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Different tillage technologies have different effects on CO 2 emissions from soil. Unfortunately, little information exists about the impact of different types of tillage as compared with no-tillage, and the main controls. The aim of this research is to determine the relationship between physicomechanical, chemical and biological properties of soil and CO 2 emissions from differently tilled soils under the climatic conditions of central Lithuania before and after autumn tillage. The studies were conducted in 2009-2012 and 2014 at the Experimental Station of Aleksandras Stulginskis University in Central Lithuania. Different tillage technologies were applied: deep ploughing at 23-25 cm depth (DP); shallow ploughing at 12-15 cm depth (SP); deep cultivation with a cultivator at 25-27 cm depth (DC); shallow cultivation with a disc harrow at 12-15 cm depth (SC); and no-tillage (NT). The correlation of physicomechanical, chemical and biological soil properties with CO 2 emissions was determined. During all the experimental period total CO 2 emissions from soil in DP, SP, DC, SC and NT technologies were respectively 6.05, 4.25, 4.97, 4.42, 3.94 μmol m -2  s -1 before autumn soil tillage and 29.88, 22.50, 16.73, 13.72, 10.00 μmol m -2  s -1 after autumn tillage. Negative correlation between soil temperature and CO 2 emissions before the autumn tillage from soil was evidenced (r = -0.98). A strong negative correlation between soil respiration and total soil porosity was observed. Correlation between aeration soil porosity and CO 2 emissions was strong. After autumn tillage, the strongest correlations were found between soil penetration resistance and respiration in the upper (r = -0.75) and deeper (r = -0.71) layers. In autumn, a significant strong correlation (r = 0.78) between soil respiration and aeration porosity was obtained in the upper soil layer under ploughing or cultivation. This study revealed that CO 2 emissions were significantly higher immediately after autumn ploughing technologies compared to deep and shallow cultivation and no-tillage., (Copyright © 2019 Elsevier B.V. All rights reserved.)

An approach to atrial fibrillation (AF) frequency tracking in long-term ambulatory ECG recordings is presented, comprising f-wave extraction, dominant atrial frequency (DAF) tracking, and signal quality assessment. Since poor signal quality is commonly encountered in ambulatory monitoring, a recently proposed index is employed to assess f-wave signal quality in a database containing 38 patients with permanent AF. The index ensures that DAF outliers, typically associated with poor-quality segments, are excluded from further analysis. 40% of all 5-s signal segments were excluded from the database due to poor quality. The exclusion of DAF outliers significantly reduces the standard deviation of the frequency estimates (p≤0.01), allowing more reliable evaluation of the difference between day- and night-time DAF. The results show that signal quality assessment plays a central role in DAF tracking, and therefore should be employed in ambulatory monitoring., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Global changes occurring under different environmental conditions have changed stand competition, as well as nutrient and light availability, which has resulted in changes in productivity. Therefore, in the present study, the characteristics of tree-ring width formation of the prevailing Lithuanian tree species, Norway spruce, Scots pine and silver and downy birch, and key factors resulting in their differences during the last 36-year period were investigated at forest sites located on poor mineral oligotrophic and on nutrient-rich organic mesoeutrophic soils. The aim of the study was as follows: first, to separately detect the maximum possible seasonal effect of three groups of variables - meteorology, acidifying pollutants and surface ozone on the stem basal area increment (BAI) of the evaluated tree species; second, to assess the significance of each group of variables affecting the BAI of these tree species integrally with the remaining groups of variables. Norway spruce was found to be well adapted to recent environmental changes, which makes it one of the most favourable tree species for silviculture in the northeastern part of Europe. The rapid increases recorded in growth intensity since 1980 were attributed to the increase in air temperature, precipitation amount, nitrogen deposition during the vegetative stage and reductions in SO 2 concentrations and S deposition. Scots pine demonstrated the highest level of resilience and capacity to adapt to recent global changes because its reaction to both negative and favourable environmental factors was best expressed. Silver and downy birch tree reactions to the effects of air concentrations of acidifying compounds, their deposition and surface ozone concentrations were the least expressed; however, a significant decline in growth intensity indicated that these tree species experienced a reduced resistance to recent changes in environmental conditions in the mature and over-mature age groups., (Copyright © 2017 Elsevier B.V. All rights reserved.)

This study presents a system that aims to estimate changes in arterial health status in an unobtrusive way. It might be especially useful in long-term self-monitoring of cardiovascular performance for successful treatment and empowerment of patients. This system applies the electrocardiographic and impedance plethysmographic signals acquired using modified body composition scales for the calculation of pulse arrival time, which is directly related to arterial stiffness. The proposed device was tested in a cohort of 14 subjects. The modified scales were compared to the commercial PulsePen tonometer and the results showed significant relationship between these different devices (r s =0.93, p<0.01). The system also showed the ability to track small pulse arrival time variations induced by paced respiration. These findings suggest that scales evaluating parameters of cardiovascular function have potential to become a convenient device for self-monitoring of arterial stiffness., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A phenomenological model for simulating the photoplethysmogram (PPG) during atrial fibrillation (AF) is proposed. The simulated PPG is solely based on RR interval information, and, therefore, any annotated ECG database can be used to model sinus rhythm, AF, or rhythms with premature beats. A PPG pulse is modeled by a linear combination of a log-normal and two Gaussian waveforms. The model PPG is obtained by placing individual pulses according to the RR intervals so that a connected signal is created. The model is evaluated on synchronously recorded ECG and PPG signals from the MIMIC and the University of Queensland Vital Signs Dataset databases. The results show that the model PPG signals closely resemble real signal for sinus rhythm, premature beats, as well as for AF. The model is used to study the performance of a low-complexity RR interval-based AF detector on simulated PPG signals with five different pulse types generated using the MIT-BIH AF database at signal-to-noise ratios (SNRs) from 0 to 30dB. PPGs composed of pulses with a dicrotic notch tend to increase the rate of false alarms, especially at lower SNRs. The model is capable of generating simulated PPG signals from RR interval series with sinus rhythm, AF, and premature beats. Considering the lack of annotated, public PPG databases with arrhythmias, the simulation of realistic PPG signals based on annotated ECG signals is expected to facilitate the development and testing of PPG-specific AF detectors., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

This study describes an atrial fibrillation (AF) detector whose structure is well-adapted both for detection of subclinical AF episodes and for implementation in a battery-powered device for use in continuous long-term monitoring applications. A key aspect for achieving these two properties is the use of an 8-beat sliding window, which thus is much shorter than the 128-beat window used in most existing AF detectors. The building blocks of the proposed detector include ectopic beat filtering, bigeminal suppression, characterization of RR interval irregularity, and signal fusion. With one design parameter, the performance can be tuned to put more emphasis on avoiding false alarms due to non-AF arrhythmias or more emphasis on detecting brief AF episodes. Despite its very simple structure, the results show that the detector performs better on the MIT-BIH Atrial Fibrillation database than do existing detectors, with high sensitivity and specificity (97.1% and 98.3%, respectively). The detector can be implemented with just a few arithmetical operations and does not require a large memory buffer thanks to the short window., (Copyright © 2015 Elsevier Ltd. All rights reserved.)