The emergence of multidrug resistant bacteria in clinically challenging situations is a global concern. Staphylococcus resistance poses a threat to available therapeutic agents in management of camel diseases. S. aureus is often isolated from mastitic camel milk. Coagulase negative Staphylococcus (CoNS) can be pathogenic in humans and animals. This cross-sectional study investigated the antimicrobial resistance phenotypes of Staphylococci species in raw camel milk from Garissa County, Kenya. A total of 231 raw camel milk samples from healthy camels were collected. Disk diffusion was used to determine antimicrobial susceptibility of the isolates. Bacteria were revived in Buffered Peptone Water (BPW). Staphylococcus isolates were cultured on Mannitol Salt agar (MSA) and Blood Agar (BA). Coagulase and catalase tests were used to biochemically characterize the isolates. Antibiotic disks were placed on Mueller Hinton Agar and incubated at 37°C for 24 hours and diameters of zones inhibition measured. The readings were recorded as either susceptible, intermediate, or resistant based on the interpretative breakpoints by the veterinary Clinical Laboratory Standards Institute (CLSI) guidelines. Antimicrobial agents tested included; Ampicillin, Streptomycin, Cephalexin, Erythromycin, Ciprofloxacin, Cefoxitin, Tetracycline and Chloramphenicol. Out of the 231 raw camel milk samples cultured, 52.8% (122/231) Staphylococci isolates were recovered. Among the Staphylococci isolates 83.6% (102) were S. aureus and 16.4% (20) were CoNS. Overall, 83 (68%) isolates were catalase positive and 122 (91.7%) showed β-haemolysis on BA culture. Highest resistance was observed against Cephalexin (81.9%) and Streptomycin (72.1%) while the lowest resistance was seen against Chloramphenicol (1.6%) and Tetracycline (3.3%). MRSA and MRCoNS were reported at 9.8% and 15% of the isolates respectively. MDR was recorded in 43.4% of the isolates resistant to at least 3 or more antimicrobial groups while 39.3% isolates were resistant to 1 or 2 antimicrobial tested.   In conclusion, the study showed that CoNS and S

Design thinking a modern human centered problem-solving concept that can be used in the face of complex problems is expected to create meaningful innovations after internalizing the problems of farmers and associating them with Climate Smart Agricultural Practices which is offering array of solutions to enable farmers mitigate the problems of Climate Change. The study aims to identify factors influencing Design Thinking ability among undergraduate students of agriculture in modelling Climate Smart Agricultural Practices. This inquiry was conducted at three Colleges of Agriculture under Central Agricultural University, Imphal, in which B.Sc. (Agriculture) degree is provided. Total of 28 final year students have been randomly selected as respondents for the study. Nine independent variable viz., Age, Gender; OGPA; Competency on ICT; Creative Problem Solving; Ability to Visualize Abstract Ideas; Memory Retention, Aptitude & Reading Behavior; and one dependent variable viz. Operationalization of Design Thinking were considered in the scientific inquiry. The binary logistic regression model was significant at p = 0.037 with AIC & BIC values of 40.86 & 54.18, respectively indicating moderate acceptable explanations of independent variables on outcome of dependent variable. With the subsequent Cox & Snell R 2 and Nagelkerke R 2 values of 0.471 and 0.629, revealed that the independent variables interacted and explained the significant outcome of the dependent variable in the range of 47.10 to 62.90%. The model identified; Age; Gender; OGPA and Creative Problem Solving had significant effect on Design Thinking. The study suggested that strategies need to be focused on development of students' Aptitude; Competency on ICT, Memory Retention; Ability to Visualize Abstract Ideas and Reading Behavior.

Aims: This study uses Social Network Analysis (SNA) to investigate the social interaction that shape student collaborative problem solving activity when undergoing Design Thinking (DT) to improvise Climate Smart Agricultural Practices (CSAPs). Place and Duration of Study: The study was conducted at the three Colleges of Agriculture (CoAs) under Central Agricultural University, Imphal at Manipur viz., the (1) CoA, Imphal at Manipur, (2) CoA, Pasighat at Arunachal Pradesh; and (3) CoA, Kyrdemkulai at Meghalaya. The study was conducted between November 2019 and February 2020. Methodology: A sample of 28 respondents who constituted fifty percent of population of final year B.Sc. (Agriculture) students was selected through simple random sampling without replacement from the three CoAs. SNA of respondent-students was analyzed using Gephi 0.9.2 software with the following attributes to understand the student community viz., average degree, modularity, average clustering coefficient and average path length. Results: The network for CoA, Imphal displayed the following characteristic as ‘Average Degree’ of 5.69, ‘Modularity’ of 0.149, ‘Average Clustering Coefficient’ of 0.468 and ‘Average Path Length’ of 1.57. In case of CoA, Pasighat, the attributes of social network were as ‘Average Degree’ of 3.63, ‘Modularity’ of 0.513, ‘Average Clustering Coefficient’ of 0.099 and ‘Average Path Length’ of 1.52j; while for the case of CoA, Kyrdemkulai, it had ‘Average Degree’ of 3.86, ‘Modularity’ of 0.024, ‘Average Clustering Coefficient’ of 0.650 and ‘Average Path Length’ of 1.360. Conclusion: For meaningful improvising of CSAPs using DT, the efficiency of social network was more functional on smaller collaborative working groups as information flow was found to be high in small groups leading to development of more ideas on DT.