Conditional Probabilities and Contingency Space Analysis: A Statistical Overview of the Relationship Between Student Behavior and Teacher Consequence

The research on classroom management systems has provided a comprehensive evidence base for effective classroom management strategies for teachers to adopt in their classrooms. The most common strategies found in the literature are rules, reprimands, and praise. Reprimands and praise are used by the teacher as part of the reinforcement schedule to implement classroom rules (Acker & O'Leary, 1987; Sherman & Cormier, 1974). The purpose of the current study was to analyze the conditional probabilities of teachers' use of reprimands and praise following student disruption and on-task behavior from baseline to an intervention known as the Class-Wide Function-related Intervention Teams (CW-FIT; Wills et al., 2010). The conditional probabilities of teacher reprimands and praise given student disruptive and on-task behavior were also examined through a contingency space analysis (CSA; Martens, DiGennaro, Reed, Szczech, & Rosenthal, 2008). The participants included 50 teachers and 100 students. Results showed that reprimands followed disruptive behavior less frequently during CW-FIT. Results also showed that praise followed on-task behavior more frequently during CW-FIT. In other words, teachers were more likely to use praise following on-task behavior from baseline phase to CW-FIT phase than they were to use reprimands following disruptive behavior. As a means of evaluating the CW-FIT intervention program, CSA depicts that the intervention resulted in the anticipated changes in the behavior of both the teachers and the students, as teacher attention was more likely dependent or contingent on on-task behavior than it was on student disruption, and to a slightly higher extent than during baseline. When CW-FIT was implemented, the conditional probabilities that teacher praise was used given on-task behavior increased for a majority of students. Results imply that CW-FIT improves the teacher-student interaction for students at-risk for behavioral disorders when used as a classroom management system

The rolling circle amplification and next generation sequencing approaches reveal genome wide diversity of Kenyan cassava mosaic geminivirus

Rolling circle amplification is a simple approach of enriching populations of single-stranded DNA plant begomovirus genomes (genus, Begomovirus; family,  Geminiviridae). This is an innovative approach that utilizes the robustness of the bacteriophage phi29 DNA polymerase used in circle amplification, together with deep sequencing using Illumina Miseq and bioinformatics to assess population  diversity of begomoviruses in naturally infected cassava. The approach is suitable for detecting rare members in a population in begomoviral populations in situation where mixtures of isolates, strains, and multiple species occur. The main objectives were to increase the sensitivity of detection of next generation sequencing by enriching it using rolling circle amplification then determination of the diversity of  the cassava mosaic geminivirus. This was done by total nucleic acids isolated from symptomatic, field cassava infected plants, then using rolling circle amplification to multiply the less abundant viral  sequences. Enriched and non-enriched virus-libraries were subjected to deep sequencing using Illumina Miseq. Using  bioinformatic CLC Genomics 5.5.1 software programs the quality assessment of reads and contig assembly of viral sequences. This was done through de novo and reference-guided assembly. The identity and diversities of the begomoviral sequences were compared with sequences in Sanger sequencing of viral components deposited in the NCBI Gene Bank. In this study we have demonstrated that RCA increases the chances of detecting the virus by approximately 10 to 1000 fold and wide genome diversity of cassava mosaic geminivirus in various cassava growing zones in Kenya were detected. In conclusion, this approach described herein is simple and will enhance the exploration of begomovirus diversities from cassava infected plants, irrespective of their viral abundance. This will make it possible for routine screening of field samples as the cost of deep sequencing NGS is decreasing and the advances of bioinformatic software development become enhanced. This is the first report of the RCA-Illumina-NGS approach to explore cassava infected with begomoviruses under field conditions and their diversities. Key words: Illumina Miseq sequencing, geminivirus, ssDNA viruses, viral sequence enrichment, de novo genome assembly, rolling cycle amplification (RCA)

Cassava brown streak disease: historical timeline, current knowledge and future prospects

Cassava is the second most important staple food crop in terms of per capita calories consumed in Africa and holds potential for climate change adaptation. Unfortunately, productivity in East and Central Africa is severely constrained by two viral diseases: cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). CBSD was first reported in 1936 from northeast Tanzania. For approximately seventy years CBSD was restricted to coastal East Africa and so had a relatively low impact on food security compared to CMD. However, at the turn of the 21st century CBSD re-emerged further inland, in areas around Lake Victoria and it has since spread through many East and Central African countries, causing high yield losses and jeopardising the food security of subsistence farmers. This recent re-emergence has attracted intense scientific interest, with studies shedding light on CBSD viral epidemiology, sequence diversity, host interactions and potential sources of resistance within the cassava genome. This review reflects on 80 years of CBSD research history (1936 – 2016) with a timeline of key events. We provide insights into current CBSD knowledge, management efforts and future prospects for improved understanding needed to underpin effective control and mitigation of impacts on food security

Coffee Leaf Rust (Hemileia vastatrix) in Kenya—A Review

Coffee is one of the most important cash crops and beverages in the world. Production of coffee is limited by many factors, which include insect pests and diseases, among others. One of the most devastating coffee diseases in many coffee-producing countries is Coffee Leaf Rust caused by the fungus Hemileia vastatrix. Kenya is a coffee-producing country and has conducted studies to understand and manage the disease. Management strategies for the disease include the development and use of fungicide spray programs, cultural control practices, breeding resistant coffee varieties, and biological control agents. This paper reviews the status of the disease and management options applied in Kenya