Abstract In this paper, we introduce a U-Net model of deep learning algorithms for reconstructions of the 3D peculiar velocity field, which simplifies the reconstruction process with enhanced ...precision. We test the adaptability of the U-Net model with simulation data under more realistic conditions, including the redshift space distortion effect and halo mass threshold. Our results show that the U-Net model outperforms the analytical method that runs under ideal conditions, with a 16% improvement in precision, 13% in residuals, 18% in correlation coefficient, and 27% in average coherence. The deep learning algorithm exhibits exceptional capacities to capture velocity features in nonlinear regions and substantially improve reconstruction precision in boundary regions. We then apply the U-Net model trained under Sloan Digital Sky Survey (SDSS) observational conditions to the SDSS Data Release 7 data for observational 3D peculiar velocity reconstructions.
By natural selection, organisms evolve different solutions to cope with extremely cold weather. The emergence of an antifreeze protein gene is one of the most momentous solutions. Antifreeze proteins ...possess an importantly functional ability for organisms to survive in cold environments and are widely found in various cold-tolerant species. In this review, we summarize the origin of antifreeze proteins, describe the diversity of their species-specific properties and functions, and highlight the related biotechnology on the basis of both laboratory tests and bioinformatics analysis. The most recent advances in the applications of antifreeze proteins are also discussed. We expect that this systematic review will contribute to the comprehensive knowledge of antifreeze proteins to readers.
We propose a novel method to constrain the missing fraction of galaxies using galaxy clustering measurements in the galaxy conditional stellar mass function (CSMF) framework, which is applicable to ...surveys that suffer significantly from sample selection effects. The clustering measurements, which are not sensitive to the random sampling (missing fraction) of galaxies, are widely used to constrain the stellar-halo mass relation (SHMR). By incorporating a missing fraction (incompleteness) component into the CSMF model (ICSMF), we use the incomplete stellar mass function and galaxy clustering to simultaneously constrain the missing fractions and the SHMRs. Tests based on mock galaxy catalogs with a few typical missing fraction models show that this method can accurately recover the missing fraction and the galaxy SHMR, hence providing us with reliable measurements of the galaxy stellar mass functions. We then apply it to the Baryon Oscillation Spectroscopic Survey (BOSS) over the redshift range of 0.1 < z < 0.8 for galaxies of M* > 1011 M . We find that the sample completeness for BOSS is over 80% at z < 0.6 but decreases at higher redshifts to about 30%. After taking these completeness factors into account, we provide accurate measurements of the stellar mass functions for galaxies with , as well as the SHMRs, over the redshift range 0.1 < z < 0.8 in this largest galaxy redshift survey.
Fluorescence‐guided cytoreductive surgery is one of the most promising approaches for facile elimination of tumors in situ, thereby improving prognosis. Reported herein is a simple strategy to ...construct a novel chainlike NIR‐II nanoprobe (APP‐Ag2S‐RGD) by self‐assembly of an amphiphilic peptide (APP) into a nanochain with subsequent chemical crosslinking of NIR‐II Ag2S QDs and the tumor‐targeting RGD peptide. This probe exhibits higher capability for cancer cell detection compared with that of RGD‐functionalized Ag2S QDs (Ag2S‐RGD) at the same concentration. Upon intraperitoneal injection, superior tumor‐to‐normal tissue signal ratio is achieved and non‐vascularized tiny tumor metastatic foci as small as about 0.2 mm in diameter could be facilely eliminated under NIR‐II fluorescent imaging guidance. These results clearly indicate the potential of this probe for fluorescence‐guided tumor staging, preoperative diagnosis, and intraoperative navigation.
Nanochains: A novel chainlike NIR‐II nanoprobe (APP‐Ag2S‐RGD) was prepared by APP‐based self‐assembly and chemically crosslinked with Ag2S QDs and RGD peptide. The flexible geometry and multivalent targeting, as well as unique NIR‐II fluorescence properties of APP‐Ag2S‐RGD results in unparalleled detection sensitivity during surgery on peritoneal carcinomas.
Image-guided photothermal therapy (PTT) is an attractive strategy to improve the diagnosis accuracy and treatment outcomes by monitoring the accumulation of photothermal agents in tumors in real-time ...and determining the best treatment window. Taking advantage of the superior imaging quality of NIR-II fluorescence imaging and remote-controllable phototherapy modality of PTT, we developed a facile macromolecular fluorophore (PF) by conjugating a small-molecule NIR-II fluorophore (Flav7) with an amphiphilic polypeptide. The PF can form uniform micelles in aqueous solution, which exhibit a slight negative charge. In vitro experimental results showed that the PF nanoparticles showed satisfactory photophysical properties, prominent photothermal conversion efficiency (42.3%), excellent photothermal stability, negligible cytotoxicity, and photothermal toxicity. Meanwhile, the PF can visualize and feature the tumors by NIR-II fluorescence imaging owing to prolonged blood circulation time and enhanced accumulation in tumors. Moreover, in vivo studies revealed that the PF nanoparticles achieved an excellent photothermal ablation effect on tumors with a low dose of NIR-II dye and light irradiation, and the process can be traced by NIR fluorescence imaging.
Defect prediction has been an active research area for over four decades. Despite numerous studies on defect prediction, the potential value of defect prediction in practice remains unclear. To ...address this issue, we performed a mixed qualitative and quantitative study to investigate what practitioners think, behave and expect in contrast to research findings when it comes to defect prediction. We collected hypotheses from open-ended interviews and a literature review of defect prediction papers that were published at ICSE, ESEC/FSE, ASE, TSE and TOSEM in the last 6 years (2012-2017). We then conducted a validation survey where the hypotheses became statements or options of our survey questions. We received 395 responses from practitioners from over 33 countries across five continents. Some of our key findings include: 1) Over 90 percent of respondents are willing to adopt defect prediction techniques. 2) There exists a disconnect between practitioners' perceptions and well supported research evidence regarding defect density distribution and the relationship between file size and defectiveness. 3) 7.2 percent of the respondents reveal an inconsistency between their behavior and perception regarding defect prediction. 4) Defect prediction at the feature level is the most preferred level of granularity by practitioners. 5) During bug fixing, more than 40 percent of the respondents acknowledged that they would make a "work-around" fix rather than correct the actual error-causing code. Through a qualitative analysis of free-form text responses, we identified reasons why practitioners are reluctant to adopt defect prediction tools. We also noted features that practitioners expect defect prediction tools to deliver. Based on our findings, we highlight future research directions and provide recommendations for practitioners.
We present a new model to describe the galaxy-dark matter connection across cosmic time, which unlike the popular subhalo abundance-matching technique is self-consistent in that it takes account of ...the facts that (1) subhalos are accreted at different times and (2) the properties of satellite galaxies may evolve after accretion. Using observations of galaxy stellar mass functions (SMFs) out to z ~ 4, the conditional SMF at z ~ 0.1 obtained from Sloan Digital Sky Survey galaxy group catalogs, and the two-point correlation function (2PCF) of galaxies at z ~ 0.1 as a function of stellar mass, we constrain the relation between galaxies and dark matter halos over the entire cosmic history from z ~ 4 to the present. This relation is then used to predict the median assembly histories of different stellar mass components within dark matter halos (central galaxies, satellite galaxies, and halo stars). We also make predictions for the 2PCFs of high-z galaxies as function of stellar mass. Our main findings are the following: (1) Our model reasonably fits all data within the observational uncertainties, indicating that the LAMBDACDM concordance cosmology is consistent with a wide variety of data regarding the galaxy population across cosmic time. (2) At low-z, the stellar mass of central galaxies increases with halo mass as M super(0.3) and M super(> ~4.0) at the massive and low-mass ends, respectively. The ratio Mlow *,c/M reveals a maximum of ~0.03 at a halo mass M ~ 10 super(11.8) h super(-1) M sub(middot in circle), much lower than the universal baryon fraction (~0.17). At higher redshifts the maximum in Mlow *,c/M remains close to ~0.03, but shifts to higher halo mass. (3) The inferred timescale for the disruption of satellite galaxies is about the same as the dynamical friction timescale of their subhalos. (4) The stellar mass assembly history of central galaxies is completely decoupled from the assembly history of its host halo; the ratio Mlow *,c/M initially increases rapidly with time until the halo mass reaches ~10 super(12) h super(-1) M sub(middot in circle), at which point Mlow *,c/M ~ 0.03. Once M > ~10 super(12) h super(-1) M sub(middot in circle), there is little growth in Mlow *,c, causing the ratio Mlow *,c/M to decline. In Milky Way (MW)-sized halos more than half of the central stellar mass is assembled at z <, ~ 0.5. (5) In low-mass halos, the accretion of satellite galaxies contributes little to the formation of their central galaxies, indicating that most of their stars must have formed in situ. In massive halos more than half of the stellar mass of the central galaxy has to be formed in situ, and the accretion of satellites can only become significant at z <, ~ 2. (6) The total mass in halo stars is more than twice that of the central galaxy in massive halos, but less than 10% of Mlow *,c in MW-sized halos. (7) The 2PCFs of galaxies on small scales hold important information regarding the evolution of satellite galaxies, which at high-z is predicted to be much steeper than at low-z, especially for more massive galaxies. We discuss various implications of our findings regarding the formation and evolution of galaxies in a LambdaCDM cosmology.
Abstract
We carry out a thermal energy census of hot baryons at
z
< 1, by cross correlating the Planck Modified Internal Linear Combination Algorithm (MILCA)
y
map with 0.8 million clusters/groups ...selected from the Yang et al. catalog. The thermal Sunyaev–Zel’dovich effect around these clusters/groups is reliably obtained, which enables us to make our model constraints based on one-halo (1h) and two-halo (2h) contributions, respectively. (1) The total measurement signal-to-noise (S/N) of the one-halo term is 63. We constrain the
Y
–
M
relation over the halo mass range of 10
13
–10
15
M
⊙
h
−1
, and find
Y
∝
M
α
with
α
= 1.8 at
z
= 0.14 (
α
= 2.1 at
z
= 0.75). The total thermal energy of gas bound to clusters/groups increases from 0.1 meV cm
−3
at
z
= 0.14 to 0.22 meV cm
−3
at
z
= 0.75. (2) The 2h term is used to constrain the bias-weighted electron pressure 〈
b
y
P
e
〉. We find that 〈
b
y
P
e
〉 (in units of meV cm
−3
) increases from 0.24 ± 0.02 at
z
= 0.14 to 0.45 ± 0.02 at
z
= 0.75. These results lead to several implications. (i) The hot gas fraction
f
gas
in clusters/groups monotonically increase with the halo mass, where
f
gas
of a 10
14
M
⊙
h
−1
halo is ∼50% (25%) of the cosmic mean at
z
= 0.14 (0.75). (ii) By comparing the 1h and 2h terms, we obtain a tentative constraint on the thermal energy of unbound gas. (iii) The above results lead to significant suppression of the matter and weak-lensing power spectrum at small scales. These implications are important for astrophysics and cosmology, and we will further investigate them with improved data and gas modeling.
Clusters, filaments, sheets, and voids are the building blocks of the cosmic web. Forming dark matter halos respond to these different large-scale environments, and this in turn affects the ...properties of galaxies hosted by the halos. It is therefore important to understand the systematic correlations of halo properties with the morphology of the cosmic web, as this informs both about galaxy formation physics and possible systematics of weak lensing studies. In this study, we present and compare two distinct algorithms for finding cosmic filaments and sheets, a task which is far less well established than the identification of dark matter halos or voids. One method is based on the smoothed dark matter density field and the other uses the halo distributions directly. We apply both techniques to one high-resolution N-body simulation and reconstruct the filamentary/sheet like network of the dark matter density field. We focus on investigating the properties of the dark matter halos inside these structures, in particular, on the directions of their spins and the orientation of their shapes with respect to the directions of the filaments and sheets. We find that both the spin and the major axes of filament halos with masses 1013 h -1 M are preferentially aligned with the direction of the filaments. The spins and major axes of halos in sheets tend to lie parallel to the sheets. There is an opposite mass dependence of the alignment strength for the spin (negative) and major (positive) axes, i.e. with increasing halo mass the major axis tends to be more strongly aligned with the direction of the filament, whereas the alignment between halo spin and filament becomes weaker with increasing halo mass. The alignment strength as a function of the distance to the most massive node halo indicates that there is a transit large-scale environment impact: from the two-dimensional collapse phase of the filament to the three-dimensional collapse phase of the cluster/node halo at small separation. Overall, the two algorithms for filament/sheet identification investigated here agree well with each other. The method based on halos alone can be easily adapted for use with observational data sets.
Honeycomb structures, inspired from bee honeycombs, had found widespread applications in various fields, including architecture, transportation, mechanical engineering, chemical engineering, ...nanofabrication and, recently, biomedicine. A major challenge in this field is to understand the unique properties of honeycomb structures, which depended on their structures, scales and the materials used. In this article, we presented a state-of-the-art review of the interdisciplinary efforts to better understand the design principles for products with honeycomb structures, including their fabrication, performance (e.g., mechanical, thermal and acoustic properties) as well as optimization design. We described how these structural perspectives have led to new insights into the design of honeycomb structures ranging from macro-, micro- to nano-scales. We presented current scientific advances in micro- and nano-technologies that hold great promise for bioinspired honeycomb structures. We also discussed the emerging applications of honeycomb structures in biomedicine such as tissue engineering and regenerative medicine. Understanding the design principles underlying the creation of honeycomb structures as well as the related scientific discovery and technology development is critical for engineering bioinspired materials and devices designed based on honeycomb structures for a wide range of practical applications.
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