Multi-scale diff-changed feature fusion network for hyperspectral image change detection.

For hyperspectral images (HSI) change detection (CD), multi-scale features are usually used to construct the detection models. However, the existing studies only consider the multi-scale features containing changed and unchanged components, which is difficult to represent the subtle changes between bi-temporal HSIs in each scale. To address this problem, we propose a multi-scale diff-changed feature fusion network (MSDFFN) for HSI CD, which improves the ability of feature representation by learning the refined change components between bi-temporal HSIs under different scales. In this network, a temporal feature encoder-decoder sub-network, which combines a reduced inception module and a cross-layer attention module to highlight the significant features, is designed to extract the temporal features of HSIs. A bidirectional diff-changed feature representation module is proposed to learn the fine changed features of bi-temporal HSIs at various scales to enhance the discriminative performance of the subtle change. A multi-scale attention fusion module is developed to adaptively fuse the changed features of various scales. The proposed method can not only discover the subtle change of bi-temporal HSIs but also improve the discriminating power for HSI CD. Experimental results on three HSI datasets show that MSDFFN outperforms a few state-of-the-art methods

Vehicle emission and atmospheric pollution in China: problems, progress, and prospects

China has been the largest vehicle market in the world since 2009. The stalemate between the rapid development of the vehicle industry and delayed vehicle emission control has become increasingly prominent. Vehicle emission has become a significant source of air pollution in China’s cities. Understanding the current barriers in the vehicle industry is necessary for the development of effective and sustainable measures and policy to manage vehicle-induced air pollution. This review provides insight into the circumstances and causes of vehicle-induced air pollution and outlines recent progress in policy-makers’ long-term strategies and regulations. The development of an integrated mechanism of social participation, technical revolution, and regulatory innovation in vehicles, fuel, and roads is suggested to break the stalemate between air pollution and the automobile boom in China; the implications of this review extend to other countries facing the similar atmospheric pollution problems

Flexible wavelength-, pulse-controlled mode-locked all-fiber laser based on a fiber Lyot filter

In this paper, we report a flexible wavelength-, pulse-controlled mode-locked all-fiber laser based on a novel fiber optic Lyot filter. The wavelength, pulse duration and spectral bandwidth of passive mode-locked lasers can be tuned by controlling the polarization controller. The proposed Lyot filter was constructed by a single-mode fiber insertion between two polarization-maintaining fibers. The filter bandwidth and laser output tunability were based on the birefringence characteristics of the polarization-maintaining fibers. This all-fiber laser is simple and stable and can be used for various applications where width-tunable or wavelength-tunable pulses are necessary

Mitigating Psychological Trauma on Adult Burn Patients Based on Virtual Reality Technology of Smart Medical Treatment

Virtual reality (VR) is one of the hot spots in the computer network world in recent years, which has attracted more and more people’s attention. This study mainly explores the effect of mitigating the psychological trauma of adult burn patients based on the VR technology of smart medical treatment. First, the EEG data are sent to the data processing module through a wireless protocol; then, the data processing module denoises the EEG data and performs feature extraction and feedback parameter calculation; after that, these parameters will be sent to the VR interaction engine; based on this, these parameters change the VR scene to capture and reflect the physiological activities of the patient’s brain in real time; finally, the patient uses the VR scene content presented by the real-time feedback of the captured EEG signal as a guide to making self-adjustment in time, and the electrical signal of captured brain at this time is again transmitted to the next work cycle and continues to feed back and present new VR interactive scenes to guide and intervene in the patient’s self-regulation behavior. The VR feedback training module is responsible for receiving the characteristic data calculated from the EEG acquisition and processing module and converts it into parameter variables that control the VR intervention system. The system user adjusts the state according to the feedback information displayed in the VR scene and generates new EEG signals to promote the realization of self-adjustment. The biofeedback training based on EEG feeds back the intuitive EEG state to the patient, prompting them to learn how to realize self-regulation and achieve the purpose of adjusting the level of mental health. The degree of itching and pain in the VR treatment group was alleviated, and compared with the normal training treatment results, it was statistically significant (P>0.05). This study has a positive effect on the psychological intervention of patients with facial injuries

The growth, lipid accumulation and adaptation mechanism in response to variation of temperature and nitrogen supply in psychrotrophic filamentous microalga Xanthonema hormidioides (Xanthophyceae)

Abstract Background Microalgae are promising feedstocks for production of renewable biofuels and value-added bioproducts. Temperature and nitrogen supply are important environmental and nutritional factors affecting the growth and metabolism of microalgae, respectively. In this study, the growth and lipid accumulation of filamentous microalgae Xanthonema hormidioides under different temperatures (5, 7, 10, 15, 20, 25, 27 and 30 °C) and initial nitrogen concentrations (3, 9, 18 mM) were investigated, and its adaptive mechanisms of tolerance to low temperature and nitrogen stress were analysis by proteomics. Results The optimum temperature range for the growth of X. hormidioides was between 15 and 20 °C, and the algal cells had slow growth rate at 5 °C and could not survive at 30 °C. The maximum biomass concentration was 11.73 g L−1 under the temperature of 20 °C, and the highest total lipid content was 56.63% of dry weight. Low temperature did not change the fatty acids profiles but promoted the accumulation of unsaturated fatty acids of X. hormidioides. The maximum contents of palmitoleic acid, eicosapentaenoic acid and total fatty acid were 23.64%, 2.49% and 41.14% of dry weight, respectively. Proteomics was performed under three temperature (7, 15, 25 °C), two nitrogen concentrations (3 and 18 mM) and two cultivation times (day 3 and 12). A total of 6503 proteins were identified. In the low temperature, photosynthesis-related proteins were down-regulated to protect the photosynthetic apparatus. The up-regulation of key enzymes DGAT and PDAT demonstrated the accumulation of TAGs under low nitrogen treatment. The proteins related to ribosome, phosphatidylinositol signaling system, antioxidant system and cold shock proteins (CSPs) in X. hormidioides were co-upregulated under the treatment of low temperature, which can alleviate the damages induced by temperature stress and maintain the normal growth and metabolism of algal cells. Conclusions X. hormidioides is a psychrotolerant microalga. It is an oleaginous filamentous microalga containing hyper palmitoleic acid and a certain amount of eicosapentaenoic acid with great potential for biofuel development, as well as for applications in nutritional health products and other industries