This article focuses upon the postgraduate learner and the nature of support offered to them within increasingly popular online programs. In recent times learners are more readily considering online education options as opposed to face-to-face classroom environments, particularly when learning is beyond an undergraduate level. In seeking to fully utilise the opportunities associated with online learning this article provides practical recommendations for potential postgraduate learners, their teachers and the learning environment itself. The utility of the recommendations discussed extend to a range of domains that are being presently taught and facilitate the design and delivery of future online learning approaches.

This study aims to determine analysis of sports injuries in cycling during the covid-19 pandemic. This type of research is a qualitative research. The population of this research is the people of Lampung province. The informant retrieval technique uses the Snowball Sampling technique. Data collection techniques using observation, interviews, and document analysis. The data validity technique uses two triangulation techniques, namely data triangulation and method triangulation. Data analysis was carried out in four stages, namely: the data collection stage, the data reduction stage, the data presentation stage, and the conclusion drawing stage. This study can be concluded that the injury is a problem that arises in a person after doing physical activity or sports both in training and competing, the incident can occur suddenly and is difficult to avoid. Sports injuries experienced by a person will cause pain caused by damage to body structures or functions such as bones, joints, ligaments and muscles, either in the form of closed injuries or open injuries. The analysis of injuries in cycling sports include: Plantar fascilits, Ankle sprains, Achilles Ankle Tendon, Muscle Tension, Shin Splint, Piriformis syndrome and low back pain, Neck Pain and Hand Injury.

The Sylhet region is famous for its citrus cultivation. However, the citrus biodiversity in this region is decreasing day by day. Therefore, the current study was carried out to investigate the present status of Citrus cultivation at Rajnagar upazila of Moulvibazar district under Sylhet division. Primary data was collected from 80 respondents from four selected unions in Rajnagar upazila through face-to-face interviews using a well-structured questionnaire and field observation from April to June 2021. During field observation, a total of 13 citrus species were found in the study area. However, farmers opined that the previous 15 species were available in that area, which indicates that conservation of the citrus species is required to maintain citrus biodiversity. Field observation and farmers' opinions revealed that Kagzi lebu (Citrus aurantifolia) and Elachi lebu (C. limon) were the most dominant citrus species in that area, and farmers cultivated those species for their food items such as fruit, salad, or pickles. Most of the farmers collect their citrus planting materials from the local market. However, due to the poor market price, they are losing interest in continuing citrus cultivation on their farm or homestead. Citrus disease (such as die back, citrus canker, and so on) and insect pests (such as citrus leaf miner, bark and stem borer, and so on) were the major problems causing reductions in citrus species. Farmers should be trained by the government and non-government organization on citrus orchard management and the value of citrus biodiversity in order to conserve citrus biodiversity on-farm.

This paper is a simple tutorial for researchers interested in ant colony optimization (ACO) in general and max-min ant system (MMAS) in particular. The paper compares the differences in implementing these algorithms to solve sequencing and selection problems. For selection problems, we use the famous knapsack problem (KP) to demonstrate how MMAS can be used, wherease, for the sequencing problem, we use the famous travelling salesman problem (TSP). Results from the literature shows how a MMAS algorithm can outperform other meta-heuristics in solving these two types of problems.