Theoretical Analysis Research Articles

Revolutionizing getaways: automation and artificial intelligence’s transformative journey in tourism and hospitality

PurposeThis theme issue aims to explore the depth and breadth of automation and artificial intelligence’s (AI’s) impact on the hospitality and tourism industry.Design/methodology/approachThe thematic examination of the articles presented in this theme issue highlights the central results concerning the strategic inquiry, especially regarding their addition to knowledge, which is vital for fostering idea creation and theoretical research beneficial to various stakeholders in the tourism and hospitality sector. Given the swift evolution of these technologies, grasping their utilization, advantages and obstacles is essential for industry experts, decision-makers and scholars.FindingsThis theme issue encapsulates the transformative impact of automation and AI in the tourism and hospitality industry, highlighting the juxtaposition of enhanced operational efficiency against employment security concerns. It emphasizes the need for ethical governance to address AI’s ethical dilemmas and security vulnerabilities. The exploration of consumer attitudes towards AI, particularly in service robots and facial emotion recognition technologies, is deemed crucial for leveraging AI’s full potential in service delivery. Furthermore, AI’s entry into gastronomy prompts a reevaluation of traditional culinary practices, advocating for a balance between technological innovation and the preservation of cultural heritage.Originality/valueThis theme issue stands out for its focused exploration of the transformative effects of automation and AI within the hospitality and tourism industry. Unlike broader discussions on technology in business, it delves into specific AI-driven innovations, operational changes and the resultant shifts in consumer behavior and industry standards. By curating a collection of empirical research, theoretical analyses and content analyses, this issue is providing important insights into how automation and AI are reshaping service delivery, management practices and strategic decision-making in an industry characterized by its intense customer focus and reliance on human-to-human interaction.

Multiple coherent amplitude modes and exciton-phonon coupling in quasi-one-dimensional excitonic insulator Ta2NiSe5.

An excitonic insulator (EI) is an intriguing correlated electronic phase of condensed excitons. Ta2NiSe5 is a model material for investigating condensed excitonic states. Herein, femtosecond pump-probe spectroscopy is used to study the coherent phonon dynamics and associated exciton-phonon coupling in single-crystal Ta2NiSe5. The reflectivity time series consists of exponential decay due to hot carriers and damped oscillations due to the Ag phonon vibration. Given the in-plane anisotropic thermal conductivity of Ta2NiSe5, coherent phonon oscillations are stronger with perpendicular polarization to its quasi-one-dimensional chains. The 1-, 2-, and 4-THz vibration modes show coherent amplitude responses in the EI phase of Ta2NiSe5 with increasing temperature, totally different from those of normal coherent phonons (the 3- and 3.7-THz modes). The amplitude modes at higher frequencies decouple with the EI order parameter at lower temperatures, as supported by theoretical analysis with a model Hamiltonian of the exciton-phonon coupling system. Our work provides valuable insights into the character of the EI order parameter and its coupling to multiple coherent amplitude modes.

D-Band Engineering in Pd-Based Nanowire Networks for Further Enhancement in Ethanol Electrooxidation Reaction.

The development of highly efficient electrocatalysts for the ethanol oxidation reaction (EOR) is essential for the commercialization of direct ethanol fuel cells, yet challenges remain. In this study, a one-pot solution-phase method to synthesize Pd nanowire networks (NNWs) with very high surface-to-volume ratio having numerous twin and grain boundaries is developed. Using the same method, the Pd lattice is further engineered by introducing Ag and Cu atoms to produce AgPd, and CuPd alloy structure which significantly shifts the Pd d-band center upward and downward, respectively due to strain and ligand effects. Theoretical analysis employing density functional theory (DFT) demonstrates that such modification of the d-band center significantly influences the adsorption energies of reactants on the catalytic surface. Owing to their notably high surface-to-volume ratio and the presence of multiple twin and grain boundaries, Pd NNWs demonstrate significantly enhanced electrocatalytic activity toward EOR, ≈7.2 times greater than that of commercial Pd/C. Remarkably, compared to Pd NNWs, AgPd, and CuPd NNWs display enlarged and reduced electrocatalytic activity toward EOR, respectively. Specifically, Ag4Pd7 NNWs achieve a remarkable mass activity of 9.00Amgpd -1 for EOR, which is 13.6 times higher than commercial Pd/C.

Discovery of a new bimetallic borate with strong optical anisotropy activated by π-conjugated [B2O5] units.

Birefringent materials with high optical anisotropy have been identified as a research hotspot owing to their significant scientific and technological significance in modern optoelectronics for manipulating light polarization. Researchers studying borate systems have discovered that adding π-conjugated units placed in parallel can significantly increase the birefringence of crystalline solids; some examples include [BO3] units, [B2O5] units, and [B3O6] units. However, there are not many borates with strictly parallel configurations of π-conjugated [B2O5] units. In this study, a new bimetallic borate Sr2Cd4(B2O5)3 with near-parallel arrangement of π-conjugated [B2O5] units was discovered. Sr2Cd4(B2O5)3 possesses the maximum number density of [B2O5] units, shortest dihedral angle of [B2O5] units (between the two [BO3]), and largest degree of [CdO6] octahedral distortion among all the currently known Sr-Cd-B-O tetragonal system borates, making it demonstrate a large birefringence of 0.102 at 532 nm. Theoretical analysis proves that π-conjugated [B2O5] anions are the primary source of the large birefringence of Sr2Cd4(B2O5)3.

Mapping for stable bilateral teleoperation of manipulators considering time delays

Teleoperation of manipulators has allowed extending the human skills to several areas, where the commands generated by a human operator on the leader robot are followed by a remote robot. For this purpose, position-position tracking requires a mapping given the mismatch between robot workspaces. This paper compares a pair of functions for mapping the haptic device commands to handle a remote robot, considering non-identical workspaces and a classic P+d control scheme. As part of the theoretical analysis, a Lyapunov-Krasovskii-based stability analysis is developed in steps, allowing us for determining the boundedness of velocities and coordination errors. Subsequently, the performance of the teleoperation system is compared using two mapping functions. To achieve a fair comparison of results, a test protocol is developed, where different levels of haptic device damping, time delays, and workspace scales are used to evaluate the time to complete the task and the average coordination errors. Based on the results, the mapping function influences the calculation of force feedback, stability of the system, and performance metrics. During a pick-and-place task, a reduction in coordination error is observed when the linear function is chosen, while the time to complete the task is lower when a non-linear function is considered.

A Comprehensive Review of Image Line Segment Detection and Description: Taxonomies, Comparisons, and Challenges.

An image line segment is a fundamental low-level visual feature that delineates straight, slender, and uninterrupted portionsof objects and scenarios within images. Detection and description of line segments lay the basis for numerous vision tasks. Althoughmany studies have aimed to detect and describe line segments, a comprehensive review is lacking, obstructing their progress. This studyfills the gap by comprehensively reviewing related studies on detecting and describing two-dimensional image line segments to provideresearchers with an overall picture and deep understanding. Based on their mechanisms, two taxonomies for line segment detectionand description are presented to introduce, analyze, and summarize these studies, facilitating researchers to learn about them quicklyand extensively. The key issues, core ideas, advantages and disadvantages of existing methods, and their potential applications for eachcategory are analyzed and summarized, including previously unknown findings. The challenges in existing methods and correspondinginsights for potentially solving them are also provided to inspire researchers. In addition, some state-of-the-art line segment detectionand description algorithms are evaluated without bias, and the evaluation code will be publicly available. The theoretical analysis, coupledwith the experimental results, can guide researchers in selecting the best method for their intended vision applications. Finally, this studyprovides insights for potentially interesting future research directions to attract more attention from researchers to this field.

The synergy effect of agricultural dual-scale management on farmers' income: evidence from rural China

PurposeThis study aims to estimate the synergy effect of agricultural dual-scale management (ADM) on farmers' total household income, its heterogeneous effects and its mechanisms.Design/methodology/approachThis study constructs a theoretical analysis framework based on the division of labor and synergy theory, empirically assesses the impact of ADM on farmers' income, and further discusses the heterogeneity and mechanisms using the propensity score matching (PSM) and quantile treatment effect (QTE) models. Data is collected from 1,076 households across 4 cities in Liaoning Province of China in 2021.FindingsADM can improve the total household income of farmers, and the impact force is greater than that of the single-scale management mode. ADM is more conducive to improving the income of farmers with low income and low labor endowment. Moreover, ADM can improve agriculture production efficiency, increase net grain production income. Nevertheless, it has no significant effect on farmers' off-farm employment income.Originality/valuePrevious studies have mainly focused on the income effect of land scale management or service scale management. To the best of our knowledge, this study is the first to identify the synergy effect of ADM on farmers' income in China. It provides new insights into the process of agricultural production and management mode transitions in rural China.

Provable Unrestricted Adversarial Training without Compromise with Generalizability.

Adversarial training (AT) is widely considered as the most promising strategy to defend against adversarial attacks and has drawn increasing interest from researchers. However, the existing AT methods still suffer from two challenges. First, they are unable to handle unrestricted adversarial examples (UAEs), which are built from scratch, as opposed to restricted adversarial examples (RAEs), which are created by adding perturbations bound by an lp norm to observed examples. Second, the existing AT methods often achieve adversarial robustness at the expense of standard generalizability (i.e., the accuracy on natural examples) because they make a tradeoff between them. To overcome these challenges, we propose a unique viewpoint that understands UAEs as imperceptibly perturbed unobserved examples. Also, we find that the tradeoff results from the separation of the distributions of adversarial examples and natural examples. Based on these ideas, we propose a novel AT approach called Provable Unrestricted Adversarial Training (PUAT), which can provide a target classifier with comprehensive adversarial robustness against both UAE and RAE, and simultaneously improve its standard generalizability. Particularly, PUAT utilizes partially labeled data to achieve effective UAE generation by accurately capturing the natural data distribution through a novel augmented triple-GAN. At the same time, PUAT extends the traditional AT by introducing the supervised loss of the target classifier into the adversarial loss and achieves the alignment between the UAE distribution, the natural data distribution, and the distribution learned by the classifier, with the collaboration of the augmented triple-GAN. Finally, the solid theoretical analysis and extensive experiments conducted on widely-used benchmarks demonstrate the superiority of PUAT.

The Impact of Realism on U.S. Foreign Policy during the Trump Presidency

Purpose: This article explored the impact of realism on American foreign policy during the Trump administration, striving to answer whether Trump adopted a realist stance or employed a unique blend of realism to enhance American interests on the global stage. Methodology: Centering on theoretical analysis and historical context, this study investigated the alignment of Trump's controversial personality and his "America First" slogan with the quest for national interests and power dynamics. This paper spotlighted Trump's unorthodox implementation of realism by exploring specific global issues, such as security strategies, trade policies, and diplomatic methods. Findings: This paper underscored Trump's deviation from traditional realism and adopting an unconventional realist approach. Particular emphasis was placed on this approach's implications for global power dynamics and the ethical dimensions of U.S. foreign policy. This study pinpointed noteworthy results from Trump's unique fusion of realism, providing insights into its effects on international relations. Unique Contribution to Theory, Practice and Policy: This research contributed to theoretical comprehension and practical implications for future American foreign policy. It illuminated the Trump administration's unorthodox implementation of realism and its ramifications for international cooperation. Moreover, this paper advocated for a balanced approach incorporating strategic pragmatism with ethical leadership to efficiently tackle intricate global challenges and uphold the United States' role in the international arena.

Failure analysis of the suspender fracture in a railway self-anchored suspension bridge: Damage identification, fatigue mechanism and remaining life prediction

A suspender fracture accident was reported in a railway self-anchored suspension bridge, arousing intensive concern to fatigue issue in the suspender end connector area which is exposed to complex stress states and cyclic traffic loads. Some critical issues involving the fatigue mechanism, the damage identification, and the remaining life prediction were investigated on the basis of on-site and lab tests, numerical simulations, and theoretical analyses. It was found that the root of an ear-plate screw with threads becomes the fatigue-prone detail since action of stress concentration and the unexpected cyclic bending. Also, an effective crack identification scheme by the ultrasonic phased array inspection as well as a verified prediction method for remaining life were proposed. Short suspenders in the main span are significantly affected by the cyclic bending, resulting in the extremely lower fatigue life than that of a long or side-span suspender. Suggestions for a classified disposal plan are provided based on fatigue risk for individual suspender.

New discrete-time zeroing neural network for solving time-dependent linear equation with boundary constraint

Recently, continuous- and discrete-time models of a zeroing neural network (ZNN) have been developed to provide online solutions for the time-dependent linear equation (TDLE) with boundary constraint. This paper presents a novel approach to address the bound-constrained TDLE (BCTDLE) problem by proposing a new discrete-time ZNN (DTZNN) model. The proposed DTZNN model is designed using the Taylor difference formula to discretize the previous continuous-time ZNNN (CTZNN) model. Theoretical analysis indicates the computational property of the proposed DTZNN model, and numerical results further demonstrate its validity. The applicability of the proposed DTZNN model is finally confirmed via its application to the motion planning of a PUMA560 robotic arm.

Social Responsibility and Financial Performance in The Covid-19 era: Support for the Experience of Moroccan SMB

Objective: The objective seems to be to explore the importance of the concept of Corporate Social Responsibility (CSR) as a means of crisis management and performance lever allowing companies to withstand current financial and economic shocks. Theoretical Framework: The text mentions the intention to provide a historical overview of CSR, define CSR, financial performance, SMB, the role of SMB on economic growth, and cite organizational theories related to the importance of CSR in times of crisis. This section constitutes the theoretical framework by linking CSR to different economic concepts and organizational theories. Method: this article suggests a theoretical and descriptive approach, analyzing the economic impact of health measures and proposing recommendations, which involves documentary and theoretical analysis. Results and Discussion: The text focuses on presenting the topic and theoretical framework without providing specific results or data analyses. Research Implications: e research aims to highlight the importance of CSR for crisis management and financial performance of companies, particularly in the context of the COVID-19 crisis. The implications could concern strategies business, public policy, and managerial theory. Originality/Value: The originality of this research could lie in its analysis of the impact of CSR during the COVID-19 crisis, a relatively new and current topic. The combination of crisis management, financial performance and health measures from the perspective of CSR can constitute an original contribution to the existing literature on the subject.

A Survey of Flow Field and Combustion Characteristics under Subatmospheric Pressure

This paper presents a summary of and introduction to research on high-altitude and subatmospheric combustion concerning turbine and scramjet engines. The investigation includes theoretical analysis, experimental studies, and numerical simulations. The analysis encompasses the flow field structure, fuel atomization, and combustion performance. Subsequently, recent research on the combustion performance of liquid fuels, solid fuels, and gaseous fuels under high-altitude and low-pressure plateau environments is reviewed. This includes an evaluation of flame height, flame temperature, combustion rate, fire spread rate, and heat radiation flux. Additionally, combustion performance prediction models for high-altitude environments based on experimental and theoretical analysis have been introduced. Lastly, issues in subatmospheric combustion in the aerospace and plateau fire fields are presented based on the current research.

Electromagnetically-induced transparency assists the Raman gradient echo memory at moderate detuning, dependent on gradient order

Abstract Optical quantum memories are essential for quantum communications and photonic quantum technologies. Ensemble optical memories based on 3-level interactions are a popular basis for implementing these memories. All such memories, however, suffer from loss due to scattering. In off-resonant 3-level interactions, such as the Raman gradient echo memory (GEM), scattering loss can be reduced by a large detuning from the intermediate state. In this work, we show how electromagnetically induced transparency adjacent to the Raman absorption line plays a crucial role in reducing scattering loss, so that maximum efficiency is in fact achieved at a moderate detuning. Furthermore, the effectiveness of the transparency, and therefore the efficiency of GEM, depends on the order in which gradients are applied to store and recall the light. We provide a theoretical analysis and show experimentally how the efficiency depends on gradient order and detuning.

BPA: A Novel Blockchain-Based Privacy-Preserving Authentication Scheme for the Internet of Vehicles

The Internet of Vehicles (IoV) connects an isolated individual on the road to share information, which can improve traffic efficiency. However, the promotion of information sharing brings the critical security issues of identity authentication, followed by privacy protection issues in the authentication process in the IoV. In this study, we designed a blockchain-based conditional privacy-preserving authentication scheme for the IoV (BPA). Our scheme implements zero-knowledge proof (ZKP) to verify the identities of vehicles, which moves the authentication process down to the Roadside Units (RSUs) and achieves decentralized authentication at the edge nodes. Moreover, blockchain technology is utilized to synchronize a consistent ledger across all RSUs for recording and disseminating vehicle authentication states, which enhances the overall authentication process efficiency. We provide a theoretical analysis asserting that the BPA ensures enhanced security and effectively protects the privacy of all participating vehicles. Experimental evaluations confirm that our scheme outperforms existing solutions in terms of the computational and communication overhead.

Fluid entrapment during forced imbibition in a multidepth microfluidic chip with complex porous geometry

Understanding and controlling fluid entrapment during forced imbibition in porous media is crucial for many natural and industrial applications. However, the microscale physics and macroscopic consequences of fluid entrapment in these geometric-confined porous media remain poorly understood. Here, we introduce a novel multidepth microfluidic chip, which can mitigate the depth confinement of traditional two-dimensional (2-D) microfluidic chips and mimic the wide pore size distribution as natural-occurring three-dimensional (3-D) porous media. Based on microfluidic experiments and direct numerical simulations, we observe the fluid-entrapment scenarios and elucidate the underlying complex interaction between geometric confinement, capillary number and wettability. Increasing depth variation can promote fluid entrapment, whereas increasing capillary number and contact angle yield the opposite effect, which seemingly contradicts conventional expectations in traditional 2-D microfluidic chips. The fluid-entrapment scenario in depth-variable microfluidic chips stems from microscopic interfacial phenomena, classified as snap-off and bypass events. We provide theoretical analyses of these pore-scale events and validate corresponding phase diagrams numerically. It is shown that increasing depth variation triggers snap-off and bypass events. Conversely, a higher capillary number suppresses snap-off events under strong imbibition, and an increased contact angle inhibits bypass events under imbibition. These macroscopic imbibition patterns in microfluidic porous media can be linked with these pore-scale events by improved dynamic pore-network models. Our findings bridge the understanding of forced imbibition between 2-D and 3-D porous media and provide design principles for newly engineered porous media with respect to their desired imbibition behaviours.

Numerical and theoretical analysis of multi-pillar instability under elastic beams

With the increase of mining scale and depth, the cascading pillar failure (CPF) disaster has gradually become one of the core technical challenges for safe mining. This paper studies the CPF disaster of multi-pillar (P1-2, P2-3, P3-4 and P4-5) at 848 m level of Alhada Lead-Zinc Mine based on the RFPA2D numerical simulation software and stiffness theory. The numerical simulation results indicate that the load transfer effect induces the domino instabilities of double pillar (P2-3 and P3-4) and double pillar (P1-2 and P4-5), which is characterized by the ‘2 + 2’ compound failure mode. The physical essence of load transfer effect is revealed through numerical simulation, which is the elastic rebound of surrounding rockmass (such as roof-floor). In addition, the theoretical model of rebound overload mechanism of roof-multi-pillar-floor system is established based on the catastrophe theory, and the instability criterion, sudden jump and energy release of roof-multi-pillar-floor system are derived. Finally, the main influencing factors of load transfer effect such as pillar spacing and damage fracture zone are quantitatively analyzed, and the load transfer law shows that the load transfer effect decreases with the increasing pillar spacing and is hindered by the structural plane in the surrounding rockmass.

Influence of High-Frequency Operation on the Efficiency of a PMSM Drive with SiC-MOSFET Inverter

This paper investigates the effects of high-frequency switching and a high fundamental frequency on the parameters and efficiency of a high-speed permanent magnet synchronous machine (PMSM) drive. We discuss the design and modeling of the PMSM, taking into account these high-frequency effects. The impact of high frequencies is analyzed across three different inverters (IGBT, Fast IGBT, and SiC-MOSFET) and the motor, and we employ theoretical analysis, computer simulations, and experimental tests for validation. Our goal is to enhance our understanding of how these high-frequency factors affect the performance of the motor drive.

Black Men Writing, Reflecting, and Discovering Self: Personal Narrative Essays of College-aged African American Men at an All-male Historically Black College or University (HBCU)

<p>Personal narratives are studied in many disciplines, but theoretical analysis of the personal narrative in composition classes has lagged behind the research. This qualitative study examines the personal narratives of thirty Black college-aged men. This study presents the feelings and thoughts of Black males through their personal stories and perspectives; in the study, they detail their life experiences. The narratives were analyzed for elements of narrative discourse, which include (1) Thesis; (2) Transitions; (3) Use and Evaluation of Sources; (4) Audience, Tone, and Rhetorical Appeals; (5) Organization; (6) Claims, Warrants, and Support; (7)Paraphrases, Direct Quotes, and Summary; (8) In-text Citations and Works Cited Page; (9) Style and Syntax; and (10) Mechanics (see scoring procedures). Each narrative was analyzed according to the criteria described in the Personal Narrative Rubric; the number of elements was counted for each category. The researcher recommends additional narrative studies of Black men in different age groups, educational backgrounds, social and economic levels, and geographical regions.</p>

A linearly polarized light emission with a composite nanowire grating in whole white band

To obtain a highly linearly polarized light, a composite model consisting of white light emission, anti-reflection film, and metal-dielectric-metal nanowire grating was designed, analyzed, optimized, and fabricated. Based on the finite-difference time-domain method, the impacts of material, period, height, and incidence angle on the polarization performance of the composite model were discussed. The metal-dielectric-metal nanowire grating was fabricated on blue chip and fluorescent ceramics using nanoimprint technology. The employed materials of metal-dielectric-metal nanowire grating were aluminum and PMMA, with the period of 200 nm, wire width of 100 nm, and the height of metal and dielectric were 100 nm and 120 nm. Additionally, the anti-reflection film consisting of PMMA with the thickness of 45 nm was incorporated on fluorescent ceramics to enhance energy efficiency. Finally, through a series of test experiments, the composite model can be realized by the extinction ratio of 40 dB, while the transmittance of TM mode exceeds 50% at 450–750 nm. The theoretical analysis of this study is verified by experiments, and it has significant potential in the pursuit of high brightness, ultra-thin micro displays.