Gap Estimates Research Articles

First principles approach and experimental exploration of a new double perovskite phase Sr2(In0.33 Sn0.33Sb0.33)2O6: evaluation of structural, optical, and dielectric properties.

A new double perovskite phase, Sr2(Sn0.33Sb0.33In0.33)2O6, was successfully synthesized via a solid-state reaction and comprehensively characterized using both experimental and theoretical techniques. Powder X-ray diffraction was used to determine the crystal structure, while scanning electron microscopy (SEM) revealed a high degree of densification and uniform grain distribution across the ceramic. Raman and Fourier-transform infrared (FTIR) absorption spectra of the powder present broad bands predominantly due to different stretching modes of the various SnO3 2-, InO3 2- and SbO3 2- octahedra in the region ν = 400-800 cm-1. An analysis of the UV-Vis diffuse reflectance spectrum shows excellent optical transparency and gives an estimation of an optical gap E g ∼ 3.6 eV on bulk Sr2(Sn0.33Sb0.33In0.33)2O6, making this material a promising candidate for optoelectronic devices. Density Functional Theory calculations further validated the experimental findings, confirming the crystal structure and providing insight into the electronic and vibrational properties. Impedance spectroscopy revealed non-Debye dielectric relaxation and confirmed typical negative temperature coefficient of resistance (NTCR) behavior, underscoring the material's potential for temperature-sensing applications. The primary conduction mechanism, modeled as correlated barrier-hopping (CBH), was complemented by an Arrhenius-type process with activation energies of 0.33 eV and 0.9 eV across two distinct temperature ranges.

Micro-Founded Output Gap Estimations with Business Tendency Survey Data

Micro-Founded Output Gap Estimations with Business Tendency Survey Data

Sonochemical synthesis of New Thiazolidin-4-one derivatives as potent anticancer and antimicrobial agents with Docking design, and Energy gap estimation

Thiazolidin-4-ones have important biological features, which has led to the development of new derivatives employing an efficient ultrasonic method. Schiff base derivatives were synthesized by condensation of 4,4′-diaminophenylmethane with various substituted benzaldehyde. These derivatives are subsequently subjected to cyclization, leading to the formation of thiazolidine-4-ones with favorable yields. The synthesized compounds were characterized using various analytical techniques such as FT-IR, 1H and 13C NMR, HRMS spectroscopy, and CHNS analysis. Thiazolidin-4-ones demonstrated anticancer potential with percentage cell viability at different concentrations (1mM, 3mM, and 5mM) and cell toxicity (1mM, 3mM, and 5mM). The IC50 values of compound 4g were found to be (72.27±1.39, 67.28±1.63, and 63.22±1.82), (36.77±0.11, 32.71±0.31, and 32.71±0.31), and 10.77±0.95, respectively. It is a good result according to the standard. The tested compounds demonstrated remarkable antimicrobial efficacy against bacterial strains like Staphylococcus aureus, Escherichia coli, and the fungal strain Candida albicans. The Minimum Inhibitory Concentrations (MIC) of compound 4g against Staphylococcus aureus, Escherichia coli, and Candida albicans were found to be 0.50±0.027, 0.70±0.040, and 0.80±0.036, respectively, which are comparable to reference medications. Docking design was conducted with the Staphylococcus aureus MurB protein (ID Code: 1HSK) and Novel CDK-5 inhibitor EFP crystal structure with CDK-2 (ID Code: 3IG7) for colon carcinoma HT29. Finally, the energy gaps were estimated by calculating HUMO and LUMO energy levels using the DFT/B3LYP method with the 6-31 G (d, p) basis set.

Brain Age Estimation on a Dementia Cohort Using FLAIR MRI Biomarkers.

The prodromal stage of Alzheimer's disease presents an imperative intervention window. This work focuses on using brain age prediction models and biomarkers from FLAIR MR imaging to identify subjects who progress to Alzheimer's disease (converting mild cognitive impairment) or those who remain stable (stable mild cognitive impairment). A machine learning model was trained to predict the age of normal control subjects on the basis of volume, intensity, and texture features from 3239 FLAIR MRI volumes. The brain age gap estimation (BrainAGE) was computed as the difference between the predicted and true age, and it was used as a biomarker for both cross-sectional and longitudinal analyses. Differences in biomarker means, slopes, and intercepts were investigated using ANOVA and Tukey post hoc test. Correlation analysis was performed between brain age gap estimation and established Alzheimer's disease indicators. The brain age prediction model showed accurate results (mean absolute error = 2.46 years) when testing on held out normal control data. The computed BrainAGE metric showed significant differences between the stable mild cognitive impairment and converting mild cognitive impairment groups in cross-sectional and longitudinal analyses, most notably showing significant differences up to 4 years before conversion to Alzheimer's disease. A significant correlation was found between BrainAGE and previously established Alzheimer's disease conversion biomarkers. The BrainAGE metric can allow clinicians to consider a single explainable value that summarizes all the biomarkers because it considers many dimensions of disease and can determine whether the subject has normal aging patterns or if he or she is trending into a high-risk category using a single value.

BrainAGE as a measure of maturation during early adolescence

Abstract The Brain-Age Gap Estimation (BrainAGE) is an important new tool that purports to evaluate brain maturity when used in adolescent populations. However, it is unclear whether BrainAGE tracks with other maturational metrics in adolescence. In the current study, we related BrainAGE to metrics of pubertal and cognitive development using both a previously validated model and a novel model trained specifically on an early adolescent population. The previously validated model was used to predict BrainAGE in two age bands, 9-11 and 10-13 years old, while the novel model was used with 9-11 year olds only. Across both models and age bands, an older BrainAGE was related to more advanced pubertal development. The relationship between BrainAGE and cognition was less clear, with conflicting relationships across the two models. Additionally, longitudinal analysis revealed moderate to high stability in BrainAGE across early adolescence. The results of the current study provide initial evidence that BrainAGE tracks with some metrics of maturation, including pubertal development. However, the conflicting results between BrainAGE and cognition lead us to question the utility of these models for non-biological processes.

Is there hysteresis in potential output estimates?

Using an error correction model, this paper studies the dynamics of GDP and potential GDP using OECD's Economic Outlook and IMF's World Economic Outlook estimates of the output gap. The findings suggest the presence of hysteresis, implying that short-run shocks to GDP have sizeable permanent effects on potential GDP.

Lower cortical thickness and increased brain aging in adults with cocaine use disorder.

Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear. Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses. We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration. Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.

Large-Scale Nonconvex Optimization: Randomization, Gap Estimation, and Numerical Resolution

Large-Scale Nonconvex Optimization: Randomization, Gap Estimation, and Numerical Resolution

Blue-Noise-Based Disordered Photonic Structures Show Isotropic and Ultrawide Band Gaps

Spatially disordered but uniformly distributed point patterns characterized by so-called blue-noise long-range spatial correlations are of great benefit in computer graphics, especially in spatial dithering thanks to the spatial isotropy. Herein, the potential photonic properties of blue-noise disordered, homogeneous point processes based on farthest-point optimization are numerically investigated for silicon photonics. The photonic properties of blue-noise two-dimensional patterns are studied as a function of the filling fraction and benchmarked with photonic crystals with a triangular lattice. Ultrawide and omnidirectional photonic band gaps spanning most of the visible spectrum are found with estimates of gap–midgap ratios of up to 55.4% for transverse magnetic polarization, 59.4% for transverse electric polarization, and 32.7% for complete band gaps. The waveguiding effect in azimuthal defect lines is also numerically evaluated. These results corroborate the idea that long-range correlated disordered structures are helpful for engineering novel devices with the additional degree of freedom of spatial isotropy, and capable of bandgap opening even without total suppression of infinite-wavelength density fluctuations.

Automatic MRI volumetry in asymptomatic cases at risk for normal pressure hydrocephalus.

The occurrence of significant Alzheimer's disease (AD) pathology was described in approximately 30% of normal pressure hydrocephalus (NPH) cases, leading to the distinction between neurodegenerative and idiopathic forms of this disorder. Whether or not there is a specific MRI signature of NPH remains a matter of debate. The present study focuses on asymptomatic cases at risk for NPH as defined with automatic machine learning tools and combines automatic MRI assessment of cortical and white matter volumetry, risk of AD (AD-RAI), and brain age gap estimation (BrainAge). Our hypothesis was that brain aging and AD process-independent volumetric changes occur in asymptomatic NPH-positive cases. We explored the volumetric changes in normal aging-sensitive (entorhinal cortex and parahippocampal gyrus/PHG) and AD-signature areas (hippocampus), four control cortical areas (frontal, parietal, occipital, and temporal), and cerebral and cerebellar white matter in 30 asymptomatic cases at risk for NPH (NPH probability >30) compared to 30 NPH-negative cases (NPH probability <5) with preserved cognition. In univariate regression models, NPH positivity was associated with decreased volumes in the hippocampus, parahippocampal gyrus (PHG), and entorhinal cortex bilaterally. The strongest negative association was found in the left hippocampus that persisted when adjusting for AD-RAI and Brain Age values. A combined model including the three parameters explained 36.5% of the variance, left hippocampal volumes, and BrainAge values, which remained independent predictors of the NPH status. Bilateral PHG and entorhinal cortex volumes were negatively associated with NPH-positive status in univariate models but this relationship did not persist when adjusting for BrainAge, the latter remaining the only predictor of the NPH status. We also found a negative association between bilateral cerebral and cerebellar white matter volumes and NPH status that persisted after controlling for AD-RAI or Brain Age values, explaining between 50 and 65% of its variance. These observations support the idea that in cases at risk for NPH, as defined by support vector machine assessment of NPH-related MRI markers, brain aging-related and brain aging and AD-independent volumetric changes coexist. The latter concerns volume loss in restricted hippocampal and white matter areas that could be considered as the MRI signature of idiopathic forms of NPH.

Realistic Approach for Capacity Estimation of U-Turns Under Heterogeneous Traffic Condition

The main purpose of the present study is to estimate U-turn capacity at mid-block median openings (MBMO). Estimation of U-turn capacity requires three key parameters, namely: conflicting traffic volume, critical gap, and follow-up time. Conflicting traffic volume has been estimated by introducing a novel parameter, namely, spatiotemporal conflicting factor. Critical gap has been estimated using five different methods: modified Raff method, Ashworth method, logit model, occupancy time method, and support vector machine technique. The follow-up time has been estimated directly from recorded videos. Subsequently, capacity has been estimated for different types of vehicles along with the U-turning stream capacity. The estimated capacity has been validated using field capacity, using Kyte’s method. Further, a suitable method for the estimation of critical gap in the Indian context has been determined. This study could be used as a guideline for the U-turn capacity estimation for efficient design and management of traffic at MBMO.

Motherhood and the Gender Productivity Gap

Abstract Using Danish matched employer–employee data, I compare the relative pay of men and women to their relative productivity as measured by production function estimation. I find that the gender “productivity gap” is 8%, implying that almost two thirds of the residual gender wage gap is due to productivity differences between men and women. Motherhood plays an important role, yet it also reveals a puzzle: The pay gap for mothers is entirely explained by productivity, whereas the gap for non-mothers is not. In addition, the decoupling of pay and productivity for women without children happens during their prime-child bearing years. These estimates are robust to a variety of specifications for the impact of observables on productivity, and robust to accounting for endogenous sorting of women into less productive firms using a control-function approach. This paper also provides estimates of the productivity gap across industries and occupations, finding the same general patterns for mothers compared to women without children within these subgroups.

MRI BrainAGE demonstrates increased brain aging in systemic lupus erythematosus patients.

Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting multiple organs in the human body, including the central nervous system. Recently, an artificial intelligence method called BrainAGE (Brain Age Gap Estimation), defined as predicted age minus chronological age, has been developed to measure the deviation of brain aging from a healthy population using MRI. Our aim was to evaluate brain aging in SLE patients using a deep-learning BrainAGE model. Seventy female patients with a clinical diagnosis of SLE and 24 healthy age-matched control females, were included in this post-hoc analysis of prospectively acquired data. All subjects had previously undergone a 3 T MRI acquisition, a neuropsychological evaluation and a measurement of neurofilament light protein in plasma (NfL). A BrainAGE model with a 3D convolutional neural network architecture, pre-trained on the 3D-T1 images of 1,295 healthy female subjects to predict their chronological age, was applied on the images of SLE patients and controls in order to compute the BrainAGE. SLE patients were divided into 2 groups according to the BrainAGE distribution (high vs. low BrainAGE). BrainAGE z-score was significantly higher in SLE patients than in controls (+0.6 [±1.1] vs. 0 [±1.0], p = 0.02). In SLE patients, high BrainAGE was associated with longer reaction times (p = 0.02), lower psychomotor speed (p = 0.001) and cognitive flexibility (p = 0.04), as well as with higher NfL after adjusting for age (p = 0.001). Using a deep-learning BrainAGE model, we provide evidence of increased brain aging in SLE patients, which reflected neuronal damage and cognitive impairment.

Isotropic pressure induced structural, electronic, photocatalytic, elastic and mechanical properties of RbPbF3: GGA-PBE and HSE03 based computational estimation

The main objective of this study is to present a comprehensive computational analysis, with Generalized Gradient Approximations (GGA) and Heyd–Scuseria–Ernzerhof (HSE03) correlation functionals, of the structural, optoelectronic, photocatalytic and elastic properties of Rubidium Lead Fluoride (RbPbF3) under the systematic isotropic pressure range of 0–55 GPa. Under stress a systematic decrease in lattice parameters and band gap (4.869 eV − 1.105 eV) is observed upto 55 GPa. For comprehensive evaluation of band gap, PDOS and EPDOS have also been determined. Photocatalytic properties of RbPbF3 under stress demonstrate the best photocatalytic water-splitting potential, aligning with the band gap estimation. The significant variation in optical parameters is found with a varying stress array from 0–55 GPa. Optically this compound can be utilized as a UV detector because absorption bands are seen in the UV spectrum. The material exhibits mechanical stability, and ductile behavior, with ionic and covalent bonding. The anisotropic nature is observed in our estimated results.

Impact of Lu-Substitution in Yb14-xLuxZnSb11: Thermoelectric Properties and Oxidation Studies.

Yb14ZnSb11 is one of the newest additions to the high-performance Yb14MSb11 (M = Mn, Mg, and Zn) family of p-type high-temperature thermoelectric materials and shows promise for forming passivating oxide coatings. Work on the oxidation of rare earth (RE)-substituted Yb14-xRExMnSb11 single crystals suggested that substituting late RE elements may form more stable passivation oxide coatings. Yb14-xLuxZnSb11 (x = 0.1, 0.2, 0.3, 0.4, 0.5, and 0.7) samples were synthesized, and Lu-substitution's effects on thermoelectric and oxidation properties are investigated. The solubility of Lu within the system was found to be quite low with xmax ∼ 0.3; samples with x > 0.3 contained impurities of LuSb. Goldsmid-Sharp band gap estimations show that introducing Lu reduces the apparent band gap. Because of this, the Lu-substituted samples show a reduction in the maximum Seebeck coefficient, decreasing the high-temperature zT. This contrasts with the impact of Lu3+ substitution in Yb14MnSb11, where the addition of Lu3+ for Yb2+ results in increases in both resistivity and the Seebeck coefficient. Oxidation of the x = 0.3 solid solution was studied by thermogravimetric- differential scanning calorimetry , powder X-ray diffraction, scanning electron microscopy-energy-dispersive spectroscopy, and optical images. The samples show no mass gain before 785 K, and ensuing oxidation reactions are proposed. At the highest temperatures, significant amounts of Yb14-xLuxZnSb11 remained beneath an oxide coating, suggesting that passivation may be achievable in oxygen environments.

Corporate Income Tax Gap Estimation by using Bottom-Up Techniques in Selected Countries

Corporate Income Tax Gap Estimation by using Bottom-Up Techniques in Selected Countries

Inflation measurement in times of large consumption shifts – Evidence of the CPI bias from Poland

AbstractThe paper addresses the problem of inflation measurement and the way it is affected by the choice of CPI weights. We focus on the bias resulting from using weights reflecting the past structure of consumption and the choice of the plutocratic index. The study is based on a comparison of the official consumer price index in Poland with superlative indices. Contrary to most literature, our findings indicate an understatement of the CPI. Additionally, in 2020 due to large changes in the pattern of household consumption, the underestimation increased. This results from the increase in the expenditure on the relatively more expensive goods which could not be accounted for in real time. In general, the lack of overstatement in the Polish CPI may result from frequent adjustments in the weights used for the calculation of CPI and a faster-than-CPI rise in the prices of those goods and services for which demand is relatively inelastic. Additionally, we deliver the estimates of the plutocratic gap, which indicates that the use of the plutocratic weights in the calculation of CPI leads to a lower price index than its democratic equivalent.

Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate

AbstractA factor stochastic volatility model estimates the common component to output gap estimates produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. The output gap estimates are uncertain even well after the fact. Nevertheless, the common component is clearly procyclical, and positive innovations to the common component produce movements in macroeconomic variables consistent with an increase in aggregate demand. Heightened macroeconomic uncertainty, as measured by the common component's volatility, leads to persistently negative economic responses.

Widening rural–urban gap in life expectancy in China since COVID-19

IntroductionDisparities in life expectancy between rural and urban populations are well established but how it varies with epidemics and pandemics remains poorly understood. We aimed to quantify the rural–urban differences...

A semiconducting supramolecular novel Co(II)-metallogel based on 5-aminoisophthalic acid gelator: Toward efficient microelectronic device application

A novel ultrasonication method was successfully employed to prepare a metallogel using 5-aminoisophthalic acid as a low molecular weight gelator and cobalt(II)-acetate in N,N-dimethyl formamide at room temperature. Mechanical properties were analyzed through rheological analysis, microstructure through scanning electron microscopy and EDX mapping, and formation strategy via FT-IR and Raman spectroscopy. Crystalline nature was confirmed by PXRD analysis. The gel exhibited a strong semiconducting nature, supported by optical band gap estimation, electronic device characterization, and charge carrier mobility assessment. Remarkably high electron mobility, potentially surpassing reported metallogels, was observed.