Influence of seasons on heart rate variability during cognitive activity in students with different types of daily activity

2021 ◽  
Author(s):  
S.I. Pavlenko ◽  
O.A. Vedyasova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cognitive Load ◽  
Cognitive Activity ◽  
Winter Season ◽  
Summer Season ◽  
Winter Period ◽  
Summer Period ◽  
Different Types ◽  
School Day

It is shown that changes of heart rate variability (HRV) in students with morning, afternoon and evening chronotypes under cognitive load are characterized by seasonal dependence. A more pronounced seasonal modulation of HRV is characteristic of "pigeons", whose background values of HRV parameters and responses to load during the school day are greater in the autumn-winter period than in the spring-summer period. In" larks", HRV changes in the conditions of cognitive activity dominate in the spring-summer season, and in "owls" – in the autumn-winter season, but the observed reactions are weaker than in "pigeons". The observed differences in HRV may be caused by seasonal features of mechanisms of the heart adaptation in different chronotypes. Keywords: heart rate variability, seasons of the year, chronotypes, cognitive load.

scholarly journals Analysis of climate of Rivnenskyi Nature Reserve from 2000 to 2015

2018 ◽  
pp. 53-60
Author(s):  
Oleksandr Horbach
Keyword(s):  
Nature Reserve ◽  
Winter Season ◽  
Summer Season ◽  
Daily Temperature ◽  
Winter Period ◽  
Autumn Period ◽  
Average Daily Temperature ◽  
Spring Period ◽  
Unstable Temperature

The analysis of monthly climatic terms of Rivnenskyi Nature Reserve was conducted. It is marked that weather terms have substantial differences due to an unstable temperature condition since creation of reserve. A spring period was the shortest in 2013 – 64 days and had the greatest average daily temperature 11.9 °С. Protracted a spring period was in 2002 – 123 days. The most of precipitations in a spring period was fixed in 2008 – 196.2 mm, and the least in 2011 – 42.1 mm. A summer period in 2015 became the most protracted – 131 day. Moreover, the least protracted summer was in 2006 – 90 days. The warmest summer season was in 2010 with an average daily temperature 19.8 °С. The most raining summer was in 2007 when a 471.3 mm of precipitations is fixed, and the least raining summer was in 2002 (144.6 mm of precipitations). The most protracted autumn period was in 2006 – 107 days and the shortest one was in 2001 – 57 days. The warmest autumn was in 2004 when an average daily temperature reached 9.2°С. The most of precipitations in the autumn period is fixed in 2009 – 178 mm, and the least in 2001 – 39 mm. The winter periods were protracted in 2004/05 and 2005/06. Their duration was 114 days. Winter period in 2009/10 with an average daily temperature -7.9°С was the coldest one. The most precipitations are fixed in winter 2005/06 – 208.4 mm, and the least in a winter period 2012/13 are a 52.2 mm. The most of precipitations for a year fell out 777.8 mm in 2012, and the least one in 2011 – 427 mm. The average long-term dates of the beginning of the year seasons are defined. The average long-term date of the beginning of the spring season is on February 27; the summer season is on May 26; the autumn season is on September 14; the winter season is on December 5. Key words: Rivnenskyi Nature Reserve, seasons of the year, precipitation, climatic terms, temperature, long-term date.

scholarly journals Distribution and seasonal dynamics of bacterioplankton along the westernborder of the Barents Sea.

2020 ◽  
Vol 11 (5-2020) ◽  
pp. 37-50
Author(s):  
M.P. Venger ◽  
Keyword(s):  
Barents Sea ◽  
Structural Characteristics ◽  
Single Cells ◽  
Winter Season ◽  
Polar Front ◽  
Summer Season ◽  
Total Biomass ◽  
Summer Period ◽  
The Barents Sea ◽  
Summer Maximum

The structural characteristics of bacterioplankton were studied in the waters of the Cape`s Nordkap (cut I) and Zuydkap (cut II) of Mezhvezhiy island. Its abundance and biomass in the upper part of the photic layer of coastal and Atlantic waters in cut I was comparable and increased from the late spring to the summer season. Moreover, in cuts I and II, the values of summer maximum corresponded to the zone of the Polar Front and adjacent Arctic waters. By the beginning of the winter season, the level of development of communities in waters of different genesis decreased everywhere, but still did not reach the minimum, observed insummer in layers deeper than 200 m. The structure of bacterioplankton was determined by single cells of the smallest size, mainly of a cocci-form. The arrival of rod-shaped bacteria (contribution to the total biomass could reach 50%) was recorded in the summer period.

scholarly journals Comparative Characteristics of Sensorimotor Reactions of Highly Qualified Athletes with Different Types of Heart Rate Regulation

2021 ◽  
Vol 6 (5) ◽  
pp. 456-464
Author(s):  
A. P. Romanchuk ◽  
◽  
O. V. Guzii ◽  
A. V. Maglyovanyi ◽  
◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Type I ◽  
Sensorimotor Function ◽  
Type Ii ◽  
Highly Qualified ◽  
Rate Regulation ◽  
Type Iv ◽  
Heart Rate Regulation ◽  
Different Types

The purpose of the study was a comparative analysis of sensorimotor reactions in highly trained athletes with different types of heart rate regulation. Materials and methods. 202 highly trained male athletes aged 22.6±2.8 years, who are engaged in acyclic sports – martial arts (karate, taekwondo, kickboxing, boxing, freestyle wrestling, Greco-Roman wrestling, judo, sambo) and games (water polo, soccer) were examined. The experience in sports was 10.3±3.1 years. All studies were conducted in the pre-competition period in the morning. Based on the study of heart rate variability in athletes, the type of heart rate regulation was determined. The basis for determining the types of regulation is the classification of heart rate variability indicators, taking into account their inclusion in certain limits. Heart rate variability indicators that reflect the dual-circuit model of heart rate regulation and are used for diagnosis include: total heart rate variability – total power (ms2), very low frequency (ms2), and stress-index (e.u.), which reflect the various chains of regulatory effects on heart rate. According to certain data types, 4 groups were formed. 1 group (type I) consisted of 42 athletes, 2 (type II) – 28 athletes, 3 (type III) – 88 athletes, 4 (type IV) – 44 athletes. The study of sensorimotor function was performed using the device KMM-3. Results and discussion. It is shown that the most balanced sensorimotor reactions are in athletes with type III regulation of heart rate. The most strain sensorimotor reactions are observed in type II regulation of heart rate, which is reflected in the pronounced central asymmetry of movement control with acceleration to the left against the background of deteriorating accuracy of right (due to flexors) and left (due to extensors) limbs, and the right-hand predominance. Sensorimotor reactions are quite strain in type IV of heart rate regulation, which is characterized by slow reactions at the synaptic and peripheral levels. In type I of heart rate regulation, the disorders observed at the central level of regulation relate to the asymmetry of short-term motor memory processes, which are significantly reduced in the left hemisphere. Conclusion. The study shows that the differences in the regulatory support of heart rate in highly qualified athletes are accompanied by characteristic differences in sensorimotor function. The latter can be useful for the diagnosis and further correction of conditions associated with the development of overexertion and overtraining

scholarly journals Effects of Different Types of Verbal Activities on Heart Rate Variability

Engineering ◽  
2013 ◽  
Vol 05 (10) ◽  
pp. 310-313
Author(s):  
Ping Shi ◽  
Youfang Fang ◽  
Hongliu Yu
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Different Types

scholarly journals Effect of the transport duration time and season on some physicochemical properties of beef meat

2012 ◽  
Vol 55 (2) ◽  
pp. 123-131
Author(s):  
D. Marenčić ◽  
A. Ivanković ◽  
V. Pintić ◽  
N. Kelava ◽  
T. Jakopović
Keyword(s):  
Quality Indicators ◽  
Summer Season ◽  
Longissimus Dorsi ◽  
Winter Period ◽  
Summer Period ◽  
Beef Quality ◽  
Transport Time ◽  
Beef Meat ◽  
Short Period

Abstract. The objective of this study was to examine the effect of season and transport time on beef quality. The study was conducted during 12 months of 2009 on 480 bulls and 480 heifers of Simmental breed. The cattle were divided into 2 transport groups and then into 4 season groups according to the journey. Quality indicators pH, electrical conductivity (EC) and meat colour values were measured 24 h post mortem on m. longissimus dorsi. Heifer beef compared to bull beef had better values of quality indicators (P<0.05). Differences in quality indicators were found between cattle slaughtered in the spring and summer seasons and between cattle slaughtered in the autumn and summer seasons (P<0.05). Bull beef had poorer colour, pH and EC values in the summer and winter seasons compared to the spring season, whereas heifer beef had poorer pH, EC and colour values in the summer period compared to other seasons (P<0.05). In the summer season, poorer pH, EC and colour (L* and h*) values were obtained in groups of heifers transported for a longer time compared to heifers transported for a shorter time (P<0.05). In groups of bulls transported for a shorter time during the winter period poorer pH, EC and colour values were obtained (P<0.05). This study suggests that the quality of Simmental beef was associated with the season and that environmental factors should be considered when deciding about the time of cattle transport, since this can reduce beef colour in a very short period of time.

scholarly journals The typology of mechanisms of adaptation to the cognitive load on the variability of heart rate dynamics

2018 ◽  
Vol 11 (3) ◽  
pp. 78-93
Author(s):  
I.G. Bodrov ◽  
A.Yu. Shishelova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cognitive Load ◽  
Tension Index ◽  
Higher Power ◽  
Heart Rate Dynamics ◽  
Sensory Motor ◽  
Mechanisms Of Adaptation ◽  
Cognitive Activities ◽  
Regulatory Effects

While analyzing heart rate variability there were detected two types of visceral adaptation to cognitive activities: the first one is characterized by decrease of tension index (Baevskiy, 1984) and increase of heart rate variability at a cognitive load, along with increased power of regulatory effects on the heart rate; the second one is defined by higher heart rate variability, higher power of regulatory effects before the cognitive load and increase of the strain index during cognitive load in the absence of other significant changes. It is peculiar for people related to these types to possess different correlation relationships between the indices of sensory-motor reactions and heart rate variability.

scholarly journals Biomass burning contribution to Beijing aerosol

2013 ◽  
Vol 13 (3) ◽  
pp. 8387-8434 ◽  
Author(s):  
Y. Cheng ◽  
G. Engling ◽  
K. B. He ◽  
F. K. Duan ◽  
Y. L. Ma ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Elemental Carbon ◽  
Organic Aerosol ◽  
Water Soluble ◽  
Winter Period ◽  
Summer Period ◽  
Pmf Model ◽  
Different Types ◽  
Biomass Burning Aerosol ◽  
Typical Summer

Abstract. Biomass burning, the largest global source of elemental carbon (EC) and primary organic carbon (OC), is strongly associated with many subjects of great scientific concern, such as secondary organic aerosol and brown carbon which exert important effects on the environment and on climate in particular. This study investigated the relationships between levoglucosan and other biomass burning tracers (i.e. water soluble potassium and mannosan) based on both ambient samples collected in Beijing and source samples. Compared with North America and Europe, Beijing was characterized by high ambient levoglucosan concentrations and low winter to summer ratios of levoglucosan, indicating significant impact of biomass burning activities throughout the year in Beijing. Comparison of levoglucosan and water soluble potassium (K+) levels suggested that it was acceptable to use K+ as a biomass burning tracer during summer in Beijing, while the contribution of fireworks to K+ could be significant during winter. Moreover, the levoglucosan to K+ ratio was found to be lower during the typical summer period (0.21±0.16) compared with the typical winter period (0.51±0.15). On the other hand, levoglucosan correlated strongly with mannosan (R2=0.97) throughout the winter and the levoglucosan to mannosan ratio averaged 9.49±1.63, whereas levoglucosan and mannosan exhibited relatively weak correlation (R2=0.73) during the typical summer period when the levoglucosan to mannosan ratio averaged 12.65±3.38. Results from PMF model analysis showed that about 50% of the OC and EC in Beijing were associated with biomass burning processes. In addition, a new source-identification method was developed based on the comparison of the levoglucosan to K+ ratio and the levoglucosan to mannosan ratio among different types of biomass. Using this method, the major source of biomass burning aerosol in Beijing was suggested to be the combustion of crop residuals, while the contribution from softwood burning was also non-negligible, especially in winter.

ON CHAOS DETECTION METHODS

1996 ◽  
Vol 06 (03) ◽  
pp. 529-543 ◽  
Author(s):  
KARIN VIBE ◽  
JEAN-MARC VESIN
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Scientific Community ◽  
Detection Methods ◽  
Nonlinear Prediction ◽  
Attractor Dimension ◽  
Chaos Detection ◽  
Different Types ◽  
Data Length

Reliable chaos detection in real-world time series is attracting increasing attention in the scientific community. This work shows that it is possible to use chaos analysis methods such as attractor dimension estimation, Lyapunov exponents estimation and nonlinear prediction, under the condition that the limitations and drawbacks of the algorithms used are kept in mind. Three existing algorithms for chaos characterization are analyzed in terms of classification performances and robustness with respect to noise and data length. It is shown that all three help detect chaos and even classify different types of signals, but that their results are not devoid of ambiguity. An illustrative example is given, in which the algorithms presented are applied to heart rate variability signals, and directions of research are proposed for the design of a straightforward and simple chaos detection methodology.

scholarly journals DETRENDED FLUCTUATION ANALYSES OF SHORT-TERM HEART RATE VARIABILITY IN SURGICAL INTENSIVE CARE UNITS

2006 ◽  
Vol 18 (02) ◽  
pp. 67-72 ◽  
Author(s):  
RONG-GUAN YEH ◽  
JIANN-SHING SHIEH ◽  
YIN-YI HAN ◽  
YU-JUNG WANG ◽  
SHIH-CHUN TSENG
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Intensive Care ◽  
White Noise ◽  
Short Term ◽  
Surgical Intensive Care ◽  
Ecg Signals ◽  
Different Types ◽  
Group A ◽  
Detrended Fluctuation

We examine the dynamics of complex physiologic fluctuations using methods developed very recently in statistical physics. The method based on detrended fluctuation analysis (DFA) has been used to investigate the profile of different types of physiologic states under long term (i.e., 24 hr) analysis of heart rate variability (HRV). In this paper, this method to investigate the output of central physiologic control system under short term (i.e., 1 hr) of HRV in surgical intensive care units (SICU). Electrocardiograph (ECG) signals lasting around 1 hr were collected from ten college student volunteers as group A. Ten computes-generates white noise signals as group B also provided ECG signals lasting around 1 hr. Finally, seventeen patients representing 37 cases undergoing different types of neurosurgery were studied as group C. From this group, 25 cases were selected from 15 patients with brain injury and 12 cases were selected from 2 patients with septicemia. Group A and B were used as high and low limits of baseline for comparison with pathologic states in the SICU. The a values of DFA of groups A, B, and C were 0.958 ± 0.034, 0.521 ± 0.010, and 0.815 ± 0.183, respectively. It was found that the α value of patients in the SICU was significantly lower (P < 0.05) than that of healthy volunteers and significantly higher (P < 0.05) than white noise signals. Hence, it can be concluded that α values based on the DFA statistical concept can clearly distinguish pathologic states in SICU patients from the healthy group and from white noise signals.

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