How did varying levels of intensity of the 2005 Pakistan earthquake differentially affect women’s fertility decisions and children’s health outcomes?

This paper uses a difference in difference model to investigate the impact of a large scale and high mortality 2005 earthquake in Pakistan on women’s fertility decisions and children’s health outcomes. Using a nationally representative, cross sectional DHS data from 2006 and geographical data from USGS, this paper investigates how variation in earthquake intensity levels can differentially impact total fertility for women and the likelihood of children suffering from diseases such as diarrhea, Acute Respiratory Infections (ARI) and fever. The post-earthquake results demonstrate a statistically significant increase in total fertility for areas closer to the epicenter of the earthquake, within a 100km radius of the rupture surface and at higher altitudes. Similarly, for children who were in-utero at the time of the earthquake, the probability of having early symptoms of ARI or fever was much smaller in lower earthquake intensity zones compared to the highest intensity zone.

Adults with autism spectrum disorders exhibit decreased sensitivity to reward parameters when making effort-based decisions.

BACKGROUND: Efficient effort expenditure to obtain rewards is critical for optimal goal-directed behavior and learning. Clinical observation suggests that individuals with autism spectrum disorders (ASD) may show dysregulated reward-based effort expenditure, but no behavioral study to date has assessed effort-based decision-making in ASD. METHODS: The current study compared a group of adults with ASD to a group of typically developing adults on the Effort Expenditure for Rewards Task (EEfRT), a behavioral measure of effort-based decision-making. In this task, participants were provided with the probability of receiving a monetary reward on a particular trial and asked to choose between either an "easy task" (less motoric effort) for a small, stable reward or a "hard task" (greater motoric effort) for a variable but consistently larger reward. RESULTS: Participants with ASD chose the hard task more frequently than did the control group, yet were less influenced by differences in reward value and probability than the control group. Additionally, effort-based decision-making was related to repetitive behavior symptoms across both groups. CONCLUSIONS: These results suggest that individuals with ASD may be more willing to expend effort to obtain a monetary reward regardless of the reward contingencies. More broadly, results suggest that behavioral choices may be less influenced by information about reward contingencies in individuals with ASD. This atypical pattern of effort-based decision-making may be relevant for understanding the heightened reward motivation for circumscribed interests in ASD.

Age and Life Course Location as Interpretive Resources for Decisions Regarding Disclosure of HIV to Parents and Children: Findings from the HIV and Later Life Study

Studies of disclosure among older people living with HIV (PLWH) are uninformed by critical social-gerontological approaches that can help us to appreciate how older PLWH see and treat age as relevant to disclosure of their HIV status. These approaches include an ethnomethodologically-informed social constructionism that explores how ‘the’ life course (a cultural framework depicting individuals’ movement through predictable developmental stages from birth to death) is used as an interpretive resource for determining self and others’ characteristics, capacities, and social circumstances: a process Rosenfeld and Gallagher (2002) termed ‘lifecoursing’. Applying this approach to our analysis of 74 life-history interviews and three focus groups with older (aged 50+) people living with HIV in the United Kingdom, we uncover the central role that lifecoursing plays in participants’ decision-making surrounding disclosure of their HIV to their children and/or older parents. Analysis of participants’ accounts uncovered four criteria for disclosure: the relevance of their HIV to the other, the other’s knowledge about HIV, the likelihood of the disclosure causing the other emotional distress, and the other’s ability to keep the disclosed confidential. To determine if these criteria were met in relation to specific children and/or elders, participants engaged in lifecoursing, evaluating the other’s knowledge of HIV, and capacity to appropriately manage the disclosure, by reference to their age. The use of assumptions about age and life-course location in decision-making regarding disclosure of HIV reflects a more nuanced engagement with age in the disclosure decision-making process than has been captured by previous research into HIV disclosure, including on the part of people aging with HIV.

Decisions, decisions everywhere (in the open data era).

Abstract: Decision support systems have been widely used for years in companies to gain insights from internal data, thus making successful decisions. Lately, thanks to the increasing availability of open data, these systems are also integrating open data to enrich decision making process with external data. On the other hand, within an open-data scenario, decision support systems can be also useful to decide which data should be opened, not only by considering technical or legal constraints, but other requirements, such as "reusing potential" of data. In this talk, we focus on both issues: (i) open data for decision making, and (ii) decision making for opening data. We will first briefly comment some research problems regarding using open data for decision making. Then, we will give an outline of a novel decision-making approach (based on how open data is being actually used in open-source projects hosted in Github) for supporting open data publication. Bio of the speaker: Jose-Norberto Mazón holds a PhD from the University of Alicante (Spain). He is head of the "Cátedra Telefónica" on Big Data and coordinator of the Computing degree at the University of Alicante. He is also member of the WaKe research group at the University of Alicante. His research work focuses on open data management, data integration and business intelligence within "big data" scenarios, and their application to the tourism domain (smart tourism destinations). He has published his research in international journals, such as Decision Support Systems, Information Sciences, Data & Knowledge Engineering or ACM Transaction on the Web. Finally, he is involved in the open data project in the University of Alicante, including its open data portal at http://datos.ua.es

A Computer-Aided Decision Support System for Making Locational Decisions, 1990

This report is the product of a first-year research project in the University Transportation Centers Program. This project was carried out by an interdisciplinary research team at The University of Iowa's Public Policy Center. The project developed a computerized system to support decisions on locating facilities that serve rural areas while minimizing transportation costs. The system integrates transportation databases with algorithms that specify efficient locations and allocate demand efficiently to service regions; the results of these algorithms are used interactively by decision makers. The authors developed documentation for the system so that others could apply it to estimate the transportation and route requirements of alternative locations and identify locations that meet certain criteria with the least cost. The system was developed and tested on two transportation-related problems in Iowa, and this report uses these applications to illustrate how the system can be used.

Using social network analysis to identify key stakeholders in agricultural biodiversity governance and related land-use decisions at regional and local level

In 2013 the European Commission launched its new green infrastructure strategy to make another attempt to stop and possibly reverse the loss of biodiversity until 2020, by connecting habitats in the wider landscape. This means that conservation would go beyond current practices to include landscapes that are dominated by conventional agriculture, where biodiversity conservation plays a minor role at best. The green infrastructure strategy aims at bottom-up rather than top-down implementation, and suggests including local and regional stakeholders. Therefore, it is important to know which stakeholders influence land-use decisions concerning green infrastructure at the local and regional level. The research presented in this paper served to select stakeholders in preparation for a participatory scenario development process to analyze consequences of different implementation options of the European green infrastructure strategy. We used a mix of qualitative and quantitative social network analysis (SNA) methods to combine actors’ attributes, especially concerning their perceived influence, with structural and relational measures. Further, our analysis provides information on institutional backgrounds and governance settings for green infrastructure and agricultural policy. The investigation started with key informant interviews at the regional level in administrative units responsible for relevant policies and procedures such as regional planners, representatives of federal ministries, and continued at the local level with farmers and other members of the community. The analysis revealed the importance of information flows and regulations but also of social pressure, considerably influencing biodiversity governance with respect to green infrastructure and biodiversity.

Oncology research and clinical decisions based on immunohistochemistry: the importance of the technical aspects that support a complex method

Immunohistochemistry (IHC) is the group of techniques that use antibodies as specific reagents to identify and demonstrate several cell and tissue components that are antigens. This linking allows locating and identifying the in situ presence of various substances by means of color that is associated with the formed antigen-antibody complexes. The practical value of this biotechnology area, widely used in Pathology and Oncology, in diagnostic, prognostic, theranostic and research context, results from the possibility of combining a colour marker with an antibody without causing any damage to specific binding established between antibody and antigen. This provides the microscopic observation of the target locations where the antibody and hence the antigen are present. IHC is presented as a powerful means for identification of several cellular and tissue structures that can be associated with pathologies, and of the consequences, at functional and morphological level, of these same elements action.

Defining the Resolution of a Network for Transportation Analyses: a New Method to Improve Transportation Planning Decisions

Travel demand models are important tools used in the analysis of transportation plans, projects, and policies. The modeling results are useful for transportation planners making transportation decisions and for policy makers developing transportation policies. Defining the level of detail (i.e., the number of roads) of the transport network in consistency with the travel demand model’s zone system is crucial to the accuracy of modeling results. However, travel demand modelers have not had tools to determine how much detail is needed in a transport network for a travel demand model. This dissertation seeks to fill this knowledge gap by (1) providing methodology to define an appropriate level of detail for a transport network in a given travel demand model; (2) implementing this methodology in a travel demand model in the Baltimore area; and (3) identifying how this methodology improves the modeling accuracy. All analyses identify the spatial resolution of the transport network has great impacts on the modeling results. For example, when compared to the observed traffic data, a very detailed network underestimates traffic congestion in the Baltimore area, while a network developed by this dissertation provides a more accurate modeling result of the traffic conditions. Through the evaluation of the impacts a new transportation project has on both networks, the differences in their analysis results point out the importance of having an appropriate level of network detail for making improved planning decisions. The results corroborate a suggested guideline concerning the development of a transport network in consistency with the travel demand model’s zone system. To conclude this dissertation, limitations are identified in data sources and methodology, based on which a plan of future studies is laid out.

HOLDING DECISIONS FOR CORRELATED VEHICLE ARRIVALS AT INTERMODAL FREIGHT TRANSFER TERMINALS

A vehicle holding method is proposed for mitigating the effect of service disruptions on coordinated intermodal freight operations. Existing studies are extended mainly by (1) modeling correlations among vehicle arrivals and (2) considering decision risks with a mean-standard deviation optimization model. It is shown that the expected value of the total cost in the proposed formulation is not affected by the correlations, while the variance can be miscomputed when arrival correlations are neglected. Some implications of delay propagation are also identified when optimizing vehicle holding decisions in real-time. General criteria are provided for determining the boundary of the affected region and length of the numerical search, based on the frequency of information updates. Theoretical analyses are supported by three numerical examples.

Future consumers’ perceptions of sustainability, and their reflections on buying decisions

The purpose of this quantitative study is to study future consumers’ perception of sustainability in relation to business in general and specifically concerning the forest industry. The aim is to understand, what they feel is important for sustainable business and how the forest industry, in their opinion, is performing in this respect. Further, it aims to study how these perceptions reflect in their buying decisions. The research was conducted by a quantitative survey in two countries, Finland and Hong Kong, in the spring of 2015. All data used in the research is primary. The result indicate that consumers see sustainability issues important today and in the future. Sustainability is seen important both for business in general for the forest industry. The industry is considered sustainable now, but room for improvements exists. The appreciation of sustainability does not reflect to buying decisions, however. The buying of ecological products seems to be more up to chance than to intention. Consumers are not proactive in searching for more ecological or responsible options. Information needs to be taken to them. Ecologicalness as such is still not a strong selling point.

Optimal Budget-Constrained Sample Allocation for Selection Decisions with Multiple Uncertain Attributes

A decision-maker, when faced with a limited and fixed budget to collect data in support of a multiple attribute selection decision, must decide how many samples to observe from each alternative and attribute. This allocation decision is of particular importance when the information gained leads to uncertain estimates of the attribute values as with sample data collected from observations such as measurements, experimental evaluations, or simulation runs. For example, when the U.S. Department of Homeland Security must decide upon a radiation detection system to acquire, a number of performance attributes are of interest and must be measured in order to characterize each of the considered systems. We identified and evaluated several approaches to incorporate the uncertainty in the attribute value estimates into a normative model for a multiple attribute selection decision. Assuming an additive multiple attribute value model, we demonstrated the idea of propagating the attribute value uncertainty and describing the decision values for each alternative as probability distributions. These distributions were used to select an alternative. With the goal of maximizing the probability of correct selection we developed and evaluated, under several different sets of assumptions, procedures to allocate the fixed experimental budget across the multiple attributes and alternatives. Through a series of simulation studies, we compared the performance of these allocation procedures to the simple, but common, allocation procedure that distributed the sample budget equally across the alternatives and attributes. We found the allocation procedures that were developed based on the inclusion of decision-maker knowledge, such as knowledge of the decision model, outperformed those that neglected such information. Beginning with general knowledge of the attribute values provided by Bayesian prior distributions, and updating this knowledge with each observed sample, the sequential allocation procedure performed particularly well. These observations demonstrate that managing projects focused on a selection decision so that the decision modeling and the experimental planning are done jointly, rather than in isolation, can improve the overall selection results.

Empirical studies on share issuance and repurchase decisions

Financial constraints influence corporate policies of firms, including both investment decisions and external financing policies. The relevance of this phenomenon has become more pronounced during and after the recent financial crisis in 2007/2008. In addition to raising costs of external financing, the effects of financial crisis limited the availability of external financing which had implications for employment, investment, sale of assets, and tech spending. This thesis provides a comprehensive analysis of the effects of financial constraints on share issuance and repurchases decisions. Financial constraints comprise both internal constraints reflecting the demand for external financing and external financial constraints that relate to the supply of external financing. The study also examines both operating performance and stock market reactions associated with equity issuance methods. The first empirical chapter explores the simultaneous effects of financial constraints and market timing on share issuance decisions. Internal financing constraints limit firms’ ability to issue overvalued equity. On the other hand, financial crisis and low market liquidity (external financial constraints) restrict availability of equity financing and consequently increase the costs of external financing. Therefore, the study explores the extent to which internal and external financing constraints limit market timing of equity issues. This study finds that financial constraints play a significant role in whether firms time their equity issues when the shares are overvalued. The conclusion is that financially constrained firms issue overvalued equity when the external equity market or the general economic conditions are favourable. During recessionary periods, costs of external finance increase such that financially constrained firms are less likely to issue overvalued equity. Only unconstrained firms are more likely to issue overvalued equity even during crisis. Similarly, small firms that need cash flows to finance growth projects are less likely to access external equity financing during period of significant economic recessions. Moreover, constrained firms have low average stock returns compared to unconstrained firms, especially when they issue overvalued equity. The second chapter examines the operating performance and stock returns associated with equity issuance methods. Firms in the UK can issue equity through rights issues, open offers, and private placement. This study argues that alternative equity issuance methods are associated with a different level of operating performance and long-term stock returns. Firms using private placement are associated with poor operating performance. However, rights issues are found empirically to be associated with higher operating performance and less negative long-term stock returns after issuance in comparison to counterpart firms that issue private placements and open offers. Thus, rights issuing firms perform better than open offers and private placement because the favourable operating performance at the time of issuance generates subsequent positive long-run stock price response. Right issuing firms are of better quality and outperform firms that adopt open offers and private placement. In the third empirical chapter, the study explores the levered share repurchase of internally financially unconstrained firms. Unconstrained firms are expected to repurchase their shares using internal funds rather than through external borrowings. However, evidence shows that levered share repurchases are common among unconstrained firms. These firms display this repurchase behaviour when they have bond ratings or investment grade ratings that allow them to obtain cheap external debt financing. It is found that internally financially unconstrained firms borrow to finance their share repurchase when they invest more. Levered repurchase firms are associated with less positive abnormal returns than unlevered repurchase firms. For the levered repurchase sample, high investing firms are associated with more positive long-run abnormal stock returns than low investing firms. It appears the market underreact to the levered repurchase in the short-run regardless of the level of investments. These findings indicate that market reactions reflect both undervaluation and signaling hypotheses of positive information associated with share repurchase. As the firms undertake capital investments, they generate future cash flows, limit the effects of leverage on financial distress and ultimately reduce the risk of the equity capital.

SEQUENTIAL DECISIONS AND PREDICTIONS IN NATURAL LANGUAGE PROCESSING

Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.

Reproductive decisions of couples living with HIV in Malawi: What can we learn for future policy and research studies?

Background The rapid scale-up of free antiretroviral therapy has lead to decline in adult mortality at the population level and reduction of vertical transmission. Consequently, some couples living with HIV are maintaining their reproductive decisions; marrying and having children. This paper analyses policies and guidelines on HIV, AIDS and sexual and reproductive health in Malawi for content on marriage and childbearing for couples living with HIV. Methods A qualitative study using interpretive policy analysis approach was conducted from July to December 2010 in two phases. First, data on access to HIV, AIDS and sexual and reproductive health services were collected using in-depth interviews with twenty couples purposively sampled in matrilineal Chiradzulu and patrilineal Chikhwawa communities. Secondly, data were collected from Malawi policies and guidelines on HIV, AIDS and sexual and reproductive health. The documents were reviewed for content on marriage and childbearing for couples living with HIV. Data were analysed using framework approach for applied policy analysis. Results Four categories emerged from each phase. From the study, we extracted health workers attitudes, weak linkage between HIV, AIDS and sexual and reproductive health services, contradictory messages between media and the hospitals and lack of information as factors directly related to guidelines and policies. Analysis of guidelines and policies showed nonprescriptiveness on issues of HIV, AIDS and reproduction: they do not reflect the social cultural experiences of couples living with HIV. In addition, there is; lack of clinical guidelines, external influence on adoption of the policies and guidelines and weak linkages between HIV and AIDS and sexual and reproductive health services. Conclusion This synthesis along with more detailed findings which are reported in other published articles, provide a strong basis for updating the policies and development of easy-to-follow guidelines in order to effectively provide services to couples living with HIV in Malawi.