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Drawing on cultural geographical work on mobilities and landscape, this article examines parkour in Singapore, a context in which everyday mobile practices are conventionally understood to be heavily constrained and disciplined. As an urban mobile practice that involves bodily adaptation to and dynamic interaction with the prevailing built environment, parkour reveals complex relationships between the self and the landscape. For its practitioners, the doing of parkour holds potential not only for reimagining what Singapore's urban landscape is or can be but also for reconfiguring understandings of themselves. The term landscaping captures the continuous and concurrent shaping of self and landscape through parkour; landscapes affect individual bodies and are actively (re)constituted through embodied movement. The article engages parkour in more-than-representational terms. By segueing between discursive and phenomenological approaches to mobilities and landscape, a dual emphasis on corporeal experience and representational frameworks highlights how both create and/or regulate such mobile bodies and practices within the landscape.

We used modeling advantage, a concept developed by Chiou and Yang (2006), to examine the likelihood that students will identify with a particular teaching model over other competing models. In this research we examined the effects of 2 kinds of teaching styles on students' learning
styles during the collaborative teaching of technical courses. Undergraduates in a 1-semester course (229 women, 264 men; M age = 20.8 years, SD = 1.5) were given pretests and posttests to investigate how their learning styles related to their teachers' learning styles. The findings
showed that the learning styles of students were associated with their role models, which reinforced Chiou and Yang's previous work with undergraduates in different subject areas. After a semester, the learning styles of students became congruent with those of their role models. Implications
and limitations of the study are discussed.

The purpose of this paper is to examine the effect of the FDI decision on domestic investment in the case of Taiwanese manufacturing firms. In addition, we also consider the deferral effect of the FDI decision and the role of firm size. To this end, this paper takes advantage of an endogenous switching model from which consistent estimators are obtained after correcting for the self‐selection problem. The empirical results show that the effect of these manufacturing firms' FDI decisions on domestic investment is significant within the firms. Furthermore, a crowding‐out effect of FDI on domestic investment is found when Taiwanese firms engage in defensive FDI. Finally, FDI is found to have a positive influence on the domestic investment of the larger firms, while the influence is negative in the case of the smaller firms.

In advertising of caffeinated energy drinks, there appears to be a consistent emphasis reinforcing masculine identification. Greater tolerance of social pain in a situation of exclusion is a characteristic particularly identified with masculinity. In this study, we tested the priming
effect of an energy drink on men's social pain tolerance in the situation of experiencing social exclusion in Cyberball, a virtual ball-tossing game. We recruited 93 men who were undergraduate students at a university in Taiwan to participate in an experimental study. Results showed that the
men exposed to a popular caffeinated energy drink (Red Bull) tolerated being excluded from a greater number of throws in Cyberball than did those with a neutral prime or no prime. Induced conformity to masculine norms mediated the link between the energy drink prime and increased tolerance
of social pain. These findings suggest that mere exposure to energy drinks may lead men to behave according to masculine norms in a seemingly unrelated domain.

With the development of drone technology, drones have been deployed in civilian and military fields for target surveillance. As the endurance of drones is limited, large-scale target surveillance missions encounter some challenges. Based on this motivation, we proposed a new target surveillance mode via the cooperation of a truck and multiple drones, which enlarges the range of surveillance. This new mode aims to rationally plan the routes of trucks and drones and minimize the total cost. In this mode, the truck, which carries multiple drones, departs from its base, launches small drones along the way, surveils multiple targets, recycles all drones and returns to the base. When a drone is launched from the truck, it surveils multiple targets and flies back to the truck for recycling, and the energy consumption model of the drone is taken into account. To assist the new problem-solving, we developed a new heuristic method, namely, adaptive simulated annealing with large-scale neighborhoods, to optimize truck and drone routes, where a scoring strategy is designed to dynamically adjust the selection weight of destroy operators and repair operators. Additionally, extensive experiments are conducted on several synthetic cases and one real case. The experimental results show that the proposed algorithm can effectively solve the large-scale target surveillance problem. Furthermore, the proposed cooperation of truck and drone mode brings new ideas and solutions to targets surveillance problems.

We drew on affective events theory to investigate the ways in which workplace fun motivates employees and improves their job performance. Analyzing the data collected from supervisor–knowledge worker subordinate dyads in high-tech organizations in mainland China and Taiwan, we
found that employees' perceived person–organization value congruence moderated the relation between workplace fun and employees' job performance, and this effect was mediated through their experienced fun. We discuss the theoretical and managerial implications of this mediated moderation
mechanism.

In this study, a mobile air pollution sensing unit based on the Internet of Things framework was designed for monitoring the concentration of fine particulate matter in three urban areas. This unit was developed using the NodeMCU-32S microcontroller, PMS5003-G5 (particulate matter sensing module), and Ublox NEO-6M V2 (GPS positioning module). The sensing unit transmits data of the particulate matter concentration and coordinates of a polluted location to the backend server through 3G and 4G telecommunication networks for data collection. This system will complement the government's PM2.5 data acquisition system. Mobile monitoring stations meet the air pollution monitoring needs of some areas that require special observation. For example, an AIoT development system will be installed. At intersections with intensive traffic, it can be used as a reference for government transportation departments or environmental inspection departments for environmental quality monitoring or evacuation of traffic flow. Furthermore, the particulate matter distributions in three areas, namely Xinzhuang, Sanchong, and Luzhou Districts, which are all in New Taipei City of Taiwan, were estimated using machine learning models, the data of stationary monitoring stations, and the measurements of the mobile sensing system proposed in this study. Four types of learning models were trained, namely the decision tree, random forest, multilayer perceptron, and radial basis function neural network, and their prediction results were evaluated. The root mean square error was used as the performance indicator, and the learning results indicate that the random forest model outperforms the other models for both the training and testing sets. To examine the generalizability of the learning models, the models were verified in relation to data measured on three days: 15 February, 28 February, and 1 March 2019. A comparison between the model predicted and the measured data indicates that the random forest model provides the most stable and accurate prediction values and could clearly present the distribution of highly polluted areas. The results of these models are visualized in the form of maps by using a web application. The maps allow users to understand the distribution of polluted areas intuitively.

Previous researchers have pointed out that different negative affects with the same degree of negative valence may have distinct, yet predictable, influences on information processing. Based upon the perspective of "affect-as-information" and the mood repair hypothesis,
we examined differences in individuals' perspective taking arising when they felt either guilt or shame. Undergraduates (N = 114) were randomly assigned to 1 of 3 affect-inducing conditions. After receiving affect manipulation, they were asked to engage in a perspective-taking task
and to make judgments about how other people thought. Compared with participants in a neutral mood, participants experiencing guilt showed better perspective taking, and participants experiencing shame showed worse perspective taking. In general, the results suggest that an individual's inclination
to take other persons' perspectives into consideration has a differential effect on mood repair depending on whether behavior is motivated by shame or guilt.

The aim of this research was to investigate whether adolescents' willingness to correspond with cyber friends who had disclosed information about their own sexuality differed by the gender composition of correspondent and discloser dyads. The study involved 192 Taiwanese late adolescents,
all of whom reported having had sexual self-disclosure experiences in cyberspace. When males received sexual disclosure from male correspondents and females received sexual disclosure from female correspondents, they were more likely to exchange information as the topics increased in intimacy,
revealing a reciprocal strategy in impression management. Regardless of the intimacy of the topic, males showed a high level of willingness to correspond with a female discloser, revealing a liberal strategy of impression management. In contrast, females were less willing to correspond with
male disclosers, revealing a conservative strategy of impression management.