Hong Kong Baptist University

About: Hong Kong Baptist University is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: China & Population. The organization has 7811 authors who have published 18919 publications receiving 555274 citations. The organization is also known as: Hong Kong Baptist College & HKBU.

Fused Benzothiadiazole: A Building Block for n-Type Organic Acceptor to Achieve High-Performance Organic Solar Cells

Abstract: Narrow bandgap n-type organic semiconductors (n-OS) have attracted great attention in recent years as acceptors in organic solar cells (OSCs), due to their easily tuned absorption and electronic energy levels in comparison with fullerene acceptors. Herein, a new n-OS acceptor, Y5, with an electron-deficient-core-based fused structure is designed and synthesized, which exhibits a strong absorption in the 600-900 nm region with an extinction coefficient of 1.24 × 105 cm-1 , and an electron mobility of 2.11 × 10-4 cm2 V-1 s-1 . By blending Y5 with three types of common medium-bandgap polymers (J61, PBDB-T, and TTFQx-T1) as donors, all devices exhibit high short-circuit current densities over 20 mA cm-2 . As a result, the power conversion efficiency of the Y5-based OSCs with J61, TTFQx-T1, and PBDB-T reaches 11.0%, 13.1%, and 14.1%, respectively. This indicates that Y5 is a universal and highly efficient n-OS acceptor for applications in organic solar cells.

Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions

Abstract: To enhance environmental sustainability, many countries will electrify their transportation systems in their future smart city plans. So the number of electric vehicles (EVs) running in a city will grow significantly. There are many ways to re-charge EVs' batteries and charging stations will be considered as the main source of energy. The locations of charging stations are critical; they should not only be pervasive enough such that an EV anywhere can easily access a charging station within its driving range, but also widely spread so that EVs can cruise around the whole city upon being re-charged. Based on these new perspectives, we formulate the Electric Vehicle Charging Station Placement Problem (EVCSPP) in this paper. We prove that the problem is non-deterministic polynomial-time hard. We also propose four solution methods to tackle EVCSPP and evaluate their performance on various artificial and practical cases. As verified by the simulation results, the methods have their own characteristics and they are suitable for different situations depending on the requirements for solution quality, algorithmic efficiency, problem size, nature of the algorithm, and existence of system prerequisite.

Coping with Workplace Ostracism: The Roles of Ingratiation and Political Skill in Employee Psychological Distress

Abstract: The study reported here examined the relationship between workplace ostracism and employee psychological distress (i.e. job tension, emotional exhaustion, and depressed mood at work) by focusing on the joint moderating effects of ingratiation and political skill. Data from a two-wave survey of 215 employees in two oil and gas firms in China indicated that as predicted, workplace ostracism was positively related to psychological distress. Moreover, the findings showed that when employee political skill was high, ingratiation neutralized the relationship between workplace ostracism and psychological distress, but when it was low, ingratiation exacerbated the relationship.

Visible thermal person re-identification via dual-constrained top-ranking

Abstract: Cross-modality person re-identification between the thermal and visible domains is extremely important for night-time surveillance applications. Existing works in this filed mainly focus on learning sharable feature representations to handle the cross-modality discrepancies. However, besides the cross-modality discrepancy caused by different camera spectrums, visible thermal person re-identification also suffers from large cross-modality and intra-modality variations caused by different camera views and human poses. In this paper, we propose a dual-path network with a novel bi-directional dual-constrained top-ranking loss to learn discriminative feature representations. It is advantageous in two aspects: 1) end-to-end feature learning directly from the data without extra metric learning steps, 2) it simultaneously handles the cross-modality and intra-modality variations to ensure the discriminability of the learnt representations. Meanwhile, identity loss is further incorporated to model the identity-specific information to handle large intra-class variations. Extensive experiments on two datasets demonstrate the superior performance compared to the state-of-the-arts.