Rationalizing Historical Successes of Malaria Control in Africa in Terms of Mosquito Resource Availability Management.

Environmental management of mosquito resources is a promising approach with which to control malaria, but it has seen little application in Africa for more than half a century. Here we present a kinetic model of mosquito foraging for aquatic habitats and vertebrate hosts that allows estimation of malaria transmission intensity by defining the availability of these resources as the rate at which individual mosquitoes encounter and use them. The model captures historically observed responses of malaria transmission to environmental change, highlights important gaps in current understanding of vector ecology, and suggests convenient solutions. Resource availability is an intuitive concept that provides an adaptable framework for models of mosquito population dynamics, gene flow, and pathogen transmission that can be conveniently parameterized with direct field measurements. Furthermore, the model presented predicts that drastic reductions of malaria transmission are possible with environmental management and elucidates an ecologic basis for previous successes of integrated malaria control in Africa before the advent of DDT or chloroquine. Environmental management for malaria control requires specialist skills that are currently lacking in sub-Saharan Africa where they are needed most. Infrastructure and human capacity building in clinical, public health, and environmental disciplines should therefore be prioritized so that growing financial support for tackling malaria can be translated into truly integrated control programs

An integrated molecular and conventional breeding scheme for enhancing genetic gain in maize in Africa

Open Access Journal; Published online: 06 Nov 2019Maize production in West and Central Africa (WCA) is constrained by a wide range of interacting stresses that keep productivity below potential yields. Among the many problems afflicting maize production in WCA, drought, foliar diseases, and parasitic weeds are the most critical. Several decades of efforts devoted to the genetic improvement of maize have resulted in remarkable genetic gain, leading to increased yields of maize on farmers’ fields. The revolution unfolding in the areas of genomics, bioinformatics, and phenomics is generating innovative tools, resources, and technologies for transforming crop breeding programs. It is envisaged that such tools will be integrated within maize breeding programs, thereby advancing these programs and addressing current and future challenges. Accordingly, the maize improvement program within International Institute of Tropical Agriculture (IITA) is undergoing a process of modernization through the introduction of innovative tools and new schemes that are expected to enhance genetic gains and impact on smallholder farmers in the region. Genomic tools enable genetic dissections of complex traits and promote an understanding of the physiological basis of key agronomic and nutritional quality traits. Marker-aided selection and genome-wide selection schemes are being implemented to accelerate genetic gain relating to yield, resilience, and nutritional quality. Therefore, strategies that effectively combine genotypic information with data from field phenotyping and laboratory-based analysis are currently being optimized. Molecular breeding, guided by methodically defined product profiles tailored to different agroecological zones and conditions of climate change, supported by state-of-the-art decision-making tools, is pivotal for the advancement of modern, genomics-aided maize improvement programs. Accelerated genetic gain, in turn, catalyzes a faster variety replacement rate. It is critical to forge and strengthen partnerships for enhancing the impacts of breeding products on farmers’ livelihood. IITA has well-established channels for delivering its research products/technologies to partner organizations for further testing, multiplication, and dissemination across various countries within the subregion. Capacity building of national agricultural research system (NARS) will facilitate the smooth transfer of technologies and best practices from IITA and its partners

Participation in California’s Forest Carbon Offset Program: Motivations and Barriers

The State of California has the most comprehensive climate change policy in the United States in the form of a cap and trade program. The program has received international attention as a potential model for government-driven mitigation strategies. Within the program is a carefully constructed forest carbon offset component. Although the program is still relatively new, continuing analyses can assist in providing feedback for improving the program and for highlighting exemplary features that can be used by other programs in their formative stages. This work investigates the forest offset protocols where there are low rates of participation. Interviews and surveys provide a basis for understanding the motivations for entry and the barriers to participation landowners face in registering a project into California’s forest carbon offset program. Six major criteria for credits are discussed (real, enforceable, verifiable, additional, permanent, and quantifiable) and preliminary findings suggest that the most serious barriers are the long time commitment, the high cost of entry coupled with a low-rate of return, and competing environmental programs. Finally, recognizing the ultimate goal of mitigating the effects of climate change, commentary about perceived barriers and recommendations for reducing barriers is included

Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response to energy price changes and get incentives in return. In this paper, we study the effect of various time-based rate (TBR) programs on the stochastic day-ahead energy and reserve scheduling in residential islanded microgrids (MGs). An effective approach is presented to schedule both energy and reserve in presence of renewable energy resources (RESs) and electric vehicles (EVs). An economic model of responsive load is also proposed on the basis of elasticity factor to model the behavior of customers participating in various DR programs. A two-stage stochastic programming model is developed accordingly to minimize the expected cost of MG under different TBR programs. To verify the effectiveness and applicability of the proposed approach, a number of simulations are performed under different scenarios using real data; and the impact of TBR-DR actions on energy and reserve scheduling are studied and compared subsequently

The effectiveness of supported employment programs : Meta-regression analysis of the global secular trend, 1990-2015

Importance: Supported employment programs aim to re-integrate unemployed people with mental illness into the competitive labour market. While it is known that short-term economic developments like the 2008 recession may have negative consequences on the supported employment effectiveness rates, research into long-term secular trends has not yet been conducted. Objective: The primary objective of the regression analysis was to assess the effectiveness of supported employment programs for clients with any mental disorder over a longer time period. Further objectives were a comparison to prevocational training and the identification of moderating variables. Data sources: We retrieved publications on randomized controlled trials and on routine implementation programs that were included in four recent systematic reviews on supported employment for people with mental illness, plus very recent publications that were identified by a new search. This search was conducted in the following databases: Pubmed, PsycInfo, CINAHL (Cumulative Index on Nursing and Allied Health Literature), and Google Scholar. Study selection: We included any publication that was used in the four meta-analyses plus very recently published studies. The included studies were conducted between 1990 and 2015. Data extraction and synthesis: 80 studies with 14,437 participants were included in the analysis. Data was extracted by one author and cross-checked by the second author. We have conducted univariate and multivariate meta-regressions on the basis of a random-effects meta-analysis of proportions. The best-fitting model was computed by utilizing a statistical model selection procedure. Main Outcome and Measures: The outcome was the competitive employment rate over time. The year of study conduction (1990 to 2015) was regressed on the competitive employment rate. Regression coefficient estimates were computed and graphically displayed. Results: The competitive employment rate of supported employment programs was negatively associated with the study year (estimate -0.0068, CI -0.0114 - -0.0021) and the study period 2008 to 2015 had a larger decline in the competitive employment rate than the period 2000 to 2007. For prevocational training we found no change (estimate 0.0002, CI -0.0059 – 0.0063). Significant moderators were covariates study year/study period, augmented programs and study design (RCT vs. routine implementation). Conclusions and relevance: Results of this meta-regression suggest that supported employment programs have become less effective over time. Supported employment programs need to adapt to a changing labour market that is becoming more challenging to people with mental illness

Social Safety Nets Programs in Bangladesh: Preparing for Adaption to Demographic Change, Disaster, and Poverty Reduction

From the last two decades, Bangladesh has experienced a rapid decline in birth rate and childhood mortality rate simultaneously. Due to increase in literacy rate, per capita income, more awareness about life, and better nutrition, life expectancy has also increased rapidly in Bangladesh. As a result, the increase in population and life expectancy undeniably has an impact on the demographic profile of the population. As a disaster prone and large populated country with limited resources, a big share of population is still poor and vulnerable. To tackle the situation a large scale social safety net (SSN) programs with grants cash, in-kind or both for targeted people have been implementing by the government and non-government organization. This paper is an attempt to provide an overview of the current SSN program implemented by the government. Considering existing literature and document, this paper identifies three models of SSN transfers: natural shocked-based, extreme poverty-based and age-based transfers model. It concludes that coverage and amount of age-based transfer need to increase at priority basis as the number of elderly increases over the year. It also concludes that for extreme poverty reduction the coverage and amount of benefit as last resort of other two transfer models can be revised. Keywords: social safety nets, demographic change, vulnerability, elderly, and povert

Vegetation restoration in Northern China: A contrasted picture

China started a long- term effort to mitigate desertification and ensure the sustainability of its environment by implementing multiple large- scale national ecological restoration projects since 1978, but their success has been highly debated for a long time. Here, we estimated the change of vegetation fraction cover (VFC) in the Three- North Shelterbelt Programme (TNSP) region over the past three decades on the basis of the Normalized Difference Vegetation Index dataset from the Global Inventory Monitoring and Modeling System. We evaluate the national strategy of vegetation restoration in North China by comparing rainfall patterns, vegetation change, and national ecological restoration programs on the basis of the Global Meteorological Forcing Dataset and the China Forestry Statistical Yearbooks. We find that the western, central, and eastern parts of the TNSP region exhibited a distinct increase in vegetation coverage. The western region had the highest increase of annual precipitation, but this did not result in the highest VFC increase. We infer that ecological restoration activities are the factor leading to the observed increase in VFC in the eastern and central region compared with the western region. The low survival rate of planted trees in the forest of the TNSP region indicates that it is necessary to improve the mode of vegetation restoration to obtain optimal returns and avoid excessive investment. The success of new strategies, for example, natural restoration and quasinatural afforestation are promising as an alternative method. China’s experiences in reforestation will be very beneficial for other countries to promote land degradation mitigation and vegetation improvement in the arid and semiarid areas.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154888/1/ldr3314_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154888/2/ldr3314.pd

Control of an industrial desktop robot using computer vision and fuzzy rules

Desktop robots are suitable for various production line systems in industrial applications like dispensing, soldering, screw tightening, pick’n place, welding or marking. Despite their capabilities to meet diverse requirements, they have to be programmed off-line using waypoints and path information. Misalignments in the workspace location during loading cause injuries in the workpiece and tool. Further, in modern flexible industrial production, machinery must adapt to changing product demands, both to the simultaneous production of different types of workpieces and to product styles with short life cycles. In this paper, visual data processing concepts on the basis of fuzzy logic are applied to enable an industrial desktop robot to raise its flexibility and address these problems that limit the production rate of small industries. Specifically, a desktop robot performing dispensing tasks is equipped with a CCD camera. Visual information is used to autonomously change previously off-line stored robot programs for known workpieces or to call worker’s attention for unknown/misclassified workpieces. A fuzzy inference classifier based on a fuzzy grammar, is used to describe/identify workpieces. Fuzzy rules are automatically generated from features extracted from the workpiece under analysis. Regarding the evaluation of the system performance, different types of workpieces were tested and a good rate performance, higher than 90%, was achieved. The obtained results illustrate both the flexibility and robustness of the proposed solution as well as its capabilities for good classification of workpieces. The overall system is being implemented in an industrial environment