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Abstract The sub-Saharan Africa region continues to experience food insecurity, a consequence of the less productive agricultural sector that has dragged to adapt to the effects of climate change. As the region’s population continues to grow, there is a need to modernize the region’s agricultural sector to meet the increasing food demand. Although extreme atmospheric conditions cannot be entirely mitigated, however, the integration of technologies such as the Internet of things (IoT) and machine learning (ML) can increase the quantity and quality of production from the crop fields. These technologies have the potential to empower agricultural management systems to handle both climatic and farm data in an orchestrated manner, and inform the formulation of effective strategies. This study presents the design and development of a system for predicting crop yields that integrates IoT and ML. The system combines historic and current weather and crop yield data to predict seasonal crop yields. The weather parameters including, rainfall, temperature, humidity and soil moisture are collected by IoT sensors and transmitted to the cloud for crop yield forecasting. The system is used to analyze seasonal yields of Irish-Potato and Maize in Musanze District of Rwanda. Using data over different agricultural seasons, the system achieved favorable predictive accuracy with mean absolute percentage error (MAPE) values of 0.339, 0.309, and 0.177 for two seasons of Irish potatoes and one season of maize, respectively. Such predictive yield systems can reduce food insecurity risks and enhance harvest efficiency by enabling early awareness of crop production, fostering effective strategies shared among decision-makers and stakeholders. While maize and Irish potatoes were the initial case studies, expansion to include other crops and more variables is envisioned.

Climate change is causing significant damage to crop production in the central plateau zone of Rwanda, particularly affecting sorghum, food, and the incomes of smallholder farmers. Understanding farmers’ perceptions and the factors impacting their responses is crucial for improving sorghum production policies and programs. Therefore, a study was conducted to assess sorghum farmers’ perceptions of climate change and the factors determining their adaptation strategies. A multistage sampling method and a cluster random selection were utilized to select 345 respondents from five districts of the study area. The data were analyzed using descriptive statistics and a multivariate probit model. The results showed that 98.8% of farmers were aware of climate change, with deforestation being the main anthropogenic activity causing it. Consequently, 95.7% and 84.3% of farmers experienced grain yield reductions, and over 20 sorghum varieties disappeared. To address these impacts, farmers adopted five adaptation strategies: early maturing sorghum varieties (67%), adjusting planting dates (50.1%), drought-tolerant varieties (46.7%), soil conservation practices (38.3%), and crop diversification (32.8%). The multivariate probit model results showed the age and literacy level of the household head, access to extension services, access to information, access to credit, farming experience, and land size as the important factors influencing at least one of the climate change adaptation strategies. The study concluded that sorghum farmers are aware of the impacts of climate change and are acting to address its negative effects. The results suggest that the government and stakeholders should support farmers in strengthening their adaptation strategies for sustainable sorghum production.

Hot pepper (Capsicum spp.) is an important cash crop in Rwanda however, its productivity can only increase after addressing factors that limit its production. This study aimed at revealing the farmers knowledge and perceptions of virus diseases and their management in Rwanda. A survey was conducted between February and March 2018 in the main hot pepper growing areas covering low, mid and high-altitude agro-ecological zones (AEZs). Household data were collected using a structured questionnaire from 101 respondents and analysed using descriptive statistics. Majority of farmers (86.1%) indicated that pests and diseases were the main constraints to hot pepper production. Viral diseases were perceived by 71.9% of the farmers as the most serious diseases while 51.4% and 12.9% of them reported that aphids and whiteflies were the major insect pests of hot pepper, respectively. Only 17.8% and 25.7% of the farmers attributed the cause of the viral diseases to insect vectors and the use of infected seeds, respectively. The main method used to control viral diseases was application of synthetic pesticides. About two-thirds of the farmers lacked in knowledge of viral disease symptoms, spread and management across all AEZs. Majority of the farmers (80.2%) did not have access to extension service or training but relied mainly on farmer-interactions for information. Therefore, interventions such as farm-level training to raise the farmers awareness of diseases, especially viral diseases and integrated disease management are needed. This study provides baseline information for the development of sustainable integrated pest management (IPM) strategy for hot pepper viral diseases in Rwanda. [Fundam Appl Agric 2020; 5(3.000): 319-329]

Although agriculture remains the dominant economic activity in many countries around the world, in recent years this sector has continued to be negatively impacted by climate change leading to food insecurities. This is so because extreme weather conditions induced by climate change are detrimental to most crops and affect the expected quantity of agricultural production. Although there is no way to fully mitigate these natural phenomena, it could be much better if there is information known earlier about the future so that farmers can plan accordingly. Early information sharing about expected crop production may support food insecurity risk reduction. In this regard, this work employs data mining techniques to predict future crop (i.e., Irish potatoes and Maize) harvests using weather and yields historical data for Musanze, a district in Rwanda. The study applies machine learning techniques to predict crop harvests based on weather data and communicate the information about production trends. Weather data and crop yields for Irish potatoes and maize were gathered from various sources. The collected data were analyzed through Random Forest, Polynomial Regression, and Support Vector Regressor. Rainfall and temperature were used as predictors. The models were trained and tested. The results indicate that Random Forest is the best model with root mean square error of 510.8 and 129.9 for potato and maize, respectively, whereas R2 was 0.875 and 0.817 for the same crops datasets. The optimum weather conditions for the optimal crop yield were identified for each crop. The results suggests that Random Forest is recommended model for early crop yield prediction. The findings of this study will go a long way to enhance reliance on data for agriculture and climate change related decisions, especially in low-to-middle income countries such as Rwanda.

This study was carried out to determine the effect of vine and fruit pruning on watermelon (Citrullus lanatus) yield. Five pruning methods: P1=no pruning at all, P2=pruning to four vines with two fruits per vine, P3=pruning to four vines with one fruit per vine, P4=pruning to three vines with two fruits per vine and P5=pruning to three vines with one fruit per vine were evaluated on two watermelon cultivars: ‘Sugar baby’ and ‘Julie F1’ under a factorial randomized complete block design with three replications. Investigations were carried out in the seasons 2017A (short rains) and 2017B (long rains) at Karama and Rubona experimental sites belonging to Rwanda Agriculture and Animal Resources Development Board. The obtained results indicated a significant difference among the different cultivars and pruning methods tested during both seasons and at two sites. Generally, all studied parameters recorded higher values during season 2017B than in season 2017A at Rubona site. A similar trend was recorded at Karama site except that the fruit yield per plant and per hectare for plants which were pruned to three vines with one fruit reduced during season 2017B as compared to season 2017A. The highest number of fruits per plant, fruit weight, fruit yield per plant and per hectare was recorded in ‘Julie F1’ compared to ‘Sugar baby’ at both sites and during both seasons. Higher fruit weight was obtained when both cultivars were pruned to three or four vines with one fruit per vine. Higher number of fruits per plant and higher fruit yield per plant was observed under pruning to four vines with two fruits per vine at Rubona site; while at Karama site, higher fruit yield per plant was recorded under pruning to three vines with one fruit or two fruits per vines and pruning to four vines with two fruits per vine. A similar trend was observed in fruit yield per hectare. Based on results of the current study, cultivation of the hybrid ‘Julie F1’ and pruning to three vines with one fruit per vine is recommended for optimum watermelon yield with big-sized fruits.

Hot pepper is an important crop in Rwanda but viral diseases and pests are major constraints to its production. Field experiments were conducted to evaluate the resistance of 18 hot pepper genotypes (4 commercials, 5 introduced and 9 local) to natural infection by viruses and aphid infestation, in two agro­ecological zones of Rwanda. Fourteen genotypes were further evaluated for resistance to Cucumber mosaic virus (CMV) under screenhouse conditions. Disease incidence and severity were recorded in all experiments while population of aphids was assessed in the field. Diseased leaf samples from each genotype in the field were analysed using polymerase chain reaction to detect the presence of viruses, while samples from the screenhouse were analysed using serological assay. Results showed significant (p

Pharmacological targeting of the dopamine D 4 receptor (D 4 R)─expressed in brain regions that control cognition, attention, and decision-making─could be useful for several neuropsychiatric disorders including substance use disorders (SUDs). This study focused on the synthesis and evaluation of a novel series of benzothiazole analogues designed to target D 4 R. We identified several compounds with high D 4 R binding affinity ( K i ≤ 6.9 nM) and >91-fold selectivity over other D 2 -like receptors (D 2 R, D 3 R) with diverse partial agonist and antagonist profiles. Novel analogue 16f is a potent low-efficacy D 4 R partial agonist, metabolically stable in rat and human liver microsomes, and has excellent brain penetration in rats (AUC brain/plasma > 3). 16f (5-30 mg/kg, i.p.) dose-dependently decreased iv cocaine self-administration in rats, consistent with previous results produced by D 4 R-selective antagonists. Off-target antagonism of 5-HT 2A or 5-HT 2B may also contribute to these effects. Results with 16f support further efforts to target D 4 R in SUD treatment.

Background: Effective management of metastatic disease requires multidisciplinary input and entails high risk of disease-related and treatment-related morbidity and mortality. The factors that influence clinician decision-making around spinal metastases are not well understood. We conducted a qualitative study that included a multidisciplinary cohort of physicians to evaluate the decision-making process for treatment of spinal metastases from the clinician's perspective., Methods: We recruited operative and nonoperative clinicians, including orthopaedic spine surgeons, neurosurgeons, radiation oncologists, and physiatrists, from across North America to participate in either a focus group or a semistructured interview. All interviews were audiorecorded and transcribed verbatim. We then performed a thematic analysis using all of the available transcript data. Investigators sequentially coded transcripts and identified recurring themes that encompass overarching patterns in the data and directly bear on the guiding study question. This was followed by the development of a thematic map that visually portrays the themes, the subthemes, and their interrelatedness, as well as their influence on treatment decision-making., Results: The thematic analysis revealed that numerous factors influence provider-based decision-making for patients with spinal metastases, including clinical elements of the disease process, treatment guidelines, patient preferences, and the dynamics of the multidisciplinary care team. The most prominent feature that resonated across all of the interviews was the importance of multidisciplinary care and the necessity of cohesion among a team of diverse health-care providers. Respondents emphasized aspects of care-team dynamics, including effective communication and intimate knowledge of team-member preferences, as necessary for the development of appropriate treatment strategies. Participants maintained that the primary role in decision-making should remain with the patient., Conclusions: Numerous factors influence provider-based decision-making for patients with spinal metastases, including multidisciplinary team dynamics, business pressure, and clinician experience. Participants maintained a focus on shared decision-making with patients, which contrasts with patient preferences to defer decisions to the physician, as described in prior work., Clinical Relevance: The results of this thematic analysis document the numerous factors that influence provider-based decision-making for patients with spinal metastases. Our results indicate that provider decisions regarding treatment are influenced by a combination of clinical characteristics, perceptions of patient quality of life, and the patient's preferences for care., Competing Interests: Disclosure: This research was funded by National Institutes of Health (NIH-NIAMS) grants K23-AR071464 to Dr. Schoenfeld, K24-AR057827 to Dr. Losina, and P30-AR072577 to Drs. Katz and Losina. On the Disclosure of Potential Conflicts of Interest forms, which are provided with the online version of the article, one or more of the authors checked “yes” to indicate that the author had a relevant financial relationship in the biomedical arena outside the submitted work (http://links.lww.com/JBJS/G182)., (Copyright © 2020 by The Journal of Bone and Joint Surgery, Incorporated.)

Study Objective: Emergency department (ED) visits provide an important opportunity for elder abuse identification. Our objective was to assess the accuracy of the ED Senior Abuse Identification (ED Senior AID) tool for the identification of elder abuse., Methods: We conducted a study of the ED Senior AID tool in 3 US EDs. Participants were English-speaking patients 65 years old and older who provided consent or for whom a legally authorized representative provided consent. Research nurses administered the screening tool, which includes a brief mental status assessment, questions about elder abuse, and a physical examination for patients who lack the ability to report abuse or for whom the presence or absence of abuse was uncertain. The reference standard was based on the majority opinion of a longitudinal, expert, all data (LEAD) panel following review and discussion of medical records, clinical social worker notes, and a structured social and behavioral evaluation. For the reference standard, LEAD panel members were blinded to the results of the screening tool., Results: Of 916 enrolled patients, 33 (3.6%) screened positive for elder abuse. The LEAD panel reviewed 125 cases: all 33 with positive screen results and a 10% random sample of negative screen results. Of these, the panel identified 17 cases as positive for elder abuse, including 16 of the 33 cases that screened positive. The ED Senior AID tool had a sensitivity of 94.1% (95% confidence interval [CI] 71.3% to 99.9%) and specificity of 84.3% (95% CI 76.0% to 90.6%)., Conclusion: This multicenter study found the ED Senior AID tool to have a high sensitivity and specificity as a screening tool for elder abuse, albeit with wide CIs., (Copyright © 2020 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

The yam bean ( Pachyrizhus spp ) was recently introduced as a root crop with high-yield potential, considerable protein and micro-nutrient concentration to investigate its potential for food production in Rwanda. Except for Chuin types ( Pachyrizhus tuberosus ) which have high storage root dry matter (RDM) (26 to 36%), most accessions are consumed raw and are reported to have low RDM. The present study aimed to evaluate and identify adapted high yielding yam bean accessions in major agro-ecological zones of Rwanda. Field experiments with 22 accessions were conducted in 2012 at three research sites representing the major agro-ecologies of Rwanda. Strict reproductive pruning was followed to enhance fresh storage root yields. Across locations, ANOVA indicated highly significant differences ( p  < 0.01) for genotypes (G), locations (L), seasons (S) and G x L effects for storage root yield, vine yield and harvest index and accounted for 21.88%, 43.41%, 1.43% and 13.25% of the treatment sum of squares, respectively. The GGE bi-plot revealed that EC209018 is high yielding but unstable. However, genotypes, AC209034, AC209035 and EC209046, were outstanding in terms of adaptation and relative stability across the 3 locations, suggesting consistent root yields irrespective of location and environmental conditions. The GGE scatter plot showed that all genotypes formed one mega-environment for storage root yield (Karama, Musanze and Rubona) and two mega-environments for biomass yield (Karama and Rubona as one mega-environment and Musanze the second one). This study revealed that Karama is the most suitable environment for evaluation and selection of yam bean for yield components in Rwanda.

Mechanical properties of repairs of the piriformis tendon to the proximal femur were examined in a cadaveric model. Four constructs were separately tested: a suture anchor in the proximal femur, the anchor to suture interface, the suture in tendon interface, and a bone bridge style repair. The weakest interface was the anchor in the bone in cases in which the bone quality was poor. In specimens with high bone quality, the weakest interface was the suture in the anchor. A positive correlation was seen between Singh score for each femur and failure load of the anchor-bone constructs. Therefore, repairing the short external rotators after procedures involving a posterior approach to the hip may be warranted in patients with good bone quality.