ALBERT

Beschreibung: Users more easily become lost in complex indoor environments than in outdoor environments. Users with diverse backgrounds encounter different self-location, route memorization, and route following problems during wayfinding. This study intends to explore gender and age effects on the use of indoor maps for wayfinding in real environments. We used eye-tracking and retrospective verbal protocol methods to conduct a wayfinding experiment in a newly opened building. Statistical data were collected and three findings were obtained. Finding 1: Males had no significant differences with females in indoor self-location, route reading, and route following. However, males paid less visual attention to the landmark and legend than females during route reading. Finding 2: Age-related differences were significant in indoor wayfinding. Younger adults generally outperformed elderly adults in wayfinding in real indoor environments. Finding 3: Gender and age interactive effects were significant in self-location and route memorization. The mean differences of visual attention on the self-location map reading and route memorization between males and females increased with age.

Beschreibung: This study evaluated compliance with the comprehensive smoke-free law in public indoor places introduced in Shanghai in March 2017. Observations and PM2.5 monitoring over 30 min intervals in 8 types of the venue were conducted three times: within a month before implementation and 3- and 12-months post implementation. Observations of evidence of smoking decreased from 66.2% before legislation to 52.8% three months after (p = 0.002) and 49.7% one year after (p 〈 0.001). The density of lit cigarettes also reduced significantly after implementation (p 〈 0.001). When adjusting for outdoor, indoor PM2.5 levels were significantly lower after the legislation, but only by a small amount (three months later: −0.27, p = 0.08; one year later: −0.12; p = 0.03). Evidence of compliance was weakest in farmer’s markets and bars, and smoking in male toilets did not change significantly. The reduction in smoking was affected by the management performance of their obligations. The comprehensive smoke-free law led to modest reductions in smoking and PM2.5 levels as a result, but from levels suggesting quite high levels of pre-compliance. However, compliance was limited in some areas, suggesting more effort is required on management to gain better compliance in some places like farmer’s markets, bars, and toilets.

Beschreibung: For a transcendental meromorphic function f ( z ) , the main aim of this paper is to investigate the properties on the zeros and deficiencies of some differential-difference polynomials. Some results about the deficiencies of some differential-difference polynomials concerning Nevanlinna deficiency and Valiron deficiency are obtained, which are a generalization of and improvement on previous theorems given by Liu, Lan and Zheng, etc.

Beschreibung: Four kinds of cold recycling (CR) mixtures with different asphalt emulsions were studied for their high-temperature performance in both binder properties and internal structures aspects. Digital image processing was introduced to determine the thickness spectrum for the asphalt mortar of the CR mixtures from a mesoscopic perspective. The time–temperature sweep (TTS) test was conducted to obtain the rheological parameters of each corresponding emulsified residue and the permanent deformation performance of each CR mixture was measured by dynamic creep test. A principle component analysis (PCA) was used to compare the typical performance parameters of the CR mixtures and find the factors controlling the rutting resistance of CR mixtures. The results show that the high-temperature performance of the CR mixtures with a modified emulsified asphalt showed improvements relative to the nominal case. Including Marshall stability, several parameters from the rheological properties of binder (G*/sinδ, flow number) and mortar thickness (max, range proportion 0–10 mm) could significantly influence the high-temperature performance and rutting resistance of the CR mixtures.

Beschreibung: Dynamic monitoring of carbon storage in forests resources is important for tracking ecosystem functionalities and climate change impacts. In this study, we used multi-year Landsat data combined with a Random Forest (RF) algorithm to estimate the forest aboveground carbon (AGC) in a forest area in China (Hang-Jia-Hu) and analyzed its spatiotemporal changes during the past two decades. Maximum likelihood classification was applied to make land-use maps. Remote sensing variables, such as the spectral band, vegetation indices, and derived texture features, were extracted from 20 Landsat TM and OLI images over five different years (2000, 2004, 2010, 2015, and 2018). These variables were subsequently selected according to their importance and subsequently used in the RF algorithm to build an estimation model of forest AGC. The results showed the following: (1) Verification of classification results showed maximum likelihood can extract land information effectively. Our land cover classification yielded overall accuracies between 86.86% and 89.47%. (2) Additionally, our RF models showed good performance in predicting forest AGC, with R2 from 0.65 to 0.73 in the training and testing phase and a RMSE range between 3.18 and 6.66 Mg/ha. RMSEr in the testing phase ranged from 20.27 to 22.27 with a low model error. (3) The estimation results indicated that forest AGC in the past two decades increased with density at 10.14 Mg/ha, 21.63 Mg/ha, 26.39 Mg/ha, 29.25 Mg/ha, and 44.59 Mg/ha in 2000, 2004, 2010, 2015, and 2018. The total forest AGC storage had a growth rate of 285%. (4) Our study showed that, although forest area decreased in the study area during the time period under study, the total forest AGC increased due to an increment in forest AGC density. However, such an effect is overridden in the vicinity of cities by intense urbanization and the loss of forest covers. Our study demonstrated that the combined use of remote sensing data and machine learning techniques can improve our ability to track the forest changes in support of regional natural resource management practices.