66 research outputs found

    Reconstructing solar wind inhomogeneous structures from stereoscopic observations in white-light: Small transients along the Sun-Earth line

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    The Heliospheric Imagers (HI) on board the two spacecraft of the Solar Terrestrial Relations Observatory (STEREO) provided white-light images of transients in the solar wind from dual perspectives from 2007 to 2014. In this paper, we develop a new method to identify and locate the transients automatically from simultaneous images from the two inner telescopes, known as HI-1, based on a correlation analysis. Correlation coefficient (cc) maps along the Sun-Earth line are constructed for the period from 1 Jan 2010 to 28 Feb 2011. From the maps, transients propagating along the Sun-Earth line are identified, and a 27-day periodic pattern is revealed, especially for small-scale transients. Such a periodicity in the transient pattern is consistent with the rotation of the Sun's global magnetic structure and the periodic crossing of the streamer structures and slow solar wind across the Sun-Earth line, and this substantiates the reliability of our method and the high degree of association between the small-scale transients of the slow solar wind and the coronal streamers. Besides, it is suggested by the cc map that small-scale transients along the Sun-Earth line are more frequent than large-scale transients by a factor of at least 2, and that they quickly diffused into background solar wind within about 40 Rs in terms of the signal-to-noise ratio of white-light emissions. The method provides a new tool to reconstruct inhomogeneous structures in the heliosphere from multiple perspectives.Comment: 24 pages, 9 figures, to be published on Journal of Geophysical Research - Space Physic

    Ambush from All Sides: Understanding Security Threats in Open-Source Software CI/CD Pipelines

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    The continuous integration and continuous deployment (CI/CD) pipelines are widely adopted on Internet hosting platforms, such as GitHub. With the popularity, the CI/CD pipeline faces various security threats. However, current CI/CD pipelines suffer from malicious code and severe vulnerabilities. Even worse, people have not been fully aware of its attack surfaces and the corresponding impacts. Therefore, in this paper, we conduct a large-scale measurement and a systematic analysis to reveal the attack surfaces of the CI/CD pipeline and quantify their security impacts. Specifically, for the measurement, we collect a data set of 320,000+ CI/CD pipeline-configured GitHub repositories and build an analysis tool to parse the CI/CD pipelines and extract security-critical usages. Besides, current CI/CD ecosystem heavily relies on several core scripts, which may lead to a single point of failure. While the CI/CD pipelines contain sensitive information/operations, making them the attacker's favorite targets. Inspired by the measurement findings, we abstract the threat model and the attack approach toward CI/CD pipelines, followed by a systematic analysis of attack surfaces, attack strategies, and the corresponding impacts. We further launch case studies on five attacks in real-world CI/CD environments to validate the revealed attack surfaces. Finally, we give suggestions on mitigating attacks on CI/CD scripts, including securing CI/CD configurations, securing CI/CD scripts, and improving CI/CD infrastructure

    Ferroptosis: a new mechanism of traditional Chinese medicine for cancer treatment

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    Ferroptosis, distinct from apoptosis, is a novel cellular death pathway characterized by the build-up of lipid peroxidation and reactive oxygen species (ROS) derived from lipids within cells. Recent studies demonstrated the efficacy of ferroptosis inducers in targeting malignant cells, thereby establishing a promising avenue for combating cancer. Traditional Chinese medicine (TCM) has a long history of use and is widely used in cancer treatment. TCM takes a holistic approach, viewing the patient as a system and utilizing herbal formulas to address complex diseases such as cancer. Recent TCM studies have elucidated the molecular mechanisms underlying ferroptosis induction during cancer treatment. These studies have identified numerous plant metabolites and derivatives that target multiple pathways and molecular targets. TCM can induce ferroptosis in tumor cells through various regulatory mechanisms, such as amino acid, iron, and lipid metabolism pathways, which may provide novel therapeutic strategies for apoptosis-resistant cancer treatment. TCM also influence anticancer immunotherapy via ferroptosis. This review comprehensively elucidates the molecular mechanisms underlying ferroptosis, highlights the pivotal regulatory genes involved in orchestrating this process, evaluates the advancements made in TCM research pertaining to ferroptosis, and provides theoretical insights into the induction of ferroptosis in tumors using botanical drugs

    Predictive and prognostic value of preoperative pan-immune-inflammation value in patients with locally advanced rectal cancer

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    This study aimed to investigate the prognostic value of the pan-immune-inflammation value (PIV) in patients with locally advanced rectal cancer (LARC) who received neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision. We retrospectively collected and analyzed the clinicopathological data of 215 resected LARC patients. X-tile software was used to determine the optimal threshold value for PIV in predicting overall survival (OS). The predictive ability of PIV for pathological complete regression (pCR), OS, and disease-free survival (DFS) was evaluated and compared with other inflammation markers. Univariate and multivariate logistic regression analyses for pCR and Cox regression analyses for OS and DFS were conducted. The optimal threshold value for PIV was determined to be 454.7 based on the X-tile software. Patients were then categorized into low (≤ 454.7) and high (> 454.7) PIV groups comprising 153 and 62 patients, respectively. PIV demonstrated superior predictive ability for pCR, OS, and DFS compared to other inflammation markers. LARC patients with low PIV had significantly higher pCR (P = 0.029), OS (P = 0.002), and DFS (P = 0.001) rates compared to those with high PIV. Multivariate regression analysis identified PIV as an independent prognostic factor for pCR (odds ratio = 0.32; 95% confidence interval [CI], 0.10-0.80; P = 0.014), OS (hazard ratio = 3.08; 95% CI, 1.77-5.35; P = 0.001), and DFS (hazard ratio = 2.53; 95% CI, 1.58-4.06; P = 0.002). This study confirmed that preoperative PIV could serve as a useful independent prognostic factor in LARC patients treated with nCRT

    NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research

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    We introduce the Never Ending VIsual-classification Stream (NEVIS'22), a benchmark consisting of a stream of over 100 visual classification tasks, sorted chronologically and extracted from papers sampled uniformly from computer vision proceedings spanning the last three decades. The resulting stream reflects what the research community thought was meaningful at any point in time. Despite being limited to classification, the resulting stream has a rich diversity of tasks from OCR, to texture analysis, crowd counting, scene recognition, and so forth. The diversity is also reflected in the wide range of dataset sizes, spanning over four orders of magnitude. Overall, NEVIS'22 poses an unprecedented challenge for current sequential learning approaches due to the scale and diversity of tasks, yet with a low entry barrier as it is limited to a single modality and each task is a classical supervised learning problem. Moreover, we provide a reference implementation including strong baselines and a simple evaluation protocol to compare methods in terms of their trade-off between accuracy and compute. We hope that NEVIS'22 can be useful to researchers working on continual learning, meta-learning, AutoML and more generally sequential learning, and help these communities join forces towards more robust and efficient models that efficiently adapt to a never ending stream of data. Implementations have been made available at https://github.com/deepmind/dm_nevis
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