Dual Defense: Adversarial, Traceable, and Invisible Robust Watermarking against Face Swapping

The malicious applications of deep forgery, represented by face swapping, have introduced security threats such as misinformation dissemination and identity fraud. While some research has proposed the use of robust watermarking methods to trace the copyright of facial images for post-event traceability, these methods cannot effectively prevent the generation of forgeries at the source and curb their dissemination. To address this problem, we propose a novel comprehensive active defense mechanism that combines traceability and adversariality, called Dual Defense. Dual Defense invisibly embeds a single robust watermark within the target face to actively respond to sudden cases of malicious face swapping. It disrupts the output of the face swapping model while maintaining the integrity of watermark information throughout the entire dissemination process. This allows for watermark extraction at any stage of image tracking for traceability. Specifically, we introduce a watermark embedding network based on original-domain feature impersonation attack. This network learns robust adversarial features of target facial images and embeds watermarks, seeking a well-balanced trade-off between watermark invisibility, adversariality, and traceability through perceptual adversarial encoding strategies. Extensive experiments demonstrate that Dual Defense achieves optimal overall defense success rates and exhibits promising universality in anti-face swapping tasks and dataset generalization ability. It maintains impressive adversariality and traceability in both original and robust settings, surpassing current forgery defense methods that possess only one of these capabilities, including CMUA-Watermark, Anti-Forgery, FakeTagger, or PGD methods

Diurnal Variations in Neural Activity of Healthy Human Brain Decoded with Resting-State Blood Oxygen Level Dependent fMRI

It remains an ongoing investigation about how the neural activity alters with the diurnal rhythms in human brain. Resting-state functional magnetic resonance imaging (RS-fMRI) reflects spontaneous activities and/or the endogenous neurophysiological process of the human brain. In the present study, we applied the ReHo (regional homogeneity) and ALFF (amplitude of low frequency fluctuation) based on RS-fMRI to explore the regional differences in the spontaneous cerebral activities throughout the entire brain between the morning and evening sessions within a 24-h time cycle. Wide spread brain areas were found to exhibit diurnal variations, which may be attributed to the internal molecular systems regulated by clock genes, and the environmental factors including light-dark cycle, daily activities and homeostatic sleep drive. Notably, the diurnal variation of default mode network (DMN) suggests that there is an adaptation or compensation response within the subregions of DMN, implying a balance or a decoupling of regulation between these regions.National Natural Science Foundation of China [81371359]; National Basic Research Program of China [2015CB755500]; Basic Research Program of Shenzhen [JCYJ20160429191938883]SCI(E)[email protected]

Proteomic Analysis of Ubiquitinated Proteins in Rice (\u3ci\u3eOryza sativa\u3c/i\u3e) After Treatment With Pathogen-Associated Molecular Pattern (PAMP) Elicitors

Reversible protein ubiquitination plays essential roles in regulating cellular processes. Although many reports have described the functions of ubiquitination in plant defense responses, few have focused on global changes in the ubiquitome. To better understand the regulatory roles of ubiquitination in rice pattern-triggered immunity (PTI), we investigated the ubiquitome of rice seedlings after treatment with two pathogen-associated molecular patterns, the fungal-derived chitin or the bacterialderived flg22, using label-free quantitative proteomics. In chitin-treated samples, 144 and 167 lysine-ubiquitination sites in 121 and 162 proteins showed increased and decreased ubiquitination, respectively. In flg22-treated samples, 151 and 179 lysine-ubiquitination sites in 118 and 166 proteins showed increased and decreased ubiquitination, respectively. Bioinformatic analyses indicated diverse regulatory roles of these proteins. The ubiquitination levels of many proteins involved in the ubiquitination system, protein transportation, ligand recognition, membrane trafficking, and redox reactions were significantly changed in response to the elicitor treatments. Notably, the ubiquitination levels of many enzymes in the phenylpropanoid metabolic pathway were up-regulated, indicating that this pathway is tightly regulated by ubiquitination during rice PTI. Additionally, the ubiquitination levels of some key components in plant hormone signaling pathways were up- or down-regulated, suggesting that ubiquitination may fine-tune hormone pathways for defense responses. Our results demonstrated that ubiquitination, by targeting a wide range of proteins for degradation or stabilization, has a widespread role in modulating PTI in rice. The large pool of ubiquitination targets will serve as a valuable resource for understanding how the ubiquitination system regulates defense responses to pathogen attack

Free fatty acid hydrolyzed with lipases and their effects on enzyme-modified cheese flavor

peer reviewed: This study investigated the effects of five lipases on enzyme-modified cheese (EMC) flavor development. Results showed that lipase 30SD contained high hydrolytic activity for short, medium, and long-chain fatty acids within 24 h incubation time, and the highest content of them among different times could reach 47.24, 475.90, 1 563.92 mg/100 g fat, respectively. Lipase DF15 and MER showed moderate capacity to hydrolyze volatile fatty acids, while lipase F3G had a stronger ability to produce long-chain fatty acids. Twenty-seven new volatiles were formed during lipolysis, most of them were acids and esters. Principal component analysis results showed that EMC produced by lipase 30SD for 18 h was similar to the commercial product with a pungent, rancid, and cheddar flavor. EMCs produced by lipase DF15 were significantly distinguished from other products by their high content of ethyl heptanoate, ethyl nonanoate, and ethyl tridecanoate. The findings might be useful for the researchers who focus on lipolysis or EMC product

Aqueous Al2O3 nanofluids: the important factors impacting convective heat transfer

A high accuracy, counter flow double pipe heat exchanger system is designed for the measurement of convective heat transfer coefficients with different nanofluids. Both positive and negative enhancement of convective heat transfer of alumina nanofluids are found in the experiments. A modified equation was proposed to explain above phenomena through the physic properties of nanofluids such as thermal conductivity, special heat capacity and viscosity

Synthesis of a Dual Functional Anti-MDR Tumor Agent PH II-7 with Elucidations of Anti-Tumor Effects and Mechanisms

Multidrug resistance mediated by P-glycoprotein in cancer cells has been a major issue that cripples the efficacy of chemotherapy agents. Aimed for improved efficacy against resistant cancer cells, we designed and synthesized 25 oxindole derivatives based on indirubin by structure-activity relationship analysis. The most potent one was named PH II-7, which was effective against 18 cancer cell lines and 5 resistant cell lines in MTT assay. It also significantly inhibited the resistant xenograft tumor growth in mouse model. In cell cycle assay and apoptosis assay conducted with flow cytometry, PH II-7 induced S phase cell cycle arrest and apoptosis even in resistant cells. Consistently revealed by real-time PCR, it modulates the expression of genes related to the cell cycle and apoptosis in these cells, which may contributes to its efficacy against them. By side-chain modification and FITC-labeling of PH II-7, we were able to show with confocal microscopy that not only it was not pumped by P-glycoprotein, it also attenuated the efflux of Adriamycin by P-glycoprotein in MDR tumor cells. Real-time PCR and western blot analysis showed that PH II-7 down-regulated MDR1 gene via protein kinase C alpha (PKCA) pathway, with c-FOS and c-JUN as possible mediators. Taken together, PH II-7 is a dual-functional compound that features both the cytotoxicity against cancer cells and the inhibitory effect on P-gp mediated drug efflux

A heterozygous moth genome provides insights into herbivory and detoxification

How an insect evolves to become a successful herbivore is of profound biological and practical importance. Herbivores are often adapted to feed on a specific group of evolutionarily and biochemically related host plants1, but the genetic and molecular bases for adaptation to plant defense compounds remain poorly understood2. We report the first whole-genome sequence of a basal lepidopteran species, Plutella xylostella, which contains 18,071 protein-coding and 1,412 unique genes with an expansion of gene families associated with perception and the detoxification of plant defense compounds. A recent expansion of retrotransposons near detoxification-related genes and a wider system used in the metabolism of plant defense compounds are shown to also be involved in the development of insecticide resistance. This work shows the genetic and molecular bases for the evolutionary success of this worldwide herbivore and offers wider insights into insect adaptation to plant feeding, as well as opening avenues for more sustainable pest management.Minsheng You … Simon W Baxter … et al

Proteomic Analysis of Ubiquitinated Proteins in Rice (\u3ci\u3eOryza sativa\u3c/i\u3e) After Treatment With Pathogen-Associated Molecular Pattern (PAMP) Elicitors

Reversible protein ubiquitination plays essential roles in regulating cellular processes. Although many reports have described the functions of ubiquitination in plant defense responses, few have focused on global changes in the ubiquitome. To better understand the regulatory roles of ubiquitination in rice pattern-triggered immunity (PTI), we investigated the ubiquitome of rice seedlings after treatment with two pathogen-associated molecular patterns, the fungal-derived chitin or the bacterialderived flg22, using label-free quantitative proteomics. In chitin-treated samples, 144 and 167 lysine-ubiquitination sites in 121 and 162 proteins showed increased and decreased ubiquitination, respectively. In flg22-treated samples, 151 and 179 lysine-ubiquitination sites in 118 and 166 proteins showed increased and decreased ubiquitination, respectively. Bioinformatic analyses indicated diverse regulatory roles of these proteins. The ubiquitination levels of many proteins involved in the ubiquitination system, protein transportation, ligand recognition, membrane trafficking, and redox reactions were significantly changed in response to the elicitor treatments. Notably, the ubiquitination levels of many enzymes in the phenylpropanoid metabolic pathway were up-regulated, indicating that this pathway is tightly regulated by ubiquitination during rice PTI. Additionally, the ubiquitination levels of some key components in plant hormone signaling pathways were up- or down-regulated, suggesting that ubiquitination may fine-tune hormone pathways for defense responses. Our results demonstrated that ubiquitination, by targeting a wide range of proteins for degradation or stabilization, has a widespread role in modulating PTI in rice. The large pool of ubiquitination targets will serve as a valuable resource for understanding how the ubiquitination system regulates defense responses to pathogen attack

Salinity Assessment in Northeast Florida Bay Using Landsat TM Data

Human activities in the past century have caused a variety of environmental problems in the Greater introduction The Greater Everglades of South Florida Salinity is a fundamental characteristic of the physical conditions of the Everglades. Salinity affects water quality, plant associations, and the spatial distribution of vegetative communities. Effective salinity monitoring is critical for the achievement of CERP, especially with sea level change. Current observation of salinity in Florida Bay includes regular collection of station-based point data managed by the Everglades National Park and the South Florida Water Management District, and boat-based surveyed data managed by the United State Geological Survey (USGS). To assist in the salinity monitoring, the USGS developed a boat-mounted measuring system conducting bimonthly salinity surveys in Florida Bay. Surveys typically take 3-5 days to collect data along several predesigned transects. Little or no salinity data can be collected for regions where research boats cannot access. Field surveys are time-consuming, labor-intensive, and expensive. The surveyed datasets, although supplemented with station collected salinity, is still inadequate for ef- fective salinity monitoring because of spatial and temporal heterogeneity of the bay. Thus, salinity simulation and forecast models were constructed in order to generate a dataset with a finer temporal and spatial resolution covering larger portions of Florida Bay. These models can be grouped into two types: statistical models and mechanistic models The literature has demonstrated that remote sensing has the capability to assess water salinity. The lower microwave frequency (i.e. 1.4 GHz) is the ideal spectral channel to directly sense water salinity because of its high sensitivity to surface emissivity, which is closed related to salinity A number of studies have illustrated that Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM + ) have spectral and spatial characteristics that are suitable to monitor shallow water quality (e.g., Landsat is a remote sensing spacecraft with a 40-year long history, dating to the launch of Landsat 1 in 1972. The new mission, Landsat Data Continuity Mission (LDCM), is on schedule for a launch date of December 2012. Landsat data products are available from the USGS at no cost to the public. Landsat calibrates data by its own onboard radiometric calibration devices and the collected data serve as an on-orbit standard for cross-calibration of other Earth remote sensing missions, such as EOS-AM1 and EO-1. These features, combined with its finer spectral, spatial, and temporal resolutions, make Landsat TM data attractive for salinity monitoring. Several empirical models have been created to estimate salinity from Landsat data (e.g., Khorram 1982Khorram , 1985 study area and data Study Area The study area is located in northeast Florida Bay, a marine lagoon at the southern end of Florida In the past century, upstream water management activities have drastically altered the quantity, quality, timing, and distribution of fresh water flowing into the bay, which have dramatically modified its original healthy ecosystem for supporting a diversity of wildlife. Many environmental projects in CERP will affect the salinity level in the bay. The northeastern bay area is the discharge location of the wide C-111 canal and Taylor Slough carrying a large volume of fresh water into the bay, which makes its water mass different from its surroundings. Studies cited in the literature conclude that models for water quality parameter estimations are always sitespecific Data Data used in this study include the field surveyed salinity data and Landsat TM imagery collected in northeast Florida Bay between Water Years 2004-2006. The U.S. Geological Survey (USGS) defines Water Year as the 12-month period from October 1 of one year to September 30 of the following year, and designates it by the calendar year in which it ends. Field data were collected by USGS with a project titled ''Coastal Gradients Salinity Surveys''. In this project, salinity and temperature were measured along the southern coastline of Everglades National Park from Barnes Sound to Everglades City using four separate boats. Salinity was collected every five seconds via a boat-mounted flow-through cell to a continuous water quality meter. All salinity and temperature meters were checked in known conductivity standards prior to and following all surveys. Position is determined using a GPS unit which interfaces with the water quality meter. The surveyed data are posted on the website of South Florida Information Access (SOFIA http://sofia.usgs.gov/). Currently, the collected salinity data are available for Water Years 2004 to 2006 during which a total of 12 boat-based surveys were conducted. In this study, we employed the surveyed data in northeast Florida Bay to develop the salinity assessment algorithms for this selected area. Landsat-5 (WRS-2 Path 15, Row 42/43) collects TM images over the study area every 16 days. The footprint of the TM scene covering the study region is shown in results and discussion To effectively assess salinity from Landsat TM data, exploration of the original data is important. Scatter plots revealed the nonlinear character of the relationship between salinity and each TM band, which suggests that a nonlinear transformation of the datasets is necessary. The simple logit transformation for the TM records was found to best typify the data in this case. The correlation matrix of the data (shown in Table 2) illustrate that three visible bands were highly correlated (Bands 1, 2, and 3). Similarly, two mid-infrared bands (Bands 5 and 7) were also highly correlated. The near-infrared band (Band 4) was more correlated to the mid-infrared bands than the visible bands. Among the three visible bands, Band 1 generated the highest correlation to the salinity. Band 4 also presented a higher correlation with salinity. As far as the two mid-infrared bands are concerned, Band 5 presented a relative higher correlation to the salinity. Results of the correlation matrix for the dry season and wet season were consistent, although differences were observed for the derived coefficients between two seasons. Univariate regression and multivariate regression analyses were performed with the observed salinity as the dependent variable and one TM band or a combination of TM bands as independent variables in order to determine the optimal bands for establishing the empirical models. The results are presented in To further refine the model, a stepwise regression analysis was conducted. The result suggested that Bands 1, 3, and 4 are the most effective variables in salinity prediction. To validate this selection, a partial F-test was carried out. The partial F-test examines whether the difference is statistically significant between a full model (i.e. including Bands 1, 2, 3, 4, and 5) and a reduced model (i.e. including Bands 1, 3, and 4). The results were consistent with the stepwise regression outcomes. This selection is different from those adopted by other authors. For example, Lavery et al. The derived empirical models were validated using the field surveyed salinity data collected in Water Year 2006. The root mean squared error (RMSE) can be used to evaluate the accuracy of estimations. Salinity values were estimated for the sample locations using TM data extracted from two TM scenes collected on 11/09/2005 (dry season) and 06/21/ 2006 (wet season). The estimations were compared with the field surveyed data obtained on 11/10/2005 (dry season) and 06/28/2006 (wet season) respectively. A RMSE of 5.8 parts per thousand (PPT) was generated for the dry season, and a lower RMSE of 4.8 PPT was produced for the wet season. The scatter plots of the TM estimations and surveyed data revealed dozens of outliers in both dry and wet seasons. A geographical projection of the locations of these outliers on the map presented a clustered pattern, suggesting systematic errors may be occurring during the surveys. Omission of these outliers resulted in the RMSE decreasing from 5.8 PPT to 3.9 PPT for the dry season, and decreasing from 4.8 PPT to 3.5 PPT for the wet season. A map of salinity for northeast Florida Bay can be generated from a TM scene using the empirical models. The water body over the study area needs to be identified first. This was achieved using the near-infrared band because of the strong absorption of water over this spectral region. Salinity values were then calculated for the cloud-free water pixels using equation 1 or 2 based on the acquisition date of the TM data. The generated salinity maps for the selected TM scenes during Water We also explored the techniques for qualitative assessment of salinity using the minimum distance classification method and a neural network approach. The field 278 zhang et al. samples were grouped into several classes representing low, medium, high, and hyper salinity water categories. The sample data for each class were then randomly divided into two parts. One part was used as training data, and the other part as testing data for accuracy assessment. The commonly used minimum distance method was examined first using all TM bands. The conventional error matrix approach was employed to evaluate the classification results (Jensen 2005). The total accuracy was calculated from the number of correctly discriminated salinity classes against the total number of validation samples. The Kappa statistics is believed to be a better representation of the general quality of classification because it removes effects caused by differences in sample size and also accounts for the off-diagonal elements in the error matrix (Congalton et al. 1983). Thus, the Kappa value was also calculated to quantify the classification accuracy. An average of the total accuracy of 58.9 percent and Kappa coefficient of 0.43 was obtained for the dry season after running the algorithm 50 times with different training data and testing data selected. Correspondingly, an average total accuracy of 46.3 percent and Kappa coefficient of 0.23 were generated for the wet season. The minimum distance approach assumes that each class has one spectral signature that is the spectral mean vector of the training data for this class. Poor outcomes will be generated if multiple spectral signatures exist for each class. A supervised neural network developed by summary and conclusions In this study, we explored the potential of the Landsat TM sensor to serve as a regular salinity monitoring tool in Florida Bay to support the CERP and monitor changes in salinity with projected future sea level rise. Both quantitative and qualitative techniques were examined based on the spatially and temporally matched field surveyed salinity data and TM collected images in the northeastern bay area. The following conclusions are indicated in terms of the applicability of Landsat TM data to salinity monitoring: ≤ Landsat TM data appear to be effective for salinity assessment in northeast Florida Bay. A highly significant relationship between the TM data and salinity are identified for both dry and Salinity Assessment in Florida Bay 279 wet seasons. Expected salinity patterns are presented on the TM estimated salinity maps. Time-series salinity maps can provide variability of salinity in the bay, which can be used to measure the effects of restoration projects in CERP. ≤ The empirical approaches for quantitative salinity estimation generate more acceptable results than the classification methods for qualitative salinity assessment. The empirical algorithms are statistically significant and are preferable for operational purposes in this area. ≤ Bands 1, 3, and 4 were suitable for salinity estimation when used together. A combination of these three bands in the established models explained more than 70 percent of the variation in salinity. They afford a reliable surface salinity prediction capability. ≤ Salinity in the dry season is more predictable than in the wet season. Heavy rainfall and runoff in the wet season make the bay environment more complex. This causes the salinity assessment in the wet season more difficult. ≤ Extrapolating our empirical models to the entire Florida Bay must be done with caution. This study confirms the conclusion in the literature that models are site-specific. To obtain a general model applicable to the entire bay, more samples need to be collected to represent the range of possible salinity values in the entire bay. Further study will focus on the extendibility of these models for the entire bay using more field surveyed data