Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

A critical review of the state of the art of solid-phase microextraction of complex matrices I. Environmental analysis

Abstract: The present review, the first of a series of three, aims to describe recent developments in solid-phase microextraction (SPME) technology in the fields of environmental analysis applied to complex environmental matrices. We offer the reader an introductory, concise discussion of SPME fundamentals followed by a perspective on the most commonly used sample-preparation methods. We give particular attention to a comparison of the more recent SPME developments. We especially emphasize the development of new devices, such as cold fiber and thin films. We address quantitation in complex environmental matrices in this review with a concise discussion on calibration strategies for SPME methods.

The case for ecological neutral theory

Abstract: Ecological neutral theory has elicited strong opinions in recent years Here, we review these opinions and strip away some unfortunate problems with semantics to reveal three major underlying questions Only one of these relates to neutral theory and the importance of ecological drift, whereas the others involve the link between pattern and process, the tradeoff between simplicity and complexity in modeling, and the role of stochasticity and drift in ecology We explain how neutral theory cannot be simultaneously used both as a null hypothesis and as an approximation However, we also show how neutral theory always has a valuable use in one of these two roles, even though the real world is not neutral

In Situ Construction of a Cs2SnI6 Perovskite Nanocrystal/SnS2 Nanosheet Heterojunction with Boosted Interfacial Charge Transfer.

Abstract: Heterojunction engineering has played an indispensable role in the exploitation of innovative artificial materials with exceptional properties and has consequently triggered a new revolution in achieving high-performance optoelectronic devices. Herein, an intriguing halide perovskite (PVK) and metal dichalcogenide (MD) heterojunction, i.e., a lead-free Cs2SnI6 perovskite nanocrystal/SnS2 nanosheet hybrid, was fabricated in situ for the first time. Comprehensive investigations with experimental characterizations and theoretical calculations demonstrate that cosharing of the Sn atom enables intimate contact in the Cs2SnI6/SnS2 hybrid together with a type II band alignment structure. Additionally, ultrafast carrier separation between SnS2 and Cs2SnI6 has been observed in the Cs2SnI6/SnS2 hybrid by transient absorption measurements, which efficiently prolongs the lifetime of the photogenerated electrons in SnS2 (from 1290 to 3080 ps). The resultant spatial charge separation in the Cs2SnI6/SnS2 hybrid evidenced by Kelvin probe force microscopy (KPFM) significantly boosts the photocatalytic activity toward CO2 reduction and the photoelectrochemical performance, with 5.4-fold and 10.6-fold enhancements compared with unadorned SnS2. This work provides a facile and effective method for the in situ preparation of PVK-MD heterojunctions, which may significantly stimulate the synthesis of various perovskite-based hybrid materials and their further optoelectronic applications.

CEO Duality and Firm Performance during China's Institutional Transitions

Abstract: Does CEO duality - the practice of one person serving both as a firm's CEO and board chair - contribute to or inhibit firm performance? Agency theory suggests that CEO duality is bad for performance because it compromises the monitoring and control of the CEO. Stewardship theory, in contrast, argues that CEO duality may be good for performance due to the unity of command it presents. The empirical evidence, largely from developed economies, is largely inconclusive. This article joins the debate by extending empirical work to the largely unexplored context of institutional transitions. Our findings, based on an archival database covering 403 publicly listed firms and 1,202 company-years in China, offer stronger support for stewardship theory and relatively little support for agency theory. Finally, we also call for a contingency perspective to specify the nature of conditions such as resource scarcity and environmental dynamism under which CEO duality may be especially valuable.

Multiple Populations for Multiple Objectives: A Coevolutionary Technique for Solving Multiobjective Optimization Problems

Abstract: Traditional multiobjective evolutionary algorithms (MOEAs) consider multiple objectives as a whole when solving multiobjective optimization problems (MOPs). However, this consideration may cause difficulty to assign fitness to individuals because different objectives often conflict with each other. In order to avoid this difficulty, this paper proposes a novel coevolutionary technique named multiple populations for multiple objectives (MPMO) when developing MOEAs. The novelty of MPMO is that it provides a simple and straightforward way to solve MOPs by letting each population correspond with only one objective. This way, the fitness assignment problem can be addressed because the individuals' fitness in each population can be assigned by the corresponding objective. MPMO is a general technique that each population can use existing optimization algorithms. In this paper, particle swarm optimization (PSO) is adopted for each population, and coevolutionary multiswarm PSO (CMPSO) is developed based on the MPMO technique. Furthermore, CMPSO is novel and effective by using an external shared archive for different populations to exchange search information and by using two novel designs to enhance the performance. One design is to modify the velocity update equation to use the search information found by different populations to approximate the whole Pareto front (PF) fast. The other design is to use an elitist learning strategy for the archive update to bring in diversity to avoid local PFs. CMPSO is comprehensively tested on different sets of benchmark problems with different characteristics and is compared with some state-of-the-art algorithms. The results show that CMPSO has superior performance in solving these different sets of MOPs.