An efficient decision support system for flood inundation management using intermittent remote-sensing data

Abstract: Timely acquisition of spatial flood distribution is an essential basis for flood-disaster monitoring and management. Remote-sensing data have been widely used in water-body surveys. However, due to the cloudy weather and complex geomorphic environment, the inability to receive remote-sensing images throughout the day has resulted in some data being missing and unable to provide dynamic and continuous flood inundation process data. To fully and effectively use remote-sensing data, we developed a new decision support system for integrated flood inundation management based on limited and intermittent remote-sensing data. Firstly, we established a new multi-scale water-extraction convolutional neural network named DEU-Net to extract water from remote-sensing images automatically. A specific datasets training method was created for typical region types to separate the water body from the confusing surface features more accurately. Secondly, we built a waterfront contour active tracking model to implicitly describe the flood movement interface. In this way, the flooding process was converted into the numerical solution of the partial differential equation of the boundary function. Space upwind difference format and the time Euler difference format were used to perform the numerical solution. Finally, we established seven indicators that considered regional characteristics and flood-inundation attributes to evaluate flood-disaster losses. The cloud model using the entropy weight method was introduced to account for uncertainties in various parameters. In the end, a decision support system realizing the flood losses risk visualization was developed by using the ArcGIS application programming interface (API). To verify the effectiveness of the model constructed in this paper, we conducted numerical experiments on the model’s performance through comparative experiments based on a laboratory scale and actual scale, respectively. The results were as follows: (1) The DEU-Net method had a better capability to accurately extract various water bodies, such as urban water bodies, open-air ponds, plateau lakes etc., than the other comparison methods. (2) The simulation results of the active tracking model had good temporal and spatial consistency with the image extraction results and actual statistical data compared with the synthetic observation data. (3) The application results showed that the system has high computational efficiency and noticeable visualization effects. The research results may provide a scientific basis for the emergency-response decision-making of flood disasters, especially in data-sparse regions

Event-related potential N270 correlates of brand extension

The aim of this study is to investigate the neural mechanism of extending a brand in a speci¢c product category to other product categories. Facing two sequential stimuli in pairs consisting of beverage brand names (stimulus 1) and product names (stimulus 2) in other categories, 16 participants were asked to indicate the suitability of extending the brand in stimulus1to the product category in stimulus 2. These stimulus pairs were divided into four conditions depending on the product category in stimulus 2: beverage, snack, clothing, and household appliance. A negative component, N270, was recorded for each condition on the participants' scalps, whereas the maximum amplitude was observed at the frontal area. Greater N270 amplitude was observed when participants were presented with stronger con£ict between the brand product category (stimulus 1) and the extension category (stimulus 2). It suggests that N270 can be evoked not only by a con£ict of physical attributes (di¡erent shapes of words of brand and product names) but also by that of lexical content. From the marketing perspective, N270 can be potentially used as a reference measure in brand-extension attempts

Black-Box watermarking and blockchain for IP protection of voiceprint recognition model

Deep neural networks are widely used for voiceprint recognition, whilst voiceprint recognition models are vulnerable to attacks. Existing protection schemes for voiceprint recognition models are insufficient to withstand various robustness attacks and cannot prevent model theft. This paper proposes a black-box voiceprint recognition model protection framework that combines active and passive protection. It embeds key information into the Mel spectrogram to generate trigger samples that are difficult to detect and remove and injects them into the host model as watermark W, thereby enhancing the copyright protection performance of the voiceprint recognition model. To restrict the use of the model by unauthorized users, the index number corresponding to the model and the encrypted model information are stored on the blockchain, and then, an exclusive smart contract is designed to restrict access to the model. Experimental results show that this framework effectively protects voiceprint recognition model copyrights and restricts unauthorized access

Characteristic Aroma and Molecular Sensory Analysis of Black Teas from Different Regions by Gas Chromatography-Mass Spectrometry and Gas Chromatography-Olfactometry

In order to investigate the differences in the characteristic aroma of black teas from different regions, the volatile aroma compounds of Keemun black tea, Yichang black tea, Dianhong black tea and Yingde black tea were identified by solid phase extraction (SPE) combined with gas chromatography-mass spectrometry (GC-MS) and were evaluated by gas chromatography-olfactory (GC-O). Odor activity value (OAV) calculation and correlation analysis between sensory aroma profile and key aroma-active compounds were performed to analyze the sensory attributes and chemical basis of the characteristic aroma of black tea. The results showed that the four black teas differed in the sensory attributes of seven aroma notes such as floral, sweet and herbal notes. Additionally, 24 differential key aroma compounds were identified (P 1). Geraniol contributed most to black tea aroma with the highest OAV in Keemun black tea (16 581.33), followed by Yichang black tea (7 463.65), Dianhong black tea (2 832.13) and Yingde black tea (467.96). Partial least squares (PLS) regression analysis and Pearson correlation analysis showed that β-ionone, geraniol and indole were responsible for the floral and sweet aroma of Keemun black tea, (Z)-3-hexenol and α-terpineol contributed to the fruity and woody aroma of Dianhong black tea, and 2-heptanol and (Z)-linalooloxide were responsible for the herbal aroma of Yingde black tea. In conclusion, this study has preliminarily clarified the characteristic aroma profiles of black tea from the four regions and their material basis at the molecular level

New insights into the interplay between autophagy and cartilage degeneration in osteoarthritis

Autophagy is an intracellular degradation system that maintains the stable state of cell energy metabolism. Some recent findings have indicated that autophagy dysfunction is an important driving factor for the occurrence and development of osteoarthritis (OA). The decrease of autophagy leads to the accumulation of damaged organelles and macromolecules in chondrocytes, which affects the survival of chondrocytes and ultimately leads to OA. An appropriate level of autophagic activation may be a new method to prevent articular cartilage degeneration in OA. This minireview discussed the mechanism of autophagy and OA, key autophagy targets regulating OA progression, and evaluated therapeutic applications of drugs targeting autophagy in preclinical and clinical research. Some critical issues worth paying attention to were also raised to guide future research efforts

Gene editing in monogenic autism spectrum disorder: animal models and gene therapies

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disease, and its diagnosis is dependent on behavioral manifestation, such as impaired reciprocal social interactions, stereotyped repetitive behaviors, as well as restricted interests. However, ASD etiology has eluded researchers to date. In the past decades, based on strong genetic evidence including mutations in a single gene, gene editing technology has become an essential tool for exploring the pathogenetic mechanisms of ASD via constructing genetically modified animal models which validates the casual relationship between genetic risk factors and the development of ASD, thus contributing to developing ideal candidates for gene therapies. The present review discusses the progress in gene editing techniques and genetic research, animal models established by gene editing, as well as gene therapies in ASD. Future research should focus on improving the validity of animal models, and reliable DNA diagnostics and accurate prediction of the functional effects of the mutation will likely be equally crucial for the safe application of gene therapies

Microfluidic Assaying of Circulating Tumor Cells and Its Application in Risk Stratification of Urothelial Bladder Cancer

Bladder cancer is characterized by its frequent recurrence and progression. Effective treatment strategies need to be based on an accurate risk stratification, in which muscle invasiveness and tumor grade represent the two most important factors. Traditional imaging techniques provide preliminary information about muscle invasiveness but are lacking in terms of accuracy. Although as the gold standard, pathological biopsy is only available after the surgery and cannot be performed longitudinally for long-term surveillance. In this work, we developed a microfluidic approach that interrogates circulating tumor cells (CTCs) in the peripheral blood of bladder cancer patients to reflect the risk stratification of the disease. In a cohort of 48 bladder cancer patients comprising 33 non-muscle invasive bladder cancer (NMIBC) cases and 15 muscle invasive bladder cancer (MIBC) cases, the CTC count was found to be considerably higher in the MIBC group compared with the NMIBC group (4.67 vs. 1.88 CTCs/3 mL, P=0.019), and was significantly higher in high-grade bladder cancer patients verses low-grade bladder cancer patients (3.69 vs. 1.18 CTCs/3mL, P=0.024). This microfluidic assay of CTCs is believed to be a promising complementary tool for the risk stratification of bladder cancer