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PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262245
Author(s):  
Diogo Coutinho ◽  
Bruno Gonçalves ◽  
Hugo Folgado ◽  
Bruno Travassos ◽  
Sara Santos ◽  
...  

This study explored how manipulating the colour of training vests affects footballers’ individual and collective performance during a Gk+6vs6+Gk medium-sided game. A total of 21 under-17 years old players were involved in three experimental conditions in a random order for a total of four days: i) CONTROL, two teams using two different colour vests; ii) SAME, both teams wearing blue vests; iii) MIXED, all 6 players per team wore different colour vests. Players’ positional data was used to compute time-motion and tactical-related variables, while video analysis was used to collect technical variables. Further, these variables were synchronized with spatiotemporal data allowing to capture ball-related actions in a horizontal 2D plan. All variables were analysed from the offensive and defensive perspective. From the offensive perspective, players performed more and further shots to goal during the CONTROL than in SAME and MIXED (small effects) conditions, with a decreased distance to the nearest defender (small effects). While defending, results revealed lower distance to the nearest teammate (small effects) in the CONTROL than in the SAME and MIXED conditions, and higher team longitudinal synchronization (small effects). In addition, the CONTROL showed in general lower values of team width while defending than in the other 2 conditions. Overall, coaches may use the CONTROL condition to emphasize offensive performance and defensive behaviour over the longitudinal direction with increased physical demands. In turn, coaches may use the manipulation of players vests to emphasize defensive performance, as players seem to behave more cohesively under such scenarios.


Insects ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 3
Author(s):  
Joydeep De ◽  
Abhishek Chatterjee

We create mental maps of the space that surrounds us; our brains also compute time—in particular, the time of day. Visual, thermal, social, and other cues tune the clock-like timekeeper. Consequently, the internal clock synchronizes with the external day-night cycles. In fact, daylength itself varies, causing the change of seasons and forcing our brain clock to accommodate layers of plasticity. However, the core of the clock, i.e., its molecular underpinnings, are highly resistant to perturbations, while the way animals adapt to the daily and annual time shows tremendous biological diversity. How can this be achieved? In this review, we will focus on 75 pairs of clock neurons in the Drosophila brain to understand how a small neural network perceives and responds to the time of the day, and the time of the year.


2021 ◽  
Vol 894 (1) ◽  
pp. 012033
Author(s):  
F M Syahputra ◽  
M A Azizi ◽  
I Marwanza

Abstract Nickel ore mines have a high potential of landslides due to their weak material base, which consists of soil. It is caused by the increase of soil density in rain conditions, leading to decreased soil shear strength (c) and internal friction angle (ϕ). This research aims to determine the optimum value of the maximum iteration number based on the Cuckoo Search and Particle Swarm Optimization search method. In this research, the slope is analyzed using the 3 Dimensional limit equilibrium method “Simplified Bishop,” a slope stability analysis method that uses the principle of static equilibrium. Alongside this method, the Cuckoo Search and Particle Swarm Optimization is adopted. The Cuckoo Search and Particle Swarm Optimization are metaheuristic optimization techniques used as the slipped surface search method. Series of 3-dimensional limit equilibrium computation is performed using different amounts of nests in the cuckoo search method and different particle values and maximum iteration number. Cuckoo Search method to achieve optimal nest 100 and iteration of 80 with the fastest compute time of 3 minutes 49 seconds. While the Particle Swarm Optimization to achieve optimal on particles 60, iteration as much as 480 with a compute time of 6 minutes 46 second, with a factor of safety value of 1,12.


2021 ◽  
Author(s):  
Hans Müller Paul ◽  
Dave D Istanto ◽  
Jacob Heldenbrand ◽  
Matthew Hudson

Abstract Background: CRISPR/Cas9 technology has become an important tool to generate targeted, highly specific genome mutations. The technology has great potential for crop improvement, as crop genomes are tailored to optimize specific traits over generations of breeding. Many crops have highly complex and polyploid genomes, particularly those used for bioenergy or bioproducts. The majority of tools currently available for designing and evaluating gRNAs for CRISPR experiments were developed based on mammalian genomes that do not share the characteristics or design criteria for crop genomes. Results: We have developed the first open source tool for genome-wide design and evaluation of gRNA sequences for CRISPR experiments, CROPSR. The genome-wide approach provides a significant decrease in the time required to design a CRISPR experiment, including validation through PCR, at the expense of an overhead compute time required once per genome, at the first run. To better cater to the needs of crop geneticists, restrictions imposed by other packages on design and evaluation of gRNA sequences were lifted. A new machine learning model was developed to provide scores while avoiding situations in which the currently available tools sometimes failed to provide guides for repetitive, A/T-rich genomic regions. We show that our gRNA scoring model provides a significant increase in prediction accuracy over existing tools, even in non-crop genomes. Conclusions: CROPSR provides the scientific community with new methods and a new workflow for performing CRISPR/Cas9 knockout experiments. CROPSR reduces the challenges of working in crops, and helps speed gRNA sequence design, evaluation and validation. We hope that the new software will accelerate discovery and reduce the number of failed experiments.


2021 ◽  
Vol 18 (1) ◽  
pp. 22-30
Author(s):  
Erna Nurmawati ◽  
Robby Hasan Pangaribuan ◽  
Ibnu Santoso

One way to deal with the presence of missing value or incomplete data is to impute the data using EM Algorithm. The need for large and fast data processing is necessary to implement parallel computing on EM algorithm serial program. In the parallel program architecture of EM Algorithm in this study, the controller is only related to the EM module whereas the EM module itself uses matrix and vector modules intensively. Parallelization is done by using OpenMP in EM modules which results in faster compute time on parallel programs than serial programs. Parallel computing with a thread of 4 (four) increases speed up, reduces compute time, and reduces efficiency when compared to parallel computing by the number of threads 2 (two).


Author(s):  
Diogo Coutinho ◽  
Bruno Gonçalves ◽  
Sara Santos ◽  
Bruno Travassos ◽  
Hugo Folgado ◽  
...  

This study explored how the number of allowed ball touches per player possession affected the performance of different age groups (U9, U11, U13, U15, U17 and U19) during a Gk + 4vs4+Gk small-sided games. Each day, players randomly performed the following three conditions (for a total of 6 days): i) free-play (FP); ii) maximum of 2 touches (2 T); iii) 1 touch (1 T). Players’ positional data was used to compute time-motion and positional-related variables, while video analysis was used to capture technical performance. In general, no effects were identified in relation to the players distances (team centroid, opponents’ centroid, nearest teammate, and nearest opponent). There were small to moderate decreases in the longitudinal synchronization while playing with 1 T and 2 T in the U9 and U17, but a moderate increase in the U15. There was a general decrease in the distance covered and distance covered while running (small to moderate effects) when playing with limited touches in all age groups. Limiting the touches promoted small to moderate increases in the number of successful passes in the U9, U15, and U17 and a general increase in unsuccessful actions. Overall, playing with limited touches emphasized the passing skill while it also contributed to more unsuccessful actions and lower physical demands. As so, coaches may use the 2 T in young age groups (U9-U13) as they seem less able to successfully cope with 1 T, while using 1 T in older age groups due to their higher ability to interact with environmental information.


2021 ◽  
Author(s):  
Albert Dominguez Mantes ◽  
Daniel Mas Montserrat ◽  
Carlos Bustamante ◽  
Xavier Giró-i-Nietó ◽  
Alexander G Ioannidis

Characterizing the genetic substructure of large cohorts has become increasingly important as genetic association and prediction studies are extended to massive, increasingly diverse, biobanks. ADMIXTURE and STRUCTURE are widely used unsupervised clustering algorithms for characterizing such ancestral genetic structure. These methods decompose individual genomes into fractional cluster assignments with each cluster representing a vector of DNA marker frequencies. The assignments, and clusters, provide an interpretable representation for geneticists to describe population substructure at the sample level. However, with the rapidly increasing size of population biobanks and the growing numbers of variants genotyped (or sequenced) per sample, such traditional methods become computationally intractable. Furthermore, multiple runs with different hyperparameters are required to properly depict the population clustering using these traditional methods, increasing the computational burden. This can lead to days of compute. In this work we present Neural ADMIXTURE, a neural network autoencoder that follows the same modeling assumptions as ADMIXTURE, providing similar (or better) clustering, while reducing the compute time by orders of magnitude. In addition, this network can include multiple outputs, providing the equivalent results as running the original ADMIXTURE algorithm many times with different numbers of clusters. These models can also be stored, allowing later cluster assignment to be performed with a linear computational time.


Author(s):  
Gangadhara Rao Kommu

TeraSort is one of Hadoop’s widely used benchmarks. Hadoop’s distribution contains both the input generator and sorting implementations: the TeraGen generates the input and TeraSort conducts the sorting. We focus on the comparison of TeraSort algorithm on the different distributed platforms with different configurations of the resources. We have considered the parameters of measure of efficiency as Compute Time, Data Read, Data Write, Compute Time, and Speedup. We have conducted experiments using Hadoop map reduce and Spark (Java). We empirically evaluate the performance of TeraSort algorithm on Amazon EC2 Machine Images, and demonstrate that it achieves 3.95 × - 2.4 × speedup, compared with TeraSort, for typical settings of interest.


2021 ◽  
Author(s):  
Lubomir Jirasek

A two-step partitioning algorithm for FE meshes is proposed in this work for the purposes of time savings. A direct method based on the concept of 'separateness' was applied first, followed by a partition optimization process that used a Genetic Algorithm (GA). A total of 9 applications were evaluated to demonstrate the durability, versatility, and effectiveness of this partitioning algorithm with respect to interface node count and subdomain load balance. Beyond this wingbox optimization problem was performed on a single processor using a GA to demonstrate the possible time savings of the method. With a 30% decrease in compute time witnessed, it can be said with confidence that the propose partitioning algorithm was a success.


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