) Socio-Economic Factors, Occupation and Family Size as Predictors of Public Perception of Water Resources Planning in Oyo State

Abstract: The study investigated the effects of five socio-demographic variables (age, gender, occupation, family size, and socio-economic background) on public assessment of water resources planning in Oyo State. It employed a sample size of 210 respondents (101 males and 109 females) spread over six local government areas in Oyo State. It used a questionnaire in obtaining information from the respondents. The data obtained was analysed using frequency counts and multiple regression. The result showed that the five variables when taken together had a low positive relationship with public assessment of water resources planning (R=0.182). The observed F ratio is significant at 0.05 alpha level which signifies that the R2 value of 0.033 is not due to chance. In essence, 3.3% of the variance in public assessment of water resources planning in Oyo State is accounted for by a linear combination of the give demographic variables. However, occupation stood out as the best predictor of public assessment of water resources planning while the rest never contributed positively to the whole prediction. The result poses critical issues that need to be fully considered if the planning of water resources in Oyo State is to be effective and meaningful

Eliminating the Racial Disparity in Classroom Exclusionary Discipline

Advocates call for schools with high suspension rates to receive technical assistance in adopting “proven-effective” systematic supports. Such supports include teacher professional development. This call is justified given evidence that good teaching matters. But what types of professional development should be funded? Increasingly, research points to the promise of programs that are sustained, rigorous, and focused on teachers’ interactions with students. The current study tests whether a professional development program with these three characteristics helped change teachers’ use of exclusionary discipline practices—especially with their African American students. Exclusionary discipline is when a classroom teacher sends a student to the administrators’ office for perceived misbehavior. Administrators then typically assign a consequence, usually in the form of suspension (in-school or out-of school). The My Teaching Partner-Secondary (MTP-S) aims to improve teachers’ interactions with their students when implementing instruction and managing behavior. MTP-S helps teachers offer clear routines, implement consistent rules, and monitor behavior in a proactive way. The program also supports teachers in developing warm, respectful relationships that recognize students’ needs for autonomy and leadership. Teachers are paired with a coach for an entire school year (sustained approach), they regularly reflect on videorecordings of their classroom instruction and carefully observe how they interact with students, and they apply the validated Classroom Assessment Scoring System (CLASS-S) to improve the quality of their interactions (rigorous approach). In the current study, a randomized controlled trial found that teachers receiving MTP-S relied less on exclusionary discipline compared to the control teachers. Specifically, MTP-S teachers issued fewer exclusionary discipline referrals to their African American students. This is the first study to show that programs like MTP-S that focus on teacher-student interactions in a sustained manner using a rigorous approach can actually reduce the disproportionate use of exclusionary discipline with African American students. More broadly, the findings offer policymakers direction in identifying types of professional development programs that have promise for reducing the racial discipline gap

Distribution and status of the African forest buffalo Syncerus caffer nanus in south-eastern Nigeria

AbstractAlthough not categorized as threatened on the IUCN Red List, the African forest buffalo Syncerus caffer nanus is declining across its range. In Nigeria its distribution, abundance and status are virtually unknown. We conducted interviews with experienced hunters, and field surveys (linear and recce transects), to study the buffalo's distribution and ecology in the montane forests of Cross River State. General linear modelling indicated that the number of individuals varied significantly across survey areas and habitat types but not with the survey period, and there was no study area × study period interaction. Buffalo were found most commonly in mature and secondary forests. Given the species' scattered distribution, fragmentation of its habitat, and the relatively low numbers observed, Nigerian populations require a separate, regional categorization on the IUCN Red List

Development of a Scalable Edge-Cloud Computing Based Variable Rate Irrigation Scheduling Framework

Currently, variable-rate precision irrigation (VRI) scheduling methods require large amounts of data and processing time to accurately determine crop water demands and spatially process those demands into an irrigation prescription. Unfortunately, irrigated crops continue to develop additional water stress when the previously collected data is being processed. Machine learning is a helpful tool, but handling and transmitting large datasets can be problematic; more rural areas may not have access to necessary wireless data transmission infrastructure to support cloud interaction. The introduction of “edge-cloud” processing to agricultural applications has shown to be effective at increasing data processing speed and reducing the amount of data transmission to remote processing computers or base stations. In irrigation in particular, edge-cloud computing has so far had limited implementation. Therefore, an initial logic flow concept has been developed to effectively implement this new processing technique for VRI. Utilizing edge-cloud computer nodes in the field, autonomous data collection devices such as center pivot-mounted infrared canopy thermometers, soil moisture sensors, local weather stations, and UAVs could transmit highly localized crop data to the edge-cloud computer for processing. The edge computer Following the implementation of an irrigation strategy created by the edge-cloud computer with a machine learning model, data would be transmitted to the cloud (requiring transmission of only minimal model parameters), resulting in a feedback loop for continual improvement of the global model on the cloud (federated learning). VRI prescription maps from the SETMI model were used as the training data for training the machine learning model

Exploring the main threats to the threatened African spurred tortoise Centrochelys sulcata in the West African Sahel

AbstractThe African spurred tortoiseCentrochelys sulcatais the second largest terrestrial turtle, with a scattered distribution across the West African Sahel. This species is threatened and declining consistently throughout its range, but little is known about the causes of its decline. It has been hypothesized that the decline is attributable to (1) competition with domestic cattle, (2) wildfire, and (3) the international pet trade. We conducted a series of analyses to investigate these three causes. Hypotheses 1 and 2 were analysed using a spatially explicit approach, using a database of the Food and Agriculture Organization of the United Nations and logistic regression modelling; hypothesis 3 was tested by analysing the CITES trade database for 1990–2010. We found a significant negative correlation between intensity of grazing (expressed as density of cattle, km−2) and the presence of spurred tortoises, and this negative effect increased when coupled with high fire intensity, whereas wildfires alone did not have a significant influence on the species' distribution at the global scale. There was a decrease in the annual export of wild individuals for the pet trade after the introduction of export quotas by country and by year, but trade data must be considered with caution

SERENADE: The Study Evaluating Rimonabant Efficacy in Drug-Naive Diabetic Patients : Effects of monotherapy with rimonabant, the first selective CB1 receptor antagonist, on glycemic control, body weight, and lipid profile in drug-naive type 2 diabetes

OBJECTIVE—The purpose of this study was to assess the glucose-lowering efficacy and safety of rimonabant monotherapy in drug-naive type 2 diabetic patients