Exploring the user experience through collage

We explore the use of collage in requirements elicitation, as a tool to support potential end-users in expressing their impressions, understanding, and emotions regarding a system

House Flies: Manure, Media, and Microbes

This study was conducted to determine if there is a difference in bacterial abundance in house flies based on sex and rearing environment (manure versus artificial media) for house flies. This is important in determining the effectiveness of the facilities where the flies are being raised. Although, previous studies have shown differences in bacterial abundance between male and female house flies, it still remains unknown whether there is a discrepancy in bacterial abundance between rearing environments in the lab. We hypothesized that there would be a greater abundance of bacteria in females than males and a greater bacterial abundance in the manure environment than the artificial media. We determined that there was no significant difference between house fly sex or the environments in which they were raised. These results are meaningful because they introduce evidence of forced interaction that could skew the bacterial counts. In the future, the results would be more telling with a larger sample size.

Changing Circumstances, Changing Outcomes?: Longitudinal Relations Between Family Income, Cumulative Risk Exposure, And Children’s Educational Success

Thesis advisor: Eric DearingEmerging research in developmental psychology and neuroscience suggests that childhood poverty is associated with high levels of exposure to multiple contextual risks, which cumulatively lead to persistent elevated stress levels that have a direct, as well an indirect (e.g., through parental processes), impact on child cognitive, academic, and socioemotional functioning (Evans & Kim, 2013). Such research has begun to change the way that scholars and practitioners envision the context of poverty, the persistence of the income-achievement gap, and the types of interventions that may be most effective in addressing disparities in children’s long-term educational success. However, research on the relations between poverty-associated stress and child outcomes is still in its infancy and many questions remain. In particular, it is unclear whether changing family economic circumstances matter, a question of concern for developmental science and public policy. Moreover, there is little work on moderators of relations between income, stress, and child outcomes, which could help identify factors that buffer children from the harm of stressful home environments. With longitudinal data from the Panel Study of Income Dynamics’ Child Development Supplement, the present study used fixed effects models to examine within-child associations between changes in family income, cumulative risk exposure (as measured by an index that includes a range of poverty-related stressors, such as economic strain, neighborhood crime, and physical and psychological home environments), and children’s cognitive, academic and socioemotional functioning. In addition, moderators of these associations were investigated in order to identify potential protective mechanisms and crucial levers for interventions and policy development. On the whole, findings were consistent with the cumulative stress model. On average, the estimated direct effects of changes in family income (i.e., prior to examining mediation or moderators) were not significant for changes in child outcomes. Yet, changes in income were, for the sample as a whole, indirectly related via changes in cumulative risk exposure: increases in income predicted decreases in cumulative risk exposure which, in turn, predicted improvements in achievement and declines in externalizing behavior. Additionally, these relations were moderated by child age, initial level of family income, and initial level of cumulative risk.Thesis (PhD) — Boston College, 2017.Submitted to: Boston College. Lynch School of Education.Discipline: Counseling, Developmental and Educational Psychology

Dehiscence of detached internal limiting membrane in eyes with myopic traction maculopathy with spontaneous resolution

Background: Idjwi, an island of approximately 220,000 people, is located in eastern DRC and functions semi-autonomously under the governance of two kings (mwamis). At more than 8 live births per woman, Idjwi has one of the highest total fertility rates (TFRs) in the world. Rapid population growth has led to widespread environmental degradation and food insecurity. Meanwhile family planning services are largely unavailable.Methods: At the invitation of local leaders, we conducted a representative survey of 2,078 households in accordance with MEASURE DHS protocols, and performed ethnographic interviews and focus groups with key informants and vulnerable subpopulations. Modelling proximate determinates of fertility, we evaluated how the introduction of contraceptives and/or extended periods of breastfeeding could reduce the TFR.Results: Over half of all women reported an unmet need for spacing or limiting births, and nearly 70% named a specific modern method of contraception they would prefer to use; pills (25.4%) and injectables (26.5%) were most desired. We predicted that an increased length of breastfeeding (from 10 to 21 months) or an increase in contraceptive prevalence (from 1% to 30%), or a combination of both could reduce TFR on Idjwi to 6, the average desired number of children. Increasing contraceptive prevalence to 15% could reduce unmet need for contraception by 8%.Conclusions: To meet women’s need and desire for fertility control, we recommend adding family planning services at health centers with NGO support, pursuing a community health worker program, promoting extended breastfeeding, and implementing programs to end sexual- and gender-based violence toward women

Social, economic and environmental risk factors for acute lower respiratory infections among children under five years of age in Rwanda

BACKGROUND:In low and middle-income countries, acute lower respiratory illness is responsible for roughly 1 in every 5 child deaths. Rwanda has made major health system improvements including its community health worker systems, and it is one of the few countries in Africa to meet the 2015 Millennium Development Goals, although prevalence of acute lower respiratory infections (4 %) is similar to other countries in sub-Saharan Africa. This study aims to assess social, economic, and environmental factors associated with acute lower respiratory infections among children under five to inform potential further improvements in the health system.METHODS:This is a cross-sectional study using data collected from women interviewed in the 2010 DHS about 8,484 surviving children under five. Based on a literature review, we defined 19 health, social, economic, and environmental potential risk factors, tested bivariate associations with acute lower respiratory infections, and advanced variables significant at the 0.1 confidence level to logistic regression modelling. We used manual backward stepwise regression to arrive at a final model. All analyses were performed in Stata v13 and adjusted for complex sample design.RESULTS:The following factors were independently associated with acute lower respiratory infections: child's age, anemia level, and receipt of Vitamin A; household toilet type and residence, and season of interview. In multivariate regression, being in the bottom ten percent of households (OR: 1.27, 95 % CI: 0.85-1.87) or being interviewed during the rainy season (OR: 1.61, 95 % CI: 1.24-2.09) was positively associated with acute lower respiratory infections, while urban residence (OR: 0.58, 95 % CI: 0.38-0.88) and being age 24-59 months versus 0-11 months (OR: 0.53, 95 % CI: 0.40-0.69) was negatively associated with acute lower respiratory infections.CONCLUSION:Potential areas for intervention including community campaigns about acute lower respiratory infections symptoms and treatment, and continued poverty reduction through rural electrification and modern stove distribution which may reduce use of dirty cooking fuel, improve living conditions, and reduce barriers to health care

Evaluating the Ability to Use Contextual Features to Map Deprived Areas 'Slums' in Multiple Cities

Population living in deprived conditions continues to grow, highlighting the urgent need for accurate high-resolution maps and detailed statistics to plan interventions and monitor changes. Unfortunately, data on deprived areas or "slums"is often unavailable, incomplete, or outdated. Leveraging satellite imagery can offer timely, and consistent information on deprived areas over large area However, there are limited studies that use free and open source data that can be used to map deprived areas over large areas and across multiple cities. To address these challenges, this study examines a scalable and transferable modeling approach to map deprived areas using contextual features extracted from freely available Sentinel-2 data. Models were trained and tested on three Sub-Sahara cities: Lagos Nigeria, Accra Ghana, and Nairobi, Kenya. The results indicate that models in individual city achieved F1 scores from 0.78-0.95 for the three cities. Additionally, the results indicate that the proposed approach may allow for the ability to transfer models from city to city allowing for large area and across city mapping.</p

Towards a scalable and transferable approach to map deprived areas using Sentinel-2 images and machine learning

African cities are growing rapidly and more than half of their populations live in deprived areas. Local stakeholders urgently need accurate, granular, and routine maps to plan, upgrade, and monitor dynamic neighborhood-level changes. Satellite imagery provides a promising solution for consistent, accurate high-resolution maps globally. However, most studies use very high spatial resolution images, which often cover only small areas and are cost prohibitive. Additionally, model transferability to new cities remains uncertain. This study proposes a scalable and transferable approach to routinely map deprived areas using free, Sentinel-2 images. The models were trained and tested on three cities: Lagos (Nigeria), Accra (Ghana), and Nairobi (Kenya). Contextual features were extracted at 10 m spatial resolution and aggregated to a 100 m grid. Four machine learning algorithms were evaluated, including multi-layer perceptron (MLP), Random Forest, Logistic Regression, and Extreme Gradient Boosting (XGBoost). The scalability of model performance was examined using patches of the different deprived types identified through visual image interpretation. The study also tested the ability of models to map deprived areas of different types across cities. Results indicate that deprived areas have heterogeneous local characteristics that affect large area mapping. The top 25 features for each city show that models are sensitive to the spatial structures of deprived area types. While models performed well on individual cities with XGBoost and MLP achieving an F1 scores of over 80%, the generalized model proves to be more beneficial for modeling multiple cities. This approach offers a promising solution for scaling routine, accurate maps of deprived areas to hundreds of cities that currently lack any such map, supporting local stakeholders to plan, implement, and monitor geotargeted interventions

Combined effects of chemotherapy and Nrf2 activation in colorectal cancer cells in vitro

Colon cancer is the third leading type of cancer diagnosis in the United States (Siegel et al, 2017). Common treatments include chemotherapy, which can be toxic to the patient and produce multiple adverse side effects(Sarkar, 2008). Combination therapies with chemotherapy drugs and other compounds have been reported to decrease tumor growth in breast and colon cancer by increasing efficacy of chemotherapeutic agents at lower doses, thus reducing off-target adverse effects(Borcherding et al, 2015; Chen et al 2017). Both activation of Nrf2, a transcription factor that induces expression of anti-oxidant genes, and dopamine receptor agonists, have been shown to reduce tumor growth in multiple cancer types (Borcherding et al, 2015; Melba et al, 2013). Thus, we examined whether combining a common chemotherapy drug, Doxorubicin, with a Nrf2 activator, CDDO-ME, or a dopamine-type-1 receptor agonist, Fenoldopam, improved efficacy of chemotherapy. Treatment of HT29 and HCT116 colorectal cancer cells in vitro with or CDDO-ME in conjunction with Doxorubicin augmented the effects of Doxorubicin alone, as determined by MTT assay. The results support that Doxorubicin had an effect on both cell lines above concentrations of 100 nM. However, Fenoldopam, a dopamine-type-1 receptor agonist, did not significantly affect cell viability. Therefore, the effects of Doxorubicin may be achieved at a lower dose when administered with CDDO-ME

The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries

Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups