Variance Ratio Research Articles

Classification of sugarcane areas in Landsat images using machine learning algorithms

Monitoring sugarcane areas through remote sensing is essential for planning and management of the national sugarcane industry. The use of machine learning algorithms has provided many benefits to remote sensing. This article aims to compare the prediction quality of three important machine learning methods in identifying sugarcane areas using Landsat images: Logistic Regression (LR), Decision Tree (DT) and RandomForest (RF). LR was applied in three versions: LR without penalization, LR with Ridge penalization (LR-R) and LR with Lasso penalization (LR-L). Data obtained in this study refer to a region of approximately 306,000 ha located in the state of São Paulo, Brazil, which was segmented into approximately 46,000 polygons (observations). Six spectral bands and vegetation indices observed along 17 months resulted in 102 covariates, which were reduced via Principal Component Analysis (PCA). In total, 19 Principal Components were chosen to account for 94.61% of the cumulative explained variance ratio and were used in machine learning methods to classify each polygon as sugarcane or other land covers. The method with the highest accuracy considering testing sample of 20% of data was RF (78.51%), followed by DT (72.30%), LR-L (69.64%), LR-R (69.64%), and LR (69.52%).

Решение оптимизационной задачи оценивания моделей полносвязной линейной регрессии

<p>This article is devoted to the problem of estimating fully connected linear regression models using the maximum likelihood method. Previously, a special numerical method was developed for this purpose, based on solving a nonlinear system using the method of simple iterations. At the same time, the issues of choosing initial approximations and fulfilling sufficient conditions for convergence were not studied. This article proposes a new method for solving the optimization problem of estimating fully connected regressions, similar to the method of estimating orthogonal regressions. It has been proven that, with equal error variances of interconnected variables, estimates of b-parameters of fully connected regression are equal to the components of the eigenvector corresponding to the smallest eigenvalue of the inverse covariance matrix. And if the ratios of the error variances of the variables are equal to the ratios of the variances of the variables, then the b-parameter estimates are equal to the components of the eigenvector corresponding to the smallest eigenvalue of the inverse correlation matrix, multiplied by the specific ratios of the standard deviations of the variables. A numerical experiment was carried out to confirm the correctness of the developed mathematical apparatus. The proposed method for solving the optimization problem of estimating fully connected regressions can be effectively used when solving problems of constructing multiple fully connected linear regressions.</p>

Foundation and evaluation of a diagnosis and recommendation integrated system for star apple (Chrysophyllum cainito L.)

Diagnosis and recommendation integrated system (DRIS) is a greatly accurate and reliable mean of evaluating the exact nutrition status of crops via foliar analysis. DRIS has been applied to many types of crops, but DRIS has not been established for and applied to star apple, which is an important fruit in many countries. Therefore, this study aims to (i) detect soil obstacles in star apple cultivation, (ii) create a DRIS for star apple, and (iii) apply the created DRIS norms to evaluate the macro-nutrition status of star apple. In total, 90 leaf samples were obtained from 90 different star apple farms, where 90 soil samples were also collected. The soil analysis results revealed that concentrations of available nitrogen and soluble phosphorus were low and medium, indicating a high risk of reduction in star apple yield. The average yield of star apple was 200.0 kg plant−1. The high-yielding group had higher concentrations of N, K, and Mg in the leaf than the low-yielding group; however, the concentrations of Fe and Mn in the leaf were opposite, and the concentrations of P, Ca, Cu, and Zn were equivalent in the two groups. The DRIS norms have been established for star apple with 28 nutrient ratio pairs and consisted of means, coefficients of variation, variances (S2), and variance ratios (S2 l/S2 h), whose values were 0.136–182.6, 21.0–69.5%, 0.0024–10400.9, and 1.89–34.3, respectively. The results of applying the DRIS norms revealed that the nutrient status of star apple was deficient of N, K, and Mg.

Tau-Cell-Based Analog Silicon Retina With Spatio- Temporal Filtering and Contrast Gain Control.

Developing precise artificial retinas is crucial because they hold the potential to restore vision, improve visual prosthetics, and enhance computer vision systems. Emulating the luminance and contrast adaption features of the retina is essential to improve visual perception and efficiency to provide an environment realistic representation to the user. In this article, we introduce an artificial retina model that leverages its potent adaptation to luminance and contrast to enhance vision sensing and information processing. The model has the ability to achieve the realization of both tonic and phasic cells in the simplest manner. We have implemented the retina model using 0.18 μm process technology and validated the accuracy of the hardware implementation through circuit simulation that closely matches the software retina model. Additionally, we have characterized a single pixel fabricated using the same 0.18 μm process. This pixel demonstrates an 87.7-% ratio of variance with the temporal software model and operates with a power consumption of 369 nW.

Theoretical and experimental study of the spanwise effect of turbulence on the aerodynamic lift on a wing with different aspect ratios

In this paper, a combined theoretical and experimental study is carried out to investigate the spanwise effect of turbulence on the aerodynamic lift on a wing with different aspect ratios. The ratio of the mean square variance of the aerodynamic lift calculated by the commonly used strip theory and the two-wavenumber buffeting theory is analyzed comprehensively for the wings with different aspect ratios in turbulence with various integral scales. To validate the theoretical analysis and achieve a deeper understanding of the spanwise effects of turbulence, wind tunnel experiments are performed on National Advisory Committee for Aeronautics 0015 airfoils in grid-generated turbulent flows with different integral scales. The results demonstrate that it is essential to use the two-wavenumber buffeting theory to account for the spanwise effect of turbulence when calculating the aerodynamic lifts on wings with small aspect ratios, especially when in small-scale turbulence. The deviations between the equivalent two-wavenumber coherence function and the spanwise effect influence function at low reduced streamwise wavenumbers are the underlying causes for spanwise effects of turbulence. To achieve reliable wind tunnel testing results, appropriate simulations of the ratio of the turbulence integral scale to the chord are very important in the measurements of aerodynamic lifts on finite-span wing sections, especially for those with small aspect ratios.

Comparative analysis of stochastic seasonality, January effect and market efficiency between emerging and industrialized markets

This study investigates whether there are significant differences in investment returns between emerging markets and industrialized markets in terms of stochastic seasonality, January effect and market efficiency. Data on investments, and returns for nine emerging countries and eleven industrialized countries spanning January 1990 to December 2020, were obtained from the Organization for Economic Cooperation and Development (OECD). The spectral nonparametric test was used to determine the presence of stochastic seasonality for each market while the regression test was used to determine the presence of January effect. In the case of determining the efficiency status of the markets, the variance ratio test and the runs test were used. In cases where there appeared to be differences between the two types of market, Fisher's exact test was used to verify such differences. The results show no significant differences between the two types of markets in terms of seasonality, January effect and efficiency statuses. Apart from Brazil which recorded stochastic seasonality, all others are not stochastically seasonal. In the case of the January effect, it was a mixed bag; five emerging markets had January effect while two industrialized markets had January effect.

Random walk tests for the MENA stock returns

Purpose — The current study seeks to understand whether individual stock returns exhibit random movement and are not dependent (efficient at weak form) on fourteen out of sixteen actively traded Arab stock markets in the Middle East and North Africa (MENA) region, based on the size of the market value.Method — Various non-parametric methods, including autocorrelation test, variance ratio test, Phillips-Perron unit root test, and runs test, are used to assess the random walk hypothesis for daily data following the Covid-19 vaccination program. This analysis covers the period from January 3, 2021, to March 28, 2023.Result — The study results present evidence that all individual stock returns deviate from random walk behavior. However, only Kuwait, Jordan, and Palestine stock returns follow the random walk based on the run test results at a significance level of 10%. Therefore, it can be concluded that all stock returns are inefficient at the weak-form, suggesting that investors have opportunities for unexpected gains.Practical implications — The findings of this study suggest that investors in the MENA region may have opportunities for unexpected gains, as individual stock returns deviate from random walk behavior, highlighting the importance of considering market dynamics and employing informed investment strategies. Additionally, policymakers could benefit from understanding the inefficiencies in stock returns to implement measures that promote market stability and efficiency.

White analytical insight for sensitive fluorescent determination of semaglutide and tirzepatide in pharmaceuticals and biological matrices

The present study is focused on the sensitive determination of newly FDA-approved glucagon-like-peptide agonists semaglutide (SEM) and tirzepatide (TIR). Direct, selective and label-free spectrofluorometric method was proposed and validated (according to ICH guidelines) for determination SEM and TIR in their pure form, newly approved pharmaceuticals and spiked human plasma. The developed method was based on measuring the native fluorescence of SEM and TIR in ethanol at 294.8 and 303 nm after being excited at 216 and 225 nm for SEM and TIR in order. The method sensibility allowed the quantification of both drugs in nano-scale up to 10 ng/mL. Several experimental variables including solvent type, surfactant, and pH were optimized after several attempts to get the best sensitivity for both drugs. The mean recovery percentage of SEM was compared and found in agreement with the reported method using student’s t-test and the variance ratio F-test. Additionally, the greenness and whiteness profiles for this approach were evaluated using the GAPI, AGREE, and RGB algorithm; the positive results supported its use as great candidates for successful implementation in quality control labs and the pharmaceutical analysis companies.

Commodity Market Efficiency: New Evidence From the Russia-Ukraine War

We re-evaluate the efficiency of selected commodity markets during the Russia-Ukraine crisis using the asymptotic normal variance ratio test. We find that there is a substantial difference in the commodity prices before and after the war’s commencement. We also show that the markets are weak-form inefficient before and after the invasion except for gasoline and oats which became efficient during the war. We highlight the investment implications of the findings.

Characterization of the Ionospheric Vertical Error Correlation Lengths Based on Global Ionosonde Observations

AbstractData assimilation is one of the most important approaches to monitoring the variations of ionospheric electron densities. The construction of the background error covariance matrix is an important component of ionospheric data assimilations. To construct the background error covariance matrix, the information about the spatial ionospheric correlations is required. We present a statistical analysis on the ionospheric vertical error correlation length (VCL) based on a global network of ionosondes and the Neustrelitz Electron Density Model. We show that the locally derived VCL is well‐defined and the VCL does not show a considerable dependency on the geographical seasons while local time dependencies of the VCL are shown to be present. A novel VCL model is also established based on the ionospheric scale heights. We show that the ionospheric VCL can be characterized by the variance ratio between the ionosphere model and ionospheric measurements. The altitudinal variations of VCLs are controlled by the interactions between the inherent VCLs of the ionosphere model and the measurements. Two experiments are conducted at two different latitudes based on the proposed model. The results show that the proposed model is stable and well‐correlated with the observed VCLs, which implies a potential to be generalized for a global correlation model. The proposed model can be used in the temporal evolution of error covariance matrices in the ionospheric 4D‐Variational (4D‐Var) assimilations, which may overcome the main drawbacks of the static error covariance specifications in the ionospheric 4D‐Var assimilations.

Digital and Social-Civic Skills in Future Primary Education Teachers: A Study from the Didactics of Social Sciences for the Improvement of Teacher Training in Competences

The use of technology, especially among young people, is providing new possibilities, including in the academic field, and requires teacher training through the development of skills and competences. At this point, Social Science Didactics plays a fundamental role, as it prepares future teachers to teach social knowledge in order to achieve useful and meaningful learning for students and society. Using an online questionnaire, structured with the Likert scale, which had previously been validated and published by Professors Peart, Gutiérrez-Esteban, and Cubo-Delgado, 156 students of the Degree in Primary Education of the subject Didactics of Social Sciences at the University of Granada (Spain) participated (academic year 2023–2024), with the aim of investigating the digital and socio-civic competences of trainee teachers in order to seek ways to improve their training. The results were processed in the IBM SPSS Statistics 25 programme, carrying out a descriptive statistical analysis, considering the mode and the variance ratio. The participating students mainly use digital environments to communicate with acquaintances and, although they know and value a democratic society, they do not exercise their citizenship on the Internet. This makes it even more necessary to train future teachers in digital competences, based on digital and socio-civic skills, as only in this way will they be able to train citizens capable of facing the challenges of the knowledge society.

Market sentiment and price dynamics in weak markets: A comprehensive empirical analysis of the soybean meal option market

AbstractThis study addresses key issues of market efficiency in weak global futures markets, focusing on the intricate relationship between market sentiment and options pricing. Employing rolling variance ratio tests and information‐sharing models for market dynamics analysis, and supplemented with Granger causality tests and impulse response findings, it reveals a significant, unidirectional impact of market sentiment on options pricing, especially during periods of heightened sentiment. These insights underscore the importance of considering time dynamics in market behavior analysis, offering a novel perspective on futures and options market understanding.

Impact of the combination and replacement of SLR-based low-degree gravity field coefficients in GRACE solutions

GRACE and GRACE Follow-On (FO) missions provide time-variable gravity field models of unprecedented quality that allow for the hydrological, oceanic, and ice mass change studies on a global scale. However, the very low-degree coefficients derived from GRACE and GRACE-FO are of inferior quality due to thermal effects acting on satellites and malfunctioning of the onboard accelerometers. Therefore, C20 and C30 coefficients describing the Earth’s oblateness and the pear shape of the Earth, respectively, are being replaced by values derived from satellite laser ranging (SLR) in the standard GRACE solutions. This study assesses the impact of the replacement of low-degree gravity field coefficients in GRACE/GRACE-FO solutions by SLR data on the trend and seasonal signals of ice mass changes in Greenland and Antarctica. We found that the replacement of the low-degree gravity field coefficients changes the estimates of trends by 4, 8, and 22 Gt/year in Greenland, West, and East Antarctica, respectively, depending on the source of SLR coefficients and period for which the coefficients are replaced. In SLR and GRACE solutions, all coefficients of the same order and the same parity of degrees are strongly correlated. Therefore, replacing only two selected coefficients may lead to a biased solution. Thus, we propose to combine GRACE with SLR solutions up to a degree and order 10 × 10 to properly consider the sensitivity of each of the techniques to gravity field coefficients, instead of replacing two coefficients from SLR in GRACE solutions. The combined solution reduces the residual trend of post-glacial rebound from 1.2 to 0.9 Gt/year and from − 57.8 to − 57.0 Gt/year in Scandinavia and South Canada, respectively, when compared to GRACE/GRACE-FO solutions with the replacement of coefficients. The SLR-GRACE combination reduces the noise in the GRACE/GRACE-FO solutions by 8%, from 38 to 35 Gt, in the Fennoscandia region. In the periods when GRACE is at the end of its mission and observations are disrupted, the weights adjust the contribution from SLR and GRACE based on relative ratio of variances from each techniques. Thus, the combined solutions are more consistent with independent geophysical models of glacial isostatic adjustment, and the combinations are affected by smaller noise than the standard GRACE solutions and properly account for different sensitivities of SLR and GRACE techniques to low-degree time-variable gravity field coefficients.

A residual‐based nonparametric variance ratio no‐cointegration test

It is prominently stated in the literature that local asymptotic power properties serve as a useful indicator for the performance of residual‐based no‐cointegration tests in finite samples. However, this article comes to an opposing conclusion. In particular, we show that Breitung's (2002, Journal of Econometrics 108, 343–363) nonparameteric variance ratio unit root test applied to regression residuals serves as a no‐cointegration test but is inferior to its competitors from a local asymptotic power perspective. Nevertheless, in finite samples, the variance ratio test has good size properties, competitive power, and the convenience of being tuning parameter free. In general, we find that short‐run dynamics in the error process can have considerably larger detrimental effects on the performance of residual‐based no‐cointegration tests in finite samples than changes in the only nuisance parameter affecting local asymptotic power of the tests. The results serve as a warning for practitioners and lead to interesting directions for future research.

The Estimation of Cuscus Population and Distribution in Teluk Wondama District, West Papua Province, Indonesia

Cuscus is a marsupial mammal endemic to the eastern part of Indonesia. Populations and their habitats are under pressure due to economic development, population growth and utilization of forest resources. So far, studies on cuscus ecology have mainly focused on protected habitats or conservation areas, this study aims to identify and analyze populations and predict the distribution of cuscus in non-protectes area which is PT Wijaya Sentosa. This research conduct in November 2020 until January 2021 in several land cover categories. The methods used in this study include literature and secondary data studies, field observations using strip-transect and camera trap techniques, interviews using purposive sampling techniques. This study found nine individuals of cuscus from direct observation with strip-transects and two individuals of cuscus from camera trapping. The ground cuscus population (P. gymnotis) had the highest abundance and density, while the common spotted cuscus (S. maculatus) population owned the lowest values. The population structure dominates by male sex and adult age class, and no female sex and young age class were found. Cuscus was more commonly found solitary in the line of observation and not found in every line. The shape of the distribution pattern of the cuscus population at PT Wijaya Sentosa is cluster/aggregated, determined from the value of the dispersion index and the ratio of variance to mean. The most common ground cuscus was found in the 2018 and the 2013 logging area (LOA).

Development of a green synchronous spectrofluorimetric technique for simultaneous determination of Montelukast sodium and Bilastine in pharmaceutical formulations

For the treatment of rhinitis and asthma, a combination of Montelukast sodium and Bilastine has just been approved. Based on the first derivative of synchronous fluorescence, the current work developed a green, highly accurate, sensitive, and selective spectroscopic approach for estimating Montelukast sodium and Bilastine in pharmaceutical dosage form without previous separation. The selected technique focuses on measuring the synchronized fluorescence of the studied medications at a fixed wavelength range (Δλ) = 110 nm, and using the amplitude of the first derivative's peak at 381 and 324 nm, for quantitative estimation of Montelukast sodium and Bilastine, respectively. The impacts of different factors on the referred drugs' synchronized fluorescence intensity were investigated and adjusted. The calibration plots for were found to be linear over concentration ranges of 50–2000 ng mL−1 for Montelukast sodium and 50–1000 ng mL−1 for Bilastine. Montelukast sodium and Bilastine have LODs of 16.5 and 10.9 ng mL−1, respectively. In addition, LOQs were: 49.9 and 33.0 ng mL−1, for both drugs, respectively. The developed method was successfully employed to quantify the two drugs in synthetic tablets mixture and in laboratory prepared mixtures containing varied Montelukast and Bilastine ratios. To compare the results with the published analytical approach, a variance ratio F-test and a student t-test were used, which revealed no significant differences.

The sensitivity of risk premiums to the elasticity of intertemporal substitution

AbstractThis paper incorporates reference‐dependent preferences into a consumption‐based asset pricing model featuring Epstein–Zin utility. Three relevant results emerge from this extension. First, agents prefer the late resolution of uncertainty in recursive utility. Second, the late resolution of uncertainty helps replicate the downward‐sloping term structure of market excess return. Third, the intertemporal substitution elasticity is more sensitive to asset prices through increasing precautionary saving motivations. A closed‐form solution for the proposed model largely explains (i) high, volatile, and countercyclical equity premiums; (ii) low risk‐free rates; and (iii) the downward‐sloping term structure of equity premiums and variance ratios.

Weather types for the seasonal transitions in Central America

Unsupervised learning techniques are employed to study the relationship between atmospheric circulation and precipitation over Central America and its surrounding areas. Specifically, the clustering algorithm k-means++ is applied to three coarse-grained datasets from ERA-interim reanalysis that are the candidates for representing the atmospheric state vector, each candidate contains its full temporal variability. Datasets are composed of: a) wind fields at 925, 800 and 200 hPa, b) same as “a)” plus convective available potential energy and c) same as “a)” plus total column water vapor. Clustering metrics, namely the variance ratio criterion, the silhouette criterion and the mean squared error, are computed to quantify clustering quality. Clusters are interpreted as weather types, recurrent configurations of the atmospheric state vector associated with observable weather states. The correct number of clusters for each dataset is determined with a Monte Carlo test of normality, to assure cluster existence. The main objective is to obtain a set of weather types containing elements that characterize the transition from and to the rainy season over the Pacific side of Central America as well as other elements of the seasonal cycle of regional precipitation, such as the Mid-Summer Drought. Besides the statistical metrics, in order to select between candidate datasets and plausible number of clusters, focus is given to the temporal characteristics of the clusters. Existing literature does not provide a set of weather types suitable to analyze seasonal transitions and the differences in the mechanisms associated with rainfall maxima.

Facial Surface Electromyography: A Novel Approach to Facial Nerve Functional Evaluation after Vestibular Schwannoma Surgery.

Vestibular schwannoma (VS) surgery may cause facial nerve damage. However, a comprehensive evaluation of post-operative facial outcomes may be difficult to achieve. Surface electromyography (sEMG) is a promising non-invasive evaluation tool. However, its use in the follow-up after VS surgery has not been reported yet. The main objective was to develop and validate a new sEMG application specifically for the post-VS surgery setting. Secondary goals were to provide a systematic description of facial muscle activity after VS surgery and assess the association between sEMG parameters and Sunnybrook scale scores. Thirty-three patients with facial palsy following VS surgery were included. The clinical outcomes (Sunnybrook symmetry, movement, and synkinesis scores) and sEMG parameters (signal amplitude normalized by the maximal voluntary contraction (NEMG) and sEMG synkinesis score (ESS, number of synkinesis per movement sequence)) were evaluated at the end of the follow-up. In all tested muscles, NEMG variance was significantly higher on the affected side than the contralateral (variance ratio test, p < 0.00001 for each muscle). In total, 30 out of 33 patients (90.9%) showed an ESS ≥ 1 (median: 2.5, IQR: 1.5-3.0). On the affected side, NEMG values positively correlated with both dynamic and overall Sunnybrook scores (Spearman's model, p < 0.05 for each muscle, except orbicularis oculi). ESS significantly correlated with the Sunnybrook synkinesis score (Spearman's rho: 0.8268, p < 0.0001). We described and preliminarily validated a novel multiparametric sEMG approach based on both signal amplitude and synkinesis evaluation specifically for oto-neurosurgery. Large-scale studies are mandatory to further characterize the semiological and prognostic value of facial sEMG.

Current evidence on the efficacy of mental health smartphoneapps for symptoms of depression and anxiety. A meta-analysis of 176 randomized controlled trials.

The mental health care available for depression and anxiety has recently undergone a major technological revolution, with growing interest towards the potential of smartphone apps as a scalable tool to treat these conditions. Since the last comprehensive meta-analysis in 2019 established positive yet variable effects of apps on depressive and anxiety symptoms, more than 100 new randomized controlled trials (RCTs) have been carried out. We conducted an updated meta-analysis with the objectives of providing more precise estimates of effects, quantifying generalizability from this evidence base, and understanding whether major app and trial characteristics moderate effect sizes. We included 176 RCTs that aimed to treat depressive or anxiety symptoms. Apps had overall significant although small effects on symptoms of depression (N=33,567, g=0.28, p<0.001; number needed to treat, NNT=11.5) and generalized anxiety (N=22,394, g=0.26, p<0.001, NNT=12.4) as compared to control groups. These effects were robust at different follow-ups and after removing small sample and higher risk of bias trials. There was less variability in outcome scores at post-test in app compared to control conditions (ratio of variance, RoV=-0.14, 95% CI: -0.24 to -0.05 for depressive symptoms; RoV=-0.21, 95% CI: -0.31 to -0.12 for generalized anxiety symptoms). Effect sizes for depression were significantly larger when apps incorporated cognitive behavioral therapy (CBT) features or included chatbot technology. Effect sizes for anxiety were significantly larger when trials had generalized anxiety as a primary target and administered a CBT app or an app with mood monitoring features. We found evidence of moderate effects of apps on social anxiety (g=0.52) and obsessive-compulsive (g=0.51) symptoms, a small effect on post-traumatic stress symptoms (g=0.12), a large effect on acrophobia symptoms (g=0.90), and a non-significant negative effect on panic symptoms (g=-0.12), although these results should be considered with caution, because most trials had high risk of bias and were based on small sample sizes. We conclude that apps have overall small but significant effects on symptoms of depression and generalized anxiety, and that specific features of apps - such as CBT or mood monitoring features and chatbot technology - are associated with larger effect sizes.