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The aim of this study is to analyze the worst-case scenarios of professional futsal referees during the first and second half of official matches in the Spanish Futsal Cup using a Local Positioning System (LPS) for monitoring their movement patterns. Eight professional futsal referees (40 ± 3.43 years; 1.80 ± 0.03 m; 72.84 ± 4.01 kg) participated in the study. The external load (total distance, high-speed running distance and efforts, sprint distance and efforts, and accelerations and decelerations distances) of the referees was monitored and collected using an LPS. The results revealed significant differences in the worst-case scenarios of the futsal referees during the match according to the time window analyzed (p < 0.05). The longest time windows (120 s, 180 s, and 300 s) showed lower relative total distances in the worst-case scenarios (p < 0.05). The high-speed running distances were significatively higher in the first half for the 120 s (+2.65 m·min−1; ES: 1.25), 180 s (+1.55 m·min−1; ES: 1.28), and 300 s (+0.95 m·min−1; ES: 1.14) time windows (p < 0.05). No differences were found between the first and second half for the high-intensity deceleration distance (p > 0.05). These results will serve to prepare the referees in the best conditions for the competition and adapt the training plans to the worst-case scenarios.

This paper aims to characterise the Entrepreneurial Ecosystems (EE) at the national and regional (subnational) level in Chile, Argentina, and Uruguay employing relevant scientific literature and the latest available data from two well-known entrepreneurial ecosystem indices. Our results show that overall, Chile offers the best national-level ecosystem conditions for productive entrepreneurship among the selected countries. Uruguay and Argentina perform relatively lower than Chile, but they still show potential for improvement by addressing their key system bottlenecks. Moreover, data at the regional level shows that the performance of subnational ecosystems within each country is not homogeneous and regional ecosystems have specific combinations of strengths and weaknesses. Therefore, in a way, these findings confirm the relevance of regional perspectives for research in EE. The data synthesised in this study may be of assistance to researchers interested in understanding entrepreneurship in South American countries and for local policymakers aiming to design context-sensitive entrepreneurship policies.

Floating offshore wind turbines (FOWTs) are systems with complex and highly nonlinear dynamics; they are subjected to heavy loads, making control with classical strategies a challenge. In addition, they experience vibrations due to wind and waves. Furthermore, the control of the blade angle itself may generate vibrations. To address this issue, in this work we propose the design of an intelligent control system based on fuzzy logic to maintain the rated power of an FOWT while reducing the vibrations. A gain scheduling incremental proportional–derivative fuzzy controller is tuned by genetic algorithms (GAs) and combined with a fuzzy-lookup table to generate the pitch reference. The control gains optimized by the GA are stored in a database to ensure a proper operation for different wind and wave conditions. The software Matlab/Simulink and the simulation tool FAST are used. The latter simulates the nonlinear dynamics of a real 5 MW barge-type FOWT with irregular waves. The hybrid control strategy has been evaluated against the reference baseline controller embedded in FAST in different environmental scenarios. The comparison is assessed in terms of output power and structure stability, with up to 23% and 33% vibration suppression rate for tower top displacement and platform pitch, respectively, with the new control scheme. Fatigue damage equivalent load (DEL) of the blades has been also estimated with satisfactory results.

During domestication, lineages diverge phenotypically and genetically from wild relatives, particularly in preferred traits. In addition to evolutionary divergence in selected traits, other fitness-related traits that are unselected may change in concert. For instance, the selection of chili pepper fruits was not intended to change the structure and function of the leaf epidermis. Leaf stomata and trichome densities play a prominent role in regulating stomatal conductance and resistance to herbivores. Here, we assessed whether domestication affected leaf epidermis structure and function in Capsicum annuum. To do this, we compared leaf stomata and trichome densities in six cultivated varieties of Mexican Capsicum annuum and their wild relative. We measured stomatal conductance and resistance to herbivores. Resistance to (defense against) herbivores was measured as variation in the herbivory rate and larvae mortality of Spodoptera frugiperda fed with leaves of wild and cultivated plants. As expected, the different varieties displayed low divergence in stomatal density and conductance. Leaf trichome density was higher in the wild relative, but variation was not correlated with the herbivory rate. In contrast, a higher mortality rate of S. frugiperda larvae was recorded when fed with the wild relative and two varieties than larvae fed with four other varieties. Overall, although domestication did not aim at resistance to herbivores, this evolutionary process produced concerted changes in defensive traits.

The widespread usage of mobile devices and their seamless adaptation to each user’s needs through useful applications (apps) makes them a prime target for malware developers. Malware is software built to harm the user, e.g., to access sensitive user data, such as banking details, or to hold data hostage and block user access. These apps are distributed in marketplaces that host millions and therefore have their forms of automated malware detection in place to deter malware developers and keep their app store (and reputation) trustworthy. Nevertheless, a non-negligible number of apps can bypass these detectors and remain available in the marketplace for any user to download and install on their device. Current malware detection strategies rely on using static or dynamic app extracted features (or a combination of both) to scale the detection and cover the growing number of apps submitted to the marketplace. In this paper, the main focus is on the apps that bypass the malware detectors and stay in the marketplace long enough to receive user feedback. This paper uses real-world data provided by an app store. The quantitative ratings and potential alert flags assigned to the apps by the users were used as features to train machine learning classifiers that successfully classify malware that evaded previous detection attempts. These results present reasonable accuracy and thus work to help to maintain a user-safe environment.

The aim of this study was to analyze the influence of the match half and the playing position on physical requirements in the Spanish Professional Futsal League players during official games. The external load from distance, speed, acceleration and deceleration variables were obtained from fourteen elite futsal players during 10 official matches of the 2019–2020 season using a Local Positioning System with ultra-wideband technology installed on the futsal pitch. The results revealed similar results from physical requirements between first and second half (p > 0.05). Wingers demonstrated greater high-speed running distance (+4.04 m·min−1; CI95%: 0.35 to 7.72; ES: 0.87) than pivots (p > 0.05). There were a high number of accelerations (7.42–9.41 n·min−1) and decelerations (7.37–9.12 n·min−1) per minute in all player positions. The principal finding of the current manuscript did not evidence differences in the physical performance of players between the first and second half. The physical requirements varied among pivots and wingers regarding high-intensity actions. These outcomes add new contributions to the understanding of futsal physical demands.

The current paper addresses relevant network security vulnerabilities introduced by network devices within the emerging paradigm of Internet of Things (IoT) as well as the urgent need to mitigate the negative effects of some types of Distributed Denial of Service (DDoS) attacks that try to explore those security weaknesses. We design and implement a Software-Defined Intrusion Detection System (IDS) that reactively impairs the attacks at its origin, ensuring the “normal operation” of the network infrastructure. Our proposal includes an IDS that automatically detects several DDoS attacks, and then as an attack is detected, it notifies a Software Defined Networking (SDN) controller. The current proposal also downloads some convenient traffic forwarding decisions from the SDN controller to network devices. The evaluation results suggest that our proposal timely detects several types of cyber-attacks based on DDoS, mitigates their negative impacts on the network performance, and ensures the correct data delivery of normal traffic. Our work sheds light on the programming relevance over an abstracted view of the network infrastructure to timely detect a Botnet exploitation, mitigate malicious traffic at its source, and protect benign traffic.