Macau University of Science and Technology
Recent publications
For the first time, to the best of our knowledge, we experimentally report the optical manipulation of h-shaped pulse generation in passively mode-locked fiber lasers (PMLFLs) by constructing composite filtering functions. Different composite filtering functions can be synthetized by manipulating the superposition or multiplication between different independent filtering effects in the laser cavity. Various types of h-shaped pulses, i.e., single- or dual-wavelength h-shaped pulses, can be dynamically manipulated to generate. Single-wavelength h-shaped pulses with a spike pulse and a flat-top bunch as leading and tailing edges are generated by synthetizing the superposition of F–P- and nonlinear-polarization-rotation (NPR)-based filtering effects. On the other hand, dual-wavelength h-shaped pulses operating at heterogeneous or homogeneous pulse states are formed by constructing the multiplication between Lyot- and NPR-based filtering effects. Experimental and theoretical analyses demonstrate that the synthetized composite filtering functions are beneficial to the artificial manipulation of generating different types of h-shaped pulses. Our work contributes to a deeper understanding of the dynamics of h-shaped pulses and provides an efficient way to generate nonlinear pulses with special profiles.
This research’s objective was to analyse the impact of sustainable practices, destination image, perceived value and novelty seeking on tourist satisfaction and temporal revisit intention in Yogyakarta, Indonesia. The respondents in this study were tourists in the city of Yogyakarta, with a sample size of 420 respondents. The methodology of this research employed a purposive sampling technique. Nonprobability sampling was performed using the structural equation modelling method that was processed using AMOS 22.0. The results of this research show that sustainable practices, destination image, perceived value and novelty seeking have positive and significant effects on satisfaction. Satisfaction mediates the impact of sustainable practices, destination image, perceived value and novelty seeking on revisit intention, showing that the influence of these factors on temporal revisit intention will be enhanced if tourists are satisfied. This study has implications for marketing strategies for tourism sectors in revisiting contexts. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
Fibrotic hypersensitivity pneumonitis (FHP) remains one of fatal interstitial pulmonary disease. Comprehensively dissecting the cellular heterogeneity of FHP paves the way for developing general gene therapeutic solutions for FHP. Here, utilizing an integrated strategy based on scRNA-seq, scTCR-seq, and bulk RNA-seq analysis of FHP profiles, we identified ten major cell types and 19 unique subtypes. FHP exhibited higher features of EMT and inflammation-promoting than normal control. In distinct subsets of lung macrophages in FHP, FN1 high , PLA2G7 high , and MS4A6A high macrophages with predominant M2 phenotype exhibited higher activity of inflammatory responses and para-inflammation than other macrophages. KRT17 high basal-like epithelial cells were significantly increased in FHP, and showed higher ability to induce EMT. We identified roles for ACTA2 high , COL1A1 high , and PLA2G2A high fibroblasts in FHP, which were significantly related to interstitial fibrosis. NK cells and KLRG1 ⁺ effector CD8 ⁺ T cells had greater activity in inflammation-promoting. Our results provide a comprehensive portrait of cellular heterogeneity in FHP, and highlight the indispensable role of cell subpopulations in shaping the complexity and heterogeneity of FHP. These subpopulations are potentially key players for FHP pathogenesis.
Background Brain impairment is one of a major complication of diabetes. Dietary flavonoids have been recommended to prevent brain damage. Astragalus membranaceus is a herbal medicine commonly used to relieve the complications of diabetes. Flavonoids is one of the major ingredients of Astragalus membranaceus, but its function and mechanism on diabetic encepholopathy is still unknown. Methods Type 2 diabetes mellitus (T2DM) model was induced by high fat diet and STZ in C57BL/6J mice, and BEnd.3 and HT22 cell lines were applied in the in vitro study. Quality of flavonoids was evaluated by LC–MS/MS. Differential expressed proteins in the hippocampus were evaluated by proteomics; influence of the flavonoids on composition of gut microbiota was analyzed by metagenomics. Mechanism of the flavonoids on diabetic encepholopathy was analyzed by Q-PCR, Western Blot, and multi-immunological methods et al. Results We found that flavonoids from Astragalus membranaceus (TFA) significantly ameliorated brain damage by modulating gut-microbiota-brain axis: TFA oral administration decreased fasting blood glucose and food intake, repaired blood brain barrier, protected hippocampus synaptic function; improved hippocampus mitochondrial biosynthesis and energy metabolism; and enriched the intestinal microbiome in high fat diet/STZ-induced diabetic mice. In the in vitro study, we found TFA increased viability of HT22 cells and preserved gut barrier integrity in CaCO 2 monocellular layer, and PGC1α/AMPK pathway participated in this process. Conclusion Our findings demonstrated that flavonoids from Astragalus membranaceus ameliorated brain impairment, and its modulation on gut-brain axis plays a pivotal role. Our present study provided an alternative solution on preventing and treating diabetic cognition impairment.
Background Gastric mucosal lesions (GML) are common in gastric diseases and seriously affect the quality of life. There are inevitable side effects in drug therapy. Acupuncture is an important part of traditional Chinese medicine. Electro-acupuncture (EA) has unique curative effect in treatment of GML. However, there are still few reports on the central mechanism of electro-acupuncture in treatment of GML. In this study, NMR metabonomics was used to explore the central metabolic change mechanism of electro-acupuncture in treatment of GML. Methods SD rats were randomly divided into Control, GML and EA groups. According to different intervention time, each group was further divided into 3 subgroups. This study mainly established GML model rats by 75% ethanol. Dynamic expressions of metabolites in cerebral cortex and medulla were observed by 1D ¹ H Nuclear Magnetic Resonance (NMR) metabolomics, combined with gastric mucosal histopathological examination to evaluate the time-effect relationship of electro-acupuncture at Zusanli (ST36) and Liangmen (ST21) points for 1 day, 4 days and 7 days treatment of GML. Results The results showed that the repair effect of electro-acupuncture on gastric mucosal injury was the most obvious in 4 days and stable in 7 days, and 4 days electro-acupuncture can effectively inhibit GML gastric mucosal inflammation and the expression of inflammatory cells. Meanwhile, the NMR spectrum results of medulla and cerebral cortex showed that, 21 potential metabolites were identified to participate in the mechanism of pathogenesis of GML and the regulation of electro-acupuncture, including 15 in medulla and 10 in cerebral cortex. Metabolic pathway analysis showed that the differential metabolites involved 19 metabolic pathways, which could be divided into energy, neurotransmitters, cells and cell membrane and antioxidation according to their functions. The correlation analysis of stomach, medulla and cerebral cortex shows that the stimulation signal of GML may reach the cerebral cortex from the stomach through medulla, and electro-acupuncture can treat GML by regulating the central nervous system (CNS). Conclusions 4 days electro-acupuncture treatment can significantly improve gastric mucosal injury, and the curative effect tends to be stable in 7 days treatment. Meanwhile, the pathogenesis of GML and the efficacy of electro-acupuncture involve metabolic pathways such as energy, neurotransmitters, cells and antioxidation, and electro-acupuncture can treat GML by regulating CNS.
Modifications of the surface and interfacial properties of metal halide perovskites (MHPs) have become pivotal strategies in designing high-performance photovoltaics and light-emitting diodes. Particularly, photoelectron spectroscopy (PES) plays a vital role in the advancement of MHP-based optoelectronic devices. Herein, we review the recent studies of PESs for perovskite devices. We first give an overview of the principles of PES and related techniques. Different properties of halide perovskite material unveiled by PES are then discussed, including elemental compositions, chemical states, electronic band structures, interfaces of MHPs and functional layers, ions distribution, and thermal- and moisture-induced degradation mechanism. We also revisit some of the issues when carrying out PES measurements on MHPs, such as irradiation and ambient effects and the uncertainty in determining band edge. Based on these findings, we foresee that PES techniques combined with advanced optical and electron microscopies will become increasingly important to correlate the molecular dynamics with the interfacial and chemical properties of MHP materials and devices.
Performance measurement activities (PMA) in the humanitarian supply chain (HSC) face several issues. Many of these issues are avoidable and inter-related, subsequently producing undesirable cascading effects. HSC Stakeholders are actively looking for means to reduce the complexities associated with PMA and improve its efficiency. In this paper, we identify and model the eleven strategies that can improve both PMA and the performance measurement system (PMS). Strategies were identified using detailed literature reviews and discussions with the experts and were modelled using the grey DEMATEL and m-TISM methodology. The results indicate that the most effective strategies are fundraising for PMA, Digital supply chain adoption, Top management support, Public awareness activities and Relief worker training. Four strategies can be grouped into the cause side and seven strategies on the effect side. The key recommendation is to rapidly adopt digital supply chain applications in the HSC. HSC stakeholders also need to pay increased attentions towards fundraising activities targeting PMS. This study advances the understanding of PMS in the context of HSC. The decision-maker can adopt the study’s findings to reduce the complexities that occurred during PMA.
Under the constraint of “double carbon” goal, both environmental regulation and resource endowment are important factors affecting the technological innovation efficiency. Based on the panel data of Chinese renewable energy enterprises from 2010 to 2019, this paper uses fixed effect and sys-GMM model to investigate the moderating effect of resource endowment between environmental regulation and technological innovation efficiency. The results show that the economical and supervised environment regulation are positively correlated with technological innovation efficiency, while the legal environmental regulation is the opposite. Moreover, resource endowment is positively related to technological innovation efficiency, especially for non-state-owned renewable energy enterprises, which reflects the existence of a certain degree of “resource curse” in state-owned renewable energy enterprises. In addition, resource endowment has a significant negative moderating effect in the relationship between environmental regulation and technological innovation efficiency, which shows that with the increase of resource endowment, the impact of economical and supervised environmental regulation on technological innovation efficiency will weaken, while the impact of legal environmental regulation on technological innovation efficiency will strengthen. It is helpful for the government to formulate more accurate resource and environmental regulation policies to improve the technological innovation efficiency.
In order to better guide the residents’ energy consumption behavior to low-carbon transformation and promote the realization of the “carbon neutrality” goal in China. This study adopts the theory of planned behavior and establishes a theoretical model to study residents’ low-carbon behavior (LCB) and its influencing factors. The 872 valid questionnaires were collected from the residents in Qingdao City to obtain the basic data, and the established theoretical model was empirically tested by using the structural equation model. It can be seen from the results that the “carbon neutrality” behavior intention (CBI) of residents is the most direct psychological motivation leading to their implementation of LCB (effect value = 0.662), and has a high intensity of relationship with all behavioral dimensions. Residents’ subjective norms, perceived behavioral control, and environmental values indirectly drive their behaviors through influencing their CBI, and perceived behavioral control has the greatest effect (effect value = 0.325). Besides, the transformation process of residents’ CBI to LCB is positively regulated by the perception of energy prices and energy-efficient products economy. From the mean value of the latent variables, it can be concluded that the living environment, income, and education level have a significant impact on the LCB of residents. However, the effect of age and gender on LCB is not significant. Based on the results, this study puts forward some effective suggestions to improve the LCB of Qingdao residents.
Using the optical induced deposition, we investigate a saturable absorber (SA) based on tapered fiber and double perovskite oxide Ba2LaTaO6 for ultrashort pulse fiber laser generation. The Ba2LaTaO6 is synthesized via a high-temperature solid-state reaction method. The nonlinear optical absorption of the SA is investigated experimentally. Its saturation intensity and modulation depth are 2.66 MW/cm² and 24 %, respectively. Depend on intracavity chromatic dispersion management and evanescent field interaction between SA and continuous wave laser, a conventional soliton pulse, a harmonic mode-locking and a three order soliton molecule are also achieved in passively mode-locked fiber laser. This is the first time that double perovskite oxide Ba2LaTaO6 is applied as a saturable absorber to generate an ultrashort pulse fiber laser with abnormal dispersion regimes. The results prove great potentials of Ba2LaTaO6 for future research and applications in ultrafast photonics.
Confirmatory composite analysis (CCA) was recently proposed as a viable approach to modeling and assessing forged concepts, i.e., theoretical concepts that emerge from their components within their environment. This study introduces CCA to the field of tourism and hospitality research and shows how CCA can be conducted using estimators known from structural equation modeling (SEM) with latent variables as implemented in common SEM software. It shows how emergent variables can be employed to model forged concepts and how CCA can be used for assessing them. In doing so, we explain the four major CCA steps comprising (1) model specification, (2) model identification, (3) model estimation, and (4) model assessment. To illustrate and guide scholars in applying CCA, we provide an empirical example from the field of tourism and hospitality research.
Predicting energy demands based on the past energy consumption can allow a reasonable allocation of energy resource to avoid waste and improve utilization. To this end, linear or nonlinear forecasting models are applied. Some researchers use support vector regression models to deal with the energy consumption prediction problem as they can handle with nonlinear problems through their kernel function. However, using fuzzy rule-based models based on the granulation–degranulationmechanism to predict energy consumption can better deal with the nonlinear data and further improve the robustness and the accuracy of prediction compared with the support vector regression models. In this paper we apply a first-order fuzzy rule-based model to predict the energy data. Firstly, the data is granulated in the input space, and then the number of rules is determined according to the error value between the estimated value and the actual value. The prediction task can be completed based on a small amount of input data. It has good interpretability and delivers superior predictive performance. The experimental results show that the improvement of performance index MAE of the first-order fuzzy rule-based model is 18.59%, 37.58%, 25.82% and 8.43% better than that of the Lasso model, support vector regression, zero-order fuzzy rule-based model and LSTM-RNN model, respectively, on the testing data.
The complexity that arises between linguistic use and cultural identity during learners' study abroad experience has been emphasised to understand learner investment and learner agency. Anchored in a social view of learner agency and identity, this study used qualitative research methods to unpack the identity construction and negotiation of Chinese students studying abroad by investigating their agencies, investment, and identity construction and negotiation. Data were collected through semi-structured interviews and narrative journals from Chinese university-level students with study abroad experiences in countries where English is used as the dominant language. Using learner agency, attitude and construction of identity, and identity negotiation through intercultural conflicts as the analytical lens for data analysis, the findings showed that the participants experienced identity reconstruction by investing in their linguistic resources and practices and enacting their agency. Moreover, the participants' study abroad experiences enabled them to develop a new way to invest in language learning and use, partly change their language attitudes towards accents and negotiate their identities through intercultural conflicts, which influenced the reconstruction of their previously imagined identities of native speakers of English. The study has important implications for teaching English as a second language and for preparing students to study abroad.
This paper presents an online approach to deal with the problem of state-based K-step opacity of a discrete event system modeled with labeled Petri nets. The secret states can be described by a set of either markings or generalized mutual exclusion constraints (GMECs), which is more general than the existing approaches in which the secret states are characterized by GMECs only. We formulate an integer linear programming (ILP) model to find a marking outside the set of secret states from each of the K-delayed state estimates, avoiding a complete enumeration of reachability set. Based on the ILP model, an online algorithm is developed to verify K-step opacity of an observation (i.e., an observed sequence). As an extension of K-step opacity, we define the notion of joint K-step opacity in a decentralized structure with two local sites and extend the proposed algorithm to verify the joint K-step opacity of an observation. In addition, the relationship between joint K-step opacity and K-step opacity is formally discussed.
Pastureland used for livestock grazing is globally much bigger than arable land. This study investigates the pastureland use embedded in global supply chains by using multi-regional systems input-output anlysis, tracing embodied pastureland use from source of exploitation to sink of final consumption in the global economy. The world's pastureland resources is shown reallocated through the supply chain mainly to the four major economies: EU, the United States, China, and Japan. These four economies are responsible for driving more than half of the global pastureland exploitation. Major supply chains responsible for the global reallocation of pastureland use include the cattle supply chain from Other Asia & Pacific to the United States, China, and Japan, and the cattle supply chain from Africa to EU and the Middle East. This paper demonstrates the nature and scale of the global reallocation of pastureland resources through the supply chain, highlighting the fact that the global shift of pastureland use from nature-based to economic-based may exacerbate ecological inequity between world regions. It is proposed that future policies and regulations should encourage sustainability goals not only on a regional level but on a global scale, finding pathways to sustainable and equitable livestock production by inter-regional collaboration.
The energy industry is one of the industries with high energy consumption, high pollution and high emissions in China. Low-carbon policies in the energy sector have a vital impact on China’s carbon reduction, climate change response and social development. In 2021, China’s energy status is mainly coal, accounting for about 56% of the total energy consumption. After 20 years of rapid development of clean energy in China since the 21st century, China’s wind power generation currently ranks first in the world, and the installed capacity of newly added wind power generation equipment is the largest. In terms of solar energy, China has more than 400 photovoltaic (PV) companies, and China-made solar PV panels have accounted for more than 70% of the global market share, with its own total installed capacity reaching 253.3GW. A total of 52 nuclear power units have been put into commercial operation in Mainland China, with an installed capacity of 53,485.95MWE. In terms of nuclear energy, the accumulative power generation of commercial nuclear power units accounts for about 4.99% of China’s accumulative power generation.¹ In addition, this paper takes the power industry as an example to study the low-carbon policy of China’s energy industry. By using the policy text mining method to analyze the original text types, high-frequency words and implementation effects of 96 selected policies, the social impact of low-carbon policy on carbon reduction effect, green finance development, residents’ health, job creation and some energy-consuming enterprises is obtained. This paper puts forward targeted suggestions to provide effective reference for China’s relevant policy making.
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1,535 members
Yide Liu
  • School of Business
Huajun Tang
  • Department of Decision Sciences
Brian Tomlinson
  • Faculty of Medicine
Marta Filipa Simões
  • State Key Laboratory of Lunar and Planetary Sciences
Daniel T Baptista-Hon
  • Faculty of Medicine
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