arXiv subjects

Jianfeng Wu

Publications and source records attributed to Jianfeng Wu.

At least 55 records · Page 3Linked to original sources

arXiv2022

Bubble in the Whale: Identifying the Optical Counterparts and Extended Nebula for the Ultraluminous X-ray Sources in NGC 4631

We present a deep optical imaging campaign on the starburst galaxy NGC 4631 with CFHT/MegaCam. By supplementing the HST/ACS and Chandra/ACIS archival data, we search for the optical counterpart candidates of the five brightest X-ray sources in this galaxy, four of which are identified as ultraluminous X-ray sources (ULXs). The stellar environments of the X-ray sources are analyzed using the extinction-corrected color-magnitude diagrams and the isochrone models. We discover a highly asymmetric bubble nebula around X4 which exhibits different morphology in the H$α$ and [O III] images. The [O III]/H$α$ ratio map shows that the H$α$-bright bubble may be formed mainly via the shock ionization by the one-sided jet/outflow, while the more compact [O III] structure is photoionized by the ULX. We constrain the bubble expansion velocity and interstellar medium density with the MAPPINGS V code, and hence estimate the mechanical power injected to the bubble as $P_w \sim 5\times10^{40}$ erg s$^{-1}$ and the corresponding bubble age of $\sim7\times 10^{5}$ yr. Relativistic jets are needed to provide such level of mechanical power with a mass-loss rate of $\sim10^{-7}\ M_{\odot}\ \rm yr^{-1}$. Besides the accretion, the black hole spin is likely an additional energy source for the super-Eddington jet power.

astro-ph.HE↗

arXiv2022

Relation-dependent Contrastive Learning with Cluster Sampling for Inductive Relation Prediction

Relation prediction is a task designed for knowledge graph completion which aims to predict missing relationships between entities. Recent subgraph-based models for inductive relation prediction have received increasing attention, which can predict relation for unseen entities based on the extracted subgraph surrounding the candidate triplet. However, they are not completely inductive because of their disability of predicting unseen relations. Moreover, they fail to pay sufficient attention to the role of relation as they only depend on the model to learn parameterized relation embedding, which leads to inaccurate prediction on long-tail relations. In this paper, we introduce Relation-dependent Contrastive Learning (ReCoLe) for inductive relation prediction, which adapts contrastive learning with a novel sampling method based on clustering algorithm to enhance the role of relation and improve the generalization ability to unseen relations. Instead of directly learning embedding for relations, ReCoLe allocates a pre-trained GNN-based encoder to each relation to strengthen the influence of relation. The GNN-based encoder is optimized by contrastive learning, which ensures satisfactory performance on long-tail relations. In addition, the cluster sampling method equips ReCoLe with the ability to handle both unseen relations and entities. Experimental results suggest that ReCoLe outperforms state-of-the-art methods on commonly used inductive datasets.

cs.LG↗

arXiv2022

Improved Prediction of Beta-Amyloid and Tau Burden Using Hippocampal Surface Multivariate Morphometry Statistics and Sparse Coding

Background: Beta-amyloid (A$β$) plaques and tau protein tangles in the brain are the defining 'A' and 'T' hallmarks of Alzheimer's disease (AD), and together with structural atrophy detectable on brain magnetic resonance imaging (MRI) scans as one of the neurodegenerative ('N') biomarkers comprise the ''ATN framework'' of AD. Current methods to detect A$β$/tau pathology include cerebrospinal fluid (CSF; invasive), positron emission tomography (PET; costly and not widely available), and blood-based biomarkers (BBBM; promising but mainly still in development). Objective: To develop a non-invasive and widely available structural MRI-based framework to quantitatively predict the amyloid and tau measurements. Methods: With MRI-based hippocampal multivariate morphometry statistics (MMS) features, we apply our Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) method combined with the ridge regression model to individual amyloid/tau measure prediction. Results: We evaluate our framework on amyloid PET/MRI and tau PET/MRI datasets from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject has one pair consisting of a PET image and MRI scan, collected at about the same time. Experimental results suggest that amyloid/tau measurements predicted with our PASCP-MP representations are closer to the real values than the measures derived from other approaches, such as hippocampal surface area, volume, and shape morphometry features based on spherical harmonics (SPHARM). Conclusion: The MMS-based PASCP-MP is an efficient tool that can bridge hippocampal atrophy with amyloid and tau pathology and thus help assess disease burden, progression, and treatment effects.

physics.med-ph↗

arXiv2022

A long-period pre-ELM system discovered from LAMOST medium-resolution survey

We present LAMOST~J041920.07+072545.4 (hereafter J0419), a close binary consisting of a bloated extremely low mass pre-white dwarf (pre-ELM WD) and a compact object with an orbital period of 0.607189~days. The large-amplitude ellipsoidal variations and the evident Balmer and He~I emission lines suggest a filled Roche lobe and ongoing mass transfer. No outburst events were detected in the 15 years of monitoring of J0419, indicating a very low mass transfer rate. The temperature of the pre-ELM, $T_\mathrm{eff} = 5793_{-133}^{+124}\,\rm K$, is cooler than the known ELMs, but hotter than most CV donors. Combining the mean density within the Roche lobe and the radius constrained from our SED fitting, we obtain the mass of the pre-ELM, $M_1 = 0.176\pm 0.014\,M_\odot$. The joint fitting of light and radial velocity curves yields an inclination angle of $i = 66.5_{-1.7}^{+1.4}$ degrees, corresponding to the compact object mass of $M_2 = 1.09\pm 0.05\,M_\odot$. The very bloated pre-ELM has a smaller surface gravity ($\log g = 3.9\pm 0.01$, $R_1 = 0.78 \pm 0.02\,R_\odot$) than the known ELMs or pre-ELMs. The temperature and the luminosity ($L_\mathrm{bol} = 0.62_{-0.10}^{+0.11}\,L_\odot$) of J0419 are close to the main sequence, which makes the selection of such systems through the HR diagram inefficient. Based on the evolutionary model, the relatively long period and small $\log g$ indicate that J0419 could be close to the "bifurcation period" in the orbit evolution, which makes J0419 to be a unique source to connect ELM/pre-ELM WD systems, wide binaries and cataclysmic variables.

astro-ph.SR↗

arXiv2022

A White Dwarf-Main Sequence Binary Unveiled by Time-Domain Observations from LAMOST and TESS

We report a single-lined white dwarf-main sequence binary system, LAMOST J172900.17+652952.8, which is discovered by LAMOST's medium resolution time-domain surveys. The radial velocity semi-amplitude and orbital period of the optical visible star are measured by using the Palomar 200-inch telescope follow-up observations and the light curves from TESS. Thus the mass function of the invisible candidate white dwarf is derived, $f(M_{\rm{2}}) = 0.120\,\pm\,0.003\,M_{\odot}$. The mass of the visible star is measured based on the spectral energy distribution fitting, $M_{\mathrm{1}}$ = $0.81^{+0.07}_{-0.06}\,M_{\odot}$. Hence, the mass of its invisible companion is $M_{\rm{2}}\,\gtrsim\,0.63\,M_{\odot}$. The companion ought to be a compact object rather than a main-sequence star owing to the mass ratio $q = M_{\rm{2}} / M_{\rm 1} \gtrsim 0.78$ and the single-lined spectra. The compact object is likely to be a white dwarf except for small inclination angle, $i\,\lesssim\,40^{\circ}$. By using the GALEX NUV flux, the effective temperature of the white dwarf candidate is constrained as $T_{\rm eff}^{\rm WD}\,\lesssim\,12000-13500$ K. It is difficult to detect white dwarfs which are outshone by their bright companions via single-epoch optical spectroscopic surveys. Therefore, the optical time-domain surveys can play an important role in unveiling invisible white dwarfs and other compact objects in binaries.

astro-ph.SR↗

arXiv2022

A dynamically discovered and characterized non-accreting neutron star -- M dwarf binary candidate

Optical time-domain surveys can unveil and characterize exciting but less-explored non-accreting and/or non-beaming neutron stars (NS) in binaries. Here we report the discovery of such a NS candidate using the LAMOST spectroscopic survey. The candidate, designated LAMOST J112306.9+400736 (hereafter J1123), is in a single-lined spectroscopic binary containing an optically visible M star. The star's large radial velocity variation and ellipsoidal variations indicate a relatively massive unseen companion. Utilizing follow-up spectroscopy from the Palomar 200-inch telescope and high-precision photometry from TESS, we measure a companion mass of $1.24_{-0.03}^{+0.03}~M_{\odot}$. Main-sequence stars with this mass are ruled out, leaving a NS or a massive white dwarf (WD). Although a massive WD cannot be ruled out, the lack of UV excess radiation from the companion supports the NS hypothesis. Deep radio observations with FAST yielded no detections of either pulsed or persistent emission. J1123 is not detected in numerous X-ray and gamma-ray surveys. These non-detections suggest that the NS candidate is not presently accreting and pulsing. Our work exemplifies the capability of discovering compact objects in non-accreting close binaries by synergizing the optical time-domain spectroscopy and high-cadence photometry.

astro-ph.SR↗

arXiv2022

X-ray emission of contact binary variables within 1 kpc

By assembling the largest sample to date of X-ray emitting EW-type binaries (EWXs), we carried out correlation analyses for the X-ray luminosity log$L_{\textrm{X}}$, and X-ray activity level log($L_{\textrm{X}}$/$L_{\textrm{bol}}$) versus the orbital period $P$ and effective temperature $T_{\rm eff}$. We find strong $P$-log$L_{\textrm{X}}$ and $P$-log($L_{\textrm{X}}$/$L_{\textrm{bol}}$) correlations for EWXs with $P$ < 0.44 days and we provide the linear parametrizations for these relations, on the basis of which the orbital period can be treated as a good predictor for log$L_{\textrm{X}}$ and log($L_{\textrm{X}}$/$L_{\textrm{bol}}$). The aforementioned binary stellar parameters are all correlated with log$L_{\textrm{X}}$, while only $T_{\rm eff}$ exhibits a strong correlation with log($L_{\textrm{X}}$/$L_{\textrm{bol}}$). Then, EWXs with higher temperature show lower X-ray activity level, which could indicate the thinning of the convective area related to the magnetic dynamo mechanism. The total X-ray luminosity of an EWX is essentially consistent with that of an X-ray saturated main sequence star with the same mass as its primary, which may imply that the primary star dominates the X-ray emission. The monotonically decreasing $P$-log($L_{\textrm{X}}$/$L_{\textrm{bol}}$) relation and the short orbital periods indicate that EWXs could all be in the X-ray saturated state, and they may inherit the changing trend of the saturated X-ray luminosities along with the mass shown by single stars. For EWXs, the orbital period, mass, and effective temperature increase in concordance. We demonstrate that the period $P=0.44$ days corresponds to the primary mass of $\sim1.1 \rm M_\odot$, beyond which the saturated X-ray luminosity of single stars will not continue to increase with mass. This explains the break in the positive $P$-log$L_{\textrm{X}}$ relation for EWXs with $P>0.44$ days.

astro-ph.HE↗

arXiv2022

Connecting Low- and High-Redshift Weak Emission-Line Quasars via HST Spectroscopy of Ly$α$ Emission

We present ultraviolet spectroscopy covering the Ly$α$ + N V complex of six candidate low-redshift ($0.9 < z < 1.5$) weak emission-line quasars (WLQs) based on observations with the Hubble Space Telescope. The original systematic searches for these puzzling Type 1 quasars with intrinsically weak broad emission lines revealed an $N \approx 100$ WLQ population from optical spectroscopy of high-redshift ($z > 3$) quasars, defined by a Ly$α$ + N V rest-frame equivalent width (EW) threshold $< 15.4$ Å. Identification of lower-redshift ($z < 3$) WLQ candidates, however, has relied primarily on optical spectroscopy of weak broad emission lines at longer rest-frame wavelengths. With these new observations expanding existing optical coverage into the ultraviolet, we explore unifying the low- and high-$z$ WLQ populations via EW[Ly$α$+NV]. Two objects in the sample unify with high-$z$ WLQs, three others appear consistent with the intermediate portion of the population connecting WLQs and normal quasars, and the final object is consistent with typical quasars. The expanded wavelength coverage improves the number of available line diagnostics for our individual targets, allowing a better understanding of the shapes of their ionizing continua. The ratio of EW[Ly$α$+NV] to EW[MgII] in our sample is generally small but varied, favoring a soft ionizing continuum scenario for WLQs, and we find a lack of correlation between EW[Ly$α$+NV] and the X-ray properties of our targets, consistent with a "slim-disk" shielding gas model. We also find indications that weak absorption may be a more significant contaminant in low-$z$ WLQ populations than previously thought.

astro-ph.GA↗

arXiv2022

Detailed analysis on the reflection component for the black hole candidate MAXI J1348-630

The black hole candidate MAXI J1348-630 was discovered on January 26th, 2019, with the Gas Slit Camera (GSC) on-board \textit{MAXI}. We report a detailed spectral analysis of this source by using the archived data of \textit{NuSTAR}. A total of 9 observations covered the complete outburst evolution of MAXI J1348-630 from the hard state to the soft state and finally back to the hard state. Additionally, the intermediate state is found in the transition from the hard state to the soft state. We use the state-of-art reflection model \verb'relxill' family to fit all the 9 spectra, and the spectra from two focal plane module detectors of \textit{NuSTAR} are jointly fitted for each observation. In particular, we concentrate on the results of the black hole spin parameter and the inclination of the accretion disk. Based on the analysis of the inner radius of the accretion disk, we obtain the spin parameter $a_* =0.78_{-0.04}^{+0.04}$, and the inclination angle of the inner disk $i = 29.2_{-0.5}^{+0.3}$ degrees. Furthermore, we also find that when the black hole is in the hard state, the accretion disk would show a significant truncation. The high iron abundance and ionization of the accretion disk obtained in the fitting results can be possibly explained by the high density of the accretion disk.

astro-ph.HE↗

arXiv2021

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of biomarkers. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials.

q-bio.PE↗

arXiv2021

The Disk Veiling Effect of the Black Hole Low-Mass X-ray Binary A0620-00

The optical light curves of quiescent black hole low-mass X-ray binaries often exhibit significant non-ellipsoidal variabilities, showing the photospheric radiation of the companion star is veiled by other source of optical emission. Assessing this "veiling" effect is critical to the black hole mass measurement. Here in this work, we carry out a strictly simultaneous spectroscopic and photometric campaign on the prototype of black hole low-mass X-ray binary A0620-00. We find that for each observation epoch, the extra optical flux beyond a pure ellipsoidal modulation is positively correlated with the fraction of veiling emission, indicating the accretion disk contributes most of the non-ellipsoidal variations. Meanwhile, we also obtain a K2V spectral classification of the companion, as well as the measurements of the companion's rotational velocity $v \sin i = 83.8\pm1.9$ km s$^{-1}$ and the mass ratio between the companion and the black hole $q=0.063\pm0.004$.

astro-ph.HE↗

arXiv2021

Estimating the spin of the black hole candidate MAXI J1659-152 with the X-ray continuum-fitting method

As a transient X-ray binary, MAXI J1659-152 contains a black hole candidate as its compact star. MAXI J1659-152 was discovered on 2010 September 25 during its only known outburst. Previously-published studies of this outburst indicate that MAXI J1659-152 may have an extreme retrograde spin, which, if confirmed, would provide an important clue as to the origin of black hole spin. In this paper, utilizing updated dynamical binary-system parameters (i.e. the black hole mass, the orbital inclination and the source distance) provided by \cite{Torres2021}, we analyze 65 spectra of MAXI J1659-152 from \emph{RXTE}/PCA, in order to assess the spin parameter. With a final selection of 9 spectra matching our $f_{\mathrm{sc}} \lesssim 25 \%$, soft-state criteria, we apply a relativistic thin disk spectroscopic model \texttt{kerrbb2} over 3.0-45.0 keV. We find that inclination angle correlates inversely with spin, and, considering the possible values for inclination angle, we constrain spin to be $-1 < a_{*} \lesssim 0.44$ at 90\% confidence interval via X-ray continuum-fitting. We can only rule out an extreme prograde (positive) spin. We confirm that an extreme retrograde solution is possible and is not ruled out by considering accretion torques given the young age of the system.

astro-ph.HE↗

arXiv2021

Predicting Tau Accumulation in Cerebral Cortex with Multivariate MRI Morphometry Measurements, Sparse Coding, and Correntropy

Biomarker-assisted diagnosis and intervention in Alzheimer's disease (AD) may be the key to prevention breakthroughs. One of the hallmarks of AD is the accumulation of tau plaques in the human brain. However, current methods to detect tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (Tau PET). In our previous work, structural MRI-based hippocampal multivariate morphometry statistics (MMS) showed superior performance as an effective neurodegenerative biomarker for preclinical AD and Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) has excellent ability to generate low-dimensional representations with strong statistical power for brain amyloid prediction. In this work, we apply this framework together with ridge regression models to predict Tau deposition in Braak12 and Braak34 brain regions separately. We evaluate our framework on 925 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject has one pair consisting of a PET image and MRI scan which were collected at about the same times. Experimental results suggest that the representations from our MMS and PASCS-MP have stronger predictive power and their predicted Braak12 and Braak34 are closer to the real values compared to the measures derived from other approaches such as hippocampal surface area and volume, and shape morphometry features based on spherical harmonics (SPHARM).

physics.med-ph↗

arXiv2021

Graph Capsule Aggregation for Unaligned Multimodal Sequences

Humans express their opinions and emotions through multiple modalities which mainly consist of textual, acoustic and visual modalities. Prior works on multimodal sentiment analysis mostly apply Recurrent Neural Network (RNN) to model aligned multimodal sequences. However, it is unpractical to align multimodal sequences due to different sample rates for different modalities. Moreover, RNN is prone to the issues of gradient vanishing or exploding and it has limited capacity of learning long-range dependency which is the major obstacle to model unaligned multimodal sequences. In this paper, we introduce Graph Capsule Aggregation (GraphCAGE) to model unaligned multimodal sequences with graph-based neural model and Capsule Network. By converting sequence data into graph, the previously mentioned problems of RNN are avoided. In addition, the aggregation capability of Capsule Network and the graph-based structure enable our model to be interpretable and better solve the problem of long-range dependency. Experimental results suggest that GraphCAGE achieves state-of-the-art performance on two benchmark datasets with representations refined by Capsule Network and interpretation provided.

cs.CL↗

arXiv2021

Proof of CMB-driven X-ray brightening of high-z radio galaxies

We present a definitive assessment of the role of Inverse Compton scattering of Cosmic Microwave Background photons (IC/CMB) in the context of radio galaxies. Owing to the steep increase of the CMB radiation energy density, IC/CMB is supposed to become progressively more important with respect to radio synchrotron cooling as the redshift increases. For typical energies at play, this process will up-scatter the CMB photons into the X-ray band, and is thus expected to yield a redshift-dependent, concurrent X-ray brightening and radio dimming of the jet-powered structures. Here we show how a conclusive proof of this effect hinges on high-resolution imaging data in which the extended lobes can be distinguished from the compact hot spots where synchrotron-self-Compton dominates the X-ray emission regardless of redshift. We analyze Chandra and Very Large Array data of 11 radio galaxies between 1.3 3 radio galaxies below <1 mJy, IC/CMB alone can not be responsible for a deficit in high-z, radio-loud AGN if--as we argue--such AGN typically have bright, compact hot spots.

astro-ph.HE↗

arXiv2021

Optical and Ultraviolet Monitoring of the Black Hole X-ray Binary MAXI J1820+070/ASASSN-18ey for 18 Months

MAXI J1820+070 is a low-mass black hole X-ray binary system with high luminosity in both optical and X-ray bands during the outburst periods. We present extensive photometry in X-ray, ultraviolet, and optical bands, as well as densely-cadenced optical spectra, covering the phase from the beginning of optical outburst to $\sim$550 days. During the rebrightening process, the optical emission preceded the X-ray by 20.80 $\pm$ 2.85 days. The spectra are characterized by blue continua and emission features of Balmer series, He I, He II lines and broad Bowen blend. The pseudo equivalent width (pEW) of emission lines are found to show anticorrelations with the X-ray flux measured at comparable phases, which is due to the increased suppression by the optical continuum. At around the X-ray peak, the full width at half maximums (FWHMs) of H$_β$ and He II $λ$4686 tend to stabilize at 19.4 Angstrom and 21.8 Angstrom, which corresponds to the line forming region at a radius of 1.7 and 1.3 R_sun within the disk. We further analyzed the absolute fluxes of the lines and found that the fluxes of H$_β$ and He II $λ$4686 show positive correlations with the X-ray flux, favoring that the irradiation model is responsible for the optical emission. However, the fact that X-ray emission experiences a dramatic flux drop at t$\sim$200 days after the outburst, while the optical flux only shows little variations suggests that additional energy such as viscous energy may contribute to the optical radiation in addition to the X-ray irradiation.

astro-ph.HE↗

arXiv2021

Cortical Morphometry Analysis based on Worst Transportation Theory

Biomarkers play an important role in early detection and intervention in Alzheimer's disease (AD). However, obtaining effective biomarkers for AD is still a big challenge. In this work, we propose to use the worst transportation cost as a univariate biomarker to index cortical morphometry for tracking AD progression. The worst transportation (WT) aims to find the least economical way to transport one measure to the other, which contrasts to the optimal transportation (OT) that finds the most economical way between measures. To compute the WT cost, we generalize the Brenier theorem for the OT map to the WT map, and show that the WT map is the gradient of a concave function satisfying the Monge-Ampere equation. We also develop an efficient algorithm to compute the WT map based on computational geometry. We apply the algorithm to analyze cortical shape difference between dementia due to AD and normal aging individuals. The experimental results reveal the effectiveness of our proposed method which yields better statistical performance than other competiting methods including the OT.

cs.GR↗

arXiv2020

Developing Univariate Neurodegeneration Biomarkers with Low-Rank and Sparse Subspace Decomposition

Cognitive decline due to Alzheimer's disease (AD) is closely associated with brain structure alterations captured by structural magnetic resonance imaging (sMRI). It supports the validity to develop sMRI-based univariate neurodegeneration biomarkers (UNB). However, existing UNB work either fails to model large group variances or does not capture AD dementia (ADD) induced changes. We propose a novel low-rank and sparse subspace decomposition method capable of stably quantifying the morphological changes induced by ADD. Specifically, we propose a numerically efficient rank minimization mechanism to extract group common structure and impose regularization constraints to encode the original 3D morphometry connectivity. Further, we generate regions-of-interest (ROI) with group difference study between common subspaces of $Aβ+$ AD and $Aβ-$ cognitively unimpaired (CU) groups. A univariate morphometry index (UMI) is constructed from these ROIs by summarizing individual morphological characteristics weighted by normalized difference between $Aβ+$ AD and $Aβ-$ CU groups. We use hippocampal surface radial distance feature to compute the UMIs and validate our work in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. With hippocampal UMIs, the estimated minimum sample sizes needed to detect a 25$\%$ reduction in the mean annual change with 80$\%$ power and two-tailed $P=0.05$ are 116, 279 and 387 for the longitudinal $Aβ+$ AD, $Aβ+$ mild cognitive impairment (MCI) and $Aβ+$ CU groups, respectively. Additionally, for MCI patients, UMIs well correlate with hazard ratio of conversion to AD ($4.3$, $95\%$ CI=$2.3-8.2$) within 18 months. Our experimental results outperform traditional hippocampal volume measures and suggest the application of UMI as a potential UNB.

cs.CV↗