Mutual fund flow-performance relationship: the role of a foreign parent

In this paper we use a worldwide sample, including 31 countries, to test the influence of funds with a foreign parent on the flow-performance relationship. We study the reason behind the distinction in the way investors in different countries favor fund parents. We find that the flow-performance relationship is convex, consistent with previous studies using a worldwide sample. We also find that funds with foreign parents increase the convexity of fund flow to performance; in other words, investors buy more winners and sell less losers when funds have a foreign parent. The results also show that the enhanced convexity in funds with foreign parents is more pronounced in countries with less developed economies and financial markets, and where investors are less sophisticated.Neste estudo, utilizamos uma amostra que inclui 31 países de diferentes regiões do mundo, para testar o impacto na relação fluxo-performance que decorre de um fundo de investimento ter um parente estrangeiro. Os nossos resultados confirmam que a relação fluxo-performance é convexa, consistente com estudos anteriores usando uma amostra semelhante. Também constatamos que os fundos com parentes estrangeiros apresentam uma maior convexidade; ou seja, os investidores investem mais em fundos com uma boa performance e vendem menos fundos com pior performance, sempre que existe um parente estrangeiro. Os resultados mostram ainda que a maior convexidade nos fundos com parentes estrangeiros é mais pronunciada em países com economias e mercados financeiros menos desenvolvidas e onde os investidores são menos sofisticados

Multi-Robot Trajectory Planning with Feasibility Guarantee and Deadlock Resolution: An Obstacle-Dense Environment

This article presents a multi-robot trajectory planning method which guarantees optimization feasibility and resolves deadlocks in an obstacle-dense environment. The method is proposed via formulating an optimization problem, where the modified buffered Voronoi cell with warning band is utilized to avoid the inter-robot collision and the deadlock is resolved by an adaptive right-hand rule. Meanwhile, a novel safe corridor derived from historical planned trajectory is proposed to provide a proper space for obstacle avoidance in trajectory planning. Comparisons with state-of-the-art works are conducted to illustrate the safety and deadlock resolution in cluttered scenarios. Additionally, hardware experiments are carried out to verify the performance of the proposed method where eight nano-quadrotors fly through a 0.6m cubic framework

IoT analytics and agile optimization for solving dynamic team orienteering problems with mandatory visits

Transport activities and citizen mobility have a deep impact on enlarged smart cities. By analyzing Big Data streams generated through Internet of Things (IoT) devices, this paper aims to show the efficiency of using IoT analytics, as an agile optimization input for solving real-time problems in smart cities. IoT analytics has become the main core of large-scale Internet applications, however, its utilization in optimization approaches for real-time configuration and dynamic conditions of a smart city has been less discussed. The challenging research topic is how to reach real-time IoT analytics for use in optimization approaches. In this paper, we consider integrating IoT analytics into agile optimization problems. A realistic waste collection problem is modeled as a dynamic team orienteering problem with mandatory visits. Open data repositories from smart cities are used for extracting the IoT analytics to achieve maximum advantage under the city environment condition. Our developed methodology allows us to process real-time information gathered from IoT systems in order to optimize the vehicle routing decision under dynamic changes of the traffic environments. A series of computational experiments is provided in order to illustrate our approach and discuss its effectiveness. In these experiments, a traditional static approach is compared against a dynamic one. In the former, the solution is calculated only once at the beginning, while in the latter, the solution is re-calculated periodically as new data are obtained. The results of the experiments clearly show that our proposed dynamic approach outperforms the static one in terms of rewardsThis project has received the support of the Ajuntament of Barcelona and the Fundació “la Caixa” under the framework of the Barcelona Science Plan 2020-2023 (grant 21S09355-001)Peer ReviewedPostprint (published version

Simheuristics: an introductory tutorial

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksBoth manufacturing and service industries are subject to uncertainty. Probability techniques and simulation methods allow us to model and analyze complex systems in which stochastic uncertainty is present. When the goal is to optimize the performance of these stochastic systems, simulation by itself is not enough and it needs to be hybridized with optimization methods. Since many real-life optimization problems in the aforementioned industries are NP-hard and large scale, metaheuristic optimization algorithms are required. The simheuristics concept refers to the hybridization of simulation methods and metaheuristic algorithms. This paper provides an introductory tutorial to the concept of simheuristics, showing how it has been successfully employed in solving stochastic optimization problems in many application fields, from production logistics and transportation to telecommunication and insurance. Current research trends in the area of simheuristics, such as their combination with fuzzy logic techniques and machine learning methods, are also discussed.Peer ReviewedPostprint (author's final draft

Waste collection of medical items under uncertainty using internet of things and city open data repositories: a simheuristic approach

© 2022. IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIn a pandemic situation, a large quantity of medical items are being consumed by citizens globally. If not properly processed, these items can be pollutant or even dangerous. Inspired by a real case study in the city of Barcelona, and assuming that data from container sensors are available in the city open repository, this work addresses a medical waste collection problem both with and without uncertainty. The waste collection process is modeled as a rich open vehicle routing problem, where the constraints are not in the loading dimension but in the maximum time each vehicle can circulate without having to perform a mandatory stop, with the goal of minimizing the time required to complete the collection process. To provide high-quality solutions to this complex problem, a biased-randomized heuristic is proposed. This heuristic is combined with simulation to provide effective collection plans in scenarios where travel and pickup times are uncertainPeer ReviewedPostprint (author's final draft

Tokenized Markets Using Blockchain Technology: Exploring Recent Developments and Opportunities

[EN] The popularity of blockchain technology stems largely from its association with cryptocurrencies, but its potential applications extend beyond this. Fungible tokens, which are interchangeable, can facilitate value transactions, while smart contracts using non-fungible tokens enable the exchange of digital assets. Utilizing blockchain technology, tokenized platforms can create virtual markets that operate without the need for a central authority. In principle, blockchain technology provides these markets with a high degree of security, trustworthiness, and dependability. This article surveys recent developments in these areas, including examples of architectures, designs, challenges, and best practices (case studies) for the design and implementation of tokenized platforms for exchanging digital assets.This work has received financial support from the Horizon Europe Research & amp; Innovation Programme under Grant agreement N. 101092612 (Social and hUman ceNtered XR-SUN project), as well as from the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana "Programa Investigo" (INVEST/2022/342), within the framework of the Plan de Recuperacion, Transformacion y Resiliencia funded by the European Union-NextGenerationEU.Juan-Pérez, ÁA.; Pérez Bernabeu, E.; Li, Y.; Martín, XA.; Ammouriova, M.; Barrios, BB. (2023). Tokenized Markets Using Blockchain Technology: Exploring Recent Developments and Opportunities. Information. 14(6). https://doi.org/10.3390/info1406034714

Doping-enhanced radiative efficiency enables lasing in unpassivated GaAs nanowires

Nanolasers hold promise for applications including integrated photonics, on-chip optical interconnects and optical sensing. Key to the realization of current cavity designs is the use of nanomaterials combining high gain with high radiative efficiency. Until now, efforts to enhance the performance of semiconductor nanomaterials have focused on reducing the rate of non-radiative recombination through improvements to material quality and complex passivation schemes. Here we employ controlled impurity doping to increase the rate of radiative recombination. This unique approach enables us to improve the radiative efficiency of unpassivated GaAs nanowires by a factor of several hundred times while also increasing differential gain and reducing the transparency carrier density. In this way, we demonstrate lasing from a nanomaterial that combines high radiative efficiency with a picosecond carrier lifetime ready for high speed applications