Porters have accompanied trekkers and climbers to high altitude since the earliest expeditions in the Himalayas. As the existing body of knowledge on high altitude medicine expands, the focus remains on trekkers or climbers and published literature on medical problems in the large porter population remains sparse. It is well known that porters working at high altitude in the Nepal Himalayas are often lowland dwellers and are as prone to high altitude illnesses like acute mountain sickness (AMS), high altitude pulmonary edema (HAPE) and high altitude cerebral edema (HACE) as the trekkers. Other illnesses like diarrhea, respiratory illnesses and infections also occur in this population. In this review, studies reporting these findings will be discussed along with the local context of socio-economic barriers to adequate healthcare for these porters.
An experienced 24-y-old climber on Mount Everest presented to the Base Camp medical clinic with a friction blister on his right flank. The blister was filled with clear fluid and was located about 3 cm posterior and 3 cm superior to the highest point of the right iliac crest, the site where a climbing harness would support the climber while hanging. A diagnosis of friction blister caused by a climbing harness used while traversing between Camp 2 and Camp 3 of Mount Everest was made. The blister was managed with hydrocolloid dressing, and the patient resumed climbing after 1 wk. The lesion healed with scarring at 2 wk. Friction blisters of the feet are common in climbers wearing ill-fitting shoes, but friction blisters caused by climbing harnesses are unusual and have not been reported in the literature as far as the authors are aware. All existing guidelines for blister management pertain to blisters of the feet, and there are inconsistencies in recommendations made by various authors. This unusual case in an extreme environment provides a good learning opportunity.
Android is the most widely used operating system today and occupies more than 70% share of the smartphone market. It is also a popular target for attackers looking to exploit mobile operating systems for personal gains. More and more malware are targeting android operating system like Android Banking Trojans (ABTs) which are widely being discovered. To detect such malware, we propose a prediction model for ABTs that is based on hybrid analysis. The feature sets used with the machine learning algorithms are permissions, API calls, hidden application icon and device administrator. Feature selection methods based on frequency and gain ratio are used to minimize the number of features as well as to eliminate the low-impact features. The proposed system is able to achieve significant performance with selected machine learning algorithms and achieves accuracy up to 98% using random forest classifier.
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