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The present study aims to address the flow and heat transfer of MgO-MWCNTs/EG hybrid nanofluid in a complex shape enclosure filled with a porous medium. The enclosure is subject to a uniform inclined magnetic field and radiation effects. The effect of the presence of a variable magnetic field on the natural convection heat transfer of hybrid nanofluids in a complex shape cavity is studied for the first time. The geometry of the cavity is an annular space with an isothermal wavy outer cold wall. Two types of the porous medium, glass ball and aluminum metal foam, are adopted for the porous space. The governing equations for mass, momentum and heat transfer of the hybrid nanofluid are introduced and transformed into non-dimensional form. The actual available thermal conductivity and dynamic viscosity data for the hybrid nanofluid are directly used for thermophysical properties of the hybrid nanofluid.

The governing equations for mass, momentum and heat transfer of hybrid nanofluid are introduced and transformed into non-dimensional form. The thermal conductivity and dynamic viscosity of the nanofluid are directly used from the experimental results available in the literature. The finite element method is used to solve the governing equations. Grid check procedure and validations were performed.

The effect of Hartmann number, Rayleigh number, Darcy number, the shape of the cavity and the type of porous medium on the thermal performance of the cavity are studied. The outcomes show that using the composite nanoparticles boosts the convective heat transfer. However, the rise of the volume fraction of nanoparticles would reduce the overall enhancement. Considering a convective dominant regime of natural convection flow with Rayleigh number of 107, the maximum enhancement ratio (Nusselt number ratio compared to the pure fluid) for the case of glass ball is about 1.17 and for the case of aluminum metal foam is about 1.15 when the volume fraction of hybrid nanoparticles is minimum as 0.2 per cent.

The effect of the presence of a variable magnetic field on the natural convection heat transfer of a new type of hybrid nanofluids, MgO-MWCNTs/EG, in a complex shape cavity is studied for the first time. The results of this paper are new and original with many practical applications of hybrid nanofluids in the modern industry.

The purpose of the present paper is to model a cavity, which is equally divided vertically by a thin, flexible membrane. The membranes are inevitable components of many engineering devices such as distillation systems and fuel cells. In the present study, a cavity which is equally divided vertically by a thin, flexible membrane is model using the fluid–structure interaction (FSI) associated with a moving grid approach.

The cavity is differentially heated by a sinusoidal time-varying temperature on the left vertical wall, while the right vertical wall is cooled isothermally. There is no thermal diffusion from the upper and lower boundaries. The finite-element Galerkin technique with the aid of an arbitrary Lagrangian–Eulerian procedure is followed in the numerical procedure. The governing equations are transformed into non-dimensional forms to generalize the solution.

The effects of four pertinent parameters are investigated, i.e., Rayleigh number (104 = Ra = 107), elasticity modulus (5 × 1012 = E_T = 1016), Prandtl number (0.7 = Pr = 200) and temperature oscillation frequency (2p = f = 240p). The outcomes show that the temperature frequency does not induce a notable effect on the mean values of the Nusselt number and the deformation of the flexible membrane. The convective heat transfer and the stretching of the thin, flexible membrane become higher with a fluid of a higher Prandtl number or with a partition of a lower elasticity modulus.

The authors believe that the modeling of natural convection and heat transfer in a cavity with the deformable membrane and oscillating wall heating is a new subject and the results have not been published elsewhere.

This study aims to study the thermal identification issue by harvesting both solar energy and atmospheric thermal updraft for a solar-powered unmanned aerial vehicle (SUAV) and its electric energy performance under continuous soaring conditions.

The authors develop a specific dynamic model for SUAVs in both soaring and cruise modes. The support vector machine regression (SVMR) is adopted to estimate the thermal position, and it is combined with feedback control to implement the SUAV soaring in the updraft. Then, the optimal path model is built based on the graph theory considering the existence of several thermals distributed in the environment. The procedure is proposed to estimate the electricity cost of SUAV during flight as well as soaring, and making use of dynamic programming to maximize electric energy.

The simulation results present the integrated control method could allow SUAV to soar with the updraft. In addition, the proposed approach allows the SUAV to fly to the destination using distributed thermals while reducing the electric energy use.

Two simplified dynamic models are constructed for simulation considering there are different flight mode. Besides, the data-driven-based SVMR method is proposed to support SUAV soaring. Furthermore, instead of using length, the energy cost coefficient in optimization problem is set as electric power, which is more suitable for SUAV because its advantage is to transfer the three-dimensional path planning problem into the two-dimensional.

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

This paper aims to review research on mental health and well-being (MHW) in tourism, which the United Nations addresses in Sustainable Development Goal No. 3 (SDG 3). The authors also pinpoint future directions regarding how tourism can contribute to this goal from theoretical and practical standpoints.

The authors review the literature on MHW in tourism from the perspectives of tourists, residents and tourism workers.

Researchers have predominantly analysed tourists’ MHW outcomes through the lenses of positive psychology and tourism therapy; only a small number of studies have focused on MHW-related benefits and challenges in terms of tourism development for residents and tourism workers. Investigations of MHW in tourism require interdisciplinary approaches to reveal how tourism promotes diverse stakeholders’ mental health. Practically, there is an urgent need to incorporate tourism products and services into mental health care, and design tourism experience with positive psychology principles.

This study offers insights into fostering MHW through tourism. It specifically proposes theoretical and practical ways in which tourism might enhance MHW for various industry stakeholders, contributing to SDG 3.

本文基于联合国可持续发展目标中的第三个目标（SDG 3）, 对旅游中的心理健康和幸福感研究进行了回顾, 并就旅游如何助推这一目标的实现指明了未来的研究和实践方向。

本文从游客、居民和旅游从业者的角度对与旅游中的心理健康和幸福感相关的文献进行了回顾和评估。

当前研究主要从积极心理学和旅游疗法的视角分析了游客的心理健康和幸福感, 有关旅游业发展对居民和旅游从业者心理健康和幸福感的积极影响及挑战的研究尚不多见。因此, 需采用跨学科进路来揭示旅游业对不同利益相关者心理健康的促进作用。在实践方面, 亟需将旅游产品和服务纳入到心理健康护理体系中, 并依据积极心理学原理来开展旅游体验设计。

本文为通过旅游发展来促进心理健康与幸福感这一主题提供了见解。本文为旅游业如何提高各利益相关者的心理健康与幸福感提供了理论方面和实践方面的进路, 从而助推联合国可持续发展目标中第三个目标的实现。

Este artículo revisa los estudios y las investigaciones sobre la salud mental y el bienestar en el turismo (MHW por sus siglas en inglés, basándose en el Objetivo de Desarrollo Sostenible 3 (ODS 3) de las Naciones Unidas, y explora las futuras direcciones de investigación y práctica en el impulso del logro de este objetivo a través del turismo.

Se revisa la literatura relevante sobre la salud mental y el bienestar en el turismo desde la perspectiva de los turistas, residentes y trabajadores del sector turístico.

Actualmente, las investigaciones se centran principalmente en el análisis de la salud mental y el bienestar de los turistas desde la perspectiva de la psicología positiva y la terapia de turismo. Sin embargo, hay una falta de investigación sobre el impacto positivo y los desafíos del desarrollo turístico en la salud mental y el bienestar de los residentes y trabajadores del turismo. Por lo tanto, se requiere un enfoque interdisciplinario para revelar el papel del turismo en la promoción de la salud mental para diferentes partes interesadas. En cuanto a la práctica, se debe explorar activamente la integración de productos y servicios turísticos en el cuidado de la salud mental y diseñar actividades turísticas basadas en los principios de la psicología positiva.

Este estudio ofrece perspectivas sobre el papel del turismo en la promoción de la salud mental y el bienestar. Al proponer rutas teóricas y prácticas para mejorar la salud mental y el bienestar de las partes interesadas en el turismo, este artículo tiene como objetivo contribuir al logro del Objetivo de Desarrollo Sostenible 3 (ODS 3) de las Naciones Unidas.

The purpose of this study was to provide a new characterization of the extent to which learners complete learning activities in massive open online courses (MOOCs), a central challenge in these contexts. Prior explorations of learner interactions with MOOC materials have often described these interactions through stereotypes, which accounts for neither the full spectrum of potential learner activities nor the ways those patterns differ across course designs.

To overcome these shortcomings, the authors apply confirmatory and exploratory factor analysis to learner activities within three MOOCs to test different models of participation across courses and populations found within those courses.

Courses varied in the extent to which participation was driven by learning activities vs time/topic or a mixture of both, but this was stable across offerings of the same course.

The results call for a reconceptualization of how different learning activities within a MOOC are designed to work together, to better allow strong learning outcomes even within one activity form or more strongly encourage participation across activities.

The authors validate new continuous-patterns rather than a discrete-pattern participation model for MOOC learning.

The present contribution is in the field of quantum modelling of macroscopic phenomena. The focus is on one enigmatic aspect of quantum physics, namely, the Einstein–Podolsky–Rosen paradox and entanglement. After a review of the state-of-the-art concerning macroscopic quantum effects and quantum interaction, this paper aims to propose a link between embryology and acupuncture in the framework of macroscopic intricate states induced by quantum mechanics.

The author uses the fractaquantum hypothesis which supposes that the quantum framework is applicable to all insecable elements in nature, whatever their size.

This contribution considers an open question related to a possible link between acupuncture and embryology: can a weak form of intrication be maintained during stem cell division to interpret the acupuncture meridians as an explicit manifestation of a macroscopic intricate system? The macroscopic structure suggested by quantum mechanics could be a beginning of explanation of acupuncture through the embryologic development.

A fundamental hypothesis is the fact that during cell division, cells keep some weak intrication.

This contribution suggests a structure of the acupuncture meridians. The links between the acupuncture points have to be searched in the embryologic development of the individual through a weak remaing intrication of some of his cells and not in present explicit relations.

A new link between occidental and oriental cultures is explored.

This contribution suggests conceptual links between acupuncture, embryology and macroscopic intricate states.

The purpose of this paper is to solve the problem that the standard particle swarm optimization (PSO) algorithm has a low success rate when applied to the optimization of multi-dimensional and multi-extreme value functions, the authors would introduce the extended memory factor to the PSO algorithm. Furthermore, the paper aims to improve the convergence rate and precision of basic artificial fish swarm algorithm (FSA), a novel FSA optimized by PSO algorithm with extended memory (PSOEM-FSA) is proposed.

In PSOEM-FSA, the extended memory for PSO is introduced to store each particle’ historical information comprising of recent places, personal best positions and global best positions, and a parameter called extended memory effective factor is employed to describe the importance of extended memory. Then, stability region of its deterministic version in a dynamic environment is analyzed by means of the classic discrete control theory. Furthermore, the extended memory factor is applied to five kinds of behavior pattern for FSA, including swarming, following, remembering, communicating and searching.

The paper proposes a new intelligent algorithm. On the one hand, this algorithm makes the fish swimming have the characteristics of the speed of inertia; on the other hand, it expands behavior patterns for the fish to choose in the search process and achieves higher accuracy and convergence rate than PSO-FSA, owning to extended memory beneficial to direction and purpose during search. Simulation results verify that these improvements can reduce the blindness of fish search process, improve optimization performance of the algorithm.

Because of the chosen research approach, the research results may lack persuasion. In the future study, the authors will conduct more experiments to understand the behavior of PSOEM-FSA. In addition, there are mainly two aspects that the performance of this algorithm could be further improved.

The proposed algorithm can be used to many practical engineering problems such as tracking problems.

The authors hope that the PSOEM-FSA can increase a branch of FSA algorithm, and enrich the content of the intelligent algorithms to some extent.

The novel optimized FSA algorithm proposed in this paper improves the convergence speed and searching precision of the ordinary FSA to some degree.

Structures play a very important role in developing pressure sensors with good sensitivity and linearity, as they undergo deformation to the input pressure and function as the primary sensing element of the sensor. To achieve high sensitivity, thinner diaphragms are required; however, excessively thin diaphragms may induce large deflection and instability, leading to the unfavorable performances of a sensor in terms of linearity and repeatability. Thereby, importance is given to the development of innovative structures that offer good linearity and sensitivity. This paper aims to investigate the sensitivity of a bossed diaphragm coupled fixed guided beam three-dimensional (3D) structure for pressure sensor applications.

The proposed sensor comprises of mainly two sensing elements: the first being the 3D mechanical structure made of bulk silicon consisting of boss square diaphragm along with a fixed guided beam landing on to its center, forming the primary sensing element, and the diffused piezoresistors, which form the secondary sensing element, are embedded in the tensile and compression regions of the fixed guided beam. This micro mechanical 3 D structure is packaged for applying input pressure to the bottom of boss diaphragm. The sensor without pressure load has no deflection of the diaphragm; hence, no strain is observed on the fixed guided beam and also there is no change in the output voltage. When an input pressure P is applied through the pressure port, there is a deformation in the diaphragm causing a deflection, which displaces the mass and the fixed guided beam vertically, causing strain on the fixed guided beam, with tensile strain toward the guided end and compressive strain toward the fixed end of the close magnitudes. The geometrical dimensions of the structure, such as the diaphragm, boss and fixed guided beam, are optimized for linearity and maximum strain for an applied input pressure range of 0 to 10 bar. The structure is also analyzed analytically, numerically and experimentally, and the results are compared.

The structure offers equal magnitudes of tensile and compressive stresses on the surface of the fixed guided beam. It also offers good linearity and sensitivity. The analytical, simulation and experimental studies of this sensor are introduced and the results correlate with each other. Customized process steps are followed wherein two silicon-on-insulator (SOI) wafers are fusion bonded together, with SOI-1 wafer used to realize the diaphragm along with the boss and SOI-2 wafer to realize the fixed guided beam, leading to formation of a 3D structure. The geometrical dimensions of the structure, such as the diaphragm, boss and fixed guided beam, are optimized for linearity and maximum strain for an applied input pressure range of 0 to10 bar.

This paper presents a unique and compact 3D micro-mechanical structure pressure sensor with a rigid center square diaphragm (boss diaphragm) and a fixed guided beam landing at its center, with diffused piezoresistors embedded in the tensile and compression regions of the fixed guided beam. A total of six masks were involved to realize and fabricate the 3D structure and the sensor, which is presumed to be the first of its kind in the fabrication of MEMS-based piezoresistive pressure sensor.

Green demarketing, which promotes anti-consumption as a more extreme sustainability tactic, could help consumers and societies move toward healthier consumption patterns while building strong, long-lasting relationships with consumers. As even the most committed brands find the need to oscillate between demarketing and conventional marketing for survival, this research tests how the congruency of the campaign shown on a brand's home page (owned media) and a following retargeting ad (paid media) could impact perceived congruency and further downstream effects. In doing so, this research proposes that the media context (i.e. news or shopping browsing context) in which the retargeting ad is embedded could determine how much congruency of the demarketing campaign across owned and paid media matters.

An experiment with a 2 (home page content: green vs. demarketing) × 2 (retargeting ad content: product vs. demarketing) × 2 (browsing context: shopping vs. news) between-subjects factorial design was employed with an online panel of 430 participants. The participants first saw the brand's home page content, then were assigned to a website browsing context where the retargeting ad of the brand was embedded.

In a news browsing context, users perceived higher congruency when product retargeting ads (vs. demarketing) were shown after a green home page exposure and when demarketing retargeting ads (vs. products) were delivered after a demarketing home page. The elevated perceived congruency successfully led to higher ad argument and ad attitude. These differences were not present in a shopping browsing context. These results showed that the congruency between the home page and the retargeting ad for demarketing campaigns mattered more in certain media contexts (i.e. news browsing context).

The study closes the empirical gap in demarketing brand activism campaigns by demonstrating when and how congruency between multiple owned and paid channels for demarketing campaigns impacts consumer responses. This study provides evidence of how the match of the demarketing campaign shown on a brand's home page and a following retargeting ad could impact perceived congruency and further downstream effects of ad argument and ad attitude while considering different browsing context effects.