Bias Dependence Research Articles

The effects of oxytocin administration on social and routinized behaviors in autism: A preregistered systematic review and meta-analysis

Oxytocin administration has demonstrated considerable promise for providing individualized support for autistic people. However, studies evaluating the effects of oxytocin administration on autistic characteristics have yielded inconsistent results. This systematic review and meta-analysis investigates the effect of oxytocin administration on social and routinized behaviors in autism using recently developed methods to accurately assess the potential impact of effect size dependency and publication bias. Our frequentist meta-analysis yielded a significant summary effect size estimate for the impact of oxytocin administration on social outcomes in autism (d = 0.22, p < 0.001). The summary effect size estimate for routinized behavior outcomes was not statistically significant (d = 0.14, p = 0.22), with a follow up test indicating that the effect size estimate was not either statistically equivalent (Z = −1.06, p = 0.2), assuming a smallest effect size of interest of 0.25. Frequentist and Bayesian assessments for publication bias, as well as results from Robust Bayesian meta-analysis of oxytocin effects on social outcomes in autism, indicated that summary effect sizes might be inflated due to publication bias. Future studies should aim to reduce bias by preregistering analysis plans and to increase precision with larger sample sizes.

Bias and Temperature Dependence of Radiation-Induced Degradation for SiC MOSFETs

Bias and Temperature Dependence of Radiation-Induced Degradation for SiC MOSFETs

Study of optical float-zone grown gallium oxide Schottky barrier diode

β−Ga2O3 based lateral Schottky barrier diodes are fabricated using Ni/Au as Schottky contact and Ti/Au as Ohmic contact. The Sn-doped β−Ga2O3 sample is grown by the optical float-zone technique. The effect of trenches, which are used for mesa isolation, on breakdown voltage is investigated. The device shows near-ideal characteristics in terms of built-in potential. The parasitic series and shunt resistances are extracted, and their dependency on temperature is established. Modeling of temperature-dependent reverse leakage current is demonstrated using the thermionic emission model, Poole–Frenkel emission model, and Fowler-Nordheim tunneling mechanism. The procedure to extract relevant parameters is explained in terms of bias and temperature dependency. The combined model shows excellent agreement with experimental data over a wide range of bias and temperature. The maximum electric field of 2.3 MV cm−1 is achieved.

Current dependence of the low bias resistance of small capacitance Josephson junctions

The dc current-voltage characteristics of small Josephson junctions reveal features that are not observed in larger junctions, in particular, a switch to the finite voltage state at current values much less than the expected critical current of the junction and a finite resistance in the nominally superconducting regime. Both phenomena are due to the increased sensitivity to noise associated with the small capacitance of the Josephson junction and have been extensively studied a few decades ago. Here I focus on the current bias dependence of the differential resistance of the junction at low current bias in the nominally superconducting regime, using a quantum Langevin equation approach that enables a physically transparent incorporation of the noise environment of the junction. A similar approach might be useful in modeling the sensitivity of superconducting qubits to noise in the microwave regime.

The dependence of assembly bias on the cosmic web

ABSTRACT For low-mass haloes (i.e. Mhalo ≲ 1013 h−1 M⊙), the physical origins of halo assembly bias have been linked to the slowdown of accretion due to tidal forces, which are more dominant in some cosmic-web environments as compared to others. Here, we use publicly available data from the application of the Discrete Persistent Structures Extractor (DisPerSE) to the IllustrisTNG magnetohydrodynamical simulation to investigate the dependence of the related galaxy assembly bias effect on the cosmic web. We show that, at fixed halo mass, the galaxy population displays significant secondary bias when split by distance to DisPerSE critical points representing nodes (dnode), filaments (dskel), and saddles (dsadd), with objects closer to these features being more tightly clustered (particularly at Mhalo ≲ 1012.5 h−1 M⊙). The secondary bias produced by some of these parameters exceeds the assembly bias signal considerably at some mass ranges, especially for dsadd. We also demonstrate that the assembly bias signal is reduced significantly when clustering is conditioned to galaxies being close or far from these critical points. The maximum attenuation is measured for galaxies close to saddle points, where less than 35 per cent of the signal remains. Objects near voids, conversely, preserve a fairly pristine signal (almost 85 per cent). Our analysis confirms the importance of the tidal field in shaping assembly bias, but it is also consistent with the signal being the result of different physical mechanisms. Our work introduces new aspects of secondary bias where predictions from simulations can be directly tested with observational data.

IFRS adoption and the value-relevance of financial statements figures in Nigeria

Research Question: Has IFRS adoption improved the value-relevance of financial statement figures in Nigeria? Motivation: The informativeness of the reported earnings, book values, and cash flows depends on the accounting standards used in preparing the financial statements. IFRS is a global set of accounting standards that tries to improve the relevance of accounting figures by recommending more realistic measurement and recognition criteria and increasing the level of disclosure of relevant information. Idea: The value relevance of accounting figures in predicting stock prices is widely acknowledged. However, this study tests whether IFRS adoption significantly improves this value-relevance by increasing the degree of correlation between accounting figures and stock prices in Nigeria. Data: The data were collected from the Bloomberg market data terminal and Datastream financial database. A sample of 85 listed companies was selected. The sample period was from 2007 to 2016. Tools: The study applied the Ohlson model (using fixed and random-effect models) along with the Driscoll-Kraay standard errors (DKSE) and Panel-corrected standard errors (PCSE) to anticipate autocorrelation, heteroscedasticity, and cross-sectional dependence biases. The Ohlson model was estimated separately for the pre- and post-IFRS adoption periods to detect changes in value relevance. The interactions of the IFRS dummy with earnings, book values, and cash flows were also estimated separately to detect the significance of IFRS interaction with the accounting figures. Findings: The results showed an overall increase in value-relevance by comparing adjusted R2s across the pre- and post-IFRS adoption period. Also, the interactions of IFRS with earnings, book value, and cash flows were all significant. Contribution: The study contributes to the existing literature by including cash flow in the value-relevance test in Nigeria and by applying estimation techniques that control for possible estimation biases. The authors recommend that investors pay more attention to these accounting figures under the IFRS regime when making investment decisions.

Transformer-Based No-Reference Image Quality Assessment via Supervised Contrastive Learning

Image Quality Assessment (IQA) has long been a research hotspot in the field of image processing, especially No-Reference Image Quality Assessment (NR-IQA). Due to the powerful feature extraction ability, existing Convolution Neural Network (CNN) and Transformers based NR-IQA methods have achieved considerable progress. However, they still exhibit limited capability when facing unknown authentic distortion datasets. To further improve NR-IQA performance, in this paper, a novel supervised contrastive learning (SCL) and Transformer-based NR-IQA model SaTQA is proposed. We first train a model on a large-scale synthetic dataset by SCL (no image subjective score is required) to extract degradation features of images with various distortion types and levels. To further extract distortion information from images, we propose a backbone network incorporating the Multi-Stream Block (MSB) by combining the CNN inductive bias and Transformer long-term dependence modeling capability. Finally, we propose the Patch Attention Block (PAB) to obtain the final distorted image quality score by fusing the degradation features learned from contrastive learning with the perceptual distortion information extracted by the backbone network. Experimental results on six standard IQA datasets show that SaTQA outperforms the state-of-the-art methods for both synthetic and authentic datasets. Code is available at https://github.com/I2-Multimedia-Lab/SaTQA.

Observations and modeling of areal surface albedo and surface types in the Arctic

Abstract. An accurate representation of the annual evolution of surface albedo of the Arctic Ocean, especially during the melting period, is crucial to obtain reliable climate model predictions in the Arctic. Therefore, the output of the surface albedo scheme of a coupled regional climate model (HIRHAM–NAOSIM) was evaluated against airborne and ground-based measurements. The observations were conducted during five aircraft campaigns in the European Arctic at different times of the year between 2017 and 2022; one of them was part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2020. We applied two approaches for the evaluation: (a) relying on measured input parameters of surface type fraction and surface skin temperature (offline) and (b) using HIRHAM–NAOSIM simulations independently of observational data (online). From the offline method we found a seasonally dependent bias between measured and modeled surface albedo. In spring, the cloud effect on surface broadband albedo was overestimated by the surface albedo parametrization (mean albedo bias of 0.06), while the surface albedo scheme for cloudless cases reproduced the measured surface albedo distributions for all seasons. The online evaluation revealed an overestimation of the modeled surface albedo resulting from an overestimation of the modeled cloud cover. Furthermore, it was shown that the surface type parametrization contributes significantly to the bias in albedo, especially in summer (after the drainage of melt ponds) and autumn (onset of refreezing). The lack of an adequate model representation of the surface scattering layer, which usually forms on bare ice in summer, contributed to the underestimation of surface albedo during that period. The difference between modeled and measured net irradiances for selected flights during the five airborne campaigns was derived to estimate the impact of the model bias for the solar radiative energy budget at the surface. We revealed a negative bias between modeled and measured net irradiances (median: −6.4 W m−2) for optically thin clouds, while the median value of only 0.1 W m−2 was determined for optically thicker clouds.

Antiferromagnetic magnetostriction of IrMn detected by angular dependent exchange bias

The manipulation of Néel vector of antiferromagnetic (AFM) layer by an applied stress has attracted considerable attention due to the technical importance for AFM-based spintronic devices. Here, we fabricated CoFeB/IrMn and Ni/IrMn exchange bias (EB) bilayers on PMN-PT(011) to quantitatively study the AFM magnetostrictive behaviors of the IrMn layer. Numerical calculations based on the Stoner–Wohlfarth model show that the response of the Néel vector to compressive stress can be detected by measuring the angular dependent EB. The hysteresis loops experimentally measured with applying an electric field on PMN-PT show significantly different shape changes due to the opposite magnetostriction between CoFeB and Ni. The non-vanished EB field obtained at 90∘ indicates the rotation of Néel vector under compressive stress, suggesting the positive magnetostriction of IrMn. The numerical fitting of the angular dependent EB indicates that the Néel vectors in both samples deviate from the initial direction by the same −5∘. The AFM magnetostriction coefficient of IrMn is estimated to be 238 ppm, which is in good agreement with the theoretically predicted value.

Constraining primordial non-Gaussianity from DESI quasar targets and Planck CMB lensing

We detect the cross-correlation between 2.7 million DESI quasar targets across 14,700 deg2 (180 quasars deg-2) and Planck 2018 CMB lensing at ∼30σ. We use the cross-correlation on very large scales to constrain local primordial non-Gaussianity via the scale dependence of quasar bias. The DESI quasar targets lie at an effective redshift of 1.51 and are separated into four imaging regions of varying depth and image quality. We select quasar targets from Legacy Survey DR9 imaging, apply additional flux and photometric redshift cuts to improve the purity and reduce the fraction of unclassified redshifts, and use early DESI spectroscopy of 194,000 quasar targets to determine their redshift distribution and stellar contamination fraction (2.6%). Due to significant excess large-scale power in the quasar autocorrelation, we apply weights to mitigate contamination from imaging systematics such as depth, extinction, and stellar density. We use realistic contaminated mocks to determine the greatest number of systematic modes that we can fit, before we are biased by overfitting and spuriously remove real power. We find that linear regression with one to seven imaging templates removed per region accurately recovers the input cross-power, f NL and linear bias. As in previous analyses, our f NL constraint depends on the linear primordial non-Gaussianity bias parameter, bϕ = 2(b - p)δc assuming universality of the halo mass function. We measure f NL = -26+45 -40 with p = 1.6 (f NL = -18+29 -27 with p = 1.0), and find that this result is robust under several systematics tests. Future spectroscopic quasar cross-correlations with Planck lensing can tighten the f NL constraints by a factor of 2 if they can remove the excess power on large scales in the quasar auto power spectrum.

Temperature-resilient random number generation with stochastic actuated magnetic tunnel junction devices

Nanoscale magnetic tunnel junction (MTJ) devices can efficiently convert thermal energy in the environment into random bitstreams for computational modeling and cryptography. We recently showed that perpendicular MTJs actuated by nanosecond pulses can generate true random numbers at high data rates. Here, we explore the dependence of probability bias—the deviations from equal probability (50/50) 0/1 bit outcomes—of such devices on temperature, pulse amplitude, and duration. Our experimental results and device model demonstrate that operation with nanosecond pulses in the ballistic limit minimizes variation of probability bias with temperature to be far lower than that of devices operated with longer-duration pulses. Furthermore, operation in the short-pulse limit reduces the bias variation with pulse amplitude while rendering the device more sensitive to pulse duration. These results are significant for designing true random number generator MTJ circuits and establishing operating conditions.

Two-temperature principle for evaluating electrothermal performance of GaN HEMTs

Self-heating effects in Gallium nitride (GaN) high-electron-mobility transistors (HEMTs) can adversely impact both device reliability and electrical performance. Despite this, a holistic understanding of the relationship among heat transport mechanisms, device reliability, and degradation of electrical performance has yet to be established. This Letter presents an in-depth analysis of self-heating effects in GaN HEMTs using technology computer-aided design and phonon Monte Carlo simulations. We examine the differential behaviors of the maximum channel temperature (Tmax) and the equivalent channel temperature (Teq) in response to non-Fourier heat spreading processes, highlighting their respective dependencies on bias conditions and phonon ballistic effects. Our study reveals that Tmax, a crucial metric for device reliability, is highly sensitive to both heat source-related and cross-plane ballistic effects, especially in the saturation regime. In contrast, Teq, which correlates with drain current degradation, shows minimal bias dependence and is predominantly influenced by the cross-plane ballistic effect. These findings emphasize the importance of optimizing device designs to mitigate both Tmax and Teq, with a particular focus on thermal designs influenced by the heat source size. This work contributes to a deeper understanding of self-heating phenomena in GaN HEMTs and provides valuable insights for enhancing device performance and reliability.

Effect of thickness and temperature on interfacial interaction between Cr and Ni nanolayers: An exchange bias study

The phenomenon of negative exchange bias is typically observed in ferromagnetic and antiferromagnetic materials following a field cooling protocol. However, the occurrence of positive exchange bias is hardly found. The majority of models show positive exchange bias after undergoing field cooling or zero-field-cooling process. In this work, we achieved a novel positive exchange bias effect for Cr/Ni bilayer after gradually increasing the temperature from low temperature (5 K) to high temperature (up to RT) in the absence of magnetic field. The M−H loops at different temperatures reveal not only temperature dependent exchange bias but also thickness dependent exchange bias for Cr/Ni layer. A systematic investigation was conducted to analyse the influence of the exchange bias field on the thickness of the ferromagnetic layer. Significantly, our experimental observations also reveal a notable room temperature exchange bias field measuring 320 Oe for the optimum bilayer. Moreover, to obtain a detailed understanding of coercivity in the Cr/Ni bilayer, Kerr hysteresis was also recorded at room temperature in longitudinal geometry (L-MOKE). Hence, the discovery of our work not only suggests a novel methodology to achieve positive exchange bias in ferromagnetic and antiferromagnetic bilayers but also the oscillatory behavior of HEB with respect to increase in temperature is observed for polycrystalline Cr (AFM) layer.

Stop Blaming Hopping Conduction in Nanocrystal Arrays, Use it for Active Photonics!

AbstractNanocrystals (NCs) are now established building blocks for photonic applications. However, their integration for optoelectronics has not yet reached the same level of maturity, in part due to the perceived bottleneck that is the inherent limited mobility resulting from hopping conduction. Significant efforts are made to improve this mobility, notably by tuning the particle surface chemistry to enable larger interparticle electronic coupling, and values of mobility of ≈10 cm2 V−1 s−1 have been achieved. It is acknowledged that this value remains significantly lower than those obtained in 2D electron gases but is on par with the mobility reported for vertical transport in epitaxially grown heterostructures with similar confinement energies. Since there appears to be limited perspectives for further increasing mobility values, a suggestion is made that efforts should instead be directed toward exploring the potential benefits offered by hopping conduction. One of these benefits is the bias dependence of the diffusion length, which plays a key role in designing bias‐reconfigurable optical responses for NC‐based devices. Some recent achievements in building bias‐activated devices will be reviewed and the essential criteria for designing future structures will be discussed. Ultimately, hopping conduction is an opportunity to generate new functionalities that low‐disorder materials would be unable to provide.

What really matters for global intergenerational mobility?

This study investigates the genuine impacts of education expansion, education inequality, and parental dependency on intergenerational mobility. It utilizes data from the Global Database on Intergenerational Mobility for 153 countries and cohorts born between the 1940s and 1980s. By employing a causal machine learning approach to address confounding problems, this research reveals that education expansion can promote intergenerational mobility to a certain extent. However, its effectiveness is partially diminished by education inequality and may be ineffective if parental dependency exists at a high level. Furthermore, this study also indicates that while gender inequality in intergenerational mobility still exists, its degree has been significantly reduced across generations. When compared to parental dependency, gender effects are far less important. Therefore, there is a need to reassess the roles of parental dependency and gender bias in intergenerational mobility, especially when parental dependency is currently underestimated, and gender bias is overemphasized.

Ionizing radiation influence on 28-nm MOS transistor's low-frequency noise characteristics

In this paper, we explore the transitions of low-frequency noise characteristics in high-k metal-gate bulk CMOS transistors induced by Total Ionizing Dose (TID). Due to the strong bias dependence of the noise characteristics, differentiating between noise shifts caused by the effective biasing change and the contribution of the newly generated traps becomes extremely challenging. In order to better understand the effects of irradiation, transistor noise had to be characterized at several biasing points, both in linear and saturation regions, before and after exposure to 1 Grad (SiO2) of TID. Correlation between shifts in time and frequency domain is presented in this work, along with possible explanations for each variation that occurs. We present examples of irradiation-generated Random Telegraph Noise (RTN) defects as well as various TID effects on noise Power Spectral Density (PSD) curves with pre-existing RTN sources.

New insights into the structure of the Ag(111)-p(4 × 4)-O phase: high-resolution STM and DFT study.

The atomic structure of the Ag(111)-p(4 × 4)-O phase was reexamined with scanning tunneling microscopy (STM) and density functional theory. We discovered two different phases with the same (4 × 4) periodicity and demonstrated that the accepted Ag6 model is incompatible with high-resolution oxygen-sensitive STM images. Using bias dependencies of the STM images, we have shown that the p(4 × 4) phase is highly nonuniform, with local oxygen coverage varying from 1/8 ML up to 1/2 ML.

Drain bias dependence of Y 22 and Y 21 signals at low frequency for on-state conditions in AlGaN/GaN high electron mobility transistors

The drain bias dependence of Y 22 and Y 21 signals has been investigated by two-port network measurement in the on-state condition of AlGaN/GaN high electron mobility transistors. Y 22 has signals for Fe-related traps in GaN layers and the self-heating effect. The Y 21 signal is unique among signals with the same drain bias dependence as Y 22 signals. This unique signal is considered to originate from AlGaN traps, using device simulation with a GaN trap, AlGaN trap and the self-heating effect. The peak frequency of GaN and AlGaN traps increases with increasing drain voltage, while the peak frequency of self-heating does not depend on the drain voltage.

The influence of unemployment and labor force participation rates on economic development in GCC countries: A cointegration approach

This study explores the relationship between GDP growth, unemployment rate, and labor force participation rate in the Gulf Cooperation Council (GCC) countries from 1990 to 2018. Furthermore, the study incorporates control factors such as government spending, trade openness, and energy use into the regression equation. We used panel dynamic ordinary least squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS) estimators to investigate the relationships between variables in this investigation. The econometric technique accounts for nonstationary, endogeneity bias and cross-sectional dependencies between country-year observations. Cointegration was found among GDP growth, unemployment rate, and labor force participation. Long-term, the unemployment rate has a statistically significant negative effect on economic growth in the GCC nations. Meanwhile, the labor force participation rate significantly influences economic expansion in the long term. The expansion of government expenditures and international trade reduces economic growth. Alternatively, it is discovered that energy consumption has a substantial and positive effect on economic expansion. Okun’s rule and the unidirectional causality from economic growth to unemployment indicate that the primary cause of unemployment in GCC nations is a failure to adequately expand their economies. When developing economic strategies to reduce unemployment, policymakers are particularly interested in determining whether or not economic development and the unemployment rate are cointegrated.

Bias dependence in statistical random telegraph noise analysis based on nanoscale CMOS ring oscillators

Random Telegraph Noise (RTN) is one of the major reliability concerns in nanoscale complementary metal-oxide semiconductor (CMOS) technologies. In this paper, we discuss the characterization of RTN in 40 nm CMOS technology using Ring Oscillators (ROSCs). We used different types of ROSCs to study the temporal and spectral characteristics of the RTN. We conducted measurements on one of the arrays with 128 identical ROSC cells. These results enabled statistical characterization of the RTN amplitude strength and its frequency characteristics in different supply voltage variations from 0.5 V to 0.7 V. At power supply of 0.65 V, dominant and observable RTN amplitude above 0.37% Δf/fmean\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta f/f_{\ ext{mean}}$$\\end{document} is found in 60% of cells in the array. Further, the capture and emission time constant τe//c\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au_{e//c}$$\\end{document} can be extracted from the measurements, the values observed ranging from 0.2 μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}s to 10 ms.