Search

It is essential to estimate the indoor pesticides/insecticides exposure risk since reports show that 80% of human exposure to pesticides occurs indoors. As one of the three major contamination sources, surface collected pesticides contributed significantly to this risk. Here, a highly sensitive liquid freestanding membrane (FSM) SERS method based on iodide modified silver nanoparticles (Ag NPs) was developed for quantitative detection of insecticide deltamethrin (DM) residues in solution phase samples and on surfaces with good accuracy and high sensitivity. The DM SERS spectrum from 500 to 2500 cm−1 resembled the normal Raman counterpart of solid DM. Similar bands at 563, 1000, 1165, 1207, 1735, and 2253 cm−1 were observed as in the literature. For the quantitative analysis, the strongest peak at 1000 cm−1 that was assigned to the stretching mode of the benzene ring and the deformation mode of C-C was selected. The peak intensity at 1000 cm−1 and the concentration of DM showed excellent linearity from 39 to 5000 ppb with a regression equation I = 649.428 + 1.327 C (correlation coefficient R2 = 0.991). The limit of detection (LOD) of the DM was found to be as low as 11 ppb. Statistical comparison between the proposed and the HPLC methods for the analysis of insecticide deltamethrin (DM) residues in solution phase samples showed no significant difference. DM residue analysis on the surface was mimicked by dropping DM pesticide on the glass surface. It is found that DM exhibited high residue levels up to one week after exposure. This proposed SERS method could find application in the household pesticide residues analysis.

To achieve automatic disc cutter replacement of shield machines, measuring the accurate pose of the disc cutter holder by machine vision is crucial. However, under polluted and restricted illumination conditions, achieving pose estimation by vision is a great challenge. This paper proposes a line-features-based pose estimation method for the disc cutter holder of the shield machine by using a monocular camera. For the blurring effect of rounded corners on the image edge, a rounded edge model is established to obtain edge points that better match the 3D model of the workpiece. To obtain the edge search box corresponding to each edge, a contour separation method based on an adaptive threshold region growing method is proposed. By preprocesses on the edge points of each edge, the efficiency and the accuracy of RANSAC linear fitting are improved. The experimental result shows that the proposed pose estimation method is highly reliable and can meet the measurement accuracy requirements in practical engineering applications.

Drowning is a major public health problem and a leading cause of death in children living in developing countries. We seek better machine learning (ML) algorithms to provide a novel risk-assessment insight on non-fatal drowning prediction. The data on non-fatal drowning were collected in Qingyuan city, Guangdong Province, China. We developed four ML models to predict the non-fatal drowning risk, including a logistic regression model (LR), random forest model (RF), support vector machine model (SVM), and stacking-based model, on three primary learners (LR, RF, SVM). The area under the curve (AUC), F1 value, accuracy, sensitivity, and specificity were calculated to evaluate the predictive ability of the different learning algorithms. This study included a total of 8390 children. Of those, 12.07% (1013) had experienced non-fatal drowning. We found the following risk factors are closely associated with the risk of non-fatal drowning: the frequency of swimming in open water, distance between the school and the surrounding open waters, swimming skills, personality (introvert) and relationality with family members. Compared to the other three base models, the stacking generalization model achieved a superior performance in the non-fatal drowning dataset (AUC = 0.741, sensitivity = 0.625, F1 value = 0.359, accuracy = 0.739 and specificity = 0.754). This study indicates that applying stacking ensemble algorithms in the non-fatal drowning dataset may outperform other ML models.

The proportion of universal segment in tunnel construction is constantly increasing. A key factor affecting the quality of tunnel construction is the selection of the shield segment assembly points. Nevertheless, the quality and efficiency of the current manual selection method cannot be guaranteed. To realize a high correct rate, high efficiency and intelligence of universal segment assembly points selection, an intelligent selection method of assembly points is proposed. First, the objective function is established by considering the thrust cylinder stroke and shield tail gap differences. Second, to adaptively optimize the weights of the objective function, the working conditions are divided into 81 intervals, and a genetic algorithm is proposed to optimize weights in each interval. Third, a Monte-Carlo-based method is proposed to generate an example dataset, which is used for the genetic algorithm to optimize the weights. Finally, the proposed method was applied to the segment assembly points selection for Line 8 of the Zhengzhou rail transit in China. The results show that the method of assembly segment selection can reach a 90.6% correct rate in the field. The research results of this paper can be used for the selection of the universal shield segment assembly points.

The visual measurement system plays a vital role in the disc cutter changing robot of the shield machine, and its accuracy directly determines the success rate of the disc cutter grasping. However, the actual industrial environment with strong noise brings a great challenge to the pose measurement methods. The existing methods are difficult to meet the required accuracy of pose measurement based on machine vision under the disc cutter changing conditions. To solve this problem, we propose a monocular visual pose measurement method consisting of the high precision optimal solution to the PnP problem (OPnP) method and the highly robust distance matching (DM) method. First, the OPnP method is used to calculate the rough pose of the shield machine’s cutter holder, and then the DM method is used to measure its pose accurately. Simulation results show that the proposed monocular measurement method has better accuracy and robustness than the several mainstream PnP methods. The experimental results also show that the maximum error of the proposed method is 0.28° in the direction of rotation and 0.32 mm in the direction of translation, which can meet the measurement accuracy requirement of the vision system of the disc cutter changing robot in practical engineering application.

The authors wish to make the following correction to this paper [1]. Due to mislabeling, the following figures: [...]

Neonatal γ-immunoglobulin (IgG) Fc receptor (FcγRn) is a receptor that transports IgG across the intestinal mucosa, placenta, and mammary gland, ensuring the balance of IgG and albumin in the body. These functions of FcγRn depend on the intracellular signal transduction and activation caused by the combination of its extracellular domain and IgG Fc domain. Nevertheless, there are still no kinetic studies on this interaction. Consequently, in the present study, we successfully constructed the human FcγRn (hFcγRn) electrochemical receptor sensor. The signal amplification system formed by chitosan nanogold-hFcγRn protein and horseradish peroxidase was used to simulate the cell signal amplification system in vivo, and the kinetic effects between seven IgG and hFcγRn receptors from different species were quantitatively measured. The results showed that the interaction of these seven IgGs with hFcγRn was similar to the catalytic kinetics of enzyme and substrate, and there was a ligand-receptor saturation effect. The order of the interconnect allosteric constants (Ka), which is similar to the Michaelis constant (Km), was human IgG < bovine IgG < horse IgG < rabbit IgG < sheep IgG < donkey IgG < quail IgY. The results showed that hFcγRn had the strongest ability to transport human IgG, which was consistent with the evolution of the system. Therefore, our hFcγRn electrochemical receptor sensor can be used to measure and evaluate the interconnected allosteric network. It is also an essential parameter of the interaction between hFcγRn and different IgGs and, thus, provides a new detection and evaluation method for immunoemulsion, therapeutic monoclonal antibody therapy, heteroantibody treatment, and half-life research.

Increased transcriptional levels of genes encoding antioxidant enzymes play important protective roles in coping with excessive accumulation of reactive oxygen species (ROS) in plants exposed to various abiotic stresses. To fully elucidate different evolutions and functions of ROS-scavenging enzymatic genes, we isolated iron superoxide dismutase (FeSOD), dehydroascorbate reductase (DHAR) and monodehydroascorbate reductase (MDHAR) from white clover for the first time and subsequently tested dynamic expression profiles of these genes together with previously identified other antioxidant enzyme genes including copper zinc superoxide dismutase (Cu/ZnSOD), manganese superoxide dismutase (MnSOD), glutathione reductase (GR), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) in response to cold, drought, salinity, cadmium stress and exogenous abscisic acid (ABA) or spermidine (Spd) treatment. The cloned fragments of FeSOD, DHAR and MDHAR genes were 630, 471 and 669 bp nucleotide sequences encoding 210, 157 and 223 amino acids, respectively. Phylogenetic analysis indicated that both amino acid and nucleotide sequences of these three genes are highly conservative. In addition, the analysis of genes expression showed the transcription of GR, POD, MDHAR, DHAR and Cu/ZnSOD were rapidly activated with relatively high abundance during cold stress. Differently, CAT, APX, FeSOD, Cu/ZnSOD and MnSOD exhibited more abundant transcripts compared to others under drought stress. Under salt stress, CAT was induced preferentially (3–12 h) compared to GR which was induced later (12–72 h). Cadmium stress mainly up-regulated Cu/ZnSOD, DHAR and MDHAR. Interestingly, most of genes expression induced by ABA or Spd happened prior to various abiotic stresses. The particular expression patterns and different response time of these genes indicated that white clover differentially activates genes encoding antioxidant enzymes to mitigate the damage of ROS during various environmental stresses.