Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection

Geospatial object detection of remote sensing imagery has been attracting an increasing interest in recent years, due to the rapid development in spaceborne imaging. Most of previously proposed object detectors are very sensitive to object deformations, such as scaling and rotation. To this end, we propose a novel and efficient framework for geospatial object detection in this letter, called Fourier-based rotation-invariant feature boosting (FRIFB). A Fourier-based rotation-invariant feature is first generated in polar coordinate. Then, the extracted features can be further structurally refined using aggregate channel features. This leads to a faster feature computation and more robust feature representation, which is good fitting for the coming boosting learning. Finally, in the test phase, we achieve a fast pyramid feature extraction by estimating a scale factor instead of directly collecting all features from image pyramid. Extensive experiments are conducted on two subsets of NWPU VHR-10 dataset, demonstrating the superiority and effectiveness of the FRIFB compared to previous state-of-the-art methods

Application of microstructured fiber sensor in the field of temperature detection

A fiber temperature sensor based on no core fiber-few mode fiber-no core fiber (NCF-FMF-NCF) is proposed. It consists of two segments of NCF and a segment of FMF, with the NCF fused at both ends of the FMF. Meanwhile, the lengths of the NCF and FMF were optimized by simulation simulations and experimental validation. The results show that the sensor has a high sensitivity to the external refractive index (RI) changes, and enables a wide range of ambient temperature measurement. A sensitivity of 0.09445nm/? was obtained in a temperature range of 25-70?. The sensor has the advantages of high stability, good linear fit and simple structure

How Important are Good Method Names in Neural Code Generation? A Model Robustness Perspective

Pre-trained code generation models (PCGMs) have been widely applied in neural code generation which can generate executable code from functional descriptions in natural languages, possibly together with signatures. Despite substantial performance improvement of PCGMs, the role of method names in neural code generation has not been thoroughly investigated. In this paper, we study and demonstrate the potential of benefiting from method names to enhance the performance of PCGMs, from a model robustness perspective. Specifically, we propose a novel approach, named RADAR (neuRAl coDe generAtor Robustifier). RADAR consists of two components: RADAR-Attack and RADAR-Defense. The former attacks a PCGM by generating adversarial method names as part of the input, which are semantic and visual similar to the original input, but may trick the PCGM to generate completely unrelated code snippets. As a countermeasure to such attacks, RADAR-Defense synthesizes a new method name from the functional description and supplies it to the PCGM. Evaluation results show that RADAR-Attack can reduce the CodeBLEU of generated code by 19.72% to 38.74% in three state-of-the-art PCGMs (i.e., CodeGPT, PLBART, and CodeT5) in the fine-tuning code generation task, and reduce the Pass@1 of generated code by 32.28% to 44.42% in three state-of-the-art PCGMs (i.e., Replit, CodeGen, and CodeT5+) in the zero-shot code generation task. Moreover, RADAR-Defense is able to reinstate the performance of PCGMs with synthesized method names. These results highlight the importance of good method names in neural code generation and implicate the benefits of studying model robustness in software engineering.Comment: UNDER REVIE

Drug delivery systems for oral disease applications

There are many restrictions on topical medications for the oral cavity. Various factors affect the topical application of drugs in the oral cavity, an open and complex environment. The complex physical and chemical environment of the oral cavity, such as saliva and food, will influence the effect of free drugs. Therefore, drug delivery systems have served as supporting structures or as carriers loading active ingredients, such as antimicrobial agents and growth factors (GFs), to promote antibacterial properties, tissue regeneration, and engineering for drug diffusion. These drug delivery systems are considered in the prevention and treatment of dental caries, periodontal disease, periapical disease, the delivery of anesthetic drugs, etc. These carrier materials are designed in different ways for clinical application, including nanoparticles, hydrogels, nanofibers, films, and scaffolds. This review aimed to summarize the advantages and disadvantages of different carrier materials. We discuss synthesis methods and their application scope to provide new perspectives for the development and preparation of more favorable and effective local oral drug delivery systems

Controlling and optimization of vehicle based on genetic algorithm method while encountering an emergency collision avoidance

In consideration of the nonlinear tire lateral deviation, a nonlinear two degrees of freedom model is established in Matlab/Simulink, which can be used for emergency avoidance steering. The correctness of the model is verified by real vehicle test. Based on vehicle handling stability evaluation and single neuron self-adaptive Proportional-Integral-Differential control theory, a control algorithm to make vehicle move along the given single route with different speed is proposed. And the result of experiment is good. Next, taking advantage of multi-island genetic algorithm, an optimal control system is achieved to optimize the controlling parameters. The same experiment is carried out again with the optimized system. The results show that the optimized control algorithm is more accurate than the previous one. And it also has good robustness and self-adaption

Effect of HDAC-6 on PD cell induced by lactacystin

AbstractObjectiveTo explore the effects of histone deacetylase 6(HDAC-6) on the PD cell model induced by proteasome inhibitor lactacystin.MethodsHuman neuroblastoma SK-N-SH cells were cultured. The wild type pcDNA3.1-alpha-synuclein eukaryotic expression plasmid was transferred into the cells which then were divided into control group, group L, group T and group T+L. The cells of group L were added with 5 μmol/L lactacystin dissolved indimethylsulfoxide (DMSO) to induce PD cell model with abnormal protein aggregation, the cells of control group were treated with 5 μmol/L DMSO, the cells of group T were treated with 5 μmol/L selective HDAC-6 inhibitor tubacin dissolved in DMSO, and the cells of group T+L were treated with 5 μmol/L lactacystin and 10 μmol/L tubacin dissolved in DMSO. The expression levels of alpha-synuclein oligomers, HSP-27 and HSP-70 were detected by Western blot and the cell survival rate of all the groups was detected by MTT colorimetric assay, and compared 24 h after the cells were treated.ResultsThe expression levels of alpha-synuclein oligomers, HSP-27 and HSP-70 of the cells of group L were significantly higher than the control group, and the cell survival rate was significantly lower (P < 0.05); the expression level of alpha-synuclein oligomers of the cells of group T+L was significantly higher than group L, but the expression level of HSP-27 and HSP-70 were significantly lower, and so as the cell survival rate (P < 0.05); the differences of the expression level of alpha-synuclein oligomers, HSP-27 and HSP-70 and the cell survival rate of the cells of group T and the control group were not statistically significant (P > 0.05).ConclusionsThe expression level of alpha-synuclein oligomers can be improved and the cell survival rate can be reduced by the PD cell model induced by lactacystin and treated with selective HDAC-6 inhibitor tubacin, which means that alpha-synuclein oligomers of the PD cell model induced by lactacystin can be inhibited and the cell survival rate can be improved by HDAC-6, and the mechanism may be related to the increased of HSP-27 and HSP-70

Proximity effect at superconducting Sn-Bi2Se3 interface

We have investigated the conductance spectra of Sn-Bi2Se3 interface junctions down to 250 mK and in different magnetic fields. A number of conductance anomalies were observed below the superconducting transition temperature of Sn, including a small gap different from that of Sn, and a zero-bias conductance peak growing up at lower temperatures. We discussed the possible origins of the smaller gap and the zero-bias conductance peak. These phenomena support that a proximity-effect-induced chiral superconducting phase is formed at the interface between the superconducting Sn and the strong spin-orbit coupling material Bi2Se3.Comment: 7 pages, 8 figure