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This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

We develop a Bayesian approach for modeling brain activation and connectivity from functional magnetic resonance image (fMRI) data. Our approach simultaneously estimates local hemodynamic response functions (HRFs) and activation parameters, as well as global effective and functional connectivity parameters. Existing methods assume identical HRFs across brain regions, which may lead to erroneous conclusions in inferring activation and connectivity patterns. Our approach addresses this limitation by estimating region-specific HRFs. Additionally, it enables neuroscientists to compare effective connectivity networks for different experimental conditions. Furthermore, the use of spike and slab priors on the connectivity parameters allows us to directly select significant effective connectivities in a given network.

We include a simulation study that demonstrates that, compared to the standard generalized linear model (GLM) approach, our model generally has higher power and lower type I error and bias than the GLM approach, and it also has the ability to capture condition-specific connectivities. We applied our approach to a dataset from a stroke study and found different effective connectivity patterns for task and rest conditions in certain brain regions of interest (ROIs).

In this research, the authors established a hierarchical motion planner for quadruped locomotion, which enables a parallel wheel-quadruped robot, the “BIT-NAZA” robot, to traverse rough three-dimensional (3-D) terrain.

Presented is a novel wheel-quadruped mobile robot with parallel driving mechanisms and based on the Stewart six degrees of freedom (6-DOF) platform. The task for traversing rough terrain is decomposed into two prospects: one is the configuration selection in terms of a local foothold cost map, in which the kinematic feasibility of parallel mechanism and terrain features are satisfied in heuristic search planning, and the other one is a whole-body controller to complete smooth and continuous motion transitions.

A fan-shaped foot search region focuses on footholds with a strong possibility of becoming foot placement, simplifying computation complexity. A receding horizon avoids kinematic deadlock during the search process and improves robot adaptation.

Both simulation and experimental results validated the proposed scenario available and appropriate for quadruped locomotion to traverse challenging 3-D terrains.

This paper analyzes kinematic workspace for a parallel robot with 6-DOF Stewart mechanism on both body and foot. A fan-shaped foot search region enhances computation efficiency. Receding horizon broadens the preview search to decrease the possibility of deadlock minima resulting from terrain variation.

This study investigates, both theoretically and empirically, the effects of joint ventures on traffic. Although alliances are a pre-condition for joint ventures, both cooperation agreements are different in their nature. The reason is that alliances are revenue-sharing agreements, whereas joint ventures also involve a cost-sharing commitment. Our empirical analysis focuses on the transatlantic market, including non-stop routings (interhub markets) and one-stopover routings (interline markets). Our theoretical and empirical findings emphasize the relevance of economies of traffic density and reveal a positive effect of joint ventures on traffic, both in interhub and interline markets.

Rambutan (Nephelium lappaceum), a ubiquitous fruit in Southeastern Asia, was rich in vitamins and phytochemicals, which were beneficial for improving of skin conditions. The fermentation process increased phytochemicals and antioxidant capacity. Thus, the purpose of this paper is to examine whether phytochemicals can be increased through the fermentation process of rambutan extracts to improve skin aging.

In this study, the authors used the three stages of fermentation with Saccharomyces cerevisiae, Lactobacillus plantarum TCI028 and Acetobacter aceti under red light to develop a fermented rambutan extract.

The level of polyphenols of red-light-based fermented rambutan extract (RLFRE) were significantly increased 108.9% (p < 0.01) and 97% (p <0.01) compared with fermented rambutan extract (FRE) and pure rambutan extract (RE), respectively. The human skin fibroblasts treated with 0.03 or 0.06% of RLFRE can significantly decrease reactive oxygen species (ROS) levels by 0.74- (p <0.001) and 0.84-fold (p <0.001) compared with H₂O₂ group, respectively. And 0.03% of RLFRE can significantly increase in elastin content by 1.13-fold (p <0.05). Also, ten compounds were identified including one new phenolic compound and nine known compounds from RLFRE. Moreover, red light could enhance the levels of compounds 4, 9 and 3 by 5, 2.5 and 2.5-fold, respectively, relative to the results of FRE. The last, RLFRE isolated compounds significantly facilitated the elastin content on fibroblast (compound 1, 7, 9, 10 compared with control: p <0.001, compound 2 compared with control: p <0.001).

In short, this was the first study to unveil that the red-light-based fermentation can enrich the antioxidant content in a rambutan extract and its product had the potential to be developed a functional product for health-promoting effects such as skin aging.

Assembly sequence optimization is a difficult combinatorial optimization problem having to simultaneously satisfy various feasibility constraints and optimization criteria. Applications of evolutionary algorithms have shown a lot of promise in terms of lower computational cost and time. But there remain challenges like achieving global optimum in least number of iterations with fast convergence speed, robustness/consistency in finding global optimum, etc. With the above challenges in mind, this study aims to propose an improved flower pollination algorithm (FPA) and hybrid genetic algorithm (GA)-FPA.

In view of slower convergence rate and more computational time required by the previous discrete FPA, this paper presents an improved hybrid FPA with different representation scheme, initial population generation strategy and modifications in local and global pollination rules. Different optimization objectives are considered like direction changes, tool changes, assembly stability, base component location and feasibility. The parameter settings of hybrid GA-FPA are also discussed.

The results, when compared with previous discrete FPA and GA, memetic algorithm (MA), harmony search and improved FPA (IFPA), the proposed hybrid GA-FPA gives promising results with respect to higher global best fitness and higher average fitness, faster convergence (especially from the previously developed variant of FPA) and most importantly improved robustness/consistency in generating global optimum solutions.

It is anticipated that using the proposed approach, assembly sequence planning can be accomplished efficiently and consistently with reduced lead time for process planning, making it cost-effective for industrial applications.

Different representation schemes, initial population generation strategy and modifications in local and global pollination rules are introduced in the IFPA. Moreover, hybridization with GA is proposed to improve convergence speed and robustness/consistency in finding globally optimal solutions.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

The term relevance weighting method has been shown to produce optimal information retrieval queries under well‐defined conditions. Unfortunately, the relevance weights cannot be determined in the absence of accurate knowledge of the occurrence frequencies of the terms in the relevant and non‐relevant documents of a collection. This study presents a realistic method for estimating the term relevance weights from information derived in an interactive search environment where relevance assessments for previously retrieved items are used later to construct improved query statements. Procedures are introduced for constructing the initial query weights by using estimated term relevance factors. These initial weights are then modified during the relevance feedback process by utilizing the occurrence frequencies of the terms in the retrieved documents obtained from an earlier search. The procedures used to construct the term relevance weights are covered in detail, and experimental output is included to illustrate the effectiveness of the methods.

In this chapter, we estimate the allocative efficiency of Spanish airports in the pre-privatization period from 2009 until 2014. The estimation of an input-oriented distance system of equations allows us to calculate different allocative efficiency measures using two approaches. The results show that allocative inefficiencies exist for Spanish airports during this period. Moreover, in breaking down allocative efficiency changes by periods coinciding with different government strategies of privatization, we find important differences. In the initial period, when the government encouraged decentralized management of airports and privatization of the largest airports, allocative efficiency improved (from 2009 to 2012). In the second period, however, when the government focused on centralized airport management and privatization of the system as a whole (from 2012 to 2014), inefficiencies slightly increased again.