Understanding the Persistent Low Performance of African Agriculture

2006 ◽  
Author(s):  
Sylvain Dessy ◽  
Jacques Ewoudou ◽  
Isabelle Ouellet
2014 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)

2013 ◽  
Vol 13 (3) ◽  
Author(s):  
Djawardi Djawardi ◽  
Yustiar Gunawan

The business unit's black tea processing of Perkebunan Nusantara suffered a loss of approximately Rp.60 billion. This is caused by the failure to achieve the quality and quantity of production which has been targeted by the management. Black tea processing factory "Pahit Madu" is required to improve the performance of the production process. To improve the production of black tea starts from improved production equipment through improved equipment utilization. One method ofmeasuring the effectiveness of using an apparatus is Overall EquipmentEffectiveness (OEE). OEE calculation results show that black tea factory "Pahit Madu" for four (4) years under the standard. Means, the effectiveness of utilization of equipment in the factory black tea "Pahit Madu" was still very low. This was shown by the low performance equipment in the milling unit, drying unit and sortation unit. Toimprove the performance of the plant should begin by increasing the Cutting Tearing Curling (CTC) machine in milling stations, machines Fluid Bed Dryer (FBD) and Heat Exchanger (HE) at the drying stations, and Winnower machines at the sortation stations.


2020 ◽  
Vol 24 (1) ◽  
pp. 60-66
Author(s):  
I. V. Lavrishcheva ◽  
A. Sh. Rumyantsev ◽  
M. V. Zakharov ◽  
N. N. Kulaeva ◽  
V. M. Somova

BACKGROUND. The lack of data on the epidemiology of presarcopenia/sarcopenia leads to an underestimation of the role of this condition in the structure of morbidity and mortality of haemodialysis patients in theRussian Federation. THE AIM: to study the epidemiological aspects of presarcopenia /sarcopenia in patients with chronic kidney disease stage 5d. PATIENTS AND METHODS. This study comprised 317 patients receiving programmed bicarbonate haemodialysis for 8.2 ± 5.1 years, among them 171 women and 146 men, the average age was 57.1 ± 11.3 years. The assessment of the presence of sarcopenia was performed using the method recommended by the European Working Group on Sarcopenia in Older People. RESULTS. The prevalence of presarcopenia was 0.7 % and sarcopenia 29.6 %. The incidence of skeletal muscle mass deficiency according to muscle mass index (IMM) was 30.3 %, 48.7 % showed a decrease in muscle strength according to dynamometry, and low performance of skeletal muscles according to 6 minute walk test was determined in 42.8 %. Sarcopenia patients were significantly characterized by lower body mass index, as well as higher body fat mass values. The duration of haemodialysis (χ2 = 22.376, p = 0.0001) and the patient's age (χ2 = 10.545 p = 0.014) were an independent risk factors for the development of sarcopenia. CONCLUSION. Sarcopenia is recorded more frequently in hemodialysis patients than presarcopenia. Its prevalence increases among patients of older age groups and with a hemodialysis duration of more than 5 years. The age and experience of dialysis make their independent contribution to the development of this syndrome.


Author(s):  
Gustavo Rafael Escobar Delgado ◽  
Anicia Katherine Tarazona Meza ◽  
Andy Einstein García García

The research analyzes the relationship between factors of resilience and academic performance in disabled students studying at the Technical University of Manabí. It is a correlational descriptive study conducted with a population of 88 disabled students, of which two groups were selected, one with high academic performance and the other with low performance. A questionnaire was designed and applied to determine the level of quality of life and risk factors of adolescents. Resilience was measured with the SV-RES scale created for the Latin American population.


2021 ◽  
Vol 13 (15) ◽  
pp. 8564
Author(s):  
Elizabeth Mkandawire ◽  
Melody Mentz-Coetzee ◽  
Margaret Najjingo Mangheni ◽  
Eleonora Barusi

Globally, gender inequalities constrain food security, with women often disproportionately affected. Women play a fundamental role in household food and nutrition security. The multiple roles women play in various areas of the food system are not always recognised. This oversight emerges from an overemphasis on one aspect of the food system, without considering how this area might affect or be affected by another aspect. This study aimed to draw on international commitments and treaties using content analysis to enhance the Global Panel on Agriculture and Food Security food systems framework by integrating a gender perspective. The study found that generally, there is a consensus on specific actions that can be taken to advance gender equality at specific stages of the food system. However, governance and social systems constraints that are not necessarily part of the food system, but have a significant bearing on men and women’s capacity to effectively participate in the food system, need to be addressed. While the proposed conceptual framework has some limitations, it offers a foundation on which researchers, policymakers and other stakeholders can begin conceptualising the interconnectedness of gender barriers in the food system.


Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Sang-Won Kim ◽  
Kee-Cheon Kim

In this paper, we propose a system that can recognize traffic types without prior knowledge of static features such as protocol header information by combining protocol analysis based on an ecological sequence alignment algorithm in a bioinformatics and fuzzy inference system. The algorithm proposed in this paper obtained up to a 91% level of performance at a similar level to several existing algorithms in experiments using datasets containing various types of traffic. In addition, it showed an excellent accuracy of 82.5% or more even under severe conditions that lowered the amount of data to a level of at least 40% or only included data in the middle of the traffic. This shows that the problem of dependence on initial data that frequently occurs in existing machine learning and deep learning-based traffic classification algorithms does not appear in the proposed algorithm. Furthermore, based on the ability to directly extract traffic characteristics without being dependent on static field values, it has secured the ability to respond with a small number of data by taking advantage of the flexibility of the membership function of the fuzzy inference engine. Through this, the applicability to low-power and low-performance environments such as IoT networks was confirmed. In this paper, we describe in detail the theoretical background for constructing such an algorithm and relevant experiments and considerations for actual verification.


2021 ◽  
pp. 102551
Author(s):  
Rami Eid ◽  
Ghali Jaber ◽  
Avraham N. Dancygier ◽  
Avigdor Rutenberg

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