We report the multiwavelength properties of eROSITA Final Equatorial Depth Survey (eFEDS) J084222.9+001000 (hereafter ID830), a quasar at z = 3.4351, identified as the most X-ray luminous radio-loud quasar in the eFEDS field. ID830 shows a rest-frame 0.5-2 keV luminosity of log (L0.5-2kev/erg S-1)=46.20 +/- 0.12, with a steep X-ray photon index (Gamma = 2.43 +/- 0.21), and a significant radio counterpart detected with the Very Large Array FIRST 1.4 GHz and Very Large Array Sky Survey 3 GHz bands. The rest-frame UV to optical spectra from Sloan Digital Sky Survey and Subaru/MOIRCS J band show a dust-reddened quasar feature with A(V) = 0.39 +/- 0.08 mag, and the expected bolometric active galactic nuclei luminosity from the dust-extinction-corrected UV luminosity reaches L-bol,L-3000 & Aring; = (7.62 +/- 0.31) x 10(46) erg s(-1). We estimate a black hole mass of M-BH = (4.40 +/- 0.72) x 10(8) M-circle dot based on the Mg II lambda 2800 emission-line width, and Eddington ratios from the dust-extinction-corrected UV continuum luminosity and X-ray luminosity that reach lambda(Edd,UV) = 1.44 +/- 0.24 and lambda(Edd,X) = 12.8 +/- 3.9, respectively, both indicating super-Eddington accretion. ID830 shows a high ratio of UV to X-ray luminosities, alpha(OX) = -1.20 +/- 0.07 (or alpha(OX) = -1.42 +/- 0.07 after correcting for jet-linked X-ray excess), higher than quasars and little red dots in the super-Eddington phase with similar UV luminosities, with alpha(OX) < -1.8. Such a high alpha(OX) suggests the coexistence of a prominent radio jet and X-ray corona in this high-Eddington-accretion phase. We propose that ID830 may be in a transitional phase after an accretion burst, evolving from a super-Eddington to a sub-Eddington state, which could naturally describe the high alpha(OX).
The lateral geniculate nucleus (LGN) is a key thalamic nucleus in the primate visual system that relays visual information from the retina to cortical visual areas. While functional and microanatomical characteristics of the LGN and its layers have been extensively studied, previous investigations on its receptor architecture have been restricted to a small subset of neurotransmitter receptors. To characterise the receptor architecture of the macaque LGN in greater detail, we analysed in vitro autoradiography data to quantify the density of 15 neurotransmitter receptors at the sublayer level, thus improving our understanding of the molecular architecture supporting primate visual function. For comparison, we also determined the densities of these receptors in the primary visual cortex (V1) at a laminar level. Though comparable in shape, the receptor fingeprints of magnocellular layers were larger than those of parvocellular layers. In contrast, receptor fingerprints of cytoarchitectonic layers in V1 differed in both shape and size. Ionotropic/metabotropic and excitatory/inhibitory receptor ratios were significantly larger in V1 than in the LGN, suggesting a greater prominence of inhibitory neurotransmission in the latter region. The nicotinic α4β2 receptor was the only receptor type with a higher density in the LGN compared to V1, highlighting the particular importance of acetylcholine in the modulation of visual stimuli. These findings provide insights into the receptor architecture underlying functions of the LGN, with implications for mechanisms such as visual signal encoding and surround suppression.
The study examines the influence of indoor relative humidity on thermal and humidity perception, working memory performance, and physiological responses, with an emphasis on gender-based differences. A data-driven model was used to predict working memory based on humidity-related preferences, identifying key physiological and perceptual factors that contributed to the prediction of cognitive performance. Sensations and preferences related to humidity and temperature, as well as heart rate and electrodermal activity (EDA), were recorded under different humidity conditions, while the Operation Span Task was employed to assess working memory. Results revealed that humidity sensation responded sensitively to a 20% change in humidity, whereas temperature sensation required a 30% change. In contrast, temperature preference shifted significantly in response to smaller humidity changes than humidity preference. Higher humidity levels increased heart rate and EDA and reduced working memory, with these effects more pronounced in males. Moreover, males' perceptions of temperature and humidity showed significant correlations with both physiological responses and working memory, while females displayed limited correlations. Notably, the model demonstrated that working memory can be predicted from subjective humidity-related preferences rather than the actual humidity level as an input variable, underscoring the value of human perception in forecasting cognitive outcomes.
Oscillatory compositional zoning (OCZ), widely observed in minerals, suggests the presence of self-organizing mechanisms inherent in the mineral formation process. In recent years, a mechanism for OCZ formation has been proposed, focusing on impurity-induced inhibition of crystal surface growth. We performed a numerical simulation that couples step dynamics and random impurity adsorption–desorption on the crystal surface with diffusive solute transport around the crystal. The results demonstrate that, even under static external conditions, the crystal growth rate exhibits spontaneous periodic variation, leading to oscillatory impurity incorporation. The resulting compositional zoning shows a periodicity on the order of several tens of nanometers, consistent with nanoscale periodic structures observed in natural minerals such as dolomite, garnet, and zircon. This study presents a novel theoretical framework that attributes the origin of the nanoscale ultra-fine OCZ to the nonlinear response of crystal growth, providing significant insights into self-organization phenomena in mineralogy and crystal growth science.
This study systematically examines the robustness of the Akaike Information Criterion (AIC) in determining the optimal order (p) of an autoregressive (AR) model applied to the RR interval time series of the PhysioNet healthy subject database. The AR approach is widely used to estimate the power spectral density (PSD) of heart rate variability (HRV), and accurate order selection is essential for model stability and reliable spectral estimation. Although the AIC is designed to balance model fit and complexity, it suffers from the problem of arbitrary model selection. This study provides a quantitative robustness analysis of information-criterion-based AR order selection under controlled expansion of the search space. Specifically, we investigated the behavior of the AIC using the PhysioNet database (N = 1257) under conditions where the maximum search order was set to an excessively high value (p = 50), far exceeding the commonly recommended range. Our analysis suggested that the AR model began to capture subtle noise and nonstationary components rather than the intrinsic HRV structure, leading to overfitting and excessive order selection, resulting in false peaks in the PSD and reduced robustness. In conclusion, order decisions based solely on information criteria such as the AIC become unstable when the search range is too large. To ensure robustness, it is recommended to complement the AIC with more stringent criteria such as the Bayesian Information Criterion (BIC) or Final Prediction Error (FPE), in addition to the traditional maximum order restriction.
