Search

Aralia continentalis Kitag. (A. continentalis) holds significant medicinal value among the Aralia genus. It has traditionally been employed in ethnomedicine to address a wide range of conditions, including wind–cold–dampness arthralgia; rheumatic pain in the waist and lower extremities; lumbar muscular strain; injuries resulting from falls, fractures, contusions, and strains; headache; toothache; and abscesses. Modern pharmacological research has validated its therapeutic potential, encompassing anti-inflammatory, analgesic, antioxidant, antimicrobial, insecticidal, hepatoprotective, anti-diabetic, and cytotoxic properties, among other pharmacological effects. To compile comprehensive knowledge on A. continentalis, a rigorous literature search was undertaken utilizing databases like SciFinder, PubMed, and Web of Science. This review seeks to delve into the plant's traditional applications, geographical distribution, botanical characteristics, phytochemistry, and pharmacology. The objective is to lay a foundation and propose novel research directions for exploring the plant's potential applications. Currently, one hundred and fifty-nine compounds have been isolated and identified from A. continentalis, encompassing diterpenoids, steroids, triterpenoids, volatile components, phenolics, vitamins, trace elements, and other compounds. Notably, diterpenoids, steroids, triterpenoids, volatile components, and phenolics have exhibited pronounced pharmacological effects, such as anti-inflammatory, analgesic, antioxidant, hepatoprotective, antidiabetic, and antimicrobial activities. However, despite the extensive research conducted, further studies are imperative to unravel new components and mechanisms of action, necessitating more in-depth investigations. This comprehensive exploration could pave the way for advancing and harnessing the potential of A. continentalis. [ABSTRACT FROM AUTHOR]

In view of the inefficiency and cheating in time attendance, a face recognition attendance management system has been developed. The system is developed under Windows 10 using Java language and MySql database. After the user logs on to the system, click the punch-in button. The system calls camera through openCV to take pictures, and then matches this photo with the photo in the database. If the match is successful, the system can punch in successfully. The full day's work time is calculated by clocking in to record the employee's clock-in time each time. In order to improve the speed of face recognition, the face recognition algorithm in this system first uses the perceptual hash algorithm to filter the photos, and then calls the face comparison interface of the Rainbow Soft Face Recognition Engine for face recognition, thereby improving the speed of face recognition.

Community-based tourism is a sustainable form of tourism development where tourists visit residential communities to interact with local lives and cultures for an enhanced travel experience. Identifying and tracking tourist activities in community-based tourism is particularly challenging, as tourists have shared activity spaces with residents. The paper proposes a new method to study the space–time patterns of the tourist flow using Wi-Fi data. Specifically, we have tracked Wi-Fi probe requests over six months in the Shichahai scenic area, a famous community-based tourist attraction in Beijing, China. After deriving the tourist flow from the Wi-Fi data, we have applied the empirical orthogonal function (EOF) method to the identification of the spatial aggregation pattern and the temporality of the tourist flow. A follow-up explanatory analysis examines the environmental impacts, such as weather conditions, air quality, and travel days, on the space–time patterns. The study is among the first to employ Wi-Fi data to study travel behaviours in community-based tourism. The proposed method can shed insights into a better understanding of tourist behaviours in open-space, tourism-oriented urban communities. [ABSTRACT FROM AUTHOR]