1998 fisheries statistics, Lake Kariba - Zimbabwe shore

The report contains data, statistics and information for both the pelagic and inshore fisheries of Lake Kariba for the year 1998. Time series data and notes for the 2 fisheries are included. The pelagic fishery exploits kapenta, the freshwater sardine Limnothrissa miodon, and is carried out all year round using light for attracting the fish. Two types of fishing vessel designs are in use (the pontoon-catamarans and the displacement monohulls) and the type of gear used is the lift net. The inshore fishery distinguishes the fishery that uses gillnets and exploits the indigenous Zambezi River fish species. This fishery is restricted to the lakeshore and uses 3 types of boats - the dugout canoe, fibreglass and metal boats

1997 fisheries statistics, Lake Kariba - Zimbabwe shore

The report provides catch records for the kapenta (Limnothrissa miodon) and inshore fisheries in the Zimbabwean waters of Lake Kariba for the year 1997. Kapenta usually constitute about 94% of the total catch from Lake Kariba; for statistical purposes catches are recorded for the 5 hydrological basins - Mlibizi, Binga, Sengwa, Bumi and Kariba. The kapenta, which occupy the open pelagic waters of the lake, represent a unit stock which is harvested by both Zimbabwe and Zambia; the artisanal fishery exploits inshore species which generally occupy water less than 10m deep along the shoreline. The Zambian and Zimbabwean inshore fisheries may therefore be considered to be exploiting 2 separate stocks. The main species in the inshore fishery are Oreochromis mortimeri, Sargochromis codringtonii, Tilapia rendalli, Labeo altivelis, Hydrocynus vittatus, Mormyrus longirostris, M.anguilloides and Clarias gariepinus

Livelihoods, Land and Political Economy: Reflections on Sam Moyo’s Research Methodology

This article focuses on the methodological lessons from Sam Moyo’s scholarship. Sam’s research is characterised by a combination of detailed empirical investigation, deep knowledge of the technical and practical aspects of agricultural production and farming livelihoods, and bigpicture political economy analysis and theory. Sam’s method is an insightful contemporary application of the method originally set out in Marx’s Grundrisse. Many contemporary explorations of agrarian political economy fail to sustain the important tension and dialectical debate, between diverse empirical realities and their ‘multiple determinations and relations’ and wider theorisation of the ‘concrete’ features of emergent processes of change. The implications of Sam’s methodological approach for the analysis of Zimbabwe’s land reform are discussed, especially in relation to the land occupations and the politics of agrarian reform since 2000

Modelling of natural fire occurrences : a case of South Africa

Abstract: In contemporary literature there have been growing concerns regarding preservations of natural ecosystems. Given the global growth in awareness of global warming, the need for natural fire prediction models has grown rapidly. Using South Africa as a case study, we evaluate the potential of integrating several natural fire prediction models and geographical information system (GIS) platforms. Initially, natural fire prone regions in South Africa were spatially demarcated basing on municipal historical data records. Thereafter, the natural fire prediction models were applied/tested in parallel to identify the best prediction models that give optimum results in predicting natural fires. The models were assessed for accuracy using historical data. Preliminary results reveal locations in the North West, Mpumalanga and Limpopo province had the highest recorded potential for natural fires. In conclusion, the work demonstrates huge potential of prediction models in informing the likelihood of natural fire outbreaks. Lastly, the work recommends the adoption of natural fire prediction models and the subsequent formulation and use of relevant future natural fire mitigation policies and techniques to avert disasters in time

The rise of policy coherence for development: a multi-causal approach

In recent years policy coherence for development (PCD) has become a key principle in international development debates, and it is likely to become even more relevant in the discussions on the post-2015 sustainable development goals. This article addresses the rise of PCD on the Western donors’ aid agenda. While the concept already appeared in the work of Organisation for Economic Co-operation and Development (OECD) in the early 1990s, it took until 2007 before PCD became one of the Organisation’s key priorities. We adopt a complexity-sensitive perspective, involving a process-tracing analysis and a multi-causal explanatory framework. We argue that the rise of PCD is not as contingent as it looks. While actors such as the EU, the DAC and OECD Secretariat were the ‘active causes’ of the rise of PCD, it is equally important to look at the underlying ‘constitutive causes’ which enabled policy coherence to thrive well

A Genomic Signal Processing-Based Coronavirus Classification Model Using Deep Learning with Web-Based Console

Various strains of Coronavirus have led to numerous deaths worldwide with CoViD-19 being the most recent. Hence, the need for various research studies to determine and develop technologies that would reduce the spread of this virus as well as aid in the early diagnosis of the disease. The Severe Acute Respiratory Syndrome CoV (SARS-CoV), which emerged in 2003, Middle East Respiratory Syndrome CoV (MERS-CoV) in 2012 and Severe Acute Respiratory Syndrome CoV 2 (SARS-CoV-2) which is generally regarded as CoViD-19, in 2019 have very similar symptoms and genetics. Without proper diagnosis of these strains, they may be mistaken for one another. Therefore, there is a need to distinguish CoViD-19 from the other two Coronaviruses to enhance prompt and specific treatment. In this study, we developed a deep learning model with a web console for the classification of genomic sequences of the three Coronavirus strains using genomic signal processing. The DNA sequences harvested from the Virus Pathogen Database and Analysis Resource (ViPR) was used as dataset and these sequences were transformed to RGB images using Voss and Z-curve encodings. A convolutional neural network (CNN) model was consequently used for classification and incorporated in a web application platform developed with the Django framework. The results of the transformation of the images highlights the similarities of the three coronaviruses in terms of visual and genetic characteristics with the CNN model distinctly classifying SARS-CoV-2, SARS-CoV and MERS-CoV with a training and validation accuracies of 95.58% and 85% respectively which compares favourably with other results in the literature

Cyber-physical energy systems modeling, test specification, and co-simulation based testing

The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification

Genetic diversity and risk factors for the transmission of antimicrobial resistance across human, animals and environmental compartments in East Africa: a review.

BACKGROUND The emergence and spread of antimicrobial resistance (AMR) present a challenge to disease control in East Africa. Resistance to beta-lactams, which are by far the most used antibiotics worldwide and include the penicillins, cephalosporins, monobactams and carbapenems, is reducing options for effective control of both Gram-positive and Gram-negative bacteria. The World Health Organization, Food and Agricultural Organization and the World Organization for Animal Health have all advocated surveillance of AMR using an integrated One Health approach. Regional consortia also have strengthened collaboration to address the AMR problem through surveillance, training and research in a holistic and multisectoral approach. This review paper contains collective information on risk factors for transmission, clinical relevance and diversity of resistance genes relating to extended-spectrum beta-lactamase-producing (ESBL) and carbapenemase-producing Enterobacteriaceae, and Methicillin-resistant Staphylococcus aureus (MRSA) across the human, animal and environmental compartments in East Africa. MAIN BODY The review of the AMR literature (years 2001 to 2019) was performed using search engines such as PubMed, Scopus, Science Direct, Google and Web of Science. The search terms included 'antimicrobial resistance and human-animal-environment', 'antimicrobial resistance, risk factors, genetic diversity, and human-animal-environment' combined with respective countries of East Africa. In general, the risk factors identified were associated with the transmission of AMR. The marked genetic diversity due to multiple sequence types among drug-resistant bacteria and their replicon plasmid types sourced from the animal, human and environment were reported. The main ESBL, MRSA and carbapenem related genes/plasmids were the CTX-Ms (45.7%), SCCmec type III (27.3%) and IMP types (23.8%), respectively. CONCLUSION The high diversity of the AMR genes suggests there may be multiple sources of resistance bacteria, or the possible exchange of strains or a flow of genes amongst different strains due to transfer by mobile genetic elements. Therefore, there should be harmonized One Health guidelines for the use of antibiotics, as well as regulations governing their importation and sale. Moreover, the trend of ESBLs, MRSA and carbapenem resistant (CAR) carriage rates is dynamic and are on rise over time period, posing a public health concern in East Africa. Collaborative surveillance of AMR in partnership with regional and external institutions using an integrated One Health approach is required for expert knowledge and technology transfer to facilitate information sharing for informed decision-making

Prior infection with SARS-CoV-2 boosts and broadens Ad26.COV2.S immunogenicity in a variant-dependent manner

The Johnson and Johnson Ad26.COV2.S single-dose vaccine represents an attractive option for coronavirus disease 2019 (COVID-19) vaccination in countries with limited resources. We examined the effect of prior infection with different SARS-CoV-2 variants on Ad26.COV2.S immunogenicity. We compared participants who were SARS-CoV-2 naive with those either infected with the ancestral D614G virus or infected in the second wave when Beta predominated. Prior infection significantly boosts spike-binding antibodies, antibody-dependent cellular cytotoxicity, and neutralizing antibodies against D614G, Beta, and Delta; however, neutralization cross-reactivity varied by wave. Robust CD4 and CD8 T cell responses are induced after vaccination, regardless of prior infection. T cell recognition of variants is largely preserved, apart from some reduction in CD8 recognition of Delta. Thus, Ad26.COV2.S vaccination after infection could result in enhanced protection against COVID-19. The impact of the infecting variant on neutralization breadth after vaccination has implications for the design of second-generation vaccines based on variants of concern