Estimation and inference for high-dimensional nonparametric additive instrumental-variables regression

The method of instrumental variables provides a fundamental and practical tool for causal inference in many empirical studies where unmeasured confounding between the treatments and the outcome is present. Modern data such as the genetical genomics data from these studies are often high-dimensional. The high-dimensional linear instrumental-variables regression has been considered in the literature due to its simplicity albeit a true nonlinear relationship may exist. We propose a more data-driven approach by considering the nonparametric additive models between the instruments and the treatments while keeping a linear model between the treatments and the outcome so that the coefficients therein can directly bear causal interpretation. We provide a two-stage framework for estimation and inference under this more general setup. The group lasso regularization is first employed to select optimal instruments from the high-dimensional additive models, and the outcome variable is then regressed on the fitted values from the additive models to identify and estimate important treatment effects. We provide non-asymptotic analysis of the estimation error of the proposed estimator. A debiasing procedure is further employed to yield valid inference. Extensive numerical experiments show that our method can rival or outperform existing approaches in the literature. We finally analyze the mouse obesity data and discuss new findings from our method.Comment: Submitted versio

Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification

Long-Term Person Re-Identification (LT-ReID) has become increasingly crucial in computer vision and biometrics. In this work, we aim to extend LT-ReID beyond pedestrian recognition to include a wider range of real-world human activities while still accounting for cloth-changing scenarios over large time gaps. This setting poses additional challenges due to the geometric misalignment and appearance ambiguity caused by the diversity of human pose and clothing. To address these challenges, we propose a new approach 3DInvarReID for (i) disentangling identity from non-identity components (pose, clothing shape, and texture) of 3D clothed humans, and (ii) reconstructing accurate 3D clothed body shapes and learning discriminative features of naked body shapes for person ReID in a joint manner. To better evaluate our study of LT-ReID, we collect a real-world dataset called CCDA, which contains a wide variety of human activities and clothing changes. Experimentally, we show the superior performance of our approach for person ReID.Comment: 10 pages, 7 figures, accepted by ICCV 202

On constraining Cosmology and the Halo Mass Function with Weak Gravitational Lensing

The discrepancy between the weak lensing (WL) and the {\it Planck} measurements of $S_8$ has been a subject of several studies. These studies tend to show that a suppression of the amplitude of the mass power spectrum $P(k)$ at high $k$ could resolve it. The WL signal at small-scale is sensitive to various effects, such as baryonic effects and intrinsic alignment. The accuracy of $P(k)$ depends on the modelling precision of these effects. A common approach for calculating $P(k)$ relies on a halo model. Amongst the various components necessary for the construction of $P(k)$, the halo mass function (HMF) is an important one. Traditionally, the HMF has been assumed to follow a fixed model. Recent literature shows that baryonic physics, amongst several other factors, could affect the HMF. In this study, we investigate the impact of allowing the HMF to vary. This provides a way of testing the validity of the halo model-HMF calibration using data. We find that the {\it Planck} cosmology is not compatible with the vanilla HMF for both the DES-y3 and the KiDS-1000 data. When the cosmology and the HMF parameters are allowed to vary, the {\it Planck} cosmology is no longer in tension. The modified HMF predicts a matter power spectrum with a $\sim 25\%$ power loss at $k\sim 1~{\rm h/Mpc}$, in agreement with the recent studies. We show that Stage IV surveys will be able to measure the HMF parameters with a few percent accuracy.Comment: 16 pages (including appendixes), 10 figures, 3 tables, main results in Figs. 5&

Cosmic star formation history with tomographic CIB-galaxy cross-correlation

In this work, we probe the star formation history of the Universe using tomographic cross-correlation between the cosmic infrared background (CIB) and galaxy samples. The galaxy samples are from the Kilo-Degree Survey (KiDS), while the CIB maps are made from \planck\, sky maps. We measure the cross-correlation in harmonic space with a significance of 43$\sigma$. We model the cross-correlation with a halo model, which links CIB anisotropies to star formation rates (SFR) and galaxy abundance. We assume that SFR has a lognormal dependence on halo mass, while galaxy abundance follows the halo occupation distribution (HOD) model. The cross-correlations give a best-fit maximum star formation efficiency of $\eta_{\mathrm{max}}= 0.41^{+0.09}_{-0.14}$ at a halo mass $\log_{10}(M_{\mathrm{peak}}/M_{\odot})= {12.14\pm 0.36}$. The derived star formation rate density (SFRD) is well constrained up to $z\sim 1.5$. The constraining power at high redshift is mainly limited by the KiDS survey depth. A combination with external SFRD measurements from previous studies gives $\log_{10}(M_{\mathrm{peak}}/M_{\odot})=12.42^{+0.35}_{-0.19}$. This tightens the SFRD constraint up to $z=4$, yielding a peak SFRD of $0.09_{-0.004}^{+0.003}\,M_{\odot} \mathrm { year }^{-1} \mathrm{Mpc}^{-3}$ at $z=1.74^{+0.06}_{-0.02}$, corresponding to a lookback time of $10.05^{+0.12}_{-0.03}$ Gyr. Both constraints are consistent, and the derived SFRD agrees with previous studies and simulations. Additionally, we estimate the galaxy bias $b$ of KiDS galaxies from the constrained HOD parameters and yield an increasing bias from $b=1.1_{-0.31}^{+0.17}$ at $z=0$ to $b=1.96_{-0.64}^{+0.18}$ at $z=1.5$. Finally, we provide a forecast for future galaxy surveys and conclude that, due to their considerable depth, future surveys will yield a much tighter constraint on the evolution of the SFRD.Comment: 22 pages, 14 figures, 3 tables, the abstract is abridge

Epigenome-wide gene–age interaction study reveals reversed effects of MORN1 DNA methylation on survival between young and elderly oral squamous cell carcinoma patients

DNA methylation serves as a reversible and prognostic biomarker for oral squamous cell carcinoma (OSCC) patients. It is unclear whether the effect of DNA methylation on OSCC overall survival varies with age. As a result, we performed a two-phase gene–age interaction study of OSCC prognosis on an epigenome-wide scale using the Cox proportional hazards model. We identified one CpG probe, cg11676291MORN1, whose effect was significantly modified by age (HRdiscovery = 1.018, p = 4.07 × 10−07, FDR-q = 3.67 × 10−02; HRvalidation = 1.058, p = 8.09 × 10−03; HRcombined = 1.019, p = 7.36 × 10−10). Moreover, there was an antagonistic interaction between hypomethylation of cg11676291MORN1 and age (HRinteraction = 0.284; 95% CI, 0.135–0.597; p = 9.04 × 10−04). The prognosis of OSCC patients was well discriminated by the prognostic score incorporating cg11676291MORN1–age interaction (HRhigh vs. low = 3.66, 95% CI: 2.40–5.60, p = 1.93 × 10−09). By adding 24 significant gene–age interactions using a looser criterion, we significantly improved the area under the receiver operating characteristic curve (AUC) of the model at 3- and 5-year prognostic prediction (AUC3-year = 0.80, AUC5-year = 0.79, C-index = 0.75). Our study identified a significant interaction between cg11676291MORN1 and age on OSCC survival, providing a potential therapeutic target for OSCC patients

Probing galaxy bias and intergalactic gas pressure with KiDS Galaxies-tSZ-CMB lensing cross-correlations

We constrain the redshift dependence of gas pressure bias $\left\langle b_{y} P_{\mathrm{e}}\right\rangle$ (bias-weighted average electron pressure), which characterises the thermodynamics of intergalactic gas, through a combination of cross-correlations between galaxy positions and the thermal Sunyaev-Zeldovich (tSZ) effect, as well as galaxy positions and the gravitational lensing of the cosmic microwave background (CMB). The galaxy sample is from the fourth data release of the Kilo-Degree Survey (KiDS). The tSZ $y$ map and the CMB lensing map are from the {\textit{Planck}} 2015 and 2018 data releases, respectively. The measurements are performed in five redshift bins with $z\lesssim1$. With these measurements, combining galaxy-tSZ and galaxy-CMB lensing cross-correlations allows us to break the degeneracy between galaxy bias and gas pressure bias, and hence constrain them simultaneously. In all redshift bins, the best-fit values of \bpe are at a level of $\sim 0.3\, \mathrm{meV/cm^3}$ and increase slightly with redshift. The galaxy bias is consistent with unity in all the redshift bins. Our results are not sensitive to the non-linear details of the cross-correlation, which are smoothed out by the {\textit{Planck}} beam. Our measurements are in agreement with previous measurements as well as with theoretical predictions. We also show that our conclusions are not changed when CMB lensing is replaced by galaxy lensing, which shows the consistency of the two lensing signals despite their radically different redshift ranges. This study demonstrates the feasibility of using CMB lensing to calibrate the galaxy distribution such that the galaxy distribution can be used as a mass proxy without relying on the precise knowledge of the matter distribution.Comment: 20 pages, 14 figures, 3 tables, accepted for publication on Astronomy & Astrophysic

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Mechanism of Cuttings Removing at the Bottom Hole by Pulsed Jet

Vibration drilling technology induced by hydraulic pulse can assist the bit in breaking rock at deep formation. Simultaneously, the pulsed jet generated by the hydraulic pulse promotes removal of the cuttings from the bottom hole. Nowadays, the cuttings removal mechanism of the pulsed jet is not clear, which causes cuttings to accumulate at the bottom hole and increases the risk of repeated cutting. In this paper, a pressure-flow rate fluctuation model is established to analyze the fluctuation characteristics of the pulsed jet at the bottom hole. Based on the model, the effects of displacement, well depth, drilling fluid viscosity, and flow area of the pulsed jet tool on the feature of instantaneous flow at the bottom hole are discussed. The results show that the pulsed jet causes flow rate and pressure to fluctuate at the bottom hole. When the displacement changes from 20 L/s to 40 L/s in a 2000 m well, the pulsed jet generates a flow rate fluctuation of 4–9 L/s and pressure fluctuation of 0.1–0.5 MPa at the bottom hole. With the flow area of the tool increasing from 2 cm2 to 4 cm2, the amplitude of flow rate fluctuation decreases by 72.5%, and the amplitude of pressure fluctuation decreases by more than 60%. Combined with the fluctuation feature of the flow field and the water jet attenuation law at the bottom hole, the force acting on the cuttings under the pulsed jet is derived. It is found that flow rate fluctuation improves the mechanical state of cuttings and is beneficial for cuttings tumbled off the bottom hole. This research provides theoretical guidance for pulsed jet cuttings cleaning at the bottom hole

characterizationofcomncatalystbyinsituxrayabsorptionspectroscopyandwaveletanalysisforfischertropschtoolefinsreaction

Cobalt carbide has recently been reported to catalyse the FTO con version of syngas with high selectivity for the production of lower olefins (C2-C4). Clarifying the formation process and atomic structure of cobalt carbide will help understand the catalytic mechanism of FTO. Herein, hydrogenati on of carb on monoxide was investigated for cobalt carbide synthesized from CoMn catalyst, followed by X-ray diffraction, transmission electron microscopy, temperature programmed reaction and in situ X-ray absorption spectroscopy. By monitoring the evolution of cobalt carbide during syngas conversion, the wavelet transform results give evidenee for the formation of the cobalt carbide and clearly demonstrate that the active site of catalysis was cobalt carbide

characterizationofcomncatalystbyinsituxrayabsorptionspectroscopyandwaveletanalysisforfischertropschtoolefinsreaction

Cobalt carbide has recently been reported to catalyse the FTO conversion of syngas with high selectivity for the production of lower olefins(C_2 –C_4). Clarifying the formation process and atomic structure of cobalt carbide will help understand the catalytic mechanism of FTO. Herein, hydrogenation of carbon monoxide was investigated for cobalt carbide synthesized from CoMn catalyst, followed by X-ray diffraction, transmission electron microscopy, temperature programmed reaction and in situ X-ray absorption spectroscopy. By monitoring the evolution of cobalt carbide during syngas conversion, the wavelet transform results give evidence for the formation of the cobalt carbide and clearly demonstrate that the active site of catalysis was cobalt carbide