No abstract

PurposeThis research tested the crossover effects of a leader’s resilience on followers’ outcomes via followers’ resilience.Design/methodology/approachSurvey data from 87 leaders with 309 followers, collected in two waves in China, were used to test the multilevel mediation hypotheses.FindingsThe results indicated that (1) resilience could transfer from the leader to followers, and (2) leader’s resilience could further contribute to alleviating followers’ job burnout, and prompt citizenship behaviors by enhancing followers’ resilience.Originality/valueThis study adopted a top-down perspective to test the crossover effects of resilience, thus expanding the resilience literature illustrating its distinct influential mechanism through a vertically interpersonal perspective.

Sleeping site selection is an important aspect of the behavioral biology of primates. Comparison of different habitats for the same species in this context enhances understanding of their adaptation to altered environments. We collected data on sleep-related behaviors for 6 groups of Francois's langur (Trachypithecus francoisi) in two habitats, in Mayanghe National Nature Reserve, Guizhou, China. Regardless of habitat, all sleeping sites were located in areas of steep terrain of ≥60°. In undisturbed habitat, sleeping sites were located only in evergreen broadleaf forest with rock caves and crevices surrounded mainly by a vegetation layer of shrub + rock. In disturbed habitat, sleeping sites were also located in mixed evergreen and deciduous broadleaf forest and in grassland, including rock caves, crevices, and pits, surrounded mainly by arbor + shrub and shrub + rock. Wild food availability was higher in undisturbed habitat than disturbed habitat, but food abundance around sleeping sites was lower. Water sources included river and seasonal gully or pond. There was strong positive correlation between use of sleeping sites away from the river valley and occurrence of seasonal water sources. The number of sleeping sites varied across groups, numbering 6, 7, and 10 for three specific groups. Few sleeping sites were used all year round. Six consecutive nights was the longest recorded run. Francois's langurs' sleeping habits differed between two habitats. In undisturbed habitat, minimizing predation risk appeared to predominate, expressed by choosing steep terrain, open visual field, and inconspicuous presleeping behavior. In disturbed habitat, along with predation avoidance, food resources may strongly influence sleeping site selection, as demonstrated by the richer food abundance and greater foraging activity around the site. Finally, water resources may influence choice of sites distant from the river; such sites were used less frequently during water shortages.

No abstract

Remote sensing change detection (RSCD) is an important yet challenging task in Earth observation. The booming development of convolutional neural networks (CNNs) in computer vision raises new possibilities for RSCD, and many recent RSCD methods have introduced CNNs to achieve promising improvements in performance. In this paper we propose a novel multidirectional fusion and perception network for change detection in bi-temporal very-high-resolution remote sensing images. First, we propose an elaborate feature fusion module consisting of a multidirectional fusion pathway (MFP) and an adaptive weighted fusion (AWF) strategy for RSCD to boost the way that information propagates in the network. The MFP enhances the flexibility and diversity of information paths by creating extra top-down and shortcut-connection paths. The AWF strategy conducts weight recalibration for every fusion node to highlight salient feature maps and overcome semantic gaps between different features. Second, a novel perceptual similarity module is designed to introduce perceptual loss into the RSCD task, which adds perceptual information, such as structure and semantic information, for high-quality change map generation. Extensive experiments on four challenging benchmark datasets demonstrate the superiority of the proposed network compared with eight state-of-the-art methods in terms of F1, Kappa, and visual qualities.

In virtual environments, virtual hand interactions play key roles in the human-computer interface. Specifically, the virtual grasping of 3D objects provides an intuitive way for users to interact with virtual objects. This paper demonstrates the creation of a sophisticated virtual hand model simulating natural anatomy in its appearance and motion. To achieve good visual realism, the virtual hand is modeled with metaball modeling, and visually enhanced by applying texture mapping. For realistic kinematics modeling, a three-layer model (skeleton, muscle and skin layers) is adopted to handle the motion as well as the deformation of the virtual hand. We also present an approach for virtual grasping of 3D objects with the realistic virtual hand driven by a CyberGlove dataglove. Grasping heuristics are proposed based on the classification with the shapes of objects, and simplified proxies for the virtual hand are used for the purpose of real-time collision detection between the virtual hand and 3D objects.

No abstract

No abstract