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The cosmological constant is normally introduced as an additional term entering the Einstein–Hilbert (EH) action. In this letter, we demonstrate that, instead, it appears naturally from the standard EH action as an invariant term emerging from spacetime symmetries. We then demonstrate that the same constraint emerging from this invariant suppresses the short wavelength modes and it favors the long wavelength ones. In this way, inside the proposed formulation, the observed value for the vacuum energy density is obtained naturally from the zero-point quantum fluctuations.

The mutual information method has demonstrated to be very useful for deriving the potential order parameter of a system. Although the method suggests some constraints which help to define this quantity, there is still some freedom in the definition. The method then results inefficient for cases where we have order parameters with a large number of constants in the expansion, which happens when we have many degenerate vacuums. Here, we introduce some additional constraints based on the existence of broken symmetries, which help us to reduce the arbitrariness in the definitions of the order parameter in the proposed mutual information method.

Theories and models try to describe the complexity of how people embrace and make use of innovations. The determinants of behavior concerning battery electric vehicles (BEVs) have traditionally revolved around factors such as vehicles’ price and range. Surprisingly, despite being small and one of the wealthiest territories in the world, Macau SAR faces challenges in BEV market penetration, underscoring the need to explore alternative causes of behavioral intention. To explain the adoption of technologies, this paper focuses on technology show-off (TS), which combines Rogers’ (2003) concepts of visibility and trialability of technology in a single construct as a determinant of behavioral intention. Therefore, when individuals perceive technology as more visible and available for trial, their behavioral intention to adopt it strengthens. Using structural equation modeling for quantitative analysis, this study examines the significance of TS in terms of the intention to adopt battery electric vehicles. The findings highlight the salience of the technology show-off construct in explaining behavioral intention, underscoring its significance in the context of modern society’s characteristics. This study contributes to advances in understanding technology acceptance and highlights the importance of incorporating experiential aspects (such as TS) into the traditional technology acceptance models.

This article reports a case study of older adults learning English in China. It indicates how, founded on consequentialist ethics, risk analysis, and safeguarding, it was decided to use covert research, drawing on the confluence of risk analysis, risk evaluation, risk management, safeguarding, research ethics, and important contextual and cultural features. Ethical principles of nonmaleficence, beneficence, safeguarding, and protection were addressed, and account was taken of the strength, likelihood, and consequences of risks, safeguards, and benefits, informed by Chinese cultural contexts, values, behaviors, and features of teaching and learning based on andragogy and geragogy. Implications are drawn for teaching and learning with older adults, advocating significant account to be taken of contextual factors.

Remote Learning's Impact on Students' Cognitive Development: Evidence from Time Series Assessment [Conference presentation]

After the Covid-19 Pandemic crisis in international economic relations it became evident that climate-smart aspects should be considered when re-establishing a new international trade order. International organizations have proclaimed that this momentum should be used to include climate-smart trade and investment provisions to enable sustainable development. It has been acknowledged that trade has an important role to play in the global response to climate change, providing economies with tools to draw on in their efforts to mitigate climate change and to adapt to its consequences. In this paper we focus the analysis on investigating the digital and sustainable component of trade facilitation measures applied in Western Balkans countries. To evaluate the importance of trade facilitation measures and their digital and sustainable components we apply standard gravity model with the data from UN Global Survey on digital and sustainable trade facilitation. The results show that trade facilitation measures are important for improving and increasing trade among the Western Balkans countries. Especially, measures connected to improving transparency procedures in trade and measures for alleviating trade formalities are most significant for increasing bilateral trade among Western Balkans countries. With a lower level of importance are the measures for improving cross-border paperless trade between these countries.

We demonstrate that black hole evaporation can be modeled as a process where one symmetry of the system is spontaneously broken continuously. We then identify three free parameters of the system. The sign of one of the free parameters governs whether the particles emitted by the black hole are fermions or bosons. The present model explains why the black hole evaporation process is so universal. Interestingly, this universality emerges naturally inside certain modifications of gravity.

Intended as an economic and development hub, the Hengqin Cooperation Zone aims to foster collaboration and integration between mainland China, Hong Kong, and Macao, serving as a platform for economic development and innovation among the three regions. The zone's development has increased demand for financial services, often offered through fintech. There is, however, a lack of interoperability between the fintech services currently used in Macao and Hengqin. This may hinder Macao users' adoption of the technology. Thus, our research objective is to identify the factors determining Macao residents' adoption of fintech services in the area and provide insights for service providers, developers, and policymakers. A framework based on the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) was used for this purpose. The responses of 103 Macao residents provided evidence that ease of use significantly and positively impacts the usefulness of the technology. This in turn influences attitudes towards fintech usage. Subjective norms and perceived behavioral control positively impact fintech adoption intentions. The fintech industry and the governments of Macao and Hengqin can work on improving technology's ease of use and usefulness. They can also promote them to Macao users, and provide the resources required for better access to fintech in the zone

Under Macau Arbitration Law (MAL, art 64.1), an award shall be made in writing and shall be signed by the arbitrator or arbitrators. Furthermore, the law provides that in case of arbitral proceedings with more than one arbitrator, the signatures of the majority of all members of the arbitral tribunal shall suffice, provided that the reason for any omitted signature is stated (MAL, art 64.2).

Integrating financial technologies with green initiatives is critical to the sustainable development agenda. This is particularly true for newly developed smart cities like Tongzhou, the sub-city center of Beijing. To assess the adoption of green fintech in Tongzhou, this paper extends the EnergyAugmented Technology Acceptance Model (EA-TAM) to incorporate two green factors – environmental awareness and green knowledge. This paper applies structural equation modeling techniques to analyze data from 403 respondents who live, work, or study in Tongzhou and finds allhypothesized constructs significant. Since green knowledge is significant to the adoption of green fintech, this paper further divides the sample into a high-education group (162 respondents with university-or-above degrees) and a low-education group (251 respondents with post-secondary-orlower degrees) to evaluate the impact of education. All the hypothesized factors are significant to the high-education group,but environmental awareness and perceived usefulness are insignificant to the low- education group. Hence, the results provide evidence that people in the newly developed smart city adopt green fintech due to their environmental sensitivity. The adoption of green fintech is more environmentally sensitive for people with high education levels.

Battery electric vehicles (BEVs) are living up to their claims as consumers choose them more frequently. The increasing demand for sustainable vehicles translates into the global need for specific components, materials, and infrastructures and drives the regulatory frameworks in each country. While BEVs offer environmental benefits and global business opportunities, the technology has not yet gained mainstream acceptance. Thus, this work aims to investigate the characteristics of BEV users and their role in the diffusion of products to larger segments, as this may vary from country to country. For this purpose, a survey based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) (Venkatesh et al., 2012) framework and structural equation modeling (SmartPLS) was adopted. The results indicated that, except for the constructs of effort expectancy (EE) and social influence (SI), the predictors in the model performed well in this context. Current users are satisfied with their vehicles and are supportive of BEVs in the future. The analysis also revealed that in addition to the availability of financial resources, early adopters are attracted by new technologies in a way that leads them to make decisions outside of the traditional influence of the other members of society. It is suggested to leverage the perceived benefits of status, differentiation, or uniqueness motives, to appeal to those seeking to appear trendy and tech-savvy in society. Companies and policymakers should acknowledge the peculiarities of early customers in their communication strategies to reach a wider audience around the globe and encourage the adoption of BEV technology.

Objective: This study highlights the potential of an Electrocardiogram (ECG) as a powerful tool for early diagnosis of COVID-19 in critically ill patients with limited access to CT–Scan rooms. Methods: In this investigation, 3 categories of patient status were considered: Low, Moderate, and Severe. For each patient, 2 different body positions have been used to collect 2 ECG signals. Then, from each collected signal, 10 non-linear features (Energy, Approximate Entropy, Logarithmic Entropy, Shannon Entropy, Hurst Exponent, Lyapunov Exponent, Higuchi Fractal Dimension, Katz Fractal Dimension, Correlation Dimension and Detrended Fluctuation Analysis) were extracted every 1s ECG time-series length to serve as entries for 19 Machine learning classifiers within a leave-one-out cross-validation procedure. Four different classification scenarios were tested: Low vs. Moderate, Low vs. Severe, Moderate vs. Severe and one Multi-class comparison (All vs. All). Results: The classification report results were: (1) Low vs. Moderate - 100% of Accuracy and 100% of F1–Score; (2) Low vs. Severe - Accuracy of 91.67% and an F1–Score of 94.92%; (3) Moderate vs. Severe - Accuracy of 94.12% and an F1–Score of 96.43%; and (4) All vs All - 78.57% of Accuracy and 84.75% of F1–Score. Conclusion: The results indicate that the applied methodology could be considered a good tool for distinguishing COVID-19’s different severity stages using ECG signals. Significance: The findings highlight the potential of ECG as a fast and effective tool for COVID-19 examination. In comparison to previous studies using the same database, this study shows a 7.57% improvement in diagnostic accuracy for the All vs All comparison.

Critical thinking (CT), as a form of higher-order thinking, is intended to help individuals form reasonable reflection and judgment to deal with increasingly severe employment situations. As the primary workforce in the labor market, undergraduates must possess a strong critical thinking disposition (CTD) to make better use of CT. Despite extensive research on components of CTD from the perspective of educational practices, there is limited emphasis on investigating the components and their relationships of CTD in the labor market and the impact of gender differences. Therefore, this study presented an analysis of 1535 Chinese undergraduates (Mage = 20.89; SD = 1.43) using the Employer-Employee-Supported Critical Thinking Disposition Inventory (2ES-CTDI), aiming to explore the CTD that undergraduates should possess before entering the labor market. The relationships among the components were examined using SmartPLS4.0 in conjunction with Partial Least Squares Structural Equation Modeling (PLS-SEM). Additionally, a multigroup analysis (PLS-MGA) with a measurement invariance (MI) test was conducted to validate the moderating effects of gender. The findings indicate that (a) self-efficacy has a significant negative effect on habitual truth-digging, and boys are more affected than girls, instant judgment plays a competitive partial mediating role in this relationship; (b) self-efficacy has a significant positive effect on instant judgment, and boys are more likely to make instant judgments than girls; (c) instant judgment significantly positively affects habitual truth-digging. These findings highlight the dynamic equilibrium among the internal components of CTD in the labor market and call for increased attention from educators to the importance of gender differences in the cultivation process.

The Revenue Management (RM) problem in airlines for a fixed capacity, single resource and two classes has been solved before by using a standard formalism. In this paper we propose a model for RM by using the semi-classical approach of the Quantum Harmonic Oscillator. We then extend the model to include external factors affecting the people’s decisions, particularly those where collective decisions emerge.

The emergence of blockchain technology in 2008 marked a significant milestone in the evolution of digital currencies, paving the way for the emergence of cryptocurrencies such as Bitcoin. Since then, blockchain has undergone four generations of development, expanding its applications across various sectors. In particular, the integration of blockchain into accounting and auditing practices has garnered significant attention due to its potential to transform traditional methods. However, there's a lack of clear understanding of how blockchain impacts traditional auditing practices and finance recordkeeping and the implications for audit quality. Significant challenges and uncertainties hinder its widespread adoption, including technical hurdles, regulatory complexities, and practical barriers. This dissertation aims to determine the transformative impact of blockchain technology on auditing practices and finance recordkeeping. In order to fully understand the impact of blockchain on auditing practices and finance recordkeeping, the dissertation utilizes a mixed sequential research approach that is divided into three phases. The first approach involves gathering qualitative data through interviews with blockchain experts. The second approach involves collecting secondary qualitative data through a systematic literature review to determine the changes that blockchain has brought to traditional auditing practices and finance recordkeeping. This is followed by a bibliometric analysis to identify current trends in blockchain research related to auditing practices and finance recordkeeping. The third approach involves gathering data through an online-focused survey distributed to finance and other industry professionals to determine the challenges organizations face in implementing blockchain technology in auditing practices and finance recordkeeping. Additionally, in phase three, case studies will be conducted based on the survey responses to examine the hindrances and challenges faced by organizations in implementing blockchain and its impact on auditing practices in different regions and among different demographic groups. As the findings indicate, Integrating blockchain technology into accounting and auditing practices can bring about significant improvements in transparency, efficiency, and fraud prevention. However, there are several challenges that must be overcome for successful implementation, such as technical difficulties, regulatory uncertainties, and privacy concerns. To overcome these hurdles, it is necessary to establish clear regulatory frameworks and innovative solutions. Although smart contracts offer automation, they also pose security risks that need to be addressed. Despite these challenges, blockchain has the potential to revolutionize auditing by enabling real-time auditing and enhancing integrity verification. To ensure audit quality, auditors must adapt to new responsibilities and stay up-to-date with emerging trends. Collaboration among stakeholders and continuous education and training programs are key to driving the successful adoption of blockchain technology

In the 21st century, complex problem-solving (CPS) serves as a key indicator of educational achievement. However, the elements of successful CPS have not yet been fully explored. This study investigates the role of strategic exploration and different problem-solving and test-taking behaviors in CPS success, using logfile data to visualize and quantify students’ problemsolving behavior on 10 CPS problems with different characteristics and levels of difficulty. Additionally, in the present study, we go beyond the limits of most studies that focus on students’ problem-solving behavior pattern analyses in European cultures and education systems to examine Arabic students’ CPS behavior. The results show that computer-based assessments of CPS are feasible and valid in Jordanian higher education. The findings also confirm the structural validity of CPS, indicating that the processes of knowledge acquisition (KAC) and knowledge application (KAP) can be distinguished and separated in the problem-solving process. Large differences were identified in students’ test-taking behavior in terms of the efficacy of their exploration strategy. We identified four latent classes based on the students’ exploration strategy behavior. The study thus leads to a better understanding of how students solve problems and behave during the problem-solving process in uncertain situations.

To evaluate 3M's intrinsic value and compare the calculated results with the stock market price as of 31 December 2022. To study 3M's future operating strategies and the internal and external factors that may impact the Company's operations