Trajectory Data Collection with Local Differential Privacy

Trajectory data collection is a common task with many applications in our daily lives. Analyzing trajectory data enables service providers to enhance their services, which ultimately benefits users. However, directly collecting trajectory data may give rise to privacy-related issues that cannot be ignored. Local differential privacy (LDP), as the de facto privacy protection standard in a decentralized setting, enables users to perturb their trajectories locally and provides a provable privacy guarantee. Existing approaches to private trajectory data collection in a local setting typically use relaxed versions of LDP, which cannot provide a strict privacy guarantee, or require some external knowledge that is impractical to obtain and update in a timely manner. To tackle these problems, we propose a novel trajectory perturbation mechanism that relies solely on an underlying location set and satisfies pure $\epsilon$-LDP to provide a stringent privacy guarantee. In the proposed mechanism, each point's adjacent direction information in the trajectory is used in its perturbation process. Such information serves as an effective clue to connect neighboring points and can be used to restrict the possible region of a perturbed point in order to enhance utility. To the best of our knowledge, our study is the first to use direction information for trajectory perturbation under LDP. Furthermore, based on this mechanism, we present an anchor-based method that adaptively restricts the region of each perturbed trajectory, thereby significantly boosting performance without violating the privacy constraint. Extensive experiments on both real-world and synthetic datasets demonstrate the effectiveness of the proposed mechanisms.Comment: Accepted by VLDB 202

Three-Dimensional Shape Measurements of Specular Objects Using Phase-Measuring Deflectometry

The fast development in the fields of integrated circuits, photovoltaics, the automobile industry, advanced manufacturing, and astronomy have led to the importance and necessity of quickly and accurately obtaining three-dimensional (3D) shape data of specular surfaces for quality control and function evaluation. Owing to the advantages of a large dynamic range, non-contact operation, full-field and fast acquisition, high accuracy, and automatic data processing, phase-measuring deflectometry (PMD, also called fringe reflection profilometry) has been widely studied and applied in many fields. Phase information coded in the reflected fringe patterns relates to the local slope and height of the measured specular objects. The 3D shape is obtained by integrating the local gradient data or directly calculating the depth data from the phase information. We present a review of the relevant techniques regarding classical PMD. The improved PMD technique is then used to measure specular objects having discontinuous and/or isolated surfaces. Some influential factors on the measured results are presented. The challenges and future research directions are discussed to further advance PMD techniques. Finally, the application fields of PMD are briefly introduce

Rice Yellow Stunt Nucleorhabdovirus Matrix Protein Mediates Viral Axonal Transport in the Central Nervous System of Its Insect Vector

Persistently transmitted plant viruses encounter multiple membrane and tissue barriers in the process of completing their infection routes within their insect vectors. Some of these viruses have been reported to overcome the elaborate barriers of the central nervous system (CNS) to travel through the nervous tissues, but the specific mechanisms of this process remain unknown. Here, we report the axonal transport mechanism of rice yellow stunt virus (RYSV), a nucleorhabdovirus, in the CNS of the green rice leafhopper (Nephotettix cincticeps). The infection route of RYSV in the internal organs of its insect vector after ingestion of the virus was investigated by immunofluorescence microscopy. RYSV was first detected in the epithelial cells of midgut regions, from where it proceeded to the nervous system, and finally into the salivary glands. We then utilized immunofluorescence and electron microscopy to investigate the distribution of RYSV particles within the leafhopper CNS, demonstrating that non-enveloped viral particles distributed along the microtubule-based neurofilaments in the axon cytoplasm following the direct interaction of leafhopper α-tubulin with the RYSV M protein. Tubulin inhibitors inhibited the dissemination of RYSV to the CNS, then into the salivary glands in leafhoppers. We therefore describe a mechanism of plant virus transport through CNS axons as an alternative means of rapid viral dissemination in an insect vector

Rapid detection of coal ash based on machine learning and X-ray fluorescence

Real-time testing of coal ash plays a vital role in the chemical, power generation, metallurgical, and coal separation sectors. The rapid online testing of coal ash using radiation measurement as the mainstream technology has problems such as strict coal sample requirements, poor radiation safety, low accuracy, and complicated equipment replacement. In this study, an intelligent detection technique based on feed-forward neural networks and improved particle swarm optimization (IPSO-FNN) is proposed to predict coal quality ash content in a fast, accurate, safe，and convenient manner. The data set was obtained by testing the elemental content of 198 coal samples with X-ray fluorescence (XRF). The types of input elements for machine learning (Si, Al, Fe, K, Ca, Mg, Ti, Zn, Na, P) were determined by combining the X-ray photoelectron spectroscopy (XPS) data with the change in the physical phase of each element in the coal samples during combustion. The mean squared error and coefficient of determination were chosen as the performance measures for the model. The results show that the IPSO algorithm is useful in adjusting the optimal number of nodes in the hidden layer. The IPSO-FNN model has strong prediction ability and good accuracy in coal ash prediction. The effect of the input element content of the IPSO-FNN model on the ash content was investigated, and it was found that the potassium content was the most significant factor affecting the ash content. This study is essential for real-time online, accurate, and fast prediction of coal ash

Effect of reduced nitrogen fertilizer application combined with biochar on nitrogen utilization of flue-cured tobacco and its association with functional gene expressions of the nitrogen cycle in rhizosphere soil

Studies have shed light on the impact of the co-application of inorganic fertilizer and biochar on soil fertility, health, and crop growth performance and yield. However, insufficient literature exists regarding the appropriate nitrogen reduction ratio for enhancing soil quality and maximizing crop nitrogen utilization following the application of biochar in a continuous tobacco-rice rotation field. Here, we explored nitrogen absorption and utilization patterns of tobacco crops, as well as the response characteristics of functional genes related to soil nitrogen cycling subjected to the interaction of reduced nitrogen utilization ratios following biochar application in a long-term tobacco-rice rotation field. The results showed that the treatments with 10% (T2) and 20% (T3) nitrogen reduction combined with biochar (30 t∙ha−1) promoted nitrogen utilization efficiency and nitrogen harvest index of tobacco plants. In the second year of the experiment, T2 and T3 significantly increased the nitrogen harvest index by 3.85% and 5.78% compared with the conventional nitrogen application treatment (T1), respectively. We believe that the increase in abundance of nitrification, nitrogen fixation, and ammonification genes, including nxrA, nifH, and UreC in the rhizosphere soil, precipitate the high nitrogen absorption and utilization efficiency in the biochar combined with nitrogen reduction treatments, respectively. This suggests that biochar application at a rate of 30 t·ha−1, nitrogen fertilizer usage can be reduced by 10% and 20% to achieve optimal and sustainable tobacco production