scholarly journals The Polarization-Index: A Simple Calculation to Distinguish Polarized From Non-polarized Training Intensity Distributions

2019 ◽  
Vol 10 ◽  
Author(s):  
Gunnar Treff ◽  
Kay Winkert ◽  
Mahdi Sareban ◽  
Jürgen M. Steinacker ◽  
Billy Sperlich
Keyword(s):  
Simple Calculation ◽  
Training Intensity ◽  
Polarization Index

A Simple Calculation Method of Flashover Characteristics for Long Air Gaps under Various Discharge Conditions

1993 ◽  
Vol 113 (3) ◽  
pp. 252-258
Author(s):  
Kiyoto Nishijima ◽  
Itaru Tsuneyasu ◽  
Hiraku Nakahodo ◽  
Masaharu Minakami
Keyword(s):  
Calculation Method ◽  
Simple Calculation ◽  
Air Gaps

scholarly journals Author Correction: The effect of training intensity on implicit learning rates in schizophrenia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Natasza D. Orlov ◽  
Jessica Sanderson ◽  
Syed Ali Muqtadir ◽  
Anastasia K. Kalpakidou ◽  
Panayiota G. Michalopoulou ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Training Intensity ◽  
Learning Rates

scholarly journals Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 905
Author(s):  
Naseem Akhtar ◽  
Muhammad Izzuddin Syakir Ishak ◽  
Mardiana Idayu Ahmad ◽  
Khalid Umar ◽  
Mohamad Shaiful Md Yusuff ◽  
...  
Keyword(s):  
Water Quality ◽  
Decision Making ◽  
Water Quality Index ◽  
Quality Index ◽  
Water Quality Assessment ◽  
Simple Calculation ◽  
Great Accuracy ◽  
Parameter Selection ◽  
Human Consumption ◽  
Multi Criteria Decision Making

Human activities continue to affect our water quality; it remains a major problem worldwide (particularly concerning freshwater and human consumption). A critical water quality index (WQI) method has been used to determine the overall water quality status of surface water and groundwater systems globally since the 1960s. WQI follows four steps: parameter selection, sub-indices, establishing weights, and final index aggregation, which are addressed in this review. However, the WQI method is a prolonged process and applied to specific water quality parameters, i.e., water consumption (particular area and time) and other purposes. Therefore, this review discusses the WQI method in simple steps, for water quality assessment, based on two multi-criteria decision-making (MCDM) methods: (1) analytical hierarchical process (AHP); and (2) measuring attractiveness by a categorically based evaluation technique (MACBETH). MCDM methods can facilitate easy calculations, with less effort and great accuracy. Moreover, the uncertainty and eclipsing problems are also discussed—a challenge at every step of WQI development, particularly for parameter selection and establishing weights. This review will help provide water management authorities with useful knowledge pertaining to water usage or modification of existing indicators globally, and contribute to future WQI planning and studies for drinking, irrigation, domestic, and industrial purposes.

scholarly journals Monitoring Training and Recovery during a Period of Increased Intensity or Volume in Recreational Endurance Athletes

2021 ◽  
Vol 18 (5) ◽  
pp. 2401
Author(s):  
Olli-Pekka Nuuttila ◽  
Ari Nummela ◽  
Keijo Häkkinen ◽  
Santtu Seipäjärvi ◽  
Heikki Kyröläinen
Keyword(s):  
Heart Rate ◽  
Control Period ◽  
Endurance Performance ◽  
Training Period ◽  
Training Intensity ◽  
Countermovement Jump ◽  
Maximal Speed ◽  
Individualized Approach ◽  
Monitoring Training

The purpose of the study was to examine the effects of progressively increased training intensity or volume on the nocturnal heart rate (HR) and heart rate variability (HRV), countermovement jump, perceived recovery, and heart rate-running speed index (HR-RS index). Another aim was to analyze how observed patterns during the training period in these monitoring variables were associated with the changes in endurance performance. Thirty recreationally trained participants performed a 10-week control period of regular training and a 10-week training period of either increased training intensity (INT, n = 13) or volume (VOL, n = 17). Changes in endurance performance were assessed by an incremental treadmill test. Both groups improved their maximal speed on the treadmill (INT 3.4 ± 3.2%, p < 0.001; VOL 2.1 ± 1.8%, p = 0.006). In the monitoring variables, only between-group difference (p = 0.013) was found in nocturnal HR, which decreased in INT (p = 0.016). In addition, perceived recovery decreased in VOL (p = 0.021) and tended to decrease in INT (p = 0.056). When all participants were divided into low-responders and responders in maximal running performance, the increase in the HR-RS index at the end of the training period was greater in responders (p = 0.005). In conclusion, current training periods of increased intensity or volume improved endurance performance to a similar extent. Countermovement jump and HRV remained unaffected, despite a slight decrease in perceived recovery. Long-term monitoring of the HR-RS index may help to predict positive adaptations, while interpretation of other recovery-related markers may need a more individualized approach.

scholarly journals Functional Translation of Exercise Responses from Exercise Testing to Exercise Training: The Test of a Model

2021 ◽  
Vol 6 (3) ◽  
pp. 66
Author(s):  
Tristan Tyrrell ◽  
Jessica Pavlock ◽  
Susan Bramwell ◽  
Cristina Cortis ◽  
Scott T. Doberstein ◽  
...  
Keyword(s):  
Exercise Testing ◽  
Exercise Test ◽  
Perceived Exertion ◽  
Exercise Prescription ◽  
Test Results ◽  
Training Intensity ◽  
Ratings Of Perceived Exertion ◽  
Metabolic Equivalents ◽  
Cardiovascular Drift ◽  
And Training

Exercise prescription based on exercise test results is complicated by the need to downregulate the absolute training intensity to account for cardiovascular drift in order to achieve a desired internal training load. We tested a recently developed generalized model to perform this downregulation using metabolic equivalents (METs) during exercise testing and training. A total of 20 healthy volunteers performed an exercise test to define the METs at 60, 70, and 80% of the heart rate (HR) reserve and then performed randomly ordered 30 min training bouts at absolute intensities predicted by the model to achieve these levels of training intensity. The training HR at 60 and 70% HR reserve, but not 80%, was significantly less than predicted from the exercise test, although the differences were small. None of the ratings of perceived exertion (RPE) values during training were significantly different than predicted. There was a strong overall correlation between predicted and observed HR (r = 0.88) and RPE (r = 0.52), with 92% of HR values within ±10 bpm and 74% of RPE values within ±1 au. We conclude that the generalized functional translation model is generally adequate to allow the generation of early absolute training loads that lead to desired internal training loads.

scholarly journals Balancing the 2 Hemispheres in Simple Calculation: Evidence From Direct Cortical Electrostimulation

2016 ◽  
Author(s):  
C. Semenza ◽  
E. Salillas ◽  
S. De Pallegrin ◽  
A. Della Puppa
Keyword(s):  
Simple Calculation
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