Covariance Method Research Articles

A pre-whitening with block-bootstrap cross-correlation procedure for temporal alignment of data sampled by eddy covariance systems

The eddy covariance (EC) method is a standard micrometeorological technique for monitoring the exchange rate of the main greenhouse gases across the interface between the atmosphere and ecosystems. One of the first EC data processing steps is the temporal alignment of the raw, high frequency measurements collected by the sonic anemometer and gas analyser. While different methods have been proposed and are currently applied, the application of the EC method to trace gases measurements highlighted the difficulty of a correct time lag detection when the fluxes are small in magnitude. Failure to correctly synchronise the time series entails a systematic error on covariance estimates and can introduce large uncertainties and biases in the calculated fluxes. This work aims at overcoming these issues by introducing a new time lag detection procedure based on the assessment of the cross-correlation function (CCF) between variables subject to (i) a pre-whitening based on autoregressive filters and (ii) a resampling technique based on block-bootstrapping. Combining pre-whitening and block-bootstrapping facilitates the assessment of the CCF, enhancing the accuracy of time lag detection between variables with correlation of low order of magnitude (i.e. lower than -1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-1$$\\end{document}) and allowing for a proper estimate of the associated uncertainty. We expect the proposed procedure to significantly improve the temporal alignment of the EC time-series measured by two physically separate sensors, and to be particularly beneficial in centralised data processing pipelines of research infrastructures (e.g. the Integrated Carbon Observation System, ICOS-RI) where the use of robust and fully data-driven methods, like the one we propose, constitutes an essential prerequisite.

Low-pressure measurements of energy depositions in nanometre objects with a single ionisation chamber in a 60Co beam using the variance–covariance method

Dose-mean lineal energies were measured using the variance–covariance method and commercial ionisation chambers in a therapy level 60Co field at several different air pressures. The results confirmed the trend from previous studies and the experimental data was extended down to a simulated object diameter of 4.2 nm using a low-noise electrometer. The variance–covariance method was adapted to consecutive charge integrations from a single ionisation chamber and used to correct for signal variations due to pressure drifts in the ion chamber. Monte Carlo simulations using MCNP 6.2 were performed, and the results follow the trend of the experimental values in the nanometric region.

Assessing Satellite-Derived OpenET Platform Evapotranspiration of Mature Pecan Orchard in the Mesilla Valley, New Mexico

Pecan is a major crop in the Mesilla Valley, New Mexico. Due to prolonged droughts, growers face challenges related to water shortages. Therefore, irrigation management is crucial for farmers. Advancements in satellite-derived evapotranspiration (ET) models and accessibility to data from web-based platforms like OpenET provide farmers with new tools to improve crop irrigation management. This study evaluates the evapotranspiration (ET) of a mature pecan orchard using OpenET platform data generated by six satellite-based models and their ensemble. The ET values obtained from the platform were compared with the ET values obtained from the eddy covariance (ETec) method from 2017 to 2021. The six models assessed included Google Earth Engine implementation of the Surface Energy Balance Algorithm for Land (geeSEBAL), Google Earth Engine implemonthsmentation of the Mapping Evapotranspiration at High Resolution with Internalized Calibration (eeMETRIC) model, Operational Simplified Surface Energy Balance (SSEBop), Satellite Irrigation Management Support (SIMS), Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), and Atmosphere–Land Exchange Inverse and associated flux disaggregation technique (ALEXI/DisALEXI). The average growing season ET of mature pecan estimated from April to October of 2017 to 2021 by geeSEBAL, eeMETRIC, SSEBop, SIMS, PT-JPL, ALEXI/DisALEXI, and the ensemble were 1061, 1230, 1232, 1176, 1040, 1016, and 1130 mm, respectively, and 1108 mm by ETec. Overall, the ensemble model-based monthly ET of mature pecan during the growing season was relatively close to the ETec (R2 of 0.9477) with a 2% mean relative difference (MRD) and standard error of estimate (SEE) of 15 mm/month for the five years (N = 60 months). The high agreement of the OpenET ensemble of the six satellite-derived models’ estimates of mature pecan ET with the ETec demonstrates the utility of this promising approach to enhance the reliability of remote sensing-based ET data for agricultural and water resource management.

Equilibration of athletes’ body state in the course of increasing the training intensity

Recovery of an athlete after injury allows to achieve either the previous results or relatively equal. Moreover, the prescribed drugs or recovery exercises are offered in courses without the possibility of process adjustments. The relevance of the study is determined primarily by a large number of universal methods of restoration, if necessary, development of more patient-specific approach. The novelty of the study is determined by the fact that the human body is a dynamic system, the state of which is different at any time. The authors developed the idea of a stochastic process problem in the form of a system with a variable state, which can be utilized to generate a process, in order to build a technique for recognizing and predicting the state of dynamic systems. The authors showed that the dynamic system of the body can be considered not only as a process element, but also as a structure that allows to fully achieve recovery during the training period of athletes and their off-season indicators. The paper has developed a model that allows to predict the state of the dynamic system and harmonise the load and the recovery process of the athlete's body. The developed method for identifying and predicting the state of dynamical systems with the improvement of the method of covariance functions factorisation makes it possible to determine the main matrices of a dynamical system using the Riccati equation.

Determinants of funding intention of crowdfunding campaigns from India – a subregional cultural variation and transnational migrants perspective

PurposeThis paper aims to explore how sub-national or regional cultural differences influence backers’ willingness to crowdfund projects. The paper also explores how migrant transnationalism influences the impact of backer’s sub-national culture and crowdfunding relationships.Design/methodology/approachThis paper is based on the experimental design technique using analysis of covariance methods. The authors tested the study hypotheses on a sample of 790 respondents.FindingsThe study results suggest that individuals differ in their intent to crowdfund product campaigns depending on value congruence between their cultural values derived from the region to which they belong and the nature of the product category, such as environmentally friendly or happiness-enhancing products.Originality/valueThis paper explores the role of regional cultural differences in determining the intention to crowdfund different campaigns based on the nature of the product. Value congruence, as driven by regional cultural differences with crowdfunding campaigns, has not been explored before.

Wet canopy photosynthesis in a temperate Japanese cypress forest.

This study aimed to reveal the mechanism and significance of wet canopy photosynthesis during and after rainfall in temperate coniferous ecosystems by evaluating the influence of abaxial leaf interception on wet canopy photosynthesis. We used the eddy covariance method in conjunction with an enclosed-path gas analyser to conduct continuous ecosystem CO2 flux observations in a Japanese cypress forest within the temperate Asian monsoon area over 3years. The observation shows that wet-canopy CO2 uptake predominantly occurred during the post-rainfall canopy-wet period rather than the during-rainfall period. Then, the measured canopy-wet net ecosystem exchange was compared with the soil-vegetation-atmosphere transfer multilayer model simulations under different parameter settings of the abaxial (lower) leaf surface wet area ratio. The multilayer model predicted net ecosystem exchange most accurately when it assumed the wet area ratio of the abaxial surface was 50% both during and after rainfall. For the wet canopy both during and after rainfall, the model overestimated CO2 uptake when it assumed no abaxial interception in the simulation, but underestimated CO2 uptake when it assumed that the entire abaxial leaf surface was wet. These results suggest that the abaxial surface of the Japanese cypress leaf is only partly wet to maintain stomatal openness and a low level of photosynthesis. These results allow for an evaluation of the effect of rainfall on forest carbon circulation under a changing climate, facilitating an improvement of ecosystem carbon exchange models.

A multi-source molecular network representation model for protein–protein interactions prediction

The prediction of potential protein–protein interactions (PPIs) is a critical step in decoding diseases and understanding cellular mechanisms. Traditional biological experiments have identified plenty of potential PPIs in recent years, but this problem is still far from being solved. Hence, there is urgent to develop computational models with good performance and high efficiency to predict potential PPIs. In this study, we propose a multi-source molecular network representation learning model (called MultiPPIs) to predict potential protein–protein interactions. Specifically, we first extract the protein sequence features according to the physicochemical properties of amino acids by utilizing the auto covariance method. Second, a multi-source association network is constructed by integrating the known associations among miRNAs, proteins, lncRNAs, drugs, and diseases. The graph representation learning method, DeepWalk, is adopted to extract the multisource association information of proteins with other biomolecules. In this way, the known protein–protein interaction pairs can be represented as a concatenation of the protein sequence and the multi-source association features of proteins. Finally, the Random Forest classifier and corresponding optimal parameters are used for training and prediction. In the results, MultiPPIs obtains an average 86.03% prediction accuracy with 82.69% sensitivity at the AUC of 93.03% under five-fold cross-validation. The experimental results indicate that MultiPPIs has a good prediction performance and provides valuable insights into the field of potential protein–protein interactions prediction. MultiPPIs is free available at https://github.com/jiboyalab/multiPPIs.

The Productivity and Carbon Exchange of an Intensively Managed Pasture in Central Kentucky

Intensive pasture management that aims at providing season-long forage while minimizing soil degradation is increasingly becoming an important grazing strategy in Kentucky. Typically, it involves the use of high-yielding warm and cool season forage species that are well suited to local soil and climate conditions, meeting the dual-purpose provision of high nutritional value while remaining resilient to grazing pressure and changing climate. Monitoring carbon exchange is a crucial component for effective pasture management to promote sustainable pastureland management practices. We hypothesized that pasturelands, when intensively managed, would exhibit a small but important CO2 cumulative uptake year-round. We used the Eddy covariance method to measure the net ecosystem exchange of CO2 (NEE) and productivity of an intensively managed pastureland at Kentucky State University Research and Demonstration station from 2015 to 2020. The study has two objectives: to quantify interannual variability in net ecosystem exchange, and examine the controlling environmental factors, in particular temperature, sunlight, and precipitation of NEE. Diurnal and seasonal fluctuations followed typical patterns of carbon uptake and release. Overall, the pasture site consistently was carbon sink except for 2016, in part due to a warmer winter season than usual, sequestering 1394 gCm−2 over the study period. Precipitation and temperature were critical environmental factors underpinning seasonal CO2 uptake and release. Of critical importance was the net carbon uptake during the non-growing season.

Variables controlling growing season carbon dynamics in desert shrub ecosystem

Arid and semi-arid lands (drylands) are under the influence of extreme environmental conditions and cover large areas on Earth’s land surface. Determining temporal and spatial variations of the greenhouse gas and energy exchange in these ecosystems will provide a better understanding of both, the dynamics between the drylands’s surface and the atmosphere and the importance in climate change. In this study, CO2 exchanges over a shrub steppe ecosystem were determined using the Eddy Covariance method during both dry and wet growing seasons in the Gobi Desert, Mongolia. The net ecosystem exchange (NEE) was modeled using the extreme gradient boosting method (XGBOOST). Variables influencing NEE were estimated employing the SHapley Additive exPlanations algorithm (SHAP). The XGBOOST predictions demonstrated impressive results across all growing seasons, with high performance metrics (R2 = 0.821; NSE = 0.817), particularly notable during the wet season (R2 = 0.932; NSE = 0.929). The total NEE changed between 79.7 and -110.4 gC m−2 throughout the growing seasons. Especially the precipitation before the growing period has a positive impact on carbon sequestration in the shrub ecosystem in the following dry season. A high similarity was found in the patterns of daily NEE of all growing seasons and normalized difference vegetation index (NDVI), albedo, soil water content, temperature, sensible heat flux, the difference between air and soil temperature in desert shrub ecosystem. Although NDVI was the dominant factor during the wet season, there was a weaker relationship between these factors and NEE in the dry season than in the wet season.

Recursive construction for expansions of tree Yang–Mills amplitudes from soft theorem

In this paper, we introduce a fundamentally different approach, based on a bottom-up methodology, for expanding tree-level Yang–Mills (YM) amplitudes into Yang–Mills-scalar (YMS) amplitudes and bi-adjoint-scalar (BAS) amplitudes. Our method relies solely on the intrinsic soft behavior of external gluons, eliminating the need for external aids such as Feynman rules or CHY rules. The recursive procedure consistently preserves explicit gauge invariance at every step, ultimately resulting in a manifest gauge-invariant outcome when the initial expression is already framed in a gauge-invariant manner. The resulting expansion can be directly analogized to the expansions of gravitational (GR) amplitudes using the double copy structure. When combined with the expansions of Einstein–Yang–Mills amplitudes obtained using the covariant color-kinematic duality method from existing literature, the expansions presented in this note yield gauge-invariant Bern–Carrasco–Johansson (BCJ) numerators.

Applicability of the generalized wind profile model over mountainous forests.

The analytical equation based on Monin-Obukhov (M-O) similarity theory (i.e., wind profile equation) has been adopted since 1970s for using in the prediction of wind vertical profile over flat terrains, which is mature and accurate. However, its applicability over complex terrains remains unknown. This applicability signifies the accuracy of the estimations of aerodynamic parameters for the boundary layer of non-flat terrain, such as zero-displacement height (d) and aerodynamic roughness length (z0), which will determine the accuracy of frequency correction and source area analysis in calculating carbon, water, and trace gas fluxes based on vorticity covariance method. Therefore, the validation of wind profile model in non-flat terrain is the first step to test whether the flux model needs improvement. We measured three-dimensional wind speed data by using the Ker Towers (three towers in a watershed) at Qingyuan Forest CERN in the Mountainous Region of east Liaoning Province, and compared them with data from Panjin Agricultural Station in the Liaohe Plain, to evaluate the applicability of a generalized wind profile model based on the Monin-Obukhov similarity theory on non-flat terrain. The results showed that the generalized wind profile model could not predict wind speeds accurately of three flux towers separately located in different sites, indicating that wind profile model was not suitable for predicting wind speeds in complex terrains. In the leaf-off and leaf-on periods, the coefficient of determination (R2) between observed and predicted wind speeds ranged from 0.12 to 0.30. Compared to measured values, the standard error of the predicted wind speeds was high up to 2 m·s-1. The predicted wind speeds were high as twice as field-measured wind speed, indicating substantial overestimation. Nevertheless, this model correctly predicted wind speeds in flat agricultural landscape in Panjin Agricultural Station. The R2 between observed wind speeds and predicted wind speed ranged from 0.90 to 0.93. The standard error between observed and predicted values was only 0.5 m·s-1. Results of the F-test showed that the root-mean-square error of the observed and predicted wind speeds in each secondary forest complex terrain was much greater than that in flat agricultural landscape. Terrain was the primary factor affecting the applicability of wind profile model, followed by seasonality (leaf or leafless canopy). The wind profile model was not applicable to the boundary-layer flows over forest canopies in complex terrains, because the d was underestimated or both the d and z0 were underestimated, resulting in inaccurate estimation of aerodynamic height.

Impact Analysis of H2O Fluxes and High-Frequency Meteorology–Water Quality: Multivariate Constrained Evaporation Modelling in Lake Wuliangsuhai, China

It is imperative to elucidate the process of evaporation in lakes, particularly those that are freshwater and are situated in middle and high latitudes. Based on one-year evaporation and high-frequency meteorological–water quality data of Lake Wuliangsuhai, this study analyzed the applicability and driving mechanism of the evaporation model. These dynamics are elucidated by the vorticity covariance method combined with the multivariate constrained evaporation Modelling method. The findings of this study revealed that (1) Lake evaporation (ET) is affected by multiple meteorological–water quality constraints, and the water quality indicators significantly related to ET are also affected by lake stratification. The coupled meteorological–water quality evaporation model can explain 93% of the evaporation change, which is 20% higher than the traditional meteorological Modelling evaporation model. (2) The nighttime ET is mainly affected by the thermal inertia lag, and the nighttime ET loss in Lake Wuliangsuhai accounts for 37.34% of the total evaporation, which cannot be ignored. (3) The actual water surface evaporation of the lake is much smaller than that measured by the pan conversion method and the regional empirical C formula method. The cumulative evaporation of Lake Wuliangsuhai from the non-freezing period to the early glacial period converted from meteorological station data is 1333.5 mm. The total evaporation in the non-freezing period is 2.77~3.68 × 108 m3, calculated by the lake area of 325 km2, while the evaporation calculated by the eddy station is 1.91 × 108 m3. In addition, the ET value measured by the cumulative C formula method was 424.2% higher than that of the model method and exceeded the storage capacity. Low-frequency and limited environmental index observations may lead to an overestimation of the real lake evaporation. Therefore, in situ, high-frequency meteorological–water quality monitoring and the eddy method deserve more consideration in future research on lake evaporation.

Ecosystem CO2 Exchange and Its Environmental Regulation of a Restored Wetland in the Liaohe River Estuary

Coastal wetlands are important carbon sinks， and they contribute to reducing the effects of global warming. This study used the eddy covariance method to detect the CO2 flux in the restoration wetland of the Liaohe River estuary in 2021 and investigate the characteristics of ecosystem CO2 exchange and its environmental control factors. The aim was to assess the carbon source/sink capacity of salt marshes in the restored area and to provide data support and theoretical basis for evaluating the effectiveness of ecological restoration projects. The study revealed "U" curves in spring and autumn， "V" curves in summer， and horizontal lines in winter for the average daily variation curve of net ecosystem CO2 exchange （NEE） in the restored area. Its carbon sink efficiencies were -40.06， -63.62， 2.33， and 34.43 g·m-2 in the spring， summer， autumn， and winter， respectively. In the restored area， the daily cumulative variation in NEE was "V" shaped， and the monthly cumulative changes in NEE， ecosystem respiration （Reco）， and gross primary productivity （GPP） were obviously different. Photosynthetically active radiation （PAR） was an important regulation factor of daytime NEE in the restored area in 2021， and they displayed a rectangular hyperbolic relationship. PAR could explain 53% of the variation in the daytime NEE. Air temperature （Ta） was the main control factor of Reco，night， and there was an exponential relationship between them. When Ta < 5.5 ℃， the temperature sensitivity of ecosystem respiration （Q10） was 2.19， and Ta could explain 42% of the variation in the Reco，night； when Ta ≥ 5.5 ℃， the Q10 was 1.81， and Ta could explain 51% of the variation in the Reco，night. Additionally， there were significant linear negative correlations between NEE and both soil water content （SWC） and vapor pressure deficit （VPD）， whereas NEE was not significantly correlated with soil temperature （Ts） or relative humidity （RH）. In 2021， the restored wetland in the Liaohe River estuary acted as a CO2 sink， and the total net carbon sequestration was -66.89 g·m-2. The restored salt plays a role as an important carbon sink and has long-term carbon sequestration potential.

The Effectiveness of Logotherapy on Pain Coping Strategies/ Psychological Capital and Death Anxiety in women with Breast Cancer

Introduction: Breast cancer is one of the most challenging diseases in the world. The purpose of this study was to investigate the effectiveness of logotherapy on coping strategies for pain, psychological capital, and death anxiety in women with breast cancer. Materials and Methods: This was an applied and semi-experimental research with a pretest-posttest design and a control group. The statistical population included women referring to Zafar Medical Complex in Karaj city, among whom 30 women with breast cancer were selected by non-random sampling method. The samples were divided into two experimental and control groups using the multivariate covariance method after applying inclusion and exclusion criteria. Having obtained written consent from the participants, they filled out questionnaires of Rosenstein's Pain Coping Strategies, Luthans' Psychological Capitals, and Templer's Death Anxiety at the pre-test stage. Following that, the experimental group was trained in Blair's logotherapy protocol for 10 sessions. The control group did not receive any intervention. Both groups completed the questionnaires once more during the post-test stage. The data was analyzed in SPSS-22 software using a multivariate covariance test. Results: Data analysis after logotherapy showed a significant difference in the test group, including pain coping strategies (returning attention, P=14.667; reinterpretation of pain, P=6.248; self-talk, P=0.0001; invisibility of pain, P=0.002; disaster, P=0.002; prayer-hope, P=0.004; psychological capitals, P=0.0001; and death anxiety, P=0.51) compared to the investigated variables in the control group. Moreover, the results of the covariance in the test group demonstrated a significant difference in the mean scores before and after logotherapy in coping strategies with pain, including returning attention (8.47±1.278), reinterpretation of pain (11.40 ± 11.120), self-talk (20.27 ± 2.183), invisibility of pain (9.93 ± 0.796), catastrophizing (13.53 ± 1.641), prayer hope (14.00 ± 1.418), psychological capitals (54.33 ± 1.968), and death anxiety (0.859 ± 9.40) (P<0.05). However, no significant difference was observed in the control group in this regard. The value of eta showed that 64% of the changes in psychological capital, 54% of the changes in returning attention, 36% of the changes in the reinterpretation of pain, 61% of self-talk changes, 59% of pain-ignoring changes, 34% of catastrophizing changes 53% of changes in prayer-hope, 52% of changes in activity ability and 51% of changes in death anxiety were due to the effect of treatment. Conclusion: Logotherapy proves to be efficacious in aiding women with breast cancer in managing strategies related to coping with psychological strength and fear of death.

Compilation of an Integrated Therapy Model Based on Compassion-Focused Therapy, Integrated Islamic Therapy and Therapy Based on Acceptance and Commitment and Its Effectiveness on Life Satisfaction of Depressed Married Women in Yazd City

Introduction: As a large part of society who experience different restrictions according to different cultural, historical and social situations, women face difficult emotional conditions during marriage. This research is conducted with the aim of developing a combination treatment model based on compassion-focused therapy, integrated Islamic therapy, and therapy based on acceptance and commitment and its effectiveness on life satisfaction of depressed married women in Yazd city in 1400.
 Methods: The research method was a combination of an exploratory design with a compilation and classification approach. The first stage was done qualitatively and based on a descriptive phenomenological strategy. In the qualitative part of the research, a combination treatment protocol based on the approach of combining psychotherapies by Stricker (2006) was compiled and validated. In the quantitative (second) part, based on convenience sampling, 30 depressed married women were selected, and then, through a quasi-experimental method with a pre-test and post-testregarding the two test groups and proof, the effectiveness of the developed protocol on their life satisfaction was assessed. The statistical population of the research included all the women who referred to counseling centers in Yazd city, for whom the diagnosis of depression (Beck Depression Scale) was given. In order to measure people's life satisfaction, Diener's life satisfaction scale was used. In order to analyze the quantitative data of the research, the analysis of covariance method was used.
 Results: After extracting 11 main categories, a unified treatment protocol was formulated according to the findings. For validation, ratio coefficients and content validity index were used. The coefficients in all items were higher than 0/79 for CVI index and higher than 0./56 for CVR index.
 Conclusion: The results of the analysis of the findings showed that integrated psychotherapy based on self-discipline approach, integrated Islamic treatment approach, and treatment approach based on acceptance and commitment increase life satisfaction of depressed married women in Yazd city.

Population pharmacokinetics of rotigotine extended-release microspheres for intramuscular injection in patients with early-stage Parkinson's disease.

Rotigotine extended-release microspheres is a weekly intramuscular injection formulation to treat Parkinson's disease. This study aimed to develop a population pharmacokinetics (PK) model for rotigotine extended-release microspheres to investigate its PK ethnic differences. Data for the study were obtained from three studies in China, Japan and the US. The population PK model was developed using the Phoenix NLME 8.3.5 software. Two parallel absorption models were created to include both zero- and first-order absorptions. The elimination phase was evaluated for one- and two-compartment linear models. Moreover, covariates including sex, body weight, body mass index, albumin, creatinine clearance and race were input into the model using a stepwise covariate method. We constructed a one-compartment linear model with the first parallel absorption model identified as the best-fitting model. Simulation results in patients with lighter body weight (45 kg) exhibited a 27% increase in Cmax,ss and a 31% increase in AUCtau,ss compared to those with median body weight (65 kg). Patients with heavier body weight (103 kg) showed a 27% decrease in Cmax,ss and a 29% decrease in AUCtau,ss compared to the median body weight group. Asian patients displayed only a 21% increase in Cmax,ss and a 6% increase in AUCtau,ss compared to non-Asian. While we could not fully conclude that race does not affect rotigotine exposure, dosage adjustments based on race were not deemed necessary. Exposure differences were mainly attributed to body weight, while dose adjustments were not needed for patients of different racial identities.

A Beginner's Guide to Eddy Covariance: Methodology and Its Applications to Photosynthesis.

The eddy covariance technique, commonly applied using flux towers, enables the investigation of greenhouse gas (e.g., carbon dioxide, methane, nitrous oxide) and energy (latent and sensible heat) fluxes between the biosphere and the atmosphere. Through measuring carbon fluxes in particular, eddy covariance flux towers can give insight into how ecosystem scale photosynthesis (i.e., gross primary productivity) changes over time in response to climate and management. This chapter is designed to be a beginner's guide to understanding the eddy covariance method and how it can be applied in photosynthesis research. It introduces key concepts and assumptions that apply to the method, what materials are required to set up a flux tower, as well as practical advice for site installation, maintenance, data management, and postprocessing considerations. This chapter also includes examples of what can go wrong, with advice on how to correct these errors if they arise. This chapter has been crafted to help new users design, install, and manage the best towers to suit their research needs and includes additional resources throughout to further guide successful eddy covariance research activities.

Examining the Effectiveness of Emotional Intelligence Training on Alexithymia Components in Students

Objective: Emotional intelligence is the most crucial factor in decision-making and the selection of future goals, as well as the substitution of goals in various situations and circumstances. The purpose of this article was to determine the effectiveness of emotional intelligence training on alexithymia components in students. Methods and Materials: This study was applied, quantitative, and of a quasi-experimental pre-test - post-test design with a control group and training. The population consisted of 30 students suffering from alexithymia, selected from 5 treatment centers, with 15 students allocated to the control group and 15 to the training group. The data collection tool in this research was the Toronto Alexithymia Scale (TAS-20), and Goleman's (1996) emotional intelligence training protocol was used for the experimental group. Data were analyzed using SPSS software and multivariate analysis of covariance method. Findings: The F-value in the univariate analysis of covariance for the subscale of identifying emotions (F=13.266, P=0.000), for the subscale of describing emotions (F=19.917, P=0.000), and for the subscale of external-oriented thinking (F=11.108, P=0.000) were significant. These findings indicate that there is a significant difference between the emotional intelligence training group and the control group in the dependent variables (alexithymia components). Conclusion: It can be concluded that the use of emotional intelligence training is beneficial for improving alexithymia in students with learning disabilities.

Impact of manager’s motivation on fraudulent accounting: An empirical study

This study empirically examines the motives of Indian firms’ managers to violate Generally Accepted Accounting Principles (GAAP) and engage in so-called fraudulent accounting. Managers’ motivations for fraudulent accounting rather than profit adjustment are empirically analyzed using data from Indian-listed companies. The sample includes 91 firms and the period of study is March 2001 to March 2022. The tests were conducted using single and multiple variables by the empirical methods used in other studies on profit adjustment. In the case of single variables, the tests are the chi-square test of independence for dummy variables and the significance test of the difference between the mean and median for continuous variables. In the case of multiple variables, the sample firms with a dependent variable of 1 and the control firms with a dependent variable of 0 are analyzed using the logit model. The estimation is done by the robust covariance method. The findings indicate that firms that engage in fraudulent accounting are significantly worse off than other firms in terms of their financial position and operating results, have significantly higher financing needs, and significantly more frequently conduct initial public offerings (IPOs).

The effectiveness of the stroke sign by sticker: Enhancing stroke knowledge among village health volunteers in community care.

Stroke is a global and Thai concern. Village Health Volunteers (VHVs) are vital in community healthcare but lack stroke knowledge. Prior efforts to improve their knowledge were ineffective. The "Stroke Sign by Sticker" application was created to enhance VHV literacy. To evaluate the effectiveness of the "Stroke Sign by Sticker" line application in enhancing stroke awareness among VHVs. The study was conducted in a health community setting using a quasi-experimental design. The study was conducted within a healthcare community in Thailand. The "Stroke Sign by Sticker" mobile application was developed specifically for the LINE platform. The knowledge scores were measured using a tool that demonstrated a high validity coefficient of. 93. The intervention itself lasted for 3 weeks. The entire process, from the development of the mobile application to the assessment of its effectiveness, took place during the period of 2021-2022. The R program was used to implement the analysis of covariance method for adjusting pretest scores as a covariate. A total of 60 participants were included, with half assigned to the experimental group and the other half to the control group. The post-test knowledge scores were the main outcome measure of interest. The results showed a significant effect of the independent variable, with the experimental group exhibiting a higher mean knowledge score compared to the control group (F = 24.26, P < .001). The "Stroke Sign by Sticker" line application demonstrated its effectiveness in promoting stroke knowledge among VHVs, underscoring its potential as a valuable tool for health promotion and education within healthcare settings.