Morphology of Galaxies in JWST Fields: Initial Distribution and Evolution of Galaxy Morphology

A recent study from the Horizon Run (HR5) cosmological simulation has predicted that galaxies with ${\rm log}~M_{\ast}/M_{\odot}\lesssim 10$ in the cosmic morning ($10\gtrsim z\gtrsim 4$) dominantly have disk-like morphology in the $\Lambda$CDM universe, which is driven by the tidal torque in the initial matter fluctuations. For a direct comparison with observation, we identify a total of about $19,000$ James Webb Space Telescope (JWST) galaxies with ${\rm log}~M_{\ast}/M_{\odot}>9$ at $z=0.6-8.0$ utilizing deep JWST/NIRCam images of publicly released fields, including NEP-TDF, NGDEEP, CEERS, COSMOS, UDS, and SMACS J0723$-$7327. We estimate their stellar masses and photometric redshifts with the redshift dispersion of $\sigma_{\rm NMAD}=0.009$ and outlier fraction of only about $6\%$. We classify galaxies into three morphological types, `disks', `spheroids', and `irregulars', applying the same criteria used in the HR5 study. The morphological distribution of the JWST galaxies shows that disk galaxies account for $60-70\%$ at all redshift ranges. However, in the high-mass regime (${\rm log}~M_{\ast}/M_{\odot}\gtrsim11$), spheroidal morphology becomes the dominant type. This implies that mass growth of galaxies is accompanied with morphological transition from disks to spheroids. The fraction of irregulars is about 20\% or less at all mass and redshifts. All the trends in the morphology distribution are consistently found in the six JWST fields. These results are in close agreement with the results from the HR5 simulation, particularly confirming the prevalence of disk galaxies at small masses in the cosmic morning and noon.Comment: Accepted for publication in ApJ, 30 pages, 14 figures, 5 tables, 3 appendice

Low-Thermal-Budget Ferroelectric Field-Effect Transistors Based on CuInP2S6 and InZnO

In this paper, we demonstrate low-thermal-budget ferroelectric field-effect transistors (FeFETs) based on two-dimensional ferroelectric CuInP2S6 (CIPS) and oxide semiconductor InZnO (IZO). The CIPS/IZO FeFETs exhibit non-volatile memory windows of ~1 V, low off-state drain currents, and high carrier mobilities. The ferroelectric CIPS layer serves a dual purpose by providing electrostatic doping in IZO and acting as a passivation layer for the IZO channel. We also investigate the CIPS/IZO FeFETs as artificial synaptic devices for neural networks. The CIPS/IZO synapse demonstrates a sizeable dynamic ratio (125) and maintains stable multi-level states. Neural networks based on CIPS/IZO FeFETs achieve an accuracy rate of over 80% in recognizing MNIST handwritten digits. These ferroelectric transistors can be vertically stacked on silicon CMOS with a low thermal budget, offering broad applications in CMOS+X technologies and energy-efficient 3D neural networks

One-ninth magnetization plateau stabilized by spin entanglement in a kagome antiferromagnet

The spin-1/2 antiferromagnetic Heisenberg model on a Kagome lattice is geometrically frustrated, which is expected to promote the formation of many-body quantum entangled states. The most sought-after among these is the quantum spin liquid phase, but magnetic analogs of liquid, solid, and supersolid phases may also occur, producing fractional plateaus in the magnetization. Here, we investigate the experimental realization of these predicted phases in the Kagome material YCu3(OD)6+xBr3-x (x=0.5). By combining thermodynamic and Raman spectroscopic techniques, we provide evidence for fractionalized spinon excitations and observe the emergence of a 1/9 magnetization plateau. These observations establish YCu3(OD)6+xBr3-x as a model material for exploring the 1/9 plateau phase.Comment: to appear in Nature Physics, 33 pagses, 15 figure

Field-induced spin level crossings within a quasi-XY antiferromagnetic state in Ba2_{2}FeSi2_{2}O7_{7}

We present a high-field study of the strongly anisotropic easy-plane square lattice $S$ = 2 quantum magnet Ba$_{2}$FeSi$_{2}$O$_{7}$. This compound is a rare high-spin antiferromagnetic system with very strong easy-plane anisotropy, such that the interplay between spin level crossings and antiferromagnetic order can be studied. We observe a magnetic field-induced spin level crossing occurring within an ordered state. This spin level crossing appears to preserve the magnetic symmetry while producing a non-monotonic dependence the order parameter magnitude. The resulting temperature-magnetic field phase diagram exhibits two dome-shaped regions of magnetic order overlapping around 30 T. The ground state of the lower-field dome is predominantly a linear combination of $| S^{z} = 0 \rangle$ and $|S^{z} = 1 \rangle$ states, while the ground state of the higher-field dome can be approximated by a linear combination of $| S^{z} = 1 \rangle$ and $| S^{z} = 2\rangle$ states. At 30 T, where the spin levels cross, the magnetization exhibits a slanted plateau, {\color {black}the magnetocaloric effect shows a broad hump, and the electric polarization shows a weak slope change}. We determined the detailed magnetic phase boundaries and the spin level crossings using measurements of magnetization, electric polarization, and the magnetocaloric effect in pulsed magnetic fields to 60 T. We calculate these properties using a mean field theory based on direct products of SU(5) coherent states and find good agreement. Finally, we measure and calculate the magnetically-induced electric polarization that reflects magnetic ordering and spin level crossings. This multiferroic behavior provides another avenue for detecting phase boundaries and symmetry changes.Comment: 9 pages, 5 figure

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Interpolation time-optimized aortic pulse wave velocity estimation by 4D flow MRI

Abstract Four-dimensional flow magnetic resonance imaging-based pulse wave velocity (4D flow PWV) estimation is a promising tool for measuring regional aortic stiffness for non-invasive cardiovascular disease screening. However, the effect of variations in the shape of flow waveforms on 4D flow PWV measurements remains unclear. In this study, 4D flow PWV values were compared using cross-correlation algorithm with different interpolation times (iTs) based on flow rate and beat frequency. A critical iT (iTCrit) was proposed from in vitro study using flexible and stiff phantom models to simultaneously achieve a low difference and a low computation time. In vivo 4D flow PWV values from six healthy volunteers were also compared between iTCrit and the conventionally used interpolation time of 1 ms (iT1 ms). The results indicated that iTCrit reduced the mean difference of in vitro 4D flow PWV values by 19%, compared to iT1 ms. In addition, iTCrit measured in vivo 4D flow PWV, showing differences similar to those obtained with iT1 ms. A difference estimation model was proposed to retrospectively estimate potential differences of 4D flow PWV using known values of PWV and the used iT. This study would be helpful for understanding the differences of PWV generated by physiological changes and time step of obtained flow waveforms