Self perception of decision making competence in spanish football players

Background: It is known that competence to make decisions is a fundamental aspect of sport competition. Objective: This study has analyzed the decision profile of a sample of Spanish football players of different levels of expertise. Methods: 690 Spanish football players of national and international level completed the decision making questionnaire, which cover three dimensions ? perceived decision competence, decision anxiety and commitment with decision learning. MANCOVA and ANOVA analysis were carried out to analyse the differences in each dimension based on the level of expertise. Results: Results showed that perception of decision making competence increased and the anxiety decreased with the level of expertise. Conclusions: This study confirmed the usefulness of this questionnaire in the process of training for coaches and sport psychologists

Aplicación de la topología molecular en la predicción de la inhibición de Trypanosoma cruzi Hexokinasa y un grupo de derivados bifosfonatos

A topological-mathematical model has been arranged to search for new derivatives of bisphosphonate compounds actingas inhibitors against Trypanosoma cruzi hexokinase. By using linear discriminant analysis, a four-variable function wasachieved allowing an accurate prediction of the IC50 for each compound of the training and test series. After carryingout a virtual screening based upon such a model, new structures potentially actives against T. cruzi are proposedSe ha desarrollado un modelo topológico-matemático para la búsqueda de nuevos derivados bisfosfonatos activosfrente a la hexokinasa de Trypanosoma cruzi. Utilizando el análisis lineal discriminante se ha seleccionado una funcióncon cuatro variables capaz de predecir adecuadamente la CI50 para cada compuesto de las series de entrenamientoy test. El modelo propuesto se ha aplicado a una librería molecular y se han propuesto nuevas estructuraspotencialmente activas frente a T. cruzi

Sustainable sugarcane vinasse biorefinement for trans-aconitic acid-based biopolymer synthesis and bioenergy generation

This study aimed at developing a multiproduct biorefinery scheme for vinase valorization. It involved the extraction of trans-aconitic acid, its transformation into biopolymers using microwave irradiation and the use of the raffinated-vinasse for biogas production. Each technology was assessed individually, followed by a process integration at bench scale, from which a mass balance was calculated, supporting the feasibility of the approach. As a renewable source derived from a residue, these bioproducts can replace crude-oil-based materials in various chemical industrial processes; however, a detailed techno-economic and life-cycle analysis are required to defined the sustainability of the process

Relocation and investment in R&D by firms

The literature on foreign direct investment has analyzed corporate location decisions when firms invest in R&D to reduce production costs. Such firms may set up new plants in other developed countries while maintaining their domestic plants. In contrast, we here consider firms that close down their domestic operations and relocate to countries where wage costs are lower. Thus, we assume that firms may reduce their production costs by investing in R&D and likewise by moving their plants abroad. We show that these two mechanisms are complementary. When a firm relocates it invests more in R&D than when it does not change its location and, therefore, its production cost is lower in the first case. As a result, investment in R&D encourages firms to relocate.info:eu-repo/semantics/publishedVersio

LMTurk: Few-Shot Learners as Crowdsourcing Workers in a Language-Model-as-a-Service Framework

Vast efforts have been devoted to creating high-performance few-shot learners, i.e., large-scale pretrained language models (PLMs) that perform well with little downstream task training data. Training PLMs has incurred significant cost, but utilizing the few-shot learners is still challenging due to their enormous size. This work focuses on a crucial question: How to make effective use of these few-shot learners? We propose LMTurk, a novel approach that treats few-shotlearners as crowdsourcing workers. The rationale is that crowdsourcing workers are in fact few-shot learners: They are shown a few illustrative examples to learn about a task and then start annotating. LMTurk employs few-shot learners built upon PLMs as workers. We show that the resulting annotations can be utilized to train models that solve the task well and are small enough to be deployable in practical scenarios. Active learning is integrated into LMTurk to reduce the amount of queries made to PLMs, minimizing the computational cost of running PLM inference passes. Altogether, LMTurk is an important step towards making effective use of current PLMs

Interplay between liver and blood stages of Plasmodium infection dictates malaria severity via γδ T cells and IL-17-promoted stress erythropoiesis

© 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Plasmodium replicates within the liver prior to reaching the bloodstream and infecting red blood cells. Because clinical manifestations of malaria only arise during the blood stage of infection, a perception exists that liver infection does not impact disease pathology. By developing a murine model where the liver and blood stages of infection are uncoupled, we showed that the integration of signals from both stages dictated mortality outcomes. This dichotomy relied on liver stage-dependent activation of Vγ4+ γδ T cells. Subsequent blood stage parasite loads dictated their cytokine profiles, where low parasite loads preferentially expanded IL-17-producing γδ T cells. IL-17 drove extra-medullary erythropoiesis and concomitant reticulocytosis, which protected mice from lethal experimental cerebral malaria (ECM). Adoptive transfer of erythroid precursors could rescue mice from ECM. Modeling of γδ T cell dynamics suggests that this protective mechanism may be key for the establishment of naturally acquired malaria immunity among frequently exposed individuals.We would like to acknowledge Freddy Frischknecht (Integrative Parasitology Center for Infectious Diseases, Heidelberg) for providing the Plasmodium berghei lisp2− parasite line, Immo Prinz (Hannover Medical School, Hannover) for providing genetically modified mouse lines, Ana Parreira (iMM-JLA, Portugal) and Geoff McFadden’s lab (School of BioSciences, University of Melbourne, Australia) for mosquito rearing and infection with Plasmodium parasites, Helena Pinheiro (iMM-JLA, Portugal) for assistance with graphical design, Inês Bento and Miguel Prudêncio for critically reviewing this manuscript, and the Flow Cytometry and Rodent Facilities teams (iMM-JLA, Portugal) for their assistance. Work at iMM-JLA was supported by Fundação para a Ciência e a Tecnologia. Portugal (PTDC/MED-IMU/28664/2017) and the “La caixa” Banking Foundation, Spain (HR17-00264-PoEMM) grants attributed to Â.F.C. and M.M.M., respectively. Work at the Department of Microbiology and Immunology, The University of Melbourne, Australia, was funded by the National Health and Medical Research Council, Australia (1113293, 1154457) and the Australian Research Council, Australia (CE140100011). Â.F.C., S.M., J.L.G., M.I.M., R.M.R., and K.S. were supported by Fundação para a Ciência e a Tecnologia, Portugal (DL57/2016/CP1451/CT0004, DL57/2016/CP1451/CT0010, PD/BD/139053/2018, PD/BD/135454/2017, PTDC/MAT-APL/31602/2017, and CEECIND/00697/2018, respectively), P.L. was supported by Conselho Nacional de Desenvolvimento Científico e Tenológico, Brazil (SN/CGEFO/CNPQ 201801/2015-9), and A.T.T. was supported in part by Alfred P. Sloan Foundation Fellowship (FG-2020-12949).info:eu-repo/semantics/publishedVersio

Mobile sink based fault diagnosis scheme for wireless sensor networks

Network diagnosis in Wireless Sensor Networks (WSNs) is a difficult task due to their improvisational nature, invisibility of internal running status, and particularly since the network structure can frequently change due to link failure. To solve this problem, we propose a Mobile Sink (MS) based distributed fault diagnosis algorithm for WSNs. An MS, or mobile fault detector is usually a mobile robot or vehicle equipped with a wireless transceiver that performs the task of a mobile base station while also diagnosing the hardware and software status of deployed network sensors. Our MS mobile fault detector moves through the network area polling each static sensor node to diagnose the hardware and software status of nearby sensor nodes using only single hop communication. Therefore, the fault detection accuracy and functionality of the network is significantly increased. In order to maintain an excellent Quality of Service (QoS), we employ an optimal fault diagnosis tour planning algorithm. In addition to saving energy and time, the tour planning algorithm excludes faulty sensor nodes from the next diagnosis tour. We demonstrate the effectiveness of the proposed algorithms through simulation and real life experimental results