Precision agriculture research in sub-Saharan Africa countries: a systematic map

Precision agriculture (PA) has a huge potential for growth in sub-Saharan Africa (SSA), but it faces a number of social-economic and technological challenges. This study sought to map existing PA research and application in SSA countries following the methodology for systematic mapping in environmental sciences. After screening for relevance, the initial about 7715 articles was reduced to 128. Results show that most of the studies were conducted in countries with socio-economic and technological advancement, mainly South Africa followed by Nigeria and Kenya. The studies were conducted at various scales ranging from field to country level with field scale studies being the most common. Most studies were conducted in relatively small farms typical of most farmlands in SSA. Studies done in relatively large farms are fewer, and such farms would likely belong to a few organisations and individuals with high economic capacity. Many of these studies have been conducted by researchers from outside SSA and a combination of researchers from within and outside SSA. However, based on authorship of the articles, it appears that most of the studies conducted in SSA on precision agriculture have either involved or depended on non-African researchers. It is concluded that there have been significant strides towards use of precision agriculture in SSA. However, with about 21 countries having no research done, there exists greater potential for precision agriculture in the region. Besides, there is need for more research to investigate the low usage of precision agriculture for livestock management

Local Knowledge on the Changes in Vegetation Composition and Abundance in Rusinga Island, Homa Bay County, Kenya

Local communities have been coping with environmental dynamics since time immemorial, and they often possess considerable knowledge about environmental change, as well as mechanisms of coping with the consequences of such changes. Local knowledge on the changes in vegetation composition and abundance is therefore fundamental for the development of management strategies aimed at sustainable use and conservation of natural vegetation resources. Household interviews (n=150), Key informant interviews (n=30) and Focus group discussions (n=4) were used in this study to extract information on the communities’ perceptions on the status of vegetation in Rusinga Island of Homa Bay County of Kenya, and the suggested management strategies for the environment, particularly the vegetation resources for posterity. Rusinga Island is a biodiversity hotspot and an ancient historic area with numerous archeological sites that have given the World fossils dating back millions of years but the area has been experiencing downward trend in its ecosystems. Majority (86%) of the respondents reported having observed changes in vegetation composition and abundance in the study area. The changes were attributed to deforestation, high human population, overgrazing, inadequate rainfall, and soil erosion. Most (68%) of the respondents perceived the changes had occurred mainly in the forests/hills, in the entire Island (15.3%) and in the homesteads (2.7 %). To reverse the changes, the local community proposed tree planting, protection of existing trees, use of alternative sources of fuel, increased awareness creation on environmental conservation and controlled livestock grazing as the best strategies to reduce vegetation degradation. Besides sensitization and building capacity of the communities to engage in sustainable management of vegetation resources, land restoration interventions in the study area should target the plants species at risk through re-introduction and re-afforestation practices

Woody Plant Species Composition and Diversity in Rusinga Island, Homa Bay County, Kenya

Information on the state of woody vegetation of Rusinga Island is urgently needed in order to develop appropriate and effective conservation guidelines. Rusinga Island is an ancient historic area with numerous archeological sites and a bountiful of birdlife. However, the Island is characterized by highly degraded ecosystems from human disturbances such as cutting down of trees for fuel, construction poles, and overgrazing resulting in a remarkable degradation of flora, alteration of the ecosystems and loss of biodiversity. This study sought to determine the composition and diversity of woody plant species in Rusinga Island to understand the current status in order to develop appropriate and effective conservation measures since no such study has been conducted in the area before. Three hills (Ligongo, Agiro and Wanyama) were selected for sampling and demarcated into three study zones differentiated by the slope gradient and land use. A systematic random sampling approach was adopted to establish 98 sampling plots measuring 20 m x20 m (400m2) for recording tree species and subplots of 10 m by 10 m within the main plots for recording shrubs and lianas across the three study zones at an interval of 200m. A total of 63 woody plant species belonging to 32 families and 51 genera were recorded, out of which 66.7% were trees, 31.7% shrubs and 1.6% lianas. The upper zones had significantly higher species diversity, species richness, evenness and abundance compared to the middle and lower zones. The lower zones depicted a lower abundance of plants and least similarities of species compared to the middle and upper zones. Development of appropriate conservation and management strategies is required in order to protect the woody plant resources from unsustainable human activities and to improve the natural diversity of the Island

Effects of Imprisonment on Depression among Female Inmates in Selected Prisons in Kenya

This study examined the effects of imprisonment on depression among female inmates in selected prisons in Kenya. Descriptive survey research design was adopted for the study. A sample of 295 respondents was randomly selected to participant in the study. The study utilized semi structured questionnaires, interview schedules and observation guides to collect the desired data. The reliability of the instruments was estimated using Cronbach Alpha Coefficient. The instrument yielded a reliability coefficient of 0.857. Descriptive and inferential statistics were used for data analysis. The findings of the study indicated significant effects of imprisonment on depression among the female inmates. The study recommended reevaluation of the prisons’ physical, psychological and social environments to root out depression trigger factors. There was also need for recruitment of professional counselors to counsel the psychologically disturbed inmates. This would conveniently be achieved through partnership with religious institutions and non-governmental organizations that provide such services. Keywords: Imprisonment, Depression, Female Inmate

Efficacy Level of Therapeutic Counselling in Dealing with Depression among Adult Refugees: A Case of Dadaab Refugee Camp, Garissa County, Kenya

The purpose of this study was to investigate efficacy level of therapeutic counselling in dealing with depression among adult refugees at Dadaab refugee camp. Ex Post Facto research design was adopted for the study. A sample of 382 adult refugees and 16 section leaders were randomly selected to participate in the study while 5 counsellors were purposively selected. Data was collected using questionnaires, Focus Group Discussions and Interview guides. The reliability of the instrument was estimated using Cronbach Alpha Coefficient. The instrument yielded a reliability coefficient of 0.811. Descriptive and inferential statistics were used to analyze data. The study established that therapeutic counselling had positive satisfaction among adult refugees and hence efficacious in dealing with depression. The study recommended that there is need to allocate more funds towards mental and psychological health care at Dadaab refugee camp. This would enable counselling agencies to improve the counselling services. Keywords: Efficacy levels, therapeutic counseling, depression, adult refugees

The Non-Negative –Matrix Completion Problem for 5×5 Matrices Specifying Cyclic Diagraphs with 5 Vertices and 4 Arcs

The non-negative P0-matrix completion is considered for 5×5 matrices specifying digraphs with p=5 and q=4.The research determines which of the digraphs with p=5 and q=4 and specifying 5×5 partial matrices have non-negative P0-completion. Considering the 5×5 matrices with q=4, all the sixty one (61) non-isomorphic digraphs shall be constructed. All the partial non-negative P0-matrices will be extracted from each digraph. To establish if the pattern has non-negative P0-completion or not, zero completion will be performed on each of the partial matrix extracted. The study establishes that all acyclic digraphs of an 5×5 matrix with q=4 have non-negative P0-completion. The matrix completion problem is to find the values of an n x m matrix M, given a sparse and incomplete set of observations. Possible areas of applications include Seismic data reconstruction to recover missing traces when data is sparse and incomplete ,say due to malfunctioned measuring instruments, biased or corrupted traces, ground barriers, or due to financial limitation to access complete data. Others include incomplete market surveys (eg movie ratings to complete missing data so as to recommend appropriately to viewers), weather forecasting from historical data recordings as well as future predictions from computer simulations, reconstruction of images in computer; and finding the positions of sensors in Global Positioning from distances available in a local network

Factors that influence the quality of final impressions for fixed dental prostheses in Nairobi, Kenya

Background: Good quality dental impressions free of air bubbles, voids, steps, drags, streaks and tears are a pre-requisite for the fabrication of well-fitting fixed dental prostheses (FDP). The quality of impressions is dependent on clinician and material factors. Aim: To evaluate factors that influence the quality of final impressions for FDP in Nairobi, Kenya.  Methods: In this cross-sectional study, 234 impressions received by five dental laboratories were analyzed. The study collected information on the type of tray, impression material, technique, type of prostheses, and clinically detectable errors, including voids, inadequate material at margins, tears, steps, drags, and streaks. Impression quality was the outcome assessed as good, fair, or poor by two investigators. The independent variables influencing impression quality included clinician specialty, experience, impression material, technique, and tray type. Results: Inter-rater agreement was 96.8% (p<0.001). Clinician experience ranged between 1-45yrs, median 13.5yrs and mean 8.39±11.96yrs. The majority were GPs, 80.8% while restorative dentists were 11.5% and other specialists, 7.7%. Most impressions were non-aqueous elastomers, 97.9% employing dual-viscosity technique, 75.6%. Impression trays included stock metal, 60.3%, stock plastic, 34.2%, and custom, 5.5%. Impression quality was good, 24.8%, fair, 37.2% or poor, 38.0%. Cumulatively, 74.5% impressions had bubbles/voids, 53.0% tears and 43.2% poor margins. Clarity of margins was associated with clinician specialty, (Fisher’s exact=9.372, p=0.047), and impression technique with impression quality, (Pearson’s ?2 = 6.385, p=0.041). Compared to restorative specialists, estimated odds of other specialists producing poor margins was 5.71, 95%CI 1.55,21.06, Wald ?2=5.24, p=0.009 while for GPs, the estimated odds was 2.19, 95%CI 0.88, 5.43, Wald ?2 = 2.86, p=0.09. Compared to dual viscosity, estimated odds of monophase giving a poor-quality impression was 1.52, 95%CI 0.83,2.78, Wald ?2 = 1.52, p=0.18. Conclusion: Most impressions were good or fair hence acceptable. Quality of impressions was influenced by clinician specialty and impression technique

Digital Triplet Approach for Real-Time Monitoring and Control of an Elevator Security System

As Digital Twins gain more traction and their adoption in industry increases, there is a need to integrate such technology with machine learning features to enhance functionality and enable decision making tasks. This has lead to the emergence of a concept known as Digital Triplet; an enhancement of Digital Twin technology through the addition of an ’intelligent activity layer’. This is a relatively new technology in Industrie 4.0 and research efforts are geared towards exploring its applicability, development and testing of means for implementation and quick adoption. This paper presents the design and implementation of a Digital Triplet for a three-floor elevator system. It demonstrates the integration of a machine learning (ML) object detection model and the system Digital Twin. This was done to introduce an additional security feature that enabled the system to make a decision, based on objects detected and take preliminary security measures. The virtual model was designed in Siemens NX and programmed via Total Integrated Automation (TIA) portal software. The corresponding physical model was fabricated and controlled using a Programmable Logic Controller (PLC) S7 1200. A control program was developed to mimic the general operations of a typical elevator system used in a commercial building setting. Communication, between the physical and virtual models, was enabled using the OPC-Unified Architecture (OPC-UA) protocol. Object recognition using “You only look once” (YOLOV3) based machine learning algorithm was incorporated. The Digital Triplet’s functionality was tested, ensuring the virtual system duplicated actual operations of the physical counterpart through the use of sensor data. Performance testing was done to determine the impact of the ML module on the real-time functionality aspect of the system. Experiment results showed the object recognition contributed an average of 1.083s to an overall signal travel time of 1.338 s

Epigeneti-What? Approaches on Translating Research for Primary Breast Cancer Prevention

In fiscal year 2017, the National Cancer Institute devoted more than a half billion dollars to breast cancer research. Since 2012, the total investment has been more than $3 billion. Despite this significant investment, breast cancer still has no known immediate causes as it generally develops over the life course. Therefore, research is unable to provide the public any sort of magic bullet, or conclusive link between certain environmental exposures and the development of breast cancer later in life. What research is only able to report are likelihoods—possible links—things people might want to consider avoiding or doing in their everyday lives to reduce their future risks of developing breast cancer. This abundance of rigorously performed, albeit causally inconclusive, research focused on “plausible” links poses a challenge for health communicators who are tasked with seeking to find ways to translate this science into advice that people can act upon today. However, if society must wait for the science to provide 100% conclusive evidence before anyone ever takes action, how many lives could have been saved in the interim? Therefore, we advocate a two-pronged approach to translating scientific findings regarding environmental exposures and breast cancer prevention: a bottom-up approach—focused on informing the lay public and individuals, while simultaneously performing a top-down approach—focused on influencing policymakers. The current perspective analyzes the strengths and weaknesses to both of these approaches, and encourages scientists to work closely with health communicators to develop theoretically-driven strategies to drive positive changes over time