Evaluating Freshness Loss of Green Tea with Q10 Method and Weibull Hazard Analysis under Accelerated Shelf Life Testing

The important quality of green tea is freshness, but high temperature, light, oxygen, and humidity during storage may reduce the freshness of green tea. Thus, this study investigated the freshness loss of green tea (FLGT) under an accelerated shelf-life testing (ASLT) by sensory evaluation and acceptability test. The FLGTs of the samples stored at 20°C, 30°C, and 40°C, were determined as 67 days, 55 days, and 45 days, respectively by the Q10 method. In addition, they were further determined as 67 days, 57 days, and 42 days, respectively, by the Weibull Hazard Analysis (WHA). The sensory evaluation and acceptability test confirmed the correctness of the above results by 2-alternative choice analysis and chemical analysis. The Q10 method was applied to predict the FLGTs stored at 4°C and −20°C which were 93 days and 150 days, which was further verified by 2-alternative choice analysis and chemical analysis. The results show that it is possible to predict the suitable drinking period of green tea during storage by the Q10 method.

Incorporating heterogeneity of travelers’ preferences into the overall hostel performance rating

Hostels have become a very popular form of accommodation and their varieties have grown steadily in recent years. To ensure the sustainability of this business model, it is necessary to understand the main drivers influencing travelers to choose a hostel accommodation. For this purpose, we conducted an online survey using convenience sampling and purposive sampling techniques. Respondents' preferences to six hostel attributes (cleanliness, location, staff, atmosphere, facilities, and cancellation policy) were determined using discrete choice analysis. Sample results showed that the most important attributes are cleanliness and location, while the atmosphere is the least important one. However, widespread heterogeneity in preferences was observed, and cluster analyzes identified three distinct groups of travelers: “cleanliness sticklers”, “location demanders” and “party seekers”. Facilities and atmosphere were found to be very important attributes for particular clusters. These findings can help design a marketing strategy for each of the identified segments to ensure sustainable business. Finally, we have proposed a new approach to calculating the hostel overall rating based on attribute importance, which shows much better discriminatory power compared to the traditional average-based approach.

The effect of using local mean versus constant reference salinity to estimate Arctic Ocean freshwater content changes

Changes of high-latitude freshwater content (FWC) play an important role in shaping the variability of polar oceans. FWC is defined as depth-integrated departure of salinity from a reference salinity Sref divided by this Sref . A constant Sref is often used for high-latitude FWC estimates. Here it is argued that for analyzing FWC spatiotemporal changes the use of local mean Sref is a better choice. Analysis of 2007 FWC anomalies in the 25–75 m layer demonstrated, for example, that the choice of Sref = 34.8 (which is often used in climate studies) leads to FWC spatial anomalies exaggerated, on average, by ~0.6 m, which is a substantial fraction of total spatial FWC changes. The problem is aggravated in areas where the difference between the local Sref and Sref = 34.8 is greater. Thus, it is concluded that using climatological mean salinities as Sref provides superior estimates of spatiotemporal Arctic Ocean FWC changes.

Considering Space Syntax in Bicycle Traffic Assignment with One or More User Classes

Modeling bicycle traffic assignment requires consideration of the various factors and criteria that could play a role in a cyclist’s route decision-making process. However, existing studies on bicycle route choice analysis tend to overlook the less tangible or measurable aspects of cyclist route decision-making, such as a cyclist’s cognitive understanding of the network and a cyclist’s biking experience. This study explores the applicability of space syntax as a route cognitive attribute in a bicycle traffic assignment model. Since space syntax is a tool that links urban spatial layout to human movement, the results of a space syntax model can be used as a cognitive attribute for modeling bicycle movements with explicit consideration of the cognitive complexities of navigating through the environment. In developing a bicycle traffic assignment model, we considered relevant attributes such as route cognition, distance, and safety and integrated multiple user class analysis to reflect different biking experience levels. Numerical experiments using the Winnipeg network are conducted to demonstrate the applicability of the proposed bicycle traffic assignment model with one or more user classes.