Environmental management for malaria control: knowledge and practices in Mvomero, Tanzania.

Environmental conditions play an important role in the transmission of malaria; therefore, regulating these conditions can help to reduce disease burden. Environmental management practices for disease control can be implemented at the community level to complement other malaria control methods. This study assesses current knowledge and practices related to mosquito ecology and environmental management for malaria control in a rural, agricultural region of Tanzania. Household surveys were conducted with 408 randomly selected respondents from 10 villages and qualitative data were collected through focus group discussions and in-depth interviews. Results show that respondents are well aware of the links between mosquitoes, the environment, and malaria. Most respondents stated that cleaning the environment around the home, clearing vegetation around the home, or draining stagnant water can reduce mosquito populations, and 63% of respondents reported performing at least one of these techniques to protect themselves from malaria. It is clear that many respondents believe that these environmental management practices are effective malaria control methods, but the actual efficacy of these techniques for controlling populations of vectors or reducing malaria prevalence in the varying ecological habitats in Mvomero is unknown. Further research should be conducted to determine the effects of different environmental management practices on both mosquito populations and malaria transmission in this region, and increased participation in effective techniques should be promoted.

Knowledge and judgments about events that occurred prior to birth: The measurement of the persistence of information

Data from five laboratories using five different techniques were reanalyzed to measure subjects' knowledge of events that occurred over the past 70 years. Subjects were about 20 years of age, so the measures included events that extended up to 50 years before birth. The functions relating knowledge about the events to age do not decrease precipitously at birth but gradually drop to above-chance levels. Techniques usually used to study retention within the individual can be used to study the persistence of ideas and fashions within an age cohort in a culture.

Internal Capital, External Knowledge, and Random Draws: Three Drivers of Organizational Structure

This dissertation explores the complex interactions between organizational structure and the environment. In Chapter 1, I investigate the effect of financial development on the formation of European corporate groups. Since cross-country regressions are hard to interpret in a causal sense, we exploit exogenous industry measures to investigate a specific channel through which financial development may affect group affiliation: internal capital markets. Using a comprehensive firm-level dataset on European corporate groups in 15 countries, we find that countries

with less developed financial markets have a higher percentage of group affiliates in more capital intensive industries. This relationship is more pronounced for young and small firms and for affiliates of large and diversified groups. Our findings are consistent with the view that internal capital markets may, under some conditions, be more efficient than prevailing external markets, and that this may drive group affiliation even in developed economies. In Chapter 2, I bridge current streams of innovation research to explore the interplay between R&D, external knowledge, and organizational structure–three elements of a firm’s innovation strategy which we argue should logically be studied together. Using within-firm patent assignment patterns,

we develop a novel measure of structure for a large sample of American firms. We find that centralized firms invest more in research and patent more per R&D dollar than decentralized firms. Both types access technology via mergers and acquisitions, but their acquisitions differ in terms of frequency, size, and i\ntegration. Consistent with our framework, their sources of value creation differ: while centralized firms derive more value from internal R&D, decentralized firms rely more on external knowledge. We discuss how these findings should stimulate more integrative work on theories of innovation. In Chapter 3, I use novel data on 1,265 newly-public firms to show that innovative firms exposed to environments with lower M&A activity just after their initial public offering (IPO) adapt by engaging in fewer technological acquisitions and

more internal research. However, this adaptive response becomes inertial shortly after IPO and persists well into maturity. This study advances our understanding of how the environment shapes heterogeneity and capabilities through its impact on firm structure. I discuss how my results can help bridge inertial versus adaptive perspectives in the study of organizations, by

documenting an instance when the two interact.

Knowledge and perceptions among overweight and obese employees about lifestyle-related health benefit changes.

We investigated perceptions among overweight and obese state employees about changes to health insurance that were designed to reduce the scope of health benefits for employees who are obese or who smoke. Before implementation of health benefit plan changes, 658 state employees who were overweight (ie, those with a body mass index [BMI] of 25-29.9) or obese (ie, those with a BMI of > or = 30) enrolled in a weight-loss intervention study were asked about their attitudes and beliefs concerning the new benefit plan changes. Thirty-one percent of employees with a measured BMI of 40 or greater self-reported a BMI of less than 40, suggesting they were unaware that their current BMI would place them in a higher-risk benefit plan. More than half of all respondents reported that the new benefit changes would motivate them to make behavioral changes, but fewer than half felt confident in their ability to make changes. Respondents with a BMI of 40 or greater were more likely than respondents in lower BMI categories to oppose the new changes focused on obesity (P < .001). Current smokers were more likely than former smokers and nonsmokers to oppose the new benefit changes focused on tobacco use (P < .01). Participants represented a sample of employees enrolled in a weight-loss study, limiting generalizability to the larger population of state employees. Benefit plan changes that require employees who are obese and smoke to pay more for health care may motivate some, but not all, individuals to change their behaviors. Since confidence to lose weight was lowest among individuals in the highest BMI categories, more-intense intervention options may be needed to achieve desired health behavior changes.

PARTAKE survey of public knowledge and perceptions of clinical research in India.

BACKGROUND: A public that is an informed partner in clinical research is important for ethical, methodological, and operational reasons. There are indications that the public is unaware or misinformed, and not sufficiently engaged in clinical research but studies on the topic are lacking. PARTAKE - Public Awareness of Research for Therapeutic Advancements through Knowledge and Empowerment is a program aimed at increasing public awareness and partnership in clinical research. The PARTAKE Survey is a component of the program. OBJECTIVE: To study public knowledge and perceptions of clinical research. METHODS: A 40-item questionnaire combining multiple-choice and open-ended questions was administered to 175 English- or Hindi-speaking individuals in 8 public locations representing various socioeconomic strata in New Delhi, India. RESULTS: Interviewees were 18-84 old (mean: 39.6, SD ± 16.6), 23.6% female, 68.6% employed, 7.3% illiterate, 26.3% had heard of research, 2.9% had participated and 58.9% expressed willingness to participate in clinical research. The following perceptions were reported (% true/% false/% not aware): 'research benefits society' (94.1%/3.5%/2.3%), 'the government protects against unethical clinical research' (56.7%/26.3%/16.9%), 'research hospitals provide better care' (67.2%/8.7%/23.9%), 'confidentiality is adequately protected' (54.1%/12.3%/33.5%), 'participation in research is voluntary' (85.3%/5.8%/8.7%); 'participants treated like 'guinea pigs'' (20.7%/53.2%/26.0%), and 'compensation for participation is adequate' (24.7%/12.9%/62.3%). CONCLUSIONS: Results suggest the Indian public is aware of some key features of clinical research (e.g., purpose, value, voluntary nature of participation), and supports clinical research in general but is unaware of other key features (e.g., compensation, confidentiality, protection of human participants) and exhibits some distrust in the conduct and reporting of clinical trials. Larger, cross-cultural surveys are required to inform educational programs addressing these issues.

Men's knowledge and attitudes about cervical cancer screening in Kenya.

BACKGROUND: A number of studies have identified male involvement as an important factor affecting reproductive health outcomes, particularly in the areas of family planning, antenatal care, and HIV care. As access to cervical cancer screening programs improves in resource-poor settings, particularly through the integration of HIV and cervical cancer services, it is important to understand the role of male partner support in women's utilization of screening and treatment. METHODS: We administered an oral survey to 110 men in Western Kenya about their knowledge and attitudes regarding cervical cancer and cervical cancer screening. Men who had female partners eligible for cervical cancer screening were recruited from government health facilities where screening was offered free of charge. RESULTS: Specific knowledge about cervical cancer risk factors, prevention, and treatment was low. Only half of the men perceived their partners to be at risk for cervical cancer, and many reported that a positive screen would be emotionally upsetting. Nevertheless, all participants said they would encourage their partners to get screened. CONCLUSIONS: Future interventions should tailor cervical cancer educational opportunities towards men. Further research is needed among both men and couples to better understand barriers to male support for screening and treatment and to determine how to best involve men in cervical cancer prevention efforts.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.