This paper deals with the effect of Problem-Based Learning on Colleges of Education students’ achievement in, and attitude toward Probability in Tamale Metropolitan of Ghana. The research design was quasi-experimental pre-test post-test two-group design. Convenience and simple random sampling techniques were employed to obtain a sample of 100 students which comprised of 51 students in the control group and 49 in the experimental group. Tests, questionnaire and semi-structured interview were the instruments used for data gathering. Descriptive, Independent samples t-test, ANCOVA and paired samples t-test were used in analysing data. The results indicated that there was a statistically significant difference between students of the experimental group exposed to Problem-Based Learning approach and control group exposed to Traditional Method. Problem-Based Learning developed students critical thinking, good problem solvers and self-directed learners which would lead to life-long memory of Probability concepts and its applications to real-life situations.

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Coagulase negative staphylococci (CNS) are primary cause of mastitis in ruminant animal, and can either be transmitted by contagious or by environmental means. Therefore, we speculate whether there are similarity in the species distribution of CNS colonsing the anterior nare and milk of ruminant animals that can serve as source of infection. The study examined the species of CNS from the anterior nare of ruminant animals and contact persons. A total of 75 CNS isolates were analysed using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), mecA gene detection by PCR assay and antibiotic susceptibility testing according to CSLI guidelines. Overall, four CNS spp were identified, S.sciuri predominate 71 (96%) and were recovered from all samples analysed, while one specie each (1.3%) of S.lentus, S.condementii and S.xylosus (1.3%) respectively. No mecA gene was detected in the CNS spp identified. The CNS spp demonstrated low to moderate resistance pattern (15-30%) to all antibiotics tested. In conclusion, the study provided a baseline epidemiological information on CNS spp colonizing the ruminants ruminant animal and contact persons. In addition, non-detection of mecA gene and high sensitivity pattern demonstrated by the CNS species.

The objective of the study is to develop low-cost IoT based sensor to monitor real-time greenhouse gases (GHG) emissions data from selected industry locations (city blocks) in a top-down approach. Three (3) industry locations were selected within the Suame Industrial complex (the largest single cluster of artisanal engineering and light manufacturing in Sub Saharan Africa and even Africa) which has no reported GHG emissions data. A GHG monitor was developed using Atmega328 microcontroller and a sim800I GSM module was used to collect a 24-hour real-time minute-by-minute emissions data from the selected industry locations. A MQ-4 (methane/natural gas sensor), MQ-135 (Nitrous Oxide sensors) and DHT22 (temperature and humidity sensor) were used in the GHG monitor design. The GHG of concern were carbon dioxide, methane and nitrous oxide. A total of 3627 emissions data were collected and analyzed from the three (3) industry locations. Location 3 had the highest average carbon dioxide emissions of 508.11 ppm, followed by location 2 with 477.31 ppm with the least emissions in location 1 with 472.51 ppm which are above the global carbon dioxide average of 414.7 ppm. The average methane emission was highest in location 1 with 0.1599 ppm (1599 ppb), followed by location 3 with 0.1366 ppm (1366 ppb) with the least average methane emission of 0.1358 ppm (1358 ppb) in location 2 which are slightly below the global methane average of 1895.7 ppb. The MQ-135 nitrous oxide sensor reported zero emissions data throughout the deployment at the various industry locations which indicated the nitrous oxides emission in the selected sample site is negligible or below the detectable range of the sensor.