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The Thurston norm is a seminorm on the second real homology group of a compact orientable 3-manifold. The unit ball of this norm is a convex polyhedron, whose shape's data (e.g. number of vertices, regularity) measures the complexity of the surfaces sitting in the ambient 3-manifold. Unfortunately, the Thurston norm is generally quite hard to compute, and a long-standing problem is to understand which polyhedra are realised as the unit balls of the Thurston norms of $3$-manifolds. We show that, when $M$ is the complement of a $2$-bridge link $L$ with components $\ell_1$ and $\ell_2$, the Thurston ball of $M$ has at most 8 faces. The proof of this result strongly relies on a description of essential surfaces in $2$-bridge link complements given by Floyd and Hatcher. Then, we exhibit norm-minimizing representatives for the integral classes of $H_2(M,\partial M)$ and use them to compare the complexity of the Thurston ball with the complexities of $L$ and of $M$. As an example, we show that all the vertices of the Thurston ball lie on the bisectors if and only if $M$ fibers over the circle with fiber a surface with boundary equal to a longitude of $\ell_1$ and some meridians of $\ell_2$. Finally, we use $2$-bridge links in satellite constructions to find $2$-component links whose complements in $S^3$ have Thurston balls with arbitrarily many vertices., Comment: 30 pages, 25 figures

As Multi-Robot Systems (MRS) become more affordable and computing capabilities grow, they provide significant advantages for complex applications such as environmental monitoring, underwater inspections, or space exploration. However, accounting for potential communication loss or the unavailability of communication infrastructures in these application domains remains an open problem. Much of the applicable MRS research assumes that the system can sustain communication through proximity regulations and formation control or by devising a framework for separating and adhering to a predetermined plan for extended periods of disconnection. The latter technique enables an MRS to be more efficient, but breakdowns and environmental uncertainties can have a domino effect throughout the system, particularly when the mission goal is intricate or time-sensitive. To deal with this problem, our proposed framework has two main phases: i) a centralized planner to allocate mission tasks by rewarding intermittent rendezvous between robots to mitigate the effects of the unforeseen events during mission execution, and ii) a decentralized replanning scheme leveraging epistemic planning to formalize belief propagation and a Monte Carlo tree search for policy optimization given distributed rational belief updates. The proposed framework outperforms a baseline heuristic and is validated using simulations and experiments with aerial vehicles.

This study investigates price seasonality in the Brazilian air transport industry, emphasizing the impact of the COVID-19 pandemic on domestic airline pricing strategies. Given potential shifts in demand patterns following the global health crisis, this study explores possible long-term structural changes in the seasonality of Brazilian airfare. We analyze an open dataset of domestic city pairs from 2013 to 2023, employing an econometric model developed using Stata software. Our findings indicate alterations in seasonal patterns and long-term trends in the post-pandemic era. These changes underscore potential shifts in the composition of leisure and business travelers, along with the cost pressures faced by airlines.

In this study, we will address some topics related to the privatization of airports in the scientific literature, in an attempt to provide an answer to the following question: does the privatization of airports bring positive results? Firstly, we turn our attention to the motivations leading to privatization, considering the two main parties involved, the government and the private sector. After all, the success of such a decision will be relative to the reasons that justify it. In a second moment, we will consider the regulatory issue, whose influence on the airport's financial performance is consolidated in the literature. In the third part, we address the main documented results of privatization, with special attention to productive efficiency, whose improvement is the most popular motivation for privatization., Comment: This article is written in Portuguese

This work focuses on trying to understand how the construction of an airline's network is made. For this purpose, the case of Azul was studied, investigating which and how factors affect the decision of this airline to enter domestic routes, in addition to analyzing how the merger of Azul with the regional airline Trip affected the company's network planning. For this, an academic study was conducted using an econometric model to understand the airline's entry model. The results show that Azul's business model is based on connecting new destinations, not yet served by its competitors, to one of its hubs, and consistently avoiding routes or airports dominated by other airlines. Regarding the effects of the merger, the results suggest that Azul moved away from its original entry model, based on JetBlue, to a model more oriented towards regional aviation, entering shorter routes and regional airports., Comment: This article is written in Portuguese

In recent years, the topic of global warming and greenhouse gas emissions has been increasingly in the media. This theme has raised various flags, showing concern for the future and seeking alternatives for a more sustainable life over the years. When studying greenhouse gas emissions, one of the main emitters of such gases is the burning of fuels, in which transport vehicles that depend on gas and oil are included. In this respect, air transport through aircraft is one of the sources emitting such gases. Aiming to reduce gas emissions, one of the ways to do this is by reducing fuel consumption; for this, aircraft would have to be more efficient, or the offer and demand for flights would be reduced. However, what if aircraft fuel consumption were taxed? What would be the effects of this on air transport? Could this be one of the alternatives to reduce emissions? To understand this relationship between taxation and a possible reduction in fuel consumption, a study was developed by the Aeronautics Institute of Technology (ITA), using an econometric model to understand how demand would be affected by changes in airfares. In addition, a simulation of possible environmental taxes on the values of air tickets was carried out to analyze the demand response and to get an idea if this taxation would really solve the emission problems., Comment: This article is written in Portuguese

The exploration of existing commercial opportunities has been increasing the share of commercial (non-aeronautical) revenues in the total revenues of airports worldwide. These revenues, also called commercial, non-aeronautical, or non-tariff revenues, come from rentals, duty-free shops, food and beverage sales, parking, advertising, etc. In other words, everything that is not the main business of the airport. Consequently, the dependence on commercial revenues has also become increasingly important, and airport managers are interested in understanding how to improve their financial results with this new revenue source, as it not only improves financial outcomes but also optimizes passengers' time and money consumption options at airports. Therefore, this chapter seeks to discuss the main determinants of commercial revenues at national airports, analyzing the possible impacts of the behavior of passengers from low-cost carriers (LCC) on these revenues, combined with other determining factors., Comment: This article is written in Portuguese

This study addresses the growing standardization of airline fleets, highlighting that frequent passengers are more likely to fly on the same aircraft model more often. The objective is to analyze the fleet management of airlines and the impact of a reduced variety of models on company operations. The benefits of standardization, such as operational efficiency, and the risks, such as vulnerability to specific model failures, are discussed. The work reviews international scientific literature on the subject, identifying consensus and disagreements that suggest areas for future research. It also includes a study on the Brazilian market, examining how standardization affects operational costs and profitability in terms of model, family, and aircraft manufacturer. Furthermore, the relationship between fleet standardization and the business model of the companies is investigated, concluding that the advantages of standardization are not exclusive to low-cost companies but can also be leveraged by other airlines., Comment: This article is written in Portuguese

This study explores the approaches used by airlines in setting flight times. It highlights the need to balance operational and strategic factors, such as optimizing the use of resources - including aircraft, crew, and fuel - and managing the risks related to delays and congestion. The work details a national analysis focused on domestic flights, investigating the factors that influence companies to adjust scheduled flight times and the impact of this practice on punctuality. The results indicate that decisions about flight time are influenced by both operational and strategic aspects, being affected by competition and the sector's policies on punctuality and slot allocation. Furthermore, it was found that adding extra time is an effective strategy for reducing delays, although it may conceal system deficiencies., Comment: This article is written in Portuguese

This work presents an analysis of recent literature examining factors that influence flight times in Brazil, with special attention to the impact of new technology implementations, specifically Performance-Based Navigation (PBN). PBN procedures began to be implemented in Brazilian airspace in 2009 and represent a new concept of air navigation, using satellites to create 3D flight routes that are shorter and more precise, potentially reducing the distances flown and consequently flight times and delays. Flight times depend on various factors, such as the size and complexity of the origin and destination airports, weather conditions, aircraft models, and how full the flights are. Therefore, to assess the impact of the new procedures, the variation in this set of factors must be taken into account. The results found in the literature suggest that Performance-Based Navigation had a positive impact, reducing flight times by about 1-2%, representing a saving of tens of thousands of flight hours from the beginning of implementations in 2009 until the end of 2018., Comment: This article is written in Portuguese

This study aims to discuss the impacts of a low-cost airline on the air transport market and, especially, to present the most recent findings from specialized literature in the field. To this end, various works on this topic, published since 2015, were selected and analyzed. From this analysis, it was possible to categorize the main topics discussed in the papers into five groups: (i) the impacts of a low-cost airline on competing airlines; (ii) impacts on airports; (iii) general impacts on the demand for air transport; (iv) effects on passengers' choice process; and (v) general effects on a geographical region., Comment: This article is written in Portuguese

Flight delays are a reality in the modern air industry worldwide. However, studies in the literature have investigated the competitive determinants of delays arising from factors originating at the airport and along the route separately. This work aims to present a national study that used a unifying approach from the literature, considering the local and global effects of competition on delays. The analysis took into account a phenomenon known as the "internalization of externalities" of airport congestion. Furthermore, it discusses the relationship between quality and competition on the route and the impacts of the entry of a low-cost carrier (LCC) on the delays of incumbent airlines in the Brazilian air market. The literature suggests that there is evidence of congestion internalization at Brazilian airports, in parallel with competition for quality at the route level. Additionally, the potential competition caused by the presence of the LCC leads to a global effect that suggests the existence of impacts other than prices on routes where it has not entered., Comment: This article is written in Portuguese

This study discusses the literature on the convergence of business models of airlines in Brazilian air transport, focusing on the formation of flight networks. Initially, it analyzes the determinants of the network formation patterns of the "fundamental" business models (archetypes) of airlines in the first years after the sector's deregulation. Then, it discusses how the business models of Brazilian companies resemble these patterns. The literature highlights convergences between the network formation strategies of full-service companies in relation to older low-cost companies, in addition to business model redirections after mergers and acquisitions., Comment: This article is written in Portuguese

This book, written in Portuguese, presents a comprehensive analysis of the air transport industry in Brazil, highlighting its vital importance to the country's economy. It explores the sector's complexity, from economic characteristics to interaction with the national aeronautical industry, through the specialization of the workforce and market demand analysis. The book delves into the economic regulation of air transport, tracing the evolution from periods of strict regulation to phases of liberalization and deregulation, and examines market dynamics, focusing on concentration and competitiveness. It also analyzes demand and supply through case studies, investigating everything from tourists traveling within Brazil to the coverage of the national territory and the prices of air tickets. Finally, the book proposes principles for the regulation and public policies of the air sector, emphasizing the priority of the passenger, the business environment, access to air transport, and economic efficiency, culminating in the advocacy for a free market, but with protection for competition and the consumer., Comment: Pezco Editora & Desenvolvimento - 1st Edition, 2009. In Portuguese

This paper presents a test of intermodal interaction between coaches and airlines in Brazil in order to check for the efficacy of recent liberalization measures designed to promote competition in both industries. Interstate travel service in the country is heavily provided by coaches, and the system is fully operated by the private sector under public delegation through permits and authorizations. Agency-based regulation was introduced in 2002 along with a price cap regime aimed at enhancing the flexibility to change fares in response to demand and cost conditions. By making use of a reaction function-based model of coach operators' pricing decisions in the interstate travel market, we then estimate the sensitivity of the changes in coach fares to the changes in airline fares in a simultaneous-equation framework. Intermodal interaction among coach operators and airlines is found to be highly significant and probably due to the competition for a small but increasing set of premium, quality-sensitive, coach passengers.

The number of air transportation passengers during the holidays in Brazil has grown notably since the late nineties. One of the reasons is greater competition in airfares made possible by economic liberalization. This paper presents an econometric model of airline pricing aiming at estimating the impacts of holiday periods on fares, with special emphasis on three-day holiday events. It makes use of a database with daily collected data from the internet between 2008 and 2010 for the major Brazilian city, Sao Paulo. The econometric panel data model employs a two-way error components "within" estimator, controlling for airline/airport-pair fixed effect along with quotation and departure months effects. The decomposition of time effects between quotation and departure month effects is the main methodological contribution of the paper. Results allow for a comparative analysis of the performance of Sao Paulo's downtown and international airports - respectively, Congonhas (CGH), and Guarulhos (GRU) airports. As a result, the price of tickets bought 60 days in advance for flights with two stops leaving from the downtown airport fell by most.

The service quality of a passenger transport operator can be measured through face-to-face surveys at the terminals or on board. However, the resulting responses may suffer from the influence of the intrinsic aspects of the respondent's personality and emotional context at the time of the interview. This study proposes a methodology to generate and select control variables for these latent psychosituational traits, thus mitigating the risk of omitted variable bias. We developed an econometric model of the determinants of passenger satisfaction in a survey conducted at the largest airport in Latin America, S\~ao Paulo GRU Airport. Our focus was on the role of flight delays in the perception of quality. The results of this study confirm the existence of a relationship between flight delays and the global satisfaction of passengers with airports. In addition, favorable evaluations regarding airports' food/beverage concessions and Wi-Fi services, but not their retail options, have a relevant moderating effect on that relationship. Furthermore, dissatisfaction arising from passengers' interaction with the airline can have negative spillover effects on their satisfaction with the airport. We also found evidence of blame-attribution behavior, in which only delays of internal origin, such as failures in flight management, are significant, indicating that passengers overlook weather-related flight delays. Finally, the results suggest that an empirical specification that does not consider the latent psychosituational traits of passengers produces a relevant overestimation of the absolute effect of flight delays on passenger satisfaction.

As the next generation of diverse workloads like autonomous driving and augmented/virtual reality evolves, computation is shifting from cloud-based services to the edge, leading to the emergence of a cloud-edge compute continuum. This continuum promises a wide spectrum of deployment opportunities for workloads that can leverage the strengths of cloud (scalable infrastructure, high reliability) and edge (energy efficient, low latencies). Despite its promises, the continuum has only been studied in silos of various computing models, thus lacking strong end-to-end theoretical and engineering foundations for computing and resource management across the continuum. Consequently, developers resort to ad hoc approaches to reason about performance and resource utilization of workloads in the continuum. In this work, we conduct a first-of-its-kind systematic study of various computing models, identify salient properties, and make a case to unify them under a compute continuum reference architecture. This architecture provides an end-to-end analysis framework for developers to reason about resource management, workload distribution, and performance analysis. We demonstrate the utility of the reference architecture by analyzing two popular continuum workloads, deep learning and industrial IoT. We have developed an accompanying deployment and benchmarking framework and first-order analytical model for quantitative reasoning of continuum workloads. The framework is open-sourced and available at https://github.com/atlarge-research/continuum., Comment: 14 pages, SPEC-RG technical report

Stream processing applications extract value from raw data through Directed Acyclic Graphs of data analysis tasks. Shared-nothing (SN) parallelism is the de-facto standard to scale stream processing applications. Given an application, SN parallelism instantiates several copies of each analysis task, making each instance responsible for a dedicated portion of the overall analysis, and relies on dedicated queues to exchange data among connected instances. On the one hand, SN parallelism can scale the execution of applications both up and out since threads can run task instances within and across processes/nodes. On the other hand, its lack of sharing can cause unnecessary overheads and hinder the scaling up when threads operate on data that could be jointly accessed in shared memory. This trade-off motivated us in studying a way for stream processing applications to leverage shared memory and boost the scale up (before the scale out) while adhering to the widely-adopted and SN-based APIs for stream processing applications. We introduce STRETCH, a framework that maximizes the scale up and offers instantaneous elastic reconfigurations (without state transfer) for stream processing applications. We propose the concept of Virtual Shared-Nothing (VSN) parallelism and elasticity and provide formal definitions and correctness proofs for the semantics of the analysis tasks supported by STRETCH, showing they extend the ones found in common Stream Processing Engines. We also provide a fully implemented prototype and show that STRETCH's performance exceeds that of state-of-the-art frameworks such as Apache Flink and offers, to the best of our knowledge, unprecedented ultra-fast reconfigurations, taking less than 40 ms even when provisioning tens of new task instances.

A traditional approach to realize self-adaptation in software engineering (SE) is by means of feedback loops. The goals of the system can be specified as formal properties that are verified against models of the system. On the other hand, control theory (CT) provides a well-established foundation for designing feedback loop systems and providing guarantees for essential properties, such as stability, settling time, and steady state error. Currently, it is an open question whether and how traditional SE approaches to self-adaptation consider properties from CT. Answering this question is challenging given the principle differences in representing properties in both fields. In this paper, we take a first step to answer this question. We follow a bottom up approach where we specify a control design (in Simulink) for a case inspired by Scuderia Ferrari (F1) and provide evidence for stability and safety. The design is then transferred into code (in C) that is further optimized. Next, we define properties that enable verifying whether the control properties still hold at code level. Then, we consolidate the solution by mapping the properties in both worlds using specification patterns as common language and we verify the correctness of this mapping. The mapping offers a reusable artifact to solve similar problems. Finally, we outline opportunities for future work, particularly to refine and extend the mapping and investigate how it can improve the engineering of self-adaptive systems for both SE and CT engineers.

The economic downturn and the air travel crisis triggered by the recent coronavirus pandemic pose a substantial threat to the new consumer class of many emerging economies. In Brazil, considerable improvements in social inclusion have fostered the emergence of hundreds of thousands of first-time fliers over the past decades. We apply a two-step regression methodology in which the first step consists of identifying air transport markets characterized by greater social inclusion, using indicators of the local economies' income distribution, credit availability, and access to the Internet. In the second step, we inspect the drivers of the plunge in air travel demand since the pandemic began, differentiating markets by their predicted social inclusion intensity. After controlling for potential endogeneity stemming from the spread of COVID-19 through air travel, our results suggest that short and low-density routes are among the most impacted airline markets and that business-oriented routes are more impacted than leisure ones. Finally, we estimate that a market with 1 per cent higher social inclusion is associated with a 0.153 per cent to 0.166 per cent more pronounced decline in demand during the pandemic. Therefore, markets that have benefited from greater social inclusion in the country may be the most vulnerable to the current crisis., Comment: 30 pages

It is well known that several viruses, as well as SARS-CoV-2, can be transmitted through airborne diffusion of saliva micro-droplets. For this reason many reserach groups have been devoted their efforts in order to gain new insight into the transport of fluids and particles originted from human respiratory tracts. This paper aims to provide a contribution to the numerical modelling of bio-aerosols. In particular, the well-known problem around the safety distance to be held for avoiding virus transmission in the absence of external wind is further investigated. Thus, new indexes capable of evaluating the contamination risk are introduced and the possibility to inactivate virus particles by means of an external UV-C radiation source is studied. For this purpose, a new model which takes into account biological inactivation deriving from UV-C exposure in a Eulerian-Lagrangian framework is presented., Comment: 12 pages, 23 figures. It will be submitted to Physics of Fluids

Streaming analysis is widely used in cloud as well as edge infrastructures. In these contexts, fine-grained application performance can be based on accurate modeling of streaming operators. This is especially beneficial for computationally expensive operators like adaptive stream joins that, being very sensitive to rate-varying data streams, would otherwise require costly frequent monitoring. We propose a dynamic model for the processing throughput and latency of adaptive stream joins that run with different parallelism degrees. The model is presented with progressive complexity, from a centralized non-deterministic up to a deterministic parallel stream join, describing how throughput and latency dynamics are influenced by various configuration parameters. The model is catalytic for understanding the behavior of stream joins against different system deployments, as we show with our model-based autoscaling methodology to change the parallelism degree of stream joins during the execution. Our thorough evaluation, for a broad spectrum of parameter, confirms the model can reliably predict throughput and latency metrics with a fairly high accuracy, with the median error in estimation ranging from approximately 0.1% to 6.5%, even for an overloaded system. Furthermore, we show that our model allows to efficiently control adaptive stream joins by estimating the needed resources solely based on the observed input load. In particular, we show it can be employed to enable efficient autoscaling, even when big changes in the input load happen frequently (in the realm of seconds)., Comment: part of the experimental campaign has been included in a different contribution

Two of the main paradigms used to build adaptive software employ different types of properties to capture relevant aspects of the system's run-time behavior. On the one hand, control systems consider properties that concern static aspects like stability, as well as dynamic properties that capture the transient evolution of variables such as settling time. On the other hand, self-adaptive systems consider mostly non-functional properties that capture concerns such as performance, reliability, and cost. In general, it is not easy to reconcile these two types of properties or identify under which conditions they constitute a good fit to provide run-time guarantees. There is a need of identifying the key properties in the areas of control and self-adaptation, as well as of characterizing and mapping them to better understand how they relate and possibly complement each other. In this paper, we take a first step to tackle this problem by: (1) identifying a set of key properties in control theory, (2) illustrating the formalization of some of these properties employing temporal logic languages commonly used to engineer self-adaptive software systems, and (3) illustrating how to map key properties that characterize self-adaptive software systems into control properties, leveraging their formalization in temporal logics. We illustrate the different steps of the mapping on an exemplar case in the cloud computing domain and conclude with identifying open challenges in the area.

The growing popularity of workflows in the cloud domain promoted the development of sophisticated autoscaling policies that allow automatic allocation and deallocation of resources. However, many state-of-the-art autoscaling policies for workflows are mostly plan-based or designed for batches (ensembles) of workflows. This reduces their flexibility when dealing with workloads of workflows, as the workloads are often subject to unpredictable resource demand fluctuations. Moreover, autoscaling in clouds almost always imposes budget constraints that should be satisfied. The budget-aware autoscalers for workflows usually require task runtime estimates to be provided beforehand, which is not always possible when dealing with workloads due to their dynamic nature. To address these issues, we propose a novel Performance-Feedback Autoscaler (PFA) that is budget-aware and does not require task runtime estimates for its operation. Instead, it uses the performance-feedback loop that monitors the average throughput on each resource type. We implement PFA in the popular Apache Airflow workflow management system, and compare the performance of our autoscaler with other two state-of-the-art autoscalers, and with the optimal solution obtained with the Mixed Integer Programming approach. Our results show that PFA outperforms other considered online autoscalers, as it effectively minimizes the average job slowdown by up to 47% while still satisfying the budget constraints. Moreover, PFA shows by up to 76% lower average runtime than the competitors., Comment: Technical Report