44 research outputs found

    Exploring a ferroptosis and oxidative stress-based prognostic model for clear cell renal cell carcinoma

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    BackgroundFerroptosis is a newly defined cell death process triggered by increased iron load and tremendous lipid reactive oxygen species (ROS). Oxidative stress-related ferroptosis is of great important to the occurrence and progression of clear cell renal cell carcinoma (ccRCC), which is particularly susceptibility to ferroptosis agonist. Therefore, exploring the molecular features of ferroptosis and oxidative stress might guide the clinical treatment and prognosis prediction for ccRCC patients.MethodsThe differentially expressed ferroptosis and oxidative stress-associated genes (FPTOSs) between normal renal and ccRCC tissues were identified based on The Cancer Genome Atlas (TCGA) database, and those with prognostic significances were applied to develop a prognostic model and a risk scoring system (FPTOS_score). The clinical parameter, miRNA regulation, tumor mutation burden (TMB), immune cell infiltration, immunotherapy response, and drug susceptibility between two FPTOS-based risk stratifications were determined.ResultsWe have identified 5 prognosis-associated FPTOSs (ACADSB, CDCA3, CHAC1, MYCN, and TFAP2A), and developed a reliable FPTOS_socre system to distinguish patients into low- and high-risk groups. The findings implied that patients from the high-risk group performed poor prognoses, even after stratified analysis of various clinical parameters. A total of 30 miRNA-FPTOS regulatory pairs were recognized to identify the possible molecular mechanisms. Meanwhile, patients from the high-risk group exhibited higher TMB levels than those from the low-risk groups, and the predominant mutated driver genes were VHL, PBRM1 and TTN in both groups. The main infiltrating immune cells of high- and low-risk groups were CD8+ T cells and resting mast cells, respectively, and patients from the high-risk groups showed preferable drug responsiveness to anti-PD-1 immunotherapy. Eventually, potential sensitive drugs (cisplatin, BI-D1870, and docetaxel) and their enrichment pathways were identified to guide the treatment of ccRCC patients with high-risk.ConclusionOur study comprehensively analyzed the expression profiles of FPTOSs and constructed a scoring system with considerable prognostic value, which would supply novel insights into the personalized treatment strategies and prognostic evaluation of ccRCC patient

    ChatFace: Chat-Guided Real Face Editing via Diffusion Latent Space Manipulation

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    Editing real facial images is a crucial task in computer vision with significant demand in various real-world applications. While GAN-based methods have showed potential in manipulating images especially when combined with CLIP, these methods are limited in their ability to reconstruct real images due to challenging GAN inversion capability. Despite the successful image reconstruction achieved by diffusion-based methods, there are still challenges in effectively manipulating fine-gained facial attributes with textual instructions.To address these issues and facilitate convenient manipulation of real facial images, we propose a novel approach that conduct text-driven image editing in the semantic latent space of diffusion model. By aligning the temporal feature of the diffusion model with the semantic condition at generative process, we introduce a stable manipulation strategy, which perform precise zero-shot manipulation effectively. Furthermore, we develop an interactive system named ChatFace, which combines the zero-shot reasoning ability of large language models to perform efficient manipulations in diffusion semantic latent space. This system enables users to perform complex multi-attribute manipulations through dialogue, opening up new possibilities for interactive image editing. Extensive experiments confirmed that our approach outperforms previous methods and enables precise editing of real facial images, making it a promising candidate for real-world applications. Project page: https://dongxuyue.github.io/chatface

    Global Carbon Budget 2023

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    Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based f CO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8 ± 0.4 Gt C yr−1, and SLAND was 3.8 ± 0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023)

    Soundscape in religious historical buildings: a review

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    Abstract Over the past decade, a substantial body of research exploring soundscapes in religious historical buildings has emerged, yet a comprehensive summary of this work is lacking. This paper selects 74 typical studies of soundscapes in religious historical buildings published between 2011 and 2022 to conduct quantitative statistics and visualization analysis from a bibliometric perspective. The selected literature is categorized based on the type of religious building, Christian, Islamic, or Buddhist. The literature is further segmented according to the research subject, including sound field studies, sound analyses, and evaluations of the acoustic environment. The research methods employed are also differentiated and include sound field measurements, acoustic simulations, questionnaires and auralization procedures. The analysis reveals pronounced disparities in research foci depending on the type of religious historical building. For instance, studies on the soundscape in Christian churches tend to focus on objective sound field attributes and frequently employ sound field simulations to analyse the acoustic parameters of diverse church spaces and materials. Conversely, research on the soundscape in Islamic mosques prioritizes speech intelligibility and acoustic comfort, while studies of the soundscape of Buddhist temples gravitate towards the impact of natural and religious sounds on individuals. This paper anticipates the future direction of soundscape research on religious historical buildings. Graphical Abstrac

    Sound field of a traditional Chinese Palace courtyard theatre

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    Chinese Palace theatres mostly adopt a semi-open courtyard layout, where sound field quality is crucial for the performance of Chinese dramas. This study conducted field measurements and a simulation of the Jiayintang Theatre sound field in the Shenyang Imperial Palace to determine the basic parameters of traditional courtyard theatre sound fields. Moreover, the effects of sound source directivity and the spatial elements on the sound field of the theatre were analysed. The results indicate that the acoustic parameters of the Jiayintang Theatre meet the performance requirements of traditional Beijing Operas, as the acoustic conditions are similar to those of modern Beijing Opera theatres with good listening features. Removing the roof and sidewalls reduces the sound intensity and reverberation time in the aisles. Changing the stage position from the current projecting style to the embedded style would result in a 1.6 and 2.6 dB decrease in the sound intensity in mid-frequency in the main hall and aisles, respectively, while the musical clarity (C80) as well as the speech transition index (STI) in the main hall would decrease, which would negatively affect the audience perception of acoustic quality. The pavilion roof primarily serves to support the actors considering acoustics. If the singing direction of the actors changes from the main hall to the aisles, the sound intensity in the main hall would decrease by 1.8 dB, and the STI and C80 values would also significantly decrease

    Using mask R-CNN to rapidly detect the gold foil shedding of stone cultural heritage in images

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    Abstract As immovable stone cultural heritage is kept in the open air, they are more susceptible to damage, and damage detection is very important for the protection and restoration of cultural heritage. This is especially true for gold-overlaid stone cultural heritage, which is usually more complicated than ordinary stone carvings. However, the detection of cultural heritage damages is mainly based on expert visual inspection, which is often subjective, time-consuming, and laborious. This paper uses the Mask R-CNN algorithm to rapidly and accurately detect the gold foil shedding of stone cultural heritage through two-dimensional images. The research data are from the high-precision images of the Dazu Thousand-Hand Bodhisattva Statue (World Heritage, UNESCO) in Chongqing, China. After cleaning and augmentation, 1900 images are input into Mask R-CNN model for training. Finally, the average precision value (AP) for detecting gold foil shedding is found to be 0.967. In order to test the performance of the model, the new images that do not participate in the training period are used, and it is found that the model can still accurately detect the gold foil shedding even if there are interference factors. This is the first attempt to detect the damages of gold-overlaid stone cultural heritage based on a deep learning algorithm, and it has achieved good results

    Multi-zone coupling productivity of horizontal well fracturing with complex fracture networks in shale gas reservoirs

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    In this paper, a series of specific studies were carried out to investigate the complex form of fracture networks and figure out the multi-scale flowing laws of nano/micro pores–complex fracture networks–wellbore during the development of shale reservoirs by means of horizontal well fracturing. First, hydraulic fractures were induced by means of Brazilian splitting tests. Second, the forms of the hydraulic fractures inside the rock samples were observed by means of X-ray CT scanning to measure the opening of hydraulic fractures. Third, based on the multi-scale unified flowing model, morphological description of fractures and gas flowing mechanism in the matrix–complex fracture network–wellbore, the productivity equation of single-stage horizontal well fracturing which includes diffusion, slipping and desorption was established. And fourthly, a productivity prediction model of horizontal well multi-stage fracturing in the shale reservoir was established considering the interference between the multi-stage fracturing zones and the pressure drop in the horizontal wellbore. The following results were obtained. First, hydraulic fractures are in the form of a complex network. Second, the measured opening of hydraulic fractures is in the range of 4.25–453 μm, averaging 112 μm. Third, shale gas flowing in different shapes of fracture networks follows different nonlinear flowing laws. Forth, as the fracture density in the strongly stimulated zones rises and the distribution range of the hydraulic fractures in strongly/weakly stimulated zones enlarges, gas production increases gradually. As the interference occurs in the flowing zones of fracture networks between fractured sections, the increasing amplitude of gas production rates decreases. Fifth, when the length of a simulated horizontal well is 1500 m and the half length of a fracture network in the strongly stimulated zone is 100 m, the productivity effect of stage 10 fracturing is the best. Therefore, it is necessary to control fracturing degree reasonably and optimize fracturing parameters, so as to provide a theoretical support for the optimization design of shale gas reservoir fracturing. Keywords: Shale gas, Reservoir, Fracturing, Horizontal well, Complex fracture network, Multi-zone coupling, Multi-scale, Interference, Productivity capacit

    An Efficiently Decoupled Implicit Method for Complex Natural Gas Pipeline Network Simulation

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    The simulation of a natural gas pipeline network allows us to predict the behavior of a gas network system under different conditions. Such predictions can be effectively used to guide decisions regarding the design and operation of the real system. The simulation is generally associated with a high computational cost since the pipeline network is becoming more and more complex, as well as large-scale. In our previous study, the Decoupled Implicit Method for Efficient Network Simulation (DIMENS) method was proposed based on the ‘Divide-and-Conquer Approach’ ideal, and its computational speed was obviously high. However, only continuity/momentum Equations of the simple pipeline network composed of pipelines were studied in our previous work. In this paper, the DIMENS method is extended to the continuity/momentum and energy Equations coupled with the complex pipeline network, which includes pipelines and non-pipeline components. The extended DIMENS method can be used to solve more complex engineering problems than before. To extend the DIMENS method, two key issues are addressed in this paper. One is that the non-pipeline components are appropriately solved as the multi-component interconnection nodes; the other is that the procedures of solving the energy Equation are designed based on the gas flow direction in the pipeline. To validate the accuracy and efficiency of the present method, an example of a complex pipeline network is provided. From the result, it can be concluded that the accuracy of the proposed method is equivalent to that of the Stoner Pipeline Simulator (SPS), which includes commercially available simulation core codes, while the efficiency of the present method is over two times higher than that of the SPS

    Decreased Anthropogenic CO<sub>2</sub> Emissions during the COVID-19 Pandemic Estimated from FTS and MAX-DOAS Measurements at Urban Beijing

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    The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing
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