Climate changes influence in occupational exposure to fungi and mycotoxins

Climate changes and their effects on fungal distribution and activity are aspects of concern regarding the human exposure to mycotoxins. An exhaustive search was made for papers available in scientific databases reposrting the influence that climate cchange has on fungi and mycotoxins. Also a review regarding fungal burden, collected between 2010 and 2015 in different settings, was done to support the discussion about future fungi and mycotoxins ocuupational exposure. A. flavus complex, E. graminerarum complex and F. verticilliodes were the most reported to be influenced by climate changes. We noted also that the analyzed Portuguese settings presented already an occupational problem due to their fungal burden. It will be important to know future climate changes to select what complexes/species and strains, and consequently the mycotoxins, we should consider as indicators of an occupational problem. In addition, epidemiologic studies are needed to increase knowledge about potential health effects related with the exposure to both risk factors.

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

Horse stable environment: what to expect regarding fungi and particles occupational exposure?

The simultaneous presence of fungi and particles in horse stable environment can create a singular exposure condition because particles have been reported has a good carrier for microorganisms and their metabolites. This study intends to characterize this setting and to recognize fungi and particles occupational exposure.

Improving the operational skills of the health personnel working in the emergency departments. A useful tool to give concrete answers to EU policies on patients' safety and to create new working opportunities” (VS/2013/0430) finanziato dalla Commissione Europea nell'ambito del programma PROGRESS.

A useful tool to give concrete answers to EU policies on patients' safety and to create new working opportunities (VS / 2013/0430

Learning Management Systems (LMS) and e-learning management: an integrative review and research agenda

Information Technology (IT) can be an important component for innovation since enabling e-learning it can provide conditions to which the organization can work with new business and improved processes. In this regard, the Learning Management Systems (LMS) allows communication and interaction between teachers and students in virtual spaces. However the literature indicates that there are gaps in the researches, especially concerning the use of IT for the management of e-learning. The purpose of this paper is to analyze the available literature about the application of LMS for the e-learning management, seeking to present possibilities for researches in the field. An integrative literature review was performed considering the Web of Science, Scopus, Ebsco and Scielo databases, where 78 references were found, of which 25 were full papers. This analysis derives interesting characteristics from scientific studies, highlighting gaps and guidelines for future research.

Low back pain, intervertebral disc and occupational diseases

International audience

Iowa Homeland Security and Emergency Management, Enhanced 911 Status Report, January 15, 2014

The Iowa Homeland Security and Emergency Management Department administers the E911 Program per Code of Iowa, Chapter 34A to protect the health, safety, and welfare of the people of Iowa. Iowa has 115 Public Safety Answering Points across 99 counties that handle both landline and wireless 911 calls for the citizens of Iowa.Enhanced 911 (E911) means a service which provides the user of a public telephone system the ability to reach a public safety answering point (PSAP) by dialing the digits 911.

Patologías lumbares: determinación de los factores ocupacionales y carga prestacional en una entidad promotora de salud en Bogotá

Resumen: Introducción El dolor lumbar es un trastorno músculo esquelético que afecta la parte baja de la espalda, considerado como un problema de salud pública y catalogado como un desastre en el sitio de trabajo, se encuentra en las 10 primeras causas de enfermedad profesional reportadas por las entidades prestadoras de servicios de salud, generando ausentismo y discapacidad laboral en los países industrializados, con costos que oscilan de los 20 mil a los 98 millones de dólares en los Estados Unidos. Objetivo Determinar la prevalencia de patologías lumbares calificadas y sus factores ocupacionales asociados en una entidad promotora de salud de Bogotá Colombia durante 2013 al 2014. Metodología Se realizó un estudio de corte transversal con datos secundarios pertenecientes a 318 pacientes de una entidad promotora de salud en la ciudad de Bogotá que fueron diagnosticados con patologías lumbares (lumbalgia-lumbago, discopatía lumbar, trastorno de disco intervertebral, espondilolistesis, espondilólisis, hernia discal), y remitidos a medicina laboral o solicitaron calificación de origen en primera oportunidad, en el periodo comprendido entre el año 2013 al 2014. Las variables incluidas fueron sociodemográficas, ocupacionales y diagnósticos médicos, específicamente patologías lumbares. Se realizó distribuciones de frecuencias, medidas de tendencia central y dispersión, análisis de asociación mediante la prueba Chi cuadrado de Pearson y un análisis multivariado a través del modelo de regresión binaria logística y el análisis de concordancia usando el índice de Kappa. Para las pruebas se utilizó un nivel de significación de 0,05. Se digitó y depuró en SPSS versión 23. Resultado El total de usuarios diagnosticados con patologías lumbares fue de 318 de los cuales el 57,2% fueron de sexo masculino con edad promedio de 43 años (D.E 7,9 años). Se encontró asociación significativa entre lumbalgia y movimientos de columna lumbar y levantamiento de carga (p<0,05); discopatía lumbar y movimientos de columna lumbar y factores multicausales (p<0,05); trastorno de disco intervertebral y factores multicausales (p<0.05), hernia de disco y levantamiento de cargas (p<0,05). Respecto a espondilolistesis y espondilólisis no se encontró asociación con ningún factor de riesgo, pero si se encontró asociación significativa entre origen y movimientos de columna lumbar (p= 0.010), con postura mantenida (p= 0.014), con causas multifactoriales (p= 0.000). El grado de concordancia entre la entidad promotora de salud y la administradora de riesgos laborales arrojó un valor en el índice de kappa de 0.432 (p= 0.000) correspondiendo a un grado de acuerdo moderado; para la concordancia entre la entidad promotora de salud y la junta de calificación el índice de kappa fue de 0.680 (p= 0.000) grado de acuerdo alto. Conclusión Las patologías lumbares tienen un alta prevalencia en la población trabajadora como en la no trabajadora, encontrándose un gran número de factores condicionantes a estas enfermedades generando altos costos en días perdidos laborales y en días de incapacidad: Por lo tanto, es importante determinar si estas son catalogadas de origen común o de origen laboral, para establecer programas de vigilancia epidemiológica y programas preventivos.

Urban management revolution : intelligent management systems for ubiquitous cities

A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated transparent and open decision making mechanism. The paper emphasises the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This paper introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The paper discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This paper also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities.

An investigation into the barriers to the implementation of automation and robotics technologies in the construction industry

The rising problems associated with construction such as decreasing quality and productivity, labour shortages, occupational safety, and inferior working conditions have opened the possibility of more revolutionary solutions within the industry. One prospective option is in the implementation of innovative technologies such as automation and robotics, which has the potential to improve the industry in terms of productivity, safety and quality. The construction work site could, theoretically, be contained in a safer environment, with more efficient execution of the work, greater consistency of the outcome and higher level of control over the production process. By identifying the barriers to construction automation and robotics implementation in construction, and investigating ways in which to overcome them, contributions could be made in terms of better understanding and facilitating, where relevant, greater use of these technologies in the construction industry so as to promote its efficiency. This research aims to ascertain and explain the barriers to construction automation and robotics implementation by exploring and establishing the relationship between characteristics of the construction industry and attributes of existing construction automation and robotics technologies to level of usage and implementation in three selected countries; Japan, Australia and Malaysia. These three countries were chosen as their construction industry characteristics provide contrast in terms of culture, gross domestic product, technology application, organisational structure and labour policies. This research uses a mixed method approach of gathering data, both quantitative and qualitative, by employing a questionnaire survey and an interview schedule; using a wide range of sample from management through to on-site users, working in a range of small (less than AUD0.2million) to large companies (more than AUD500million), and involved in a broad range of business types and construction sectors. Detailed quantitative (statistical) and qualitative (content) data analysis is performed to provide a set of descriptions, relationships, and differences. The statistical tests selected for use include cross-tabulations, bivariate and multivariate analysis for investigating possible relationships between variables; and Kruskal-Wallis and Mann Whitney U test of independent samples for hypothesis testing and inferring the research sample to the construction industry population. Findings and conclusions arising from the research work which include the ranking schemes produced for four key areas of, the construction attributes on level of usage; barrier variables; differing levels of usage between countries; and future trends, have established a number of potential areas that could impact the level of implementation both globally and for individual countries.

Controlled flexibility and lifecycle management of business processes through extensibility

Vendors provide reference process models as consolidated, off-the-shelf solutions to capture best practices in a given industry domain. Customers can then adapt these models to suit their specific requirements. Traditional process flexibility approaches facilitate this operation, but do not fully address it as they do not sufficiently take controlled change guided by vendors' reference models into account. This tension between the customer's freedom of adapting reference models, and the ability to incorporate with relatively low effort vendor-initiated reference model changes, thus needs to be carefully balanced. This paper introduces process extensibility as a new paradigm for customizing reference processes and managing their evolution over time. Process extensibility mandates a clear recognition of the different responsibilities and interests of reference model vendors and consumers, and is concerned with keeping the effort of customer-side reference model adaptations low while allowing sufficient room for model change.