scholarly journals Monthly mobility inferred from isoscapes and laser ablation strontium isotope ratios in caprine tooth enamel

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
N. Lazzerini ◽  
V. Balter ◽  
A. Coulon ◽  
T. Tacail ◽  
C. Marchina ◽  
...  
Keyword(s):  
High Frequency ◽  
Tooth Enamel ◽  
Isotope Composition ◽  
Isotopic Analysis ◽  
Strontium Isotope ◽  
Gps Tracking ◽  
Altai Mountains ◽  
Short Term ◽  
Domestic Livestock ◽  
Isotope Variation

AbstractStrontium isotopic analysis of sequentially formed tissues, such as tooth enamel, is commonly used to study provenance and mobility of humans and animals. However, the potential of 87Sr/86Sr in tooth enamel to track high-frequency movements has not yet been established, in part due to the lack of data on modern animals of known movement and predictive model of isotope variation across the landscape. To tackle this issue, we measured the 87Sr/86Sr in plant samples taken from a 2000 km2 area in the Altai Mountains (Mongolia), and the 87Sr/86Sr in tooth enamel of domestic caprines whose mobility was monitored using GPS tracking. We show that high-resolution, sequential profiles of strontium isotope composition of tooth enamel reliably reflect the high-frequency mobility of domestic livestock and that short-term residency of about 45 days can be resolved. This offers new perspectives in various disciplines, including forensics, ecology, palaeoanthropology, and bioarchaeology.

Prior Return Effect in Indian Stock Market: An Intra-day Analysis

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Vanita Tripathi ◽  
Shalini Aggarwal
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
High Frequency ◽  
Good News ◽  
High Frequency Data ◽  
Short Term ◽  
Fund Managers ◽  
News Events ◽  
Return Effect ◽  
Indian Stock Market

In a first of this kind, this paper examines the issue of prior return effect in Indian stock market in intra-day analysis using high frequency data. We document that in Indian stock market, security returns exhibit a reversal in their direction within few minutes of extreme price rises as well as price falls. However the speed with which the correction takes place is slightly different for good news events and bad news events. Indian investors tend to be optimistic as they immediately bring stock prices up following unjustified price falls but take time to bring stock prices down following unjustified price rises. These findings lend a further support to short-term overreaction literature. More importantly, these findings serve as a proof of predictability of the direction of future stock prices and consequent returns on an intra-day basis. It forwards important investment implications for traders, fund managers, and investors at large.

scholarly journals Small Floating Target Detection Method Based on Chaotic Long Short-Term Memory Network

2021 ◽  
Vol 9 (6) ◽  
pp. 651
Author(s):  
Yan Yan ◽  
Hongyan Xing
Keyword(s):  
High Frequency ◽  
Short Term Memory ◽  
Detection Method ◽  
Low Frequency ◽  
Sea Clutter ◽  
Short Term ◽  
Term Memory ◽  
Memory Network ◽  
Long Short Term Memory ◽  
Small Targets

In order for the detection ability of floating small targets in sea clutter to be improved, on the basis of the complete ensemble empirical mode decomposition (CEEMD) algorithm, the high-frequency parts and low-frequency parts are determined by the energy proportion of the intrinsic mode function (IMF); the high-frequency part is denoised by wavelet packet transform (WPT), whereas the denoised high-frequency IMFs and low-frequency IMFs reconstruct the pure sea clutter signal together. According to the chaotic characteristics of sea clutter, we proposed an adaptive training timesteps strategy. The training timesteps of network were determined by the width of embedded window, and the chaotic long short-term memory network detection was designed. The sea clutter signals after denoising were predicted by chaotic long short-term memory (LSTM) network, and small target signals were detected from the prediction errors. The experimental results showed that the CEEMD-WPT algorithm was consistent with the target distribution characteristics of sea clutter, and the denoising performance was improved by 33.6% on average. The proposed chaotic long- and short-term memory network, which determines the training step length according to the width of embedded window, is a new detection method that can accurately detect small targets submerged in the background of sea clutter.

scholarly journals Effect of short-term exposure to particulate air pollution on heart rate variability in normal-weight and obese adults

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Luyi Li ◽  
Dayu Hu ◽  
Wenlou Zhang ◽  
Liyan Cui ◽  
Xu Jia ◽  
...  
Keyword(s):  
Heart Rate ◽  
Air Pollution ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Normal Weight ◽  
High Frequency Power ◽  
Short Term ◽  
Particulate Air Pollution ◽  
Short Term Exposure ◽  
Frequency Power

Abstract Background The adverse effects of particulate air pollution on heart rate variability (HRV) have been reported. However, it remains unclear whether they differ by the weight status as well as between wake and sleep. Methods A repeated-measure study was conducted in 97 young adults in Beijing, China, and they were classified by body mass index (BMI) as normal-weight (BMI, 18.5–24.0 kg/m2) and obese (BMI ≥ 28.0 kg/m2) groups. Personal exposures to fine particulate matter (PM2.5) and black carbon (BC) were measured with portable exposure monitors, and the ambient PM2.5/BC concentrations were obtained from the fixed monitoring sites near the subjects’ residences. HRV and heart rate (HR) were monitored by 24-h Holter electrocardiography. The study period was divided into waking and sleeping hours according to time-activity diaries. Linear mixed-effects models were used to investigate the effects of PM2.5/BC on HRV and HR in both groups during wake and sleep. Results The effects of short-term exposure to PM2.5/BC on HRV were more pronounced among obese participants. In the normal-weight group, the positive association between personal PM2.5/BC exposure and high-frequency power (HF) as well as the ratio of low-frequency power to high-frequency power (LF/HF) was observed during wakefulness. In the obese group, personal PM2.5/BC exposure was negatively associated with HF but positively associated with LF/HF during wakefulness, whereas it was negatively correlated to total power and standard deviation of all NN intervals (SDNN) during sleep. An interquartile range (IQR) increase in BC at 2-h moving average was associated with 37.64% (95% confidence interval [CI]: 25.03, 51.51%) increases in LF/HF during wakefulness and associated with 6.28% (95% CI: − 17.26, 6.15%) decreases in SDNN during sleep in obese individuals, and the interaction terms between BC and obesity in LF/HF and SDNN were both statistically significant (p <  0.05). The results also suggested that the effects of PM2.5/BC exposure on several HRV indices and HR differed in magnitude or direction between wake and sleep. Conclusions Short-term exposure to PM2.5/BC is associated with HRV and HR, especially in obese individuals. The circadian rhythm of HRV should be considered in future studies when HRV is applied. Graphical abstract

Cibenzoline for High-Frequency Ventricular Arrhythmias: A Short-Term Comparison With Quinidine and a Long-Term Follow-up

1987 ◽  
Vol 27 (4) ◽  
pp. 283-287 ◽  
Author(s):  
Prasad R. Palakurthy ◽  
Claudio Maldonado ◽  
Gurbachan Sohi ◽  
Nancy C. Flowers
Keyword(s):  
High Frequency ◽  
Ventricular Arrhythmias ◽  
Short Term ◽  
Long Term Follow Up

scholarly journals Investigating Hydrogen Isotope Variation during Heating of n-Alkanes under Limited Oxygen Conditions: Implications for Palaeoclimate Reconstruction in Archaeological Settings

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 1830
Author(s):  
Rory Connolly ◽  
Margarita Jambrina-Enríquez ◽  
Antonio V. Herrera-Herrera ◽  
Carolina Mallol
Keyword(s):  
Depositional Environment ◽  
Low Temperature Combustion ◽  
Short Term ◽  
Oxygen Conditions ◽  
Temperature Combustion ◽  
Isotopic Variations ◽  
Isotope Variation ◽  
Hydrogen Isotopic Composition ◽  
Celtis Australis ◽  
Limited Oxygen

This paper reports on a series of heating experiments that focus on n-alkanes extracted from leaf, bark, and xylem tissues of the Celtis australis plant. These lipid biomarkers were analysed for their compound-specific hydrogen isotopic composition (δ2Hwax) under limited oxygen conditions at 150, 250, 350, and 450 °C. Our results reveal isotopic variations in wax lipids of different plant organs during short-term low-temperature combustion. We conclude that, in the absence of a detailed characterisation of the depositional environment in advance of sampling, δ2Hwax values in archaeological or otherwise highly anthropogenic environments should be interpreted cautiously. In addition, we observed that variation in δ2Hwax of leaves is minimal at temperatures ≤ 350 °C, highlighting the potential for δ2Hwax in thermally altered combustion substrates to yield palaeoclimate information, which could allow researchers to investigate links between archaeological and climatic records at a high spatial and temporal resolution.

scholarly journals Multi-Scale Spatiotemporal Change Characteristics Analysis of High-Frequency Disturbance Forest Ecosystem Based on Improved Spatiotemporal Cube Model

2021 ◽  
Vol 13 (13) ◽  
pp. 2537
Author(s):  
Yangcen Zhang ◽  
Xiangnan Liu ◽  
Meiling Liu ◽  
Xinyu Zou ◽  
Qian Zhang ◽  
...  
Keyword(s):  
High Frequency ◽  
Forest Ecosystems ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Anthropogenic Factors ◽  
Residential Areas ◽  
Short Term ◽  
Spatiotemporal Changes ◽  
Spatiotemporal Scales ◽  
The Impact

High-frequency disturbance forest ecosystems undergo complex and frequent changes at various spatiotemporal scales owing to natural and anthropogenic factors. Effectively capturing the characteristics of these spatiotemporal changes from satellite image time series is a powerful and practical means for determining their causes and predicting their trends. Herein, we combined the spatiotemporal cube and vegetation indices to develop the improved spatiotemporal cube (IST-cube) model. We used this to acquire the spatiotemporal dynamics of forest ecosystems from 1987 to 2020 in the study area and then classified it into four spatiotemporal scales. The results showed that the cube-core only exists in the increasing IST-cubes, which are distributed in residential areas and forests. The length of the IST-cube implies the duration of triggers. Human activities result in long-term small-scope IST-cubes, and the impact in the vicinity of residential areas is increasing while there is no change within. Meteorological disasters cause short-term, large scope, and irregular impacts. Land use type change causes short-term small scope IST-cubes and a regular impact. Overall, we report the robustness and strength of the IST-cube model in capturing spatiotemporal changes in forest ecosystems, providing a novel method to examine complex changes in forest ecosystems via remote sensing.

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