Soil contamination by heavy metals has become a serious environmental issue worldwide. Rapidly and reliably obtaining heavy metal concentrations in soil is vital for soil monitoring and remediation. ...Visible and near-infrared reflectance (VNIR) spectroscopy provides a promising method for the estimation of heavy metal concentrations over large areas. Ninety-three soil samples were collected from a suburb of Wuhan City, Hubei Province, China, and their reflectance spectra were measured in the laboratory. This study aimed to (i) examine the feasibility of using soil reflectance spectra to estimate the concentrations of Cd, Pb, As, Cr, Cu and Zn in suburban soils; (ii) compare the performances of different spectral pretreatments and (iii) explore the mechanism underlying the estimation of heavy metal concentration from VNIR spectra. In particular, we proposed a strategy for the mechanism investigation that combined PCA biplot analysis, correlation and partial correlation analyses. Partial least-square regression was adopted to calibrate the VNIR model. Results showed that the VNIR model provided acceptable estimation accuracies for Cr, As and Cd concentrations with the ratio of the performance to deviation (RPD) values of 2.70, 1.81 and 1.63, respectively, but unsatisfactory estimation accuracies for Pb, Cu and Zn concentrations with the RPD values of 0.70–1.03. Savitzky–Golay smoothing outperformed other spectral pretreatments. The mechanisms underlying the estimation of the six studied heavy metals varied on a case-to-case basis. Specifically, the spectral estimation of Cd (Group I) concentration was attributed to its close correlations with soil organic matter (SOM). Cr and As (Group II) concentrations could be estimated by the VNIR model on the basis of their close correlations with Fe. Pb, Cu and Zn (Group III) concentrations, however, had weak correlations with neither SOM nor Fe, resulting in poor estimations. The proposed strategy on mechanism investigation for heavy metals could be transferred to other study areas. In summary, VNIR spectroscopy combined with the PLSR model is an alternative method for the rapid monitoring of some heavy metal pollution in suburban soils.
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•VNIR spectroscopy can accurately estimate Cr concentrations in suburban soils.•We propose a comprehensive analytical framework to investigate the mechanism.•The framework involved PCA biplot, correlation and partial correlation analysis.•Estimation mechanism of Cd was attributed to its close correlation with SOM.•Estimation mechanism of As and Cr may ascribe to the close correlations with Fe.
Telomerase-independent ALT (alternative lengthening of telomeres) cells are characterized by high frequency of telomeric homologous recombination (HR), C-rich extrachromosomal circles (C-circles) and ...C-rich terminal 5' overhangs (C-overhangs). However, underlying mechanism is poorly understood. Here, we show that both C-circle and C-overhang form when replication fork collapse is induced by strand break at telomeres. We find that endogenous DNA break predominantly occur on C-rich strand of telomeres in ALT cells, resulting in high frequency of replication fork collapse. While collapsed forks could be rescued by replication fork regression leading to telomeric homologous recombination, those unresolved are converted to C-circles and C-overhang at lagging and leading synthesized strand, respectively. Meanwhile, multiple hallmarks of ALT are provoked, suggesting that strand break-induced replication stress underlies ALT. These findings provide a molecular basis underlying telomeric HR and biogenesis of C-circle and C-overhang, thus implicating the specific mechanism to resolve strand break-induced replication defect at telomeres in ALT cells.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
For decades, the widespread application of thermoelectric generators has been plagued by two major limitations: heat stagnation in its legs, which limits power conversion efficiency, and inherent ...brittleness of its constituents, which accelerates thermoelectric generator failure. While notable progress has been made to overcome these quintessential flaws, the state-of-the-art suffers from an apparent mismatch between thermoelectric performance and mechanical toughness. Here, we demonstrate an approach to potentially enhance the power conversion efficiency while suppressing the brittle failure in thermoelectric materials. By harnessing the enhanced thermal impedance induced by the cellular architecture of microlattices with the exceptional strength and ductility (>50% compressive strain) derived from partial carbonization, we fabricate three-dimensional (3D) architected thermoelectric generators that exhibit a specific energy absorption of ~30 J g
and power conversion efficiency of ~10%. We hope our work will improve future thermoelectric generator fabrication design through additive manufacturing with excellent thermoelectric properties and mechanical robustness.
This paper studies the Galerkin finite element approximations of a class of stochas- tic fractionM differential equations. The discretization in space is done by a standard continuous finite element ...method and almost optimal order error estimates are obtained. The discretization in time is achieved via the piecewise constant, discontinuous Galerkin method and a Laplace transform convolution quadrature. We give strong convergence error estimates for both semidiscrete and fully discrete schemes. The proof is based on the error estimates for the corresponding deterministic problem. Finally, the numerical example is carried out to verify the theoretical results.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NMLJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Researchers have found that macrophages are the predominant cells in the peritoneal fluid (PF) of endometriosis patients. CSF-1 has been found to accumulate in the lesions and PF of endometriosis ...patients, and CSF-1 induces THP-1-derived macrophages to polarize toward a CD169
DC-SIGN
phenotype. Does the cytokine CSF-1 induce monocytes to differentiate into macrophages with a DC-SIGN
phenotype in endometriosis?
The level of CSF-1 in the endometrium of control subjects, and the eutopic, and ectopic endometrium of endometriosis patients was evaluated by real-time polymerase chain reaction (qRT-PCR) and was determined by enzyme-linked immunosorbent assay (ELISA) in the PF of control and endometriosis patients. CSF-1 expression was examined with a MILLIPLEX MAP Mouse Cytokine/Chemokine Magnetic Bead Panel. DC-SIGN
macrophages were detected by immunohistochemical staining of tissues and flow cytometric analysis of the PF of control subjects (N = 25) and endometriosis (N = 35) patients. The phenotypes and biological activities of CSF-1 -induced macrophages were compared in an in vitro coculture system with peripheral blood lymphocytes from control subjects.
In this study, we found that the proportion of DC-SIGN
CD169
macrophages was higher in the abdominal immune microenvironment of endometriosis patients. CSF-1 was primarily secreted from ectopic lesions and peritoneum in mice with endometriosis. In addition, CSF-1 induced the polarization of macrophages toward a DC-SIGN
CD169
phenotype; this effect was abolished by the addition of an anti-CSF-1R antibody. CSF-1 induced the generation of DC-SIGN
macrophages, leading to a depressed status of peripheral blood lymphocytes, including a high percentage of Treg cells and a low percentage of CD8
T cells. Similarly, blockade with the anti-CSF-1R antibody abrogated this biological effect.
This is the first study on the role of DC-SIGN
macrophages in the immune microenvironment of endometriosis. Further study of the mechanism and biological activities of CSF-1-induced DC-SIGN
macrophages will enhance our understanding of the physiology of endometriosis.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Due to the complexity of underground reservoir distribution and the non-uniqueness of geophysical inverse problems, there is still a lack of practical and effective cross-well electromagnetic ...inversion methods. Our goal is to develop an efficient method to reduce the non-uniqueness of the physical property model recovered in the inversion. Based on a defined framework, we propose a 3-D crosswell electromagnetic sparse inversion based on iterative reweighted least squares (IRLS) method. We perform the inversion using a hybrid norm formulation, where the lp-norm (0 ≤ p ≤ 1) sparse optimization problem can be transformed into a series of weighted l2-norm optimization problems. Compared with the traditional norm inversion method, the sparse inversion method can make more effective use of the known physical information and obtain more accurate abnormal body position and shape. Finally, the effectiveness of sparse inversion method is verified by model test and inversion of measured data in mining area.
•Through different norm inversion, we can select and obtain the valuable information we need.•The inversion and recovery models of this method have distinct boundary characteristics.•It is of great significance for the effective simulation of complex 3D underground geological body by electromagnetic technique between wells.•Our method is applied to field data examples to obtain accurate information about subsurface anomalies.
Ground Penetrating Radar (GPR) is one of the most used devices for road structural damages detection. However, due to the different roadbed conditions and various disturbances in the nearby ...environment during detection, there are great difficulties in interpreting detection images, which also hinders automatic detection based on deep learning. In this work, we design a GPR image denoising method based on Cyclegan. We select the most suitable generator and add different attention mechanisms. After denoising the natural GPR road detection image, using the Yolo (You Only Look Once) to test the accuracy of the original image and the denoised image after adding different attention mechanisms. The detection accuracy is improved by 30%. The results of the detection network and the evaluation of the denoised images by GPR image interpreters indicate that the method has the following advantages: lower requirements for training data sets, a wide range of data sources, low cost, good denoising effect, and automatic detection of GPR images. It is of great help to the automatic detection of GPR images.
With improvements in the computing capability of edge devices and the emergence of edge computing, an increasing number of services are being deployed on the edge side, and container-based ...virtualization is used to deploy services to improve resource utilization. This has led to challenges in reliability because services deployed on edge nodes are pruned owing to hardware failures and a lack of technical support. To solve this reliability problem, we propose a solution based on fault prediction combined with container migration to address the service failure problem caused by node failure. This approach comprises two major steps: fault prediction and container migration. Fault prediction collects the log of services on edge nodes and uses these data to conduct time-sequence modeling. Machine-learning algorithms are chosen to predict faults on the edge. Container migration is modeled as an optimization problem. A migration node selection approach based on a genetic algorithm is proposed to determine the most suitable migration target to migrate container services on the device and ensure the reliability of the services. Simulation results show that the proposed approach can effectively predict device faults and migrate services based on the optimal container migration strategy to avoid service failures deployed on edge devices and ensure service reliability.
Chemical bonds, including covalent and ionic bonds, endow semiconductors with stable electronic configurations but also impose constraints on their synthesis and lattice-mismatched heteroepitaxy. ...Here, the unique multi-scale van der Waals (vdWs) interactions are explored in one-dimensional tellurium (Te) systems to overcome these restrictions, enabled by the vdWs bonds between Te atomic chains and the spontaneous misfit relaxation at quasi-vdWs interfaces. Wafer-scale Te vdWs nanomeshes composed of self-welding Te nanowires are laterally vapor grown on arbitrary surfaces at a low temperature of 100 °C, bringing greater integration freedoms for enhanced device functionality and broad applicability. The prepared Te vdWs nanomeshes can be patterned at the microscale and exhibit high field-effect hole mobility of 145 cm
/Vs, ultrafast photoresponse below 3 μs in paper-based infrared photodetectors, as well as controllable electronic structure in mixed-dimensional heterojunctions. All these device metrics of Te vdWs nanomesh electronics are promising to meet emerging technological demands.
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