Muestreadores pasivos en el estudio de la dinámica de plaguicidas y el impacto ambiental en el agua

RESUMEN: Los plaguicidas son las sustancias con mayor aplicación en la agricultura las cuales pueden contaminar los cuerpos de agua por descarga directa o indirecta, pero los grandes volúmenes y los procesos transformación pueden disminuir la concentración de estas sustancias y sus productos de degradación en las cuencas. Actualmente, los métodos convencionales de extracción tales como: la extracción en fase sólida (SPE) y la micro extracción en fase sólida (SPME) entre otras, no permiten bajos límites de detección, sin embargo bajos niveles de pesticidas y productos de degradación podrían producir toxicidad crónica en diferentes especies. Actualmente el muestreo pasivo es ampliamente usado en el monitoreo de plaguicidas y para el aseguramiento de la calidad del agua debido a que esta metodología es aplicada in estudios de bioacumulación y deteccion a partes por cuatrillón (ppq). Las membranas con mayor uso en el muestreo pasivo son las membranas tipo SPMD (Semi-permeable membrane devices), las cuales permiten la concentración de sustancias lipofílicas y las membranas tipo POCIS (Polar organic chemistry integrative sampler), las cuales permiten concentrar sustancias hidrofílicas. Esta revisión cubre la aplicación de los muestreadores pasivos en el análisis de plaguicidas, en los estudios de biacumulación y en la evaluación de los riesgos ecotoxicológicos. Finalmente los muestreadores pasivos permiten reducir costos, el tiempo de concentración y la cantidad de solventes orgánicos empleados en el tratamiento de muestra, lo que conduce a su clasificación dentro de las tendencias de la “química analítica verde”.ABSTRACT: Pesticides are the most applied substances in agricultural activities which can contaminate water bodies by direct or indirect discharge, but large volumes and natural transformation processes can decrease the concentration of these substances and their degradates in watershed. Currently, conventional extraction methods such as: solid phase extraction (SPE) and solid phase micro extraction (SPME) among others do not permit low detection limits. However low levels of pesticides and degradates could produce chronic toxicity in different species. Nowadays, passive sampling is widespread used for monitoring pesticides and for ensuring the water quality and bioaccumulation studies due to this methodology allows the detection of pollutant from parts per quadrillion (ppq). The most popular membranes used in passive sampling are the semipermeable membrane devices (SPMD), which permit the concentration of lipophilic substances and the polar organic chemical integrative sampler (POCIS), which permits concentration of the hydrophilic ones. This review is about the application of passive samplers in pesticides analysis, the importance of these devices in the bioaccumulation studies and the evaluation of the ecotoxicological risks. Finally, passive sampling allows reducing costs, time and the amount of organic solvent used which classifies it within the environmental trends of “green analytical chemistry”

Misleading signatures of quantum chaos

The main signature of chaos in a quantum system is provided by spectral statistical analysis of the nearest-neighbor spacing distribution P(s) and the spectral rigidity given by the Delta(3)(L) statistic. It is shown that some standard unfolding procedures, such as local unfolding and Gaussian broadening, lead to a spurious saturation of Delta(3)(L) that spoils the relationship of this statistic with the regular or chaotic motion of the system. This effect can also be misinterpreted as Berry's saturation

Measuring the Quality of Model-Driven Projects with NDT-Quality

Model-driven web engineering (MDWE) is a new paradigm which provides satisfactory results in the development of web software systems. However, as can be concluded from several research works, MDWE provokes traceability problems and the necessity of managing constraints in metamodel instances and transformation executions. The management of these aspects is usually executed manually in the most of MDWE approaches. Nevertheless, model-driven paradigm itself can offer suitable ways to manage them. This chapter presents NDT-Quality, an approach to measure the quality of web projects developed with NDT (navigational development techniques), and offers a view about the application of this tool in real web projects.Ministerio de Educación y Ciencia TIN2007-67843-C06-03Ministerio de Educación y Ciencia TIN2007-30391-

Effectiveness and Safety of a Single-Dose Ivermectin Treatment for Uncomplicated Strongyloidiasis in Immunosuppressed Patients (ImmunoStrong Study): The Study Protocol

Strongyloidiasis affects an estimated 600 million people worldwide, especially in tropical and subtropical areas. Single-dose ivermectin treatment has shown to be effective among immunocompetent patients with uncomplicated strongyloidiasis. Here, we present the protocol of the ImmunoStrong study, a prospective observational study aiming to evaluate the effectiveness and safety of a single-dose ivermectin for treatment of uncomplicated strongyloidiasis in immunosuppressed patients. The secondary objectives are to assess accuracy of molecular techniques for the follow-up of these patients and to determine the population pharmacokinetics of ivermectin. The information retrieved by this study will cover relevant information gaps in the strongyloidiasis management among immunosuppressed patients.The present work was supported by the 2020 Research Grant from the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC).S

Encoding generative adversarial networks for defense against image classification attacks

Image classification has undergone a revolution in recent years due to the high performance of new deep learning models. However, severe security issues may impact the performance of these systems. In particular, adversarial attacks are based on modifying input images in a way that is imperceptible for human vision, so that deep learning image classifiers are deceived. This work proposes a new deep neural network model composed of an encoder and a Generative Adversarial Network (GAN). The former encodes a possibly malformed input image into a latent vector, while the latter generates a reconstructed image from the latent vector. Then the reconstructed image can be reliably classified because our model removes the deleterious effects of the attack. The experiments carried out were designed to test the proposed approach against the Fast Gradient Signed Method attack. The obtained results demonstrate the suitability of our approach in terms of an excellent balance between classification accuracy and computational cost.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Sonication of intramedullary nails: Clinically-related infection and contamination

Background and Aim: Sonication is currently considered the best procedure for microbiological diagnosis of implant-related osteoarticular infection, but studies in nail-related infections are lacking. The study aim was to evaluate implant sonication after intramedullary nail explantation, and relate it to microbiological cultures and clinical outcome. Patients and Methods: A study was performed in two University Hospitals from the same city. Thirty-one patients with implanted nails were prospectively included, whether with clinical infection (8 cases) or without (23 cases). Retrieved nails underwent sonication according a previously published protocol. The clinical and microbiological outcome patient was related to the presence of microorganisms in the retrieved implant. Results: Positive results appeared in 15/31 patients (9 with polymicrobial infections) almost doubling those clinically infected cases. The most commonly isolated organisms were Staphylococcus epidermidis (19.2 %) and Staphylococcus aureus (15.4 %). A significant relationship was found between the presence of positive cultures and previous local superficial infection (p=0.019). The presence of usual pathogens was significantly related to clinical infection (p=0.005) or local superficial infection (p=0.032). All patients with positive cultures showed pain diminution or absence of pain after nail removal (15/15), but this only occurred in 8 (out of 16) patients with negative cultures. Conclusions: In patients with previously diagnosed infection or local superficial infection, study of the hardware is mandatory. In cases where pain or patient discomfort is observed, nail sonication can help diagnose the implant colonization with potential pathogens that might require specific treatment to improve the final outcomePart of this work was funded by grants from the Comunidad de Madrid (S2009/MAT-1472) and from the CONSOLIDER-INGENIO Program (FUNCOAT-CSD2008- 00023). DMM was funded by a grant from the Fundación Conchita Rábago de Jiménez Día

Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)

Abstract Background Spatial analysis is a relevant set of tools for studying the geographical distribution of diseases, although its methods and techniques for analysis may yield very different results. A new hybrid approach has been applied to the spatial analysis of treated prevalence of depression in Catalonia (Spain) according to the following descriptive hypotheses: 1) spatial clusters of treated prevalence of depression (hot and cold spots) exist and, 2) these clusters are related to the administrative divisions of mental health care (catchment areas) in this region. Methods In this ecological study, morbidity data per municipality have been extracted from the regional outpatient mental health database (CMBD-SMA) for the year 2009. The second level of analysis mapped small mental health catchment areas or groups of municipalities covered by a single mental health community centre. Spatial analysis has been performed using a Multi-Objective Evolutionary Algorithm (MOEA) which identified geographical clusters (hot spots and cold spots) of depression through the optimization of its treated prevalence. Catchment areas, where hot and cold spots are located, have been described by four domains: urbanicity, availability, accessibility and adequacy of provision of mental health care. Results MOEA has identified 6 hot spots and 4 cold spots of depression in Catalonia. Our results show a clear spatial pattern where one cold spot contributed to define the exact location, shape and borders of three hot spots. Analysing the corresponding domain values for the identified hot and cold spots no common pattern has been detected. Conclusions MOEA has effectively identified hot/cold spots of depression in Catalonia. However these hot/cold spots comprised municipalities from different catchment areas and we could not relate them to the administrative distribution of mental care in the region. By combining the analysis of hot/cold spots, a better statistical and operational-based visual representation of the geographical distribution is obtained. This technology may be incorporated into Decision Support Systems to enhance local evidence-informed policy in health system research.</p

Heterogeneous Olefin Aziridination Reactions Catalyzed by Polymer-Bound Tris(triazolyl)methane Copper Complexes

Efficient olefin aziridination has been achieved with a tris(triazolyl)methane copper catalyst supported onto polystyrene. Aryl, alkyl and methoxycarbonyl-substituted olefins are converted into N-tosylaziridines in good to high yields. The solid catalyst is readily separated by filtration and recycled, allowing its reuse with no significant loss of the catalytic activity

Vehicle Classification in Traffic Environments Using the Growing Neural Gas

Traffic monitoring is one of the most popular applications of automated video surveillance. Classification of the vehicles into types is important in order to provide the human traffic controllers with updated information about the characteristics of the traffic flow, which facilitates their decision making process. In this work, a video surveillance system is proposed to carry out such classification. First of all, a feature extraction process is carried out to obtain the most significant features of the detected vehicles. After that, a set of Growing Neural Gas neural networks is employed to determine their types. A qualitative and quantitative assessment of the proposal is carried out on a set of benchmark traffic video sequences, with favorable results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech