Your search

The information paradox suggests that the black hole loses information when it emits radiation. In this way, the spectrum of radiation corresponds to a mixed (non-pure) quantum state even if the internal state generating the black hole is expected to be pure in essence. In this paper we propose an argument solving this paradox by developing an understanding of the process by which spontaneous symmetry breaks when a black hole selects one of the many possible ground states and emits radiation as a consequence of it. Here, the particle operator number is the order parameter. This mechanism explains the connection between the density matrix, corresponding to the pure state describing the black hole state, and the density matrix describing the spectrum of radiation (mixed quantum state). From this perspective, we can recover black hole information from the superposition principle, applied to the different possible order parameters (particle number operators).

This study aims to explore the difficulties and challenges faced by regular primary school teachers in Macao when dealing with inclusive students in the classroom. As the concept of inclusive education deepens, the number of inclusive students in Macao has been increasing, but the growth of schools participating in inclusive education has been slow, posing more challenges for regular primary school teachers. This research adopts a mixed-method approach, combining classroom observations and in-depth interviews to comprehensively understand the issues teachers face. The study conducted structured observations of 15 lessons, covering 5 grade levels and 5 subjects, and carried out in-depth interviews with 7 teachers. The findings reveal: (1) Inclusive students generally experience difficulties in classroom participation, task completion, and independent learning; (2) Teachers generally lack sufficient professional knowledge and skills to effectively address the needs of inclusive students; (3) Schools lack resources and support, including adaptive curriculum arrangements and assessment methods for inclusive students; (4) There are contradictions between current educational policies and practical needs, such as the no-retention policy for grades 1-4, which may lead to missing the best intervention timing for inclusive students. Based on the research results, this paper proposes recommendations including strengthening teacher professional development, optimizing school resource allocation, improving educational policies, reinforcing early identification and intervention mechanisms, and promoting home-school cooperation. These findings and suggestions provide important references for policy-making and practical improvements in inclusive education in Macao. 本研究旨在探討澳門普通小學教師在課堂應對融合學生時所面臨的困難及挑戰。隨著融合教育理念的普及，澳門融合學生數量不斷增加，但參與融合教育的學校數量增長緩慢，使得普通小學教師面臨更多挑戰。本研究採用混合研究方法，結合課堂觀察和深度訪談，以全面了解教師面臨的問題。 研究對15節課進行了結構化觀察，涵蓋5個年級和5個學科，並對7位教師進行了深度訪談。研究發現：（一、）融合學生在課堂參與、任務完成和自主學習等方面普遍存在困難；（二、）教師普遍缺乏足夠的專業知識和技能來有效應對融合學生；（三、）學校資源和支援不足，缺乏針對融合學生的適應性課程安排和評核方式；（四、）現行教育政策與實際需求之間存在矛盾，如一至四年級不留級制度可能導致錯過融合學生最佳干預時機。 基於研究結果，本文提出了加強教師專業發展、優化學校資源配置、完善教育政策、強化早期識別和干預機制，以及促進家校合作等建議。這些發現和建議為澳門融合教育的政策制定和實踐改進提供了重要參考。

Ikea’s entry into the China market and how its become successful in the foreign country

As an important part of the global economy, family business have made a lot of contributions to the world economy. With the deepening of China's reform and opening up, the scale and volume of family business have increased dramatically in the national economy. In recent years, more and more family-owned enterprises have entered the list of “Top 500 Chinese Enterprises” and become an important part of the national economy. As a special enterprise organization, family business has certain characteristics. Most of the Chinese family business were founded in the early stage of China's reform and opening up, and now more and more family business are facing the problem that the founders need to leave the family business due to their advanced age. How to ensure the smooth succession of family business and avoid conflicts and contradictions in the process of succession is an important challenge faced by many family business. How to ensure that family business can continue to develop and maintain a high performance status is of great significance to the founders and their successors, as well as to the Chinese economy. Therefore, this research examines how the characteristics of successors affect enterprise performance based on the context of intergenerational succession in family business. This research is based on a multi-case study in which in-depth interviews were conducted with the founders and successors of five cases, which led to the conclusion that five successor characteristics have an impact on enterprise performance. They are inclusiveness, forward thinking, sociable and good communication, sense of social responsibility and sense of family mission. This finding has significant implications for the training of successors and the management of the succession process in Chinese family business. This study is conducive to the discovery of the mechanism of successor characteristics on enterprise performance as well as to make a realistic contribution to the research on the outcomes of family business in China.

<jats:p>Facial expression recognition (FER) is essential for discerning human emotions and is applied extensively in big data analytics, healthcare, security, and user experience enhancement. This study presents a comprehensive evaluation of ten state-of-the-art deep learning models—VGG16, VGG19, ResNet50, ResNet101, DenseNet, GoogLeNet V1, MobileNet V1, EfficientNet V2, ShuffleNet V2, and RepVGG—on the task of facial expression recognition using the FER2013 dataset. Key performance metrics, including test accuracy, training time, and weight file size, were analyzed to assess the learning efficiency, generalization capabilities, and architectural innovations of each model. EfficientNet V2 and ResNet50 emerged as top performers, achieving high accuracy and stable convergence using compound scaling and residual connections, enabling them to capture complex emotional features with minimal overfitting. DenseNet, GoogLeNet V1, and RepVGG also demonstrated strong performance, leveraging dense connectivity, inception modules, and re-parameterization techniques, though they exhibited slower initial convergence. In contrast, lightweight models such as MobileNet V1 and ShuffleNet V2, while excelling in computational efficiency, faced limitations in accuracy, particularly in challenging emotion categories like “fear” and “disgust”. The results highlight the critical trade-offs between computational efficiency and predictive accuracy, emphasizing the importance of selecting appropriate architecture based on application-specific requirements. This research contributes to ongoing advancements in deep learning, particularly in domains such as facial expression recognition, where capturing subtle and complex patterns is essential for high-performance outcomes.</jats:p>

Fish body mucus plays a protective role, especially in Halobatrachus didactylus, which inhabits intertidal zones vulnerable to anthropogenic contaminants. In silico predicted bioactive peptides were identified in its body mucus, namely, EDNSELGQETPTLR (HdKTLR), DPPNPKNL (HdKNL), PAPPPPPP (HdPPP), VYPFPGPLPN (HdVLPN), and PFPGPLPN (HdLPN). These peptides were studied in vitro for bioactivities and aggregation behavior under different ionic strengths and pH values. Size exclusion chromatography revealed significant peptide aggregation at 344 mM and 700 mM ionic strengths at pH 7.0, decreasing at pH 3.0 and pH 5.0. Although none exhibited antimicrobial properties, they inhibited Pseudomonas aeruginosa biofilm formation. Notably, HdVLPN demonstrated potential antioxidant activity (ORAC: 1.560 mu mol TE/mu mol of peptide; ABTS: 1.755 mu mol TE/mu mol of peptide) as well as HdLPN (ORAC: 0.195 mu mol TE/mu mol of peptide; ABTS: 0.128 mu mol TE/mu mol of peptide). Antioxidant activity decreased at pH 5.0 and pH 3.0. Interactions between the peptides and mucus synergistically enhanced antioxidant effects. HdVLPN and HdLPN were non-toxic to Caco-2 and HaCaT cells at 100 mu g of peptide/mL. HdPPP showed potential antihypertensive and antidiabetic effects, with IC50 values of 557 mu g of peptide/mL for ACE inhibition and 1700 mu g of peptide/mL for alpha-glucosidase inhibition. This study highlights the importance of validating peptide bioactivities in vitro, considering their native environment (mucus), and bioprospecting novel bioactive molecules while promoting species conservation.

<jats:p>Causal machine learning is an approach that combines causal inference and machine learning to understand and utilize causal relationships in data. In current research and applications, traditional machine learning and deep learning models always focus on prediction and pattern recognition. In contrast, causal machine learning goes a step further by revealing causal relationships between different variables. We explore a novel concept called Double Machine Learning that embraces causal machine learning in this research. The core goal is to select independent variables from a gesture identification problem that are causally related to final gesture results. This selection allows us to classify and analyze gestures more efficiently, thereby improving models’ performance and interpretability. Compared to commonly used feature selection methods such as Variance Threshold, Select From Model, Principal Component Analysis, Least Absolute Shrinkage and Selection Operator, Artificial Neural Network, and TabNet, Double Machine Learning methods focus more on causal relationships between variables rather than correlations. Our research shows that variables selected using the Double Machine Learning method perform well under different classification models, with final results significantly better than those of traditional methods. This novel Double Machine Learning-based approach offers researchers a valuable perspective for feature selection and model construction. It enhances the model’s ability to uncover causal relationships within complex data. Variables with causal significance can be more informative than those with only correlative significance, thus improving overall prediction performance and reliability.</jats:p>

This study aims to become a conduit of a missing conversation wherein our front line help-givers can express their experiences. Through a series of semi-structured questions, and theoretical analyses, the themes regarding the Experience and Perception of Helping Relationships in Macau. Findings include difficulties and challenges that the helping profession in Macau encounters in different settings related to role ambiguity and public understanding of the profession. Stigma around a person considered to be a “problem” as well as stigma related to nomenclature of mental illnesses. Factors that enable and facilitate a helping relationship were identified. Trust, sincerity, listening and positive regard were mentioned. Due to Macau’s multi-cultural background, an enabling agent to facilitate a helping relationship was identified – language. As a qualitative enquiry medium for reflection and discovery, this study hopes to bring forward the unique experiences of eleven helping professionals with a spectrum of background to provide richness and newness to the current body of literature.

Purpose Research on battery electric vehicles (BEVs) has typically considered environmental concern a key determinant of behavioral intention that leads individuals to prefer electric vehicles. This paper challenges this assumption and argues that technology frameworks may require new variables to capture consumers' preferences. A UTAUT2-based study has been developed to assess the role of environmental concern in the BEVs context and put forward the technology show-off (TS) concept to explain the technology's acceptance. Design/methodology/approach A quantitative and cross-sectional look at behavioral intention is adopted. The study uses structural equation modeling to analyze a sample of 236 Macau residents to determine the relevance of the factors behind the choice to adopt BEVs. Findings The findings indicate that environmental concern and price may be relevant to explain behavioral intention to adopt the BEVs technology. Furthermore, the UTAUT2 framework seems to benefit from adding new variables, with TS playing a pertinent role in explaining technology acceptance. Social implications The findings show that environmental concern fails to build an argument for the shift to full electric mobility and promote the desired behavioral change toward adopting BEVs. Herein lies the necessity to consider new variables that can better describe the characteristics of modern society. Originality/value This paper proposes the TS construct, combining visibility and trialability as significant determinants of behavioral intention to use technology. The study also stresses the need to reconsider the role of environmental concerns' impact on consumer decision-making.

This paper aims to investigate the factors influencing men’s purchase intentions for skincare products, particularly focusing on the evolving attitudes toward masculinity, grooming and self-care. The study seeks to identify dimensions such as self-image, health concerns, masculinity and perceptions regarding skincare, along with the impact of social media use on men’s skincare purchase intentions.,The research uses an online questionnaire to gather data from 178 valid responses. The collected data is analyzed using partial least squares structural equation modeling.,The results reveal that men’s skin health concerns significantly impact their purchase intention for skincare products. Self-image concerns and perceptions regarding skincare also emerge as influential determinants in shaping men’s purchasing decisions. Conversely, health concerns and social media platform use do not directly influence skincare purchase intention. Notably, self-image completely mediates the relationship between men’s social media usage and their intention to purchase skincare products.,The data is based on responses from an online questionnaire, which may introduce biases. In addition, the research focuses on specific personal variables and social media use, potentially overlooking other influential factors.,By recognizing the importance of men’s skin health concerns, self-image and perceptions regarding skincare, cosmetic companies can tailor marketing strategies to effectively target key dimensions to enhance sales of skincare products among men.,In a broader societal context, this research contributes to the ongoing evolution of attitudes. By identifying influential factors in men’s skincare purchase intention, the study sheds light on changing societal norms and perceptions. Acknowledging these shifts can lead to a more inclusive understanding of masculinity and contribute to breaking traditional stereotypes related to men’s grooming practices.,This research contributes to the understanding of men’s skincare purchase intention by exploring dimensions such as self-image, health concerns, masculinity and perceptions regarding skincare, in conjunction with the impact of social media use. The findings provide valuable insights, expanding on previous studies on men’s attitudes toward skincare products. The identification of self-image as a complete mediator is a novel contribution.

While soundscapes shape the structure and function of auditory systems over evolutionary timescales, there is limited information regarding the adaptation of wild fish populations to their natural acoustic environments. This is particularly relevant for freshwater ecosystems, which are extremely diverse and face escalating pressures from human activities and associated noise pollution. The Siamese fighting fish Betta splendens is one of the most important cultured species in the global ornamental fish market and is increasingly recognized as a model organism for genetics and behavioural studies. This air-breathing species (Anabantoidei), characterized by the presence of a suprabranchial labyrinth organ that enhances auditory sensitivity, is native to Southeast Asia and inhabits low flow freshwater ecosystems that are increasingly threatened due to habitat destruction and pollution. We characterized the underwater soundscape, along with various ecological parameters, across five marshland habitats of B. splendens, from lentic waterbodies to small canals near a lake in Chiang Rai province (Thailand). All habitats exhibited common traits of low dissolved oxygen and dense herbaceous vegetation. Soundscapes were relatively quiet with Sound Pressure Level (SPL) around 102-105 dB re 1 mu Pa and most spectral energy below 1,000 Hz. Sound recordings captured diverse biological sounds, including potential fish vocalizations, but primarily insect sounds. Hearing thresholds were determined using auditory evoked potential (AEP) recordings, revealing best hearing range within 100-400 Hz. Males exhibited lower hearing thresholds than females at 400 and 600 Hz. This low-frequency tuning highlights the potential susceptibility of B. splendens to anthropogenic noise activities. This study provides first characterization of the auditory sensitivity and natural soundscape of B. splendens, establishing an important ground for future hearing research in this species. The information provided on the auditory sensory adaptation of B. splendens emphasizes the importance of preserving quiet soundscapes from lentic freshwater ecosystems.

Purpose This research focuses on common misconceptions about the factors driving women to purchase footwear impulsively. Its primary objective is to explore how emotional and social triggers specifically influence women's purchasing decisions, contrasting with the traditionally rational consumer models. Design/methodology/approach An online questionnaire was administered to a sample of women, yielding 199 useable responses. Findings The findings reveal the key determinants of women's impulsive retail footwear purchases, which include self-regulation, hedonic motivations and the influence of the retail store environment. This research challenges the prevailing assumption that women's passion for shopping is driven solely by inherent characteristics and suggests that external factors substantially shape their impulsive buying behaviour. In summary, the stereotypical portrayal of women as compulsive retail footwear shoppers may result more from external stimuli and environmental factors rather than an intrinsic trait. Originality/value This study improves the existing knowledge of women’s impulsive buying behaviour by unveiling the determinants of women's impulsive footwear purchases and assessing whether prevailing stereotypes hold true.

This paper examines the evolving trends in Chinese student mobility to Thailand, highlighting three distinct phases shaped by changes in the higher education: the dominance of Thai language programmes (1990–2010), the rise of business and international programmes (2010–2020), and the increasing preference for graduate studies (2020 onwards). By analysing the economic, cultural, and institutional factors facilitating these shifts, this paper positions Thailand as an emerging alternative study destination for Chinese students. It highlights the significance of this migration within the context of Thailand’s declining fertility rate and labour shortages, focusing on how Thai universities have adapted through active recruitment strategies targeting Chinese students. This paper also addresses the push and pull factors underpinning this migration and the pursuit of alternative educational pathways among Chinese youth. Additionally, it explores the strategic role of Sino-Thai collaborations under the BRI and their broader implications for educational mobility and economic ties.

Purpose The aim of this study is to explore the role and impact of action research in the adoption of circular economy strategies by a fashion retail brand. This exploration is motivated by the need to address the underutilization of action research in management studies, despite its potential to foster a deep understanding of organizational processes and to drive positive transformations. The study seeks to illustrate how action research can contribute to the practical implementation of sustainability initiatives, specifically within the context of new environmental legislation and growing demands for sustainable practices in retailing. Design/methodology/approach This research employs an action research methodology, particularly suited to the retail field, where understanding and influencing organizational processes are key. Through a detailed case study of a fashion retail brand, the study illustrates how action research facilitates the adoption of circular economy strategies. Findings The findings of this study underscore the effectiveness of action research in implementing circular economy strategies within the fashion retail industry. Specifically, it highlights how this approach has led to the successful reduction of waste and reintegration of products into their lifecycle. Originality/value The originality of this study lies in its thorough application of action research to measure and refine the outcomes of circular economy strategies in retailing. This novel approach provides substantial insights into the potential of the circular economy to drive practical innovations in business practices within retail.

—Orthogonal time frequency space (OTFS) modulation, combined with massive multiple-input–multiple-output (MIMO) technology, offers robust performance in high-mobility environments and high-user densities by capturing the full diversity of the wireless channel and effectively utilizing spatial multiplexing. This article introduces an adaptive block sparse backtracking (ABSB) algorithm designed to enhance channel estimation in OTFS with massive MIMO (massive MIMO-OTFS) systems. The proposed ABSB algorithm features dynamic block size adjustment based on the residual signal, improving its adaptability to the varying sparsity structure of the channel. Additionally, the algorithm extends the selection range of related block atoms to increase redundancy, reducing the risk of underfitting. Comprehensive simulation results demonstrate that the ABSB algorithm significantly outperforms traditional pilot-based methods in terms of channel estimation accuracy. It also surpasses the block orthogonal matching pursuit (BOMP) method as well as other classical compressed sensing methods. Specifically, the ABSB algorithm achieves up to a 20% reduction in estimation error compared to some of these traditional methods. The enhanced adaptability and robustness of the ABSB algorithm make it a promising solution for channel estimation in massive MIMO-OTFS systems, paving the way for more reliable and efficient next-generation wireless communications.