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Moura FA, Pelegrinelli ARM, Catelli DS, Kowalski E, Lamontagne M, da Silva Torres R. On the prediction of tibiofemoral contact forces for healthy individuals and osteoarthritis patients during gait: a comparative study of regression methods. Sci Rep 2024; 14:1379. [PMID: 38228640 PMCID: PMC10791669 DOI: 10.1038/s41598-023-50481-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/20/2023] [Indexed: 01/18/2024] Open
Abstract
Knee osteoarthritis (OA) is a public health problem affecting millions of people worldwide. The intensity of the tibiofemoral contact forces is related to cartilage degeneration, and so is the importance of quantifying joint loads during daily activities. Although simulation with musculoskeletal models has been used to calculate joint loads, it demands high-cost equipment and a very time-consuming process. This study aimed to evaluate consolidated machine learning algorithms to predict tibiofemoral forces during gait analysis of healthy individuals and knee OA patients. Also, we evaluated three different datasets to train each model, considering different combinations of primary kinematic and kinetic data, and post-processing data. We evaluated 14 patients with severe unilateral knee OA and 14 healthy individuals during 3-5 gait trials. Data were split into 70% and 30% of the samples as training and test data. Test data was independently evaluated considering a mixture of pathological and healthy individuals, and only OA and Control patients. The main results showed that accurate predictions of the tibiofemoral contact forces were achieved using machine learning methods and that the predictions were sensitive to changes in the input data as training. The present study provided insights into the most promising regressions methods to predict knee contact forces representing an important starting point for the broader application of biomechanical analysis in clinical environments.
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Affiliation(s)
- Felipe Arruda Moura
- Laboratory of Applied Biomechanics, Sport Sciences Department, State University of Londrina, Londrina, Brazil.
- Wageningen Data Competence Center, Wageningen University and Research, Wageningen, The Netherlands.
| | - Alexandre R M Pelegrinelli
- Laboratory of Applied Biomechanics, Sport Sciences Department, State University of Londrina, Londrina, Brazil
- Human Movement Biomechanics Laboratory, University of Ottawa, Ottawa, Canada
| | - Danilo S Catelli
- Human Movement Biomechanics Laboratory, University of Ottawa, Ottawa, Canada
- Department of Movement Sciences, Faculty of Movement and Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Erik Kowalski
- Human Movement Biomechanics Laboratory, University of Ottawa, Ottawa, Canada
| | - Mario Lamontagne
- Human Movement Biomechanics Laboratory, University of Ottawa, Ottawa, Canada
| | - Ricardo da Silva Torres
- Wageningen Data Competence Center, Wageningen University and Research, Wageningen, The Netherlands.
- Department of ICT and Natural Sciences, NTNU-Norwegian University of Science and Technology, Ålesund, Norway.
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Caetano FG, Santiago PRP, da Silva Torres R, Cunha SA, Moura FA. Interpersonal coordination of opposing player dyads during attacks performed in official football matches. Sports Biomech 2023:1-16. [PMID: 37211810 DOI: 10.1080/14763141.2023.2212664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
The purpose of this study was to characterise the interpersonal coordination between opponent players during offensive sequences in official matches and to verify if offensive sequences ended in shots to goal present different coordination patterns when compared than those that ended in defensive tackles. A total of 580 offensive sequences occurred during matches resulting in shots to goal (n = 172) or defensive tackles (n = 408) were analysed. The bidimensional coordinates and technical actions of male professional football players (n = 1160) were obtained using a video-based tracking system. Dyads were defined using a network analysis and composed of the nearest opponent. Interpersonal coordination of the dyads was analysed using the vector coding and the frequency for each coordination pattern was computed. In-phase was predominant for all displacement directions and offensive sequences outcomes, and antiphase was the least frequent. For lateral displacements, offensive sequences ending in shot to goal presented lower frequency for in-phase and higher frequency for offensive player phase than ended in defensive tackle. This information about the relationship of opponent players dyads during decisive moments of the matches provides fundamentals for future research and assists coaches to understand the different behaviours in successful and unsuccessful attacks.
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Affiliation(s)
| | | | - Ricardo da Silva Torres
- Department of ICT and Natural Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | | | - Felipe Arruda Moura
- Department of Sport Sciences, State University of Londrina, Londrina, Brazil
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Frade MCM, Beltrame T, Gois MDO, Pinto A, Tonello SCGDM, Torres RDS, Catai AM. Toward characterizing cardiovascular fitness using machine learning based on unobtrusive data. PLoS One 2023; 18:e0282398. [PMID: 36862737 PMCID: PMC9980797 DOI: 10.1371/journal.pone.0282398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 02/14/2023] [Indexed: 03/03/2023] Open
Abstract
Cardiopulmonary exercise testing (CPET) is a non-invasive approach to measure the maximum oxygen uptake ([Formula: see text]), which is an index to assess cardiovascular fitness (CF). However, CPET is not available to all populations and cannot be obtained continuously. Thus, wearable sensors are associated with machine learning (ML) algorithms to investigate CF. Therefore, this study aimed to predict CF by using ML algorithms using data obtained by wearable technologies. For this purpose, 43 volunteers with different levels of aerobic power, who wore a wearable device to collect unobtrusive data for 7 days, were evaluated by CPET. Eleven inputs (sex, age, weight, height, and body mass index, breathing rate, minute ventilation, total hip acceleration, walking cadence, heart rate, and tidal volume) were used to predict the [Formula: see text] by support vector regression (SVR). Afterward, the SHapley Additive exPlanations (SHAP) method was used to explain their results. SVR was able to predict the CF, and the SHAP method showed that the inputs related to hemodynamic and anthropometric domains were the most important ones to predict the CF. Therefore, we conclude that the cardiovascular fitness can be predicted by wearable technologies associated with machine learning during unsupervised activities of daily living.
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Affiliation(s)
| | - Thomas Beltrame
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo, Brazil
- Samsung R&D Institute Brazil–SRBR, Campinas, São Paulo, Brazil
- * E-mail:
| | | | - Allan Pinto
- Brazilian Synchrotron Light Laboratory (LNLS), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, São Paulo, Brazil
| | | | - Ricardo da Silva Torres
- Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, NTNU—Norwegian University of Science and Technology, Ålesund, Norway
| | - Aparecida Maria Catai
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo, Brazil
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Stival L, Pinto A, de Andrade FDSP, Santiago PRP, Biermann H, Torres RDS, Dias U. Using machine learning pipeline to predict entry into the attack zone in football. PLoS One 2023; 18:e0265372. [PMID: 36652409 PMCID: PMC9847968 DOI: 10.1371/journal.pone.0265372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 12/01/2022] [Indexed: 01/19/2023] Open
Abstract
Sports sciences are increasingly data-intensive nowadays since computational tools can extract information from large amounts of data and derive insights from athlete performances during the competition. This paper addresses a performance prediction problem in soccer, a popular collective sport modality played by two teams competing against each other in the same field. In a soccer game, teams score points by placing the ball into the opponent's goal and the winner is the team with the highest count of goals. Retaining possession of the ball is one key to success, but it is not enough since a team needs to score to achieve victory, which requires an offensive toward the opponent's goal. The focus of this work is to determine if analyzing the first five seconds after the control of the ball is taken by one of the teams provides enough information to determine whether the ball will reach the final quarter of the soccer field, therefore creating a goal-scoring chance. By doing so, we can further investigate which conditions increase strategic leverage. Our approach comprises modeling players' interactions as graph structures and extracting metrics from these structures. These metrics, when combined, form time series that we encode in two-dimensional representations of visual rhythms, allowing feature extraction through deep convolutional networks, coupled with a classifier to predict the outcome (whether the final quarter of the field is reached). The results indicate that offensive play near the adversary penalty area can be predicted by looking at the first five seconds. Finally, the explainability of our models reveals the main metrics along with its contributions for the final inference result, which corroborates other studies found in the literature for soccer match analysis.
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Affiliation(s)
- Leandro Stival
- School of Technology, University of Campinas, Limeira, São Paulo, Brazil
| | - Allan Pinto
- Brazilian Synchrotron Light Laboratory (LNLS), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, São Paulo, Brazil
| | | | - Paulo Roberto Pereira Santiago
- School of Physical Education and Sport of Ribeirão Preto, University of São Paulo (USP), Ribeirão Preto, São Paulo, Brazil
| | - Henrik Biermann
- Institute of Exercise Training and Sport Informatics, German Sport, University Cologne, Cologne, Germany
| | - Ricardo da Silva Torres
- Department of ICT and Natural Sciences, NTNU—Norwegian University of Science and Technology, Aalesund, Norway
| | - Ulisses Dias
- School of Technology, University of Campinas, Limeira, São Paulo, Brazil
- * E-mail:
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Monteiro RLM, Bedo BLS, Monteiro PHM, de Andrade FDSP, Moura FA, Cunha SA, Torres RDS, Memmert D, Santiago PRP. Penalty feet positioning rule modification and laterality effect on soccer goalkeepers' diving kinematics. Sci Rep 2022; 12:18493. [PMID: 36323704 PMCID: PMC9630263 DOI: 10.1038/s41598-022-21508-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 09/28/2022] [Indexed: 11/23/2022] Open
Abstract
In 2019, a new rule was applied in soccer. It allows the goalkeeper to have only one foot or part of it on the goal line when the kicker hits the ball, unlike the previous rule that determined the goalkeeper should have both feet on the line. The purpose of the present study was to analyze how the change in the rule and the lower limbs laterality influences on the diving save kinematic performance in penalties. Six goalkeepers, two professionals and four amateurs, performed a total of 20 dives in the laboratory and had their force and impulse exerted by the lower limb and displacement/velocity data from the center of body mass collected through force plates and kinematic analysis. The side preference was collected through an inventory. The results showed that goalkeepers dive further (p < 0.001) and faster (p < 0.001) when diving according to the new rule. Dives for the non-dominant side presented higher values than the trials for the dominant side in mediolateral (p = 0.02) and resultant (p = 0.03) displacements. Concluding, the goalkeepers performed better with the new rule in the analyzed variables and the lower limb preference has influenced only the mediolateral and resultant displacement.
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Affiliation(s)
- Rafael Luiz Martins Monteiro
- grid.11899.380000 0004 1937 0722Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo (USP), Ribeirão Preto, 14040-907 Brazil ,grid.11899.380000 0004 1937 0722Program in Rehabilitation and Functional Performance, Ribeirão Preto Medical School, University of São Paulo (USP), Ribeirão Preto, 14049-900 Brazil
| | - Bruno Luiz Souza Bedo
- grid.11899.380000 0004 1937 0722School of Physical Education and Sport, University of São Paulo (USP), São Paulo, 05508-030 Brazil
| | - Pedro Henrique Martins Monteiro
- grid.11899.380000 0004 1937 0722School of Physical Education and Sport, University of São Paulo (USP), São Paulo, 05508-030 Brazil
| | - Felipe dos Santos Pinto de Andrade
- grid.11899.380000 0004 1937 0722Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo (USP), Ribeirão Preto, 14040-907 Brazil
| | - Felipe Arruda Moura
- grid.411400.00000 0001 2193 3537Laboratory of Applied Biomechanics, Department of Sport Sciences, Centre of Physical Education and Sport, State University of Londrina, Londrina, 86057‑970 Brazil
| | - Sergio Augusto Cunha
- grid.411087.b0000 0001 0723 2494Department of Sport Sciences, University of Campinas, Campinas, Brazil
| | - Ricardo da Silva Torres
- grid.5947.f0000 0001 1516 2393Department of ICT and Natural Sciences, NTNU – Norwegian University of Science and Technology, Aalesund, Norway
| | - Daniel Memmert
- grid.27593.3a0000 0001 2244 5164Institute of Exercise Training and Sport Informatics, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany
| | - Paulo Roberto Pereira Santiago
- grid.11899.380000 0004 1937 0722Biomechanics and Motor Control Laboratory, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo (USP), Ribeirão Preto, 14040-907 Brazil ,grid.11899.380000 0004 1937 0722Program in Rehabilitation and Functional Performance, Ribeirão Preto Medical School, University of São Paulo (USP), Ribeirão Preto, 14049-900 Brazil
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Bueno MJDO, Silva M, Cunha SA, Torres RDS, Moura FA. Multiscale fractal dimension applied to tactical analysis in football: A novel approach to evaluate the shapes of team organization on the pitch. PLoS One 2021; 16:e0256771. [PMID: 34469462 PMCID: PMC8409646 DOI: 10.1371/journal.pone.0256771] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 08/14/2021] [Indexed: 11/19/2022] Open
Abstract
The aim of this study was to evaluate different shape descriptors applied to images of polygons that represent the organization of football teams on the pitch. The effectiveness of different shape descriptors (area/perimeter, fractal area, circularity, maximum fractal, rectangularity, multiscale fractal curve—MFC), and the concatenation of all shape descriptors (except MFC), denominated Alldescriptors (AllD)) was evaluated and applied to polygons corresponding to the shapes represented by the convex hull obtained from players’ 2D coordinates. A content-based image retrieval system (CBIR) was applied for 25 users (mean age of 31.9 ± 8.4 years) to evaluate the relevant images. Measures of effectiveness were used to evaluate the shape descriptors (P@n and R@n). The MFD (P@5, 0.46±0.37 and P@10, 0.40±0.31, p < 0.001; R@5, 0.14±0.13 and R@10, 0.24±0.19, p < 0.001) and AllD (P@5 = 0.43±0.36 and P@10 = 0.39±0.32, p < 0.001; R@5 = 0.13±0.11 and R@10 = 0.24±0.20, p < 0.001) descriptors presented higher values of effectiveness. As a practical demonstration, the best evaluated shape descriptor (MFC) was applied for tactical analysis of an official match. K-means clustering technique was applied, and different shapes of organization could be identified throughout the match. The MFC was the most effective shape descriptor in relation to all others, making it possible to apply this descriptor in the analysis of professional football matches.
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Affiliation(s)
| | - Maisa Silva
- Institute of Computing, University of Campinas, Campinas, Brazil
| | | | - Ricardo da Silva Torres
- Department of ICT and Natural Sciences, NTNU—Norwegian University of Science and Technology, Ålesund, Norway
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Rossanez A, Dos Reis JC, Torres RDS, de Ribaupierre H. KGen: a knowledge graph generator from biomedical scientific literature. BMC Med Inform Decis Mak 2020; 20:314. [PMID: 33317512 PMCID: PMC7734730 DOI: 10.1186/s12911-020-01341-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 11/17/2020] [Indexed: 11/26/2022] Open
Abstract
Background Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational help. For example, Alzheimer’s Disease, a life-threatening degenerative disease that is not yet curable. As the scientific community strives to better understand it and find a cure, great amounts of data have been generated, and new knowledge can be produced. A proper representation of such knowledge brings great benefits to researchers, to the scientific community, and consequently, to society. Methods In this article, we study and evaluate a semi-automatic method that generates knowledge graphs (KGs) from biomedical texts in the scientific literature. Our solution explores natural language processing techniques with the aim of extracting and representing scientific literature knowledge encoded in KGs. Our method links entities and relations represented in KGs to concepts from existing biomedical ontologies available on the Web. We demonstrate the effectiveness of our method by generating KGs from unstructured texts obtained from a set of abstracts taken from scientific papers on the Alzheimer’s Disease. We involve physicians to compare our extracted triples from their manual extraction via their analysis of the abstracts. The evaluation further concerned a qualitative analysis by the physicians of the generated KGs with our software tool. Results The experimental results indicate the quality of the generated KGs. The proposed method extracts a great amount of triples, showing the effectiveness of our rule-based method employed in the identification of relations in texts. In addition, ontology links are successfully obtained, which demonstrates the effectiveness of the ontology linking method proposed in this investigation. Conclusions We demonstrate that our proposal is effective on building ontology-linked KGs representing the knowledge obtained from biomedical scientific texts. Such representation can add value to the research in various domains, enabling researchers to compare the occurrence of concepts from different studies. The KGs generated may pave the way to potential proposal of new theories based on data analysis to advance the state of the art in their research domains.
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Affiliation(s)
- Anderson Rossanez
- Institute of Computing, University of Campinas, Campinas, SP, Brazil.
| | | | - Ricardo da Silva Torres
- Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, NTNU - Norwegian University of Science and Technology, Ålesund, Norway
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Beltrame T, Gois MO, Hoffmann U, Koschate J, Hughson RL, Moraes Frade MC, Linares SN, da Silva Torres R, Catai AM. Relationship between maximal aerobic power with aerobic fitness as a function of signal-to-noise ratio. J Appl Physiol (1985) 2020; 129:522-532. [PMID: 32730176 DOI: 10.1152/japplphysiol.00310.2020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Efforts to better understand cardiorespiratory health are relevant for the future development of optimized physical activity programs. We aimed to explore the impact of the signal quality on the expected associations between the ability of the aerobic system in supplying energy as fast as possible during moderate exercise transitions with its maximum capacity to supply energy during maximal exertion. It was hypothesized that a slower aerobic system response during moderate exercise transitions is associated with a lower maximal aerobic power; however, this relationship relies on the quality of the oxygen uptake data set. Forty-three apparently healthy participants performed a moderate constant work rate (CWR) followed by a pseudorandom binary sequence (PRBS) exercise protocol on a cycle ergometer. Participants also performed a maximum incremental cardiopulmonary exercise testing (CPET). The maximal aerobic power was evaluated by the peak oxygen uptake during the CPET, and the aerobic fitness was estimated from different approaches for oxygen uptake dynamics analysis during the CWR and PRBS protocols at different levels of signal-to-noise ratio. The product moment correlation coefficient was used to evaluate the correlation level between variables. Aerobic fitness was correlated with maximum aerobic power, but this correlation increased as a function of the signal-to-noise ratio. Aerobic fitness is related to maximal aerobic power; however, this association appeared to be highly dependent on the data quality and analysis for aerobic fitness evaluation. Our results show that simpler moderate exercise protocols might be as good as maximal exertion exercise protocols to obtain indexes related to cardiorespiratory health.NEW & NOTEWORTHY Optimized methods for cardiorespiratory health evaluation are of great interest for public health. Moderate exercise protocols might be as good as maximum exertion exercise protocols to evaluate cardiorespiratory health. Pseudorandom or constant workload moderate exercise can be used to evaluate cardiorespiratory health.
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Affiliation(s)
- Thomas Beltrame
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo, Brazil.,Universidade Ibirapuera, São Paulo, São Paulo, Brazil
| | - Mariana Oliveira Gois
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo, Brazil
| | - Uwe Hoffmann
- German Sport University Cologne, Cologne, Germany
| | - Jessica Koschate
- Geriatric Medicine, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| | - Richard Lee Hughson
- University of Waterloo, Schlegel-University of Waterloo Research Institute for Aging, Waterloo, Ontario, Canada
| | | | | | - Ricardo da Silva Torres
- Department of Information and Communications Technology (ICT) and Natural Sciences, Faculty of Information Technology and Electrical Engineering, NTNU-Norwegian University of Science and Technology, Ålesund, Norway
| | - Aparecida Maria Catai
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo, Brazil
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Merlin M, Cunha SA, Moura FA, Torres RDS, Gonçalves B, Sampaio J. Exploring the determinants of success in different clusters of ball possession sequences in soccer. Res Sports Med 2020; 28:339-350. [DOI: 10.1080/15438627.2020.1716228] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Murilo Merlin
- School of Physical Education, University of Campinas, Campinas, Brazil
| | | | - Felipe Arruda Moura
- Laboratory of Applied Biomechanics, State University of Londrina, Londrina, Brazil
| | - Ricardo da Silva Torres
- Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, NTNU – Norwegian University of Science and Technology, Ålesund, Norway
| | - Bruno Gonçalves
- Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), CreativeLab Research Community, University of Tras-os-Montes and Alto Douro, Vila Real, Portugal
- Portugal Football School, Portuguese Football Federation, Oeiras, Portugal
| | - Jaime Sampaio
- Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), CreativeLab Research Community, University of Tras-os-Montes and Alto Douro, Vila Real, Portugal
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Ribeiro RV, Torres RDS. Sentinel plants as programmable processing units: insights from a multidisciplinary perspective about stress memory and plant signaling and their relevance at community level. Plant Signal Behav 2018; 13:e1526001. [PMID: 30260272 PMCID: PMC6204832 DOI: 10.1080/15592324.2018.1526001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 08/30/2018] [Accepted: 09/06/2018] [Indexed: 06/08/2023]
Abstract
Stress memory and an effective signaling among individuals in a given community are recognized to improve plant performance under recurrent stressful conditions. As living beings with memory and signaling abilities, plants can be considered as processing units and then be trained - or programmable from a computational viewpoint - and prepared for facing biotic and abiotic stresses. Here, we propose that sentinel plants could improve the resilience of agricultural and natural communities by reducing the impact of biotic or abiotic stressors on their neighbors. Modeling plants as programmable (or trainable) processing units compels us to think about a multidisciplinary perspective for integrating stress memory, signaling, and resilience of biological systems into executable programs, fostering the creation of applications and technologies that would benefit from the spatiotemporal dynamics related to plant-plant and plant-environment interactions.
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Affiliation(s)
- Rafael V. Ribeiro
- Department of Plant Biology, Institute of Biology, University of Campinas, Campinas SP, Brazil
| | - Ricardo da Silva Torres
- Department of Information Systems, Institute of Computing, University of Campinas, Campinas SP, Brazil
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dos Santos JM, de Moura ES, da Silva AS, Cavalcanti JMB, Torres RDS, Vidal MLA. A signature-based bag of visual words method for image indexing and search. Pattern Recognit Lett 2015. [DOI: 10.1016/j.patrec.2015.06.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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