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Localization is one of the essential problems in internet of things (IoT) and wireless sensor network (WSN) applications. However, most traditional range-free localization algorithms cannot fulfill the practical demand for high localization accuracy. Therefore, a localization algorithm based on an enhanced flower pollination algorithm (FPA) with Gaussian perturbation (EFPA-G) and the DV-Hop method is proposed.FPA is widely applied, but premature convergence still cannot be avoided. How to balance its global exploration and local exploitation capabilities still remains an outstanding problem. Therefore, the following improvement schemes are introduced. A search strategy based on Gaussian perturbation is proposed to solve the imbalance between the global exploration and local exploitation search capabilities. Meanwhile, to fully exploit the variability of population information, an enhanced strategy is proposed based on optimal individual and Lévy flight. Finally, in the experiments with 26 benchmark functions and WSN simulations, the former verifies that the proposed algorithm outperforms other state-of-the-art algorithms in terms of convergence and search capability. In the simulation experiment, the best value for the normalized mean squared error obtained by the most advanced algorithm, RACS, is 20.2650%, and the best value for the mean distance error is 5.07E+00. However, EFPA-G reached 19.5182% and 4.88E+00, respectively. It is superior to existing algorithms in terms of positioning, accuracy, and robustness.
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This study investigates the impact of green bond issuance on corporate performance and further checks the intermediate effect of corporate innovation performance on the primary relationship. This study uses the quarterly panel data of Chinese non-financial listed companies in 11 subdivided industry categories from January 1, 2016, to September 30, 2020. Using the difference-in-difference (DID) model and the parallel trend test, it is found that companies' issuance of green bonds has a significant positive effect on improving corporate innovation performance and corporate value. Furthermore, the improvement of innovation performance assists in enhancing the promotion effect of green bond issuance on corporate value. Despite data limitations, this study's findings can be very helpful for all relevant stakeholders, especially regulators, to introduce conducive policies to support the issuance of green bonds in Chinese. Our findings can be useful for other emerging markets that are dealing with the same green bond-based growth-sustainability conundrum.
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Borophene has been reported as the latest very promising 2D material. We theoretically investigate the thermal radiation of ß12 borophene. ß12 borophene has been composited on Ag substrate. Theoretical research frequently mentions three types of model of ß12 borophene. The energy bands of the three models are different. Homogeneous and inversion symmetric models have a gapless Dirac cone near the K(K') point, while they are gapped in the inversion non-symmetric model. The homogeneous model has gapless triplet fermions and three-band touching points at high-symmetry points. The optical conductivity exhibits peaks due to the energy transition of high-symmetry points. The radiation spectrum follows Wien's displacement law in homogeneous and inversion symmetric models, while it is broken in the inversion non-symmetric model. The total energy radiation changes as the voltage increases for the three ß12 borophene models. The radiation of energy can be controlled by applying a suitable voltage.
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Electronic band structure and optical conductivity of single-layer graphene could be altered by applied uniaxial strain. Valley and space inversion symmetries are broken. Dirac cones are deformed. We investigate the effect of uniaxial strain on the radiative properties of graphene from the perspective of direction and modulus. Optical conductivity exhibits wealthy phenomenon due to the degeneracy of the energy band broken by strain. The total energy radiation exhibits a novel behavior of periodicity inθ, in accordance with the symmetry of the hexagonal honeycomb lattice.
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PURPOSE: This study answer calls for research on host country nationals (HCNs) by examining factors that may influence HCN task performance and contextual performance during work with their self-initiated expatriate (SIE) colleagues. PARTICIPANTS AND METHODS: Data on personality traits (extraversion, openness), socialization self-efficacy, and frequency of interaction, task, and contextual performance were collected by surveying 373 Chinese HCNs. The first author recruited the HCNs through SIEs working and living in China. SIEs who participated in this project provided the email addresses of HCNs with whom they worked. RESULTS: The frequency of interactions fully mediated the relationship between (a) extraversion with task and contextual performance and (b) openness with task and contextual performance. Only socialization self-efficacy moderated the mediating effects of extraversion on task performance via the frequency of interaction; it also moderated the mediating effects of openness on contextual performance via the frequency of interactions, but not in the hypothesized direction. CONCLUSION: This study investigated the neglected stakeholder in the expatriation process, namely, HCNs, and what factors may impact HCNs' performance during work and collaboration with their SIE colleagues.