (esteros), contamination by agrochemical residues becomes a matter of much concern for the future of this industry. To provide information on the potential impacts from agriculture and urban development, a screening of the contaminants was carried out in the main lagoons of the Pacific coast. This paper presents the results of the analyses of chlorinated hydrocarbons in lagoon sediments and discusses the ecotoxicological hazard posed by the current levels of persistent pesticide residues to aquatic biota

Computational Experiments with Minimum-Distance Controlled Perturbation Methods

Abstract. Minimum-distance controlled perturbation is a recent family of methods for the protection of statistical tabular data. These methods are both efficient and versatile, since can deal with large tables of any structure and dimension, and in practice only need the solution of a linear or quadratic optimization problem. The purpose of this paper is to give insight into the behaviour of such methods through some computational experiments. In particular, the paper (1) illustrates the theoretical results about the low disclosure risk of the method; (2) analyzes the solutions provided by the method on a standard set of seven difficult and complex instances; and (3) shows the behaviour of a new approach obtained by the combination of two existing ones

Corrigendum to “Golden carbon of Sargassum forests revealed as an opportunity for climate change mitigation” [Sci. Total Environ., 729 (2020) Start page – End page/ 138745]

info:eu-repo/semantics/publishedVersio

Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions

Several network flows heuristics have been suggested in the past for the solution of the complementary suppression problem. However, a limited computational experience using them is reported in the literature, and, moreover, they were only appropriate for two-dimensional tables. The purpose of this paper is twofold. First, we perform an em-pirical comparison of two network flows heuristics. They are improved versions of already existing approaches. Second, we show that exten-sions of network flows methods (i.e., multicommodity network flows and network flows with side constraints) can model three-dimensional, hierarchical and linked tables. Exploiting this network structure can improve the performance of any solution method solely based on linear programming formulations

Identifying clinical clusters with distinct trajectories in first-episode psychosis through an unsupervised machine learning technique

The extreme variability in symptom presentation reveals that individuals diagnosed with a first-episode psychosis (FEP) may encompass different sub-populations with potentially different illness courses and, hence, different treatment needs. Previous studies have shown that sociodemographic and family environment factors are associated with more unfavorable symptom trajectories. The aim of this study was to examine the dimensional structure of symptoms and to identify individuals’ trajectories at early stage of illness and potential risk factors associated with poor outcomes at follow-up in non-affective FEP. One hundred and forty-four non-affective FEP patients were assessed at baseline and at 2-year follow-up. A Principal component analysis has been conducted to identify dimensions, then an unsupervised machine learning technique (fuzzy clustering) was performed to identify clinical subgroups of patients. Six symptom factors were extracted (positive, negative, depressive, anxiety, disorganization and somatic/cognitive). Three distinct clinical clusters were determined at baseline: mild; negative and moderate; and positive and severe symptoms, and five at follow-up: minimal; mild; moderate; negative and depressive; and severe symptoms. Receiving a low-dose antipsychotic, having a more severe depressive symptomatology and a positive family history for psychiatric disorders were risk factors for poor recovery, whilst having a high cognitive reserve and better premorbid adjustment may confer a better prognosis. The current study provided a better understanding of the heterogeneous profile of FEP. Early identification of patients who could likely present poor outcomes may be an initial step for the development of targeted interventions to improve illness trajectories and preserve psychosocial functioning

Statistical disclosure control in tabular data

Data disseminated by National Statistical Agencies (NSAs) can be classified as either microdata or tabular data. Tabular data is obtained from microdata by crossing one or more categorical variables. Although cell tables provide aggregated information, they also need to be protected. This chapter is a short introduction to tabular data protection. It contains three main sections. The first one shows the different types of tables that can be obtained, and how they are modeled. The second describes the practical rules for detection of sensitive cells that are used by NSAs. Finally, an overview of protection methods is provided, with a particular focus on two of them: “cell suppression problem” and “controlled tabular adjustment”.Postprint (published version