Limit theorems for functionals of long memory linear processes with infinite variance

Let $X=\{X_n: n\in\mathbb{N}\}$ be a long memory linear process in which the coefficients are regularly varying and innovations are independent and identically distributed and belong to the domain of attraction of an $\alpha$-stable law with $\alpha\in (0, 2)$. Then, for any integrable and square integrable function $K$ on $\mathbb{R}$, under certain mild conditions, we establish the asymptotic distributions of the partial sum $$\sum\limits_{n=1}^{N}\big[K(X_n)-\mathbb{E} K(X_n)\big]$$ as $N$ tends to infinity

Plant biomass allocation and driving factors of grassland revegetation in a Qinghai-Tibetan Plateau chronosequence

Biomass allocation is a key factor in understanding how ecosystems respond to changing environmental conditions. The role of soil chemistry in the above- and belowground plant biomass allocation in restoring grassland is still incompletely characterized. Consequently, it has led to two competing hypotheses for biomass allocation: optimal partitioning, where the plants allocate biomass preferentially to optimize resource use; and the isometric hypothesis, which postulates that biomass allocation between roots and shoots is fixed. Here we tested these hypotheses over a chronosequence of alpine grasslandsion undergoing restoration in the Qinghai-Tibetan Plateau, these range from severely degraded to those with 18 years of revegetation with an intact grassland (as a reference). A high proportion of biomass was allocated to the roots in the revegetated grasslands, and more biomass to shoots in the degraded and intact grasslands. The grasslands gradually decreased their root to shoot ratio as revegetation continued, with the lowest value in year 18 of revegetation. Our results showed that aboveground biomass (AGB) was increased by available phosphorus (P), soil moisture, and negatively related to bulk density, while belowground biomass (BGB) was positively impacted by total P and negatively by nitrate nitrogen (N). The trade-off between them was positively associated with available P and nitrate-N, and soil nutrient availability is more linked to increased AGB relative to BGB. Our study indicates that biomass allocation is highly variable during the revegetation period from degraded grassland, and is linked with soil properties, thus supporting the optimal partitioning hypothesis.</p

Fast and accurate X-ray fluorescence computed tomography imaging with the ordered-subsets expectation maximization algorithm.

The ordered-subsets expectation maximization algorithm (OSEM) is introduced to X-ray fluorescence computed tomography (XFCT) and studied; here, simulations and experimental results are presented. The simulation results indicate that OSEM is more accurate than the filtered back-projection algorithm, and it can efficiently suppress the deterioration of image quality within a large range of angular sampling intervals. Experimental results of both an artificial phantom and cirrhotic liver show that with a satisfying image quality the angular sampling interval could be improved to save on the data-acquisition time when OSEM is employed. In addition, with an optimum number of subsets, the image reconstruction time of OSEM could be reduced to about half of the time required for one subset. Accordingly, it can be concluded that OSEM is a potential method for fast and accurate XFCT imaging

A highly sensitive bio-barcode immunoassay for multi-residue detection of organophosphate pesticides based on fluorescence anti-quenching

Balancing the risks and benefits of organophosphate pesticides (OPs) on human and environmental health relies partly on their accurate measurement. A highly sensitive fluorescence anti-quenching multi-residue bio-barcode immunoassay was developed to detect OPs (triazophos, parathion, and chlorpyrifos) in apples, turnips, cabbages, and rice. Gold nanoparticles were functionalized with monoclonal antibodies against the tested OPs. DNA oligonucleotides were complementarily hybridized with an RNA fluorescent label for signal amplification. The detection signals were generated by DNA-RNA hybridization and ribonuclease H dissociation of the fluorophore. The resulting fluorescence signal enables multiplexed quantification of triazophos, parathion, and chlorpyrifos residues over the concentration range of 0.01–25, 0.01–50, and 0.1–50 ng/mL with limits of detection of 0.014, 0.011, and 0.126 ng/mL, respectively. The mean recovery ranged between 80.3% and 110.8% with relative standard deviations of 7.3%–17.6%, which correlate well with results obtained by LC-MS/MS. The proposed bio-barcode immunoassay is stable, reproducible and reliable, and is able to detect low residual levels of multi-residue OPs in agricultural products.This work was supported by the Central Public Interest Scientific Institution Basal Research Fund for the Chinese Academy of Agricultural Sciences (Grant No.: Y2021PT05), National Institute of Environmental Health Science Superfund Research Program (Grant No.: P42 ES004699), National Academy of Sciences (Subaward No.: 2000009144), and Ningbo Innovation Project for Agro-Products Quality and Safety (Grant No.: 2019CXGC007).Peer reviewe

Kernel entropy estimation for linear processes II

Let $X=\{X_n: n\in \mathbb{N}\}$ be a linear process with bounded probability density function $f(x)$. Under certain conditions, we use the kernel estimator $$\frac{2}{n(n-1)h_n} \sum_{1\le i<j\le n}K\Big(\frac{X_i-X_j}{h_n}\Big)$$ to estimate the quadratic functional of $\int_{\mathbb{R}}f^2(x)dx$ of the linear process $X=\{X_n: n\in \mathbb{N}\}$ and improve the corresponding results in [4]

An Enhanced Detection System of Drill Rod Bending Degree Based on Two-Dimensional Laser

Drill rod straightness has to be strictly controlled and the maximum bending degree detection needs to be used in the straightening process. The mechanical bending degree measurement depends on machinery instruments and workers&rsquo; experience, often with low efficiency and precision. While the optical inspection, as a non-contact detection method, with higher precision and lower installation accuracy requirements, is frequently applied in the online detection system. Based on this, an enhanced bending degree detection system for a drill rod is proposed in this paper. Compared to the existing detection system, the main progress is to use a two-dimensional laser to quickly obtain arc profile data and fit with ellipse. Segment inspection idea is also utilized is this system as the camera that could obtain the whole drill rod in one shot needs extremely high resolution and price. A specialized algorithm is designed to fit the cross-section shape and whole centerline displacement based on the least square method. Some laboratory tests are conducted to verify this detection system, findings of which are compared to manual measured results. The maximum bending degree error is 2.14 mm and the maximum position error is 8.21 mm, which are both within the tolerance of error. Those results show the feasibility and precision of this enhanced detection system

Phase retrieval without phase unwrapping for white blood cells in deep-learning phase-shifting digital holography

Phase retrieval and phase unwrapping are the two important problems for enabling quantitative phase imaging of cells in phase-shifting digital holography. To simultaneously cope with these two problems, a deep-learning phase-shifting digital holography method is proposed in this paper. The proposed method can establish the continuous mapping function of the interferogram to the ground-truth phase using the end-to-end convolutional neural network. With a well-trained deep convolutional neural network, this method can retrieve the phase from one-frame blindly phase-shifted interferogram, without phase unwrapping. The feasibility and applicability of the proposed method are verified by the simulation experiments of the microsphere and white blood cells, respectively. This method will pave the way to the quantitative phase imaging of biological cells with complex substructures