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Researching the rheology contributes to enhancing the physical and mechanical properties of concrete and promoting material sustainability. Despite the challenges posed by numerous factors influencing viscosity, leveraging machine learning in the era of big data emerges as a viable solution for predicting the general properties of construction materials. This study aims to create models to forecast the rheological properties of cementitious materials containing fly ash and nanosilica. Four models—Random Forest, XGBoost, ANN, and RNN (Stacked LSTM)—are employed to predict and assess shear rate versus shear stress and shear rate versus apparent viscosity curves. Through hyperparameter adjustments, RNN (Stacked LSTM) exhibits excellent performance, achieving a coefficient of determination (R2) of 0.9582 and 0.9257 for the two curves, demonstrating superior statistical parameters and fitting effects. The RNN (Stacked LSTM) exhibited a better generalization ability, suggesting it will be more reliable for future prediction in cementitious material viscosity.

Abstract Currently, most of the methods for mineral materials analysis generate secondary pollution, which is detrimental to human health. For instance, traditional methods for sphalerite analysis in the zinc (Zn) smelting industry including chemical titration, atomic absorption spectrometry, and inductively coupled atomic emission spectroscopy. Colored indicators and toxic heavy metals are used in the analytical processes, causing severe pollution. For some methods, liquid is transformed into gaseous plasma, which is more dangerous to human health. Due to large quantities of sphalerite being used, secondary pollution cannot be ignored. This study proposes a green analysis method for the detection of sphalerite based on colorimetry, which does not generate secondary pollution. The results show that the strong substitution ability of iron (Fe) for Zn contributes to their inverse correlation in contents. The lattice parameters decrease with the increasing Fe content, resulting in a darker coloration. Here, key colorimetry parameters of L*, a*, and b* show clear linear correlations with the Zn and Fe contents. Compared with traditional approaches, this new method is environmental friendly with high sensitivity and accuracy. The relative error and relative standard deviation were less than 10% and 5%, respectively. This study provides a significant reference for nonpollution determination of other mineral materials.

Mica is a harmful substance in sand and occurs frequently. The application of super standard mica sand is a difficult problem in large-scale engineering. In this work, the effects of an interface modifier, mineral admixture, and a curing system on the properties of cement-based materials with super standard mica sand were studied. The strength of cement-based materials linearly decreases with the mica content in sand. When the mica content in sand exceeds 6%, the compressive strength of mortar and concrete at 28 d decreases by more than 22.3% and 33.5%, respectively. By adding the silane coupling agent (SCA) of 50% mica mass and curing in natural conditions, the compressive strength of mortar increases by 10.9%. The cement-based materials with the SCA are more suitable for curing in natural conditions, and the performance of the SCA will not be affected by adding appropriate amounts of mineral admixture. The drying shrinkage strain of the concrete, with the sand containing high mica content modified by SCA, is reduced by 10.5%, and the diffusion of chloride ions in concrete is reduced. The XRD results show that the addition of the interfacial agent does not change the hydration products. The MIP and SEM results show that the SCA can form a bridge structure between the hydration products and the mica, improve the bonding strength of the interface zone, and reduce the number of harmful pores.

We characterize the multiphase circumgalactic medium (CGM) and galaxy properties at z = 6.0–6.5 in four quasar fields from the James Webb Space Telescope A SPectroscopic survey of biased halos In the Reionization Era (ASPIRE) program. We use the Very Large Telescope/X-shooter spectra of quasar J0305–3150 to identify one new metal absorber at z = 6.2713 with multiple transitions (O i , Mg ii , Fe ii, and C ii ). They are combined with the published absorbing systems in Davies et al. at the same redshift range to form a sample of nine metal absorbers at z = 6.03–6.49. We identify eight galaxies within 1000 km s ^−1 and 350 kpc around the absorbing gas from the ASPIRE spectroscopic data, with their redshifts secured by [O iii ] ( λ λ 4959, 5007) doublets and H β emission lines. Our spectral energy distribution fitting indicates that the absorbing galaxies have stellar masses ranging from 10 ^7.2 to 10 ^8.8 M _⊙ and metallicity between 0.02 and 0.4 solar. Notably, the z = 6.2713 system in the J0305–3150 field resides in a galaxy overdensity region, which contains two (tentatively) merging galaxies within 350 kpc and seven galaxies within 1 Mpc. We measure the relative abundances of α elements to iron ([ α /Fe]) and find that the CGM gas in the most overdense region exhibits a lower [ α /Fe] ratio. Our modeling of the galaxy’s chemical abundance favors a top-heavy stellar initial mass function and hints that we may be witnessing the contribution of the first generation of Population III stars to the CGM at the end of the reionization epoch.

Abstract Background Gastric cancer (GC) ranks fourth among the causes of death from malignant tumors in the world. Studies have implicated the dysregulation of circRNAs with GC. However, the relationship between hsa‐circ‐0052001 and GC is unclear. Methods In our current study, we assessed the expression levels of hsa‐circ‐0052001 in GC cells and tissues using quantitative real‐time PCR (qPCR). The role of hsa‐circ‐0052001 expression on the proliferation and invasion of GC cells was assessed using in vitro experiments. The role of hsa‐circ‐0052001 on the proliferation of GC cells was also analyzed using in vivo models. The pathways downstream of hsa‐circ‐0052001 were identified using bioinformatics analyses, western blot (WB) assays, and qRT‐PCR. Results We found that compared with normal gastric mucosa epithelial cells and adjacent paracancer tissues, hsa‐circ‐0052001 was overexpressed in GC cells and tissues. Also, the hsa‐circ‐0052001 level was linked to patient clinicopathological characteristics of GC. Cell proliferation and metastatic ability were inhibited in gastric cancer cells when hsa‐circ‐0052001 was knocked down in vitro and cancer growth in vivo. Mechanistically, hsa‐circ‐0052001 promoted the carcinogenesis of GC cells via the MAPK signal pathway. Conclusion Hsa‐circ‐0052001 functions as a tumor gene in promoting the progression of GC through MAPK pathway, which has provided a promising target for patients with GC.

Traditional fish farming methods suffer from backward production, low efficiency, low yield, and environmental pollution. As a result of thorough research using deep learning technology, the industrial aquaculture model has experienced gradual maturation. A variety of complex factors makes it difficult to extract effective features, which results in less-than-good model performance. This paper proposes a fish detection method that combines a triple attention mechanism with a You Only Look Once (TAM-YOLO)model. In order to enhance the speed of model training, the process of data encapsulation incorporates positive sample matching. An exponential moving average (EMA) is incorporated into the training process to make the model more robust, and coordinate attention (CA) and a convolutional block attention module are integrated into the YOLOv5s backbone to enhance the feature extraction of channels and spatial locations. The extracted feature maps are input to the PANet path aggregation network, and the underlying information is stacked with the feature maps. The method improves the detection accuracy of underwater blurred and distorted fish images. Experimental results show that the proposed TAM-YOLO model outperforms YOLOv3, YOLOv4, YOLOv5s, YOLOv5m, and SSD, with a mAP value of 95.88%, thus providing a new strategy for fish detection.

In aquatic animals, microbial communities associated with the host exert powerful influences on physiology, reproduction, nutrient metabolism, and phenotypic traits, as well as complex host behaviors. This relationship between host and microbes suggests that host-microbiota interactions might have influenced the host's genetic and phenotypic variation. To improve our understanding of how microbes and hosts interact and produce phenotypes, it is necessary to focus on animal phenotypic traits as a basis to understand the potential roles for the microbiome in shaping host phenotypes. Here, we review the literatures on the influences of host genetic and environmental effects on intestinal microbial community structure, and corresponding effects of microbiomes on aquatic animal host phenotypes and genetic breeding. This review provides a better understanding of how the gut microbiota establishes a connection with host genetic factors, while modulating the intestinal microbiota to affect phenotypic differentiation. A more detailed understanding of how the microbiota influences host phenotypes might contribute to determining the role of gut microbiota in the field of genetic breeding of aquatic animals.

The Fe ii /Mg ii emission line flux ratio in quasar spectra serves as a proxy for the relative Fe to α -element abundances in the broad-line regions of quasars. Due to the expected different enrichment timescales of the two elements, they can be used as a cosmic clock in the early Universe. We present a study of the Fe ii /Mg ii ratios in a sample of luminous quasars exploiting high-quality near-IR spectra taken primarily by the XQR-30 program with VLT XSHOOTER. These quasars have a median bolometric luminosity of log( L _bol [erg s ^−1 ]) ∼ 47.3 and cover a redshift range of z = 6.0–6.6. The median value of the measured Fe ii /Mg ii ratios is ∼7.9 with a normalized median absolute deviation of ∼2.2. In order to trace the cosmic evolution of Fe ii /Mg ii in an unbiased manner, we select two comparison samples of quasars with similar luminosities and high-quality spectra from the literature, one at intermediate redshifts ( z = 3.5–4.8) and the other at low redshifts ( z = 1.0–2.0). We perform the same spectral analysis for all these quasars, including the usage of the same iron template, the same spectral fitting method, and the same wavelength fitting windows. We find no significant redshift evolution in the Fe ii /Mg ii ratio over the wide redshift range from z = 1 to 6.6. The result is consistent with previous studies and supports the scenario of a rapid iron enrichment in the vicinity of accreting supermassive black holes at high redshift.

We present strong constraints on the spacetime variation of the fine-structure constant α using the Dark Energy Spectroscopic Instrument (DESI). In this pilot work, we utilize ∼110,000 galaxies with strong and narrow [O iii ] λ λ 4959, 5007 emission lines to measure the relative variation Δ α / α in space and time. The [O iii ] doublet is arguably the best choice for this purpose owing to its wide wavelength separation between the two lines and its strong emission in many galaxies. Our galaxy sample spans a redshift range of 0 < z < 0.95, covering half of all cosmic time. We divide the sample into subsamples in 10 redshift bins (Δ z = 0.1), and calculate Δ α / α for the individual subsamples. The uncertainties of the measured Δ α / α are roughly between 2 × 10 ^−6 and 2 × 10 ^−5 . We find an apparent α variation with redshift at a level of Δ α / α = (2–3) × 10 ^−5 . This is highly likely to be caused by systematics associated with wavelength calibration, since such small systematics can be caused by a wavelength distortion of 0.002–0.003 Å, which is beyond the accuracy that the current DESI data can achieve. We refine the wavelength calibration using sky lines for a small fraction of the galaxies, but this does not change our main results. We further probe the spatial variation of α in small redshift ranges, and do not find obvious, large-scale structures in the spatial distribution of Δ α / α . As DESI is ongoing, we will include more galaxies, and by improving the wavelength calibration, we expect to obtain a better constraint that is comparable to the strongest current constraint.

We study the environment of the z = 6.33 ultraluminous quasar SDSS J010013.02+280225.8 (J0100) to understand its association with large-scale structure. Theoretical models propose high-redshift quasars as markers of galaxy overdensities residing in the most massive dark matter halos (DMHs) in the early Universe. J0100 is an ultraluminous quasar with the most massive black hole known at z ≳ 6, suggesting a high likelihood of residing in a massive DMH. We present wide-field (∼522 arcmin ^2 ) imaging in the r , i , and z bands from the Large Binocular Cameras on the Large Binocular Telescope, with Y- and J -band imaging from the Wide-field Infrared Camera on the Canada–France–Hawaii Telescope, centered on J0100. Applying color selections, we identify 23 objects as i -dropout Lyman break galaxy (LBG) candidates in the J0100 field. We use the deep photometric catalog in the 1.27 deg ^2 COSMOS field to calculate the density of LBGs in a blank field, and to estimate the selection completeness and purity. The observed surface density of LBG candidates in the J0100 field corresponds to a galaxy overdensity of δ = 4 (at 8.4 σ ). This large-scale overdensity suggests that the ∼22 arcmin ^2 overdensity found by Kashino et al. using JWST data extends out to much larger scales. We calculate the angular autocorrelation function of the candidates and find a positive correlation on ≲10′ scales as well as evidence of asymmetries in their spatial distribution, further suggesting the direct detection of large-scale structure in the field of the ultraluminous quasar J0100.

The James Webb Space Telescope provides an unprecedented opportunity for unbiased surveys of H α -emitting galaxies at z > 4 with the NIRCam's wide-field slitless spectroscopy (WFSS). In this work, we present a census of Ly α escape fraction ( f _esc,Ly _α ) of 165 star-forming galaxies at z = 4.9–6.3, utilizing their H α emission directly measured from FRESCO NIRCam/WFSS data. We search for Ly α emission of each H α -emitting galaxy in the Very Large Telescope/MUSE data. The overall f _esc,Ly _α measured by stacking is 0.090 ± 0.006. We find that f _esc,Ly _α displays a strong dependence on the observed UV slope ( β _obs ) and E ( B − V ), such that the bluest galaxies ( β _obs ∼ −2.5) have the largest escape fractions ( f _esc,Ly _α ≈ 0.6), indicative of the crucial role of dust and gas in modulating the escape of Ly α photons. f _esc,Ly _α is less well related to other parameters, including the UV luminosity and stellar mass, and the variation in f _esc,Ly _α with them can be explained by their underlying coupling with E ( B − V ) or β _obs . Our results suggest a tentative decline in f _esc,Ly _α at z ≳ 5, implying increasing intergalactic medium attenuation toward higher redshift. Furthermore, the dependence of f _esc,Ly _α on β _obs is proportional to that of the ionizing photon escape fraction ( f _esc,LyC ), indicating that the escape of Ly α and ionizing photon may be regulated by similar physical processes. With f _esc,Ly _α as a proxy to f _esc,LyC , we infer that UV-faint ( M _UV > −16) galaxies contribute >70% of the total ionizing emissivity at z = 5–6. If these relations hold during the epoch of reionization, UV-faint galaxies can contribute the majority of UV photon budget to reionize the Universe.

We present the final data from the Sloan Digital Sky Survey (SDSS) Reverberation Mapping (RM) project, a precursor to the SDSS-V Black Hole Mapper RM program. This data set includes 11 yr photometric and 7 yr spectroscopic light curves for 849 broad-line quasars over a redshift range of 0.1 < z < 4.5 and a luminosity range of L _bol = 10 ^44−47.5 erg s ^−1 , along with spectral and variability measurements. We report 23, 81, 125, and 110 RM lags (relative to optical continuum variability) for broad H α , H β , Mg ii , and C iv using the SDSS-RM sample, spanning much of the luminosity and redshift ranges of the sample. Using 30 low-redshift RM active galactic nuclei with dynamical-modeling black hole masses, we derive a new estimate of the average virial factor of $\left\langle \mathrm{log}f\right\rangle =0.62\pm 0.07$ for the line dispersion measured from the rms spectrum. The intrinsic scatter of individual virial factors is 0.31 ± 0.07 dex, indicating a factor of 2 systematic uncertainty in RM black hole masses. Our lag measurements reveal significant R – L relations for H β and Mg ii at high redshift, consistent with the latest measurements based on heterogeneous samples. While we are unable to robustly constrain the slope of the R – L relation for C iv given the limited dynamic range in luminosity, we found substantially larger scatter in C iv lags at fixed L _1350 . Using the SDSS-RM lag sample, we derive improved single-epoch (SE) mass recipes for H β , Mg ii , and C iv , which are consistent with their respective RM masses as well as between the SE recipes from two different lines, over the luminosity range probed by our sample. The new H β and Mg ii recipes are approximately unbiased estimators at given RM masses, but there are systematic biases in the C iv recipe. The intrinsic scatter of SE masses around RM masses is ∼0.45 dex for H β and Mg ii , increasing to ∼0.58 dex for C iv .

We study 10 spectroscopically confirmed Ly α emitters (LAEs) at z ≈ 3.1 in the Ultra Deep Survey field, covered by the James Webb Space Telescope/NIRCam in the Public Release Imaging for Extragalactic Research program. All LAEs are detected in all NIRCam bands from F090W to F444W, corresponding to rest frame wavelengths of 2200 Å to 1.2 μ m. Based on morphological analysis of the F200W images, three out of the 10 targets are resolved into pair-like systems with separations of

We present a study of a sample of 45 spectroscopically confirmed, UV luminous galaxies at z ∼ 6. They were selected as bright Lyman-break galaxies (LBGs) using deep multiband optical images in more than 2 deg ^2 of the sky, and subsequently identified via their strong Ly α emission. The majority of these LBGs span an absolute UV magnitude range from −22.0 to −20.5 mag with Ly α equivalent width (EW) between ∼10 and ∼200 Å, representing the most luminous galaxies at z ∼ 6 in terms of both UV continuum emission and Ly α line emission. We model the spectral energy distributions of 10 LBGs that have deep infrared observations from Hubble Space Telescope, JWST, and/or Spitzer, and find that they have a wide range of stellar masses and ages. They also have high star formation rates ranging from a few tens to a few hundreds of solar mass per year. Five of the LBGs have JWST or HST images, and four of them show compact morphology in these images, including one that is roughly consistent with a point source, suggesting that UV luminous galaxies at this redshift are generally compact. The fraction of our photometrically selected LBGs with strong Ly α emission (EW > 25 Å) is about 0.2, which is consistent with previous results and supports a moderate evolution of the intergalactic medium opacity at the end of cosmic reionization. Using deep X-ray images, we do not find evidence of strong active galactic nucleus (AGN) activity in these galaxies, but our constraint is loose, and we are not able to rule out the possibility of any weak AGN activity.

We present the first results of the Hubble Deep Hydrogen Alpha (HDH α ) project, which analyzes the space-borne deep H α narrowband imaging data in the GOODS-S region. The HDH α data comprises 72 orbits’ images taken with the Hubble Space Telescope (HST) Advanced Camera for Surveys/Wide Field Channel F658N filter. The exposure time varies across a total area of ∼76.1 arcmin ^2 , adding up to a total exposure time of 195.7 ks, among which 68.8 ks are spent in the deepest region. These images are aligned, reprojected, and combined to have the same pixel grid as the Hubble Legacy Fields. The scientific goals of the HDH α include establishing a sample of emission-line galaxies (ELGs) including [O iii ] emitters at z ∼ 0.3, [O ii ] emitters at z ∼ 0.8, and Ly α emitters (LAEs) at z ∼ 4.4, studying the line morphology of ELGs with high resolution imaging data, and statistically analyzing the line luminosity functions and line equivalent-width distributions of ELGs selected with HST. Furthermore, the HDH α project enhances the legacy value of the GOODS-S field by contributing the first HST-based narrowband image to the existing data sets, which includes the HST broadband data and other ancillary data from X-ray to radio taken by other facilities. In this paper, we describe the data reduction process of the HDH α , select ELGs based on HST's F658N and broadband data, validate the redshifts of the selected candidates by crossmatching with the public spectroscopic catalogs in the GOODS-S, and present a final catalog of the confirmed [O iii ] emitters at z ∼ 0.3, [O ii ] emitters at z ∼ 0.8, and LAEs at z ∼ 4.4.

Changing-look active galactic nuclei (CL AGNs) can be generally confirmed by the emergence (turn-on) or disappearance (turn-off) of broad emission lines (BELs), associated with a transient timescale (about 100 ∼ 5000 days) that is much shorter than predicted by traditional accretion disk models. We carry out a systematic CL AGN search by crossmatching the spectra coming from the Dark Energy Spectroscopic Instrument and the Sloan Digital Sky Survey. Following previous studies, we identify CL AGNs based on H α , H β , and Mg ii at z ≤ 0.75 and Mg ii , C iii ], and C iv at z > 0.75. We present 56 CL AGNs based on visual inspection and three selection criteria, including 2 H α , 34 H β , 9 Mg ii , 18 C iii ], and 1 C iv CL AGN. Eight cases show simultaneous appearances/disappearances of two BELs. We also present 44 CL AGN candidates with significant flux variation of BELs, but remaining strong broad components. In the confirmed CL AGNs, 10 cases show additional CL candidate features for different lines. In this paper, we find: (1) a 24:32 ratio of turn-on to turn-off CL AGNs; (2) an upper-limit transition timescale ranging from 330 to 5762 days in the rest frame; and (3) the majority of CL AGNs follow the bluer-when-brighter trend. Our results greatly increase the current CL census (∼30%) and would be conducive to exploring the underlying physical mechanism.

This study aims to solve the problems of inaccurate weighing of bamboo sticks and inefficient manual counting. To overcome this problem, an improved MobileNetV3 model and a counting algorithm suitable for bamboo sticks—combined with a spatial-temporal attention mechanism—are proposed in this paper. Inspired by the idea of EfficientNet, scaling coefficients are used to scale the MobileNetV3 network structure as a whole in terms of width and height. The optimal model for bamboo-stick recognition is screened initially, and then the algorithm uses the convolutional block attention module (CBAM) attention mechanism to replace the squeeze-and-excitation (SE) attention mechanism in the MobileNetV3 network structure to allow the network to extract features in the two dimensions of channel and space. Since the number of bamboo sticks in a single image is extremely dense—generally around 1000–3000—it is difficult to effectively count them with existing algorithms. The proposed algorithm divides the image into multiple equally sized blocks and then uses the boundary processing algorithm to merge the cut bamboo stick images and count the number of sticks. Experimental results show that the proposed algorithm can effectively perform near real-time detection on a mobile terminal and its accuracy can reach approximately 97%, which is in line with actual production applications.

We report on the discovery of two low-luminosity, broad-line active galactic nuclei (AGNs) at z > 5 identified using JWST NIRSpec spectroscopy from the Cosmic Evolution Early Release Science (CEERS) survey. We detect broad H α emission in the spectra of both sources, with FWHM of 2060 ± 290 km s ^−1 and 1800 ± 200 km s ^−1 , resulting in virial black hole (BH) masses that are 1–2 dex below those of existing samples of luminous quasars at z > 5. The first source, CEERS 2782 at z = 5.242, is 2–3 dex fainter than known quasars at similar redshifts and was previously identified as a candidate low-luminosity AGN based on its morphology and rest-frame optical spectral energy distribution (SED). We measure a BH mass of M _BH = (1.3 ± 0.4) × 10 ^7 M _⊙ , confirming that this AGN is powered by the least massive BH known in the Universe at the end of cosmic reionization. The second source, CEERS 746 at z = 5.624, is inferred to be a heavily obscured, broad-line AGN caught in a transition phase between a dust-obscured starburst and an unobscured quasar. We estimate its BH mass to be in the range of M _BH ≃ (0.9–4.7) × 10 ^7 M _⊙ , depending on the level of dust obscuration assumed. We perform SED fitting to derive host stellar masses, M _⋆ , allowing us to place constraints on the BH–galaxy mass relationship in the lowest mass range yet probed in the early Universe. The M _BH / M _⋆ ratio for CEERS 2782, in particular, is consistent with or higher than the empirical relationship seen in massive galaxies at z = 0. We examine the narrow emission line ratios of both sources and find that their location on the BPT and OHNO diagrams is consistent with model predictions for moderately low metallicity AGNs with Z / Z _⊙ ≃ 0.2–0.4. The spectroscopic identification of low-luminosity, broad-line AGNs at z > 5 with M _BH ≃ 10 ^7 M _⊙ demonstrates the capability of JWST to push BH masses closer to the range predicted for the BH seed population and provides a unique opportunity to study the early stages of BH–galaxy assembly.

We present the first results from the JWST program A SPectroscopic survey of biased halos In the Reionization Era (ASPIRE). This program represents an imaging and spectroscopic survey of 25 reionization-era quasars and their environments by utilizing the unprecedented capabilities of NIRCam Wide Field Slitless Spectroscopy (WFSS) mode. ASPIRE will deliver the largest ( $\sim 280\,{\mathrm{arcmin}}^{2}$ ) galaxy redshift survey at 3–4 μ m among JWST Cycle 1 programs and provide extensive legacy values for studying the formation of the earliest supermassive black holes, the assembly of galaxies, early metal enrichment, and cosmic reionization. In this first ASPIRE paper, we report the discovery of a filamentary structure traced by the luminous quasar J0305–3150 and 10 [O iii ] emitters at z = 6.6. This structure has a 3D galaxy overdensity of δ _gal = 12.6 over 637 cMpc ^3 , one of the most overdense structures known in the early universe, and could eventually evolve into a massive galaxy cluster. Together with existing VLT/MUSE and ALMA observations of this field, our JWST observations reveal that J0305–3150 traces a complex environment where both UV-bright and dusty galaxies are present and indicate that the early evolution of galaxies around the quasar is not simultaneous. In addition, we discovered 31 [O iii ] emitters in this field at other redshifts, 5.3 < z < 6.7, with half of them situated at z ∼ 5.4 and 6.2. This indicates that star-forming galaxies, such as [O iii ] emitters, are generally clustered at high redshifts. These discoveries demonstrate the unparalleled redshift survey capabilities of NIRCam WFSS and the potential of the full ASPIRE survey data set.

Studies of rest-frame optical emission in quasars at z > 6 have historically been limited by the wavelengths accessible by ground-based telescopes. The James Webb Space Telescope (JWST) now offers the opportunity to probe this emission deep into the reionization epoch. We report the observations of eight quasars at z > 6.5 using the JWST/NIRCam Wide Field Slitless Spectroscopy as a part of the “A SPectroscopic survey of biased halos In the Reionization Era (ASPIRE)” program. Our JWST spectra cover the quasars’ emission between rest frame ∼4100 and 5100 Å. The profiles of these quasars’ broad H β emission lines span a full width at half maximum from 3000 to 6000 km s ^−1 . The H β -based virial black hole (BH) masses, ranging from 0.6 to 2.1 billion solar masses, are generally consistent with their Mg ii -based BH masses. The new measurements based on the more reliable H β tracer thus confirm the existence of a billion solar-mass BHs in the reionization epoch. In the observed [O iii ] λ λ 4960,5008 doublets of these luminous quasars, broad components are more common than narrow core components (≤ 1200 km s ^−1 ), and only one quasar shows stronger narrow components than broad. Two quasars exhibit significantly broad and blueshifted [O iii ] emission, thought to trace galactic-scale outflows, with median velocities of −610 and −1430 km s ^−1 relative to the [C ii ] 158 μ m line. All eight quasars show strong optical Fe ii emission and follow the eigenvector 1 relations defined by low-redshift quasars. The entire ASPIRE program will eventually cover 25 quasars and provide a statistical sample for the studies of the BHs and quasar spectral properties.

Hepatic ischemia–reperfusion (IR) injury is a serious clinical problem that complicates liver resection and transplantation. Despite recent advances in understanding of the pathophysiology of hepatic IR injury, effective interventions and therapeutics are still lacking. Here, we examined the role of transient receptor potential melastatin 2 (TRPM2), a Ca2+-permeable, non-selective cation channel, in mediating hepatic IR injury. Our data showed that TRPM2 deficiency attenuated IR-induced liver dysfunction, inflammation, and cell death in mice. Moreover, RNA sequencing analysis indicated that TRPM2-induced IR injury occurs via ferroptosis-related pathways. Consistently, as a ferroptosis inducer, (1S,3R)-RSL3 treatment induced mitochondrial dysfunction in hepatocytes and a TRPM2 inhibitor suppressed this. Interestingly, TRPM2-mediated calcium influx caused mitochondrial calcium accumulation via the mitochondrial Ca2+-selective uniporter and increased the expression level of arachidonate 12-lipoxygenase (ALOX12), which results in mitochondrial lipid peroxidation during hepatic IR injury. Furthermore, hepatic IR injury-induced ferroptosis was obviously relieved by a TRPM2 inhibitor or calcium depletion, both in vitro and in vivo. Collectively, these findings demonstrate a crucial role for TRPM2-mediated ferroptosis in hepatic IR injury via increased Ca2+-induced ALOX12 expression, indicating that pharmacological inhibition of TRPM2 may provide an effective therapeutic strategy for hepatic IR injury-related diseases, such as during liver resection and transplantation.

We report a candidate of a low-luminosity active galactic nucleus (AGN) at z = 5 that was selected from the first near-infrared images of the JWST CEERS project. This source, named CEERS-AGN-z5-1 at absolute 1450 Å magnitude M _1450 = −19.5 ± 0.3, was found via a visual selection of compact sources from a catalog of Lyman break galaxies at z > 4, taking advantage of the superb spatial resolution of the JWST/NIRCam images. The 20 photometric data available from CFHT, Hubble Space Telescope, Spitzer, and JWST suggest that the continuum shape of this source is reminiscent of that for an unobscured AGN, and there is a clear color excess in the filters where the redshifted H β +[O iii ] and H α are covered. The estimated line luminosity is L _H _β _+[O _III _] = 10 ^43.0 erg s ^−1 and L _H _α = 10 ^42.9 erg s ^−1 with the corresponding rest-frame equivalent width EW _H _β _+[O _III _] = 1100 Å and EW _H _α = 1600 Å, respectively. Our spectral energy distribution fitting analysis favors the scenario that this object is either a strong broad-line emitter or even a super-Eddington accreting black hole (BH), although a possibility of an extremely young galaxy with moderate dust attenuation is not completely ruled out. The bolometric luminosity, L _bol = 2.5 ± 0.3 × 10 ^44 erg s ^−1 , is consistent with those of z < 0.35 broad-line AGNs with M _BH ∼ 10 ^6 M _⊙ accreting at the Eddington limit. This new AGN population in the first 1.1 billion years of the universe may close the gap between the observed BH mass range at high redshift and that of BH seeds. Spectroscopic confirmation is awaited to secure the redshift and its AGN nature.

We present a study of seven spectroscopically confirmed (Ly α -emitting) galaxies at redshift z ≃ 6 using the JWST/NIRCam imaging data. These galaxies, with a wide range of Ly α luminosities, were recently observed in a series of NIRCam broad and medium bands. We constrain the rest-frame UV/optical continua and measure the H α line emission of the galaxies using the combination of JWST/NIRCam and archival HST/WFC3 infrared photometry. We further estimate the escape fractions of their Ly α photons ( ${f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }$ ) and the production efficiency of ionizing photons ( ξ _ion ). Among the sample, six out of seven galaxies have Ly α escape fractions of ≲10%, which might be the status for most of the star-forming galaxies at z ≃ 6. One UV-faint Ly α galaxy with an extremely blue UV slope has a large value of ${f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }$ reaching ≃50%. These galaxies have a broad range of ξ _ion over log _10 ξ _ion,0 (Hz erg ^−1 ) ∼ 25.0–26.5. We find that UV-fainter galaxies with bluer UV-continuum slopes likely have higher escape fractions of Ly α photons. We also find that galaxies with higher Ly α line emission tend to produce ionizing photons more efficiently. The most Ly α -luminous galaxy in the sample has a very high ξ _ion,0 of log _10 ξ _ion,0 (Hz erg ^−1 ) > 26. Our results support the scenario that Ly α galaxies may have served as an important contributor to cosmic reionization. Blue and bright Ly α galaxies are excellent targets for JWST follow-up spectroscopic observations.

IntroductionChemoresistance is a major barrier in the treatment of colorectal cancer (CRC) and many other cancers. ENO1 has been associated with various biological characteristics of CRC. This study aimed to investigate the function of ENO1 in regulating 5-Fluorouracil (5-FU) resistance in CRC.MethodsENO1 level in 120 pairs of tumor tissues and adjacent normal tissues was examined by immunohistochemistry, and the correlation between ENO1 expression and prognosis was explored by survival analysis. Its role and potential mechanisms in regulating 5-FU resistance in CRC were studied by Western blotting, MTT assay, colony formation assay and transwell invasion assay. Murine xenograft assay was implied to verify the results in vivo.ResultsOur study indicated that ENO1 was elevated in CRC tissues and was associated with poor patient prognosis. High levels of ENO1 expression were detected as a significant influencing factor for overall survival. Furthermore, ENO1 expression was found to have increased in drug-resistant cells (HCT116/5-FU and SW620/5-FU) constructed by increasing concentrations of 5-FU. Knockdown of ENO1 markedly increased the drug susceptibility and inhibited the proliferation and migration ability of HCT116/5-FU and SW620/5-FU cells. It was found that down-regulation of ENO1 inhibited the epithelial-mesenchymal transformation (EMT) signaling process. Finally, a murine xenograft assay verified that the depletion of ENO1 alleviated 5-FU resistance.ConclusionThis study identified that ENO1 regulated 5-FU resistance via the EMT pathway and may be a novel target in the prevention and treatment of 5-FUresistant CRC.

Limestone powder (LS) is a new environmentally-friendly concrete admixture, and its application in concrete engineering is worth exploring. The curing of LS hydraulic concrete under extreme temperatures will significantly affect the interior microstructure of concrete, which has a significant impact on the resistance to freeze-thaw cycles. This study aims to investigate the influence of LS replacement quantity (10 %, 30 % and 50 %) and curing temperatures (5 ℃, 20 ℃ and 50 ℃) on the freeze-thaw resistance of hydraulic concrete. The freeze-thaw resistance was reflected by the mass loss rate, relative dynamic modulus of elasticity (RDM) and ultrasonic inspection. The hydration products, microstructure and pore composition of LS hydraulic concrete were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP) to dissect the underlying mechanisms behind the freeze-thaw resistance. The relationship between the pore composition and the mass loss rate and RDM was established to connect the microcosmic properties with the macroscopic properties. Findings from this study provide a guidance for the application of LS in concrete engineering under harsh environments.

Deterioration process of high belite cement (HBC) paste with and without 30 wt.% fly ash, when exposed to sulfate attack, calcium leaching and the dual actions, was investigated by mass loss, expansion rate, porosity, corrosion depth, compressive strength and Vickers hardness, so did the contrastive ordinary Portland cement. Moreover, XRD, TGA, 29Si NMR, SEM and EDS linear scanning measurements were also conducted to assess the chemical attack mechanisms under corresponding aggressive conditions. Results showed that, the degradation of HBC pastes varied between different exposure conditions, and the most severely corroded samples were that exposed to (NH4)2SO4 solution with coupling sulfate attack and calcium leaching, which interacted with each other and accelerated the transfer process of sulfate ions to the cement matrix and calcium ions to external solution. Compared with ordinary Portland cement, high belite cement had a better corrosion resistance against the dual actions of sulfate attack and calcium leaching, and it could be further promoted by the moderate substitute of fly ash.

The subcellular localization of messenger RNA (mRNA) precisely controls where protein products are synthesized and where they function. However, obtaining an mRNA’s subcellular localization through wet-lab experiments is time-consuming and expensive, and many existing mRNA subcellular localization prediction algorithms need to be improved. In this study, a deep neural network-based eukaryotic mRNA subcellular location prediction method, DeepmRNALoc, was proposed, utilizing a two-stage feature extraction strategy that featured bimodal information splitting and fusing for the first stage and a VGGNet-like CNN module for the second stage. The five-fold cross-validation accuracies of DeepmRNALoc in the cytoplasm, endoplasmic reticulum, extracellular region, mitochondria, and nucleus were 0.895, 0.594, 0.308, 0.944, and 0.865, respectively, demonstrating that it outperforms existing models and techniques.

BackgroundPerioperative blood transfusion reserves are limited, and the outcome of blood transfusion remains unclear. Therefore, it is important to prepare plans for perioperative blood transfusions. This study aimed to establish a risk assessment model to guide clinical patient management.MethodsThis retrospective comparative study involving 513 patients who had total gastrectomy (TG) between January 2018 and January 2021 was conducted using propensity score matching (PSM). The influencing factors were explored by logistic regression, correlation analysis, and machine learning; then, a nomogram was established.ResultsAfter assessment of the importance of factors through machine learning, blood loss, preoperative controlling nutritional status (CONUT), hemoglobin (Hb), and the triglyceride–glucose (TyG) index were considered as the modified transfusion-related factors. The modified model was not considered to be different from the original model in terms of performance, but is simpler. A nomogram was created, with a C-index of 0.834, and the decision curve analysis (DCA) demonstrated good clinical benefit.ConclusionsA nomogram was established and modified with machine learning, which suggests the importance of the patient’s integral condition. This emphasizes that caution should be exercised regarding transfusions, and, if necessary, preoperative nutritional interventions or delayed surgery should be implemented for safety.

Abstract Background The Rician noise formed in magnetic resonance (MR) imaging greatly reduced the accuracy and reliability of subsequent analysis, and most of the existing denoising methods are suitable for Gaussian noise rather than Rician noise. Aiming to solve this problem, we proposed fuzzy c-means and adaptive non-local means (FANLM), which combined the adaptive non-local means (NLM) with fuzzy c-means (FCM), as a novel method to reduce noise in the study. Method The algorithm chose the optimal size of search window automatically based on the noise variance which was estimated by the improved estimator of the median absolute deviation (MAD) for Rician noise. Meanwhile, it solved the problem that the traditional NLM algorithm had to use a fixed size of search window. Considering the distribution characteristics for each pixel, we designed three types of search window sizes as large, medium and small instead of using a fixed size. In addition, the combination with the FCM algorithm helped to achieve better denoising effect since the improved the FCM algorithm divided the membership degrees of images and introduced the morphological reconstruction to preserve the image details. Results The experimental results showed that the proposed algorithm (FANLM) can effectively remove the noise. Moreover, it had the highest peak signal-noise ratio (PSNR) and structural similarity (SSIM), compared with other three methods: non-local means (NLM), linear minimum mean square error (LMMSE) and undecimated wavelet transform (UWT). Using the FANLM method, the image details can be well preserved with the noise being mostly removed. Conclusion Compared with the traditional denoising methods, the experimental results showed that the proposed approach effectively suppressed the noise and the edge details were well retained. However, the FANLM method took an average of 13 s throughout the experiment, and its computational cost was not the shortest. Addressing these can be part of our future research.

We present the first result in exploring the gaseous halo and galaxy correlation using the Dark Energy Spectroscopic Instrument survey validation data in the Cosmic Evolution Survey (COSMOS) and Hyper Suprime-Cam field. We obtain multiphase gaseous halo properties in the circumgalactic medium by using 115 quasar spectra (signal-to-noise ratio > 3). We detect Mg ii absorption at redshift 0.6 < z < 2.5, C iv absorption at 1.6 < z < 3.6, and H i absorption associated with the Mg ii and C iv . By crossmatching the COSMOS2020 catalog, we identify the Mg ii and C iv host galaxies in 10 quasar fields at 0.9< z < 3.1. We find that within the impact parameter of 250 kpc, a tight correlation is seen between the strong Mg ii equivalent width and the host galaxy star formation rate. The covering fraction f _c of the strong Mg ii selected galaxies, which is the ratio of the absorbing galaxy in a certain galaxy population, shows significant evolution in the main-sequence galaxies and marginal evolution in all the galaxy populations within 250 kpc at 0.9 < z < 2.2. The f _c increase in the main-sequence galaxies likely suggests the coevolution of strong Mg ii absorbing gas and the main-sequence galaxies at the cosmic noon. Furthermore, Mg ii and C iv absorbing gas is detected out of the galaxy virial radius, tentatively indicating the feedback produced by the star formation and/or the environmental effects.

We present a spectroscopic survey of Ly α emitters (LAEs) at z ∼ 3.7 and z ∼ 4.8. The LAEs are selected using the narrowband technique based on the combination of deep narrowband and broadband imaging data in two deep fields, and then spectroscopically confirmed with the MMT multifiber spectrograph Hectospec. The sample consists of 71 LAEs at z ∼ 3.7 and 69 LAEs at z ∼ 4.8 over ∼1.5 deg ^2 , making it one of the largest spectroscopically confirmed samples of LAEs at the two redshifts. Their Ly α luminosities are measured using the secure redshifts and deep photometric data, and span a range of ∼10 ^42.5 –10 ^43.6 erg s ^−1 , so these LAEs represent the most luminous galaxies at the redshifts in terms of Ly α luminosity. We estimate and correct sample incompletenesses and derive reliable Ly α luminosity function (LFs) at z ∼ 3.7 and 4.8 based on the two spectroscopic samples. We find that our Ly α LFs are roughly consistent (within a factor of 2−3) with previous measurements at similar redshifts that were derived from either photometric samples or spectroscopic samples. By comparing with previous studies in different redshifts, we find that the Ly α LFs decrease mildly from z ∼ 3.1 to z ∼ 5.7, supporting the previous claim of the slow LF evolution between z ∼ 2 and z ∼ 6. At z > 5.7, the LF declines rapidly toward higher redshift, partly due to the effect of cosmic reionization.

We present a study of Lyman continuum (LyC) emission in a sample of ∼150 Ly α emitters (LAEs) at z ≈ 3.1 in the Subaru-XMM Deep Survey field. These LAEs were previously selected using the narrowband technique and spectroscopically confirmed with Ly α equivalent widths (EWs) ≥ 45 Å. We obtain deep UV images using a custom intermediate-band filter U _J that covers a wavelength range of 3330 ∼ 3650 Å, corresponding to 810 ∼ 890 Å in the rest frame. We detect five individual LyC galaxy candidates in the U _J band, and their escape fractions ( f _esc ) of LyC photons are roughly between 40% and 80%. This supports a previous finding that a small fraction of galaxies may have very high f _esc . We find that the f _esc values of the five LyC galaxies are not apparently correlated with other galaxy properties such as Ly α luminosity and EW, UV luminosity and slope, and star formation rate (SFR). This is partly due to the fact that these galaxies only represent a small fraction (∼3%) of our LAE sample. For the remaining LAEs that are not detected in U _J , we stack their U _J -band images and constrain their average f _esc . The upper limit of the average f _esc value is about 16%, consistent with the results in the literature. Compared with the non-LyC LAEs, the LyC LAEs tend to have higher Ly α luminosities, Ly α EWs, and SFRs, but their UV continuum slopes are similar to those of other galaxies.

The formation of the first supermassive black holes is expected to have occurred in some most pronounced matter and galaxy overdensities in the early universe. We have conducted a submillimeter wavelength continuum survey of 54 z ∼ 6 quasars using the Submillimeter Common-User Bolometre Array-2 on the James Clerk Maxwell Telescope to study the environments around z ∼ 6 quasars. We identified 170 submillimeter galaxies (SMGs) with above 3.5 σ detections in 450 or 850 μ m maps. Their far-IR luminosities are (2.2–6.4) × 10 ^12 L _⊙ , and their star formation rates are ∼400–1200 M _⊙ yr ^−1 . We also calculated the SMGs’ differential and cumulative number counts in a combined area of ∼620 arcmin ^2 . To a 4 σ detection (at ∼5.5 mJy), SMGs’ overdensity is ${0.68}_{-0.19}^{+0.21}$ (±0.19), exceeding the blank-field source counts by a factor of 1.68. We find that 13/54 quasars show overdensities (at ∼5.5 mJy) of δ _SMG ∼ 1.5–5.4. The combined area of these 13 quasars exceeds the blank-field counts with the overdensity to 5.5 mJy of δ _SMG ∼ ${2.46}_{-0.55}^{+0.64}$ (±0.25) in the regions of ∼150 arcmin ^2 . However, the excess is insignificant on the bright end (e.g., 7.5 mJy). We also compare results with previous environmental studies of Ly α emitters and Lyman break galaxies on a similar scale. Our survey presents the first systematic study of the environment of quasars at z ∼ 6. The newly discovered SMGs provide essential candidates for follow-up spectroscopic observations to test whether they reside in the same large-scale structures as the quasars and search for protoclusters at an early epoch.

We present the astrometric calibration of the Beijing–Arizona Sky Survey (BASS). The BASS astrometry was tied to the International Celestial Reference Frame via the Gaia Data Release 2 reference catalog. For effects that were stable throughout the BASS observations, including differential chromatic refraction and the low charge transfer efficiency of the CCD, we corrected for these effects at the raw image coordinates. Fourth-order polynomial intermediate longitudinal and latitudinal corrections were used to remove optical distortions. The comparison with the Gaia catalog shows that the systematic errors, depending on color or magnitude, are less than 2 milliarcseconds (mas). The position systematic error is estimated to be about −0.01 ± 0.7 mas in the region between 30° and 60° of decl. and up to −0.07 ± 0.9 mas in the region north of decl. 60°.

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using Ly α forests in quasar spectra at z > 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands ( g , r , z ) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Survey Explorer. These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a random forest algorithm and selects quasars in the magnitude range of 16.5 < r < 23. Visual selection of ultra-deep observations indicates that the main selection consists of 71% quasars, 16% galaxies, 6% stars, and 7% inconclusive spectra. Using the spectra based on this selection, we build an automated quasar catalog that achieves a fraction of true QSOs higher than 99% for a nominal effective exposure time of ∼1000 s. With a 310 deg ^−2 target density, the main selection allows DESI to select more than 200 deg ^−2 quasars (including 60 deg ^−2 quasars with z > 2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.

BackgroundThe intestinal flora is correlated with the occurrence of colorectal cancer. We evaluate a new predictive model for the non-invasive diagnosis of colorectal cancer based on intestinal flora to verify the clinical application prospects of the intestinal flora as a new biomarker in non-invasive screening of colorectal cancer.MethodsSubjects from two independent Asian cohorts (cohort I, consisting of 206 colorectal cancer and 112 healthy subjects; cohort II, consisting of 67 colorectal cancer and 54 healthy subjects) were included. A probe-based duplex quantitative PCR (qPCR) determination was established for the quantitative determination of candidate bacterial markers.ResultsWe screened through the gutMEGA database to identify potential non-invasive biomarkers for colorectal cancer, including Prevotella copri (Pc), Gemella morbillorum (Gm), Parvimonas micra (Pm), Cetobacterium somerae (Cs), and Pasteurella stomatis (Ps). A predictive model with good sensitivity and specificity was established as a new diagnostic tool for colorectal cancer. Under the best cutoff value that maximizes the sum of sensitivity and specificity, Gm and Pm had better specificity and sensitivity than other target bacteria. The combined detection model of five kinds of bacteria showed better diagnostic ability than Gm or Pm alone (AUC = 0.861, P < 0.001). These findings were further confirmed in the independent cohort II. Particularly, the combination of bacterial markers and fecal immunochemical test (FIT) improved the diagnostic ability of the five bacteria (sensitivity 67.96%, specificity 89.29%) for patients with colorectal cancer.ConclusionFecal-based colorectal cancer-related bacteria can be used as new non-invasive diagnostic biomarkers of colorectal cancer. Simultaneously, the molecular biomarkers in fecal samples are similar to FIT, have the applicability in combination with other detection methods, which is expected to improve the sensitivity of diagnosis for colorectal cancer, and have a promising prospect of clinical application.

BackgroundGastric cancer is a type of malignant tumor with high morbidity and mortality. It has been shown that circular RNAs (circRNAs) exert critical roles in gastric cancer progression via working as microRNA (miRNA) sponges to regulate gene expression. However, the role and potential molecular mechanism of circRNAs in gastric cancer remain largely unknown.MethodsCircPTK2 (hsa_circ_0005273) was identified by bioinformatics analysis and validated by RT-qPCR assay. Bioinformatics prediction, dual-luciferase reporter, and RNA pull-down assays were used to determine the interaction between circPTK2, miR-196a-3p, and apoptosis-associated tyrosine kinase 1 (AATK).ResultsThe level of circPTK2 was markedly downregulated in gastric cancer tissues and gastric cancer cells. Upregulation of circPTK2 significantly suppressed the proliferation, migration, and invasion of gastric cancer cells, while circPTK2 knockdown exhibited opposite effects. Mechanically, circPTK2 could competitively bind to miR-196a-3p and prevent miR-196a-3p to reduce the expression of AATK. In addition, overexpression of circPTK2 inhibited tumorigenesis in a xenograft mouse model of gastric cancer.ConclusionCollectively, circPTK2 functions as a tumor suppressor to suppress gastric cancer cell proliferation, migration, and invasion through regulating the miR-196a-3p/AATK axis, suggesting that circPTK2 may serve as a novel therapeutic target for gastric cancer.

Abstract Background Similar to humans, the zebrafish brain plays a central role in regulating sexual reproduction, maturation and sexual behavior. However, systematic studies of the dimorphic patterns of gene expression in the brain of male and female zebrafish are lacking. Results In this study, the mRNA and lncRNA expression profiles were obtained from the brain tissue samples of the three male and three female zebrafish by high-throughput transcriptome sequencing. We identified a total of 108 mRNAs and 50 lncRNAs with sex-based differential expression. We randomly selected four differentially expressed genes for RT-qPCR verification and the results certified that the expression pattern showed a similar trend between RNA-seq and RT-qPCR results. Protein-protein interaction network analysis, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to obtain the biological significance of differentially expressed mRNA in the brain dimorphism of zebrafish. Finally, a Pearson correlation analysis was performed to construct the co-expression network of the mRNAs and lncRNAs. Conclusions We found that 12 new lncRNAs not only have significant gender specificity in the brain of zebrafish, and this finding may provide a clue to further study of the functional difference between male and female zebrafish brain.

Cancer-associated fibroblast (CAF)-derived exosomes play a major role in gastric carcinoma (GC) tumorigenesis. However, the mechanism behind the activity of circular RNAs in CAF-derived exosomes in GC remains unclear. In the present study, we identified differentially expressed circ_0088300 in GC tissues and plasma exosomes. We found that CAFs delivered functional circ_0088300 to GC tumor cells via exosomes and promoted the proliferation, migration and invasion abilities of GC cells. Furthermore, we demonstrated that circ_0088300 packaging into exosomes was driven by KHDRBS3. In addition, we verified that circ_0088300 served as a sponge that directly targeted miR-1305 and promoted GC cell proliferation, migration and invasion. Finally, the JAK/STAT signaling pathway was found to be involved in the circ_0088300/miR-1305 axis, which accelerates GC tumorigenesis. In conclusion, our results indicated a previously unknown regulatory pathway in which exosomal circ_0088300 derived from CAFs acts as a sponge of miR-1305 and promotes GC cell proliferation, migration and invasion; these data identify a potential biomarker and novel therapeutic target for GC in the future.

Hyperspectral image-anomaly detection (HSI-AD) has become one of the research hotspots in the field of remote sensing. Because HSI’s features of integrating image and spectrum provide a considerable data basis for abnormal object detection, HSI-AD has a huge application potential in HSI analysis. It is difficult to effectively extract a large number of nonlinear features contained in HSI data using traditional machine learning methods, and deep learning has incomparable advantages in the extraction of nonlinear features. Therefore, deep learning has been widely used in HSI-AD and has shown excellent performance. This review systematically summarizes the related reference of HSI-AD based on deep learning and classifies the corresponding methods into performance comparisons. Specifically, we first introduce the characteristics of HSI-AD and the challenges faced by traditional methods and introduce the advantages of deep learning in dealing with these problems. Then, we systematically review and classify the corresponding methods of HSI-AD. Finally, the performance of the HSI-AD method based on deep learning is compared on several mainstream data sets, and the existing challenges are summarized. The main purpose of this article is to give a more comprehensive overview of the HSI-AD method to provide a reference for future research work.

Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid (C), the color space coordinates of the target substance at different concentrations (L∗, a∗, b∗), and the maximum absorption wavelength (λmax); subsequently, the optimum wavelength λT of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples (i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.), and it is capable of original-state online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe3+ concentration in the colloidal process of the plant’s aging liquid (where the concentrations of Fe3+, Mn2+, and (NH4)2SO4 are 0.5–18 mg·L−1, 35–39 g·L−1, and 90–110 g·L−1, respectively). The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%. Keywords: Complex liquid, Original-state monitoring, Online real-time, Non-contact identification

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Background Recent studies showed that circRNAs are involved in the biological process of some human cancers. However, little is known about their functions in colorectal cancer (CRC). Methods Here we first revealed the expression profiles of circRNAs in the CRC tissues and the adjacent non-tumorous tissues using high-throughput sequencing. The sequence feature, chromosome location, alternative splicing and other characteristics of the circRNAs were also explored. The miRNA and mRNA expression profiles were then obtained by analyzing relevant CRC data retrived from the TCGA database. We obtained and analyzed the competing endogenous RNA (ceRNA) network of the top three pairs of the largest up-regulated and down-regulated circRNAs. Results In this study, we obtained 50,410 circRNAs in the CRC tissue and the adjacent non-tumor tissues, of which 33.7% (16,975) were new, and revealed differential changes in circRNA expression during colorectal carcinogenesis. We have identified six potential key circRNAs (circPIEZO1-3, hsa_circ_0067163, hsa_circ_0140188, hsa_circ_0002632, hsa_circ_0001998 and hsa_circ_0023990) associated with CRC, which play important roles in carcinogenesis as ceRNA for regulation of miRNA-mRNA network. In the subsequent KEGG analysis, several CRC-related pathways were found. Conclusions Our findings advance the understanding of the pathogenesis of CRC from the perspective of circRNAs and provide some circRNAs as candidate diagnostic biomarkers or potential therapeutic targets.

The mechanism was proposed of heterogeneous catalytic CO2 absorptions with primary/secondary amines involving ‘catalytic carbamate formation’. Compared with the non-catalytic ‘Zwitterion mechanism’, this Eley–Rideal model was proposed for CO2 + RR′NH with MCO3 (M = Ca, Mg, and Ba) with four elementary reaction steps: (B1) amine adsorption, (B2) Zwitterion formation, (B3) carbamate formation, and (B4) carbamate desorption. The rate law if determining step of each elementary step was generated based on ‘steady-state approximation’. Furthermore, the solid chemicals were characterized by SEM and BET, and this rate model was verified with 39 sets of experimental datasets of catalytic CO2–MEA absorptions with the existence of 0–25 g CaCO3, MgCO3 and BaCO3. The results indicated that the rate-determining step was B1 as amine adsorption onto solid surface, which was pseudo-first-order for MEA. This was the first time that the Eley–Rideal model had been adopted onto the reactions of CO2 + primary/secondary amines over alkaline earth metal carbonate (MCO3).

A design scheme of multi-element sensor which included electrical resistivity probes, multiple Cl− selective electrodes, and a steel corrosion monitoring system was proposed in this work. Embedding this multi-element sensor in concrete enables the real-time and non-destructive monitoring of internal electrical resistivity, free Cl− (Clf) contents in the concrete pore solution at different depths, and steel corrosion parameters. Based on the monitoring data obtained by the multi-element sensor, the freezing-thawing (F-T) damage degree, the Clf diffusion coefficient, the quantitative relation between F-T damage degree and Clf diffusion coefficient, the initiation period of steel corrosion, and the critical content related to steel corrosion are determined. To conclude, the multi-element sensor provides key durability parameters for the establishment of the Clf diffusion model, the assessment of health condition, and the prediction of service life of concrete under the coexistence of the F-T cycle and Cl−.

Considering the social properties of mobile sinks, we propose a biased trajectory dissemination of uncontrolled mobile sinks for event collection in wireless sensor networks. In biased trajectory dissemination of uncontrolled mobile sink, we first divide the whole network into clusters which can be managed by cluster heads that are elected in turn for intra-cluster event collection and inter-cluster communication. Second, for a mobile sink, we further divide the clusters it visits into biased clusters and non-biased clusters according to its staying probability. The mobile sink will send its mobility message which shows its location as it moves into a new cluster. We then construct a biased loop which is composed of all biased clusters and some non-biased clusters to disseminate a mobile sink’s mobility message only to clusters on it when the mobile sink moves into a biased cluster. We also construct query path that connects any cluster head that is not on the biased loop to a cluster head on it. An event could be transmitted to the biased loop along the query path for further forwarding to the mobile sink. Numerous simulations show the superior performance of biased trajectory dissemination of uncontrolled mobile sink compared to the representative schemes in terms of average path length, delay, and network energy consumption.

The isolation and observation of cardiomyocytes serve as the fundamental approach to cardiovascular research. The state-of-the-practice for the isolation and observation relies on manual operation of the entire culture process. Such a manual approach not only incurs high human errors, but also takes a long period of time. This paper proposes a new computer-aided paradigm to automatically, accurately, and efficiently perform the clustering and counting of cardiomyocytes, one of the key procedures for evaluating the success rate of cardiomyocytes isolation and the quality of culture medium. The key challenge of the proposed method lies in the unique, rod-like shape of cardiomyocytes, which has been hardly addressed in literature. Our proposed method employs a novel algorithm inspired by hesitant fuzzy sets and integrates an efficient implementation into the whole process of analyzing cardiomyocytes. The system, along with the data extracted from adult rats’ cardiomyocytes, has been experimentally evaluated with Matlab, showing promising results. The false accept rate (FAR) and the false reject rate (FRR) are as low as 1.46% and 1.97%, respectively. The accuracy rate is up to 98.7%—20% higher than the manual approach—and the processing time is reduced from tens of seconds to 3−5 s—an order of magnitude performance improvement.

In this paper, we propose a semantic segmentation method based on superpixel region merging and convolutional neural network (CNN), referred to as regional merging neural network (RMNN). Image annotation has always been an important role in weakly-supervised semantic segmentation. Most methods use manual labeling. In this paper, super-pixels with similar features are combined using the relationship between each pixel after super-pixel segmentation to form a plurality of super-pixel blocks. Rough predictions are generated by the fully convolutional networks (FCN) so that certain super-pixel blocks will be labeled. We perceive and find other positive areas in an iterative way through the marked areas. This reduces the feature extraction vector and reduces the data dimension due to super-pixels. The algorithm not only uses superpixel merging to narrow down the target’s range but also compensates for the lack of weakly-supervised semantic segmentation at the pixel level. In the training of the network, we use the method of region merging to improve the accuracy of contour recognition. Our extensive experiments demonstrated the effectiveness of the proposed method with the PASCAL VOC 2012 dataset. In particular, evaluation results show that the mean intersection over union (mIoU) score of our method reaches as high as 44.6%. Because the cavity convolution is in the pooled downsampling operation, it does not degrade the network’s receptive field, thereby ensuring the accuracy of image semantic segmentation. The findings of this work thus open the door to leveraging the dilated convolution to improve the recognition accuracy of small objects.

The wireless sensor network (WSN) is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. Therefore, energy consumption in wireless sensor networks is one of the most challenging problems in practice. On the other hand, data fusion can effectively decrease data redundancy, reduce the amount of data transmission and energy consumption in the network, extend the network life cycle, improve the utilization of bandwidth, and thus overcome the bottleneck on energy and bandwidth consumption. This paper proposes a new data fusion algorithm based on Hesitant Fuzzy Entropy (DFHFE). The new algorithm aims to reduce the collection of repeated data on sensor nodes from the source, and strives to utilize the information provided by redundant data to improve the data reliability. Hesitant fuzzy entropy is exploited to fuse the original data from sensor nodes in the cluster at the sink node to obtain higher quality data and make local decisions on the events of interest. The sink nodes periodically send local decisions to the base station that aggregates the local decisions and makes the final judgment, in which process the burden for the base station to process all the data is significantly released. According to our experiments, the proposed data fusion algorithm greatly improves the robustness, accuracy, and real-time performance of the entire network. The simulation results demonstrate that the new algorithm is more efficient than the state-of-the-art in terms of both energy consumption and real-time performance.