Health care providers' opinions on abortion: a study for the implementation of the legal abortion public policy in the Province of Santa Fe, Argentina

Background: In Argentina, abortion has been decriminalized under certain circumstances since the enactment of the Penal Code in 1922. Nevertheless, access to abortion under this regulatory framework has been extremely limited in spite of some recent changes. This article reports the findings of the first phase of an operations research study conducted in the Province of Santa Fe, Argentina, regarding the implementation of the local legal and safe abortion access policy. Methods: The project combined research and training to generate a virtuous circle of knowledge production, decision-making, and the fostering of an informed healthcare policy. The project used a pre-post design of three phases: baseline, intervention, and evaluation. It was conducted in two public hospitals. An anonymous self-administered questionnaire (n = 157) and semi-structured interviews (n = 27) were applied to gather information about tacit knowledge about the regulatory framework; personal opinions regarding abortion and its decriminalization; opinions on the requirements needed to carry out legal abortions; and service’s responses to women in need of an abortion. Results: Firstly, a fairly high percentage of health care providers lack accurate information on current legal framework. This deficit goes side by side with a restrictive understanding of both health and rape indications. Secondly, while a great majority of health care providers support abortion under the circumstances consider in the Penal Code, most of them are reluctant towards unrestricted access to abortion. Thirdly, health care providers’ willingness to perform abortions is noticeably low given that only half of them are ready to perform an abortion when a woman’s life is at risk. Willingness is even lower for each of the other current legal indications. Conclusions: Findings suggest that there are important challenges for the implementation of a legal abortion policy. Results of the study call for specific strategies targeting health care providers in order to better inform about current legal abortion regulations and to sensitize them about abortion social determinants. The interpretation of the current legal framework needs to be broadened in order to reflect a comprehensive view of the health indication, and stereotypes regarding women’s sexuality and abortion decisions need to be dismantled.

Self-reference Scrubber for TMR Systems Based on Xilinx Virtex FPGAs

SRAM-based FPGAs are sensitive to radiation effects. Soft errors can appear and accumulate, potentially defeating mitigation strategies deployed at the Application Layer. Therefore, Configuration Memory scrubbing is required to improve radiation tolerance of such FPGAs in space applications. Virtex FPGAs allow runtime scrubbing by means of dynamic partial reconfiguration. Even with scrubbing, intra-FPGA TMR systems are subjected to common-mode errors affecting more than one design domain. This is solved in inter-FPGA TMR systems at the expense of a higher cost, power and mass. In this context, a self-reference scrubber for device-level TMR system based on Xilinx Virtex FPGAs is presented. This scrubber allows for a fast SEU/MBU detection and correction by peer frame comparison without needing to access a golden configuration memory

Success possibilities of grid parity in particular cases in the new spanish regulatory framework

During the last 10 years the Spanish photovoltaic market has experienced one of the most important increases worldwide. The continuous raise on the price of the electricity in Spain, as in other European countries, USA and Japan, as well as the decrease of the cost of solar photovoltaic systems along this decade is opening a new way to reach grid parity point in some particular scenarios. A new Spanish legislation is being performed toward selfconsumption, and it is in this new context where the grid parity in a wide sense could be achieved. This work will study different cases in Spain, in order to determine whether grid parity would be possible along 2012. Keywords: grid parity, self-consumption, photovoltaic, net-metering

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Preferential self-association of basic fibroblast growth factor is stabilized by heparin during receptor dimerization and activation.

Central to signaling by fibroblast growth factors (FGFs) is the oligomeric interaction of the growth factor and its high-affinity cell surface receptor, which is mediated by heparin-like polysaccharides. It has been proposed that the binding of heparin-like polysaccharides to FGF induces a conformational change in FGF, resulting in the formation of FGF dimers or oligomers, and this biologically active form is 'presented' to the FGF receptor for signal transduction. In this study, we show that monomeric basic FGF (FGF-2) preferentially self-associates and forms FGF-2 dimers and higher-order oligomers. As a consequence, FGF-2 monomers are oriented for binding to heparin-like polysaccharides. We also show that heparin-like polysaccharides can readily bind to self-associated FGF-2 without causing a conformational change in FGF-2 or disrupting the FGF-2 self-association, but that the bound polysaccharides only additionally stabilize the FGF-2 self-association. The preferential self-association corresponds to FGF-2 translations along two of the unit cell axes of the FGF-2 crystal structures. These two axes represent the two possible heparin binding directions, whereas the receptor binding sites are oriented along the third axis. Thus, we propose that preferential FGF-2 self-association, further stabilized by heparin, like "beads on a string," mediates FGF-2-induced receptor dimerization and activation. The observed FGF-2 self-association, modulated by heparin, not only provides a mechanism of growth factor activation but also represents a regulatory mechanism governing FGF-2 biological activity.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Compliance Strategies for Gasoline Distribution Facilities

Gasoline Distribution Generally Available Control Technology (GD GACT) is a Federal environmental regulation that is specifically written and enforced to reduce HAP emissions from gasoline distribution (GD) facilities. The regulation targets four specific types of GD facilities: bulk gasoline terminals, bulk gasoline plants, pipeline breakout stations, and pipeline pumping stations. A GD GACT compliance plan was developed for a particular, representative example of each type of GD facility affected by the regulation. Each facility in the study is owned and operated by a single company. The compliance plans were developed to meet the regulatory requirements contained within GD GACT. The compliance plans will be implemented at each facility prior to the January 10, 2011 compliance date.

Returns from Income Strategies in Rural Poland. Factor Markets Working Document No. 64, August 2013

In order to stabilise and improve their income situation, rural households are strongly encouraged to diversify their activities both within and outside the agricultural sector. Often, however, this advice is only moderately pursued. This paper addresses issues of rural household income diversification in the case of Poland. It investigates returns from rural household income strategies using propensity score matching methods and extensive datasets spanning 1998-2008. Results suggest that returns from combining farm and off-farm activities were lower than returns from concentrating on farming or on self-employment outside agriculture. This differential is stable over time although returns from diversification have relatively improved after Poland’s accession to the EU. This is also visible in the fact that since 2006 returns from combining farm and off-farm activities have evened with returns from relying solely on hired off-farm labour, thus smoothing the difference observed before the accession. Further, over the analysed period, households pursuing the diversification strategy performed better than those relying solely on unearned income. Finally, in general, the income in households combining farm and off-farm activities was higher than in those combining two off-farm income sources.

Predicting Children’s Early School Outcomes from their Social-Regulatory Profiles: A Person-Centered Approach

Thesis (Ph.D.)--University of Washington, 2016-06

Implementation of a Self-Management System for Students with Disabilities in General Education Settings

Thesis (Ph.D.)--University of Washington, 2016-06

Self-Reported Fall and Associate Risk Factors Among Korean American Adults In Washington State

Thesis (Master's)--University of Washington, 2016-06

Systematic proteomic strategies to map the human signaling landscape

Thesis (Ph.D.)--University of Washington, 2016-05

A longitudinal study of employee adaptation to organizational change: The role of change-related information and change-related self-efficacy

This study examined the role of information, efficacy, and 3 stressors in predicting adjustment to organizational change. Participants were 589 government employees undergoing an 18-month process of regionalization. To examine if the predictor variables had long-term effects on adjustment, the authors assessed psychological well-being, client engagement, and job satisfaction again at a 2-year follow-up. At Time 1, there was evidence to suggest that information was indirectly related to psychological well-being, client engagement, and job satisfaction, via its positive relationship to efficacy. There also was evidence to suggest that efficacy was related to reduced stress appraisals, thereby heightening client engagement. Last, there was consistent support for the stress-buffering role of Time I self-efficacy in the prediction of Time 2 job satisfaction.

Changes to peptide structure, not concentration, contribute to expansion of the lowest avidity cytotoxic T lymphocytes

The efficient in vitro expansion of antigen-specific CD8(+) cytotoxic T lymphocytes (CTL) for use in adoptive immunotherapy represents an important clinical goal. Furthermore, the avidity of expanded CTL populations often correlates closely with clinical outcome. In our study, high-avidity CTL lines could be expanded ex vivo from an antigen-primed animal using low peptide concentration, and intermediate peptide concentrations favored the generation of lower avidity CTL. Further increases in peptide concentration during culture inhibited the expansion of all peptide-specific CD8(+) cells. In contrast, a single amino acid variant peptide efficiently generated functional CTL populations at high or low peptide concentration, which responded to wild-type epitope with the lowest average avidity seen in this study. We propose that for some peptides, the efficient generation of low-avidity CTL responses will be favored by stimulation with altered peptide rather than high concentrations of wild-type epitope. In addition, some variant peptides designed to have improved binding to major histocompatibility complex class I may reduce rather than enhance the functional avidity for the wild-type peptide of ex vivo-expanded CTL. These observations are relevant to in vitro expansion of CTL for immunotherapy and strategies to elicit regulatory or therapeutic immunity to neo-self-antigen when central tolerance has eliminated high-avidity, cognate T cells.