Accurate method based on data filtering for quantitative multi-element analysis of soils using CF-LIBS

To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.

乘积函数的双Hilbert变换和Bedrosian等式

本文研究双Hilbert变换的性质,并对于f∈L^p(R^2), g∈L^q(R^2), p^(-1)+q^(-1)≤1,探讨在双Hilbert变换作用下Bedrosian等式H_2H_1(fg)=fH_2H_1g成立的充要条件,其中H_2H_1是双Hilbert变换.

Double Hilbert transform on D（R2）

We introduce a space DHH =D（R2） H2H1D（R2）, where D（R2） is the testing function space whose functions are infinitely differentiable and have bounded support, and H2H1D（R2） is the space the double Hilbert transform acting on the testing function space. We prove that the double Hilbert transform is a homeomorphism from DHH onto itself.

NUA and ESD4 negatively regulate ABA signaling during seed germination

The phytohormone abscisic acid(ABA)plays important roles in plant growth,development and adaptative responses to abiotic stresses.SNF1-related protein kinase 2s(SnRK2)are key components that activate the ABA core signaling pathway.NUCLEAR PORE ANCHOR(NUA)is a component of the nuclear pore complex(NPC)that involves in deSU-MOylation through physically interacting with the EARLY IN SHORT DAYS 4(ESD4)SUMO protease.However,it is not clear how NUA functions with SnRK2 and ESD4 to regulate ABA signaling.In our study,we found that nua loss-of-function mutants exhibited pleiotropic ABA-hypersensitive phenotype.We also found that ABA-responsive genes remarkably up-regulated in nua by exogenous ABA.The nua snrk2.2 snrk2.3 triple mutant and nua abi5 double mutant partially rescued the ABA-hypersensitive phenotype of nua,thereby suggesting that NUA is epistatic to SnRK2s.Additionally,we observed that esd4-3 mutant was also ABA-hypersensitive.NUA and ESD4 were further demonstrated to physically interact with SnRK2s and negatively regulate ABA signaling by reducing SnRK2s stability.Taken together,our findings uncover a new regulatory mechanism that can modulate ABA signaling.

Oscillation and variation for Riesz transform in setting of Bessel operators on H1 and BMO

Letλ〉0,and let the Bessel operator△λ:=-d2/dx2-2λ/x d/dx defined on R+:=(0,∞).We show that the oscillation andρ-variation operators of the Riesz transform R△λassociated with△λare bounded on BMO(R+,dmλ),whereρ>2 and dmλ=x2λdx.Moreover,we construct a(1,∞)△λ-atom as a counterexample to show that the oscillation andρ-variation operators of R△λare not bounded from to L1(R+,dmλ).Finally,we prove that the oscillation and theρ-variation operators for the smooth truncations associated with Bessel operators R~△λare bounded from H1(R+:dmλ)to L1(R+,dmλ).

Identification of key genes and pathways in mild and severe nonalcoholic fatty liver disease by integrative analysis

Background:The global prevalence of nonalcoholic fatty liver disease(NAFLD)is increasing.The pathogenesis of NAFLD is multifaceted,and the underlying mechanisms are elusive.We conducted data mining analysis to gain a better insight into the disease and to identify the hub genes associated with the progression of NAFLD.Methods:The dataset GSE49541,containing the profile of 40 samples representing mild stages of NAFLD and 32 samples representing advanced stages of NAFLD,was acquired from the Gene Expression Omnibus database.Differentially expressed genes(DEGs)were identified using the R programming language.The Database for Annotation,Visualization and Integrated Discovery(DAVID)online tool and Search Tool for the Retrieval of Interacting Genes/Proteins(STRING)database were used to perform the enrichment analysis and construct protein-protein interaction(PPI)networks,respectively.Subsequently,transcription factor networks and key modules were identified.The hub genes were validated in a mice model of high fat diet(HFD)-induced NAFLD and in cultured HepG2 cells by real-time quantitative PCR.Results:Based on the GSE49541 dataset,57 DEGs were selected and enriched in chemokine activity and cellular component,including the extracellular region.Twelve transcription factors associated with DEGs were indicated from PPI analysis.Upregulated expression of five hub genes(SOX9,CCL20,CXCL1,CD24,andCHST4),which were identified from the dataset,was also observed in the livers of HFD-induced NAFLD mice and in HepG2 cells exposed to palmitic acid or advanced glycation end products.Conclusion:The hub genesSOX9,CCL20,CXCL1,CD24,andCHST4 are involved in the aggravation of NAFLD.Our results offer new insights into the underlying mechanism of NAFLD progression.