Getting in the flow: adolescent test-takers, motivation, and optimal performance

Experimental results demonstrate bow small differences in depth and water regime have a significant affect on the accumulation and allocation of nutrients and biomass. Because the performance of aquatic plants depends on these factors, an understanding of their influence is essential to ensure that systems function at their full potential. The responses differed for two emergent species, indicating that within this morphological category, optimal performance will fall at different locations across a depth or water regime gradient. The performance of one species was unaffected by growth in mixture, whereas the other performed better in deep water and worse in shallow.

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New directions in the psychology of optimal performance in sport: flow and clutch states

Current Opinion in Psychology ◽

10.1016/j.copsyc.2017.03.032 ◽

2017 ◽

Vol 16 ◽

pp. 48-53 ◽

Cited By ~ 16

Author(s):

Christian Swann ◽

Lee Crust ◽

Stewart A. Vella

Keyword(s):

Optimal Performance ◽

New Directions

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Optimal control of chilled water systems based on collaboration of the equipment's near-optimal performance maps

Sustainable Energy Technologies and Assessments ◽

10.1016/j.seta.2021.101236 ◽

2021 ◽

Vol 46 ◽

pp. 101236

Author(s):

Wantao Shi ◽

Jiangqing Wang ◽

Yuan Lyu ◽

Xinqiao Jin ◽

Zhimin Du

Keyword(s):

Optimal Control ◽

Water Systems ◽

Optimal Performance ◽

Chilled Water

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Reply to Comment on “Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest”

Remote Sensing ◽

10.3390/rs13051028 ◽

2021 ◽

Vol 13 (5) ◽

pp. 1028

Author(s):

Alber Hamersson Sanchez ◽

Michelle Cristina A. Picoli ◽

Gilberto Camara ◽

Pedro R. Andrade ◽

Michel Eustaquio D. Chaves ◽

...

Keyword(s):

Tropical Forest ◽

Cloud Cover ◽

Optimal Performance ◽

Detection Algorithms ◽

Sentinel 2

In their comments about our paper, the authors remark on two issues regarding our results relating to the MACCS-ATCOR Joint Algorithm (MAJA). The first relates to the sub-optimal performance of this algorithm under the conditions of our tests, while the second corresponds to an error in our interpretation of MAJA’s bit mask. To answer the first issue, we acknowledge MAJA’s capacity to improve its performance as the number of images increases with time. However, in our paper, we used the images we had available at the time we wrote our paper. Regarding the second issue, we misread the MAJA’s bit mask and mistakenly labelled shadows as clouds. We regret our error and here we present the updated tables and images. We corrected our estimation and, consequently, there is an increment in MAJA’s accuracy in the detection of clouds and cloud shadows. However, these increments are not enough to change the conclusion of our original paper.

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Design and Experimental Study of the General Mechanical Pneumatic Combined Seed Metering Device

Applied Sciences ◽

10.3390/app11167223 ◽

2021 ◽

Vol 11 (16) ◽

pp. 7223

Author(s):

Dengyu Xiong ◽

Mingliang Wu ◽

Wei Xie ◽

Rong Liu ◽

Haifeng Luo

Keyword(s):

High Efficiency ◽

Cone Angle ◽

General Purpose ◽

Optimal Performance ◽

Air Velocity ◽

General Properties ◽

Response Surface Optimization ◽

Damage Rate ◽

Air Blowing ◽

Seed Metering Device

To address the problems of high damage rate, low seeding accuracy, and poor seeding generally in the seeding process, a general-purpose seeding device was designed in this study based on the principle of mechanical pneumatic combined seeding. The air-blowing-type cleaning and seed unloading of the device laid the conditions for precise seeding and flexible seeding. In addition, single-factor experiments were performed on seeds (e.g., soybeans, corn, and rape-seeds) with different particle sizes and shapes to verify the general properties of the seed metering device. A multi-factor response surface optimization experiment was performed by applying soybean seeds as the test object to achieve the optimal performance parameters of the seed metering device. At a seed-clearing air velocity of 16.7 m/s, a seed feeding drum speed of 13.7 r/min, and a hole cone angle of 35.6°, corresponding to the optimal performance index, the qualified index, the replay index, and the missed index reached 97.94%, 0.03%, and 2.03%, respectively. The verification test results are consistent with the optimized ones. As indicated from the results, the seed metering device exhibits good general properties, low damage rate, great precision, and high efficiency; it is capable of meeting general seeding operations of different crop seeds and technically supporting for the reliability and versatility of the seeder.

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