Abstract Cold and cool gas (T ≤ 104 K) in the circumgalactic medium (CGM) and its interaction with galaxies remain poorly understood. Simulations predict that cold gas flows into galaxies through cosmic filaments, determining the disk formation and galaxy evolution. The cold gas accretion modes in the CGM and their dependence on dark matter halo mass and redshift remain puzzling. Resolving the kiloparsec-scale kinematics and dynamics of cold gas interacting with the disk, dust, and metals in different environments is particularly lacking at z > 2. Here we report two disturbed cold gas structures traced by ultra-strong MgII absorbers (rest-frame equivalent width Wr > 2 Å) exhibiting high kinematic velocities (> 500 km/s) and their environments at z ~ 4.9 and z ~ 2.6. Observations were conducted with VLT/MUSE, JWST/NIRCam, and ALMA to detect Lyα and nebular emission lines, as well as dust continuum emission in the vicinity of these two absorbing gas structures. We identify two Lyα emitters associated with a strong MgII absorber pair separated by ~1000 km/s at z ~ 4.87. The pair exhibits relative differences in metallicity, dust content, and ionization states, suggesting internal metal and dust exchange within the ultra-large cold gas structure. For the strong MgII absorber at z = 2.5652, we detect a dusty star-forming galaxy at a projected distance of D = 38 kpc. This galaxy exhibits prominent HeI, [SIII], and Paschenγ lines, along with significant dust continuum. It has a star formation rate of ~ 121+/-33 M☉/yr and likely harbors a rotating disk. These findings tentatively suggest that cold gas at high redshifts plays a critical role in driving disk formation and actively participates in the transfer of metals and dust within the overdense regions of the CGM.
In this paper, we consider nonsubsampled graph filter banks (NSGFBs) to process data on a sparse graph. The analysis filter banks of NSGFBs have small bandwidth, pass/block the normalized constant signal, and have stability on ℓ 2 . Given an analysis filter bank with small bandwidth, we introduce algebraic and optimization methods to construct well-localized synthesis filter banks such that the corresponding NSGFBs provide a perfect signal reconstruction in the noiseless setting. We also prove that the proposed NSGFBs can control the resonance effect in the presence of bounded noise and they can limit the influence of shot noise primarily to a small neighborhood near its location on the graph. We later introduce an iterative algorithm to implement the proposed NSGFBs in a distributed manner, and develop an NSGFB-based denoising technique which is demonstrated to have satisfactory performance on noise suppression.
Dictionary learning aims to find a dictionary under which the training data can be sparsely represented, and it is usually achieved by iteratively applying two stages: sparse coding and dictionary update. Typical methods for dictionary update focuses on refining both dictionary atoms and their corresponding sparse coefficients by using the sparsity patterns obtained from sparse coding stage, and hence it is a non-convex bilinear inverse problem. In this paper, we propose a Rank-One Matrix Decomposition (ROMD) algorithm to recast this challenge into a convex problem by resolving these two variables into a set of rank-one matrices. Different from methods in the literature, ROMD updates the whole dictionary at a time using convex programming. The advantages hence include both convergence guarantees for dictionary update and faster convergence of the whole dictionary learning. The performance of ROMD is compared with other benchmark dictionary learning algorithms. The results show the improvement of ROMD in recovery accuracy, especially in the cases of high sparsity level and fewer observation data.
Conjugate phase retrieval considers the recovery of a function, up to a unimodular constant and conjugation, from its phaseless measurements. In this paper, we explore the conjugate phase retrieval in a shift-invariant space generated by a Gaussian funciton. First, we show that the modulus function in the Gaussian shift-invariant space can be determined from the phaseless Hermite samples taken on a discrete sampling set. We then show that a function in the shift-invariant space generated by a Gaussian can be uniquely determined, up to a unimodular constant and conjugation, from its phaseless Hermite samples on a discrete set. For the functions with finite coefficient sequences, we provide an explicit reconstruction procedure.
Background: Previous studies have confirmed that artemisinin can prevent arrhythmia by inhibiting K+ currents. Recent findings have shown that artemisinin attenuates sodium current in nodose ganglion and endocrine cells of rats. This study investigated the effects of artemisinin on peak sodium current in ventricular myocytes. Methods: Rat ventricular myocytes were isolated by Langendorff reverse aortic perfusion method. Peak sodium current was recorded using the whole-cell patch clamp technique. Results: The INa was reduced by 50 μM artemisinin, and the steady-state activation and inactivation curves were shifted toward the left. The time constant τ of the steady-state recovery curve increased from 2.89 ms to 7.13 ms. Conclusions: Artemisinin attenuates INa by modulating the voltage dependence of the Na+ channel similar to the class I anti-arrhythmia agents.
The efficient and even distribution of resources on land cover is the key issue of these days. Information system plays vital role in planning and development land cover. The most advanced computer based information technology tool for spatial planning is the Geographic Information System, which become indispensable in planning and management of database. GIS is one of the fastest growing technologies and has became as powerful and modish way to manage vast amounts of geospatial data. It provides an skillful system by which information on location, spatial interaction and geographic relationship of various facilities can be assessed and viewed in moments. It facilitates effective and efficient means to view and access geospatial data and thus to improve decision making process. The volume, quality, and resolution of geospatial data are increasing exponentially. The development of knowledge based geospatial information system is an appropriate approach to solve the problem of efficient distribution of resources on land cover. In this paper the architecture of such system is presented.
In this paper, we consider an infinite dimensional phase retrieval problem to reconstruct real-valued signals living in a shift-invariant space from their phaseless samples taken on a discrete set with finite sampling density.In this paper, we also propose a suboptimal reconstruction algorithm when its noisy phaseless samples are available only.Numerical simulations are performed to demonstrate the stable reconstruction of B-spline signals from their noisy phaseless samples.
In order to meet the needs of intellectual property protection and controlled sharing of scientific research sensitive data, a mechanism is proposed for security protection throughout "transfer, store and use" process of sensitive data which based on blockchain. This blockchain bottom layer security is reinforced. First, the encryption algorithm used is replaced by the national secret algorithm and the smart contract is encapsulated as API at the gateway level. Signature validation is performed when the API is used to prevent illegal access. Then the whole process of data up-chain, storage and down-chain is encrypted, and a mechanism of data structure query and data query condition construction based on blockchain smart is provided to ensure that the data is "usable and invisible". Finally, data access control is ensured through role-based and hierarchical protection, and the blockchain base developed has good extensibility, which can meet the requirement of sensitive data security protection in scientific research filed and has broad application prospects.
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