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This study aims to reduce the redundant weight of the anti-roll torsion bar brought by the traditional empirical design and improving its strength and stiffness.

Based on the finite element approach coupled with the improved beluga whale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the design of the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar were defined as random variables, and the torsion bar's mass and strength were investigated using finite elements. Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whale optimization (BWO) algorithm and run case studies.

The findings demonstrate that the IBWO has superior solution set distribution uniformity, convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimize the anti-roll torsion bar design. The error between the optimization and finite element simulation results was less than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress was reduced by 35% and the stiffness was increased by 1.9%.

The study provides a methodological reference for the simulation optimization process of the lateral anti-roll torsion bar.

The microseismic monitoring technique has great advantages on identifying the location, extent and the mechanism of damage process occurring in rock mass. This study aims to analyze distribution characteristics and the evolution law of excavation damage zone of surrounding rock based on microseismic monitoring data.

In situ test using microseismic monitoring technique is carried out in the large-span transition tunnel of Badaling Great Wall Station of Beijing-Zhangjiakou high-speed railway. An intelligent microseismic monitoring system is built with symmetry monitoring point layout both on the mountain surface and inside the tunnel to achieve three-dimensional and all-round monitoring results.

Microseismic events can be divided into high density area, medium density area and low density area according to the density distribution of microseismic events. The positions where the cumulative distribution frequencies of microseismic events are 60 and 80% are identified as the boundaries between high and medium density areas and between medium and low density areas, respectively. The high density area of microseismic events is regarded as the high excavation damage zone of surrounding rock, which is affected by the grade of surrounding rock and the span of tunnel. The prediction formulas for the depth of high excavation damage zone of surrounding rock at different tunnel positions are given considering these two parameters. The scale of the average moment magnitude parameters of microseismic events is adopted to describe the damage degree of surrounding rock. The strong positive correlation and multistage characteristics between the depth of excavation damage zone and deformation of surrounding rock are revealed. Based on the depth of high excavation damage zone of surrounding rock, the prestressed anchor cable (rod) is designed, and the safety of anchor cable (rod) design parameters is verified by the deformation results of surrounding rock.

The research provides a new method to predict the surrounding rock damage zone of large-span tunnel and also provides a reference basis for design parameters of prestressed anchor cable (rod).

Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India.

Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India.

The result of the study identified many significant barriers and their importance to tourism growth in rural India.

The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism.

The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism.

This study characterizes the scenario of emerging countries (ECs) – “Brazil, Russia, India, China and South Africa (BRICS)” concerning digital transformation and its association with the Industry 4.0 (I4.0) value creation system. For such, the authors developed a discussion paper based on content analysis of 857 journals in business administration, describing in a proposed framework the institutionalization “BRICS” policies that nurture global competitiveness among ECs and development needs to catching up.

Data from 16 official documents of government, ministries and economic studies were analyzed by applying Atlas TI contrasting theory of 875 papers to develop and discuss the framework. Content analysis showed research gaps, technological needs and governance to enable firms to sustain competitive advantages applying I4.0 value creation system. Results converged into a microfoundation of the agile journey of a digital transformation to global organizations in between BRICS.

This paper's central question is to understand: How can organizations achieve a sustainable I4.0 value creation system adopting digital transformation in “BRICS”? The reduced transaction costs driven by platforms and ecosystems orchestration and the related or integrated multiple level sources of knowledge could speed benefits of domestic firms and subsidiaries of global organizations. Research gaps could be understood by a new combination of resources and knowledge, exploiting technologies and, also, the discussion of social economic relevance of I4.0.

Because of the complexity and the novelty of the framework, further studies could be discussed by its elements. New structures and paths for alternative strategic factors may be proposed in the future with the inclusion of new relationships in the adoption of platform business models and ecosystems. Future studies should consider digital knowledge-based assets attained to economic activities across national boundaries; data analytics or data-driven technology adoption and their effects on global attractiveness.

The paper implicates in evaluating whether dynamic capabilities subsidize performance propitiating the catching up with a focus on the I4.0 system and digital transformation management journey. The proposed framework demonstrates the benefits of digital transformation by enabling strategic capabilities, making efforts to reduce a lack of research paths concerning the policy attributes that define the platform use strategy from an architectural standpoint and its benefits.

The particularities of turning either an I4.0 global organization or a digital organization operate in various environments, allowing access to the activities' digital context. Social implications concerning digital resources as strategic accelerators are determined by the BRICS peculiarities, such as social behavior, consumerism or communication pattern, leadership and workforce skills. Finally, political aspects and interference in the economy are deployed in society what must be considered.

This paper proposes a conceptual framework to better understand whether the heterogeneity of resources could explain I4.0 and digital configurations, while new platforms have driven features in global industrial environments and ecosystems. The seizing opportunities in these countries and sense-making use of platforms and orchestration of ecosystems are found as the critical topics being the main value of this important discussion.

Free guided walking tours are one of the most successful tourism segments in the digital platform economy. It is beginning to be associated with negative impacts in some of the destinations where it is spreading rapidly. Although the platform economy is generating increasing academic interest, the free tour model remains largely unexplored area in the literature. This study aims to examine how such activity affects cultural destinations.

Focussing on the largest Free Tours platform operating in Spain, GuruWalk, the methodology used analyses its impact in six cultural destinations on two of the sustainability dimensions: the territorial dimension and the governance, through an exploratory study.

The findings help to understand the differences that such activity generates in each destination depending on the phase of its life cycle, and to implement, if necessary, corrective measures. The research confirms that the impacts differ according to the tourist destination’s maturity, concluding that such activity contributes to the increase of tourist agglomerations and the overcrowding of cultural destinations in their middle and mature life cycles. The findings highlighted the importance of the role of local governance on free tour activity.

The main contribution is the association of the impacts they produce (especially in terms of massification) with destination life cycle phases. There were no similar precedents with a spatial or territorial analysis to reliably demonstrate not only that this activity has an impact on the territory but also what type of impact is produced.

The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.

To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.

Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.

It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.

We previously examined the efficacy of rTMS for major depressive disorder in an applied clinical practice. Clinical response was related to severity of depression as well as the rTMS instrument utilized suggesting a relationship to instrument or magnetic field parameters and individual factors. The effectiveness of repetitive transcranial magnetic stimulation (rTMS) in the treatment of major depressive disorder was further evaluated using Log-Rank statistics for time to remission outcomes. A follow-up retrospective medical records study was carried out on patients with major depressive disorder undergoing rTMS therapy at AwakeningsKC Clinical Neuroscience Institute (CNI), a suburban tertiary psychiatric clinic. Cox Proportional Hazard with Log-Rank statistics were applied and the time course to clinical remission was evaluated over a 6-week period with respect to age, gender, and depression severity. Clinical response was observed referencing two different rTMS instruments (MagVenture; NeuroStar). Time to remission studies of 247 case reports (N=98 males; N=149 females) showed consistently greater clinically defined remission rates after 6 weeks of rTMS treatment for patients using the MagVenture vs NeuroStar instrument. Patients previously admitted for inpatient psychiatric hospitalization exhibited higher response rates when treated with the MagVenture rTMS unit. Stepwise Cox Proportional Hazards Regression final model of time to remission included rTMS unit, inpatient psychiatric hospitalization and obese body habitus. Response to rTMS in applied clinical practice is related to severity of psychiatric illness and may require consideration of magnetic field parameters of the rTMS unit with respect to individual factors such as sex or body composition.

Several studies have been made that analyze factors that affect the demand of tourism from several optics. This paper aims to study the factors that determine the demand for tourism in Mexico, through an econometric analysis, by using the Johansen cointegration model (1991) to determine the long-term elasticity between the demand of tourists and the wealth related to its main markets (the USA and Canada) and the relative prices in Mexico and its two main competitors (the Dominican Republic and Costa Rica).

The authors used econometric analysis using Johansen’s cointegration model (1991), using as a dependent variable the demand of tourists from the main countries of origin (the USA and Canada), taking as data the number of tourists by air in the period 1980-2015, according to information from the SIIMT. The independent variables are the relative wealth of the country of origin of the tourists (wealth of the tourist in Mexico concerning the wealth in their country of origin) and the relative prices of the destination country with respect to the country of competition. The source for per capita income and the consumer price index is the World Bank.

The results obtained in this document show that in the long-term the price is a factor of impact in the purchase decision of both markets analyzed. Presenting an elastic demand to the price, which implies that the market is sensitive to the variations of the price of tourist services, opting for the destination that offers better prices, with a higher sensitivity to the price when compared with Costa Rica. Coinciding with previous studies carried out in other tourist destinations, such as in the work of Patsouratis et al. (2005).

The main contribution of this work is to determine the long-term relationship, through a cointegration analysis of Johansen (1991). A methodology that has not been used to perform a competitive analysis between countries. Additionally, the present work uses variables different from those considered in previous works; the dependent variable is the demand of tourists from the main countries of origin (the USA and Canada) and as dependent variables the relative wealth of the country of origin of the tourists (Wealth of the tourist in Mexico with respect to wealth in their country of origin) and the relative prices of the destination country with respect to the country of competition.