DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery Analysis

The rapid progress in deep learning has given rise to hyper-realistic facial forgery methods, leading to concerns related to misinformation and security risks. Existing face forgery datasets have limitations in generating high-quality facial images and addressing the challenges posed by evolving generative techniques. To combat this, we present DiffusionFace, the first diffusion-based face forgery dataset, covering various forgery categories, including unconditional and Text Guide facial image generation, Img2Img, Inpaint, and Diffusion-based facial exchange algorithms. Our DiffusionFace dataset stands out with its extensive collection of 11 diffusion models and the high-quality of the generated images, providing essential metadata and a real-world internet-sourced forgery facial image dataset for evaluation. Additionally, we provide an in-depth analysis of the data and introduce practical evaluation protocols to rigorously assess discriminative models' effectiveness in detecting counterfeit facial images, aiming to enhance security in facial image authentication processes. The dataset is available for download at \url{https://github.com/Rapisurazurite/DiffFace}

Re-channelization of turbidity currents in South China Sea abyssal plain due to seamounts and ridges

Turbidity currents can be characterized as net-erosive, net-depositional or net-bypassing. Whether a flow is erosive, depositional or bypasses depends on the flow velocity, concentration and size but these can also be impacted by external controls such as the degree of confinement, slope gradient and substrate type and erodibility. Our understanding of the relative importance of these controls comes from laboratory experiments and numerical modelling, as well as from field data due to the proliferation of high-resolution 3D seismic and bathymetric data, as well as the outcrop and rock record. In this study, based on extensive multibeam and seismic reflection surveys in combination with International Ocean Discovery Program cores from the South China Sea, we document a new mechanism of turbidity current transformation from depositional to erosive resulting in channel incision. We show how confinement by seamounts and bedrock highs of previously unconfined turbidity currents has resulted in the development of seafloor channels. These channels are inferred to be the result of confinement of flows, which have traversed the abyssal plain, leading to flow acceleration allowing them to erode the seafloor substrate. This interpretation is further supported by the coarsening of flow deposits within the area of the seamounts, indicating that confinement has increased flow competency, allowing turbidity currents to carry larger volumes of coarse sediment which has been deposited in this region. This basin-scale depositional pattern suggests that pre-established basin topography can have an important control on sedimentation which can impact characteristics such as potential hydrocarbon storage

Contourite processes associated with the overflow of Pacific Deep Water within the Luzon Trough: Conceptual and regional implications

Overflows through oceanic gateways govern the exchange of water masses in the world's ocean basins. These exchanges also involve energy, salinity, nutrients, and carbon. As such, the physical features that control overflow can exert a strong influence on regional and global climate. Here, we present the first description of sedimentary processes generated by the overflow of Pacific Deep Water (OPDW). This mass flows southward at approximately 2000–3450 m water depth within the Luzon Trough (gateway) from the Pacific Ocean into the South China Sea. OPDW can be divided into: a) a lower, denser layer (including an associated weak counter-current), which has generated a large contourite depositional system (CDS-1) that includes large erosional (channel and moat), depositional (mounded and plastered drift), and mixed (terrace) contourite features along the trough bottom and walls, and b) an upper mixing layer, which has not generated any significant depositional or erosional contourite features. Where OPDW does not reach the seafloor, it is underlain by bottom water that circulates more sluggishly but has generated a second contourite depositional system (CDS-2) made of a large sheet-like drift. The OPDW flow has generally enhanced since the middle to late Miocene, except in the shallower northernmost corridor. In the deeper main trough, reductions in width and depth of the gateway by Taiwan orogenic events have likely accelerated the overflow. The latest significant enhancening may promote widespread development of contourite depositional systems along the South China Sea's lower continental slope and adjacent deeper areas. This work highlights the importance of gateway-confined overflows in controlling the morphology and sedimentary evolution of adjacent deep marine sedimentary systems. A clear understanding of overflow processes and their products is essential for decoding tectonic control in oceanographic or paleoceanographic processes

Significant increase of surface ozone at a rural site, north of eastern China

Abstract. Ozone pollution in eastern China has become one of the top environmental issues. Quantifying the temporal trend of surface ozone helps to assess the impacts of the anthropogenic precursor reductions and the likely effects of emission control strategies implemented. In this paper, ozone data collected at the Shangdianzi (SDZ) regional atmospheric background station from 2003 to 2015 are presented and analyzed to obtain the variation in the trend of surface ozone in the most polluted region of China, north of eastern China or the North China Plain. A modified Kolmogorov–Zurbenko (KZ) filter method was performed on the maximum daily average 8 h (MDA8) concentrations of ozone to separate the contributions of different factors from the variation of surface ozone and remove the influence of meteorological fluctuations on surface ozone. Results reveal that the short-term, seasonal and long-term components of ozone account for 36.4, 57.6 and 2.2 % of the total variance, respectively. The long-term trend indicates that the MDA8 has undergone a significant increase in the period of 2003–2015, with an average rate of 1.13 ± 0.01 ppb year−1 (R2 = 0.92). It is found that meteorological factors did not significantly influence the long-term variation of ozone and the increase may be completely attributed to changes in emissions. Furthermore, there is no significant correlation between the long-term O3 and NO2 trends. This study suggests that emission changes in VOCs might have played a more important role in the observed increase of surface ozone at SDZ. </jats:p

Revisiting Acceptability Judgements

In this work, we revisit linguistic acceptability in the context of large language models. We introduce CoLAC - Corpus of Linguistic Acceptability in Chinese, the first large-scale acceptability dataset for a non-Indo-European language. It is verified by native speakers and is the first acceptability dataset that comes with two sets of labels: a linguist label and a crowd label. Our experiments show that even the largest InstructGPT model performs only at chance level on CoLAC, while ChatGPT's performance (48.30 MCC) is also much below supervised models (59.03 MCC) and human (65.11 MCC). Through cross-lingual transfer experiments and fine-grained linguistic analysis, we provide detailed analysis of the model predictions and demonstrate for the first time that knowledge of linguistic acceptability can be transferred across typologically distinct languages, as well as be traced back to pre-training. Our dataset is publicly available at \url{https://github.com/huhailinguist/CoLAC}

Effects of<i>Angelica</i>Extract on Schwann Cell Proliferation and Expressions of Related Proteins

The present study investigated the effects ofAngelicaextract (AE) on Schwann cell proliferation and expressions of related proteins, including brain derived neurotrophic factor (BDNF), neural cell adhesion molecule (NCAM), and proliferating cell nuclear antigen (PCNA). Proliferation activity and cell cycles of SCs were evaluated by MTT assay and flow cytometry methods, respectively, after 12 h treatment of AE at different concentrations (62.5, 125, 250, 1000, 2000, 4000, and 8000 mg/L). SCs were treated by 500, 1000, and 2000 mg/L AE for 24 h or 48 h; the related genes mRNA and proteins expressions in SCs were detected by quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA) kit. At the concentration range of 125–2000 mg/L, the SC proliferation was induced by AE in a dose-dependent manner, especially 1000 and 2000 mg/L; cells in drug-treated groups showed the most increase.Cells counts were ascended significantly in (G2/M + S) phase compared to control group. BDNF, NCAM, and PCNA protein expressions significantly increased at drug-treated groups. Relative genes mRNA expressions levels were also significantly higher compared to control group. The results indicated that AE facilitated SC proliferation and related genes and proteins expressions, which provided a basic guideline for nerve injury repair in clinic.</jats:p

Deep Learning-Enabled Fully Automated Pipeline System for Segmentation and Classification of Single-Mass Breast Lesions Using Contrast-Enhanced Mammography: A Prospective, Multicentre Study

Background Breast cancer is the leading cause of cancer-related deaths in women. However, accurate diagnosis of breast cancer using medical images heavily relies on the experience of radiologists. This study aimed to develop an artificial intelligence model that diagnosed single-mass breast lesions on contrast-enhanced mammography (CEM) for assisting the diagnostic workflow. Methods A total of 1912 women with single-mass breast lesions on CEM images before biopsy or surgery were included from June 2017 to October 2022 at three centres in China. Samples were divided into training and validation sets, internal testing set, pooled external testing set, and prospective testing set. A fully automated pipeline system (FAPS) using RefineNet and the Xception + Pyramid pooling module (PPM) was developed to perform the segmentation and classification of breast lesions. The performances of six radiologists and adjustments in Breast Imaging Reporting and Data System (BI-RADS) category 4 under the FAPS-assisted strategy were explored in pooled external and prospective testing sets. The segmentation performance was assessed using the Dice similarity coefficient (DSC), and the classification was assessed using heatmaps, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The radiologists’ reading time was recorded for comparison with the FAPS. This trial is registered with China Clinical Trial Registration Centre (ChiCTR2200063444). Findings The FAPS-based segmentation task achieved DSCs of 0.888 ± 0.101, 0.820 ± 0.148 and 0.837 ± 0.132 in the internal, pooled external and prospective testing sets, respectively. For the classification task, the FAPS achieved AUCs of 0.947 (95% confidence interval [CI]: 0.916–0.978), 0.940 (95% [CI]: 0.894–0.987) and 0.891 (95% [CI]: 0.816–0.945). It outperformed radiologists in terms of classification efficiency based on single lesions (6 s vs 3 min). Moreover, the FAPS-assisted strategy improved the performance of radiologists. BI-RADS category 4 in 12.4% and 13.3% of patients was adjusted in two testing sets with the assistance of FAPS, which may play an important guiding role in the selection of clinical management strategies. Interpretation The FAPS based on CEM demonstrated the potential for the segmentation and classification of breast lesions, and had good generalisation ability and clinical applicability. Funding This study was supported by the Taishan Scholar Foundation of Shandong Province of China (tsqn202211378), National Natural Science Foundation of China (82001775), Natural Science Foundation of Shandong Province of China (ZR2021MH120), and Special Fund for Breast Disease Research of Shandong Medical Association (YXH2021ZX055)

Anonymous Online Survey Detection (and Journalist Verification) of Political Violence, Social Unrest, and Human Rights Violations: Results from Bangladesh and Pakistan

Multiple large bodies of scholarship engage with questions directly concerned with political violence, social unrest, and human rights abuses. Yet, efforts to collect data on these variables are fraught with challenges, and many extant empirical findings rely on data (particularly news report based events) suspected of or known to be biased in aggregate. We explore the use of anonymous, online surveying to detect otherwise unobserved activity. We run anonymous, online surveys in Bangladesh and Pakistan in the run up to, during and in the period following recent contentious 2024 elections in both countries and, separately, in the immediate aftermath of Bangladesh’s 2024 Student–People’s Uprising and expulsion of then-Prime Minister Sheikh Hasina. To assess the efficacy of the surveys, we partnered with professional journalists working on both countries to verify the authenticity of reported incidents. Results confirm their effectiveness in uncovering many instances of political violence, social unrest, and human rights abuses otherwise likely to be missed or excluded from major news media reporting and ultimately major datasets derived from it. Yet, they also suggest that anonymous online survey responses and leading event datasets effectively complement, rather than substitute for, one another. Such surveys can be deployed rapidly to communicate with some of the most difficult to reach populations globally about the most sensitive political issues of interest to social scientists and policy professionals

Divergent coupling mechanism of precipitation on plant community multifunction across alpine grassland on the Tibetan Plateau

IntroductionIt is essential to understand plant adaptive strategies on plant stoichiometric traits at the species level rather than at the community level under various environmental conditions across the Tibetan Plateau (TP).MethodsHere, plant community function and edaphic and meteorological factors were collected at 111 sites along an extensive water–heat gradient during the peak growing season in 2015. Community-weighted mean trait (CWM) was introduced to illuminating dynamics of the functional trait at the community level.ResultsOur results indicated that plant functional traits, including CWM-leaf total carbon (CWM_LTC), CWM-leaf total nitrogen (CWM_LTN), and CWM-leaf total phosphorus (CWM_LTP), showed similar and comparatively marked increases from alpine meadow (AM) to alpine steppe (AS). Moreover, since the tightly coordinated variation among each plant functional trait of AM was higher than that of AS, a more stable coupling mechanism of these plant functional traits could be observed in AM under a long-term evolutionary habit. Specifically, there was higher annual mean precipitation (AMP) in AM than that in AS significantly (P &lt; 0.01), and AMP was significantly correlated with soil moisture and soil total phosphorus in AM. Generally, our findings suggest that precipitation determines divergent coupling plant community function in both AS and AM