Pyrethrum marc rates and intra-row spacing influence on selected soil chemical parameters and yield of bush bean (Phaseolus Vulgaris L.) grown on andosol under rainfed conditions

Bush bean is an important pulse crop that enriches the Rwandan diet and is a source of cash. This staple crop is widely grown in Rwanda. However, the improper spacing and inadequate application rates of organic inputs result in low yields. The purpose of this study was to evaluate the effect of intra-row-spacing and pymarc application rate on selected soil chemical parameters and bush bean (Phaseolus Vulgaris L) yield on andosol under rainfed conditions. The experiment included five pymarc rates with four replications in a randomized complete block design: P0(No fertilizer), P1(250 kg ha-1 of NPK), P2(10 t ha-1 of pymarc + 250 Kg ha-1 of NPK), P3(15 t ha-1 of pymarc + 250 Kg ha-1 of NPK) and P4(20 t ha-1 of pymarc + 250 Kg ha-1 of NPK) and 3 spacing levels: S1(40 cm x 15 cm), S2(40 cm x 20 cm) and S3(40 cm x 30 cm). The results indicated that a significant difference was found between treatments and their interactions except for pH (p<0.05). Regarding pymarc treatments, P4 contained greater amounts of organic C(5.30 %), total N(0.30 %), available P(56.70 ppm), available K(81.30 mg dm-3), exchangeable Ca(12.61 Cmol Kg-1) and Mg(5.0 Cmol Kg-1) at harvesting compared to P0 and P1. According to plant spacing, S3 held higher amounts of OC(4.85 %), av. P(55.15 %), av. K(60.94 mg dm-3), exch. Ca(11.0 Cmol Kg-1) and exch. Mg(3.6 Cmol Kg-1) than S1. There was an interaction effect of pymarc and spacing on measured soil chemical properties except for soil pH. The correlation analysis between nutrients was positive, highly significant (p<0.01), and varied from moderate to strong (0.4<r<0.7 and r>0.7) except pH. The treatment with the highest bush bean yield was P2S1 with 3.03 t ha-1 and therefore it can be recommended to bush bean farmers of the volcanic highland region

Validation of Anxiety Sensitivity Index (ASI-16) on Nonclinical Sample of Rwandans: A Cross-Sectional Study

The editorial board announced this article has been retracted on January 17, 2019.If you have any further question, please contact us at: [email protected] Article Title: Validation of Anxiety Sensitivity Index (ASI-16) on Nonclinical Sample of Rwandans: A Cross-Sectional StudyAuthor/s: Emmanuel Biracyaza, Jean Mutabaruka, Samuel HabimanaJournal Title: International Journal of Social Science StudiesISSN: 2324-8033; E-ISSN: 2324-8041Volume and Number: Vol. 7, No. 1, 2019Pages: 53-61DOI: https://doi.org/10.11114/ijsss.v7i1.391

Patient-led active tuberculosis case-finding in the Democratic Republic of the Congo.

OBJECTIVE: To investigate the effect of using volunteer screeners in active tuberculosis case-finding in South Kivu, the Democratic Republic of the Congo, especially among groups at high risk of tuberculosis infection. METHODS: To identify and screen high-risk groups in remote communities, we trained volunteer screeners, mainly those who had themselves received treatment for tuberculosis or had a family history of the disease. A non-profit organization was created and screeners received training on the disease and its transmission at 3-day workshops. Screeners recorded the number of people screened, reporting a prolonged cough and who attended a clinic for testing, as well as test results. Data were evaluated every quarter during the 3-year period of the intervention (2014-2016). FINDINGS: Acceptability of the intervention was high. Volunteers screened 650 434 individuals in their communities, 73 418 of whom reported a prolonged cough; 50 368 subsequently attended a clinic for tuberculosis testing. Tuberculosis was diagnosed in 1 in 151 people screened, costing 0.29 United States dollars (US$) per person screened and US$ 44 per person diagnosed. Although members of high-risk groups with poorer access to health care represented only 5.1% (33 002/650 434) of those screened, they contributed 19.7% (845/4300) of tuberculosis diagnoses (1 diagnosis per 39 screened). The intervention resulted in an additional 4300 sputum-smear-positive pulmonary tuberculosis diagnoses, 42% (4 300/10 247) of the provincial total for that period. CONCLUSION: Patient-led active tuberculosis case-finding represents a valuable complement to traditional case-finding, and should be used to assist health systems in the elimination of tuberculosis

Les facteurs qui entravent l’accès aux soins de santé mentale en contexte migratoire

L’accès aux soins est primordial pour éviter la dégradation de la santé mentale des immigrants. Cet article synthétise les obstacles auxquels font face les immigrants en Amérique du Nord et en Europe, ainsi que les perceptions des cliniciens à l’égard de l’intervention interculturelle. L’objectif est d’identifier les conditions et les facteurs qui entravent l’accès aux soins culturellement adaptés en contexte migratoire.Access to health care is essential to avoid the deterioration of the mental health of immigrants. This article synthesizes the obstacles facing immigrants in North America and Europe, as well as clinicians' perceptions of intercultural intervention. The objective is to identify the conditions and factors that hinder access to culturally appropriate care in the context of migration

L’ACCESSIBILITÉ DES SERVICES DE SANTÉ MENTALE EN CONTEXTE MIGRATOIRE : LA PERCEPTION DES IMMIGRANTS

Il est essentiel d’assurer une prise en charge culturellement sensible aux besoins de santé mentale des immigrants. L’adaptation des soins en contexte migratoire est vitale afin d’éviter des évaluations et des interventions pouvant nuire à la santé mentale des populations immigrantes. Ce présent article synthétise les défis caractérisant l’accès aux soins de santé mentale selon le point de vue des usagers immigrants. Il vise à mettre l’accent sur les obstacles et les facteurs qui exercent un impact décisif sur le recours de cette clientèle à ces soins.It is essential to ensure culturally sensitive care for the mental health needs of immigrants. Adaptation of care in a migratory context is vital in order to avoid evaluations and interventions that may affect the mental health of immigrant populations. This article summarizes the challenges characterizing access to care from the point of view of immigrant users. It aims to highlight the barriers and factors that have a decisive impact on this clientele’s use of conventional mental health care

Growth and yield of Watermelon as affected by different spacing and mulching types under Rubona conditions in Rwanda

Watermelon is a new introduced cash crop in ) and higher net returns (11,345,250 Rwf) with higher benefit cost ratio (2.53). This interaction should be adopted by the farmers for profitable watermelon production in the studied zone

Prediction of Stunting Among Under-5 Children in Rwanda Using Machine Learning Techniques

Objectives: Rwanda reported a stunting rate of 33% in 2020, decreasing from 38% in 2015; however, stunting remains an issue. Globally, child deaths from malnutrition stand at 45%. The best options for the early detection and treatment of stunting should be made a community policy priority, and health services remain an issue. Hence, this research aimed to develop a model for predicting stunting in Rwandan children. Methods: The Rwanda Demographic and Health Survey 2019-2020 was used as secondary data. Stratified 10-fold cross-validation was used, and different machine learning classifiers were trained to predict stunting status. The prediction models were compared using different metrics, and the best model was chosen. Results: The best model was developed with the gradient boosting classifier algorithm, with a training accuracy of 80.49% based on the performance indicators of several models. Based on a confusion matrix, the test accuracy, sensitivity, specificity, and F1 were calculated, yielding the model’s ability to classify stunting cases correctly at 79.33%, identify stunted children accurately at 72.51%, and categorize non-stunted children correctly at 94.49%, with an area under the curve of 0.89. The model found that the mother’s height, television, the child’s age, province, mother’s education, birth weight, and childbirth size were the most important predictors of stunting status. Conclusions: Therefore, machine-learning techniques may be used in Rwanda to construct an accurate model that can detect the early stages of stunting and offer the best predictive attributes to help prevent and control stunting in under five Rwandan children

Twenty years later, the cognitive portrait of openness to reconciliation in Rwanda

International audienceWith this work, we intended to draw a cognitive portrait of openness to reconciliation. No study had yet examined the potential contribution of high‐level cognitive functioning, in addition to psychological health, to explaining attitudes towards reconciliation in societies exposed to major trauma such as post‐genocide Rwanda. We measured the contribution of general cognitive capacity, analytical thinking, and subjective judgements. Our results show that higher cognitive capacity is not associated with greater openness to reconciliation. On the other hand, proneness to think analytically about the genocide predicts more favorable attitudes towards reconciliation. The latter effect is associated with more tempered judgements about retrospective facts (e.g., number of genocide perpetrators) and prospective events (e.g., risk of genocide reoccurrence). This work establishes the importance of cognitive functioning in the aftermath of political violence: A better understanding of the influence of information processing on openness to reconciliation may help improve reconciliation policies and contribute to reducing risks of conflict reoccurrence

Cost-effective and Low-complexity Non-constrained Workflow Scheduling for Cloud Computing Environment

Cloud computing possesses the merit of being a faster and cost-effective platform in terms of executing scientific workflow applications. Scientific workflow applications are found in different domains, such as security, astronomy, science, etc. They are represented by complex sizes, which makes them computationally intensive. The main key to the successful execution of scientific workflow applications lies in task resource mapping. However, task-resource mapping in a cloud environment is classified as NP-complete. Finding a good schedule that satisfies users' quality of service requirements is still complicated. Even if different studies have been carried out to propose different algorithms that address this issue, there is still a big room for improvement. Some proposed algorithms focused on optimizing different objectives such as makespan, cost, and energy. Some of those studies fail to produce low-time complexity and low-runtime scientific workflow scheduling algorithms. In this paper, we proposed a non-constrained, low-runtime, and low-time-complexity scientific workflow scheduling algorithm for cost minimization. Since the proposed algorithm is a list scheduling algorithm, its key success is properly selecting computing resources and its operating CPU frequency for each task using the maximum cost difference and minimum cost-execution difference from the mean. Our algorithm achieves almost the same cost reduction results as some of the current states of the arts while it is still low complex and uses less run-time