Occupational exposure to poultry dust and effects on the respiratory system in workers

Farmers are occupationally exposed to many respiratory hazards at work and display higher rates of asthma and respiratory symptoms than other workers. Dust is one of the components present in poultry production that increases risk of adverse respiratory disease occurrence. Dust originates from poultry residues, molds, and feathers and is biologically active as it contains microorganisms. Exposure to dust is known to produce a variety of clinical responses, including asthma, chronic bronchitis, chronic airways obstructive disease (COPD), allergic alveolitis, and organic dust toxic syndrome (ODTS). A study was developed to determine particle contamination in seven poultry farms and correlate this with prevalence rate of respiratory defects and record by means of a questionnaire the presence of clinical symptoms associated with asthma and other allergy diseases by European Community Respiratory Health Survey. Poultry farm dust contamination was found to contain higher concentrations of particulate matter (PM) PM5 and PM10. Prevalence rate of obstructive pulmonary disorders was higher in individuals with longer exposure regardless of smoking status. In addition, a high prevalence for asthmatic (42.5%) and nasal (51.1%) symptoms was noted in poultry workers. Data thus show that poultry farm workers are more prone to suffer from respiratory ailments and this may be attributed to higher concentrations of PM found in the dust. Intervention programs aimed at reducing exposure to dust will ameliorate occupational working conditions and enhance the health of workers.

Residential property loans and performance during property price booms: evidence from European banks

Understanding the performance of banks is of the utmost relevance, because of the impact of this sector on economic growth and financial stability. Of all the different assets that make up a bank portfolio, the residential mortgage loans constitute one of its main. Using the dynamic panel data method, we analyse the influence of residential mortgage loans on bank profitability and risk, using a sample of 555 banks in the European Union (EU-15), over the period from 1995 to 2008. We find that banks with larger weights of residential mortgage loans show lower credit risk in good times. This result explains why banks rush to lend on property during booms due to the positive effects it has on credit risk. The results show further that credit risk and profitability are lower during the upturn in the residential property price cycle. The results also reveal the existence of a non-linear relationship (U-shaped marginal effect), as a function of bank’s risk, between profitability and the residential mortgage loans exposure. For those banks that have high credit risk, a large exposure of residential mortgage loans is associated with higher risk-adjusted profitability, through lower risk. For banks with a moderate/low credit risk, the effects of higher residential mortgage loan exposure on its risk-adjusted profitability are also positive or marginally positive.

Residential property loans and performance during property price booms: evidence from European

Understanding the performance of banks is of the u tmost importance due to the impact the sector may have on economic growth and financial stability. Residential mortgage loans constitute a large proportion of the portfolio of many banks and are one of the key assets in the determination of performance. Using a dynamic panel model , we analyse the impact of res idential mortgage loans on bank profitability and risk , based on a sample of 555 banks in the European Union ( EU - 15 ) , over the period from 1995 to 2008. We find that banks with larger weight s in residential mortgage loans display lower credit risk in good market conditions . This result may explain why banks rush to lend on property during b ooms due to the positive effect it has on credit risk . The results also show that credit risk and profitability are lower during the upturn in the residential property cy cle. Furthermore, t he results reveal the existence of a non - linear relationship ( U - shaped marginal effect), as a function of bank’s risk, between profitability and residential mortgage exposure . For those banks that have high er credit risk, a large exposur e to residential loans is associated with increased risk - adjusted profitability, through a reduction in risk. For banks with a moderate to low credit risk, the impact of higher exposure are also positive on risk - adjusted profitability.

Self-assembly in chains, rings, and branches: a single component system with two critical points

Agências financiadoras: FCT - PEstOE/FIS/UI0618/2011; PTDC/FIS/098254/2008 ERC-PATCHYCOLLOIDS e MIUR-PRIN

Clustering and selecting categorical features

In data clustering, the problem of selecting the subset of most relevant features from the data has been an active research topic. Feature selection for clustering is a challenging task due to the absence of class labels for guiding the search for relevant features. Most methods proposed for this goal are focused on numerical data. In this work, we propose an approach for clustering and selecting categorical features simultaneously. We assume that the data originate from a finite mixture of multinomial distributions and implement an integrated expectation-maximization (EM) algorithm that estimates all the parameters of the model and selects the subset of relevant features simultaneously. The results obtained on synthetic data illustrate the performance of the proposed approach. An application to real data, referred to official statistics, shows its usefulness.

An information model for lean, agile, resilient and green supply chain management

Dissertação para a obtenção de Grau de Mestre em Engenharia e Gestão Industrial

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.

Lean, agile, resilient and green supply chain management interoperability assessment methodology

Dissertação para obtenção de grau de Mestre em Engenharia e Gestão Industrial (MEGI)

American cutaneous leishmaniasis: presentation and problems of patient management

We report our experience with the diagnosis and treatment of 60 patients with American cutaneous leishmaniasis. They were infected in Panama (55), Brazil (4) or Colombia (I). Among 35 patients with a 3 week exposure in Panama, the mean maximum incubation period was 33 days (range 4-81 days). Diagnosis was delayed an average of 93 days after onset of skin lesions, due to the patient's delay in seeking medical attention (31 days), medical personnel's delay in considering the diagnosis (45 days), and the laboratory's delay in confirming the diagnosis (17 days). Forty-four patients (73%) developed ulcers typical of cutaneous leishmaniasis. Sixteen additional patients (27%) had atypical macular, papular, squamous, verrucous or acneiform skin lesions that were diagnosed only because leishmanial cultures were obtained. Of the 59 patients treated with pentavalent antimonial drugs, only 34 (58%) were cured after the first course of treatment. Lesions which were at least 2 cm in diameter, ulcerated, or caused by Leishmania braziliensis were less likely to be cured after a single course of treatment than were lesions smaller than 2 cm, nonulcerated or caused by Leishmania mexicana or Leishmania donovani.

A simulation model for lean, agile, resilient and green supply chain management: practices and interoperability assessment

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Methanogens, sulphate and heavy metals: a complex system

Anaerobic digestion (AD) is a well-established technology used for the treatment of wastes and wastewaters with high organic content. During AD organic matter is converted stepwise to methane-containing biogasa renewable energy carrier. Methane production occurs in the last AD step and relies on methanogens, which are rather sensitive to some contaminants commonly found in wastewaters (e.g. heavy metals), or easily outcompeted by other groups of microorganisms (e.g. sulphate reducing bacteria, SRB). This review gives an overview of previous research and pilot-scale studies that shed some light on the effects of sulphate and heavy metals on methanogenesis. Despite the numerous studies on this subject, comparison is not always possible due to differences in the experimental conditions used and parameters explained. An overview of the possible benefits of methanogens and SRB co-habitation is also covered. Small amounts of sulphide produced by SRB can precipitate with metals, neutralising the negative effects of sulphide accumulation and free heavy metals on methanogenesis. Knowledge on how to untangle and balance sulphate reduction and methanogenesis is crucial to take advantage of the potential for the utilisation of biogenic sulphide as a metal detoxification agent with minimal loss in methane production in anaerobic digesters.

Diseño y evaluación de alternativas de manejo sustentable para la recuperación y conservación de bosques degradados de la región del Espinal en la provincia de Córdoba. Design and evaluation of sustainable management alternatives for the recovery and conservation of degraded forest in the Espinal Region in Córdoba province.

El avance de la frontera agropecuaria y la urbanización han reducido la superficie boscosa del Espinal en Córdoba a fragmentos que son sumamente valiosos como relictos del ambiente original del Algarrobal y como barreras frente a la acción erosiva del agua y los vientos. Por su estructura, degradada y enmarañada, el productor agropecuario generalmente los visualiza como una molestia ya que le restan superficie apta para el cultivo y resultan poco aprovechables para el pastoreo de los animales. Bajo pautas de manejo adecuadas estos bosquecillos podrían rehabilitarse para el aprovechamiento del ganado y otros usos complementarios. Para que el productor local cuente con herramientas de manejo sustentable de sus recursos naturales es necesario generar información confiable para la zona. En ese contexto, se plantea la siguiente Hipótesis General: Existen alternativas de manejo que, aplicadas sobre los bosques del Espinal, permiten recuperar y conservar la biodiversidad a la vez que mejoran la rentabilidad del productor. El Objetivo General es diseñar y evaluar, en términos ecológicos, tecnológicos y socio-económicos, alternativas de manejo sustentable de bosques degradados del Espinal de la provincia de Córdoba tendientes a su recuperación y conservación. El proyecto se localizará en el bosque fragmentado del Campo Escuela de la FCA-UNC. Se establecerán parcelas con distintos niveles de cobertura arbustiva en las que se medirán el efecto de los arbustos sobre la regeneración de especies arbóreas deseables, la producción y calidad de la pastura, el crecimiento de los árboles y las condiciones edáficas del sistema. Además, la incidencia del ganado vacuno sobre la regeneración de especies arbóreas deseables, la riqueza y abundancia de especies forrajeras deseables y las condiciones edáficas del sistema. Se hará enriquecimiento con plantines de tres especies de Prosopis tanto en el bosque con distintos anchos de fajas como en suelo desmontado, para evaluar su comportamiento. También se probará la diseminación y establecimiento posterior de estas especies por medio de la ingesta del ganado vacuno. Se relevarán especies medicinales, aromáticas, melíferas, tintóreas y ornamentales nativas, y se las valorará económicamente según su uso actual y potencial en esta y otras zonas de la provincia y el país. Se efectuará la caracterización socio-económica y ambiental del área circundante al Campo Escuela y mediante encuestas se determinará el grado de valorización del bosque que tienen los pobladores zonales. Se realizará el análisis económico y financiero del sistema propuesto versus el sistema sin proyecto, considerando bienes producidos y servicios ambientales del bosque y se socializará el proyecto a través de encuestas y reuniones participativas con los productores zonales. Para el análisis de toda la información se usará el software INFOSTAT 2007. Se harán tablas y gráficos de estadística descriptiva para visualizar la distribución de datos. Se usará análisis de correlación, análisis de regresión lineal múltiple, ANAVA y test a posteriori. Se espera generar pautas preliminares de manejo, sencillas y económicas, fácilmente adoptables por los productores de la región, que aseguren la persistencia de estos fragmentos boscosos, relictos de la vegetación original del Espinal.