JOB SATISFACTION: A QUALITY INDICATOR IN NURSING HUMAN RESOURCE MANAGEMENT

This descriptive study addresses the job satisfaction of nurse managers and clinical nurses working at the Hematology and Hemotherapy Services of a public hospital in Sao Paulo. The study objectives were to identify the factors that caused job satisfaction among nurse managers and clinical nurses, and support the results in the development of indicators to evaluate the quality of nursing human resource management. The components of the study were: autonomy, interaction, professional status, job requirements, organizational norms and remuneration. Participants were 44 nurses. Data were collected using a Job Satisfaction Index (JSI) questionnaire. In conclusion, this study permitted the identification of the clinical nurse group, which was the most satisfied, with a JSI of 10.5; the managerial group scored 10.0. Regarding the satisfaction levels in regards to the current activity, 88.9% of the nurse managers reported feeling satisfied, as did 90.9% of clinical nurses. For both groups, autonomy was the component with the highest level of professional satisfaction.

A resource management scenario for traditional and scientific management of pink shrimp (Farfantepenaeus paulensis) in the Patos Lagoon estuary (RS), Brazil

Abstract Background This article aims to discuss the incorporation of traditional time in the construction of a management scenario for pink shrimp in the Patos Lagoon estuary (RS), Brazil. To meet this objective, two procedures have been adopted; one at a conceptual level and another at a methodological level. At the conceptual level, the concept of traditional time as a form of traditional ecological knowledge (TEK) was adopted. Method At the methodological level, we conduct a wide literature review of the scientific knowledge (SK) that guides recommendations for pink shrimp management by restricting the fishing season in the Patos Lagoon estuary; in addition, we review the ethno-scientific literature which describes traditional calendars as a management base for artisanal fishers in the Patos Lagoon estuary. Results Results demonstrate that TEK and SK describe similar estuarine biological processes, but are incommensurable at a resource management level. On the other hand, the construction of a “management scenario” for pink shrimp is possible through the development of “criteria for hierarchies of validity” which arise from a productive dialog between SK and TEK. Conclusions The commensurable and the incommensurable levels reveal different basis of time-space perceptions between traditional ecological knowledge and scientific knowledge. Despite incommensurability at the management level, it is possible to establish guidelines for the construction of “management scenarios” and to support a co-management process.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Runoff Water Quality and Pollutant Mass Loads From Extensive Green Roofs

Green roof mitigation of volume and peak flow-rate of stormwater runoff has been studied extensively. However, due to the common practice of green roof fertilization, there is the potential for introduction of nutrients into local bodies of water. Therefore, this study compares green roof runoff quality with the water quality of precipitation and runoff from a bare shingle roof. The runoff from a demonstration-scale extensive green roof was analyzed during the summer of 2011 for its effect on runoff volume and analyzed during eleven storm events in the fall and winter for concentrations of copper, cadmium, zinc, lead, nitrogen species, total nitrogen, total organic carbon, sulfate, orthophosphate, and other monovalent and divalent ions. The green roof reduced the overall volume of runoff and served as a sink for NO3 - and NH4 +. However, the green roof was also a source for the pollutants PO4 3-, SO4 2-, TOC, cations, and total nitrogen. Metals such as zinc and lead showed trends of higher mass loads in the bare roof runoff than in precipitation and green roof runoff, although results were not statistically significant. The green roof also showed trends, although also not statistically significant, of retaining cadmium and copper. With the green roof serving as a source of phosphorous species and a sink for nitrogen species, and appearing to a retain metals and total volume, the life cycle impact analysis shows minimum impacts from the green roof, when compared with precipitation and bare roof runoff, in all but fresh water eutrophication. Therefore, the best environments to install a green roof may be in coastal environments.

Resource management in location aware cognitive radio networks

Dynamic spectrum access (DSA) aims at utilizing spectral opportunities both in time and frequency domains at any given location, which arise due to variations in spectrum usage. Recently, Cognitive radios (CRs) have been proposed as a means of implementing DSA. In this work we focus on the aspect of resource management in overlaid CRNs. We formulate resource allocation strategies for cognitive radio networks (CRNs) as mathematical optimization problems. Specifically, we focus on two key problems in resource management: Sum Rate Maximization and Maximization of Number of Admitted Users. Since both the above mentioned problems are NP hard due to presence of binary assignment variables, we propose novel graph based algorithms to optimally solve these problems. Further, we analyze the impact of location awareness on network performance of CRNs by considering three cases: Full location Aware, Partial location Aware and Non location Aware. Our results clearly show that location awareness has significant impact on performance of overlaid CRNs and leads to increase in spectrum utilization effciency.

PARTICIPANT IMPACTS FROM A PARTICIPATORY WATER MODELING WORKSHOP IN THE SONORA RIVER BASIN, MEXICO

Much of the research in the field of participatory modeling (PM) has focused on the developed world. Few cases are focused on developing regions, and even fewer on Latin American developing countries. The work that has been done in Latin America has often involved water management, often specifically involving water users, and has not focused on the decision making stage of the policy cycle. Little work has been done to measure the effect PM may have on the perceptions and beliefs of decision makers. In fact, throughout the field of PM, very few attempts have been made to quantitatively measure changes in participant beliefs and perceptions following participation. Of the very few exceptions, none have attempted to measure the long-term change in perceptions and beliefs. This research fills that gap. As part of a participatory modeling project in Sonora, Mexico, a region with water quantity and quality problems, I measured the change in beliefs among participants about water models: ability to use and understand them, their usefulness, and their accuracy. I also measured changes in beliefs about climate change, and about water quantity problems, specifically the causes, solutions, and impacts. I also assessed participant satisfaction with the process and outputs from the participatory modeling workshops. Participants were from water agencies, academic institutions, NGOs, and independent consulting firms. Results indicated that participant comfort and self-efficacy with water models, their beliefs in the usefulness of water models, and their beliefs about the impact of water quantity problems changed significantly as a result of the workshops. I present my findings and discuss the results.