STUDY OF APPLICATION OF THZ TIME DOMAIN SPECTROSCOPY IN FOOD SAFETY

Abstract: In this paper, a new spectroscopy technology named terahertz time-domain spectroscopy (THz-TDS) is introduced, which is used in food safety. We describe a coherent subpicosecond THz spectroscopy system based on nonresonant optical rectification for the generation of THz radiation. As an example, we measured absorption spectrum of water vapor by THz-TDS in frequency from 0.5 to 2.5 THz, The experiment demonstrated that the spectroscopy resolution of system was up to 0.0001THz, which can be measured vegetable pesticide residual, for it neither need sample pretreatment nor cause pollution

An equilibrium analysis on the tripartite evolutionary game of garbage classification recycling

The garbage classification recycling policy is proposed to curb the waste of recyclable and land resources to reduce the environmental pollution caused by garbage. This paper establishes a tripartite evolutionary game model with governments, recycling companies, and citizens as stakeholders to discuss their corresponding strategic behaviors. Through the stability analysis, we draw a conclusion that only when governments choose to regulate the classification, while both recycling companies and citizens take an active part in the classification, can the environmental benefit be maximized. In addition, the government and recycling companies are advised to increase the rate at which the evolutionary game model converges to a steady state by reducing their own operating costs during the implementation of garbage classification. On this basis, we also recommend an appropriate increase in the benefits given to citizens, which will have a significantly positive impact on citizens and even also on the government and the recycling companies themselves

IDENTIFICATION OF TRACEABILITY BARCODE BASED ON PHASE CORRELATION ALGORITHM

Abstract: In the paper phase correlation algorithm based on Fourier transform is applied to the traceability barcode identification, which is a widely used method of image registration. And there is the rotation-invariant phase correlation algorithm which combines polar coordinate transform with phase correlation, that they can recognize the barcode with partly destroyed and rotated. The paper provides the analysis and simulation for the algorithm using Matlab, the results show that the algorithm has the advantages of good real-time and high performance. And it improves the matching precision and reduces the calculation by optimizing the rotation-invariant phase correlation

Spectroscopic and Petrographic Investigations of Lunar Mg-Suite Meteorite Northwest Africa 8687

Magnesian suite (Mg-suite) rocks represent plutonic materials from the lunar crust, and their global distribution can provide critical information for the early magmatic differentiation and crustal asymmetries of the Moon. Visible and near-infrared (VNIR) spectrometers mounted on orbiters and rovers have been proven to be powerful approaches for planetary mineral mapping, which are instrumental in diagnosing Mg-suite rocks. However, due to the scarcity and diversity of Mg-suite samples, laboratory measurements with variable proportions of minerals are imperative for spectral characterization. In this study, spectroscopic investigation and petrographic study were conducted on lunar Mg-suite meteorite Northwest Africa 8687. We classify the sample as a pink spinel-bearing anorthositic norite through spectral and petrographic characteristics. The ground-truth information of the Mg-suite rock is provided for future exploration. Meanwhile, the results imply that the VNIR technique has the potential to identify highland rock types by mineral modal abundance and could further be applied in extraterrestrial samples for primary examination due to its advantage of being fast and non-destructive

Optical Diffractive Convolutional Neural Networks Implemented in an All-Optical Way

Optical neural networks can effectively address hardware constraints and parallel computing efficiency issues inherent in electronic neural networks. However, the inability to implement convolutional neural networks at the all-optical level remains a hurdle. In this work, we propose an optical diffractive convolutional neural network (ODCNN) that is capable of performing image processing tasks in computer vision at the speed of light. We explore the application of the 4f system and the diffractive deep neural network (D2NN) in neural networks. ODCNN is then simulated by combining the 4f system as an optical convolutional layer and the diffractive networks. We also examine the potential impact of nonlinear optical materials on this network. Numerical simulation results show that the addition of convolutional layers and nonlinear functions improves the classification accuracy of the network. We believe that the proposed ODCNN model can be the basic architecture for building optical convolutional networks

A Novel Stacking Heterogeneous Ensemble Model with Hybrid Wrapper-Based Feature Selection for Reservoir Productivity Predictions

Acid fracturing is the most important stimulation method in the carbonate reservoir. Due to the high cost and high risk of acid fracturing, it is necessary to predict the reservoir productivity before acid fracturing, which can provide support to optimize the parameters of acid fracturing. However, the productivity of a single well is affected by various construction parameters and geological conditions. Overfitting can occur when performing productivity prediction tasks on the high-dimension, small-sized reservoir, and acid fracturing dataset. Therefore, this study developed a stacking heterogeneous ensemble model with a hybrid wrapper-based feature selection strategy to forecast reservoir productivity, resolve the overfitting problem, and improve productivity prediction. Compared to other baseline models, the proposed model was found to have the best predictive performances on the test set and effectively deal with the overfitting. The results proved that the hybrid wrapper-based feature selection strategy introduced in this study reduced data acquisition costs and improved model comprehensibility without reducing model performance

IGH::CD274 (PD‐L1) rearrangement in diffuse large B cell lymphoma and its therapeutic implication

Abstract Diffuse large B cell lymphoma (DLBCL) expresses abundant programmed death ligand 1 (PD‐L1), which shields tumor cells from immune attacks through the PD‐L1/PD‐1 signaling axis. The mechanism of PD‐L1 overexpression includes the deletion of the 3′end of PD‐L1, which increases its mRNA stability, and the gain or amplification of PD‐L1. Previous studies found two cases of DLBCL carrying an IGH::PD‐L1 by whole genome sequencing. We describe two more such cases by a targeted DNA next‐generation sequencing (NGS) capable of detecting IGH rearrangements, leading to PD‐L1 overexpression. DLBCL with PD‐L1 overexpression is often resistant to R‐CHOP (rituximab, cyclophosphamide, doxorubicin hydrochloride, vincristine and prednisolone). Our patients responded to a combination of R‐CHOP and a PD‐1 inhibitor