Trash Rush – Educational Mobile Game For Android Devices

As population grows faster, the rise of garbage collection follows.  Massive information dissemination of waste management has been done by local representatives to educate people but despite the effort exerted still mismanagement of waste exist that caused serious environmental consequences to nature and human beings.  This condition ignites the researchers to develop a technology-based means to help disseminate proper disposal of garbage through the use of mobile phones.  Trash Rush educational mobile game application utilized Lua Scripting Language for game features, system behavior and synchronizes the phone sensor to the system. The Lua tool is decoded to JSON codes and sent to PHP MySQL in the webserver for storage. For tilting motion and orientation of the phone, the researchers employ the accelerometer sensor as the main navigation controller.   For sound and background effects, the Reactable Application is utilized.  The Box2D game engine is used to analyze and interpret the images and graphic effects while the Box2D API is utilized for object movement and animation. The Motion Parallax effect is also used to give more realistic effects in movements of the objects and the graphical background of the game. All these components are extracted through the APK file of Corona SDK to build and publish the app.  Upon reaching to the deployment stage of iterative model, it was found out that the system became viral to grade levels in the campus because of its story and time attack mechanism.

Relationship Between Gestational Diabetes and a Positive Depression Screen

Introduction: Gestational diabetes mellitus (GDM) and its treatment have a marked effect on women’s lives consequently aggravating psychosocial disruptions of a normal pregnancy. The demand for behavioural adaptation as well as postulated biological interactions are likely to increase the risk of maternal depression in GDM patients. There is however inadequate literature concerning the relationship between GDM and depression. Objective: To compare the proportion of women with GDM who screen positive for depression and the proportion of women without GDM who screen positive for depression at the Aga Khan University Hospital, Nairobi. Socio-demographic factors associated with a positive depression screen were explored. Methods: This was a case control study, applying the Edinburgh Postnatal Depression Scale (EPDS) and a socio-demographic tool on two antenatal groups; women with GDM and women without GDM. The proportion of women with depression was determined as the percentage of pregnant women with domain and overall scores below the cut-off levels that is 13. The Chi-square test and Fisher’s exact test were used to test for statistically significant differences in the proportion of GDM and non GDM women who screened positive for depression. Secondary analysis was done using univariate and multivariate analysis to examine the relationship between gestational diabetes, mode of treatment, and selected socio-demographic characteristics and a positive depression screen. Results: A total of 315 pregnant participants were enlisted for the study (104 with GDM and 211 without GDM). The two study groups were comparable demographically except for maternal age, parity, BMI, ethnicity, mode of conception and alcohol intake (p <0.05). Thirty-five of 104 (33.7%) women with GDM had a positive depression screen compared to 13 of 211(6.2%) women without GDM (p <0.001). Multivariate analysis showed that GDM is associated with the occurrence of a positive depression screen (odds ratio 6.7, 95% confidence interval 3.3-13.6). However mode of treatment of GDM and other socio-demographic characteristics were not associated with a positive depression screen. Conclusion: Women with GDM are significantly more likely to screen positive for depression in pregnancy compared to women without GDM. Screening for depression as well as psycological support may be required in women diagnosed with GDM.