Farmers' perceptions on mechanical weeders for rice production in sub-Saharan Africa

Competition from weeds is one of the major biophysical constraints to rice (Oryza spp.) production in sub-Saharan Africa. Smallholder rice farmers require efficient, affordable and labour-saving weed management technologies. Mechanical weeders have shown to fit this profile. Several mechanical weeder types exist but little is known about locally specific differences in performance and farmer preference between these types. Three to six different weeder types were evaluated at 10 different sites across seven countries – i.e., Benin, Burkina Faso, Côte d'Ivoire, Ghana, Nigeria, Rwanda and Togo. A total of 310 farmers (173 male, 137 female) tested the weeders, scored them for their preference, and compared them with their own weed management practices. In a follow-up study, 186 farmers from Benin and Nigeria received the ring hoe, which was the most preferred in these two countries, to use it during the entire crop growing season. Farmers were surveyed on their experiences. The probability of the ring hoe having the highest score among the tested weeders was 71%. The probability of farmers’ preference of the ring hoe over their usual practices – i.e., herbicide, traditional hoe and hand weeding – was 52, 95 and 91%, respectively. The preference of this weeder was not related to gender, years of experience with rice cultivation, rice field size, weed infestation level, water status or soil texture. In the follow-up study, 80% of farmers who used the ring hoe indicated that weeding time was reduced by at least 31%. Of the farmers testing the ring hoe in the follow-up study, 35% used it also for other crops such as vegetables, maize, sorghum, cassava and millet. These results suggest that the ring hoe offers a gender-neutral solution for reducing labour for weeding in rice as well as other crops and that it is compatible with a wide range of environments. The implications of our findings and challenges for out-scaling of mechanical weeders are discussed

Analysis of Effects of Selected Aerosol Particles to the Global Climate Change and Health using Remote Sensing data: The Focus on Africa

The desert's dust and anthropogenic biomass burning's black carbon (BC) in the tropical regions are associated with many effects on climate and air quality. The dust and BC are the selected aerosols, which affect health by polluting the breathable air. This research discusses the effects of both the aerosols, especially while they interact with the clouds. The respective aerosol extinction optical thickness (AOT) extinction was analysed with the sensible heat from Turbulence. The research purposes to quantitatively study the remote sensing data for fine particulate matter, PM2.5, heterogeneously mixing both the dust and the pulverized black carbon's soot or ash, to analyse at which levels PM2.5 can endanger human health in the sub-Saharan region. The mainly analysed data had been assimilated from different remote sensing tools; the Goddard interactive online visualization and analysis infrastructure (GIOVANNI) was in the centre of data collection; GIS, the research data analysis software. In results, the rise and fall of the averaged sensible heat were associated with the rise and fall of averaged aerosol extinction AOT; the direct effects of the selected aerosols on the clouds are also presented. Regarding the health effects, PM2.5 quantities are throughout beyond the tolerably recommended quantity of 25μg/m3; thus, having referred to erstwhile research, inhabitants would consume food and drug supplements which contain vanillic acid during dusty seasons. Keywords: Geographic Information System (GIS), remotely sensed data, spatio-temporal (data) analysi

medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms.

Sub-optimal healthcare quality in low-resource settings is attributed in part to poor adherence to clinical guidelines. Clinical decision support systems (CDSS) help to integrate guideline-based algorithms into logical workflows and improve adherence to evidence-based recommendations, and hence quality of care. However, the process of translating paper-based guidelines into electronic algorithmic formats is often complex, inefficient, expensive, and error-prone due to reliance on advanced software development skills and clinical knowledge. In response to these challenges, we developed open-source software called the Medical Algorithm Suite (medAL-suite), consisting of four components, with a primary goal of increasing efficiency, accuracy, and transparency of CDSS creation by giving experienced clinicians, rather than software developers, greater control over the process. At the heart of the software suite is the medAL-creator that allows clinicians to design algorithms using a code-free drag-and-drop interface. Algorithms are subsequently automatically deployed in medAL-reader to service level clinicians in health facilities. CDSS implementers use medAL-data and medAL-hub to manage configuration, versioning, and deployment. Since its development, the medAL-suite has been used to digitalize complex primary care guidelines and deployed in large-scale clinical studies in Tanzania, Rwanda, Kenya, Senegal, and India, leading to notable outcomes such as the reduction of inappropriate antibiotic prescriptions and improvement in care quality. Over 300,000 pediatric outpatient consultations have been completed in Rwanda and Tanzania to date using the digital algorithm. The medAL-suite focused on democratized development, process-centric design, point-of-care utility, touch-screen interface, low cost, and low power consumption to contribute to sustainable digital systems in low-resource settings. Important future developments and adaptations as the software evolves should emphasize interoperability and scalability, primarily via integrating CDSS functionality into electronic medical records for a streamlined user experience that supports improved service quality at the point-of-care. Not applicable

Association between Personal Exposure to Household Air Pollution and Glycated Hemoglobin among Women in Rural Areas of Guatemala, India, Peru, and Rwanda: Household Air Pollution Intervention Network Trial.

Household air pollution from biomass cookstoves is a major concern in low- and middle-income countries because it may be linked with increasing rates of metabolic disorders such as diabetes. We assessed cross-sectional associations between household air pollution concentrations and glycated hemoglobin (HbA1c) levels. We analyzed data from 346 women 40 to years of age who cooked with biomass fuel and were enrolled in the Household Air Pollution Intervention Network (HAPIN) Trial in Guatemala, India, Peru, and Rwanda. We explored associations of 24-h average personal exposure to fine particulate matter [PM in aerodynamic diameter ( )], black carbon (BC), and carbon monoxide (CO) with HbA1c through individual pollutant linear models adjusted for potential confounders. We examined the effect modification of age, body mass index (BMI), and research site on the associations. We did not observe evidence of associations between HbA1c (percentage points) and 1-unit increases in log-transformed [ ; 95% confidence interval (CI): , 0.05], BC (0.01; 95% CI: , 0.13), or CO (0.07; 95% CI: , 0.10). Effect modification of the BC associations with HbA1c was observed for BMI and research site. An association in the hypothesized direction was observed among women with high BMI ( ): 0.13 (95% CI: , 0.31) compared with low BMI ( ): (95% CI: , 0.04; ). In the Guatemala research site, there was an association in the hypothesized direction with HbA1c and log-transformed BC (0.36; 95% CI: 0.03, 0.70) that was countered by an association in the opposite direction as that hypothesized for the India site ( ; 95% CI: , 0.02) and associations consistent with the null association in the Peru and Rwanda sites ( ). No other evidence of effect modification was observed. Evidence suggests a need for further research to better understand household air pollution's influence on HbA1c, with particular attention on potential effect modifiers. https://doi.org/10.1289/JHP1053

The Practice of Corrective Feedback Used by a Teacher in Teaching English

This study focuses on the practice of corrective feedback used by a teacher in SD Semesta Bilingual School. The objective of the study is to describe the type of corrective feedback used by a teacher in SD Semesta Bilingual School and to describe the frequency of each type of corrective feedback used by the teacher in teaching English in SD Semesta Bilingual School. This study is a qualitative research. The data were taken by interviewing an English teacher and taking video of teaching and learning process. The videos were transcribed which in the next step, they were analyzed for gaining the result. The data were analyzed in the noticing, collecting, and thinking process according to the theory of qualitative data analysis by Siedel (1998). According to the analysis, the teacher in SD Semesta Bilingual School used all kinds of corrective feedback. The result shows that explicit feedback is the most frequent corrective feedback which represents 24.14%. The other strategies are as follows: (2) Recast occurs 17.24%, (3) Clarification Request occurs 13.79%,(4) Metalinguistic Feedback occurs 13.79%, (5) Elicitation occurss 13.79%, and (6) Repetition occurs 13.79%. The most dominant type of using corrective feedback is explicit correction. The implication of using corrective feedback on English speaking is that, the student will be brave to active on every teaching learning activity especially on speaking

Analysis of Effects of Selected Aerosol Particles to the Global Climate Change and Health using Remote Sensing data: The Focus on Africa

The desert's dust and anthropogenic biomass burning's black carbon (BC) in the tropical regions are associated with many effects on climate and air quality. The dust and BC are the selected aerosols, which affect health by polluting the breathable air. This research discusses the effects of both the aerosols, especially while they interact with the clouds. The respective aerosol extinction optical thickness (AOT) extinction was analysed with the sensible heat from Turbulence. The research purposes to quantitatively study the remote sensing data for fine particulate matter, PM2.5, heterogeneously mixing both the dust and the pulverized black carbon's soot or ash, to analyse at which levels PM2.5 can endanger human health in the sub-Saharan region. The mainly analysed data had been assimilated from different remote sensing tools; the Goddard interactive online visualization and analysis infrastructure (GIOVANNI) was in the centre of data collection; GIS, the research data analysis software. In results, the rise and fall of the averaged sensible heat were associated with the rise and fall of averaged aerosol extinction AOT; the direct effects of the selected aerosols on the clouds are also presented. Regarding the health effects, PM2.5 quantities are throughout beyond the tolerably recommended quantity of 25μg/m3; thus, having referred to erstwhile research, inhabitants would consume food and drug supplements which contain vanillic acid during dusty seasons.&#x0D; Keywords: Geographic Information System (GIS), remotely sensed data, spatio-temporal (data) analysis</jats:p

Functional reorganization of motor and limbic circuits after exercise training in a rat model of bilateral parkinsonism.

Exercise training is widely used for neurorehabilitation of Parkinson's disease (PD). However, little is known about the functional reorganization of the injured brain after long-term aerobic exercise. We examined the effects of 4 weeks of forced running wheel exercise in a rat model of dopaminergic deafferentation (bilateral, dorsal striatal 6-hydroxydopamine lesions). One week after training, cerebral perfusion was mapped during treadmill walking or at rest using [(14)C]-iodoantipyrine autoradiography. Regional cerebral blood flow-related tissue radioactivity (rCBF) was analyzed in three-dimensionally reconstructed brains by statistical parametric mapping. In non-exercised rats, lesions resulted in persistent motor deficits. Compared to sham-lesioned rats, lesioned rats showed altered functional brain activation during walking, including: 1. hypoactivation of the striatum and motor cortex; 2. hyperactivation of non-lesioned areas in the basal ganglia-thalamocortical circuit; 3. functional recruitment of the red nucleus, superior colliculus and somatosensory cortex; 4. hyperactivation of the ventrolateral thalamus, cerebellar vermis and deep nuclei, suggesting recruitment of the cerebellar-thalamocortical circuit; 5. hyperactivation of limbic areas (amygdala, hippocampus, ventral striatum, septum, raphe, insula). These findings show remarkable similarities to imaging findings reported in PD patients. Exercise progressively improved motor deficits in lesioned rats, while increasing activation in dorsal striatum and rostral secondary motor cortex, attenuating a hyperemia of the zona incerta and eliciting a functional reorganization of regions participating in the cerebellar-thalamocortical circuit. Both lesions and exercise increased activation in mesolimbic areas (amygdala, hippocampus, ventral striatum, laterodorsal tegmental n., ventral pallidum), as well as in related paralimbic regions (septum, raphe, insula). Exercise, but not lesioning, resulted in decreases in rCBF in the medial prefrontal cortex (cingulate, prelimbic, infralimbic). Our results in this PD rat model uniquely highlight the breadth of functional reorganizations in motor and limbic circuits following lesion and long-term, aerobic exercise, and provide a framework for understanding the neural substrates underlying exercise-based neurorehabilitation