Task Specific Ionic Liquids for Enantiomeric Recognition and Nanomaterials for Biomedical Imaging

Ionic liquids (ILs) are organic salts that melt at or below 100°C. Interest in ILs continues to grow due to their unique properties such as lack of measurable vapor pressure, high thermal stability, tunability and recyclability. The first part of this dissertation explores the use of chiral ionic liquids (CILs) for enantiomeric recognition of chiral analytes using fluorescence spectroscopy. Chiral analyses continue to be a subject of considerable interest primarily as a result of legislation introduced by the Food and Drug Administration. This has led to an increased need for suitable chiral selectors and methods to verify the enantiomeric forms of drugs. In this study, CILs derived from amino acid esters were used simultaneously as solvents and chiral selectors for enantiomeric recognition of various fluorescent as well as non-fluorescent chiral analytes. The second part of this dissertation focuses on the development of a new class of fluorescent near infrared (NIR) nanoparticles from a Group of Uniform Materials Based on Organic Salts (GUMBOS) largely comprising frozen ILs. The GUMBOS were subsequently used to fabricate nanoGUMBOS using a reprecipitation method. The potential of the NIR nanoGUMBOS for non-invasive imaging was evaluated by fluorescence imaging of Vero cells incubated with nanoGUMBOS. Fluorescence imaging of diseased cells and tissues is useful for early detection and treatment of diseases. The work presented here is significant and may improve the quality of human life by employing NIR nanoGUMBOS as contrast agents for early diagnosis and treatment of some diseases. Through variations in the anion, different spectral properties were observed for nanoGUMBOS presenting the possibility of using a single dye for multiple applications

Accessibility of Technical And Vocational Training Among Disabled People: Survey Of TVET Institutions In North Rift Region, Kenya

People with disabilities face particular challenges in education and training. Most of them are deprived of access to basic literacy and numeracy skills. They also face barriers that affect access to Technical Vocational Education and Training (TVET) institutions some of them arising from the surrounding socio-economic environment and from mainstream TVET institutions. The main purpose of this paper was to assess barriers to accessibility of TVET institutions by disabled people in Kenya. The study was carried out in the North Rift Region of Kenya. The target population of the study consisted of the lectures and students with disabilities in 5 public TVET Institutions. Semi Structured Questionnaires were used as the main instruments for data collection. Data collected was analyzed using descriptive statistics and inferential statistics with the aid of SPSS IBM version 20. One of the most striking findings was that disabled students in TVET institutions are discriminated and isolated. Findings also indicated that the disabled students cannot access some of the school buildings; they are also barred from enrolling in TVET due to policies that provide cut off point marks or entry behavior to courses they desire to enroll in. It was also found that teachers had positive attitude toward the disabled students, contrary to the fact that students considered teachers to be unfriendly to them.  Therefore, the paper recommended that skills training and instructional mechanisms must consider specific needs of youth with different types of disabilities before putting them together in regular class. Better coordination between the government and service providers could anticipate and mitigate this barrier. There is also the need for specialized training institutions to be upgraded and modernized, and mainstream training institutions be adjusted to include training of persons with disabilities. Keywords: TVET, Disabled Students, Accessibility, Skills, PW

Advancing the use of gridded, online climate information for risk management in the Horn of Africa

This report summarizes the discussions, deliberations and recommendations made during the side event, Advancing the use of gridded, online climate information for risk management in the Horn of Africa, to the Forty Eighth Greater Horn of Africa Climate Outlook Forum (GHACOF 48). This event was co-organized by the Climate Services for Africa project—led by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS)—and the Weather and Climate Information Services for Africa (WISER) - qEnhancing National Climate Services initiative (ENACTS), that was held on 13 February 2018 in Mombasa, Kenya. The main aim of the event was to advance shared understanding, between climate information users and providers on how the GHACOF process and member country National Meteorological and Hydrological Services (NMHSs) can support more effective use of climate information. The meeting was geared towards raising awareness on recent developments in climate information products developed for the agriculture and food security sector through the ENACTS approach and demonstrate ICPAC capabilities to support member countries in the development of gridded historical and seasonal forecast climate information Maproom products tailored to user needs. Agro-climatic variables showcased included rainfall onset dates (both in historical and forecast mode), cessation dates, historical wet and dry spells, and rainfall intensity. The meeting was also intended to bring an informed agriculture user perspective into a discussion with ICPAC and NMHSs about how the GHACOF process can be made more useful for the agriculture and food security sector. The workshop brought together representatives from member country NMHSs, experienced agricultural and food security users and champions of climate information, ICPAC, WMO, and WISER and Climate Services for Africa project partners. Workshop participants appreciated the importance of these agro-climatic variables in making timely and informed decisions

Adaptation of processing technologies in the bakery industry in Kenya

This was an investigation of the ways in which firms, in the developing nations during the 1980's, have adapted production technologies in their efforts to expand the production capacities and to contribute towards the nation's capability for self-sustaining industrial operations. The study was undertaken in the bakery industry in Kenya, between 1984 and 1991, in two phases that involved a survey of 82 firms and an in-depth case study of six firms. One of the principal aims of the study was to identify a more promising strategy between the small-scale operations and the Big-Push model. The argument in this study, however, is that these two models of economic growth are subject to limitations that arise essentially from their lack of treatment of the attributes of entrepreneurs as determinant factors.Examined under the modified versions of these models are the effects of the varied characteristics of the entrepreneurs, the nature of investment and location of the firms on the types and the levels of equipment adopted, capacity utilization, labour requirements and ways for skills development. Results indicate that the modified models, to incorporate entrepreneurs among the casual factors, improve prediction of the nature of investment as well as adaptation of the production technologies. With regard to the relative advantages, it was found that while small-scale operations encouraged adoption of locally manufactured equipment and utilization of considerably higher ratio of skilled labour, they are significantly constrained by limited capabilities for adoption of advanced equipment. In contrast, whereas large-scale operations adopted modern equipment and absorbed substantially greater number of the labour force, they exerted overwhelming negative impact on local technical capabilities and entrepreneurial activities.In light of these findings it is suggested that medium size operations that offset extreme disadvantages of the two conventional models would be more favourable with respect to adaptation of the production technologies for purposes of achieving self-sustaining industrial operations in the context of the developing countries. In addition, attention should be given to policy measures that enable entrepreneurs to acquire capabilities for undertaking competitive industrial enterprises, particularly adoption and management of technically efficient techniques. One of the potential approaches is promotion of the cooperative industrial endeavour through which recent entrepreneurs can mobilize resources and operation skill

Relationship between family developmental variables and satisfaction in family development

Bibliography: p. 109-118

Improved seasonal prediction of rainfall over East Africa for application in agriculture: Statistical downscaling of CFSv2 and GFDL-FLOR

Statistically downscaled forecasts of October–December (OND) rainfall are evaluated over East Africa from two general circulation model (GCM) seasonal prediction systems. The method uses canonical correlation analysis to relate variability in predicted large-scale rainfall (characterizing, e.g., predicted ENSO and Indian Ocean dipole variability) to observed local variability over Kenya and Tanzania. Evaluation is performed for the period 1982–2011 and for the real-time forecast for OND 2015, a season when a strong El Niño was active. The seasonal forecast systems used are the National Centers for Environmental Prediction Climate Forecast System, version 2 (CFSv2), and the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution (GFDL-FLOR) version of CM2.5. The Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) rainfall dataset—a blend of in situ station observations and satellite estimates—was used at 5 km × 5 km resolution over Kenya and Tanzania as benchmark data for the downscaling. Results for the case-study forecast for OND 2015 show that downscaled output from both models adds realistic spatial detail relative to the coarser raw model output—albeit with some overestimation of rainfall that may have been derived from the downscaling procedure introducing a wet response to El Niño more typical of historical cases. Assessment of the downscaled forecasts over the 1982–2011 period shows positive long-term skill better than that documented in previous studies of unprocessed GCM forecasts for the region. Climate forecast downscaling is thus a key undertaking worldwide in the generation of more reliable products for sector specific application including agricultural planning and decision-making

Increasing the prospective capacity of global crop and rangeland monitoring with phenology tailored seasonal precipitation forecasts

Droughts are more and more often a limiting factor to agricultural production and can have severe negative effects on food security in vulnerable countries. Global agriculture early warning systems monitor agriculture in near real-time by analyzing meteorological data (e.g. precipitation and temperature) and optical remote sensing data as proxy vegetation health to detect possible negative anomalies and trigger warnings. Seasonal climate forecast can add a predictive component and inform about upcoming precipitation deficits, thus allowing anticipation and improved planning of response actions. Here, we propose a scheme to adapt the standard precipitation forecast from the seasonal Copernicus Climate Change Service multi-system to crop and rangeland phenology, making them suitable for agricultural early warning. Precipitation forecasts are first elaborated into tercile maps showing the probability of the most likely tercile (i.e. drier than normal, normal, wetter than normal) and associated skills of all possible monthly periods combinations included in the six months forecasting horizon. Afterwards, agronomically relevant tercile maps are produced for the closest season in time at any location. These maps are obtained by mosaicking the forecasts for the appropriate growing season period at each grid cell. The resulting map shows the tercile probability for the remaining part of the ongoing growing season (if any at time of analysis) or the probability of the next upcoming season (if in between growing season at time of analysis). The proposed methodology offers a precipitation seasonal forecast product ready to use by agricultural analysts and directly ingestible by automatic warning systems

Progress in climate change adaptation and mitigation actions in sub-Saharan Africa farming systems

This paper reviews the progress in climate change adaptation and mitigation actions in sub-Saharan Africa farming systems. Farmers, organizations and Governments in the region have developed policies and innovations to adapt to and mitigate the impacts of climate change. It appears that the developed and implemented innovative adaptive farming systems and technologies have culminated into resultant overall productivity improvement in farming systems, necessitating scaling up in order to widely strengthen the resilience and adaptive capacity of vulnerable communities to the impacts of climate change. Additionally, climate governance instruments that are aligned to the ratified international treaties have been developed and related programs have been rolled out in different countries. This offers hope for well-coordinated efforts and interventions for the mitigation and adaptation to the adverse impacts of climate change on the environment and livelihoods. Observably, there is a pressing need to scale up climate smart innovations sustainably through creation of an enabling policy environment, capacity building, and conducting climate change related research and outreach, and effective dissemination of climate technologies and information, especially in remote areas in the region. Since climate change is a global issue, local initiatives and actions for mitigating and adapting to the adverse impacts ought to be well integrated into the broader international context

The Impact of Prior Exposure to Engineering Through the MUT Pre-College Course - A Case Study of Kangema Sub-County Secondary Schools

In Kenya, secondary schools have a great role in preparing learners for career progression. In order to realize industrial growth, it is important to prepare more students for careers in STEM. There is relatively little research that exists on the impact of prior exposure to Engineering through pre- college sessions to students' attitude in STEM subjects. In addition, Industry 4.0 requires that the 21st century student be exposed to current trends in the industry. The purpose of this research is to investigate the impact of the pre-college sessions as a mode of prior exposure to Engineering to secondary school students on learning STEM subjects. The pre-college exposure course entailed introducing the students to green energy through Solar photovoltaic systems, automation using Arduino, advanced manufacturing through 3D printing and robotics. The research was conducted in secondary school students from Kangema subcounty. The target population is Form 1 and Form 2. In this research, the first cohort entailed 30 students who were selected from 3 secondary Schools through stratified, systematic and purposive sampling. The students were taken through the pre-college sessions. The study explored the impact of the precollege sessions to the attitude learning of STEM subjects. The study established that the students exhibited an improved attitude in learning of the STEM subjects