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We study smooth toroidal compactifications of Siegel varieties thoroughly from the viewpoints of Hodge theory and K?hler-Einstein metric. We observe that any cusp of a Siegel space can be identified as a set of certain weight one ...
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We study smooth toroidal compactifications of Siegel varieties thoroughly from the viewpoints of Hodge theory and K?hler-Einstein metric. We observe that any cusp of a Siegel space can be identified as a set of certain weight one polarized mixed Hodge structures. We then study the infinity boundary divisors of toroidal compactifications, and obtain a global volume form formula of an arbitrary smooth Siegel variety A_(g,Γ)(g >1) with a smooth toroidal compactification A_(g,Γ) such that D∞:= A_(g,Γ) \A_(g,Γ) is normal crossing. We use this volume form formula to show that the unique group-invariant K?hler-Einstein metric on A_(g,Γ) endows some restraint combinatorial conditions for all smooth toroidal compactifications of A_(g,Γ). Again using the volume form formula, we study the asymptotic behavior of logarithmical canonical line bundle on any smooth toroidal compactification of A_(g,Γ) carefully and we obtain that the logarithmical canonical bundle degenerate sharply even though it is big and numerically effective.
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This paper takes the garden road system as the research object and proposes a method of generating paths for classical gardens based on parametric design. Firstly, by studying the distribution characteristics of roads, the data on...
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This paper takes the garden road system as the research object and proposes a method of generating paths for classical gardens based on parametric design. Firstly, by studying the distribution characteristics of roads, the data on the curvature, angle, and view area of roads were collected. Secondly, the obtained data were transferred to the parameterized platform, and a method of intelligent generation was used for calculation. Finally, the road system was optimized by the genetic algorithm for better application in modern landscape design. According to the current situation, the road system plan generated by the algorithm inherits the characteristics of classical garden roads. This method can be applied to the courtyard, the community park, the urban park, and other objects. This research not only identifies the characteristics of landscape cultural heritage, but also produces an innovative, intelligent design tool. It provides new methods for the parameterized inheritance and application of traditional landscape heritage.
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Recombinant human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) monoclonal antibody JS016 showed neutralizing and therapeutic effects in preclinical studies. The clinical efficacy and safety of the therapy needed to...
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Recombinant human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) monoclonal antibody JS016 showed neutralizing and therapeutic effects in preclinical studies. The clinical efficacy and safety of the therapy needed to be evaluated. In this phase 2/3, multicenter, randomized, open-label, controlled trial, hospitalized patients with moderate or severe coronavirus disease 2019 (COVID-19) were randomly assigned in a 1:1 ratio to receive standard care or standard care plus a single intravenous infusion of JS016. The primary outcome was a six-level ordinal scale of clinical status on day 28 since randomization. Secondary outcomes include adverse events, 28-day mortality, ventilator-free days within 28 days, length of hospital stay, and negative conversion rate of SARS-CoV-2 nucleic acid on day 14. A total of 199 patients were randomized, and 197 (99 in the JS016 group and 98 in the control group) were analyzed. Most patients, 95 (96%) in the JS016 group and 97 (99%) in the control group were in the best category on day 28 since randomization. The odds ratio of being in a better clinical status was 0.31 (95% confidence interval [Cl], 0.03 to 3.19; P = 0.33). Few adverse events occurred in both groups (3% in the JS016 group and 1% in the control group, respectively; P = 0.34). SARS-CoV-2 neutralizing antibody JS016 did not show clinical efficacy among hospitalized Chinese patients with moderate to severe COVID-19 disease. Further studies are needed to assess the efficacy of the neutralizing antibody to prevent disease deterioration and its benefits among groups of patients specified by disease course and severity. (This study has been registered at ClinicalTrials.gov under identifier NCT04931238.)
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A bstract Among the allowed representations of extended supersymmetry in six dimensions there are exotic chiral multiplets that, instead of a graviton, contain mixed-symmetry spin-2 tensor fields. Notably, an N \documentclass[12pt...
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A bstract Among the allowed representations of extended supersymmetry in six dimensions there are exotic chiral multiplets that, instead of a graviton, contain mixed-symmetry spin-2 tensor fields. Notably, an N \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathcal{N} $$\end{document} = (4 , 0) multiplet has a four index exotic graviton and it was conjectured that an interacting theory based on this multiplet could arise as a strong coupling limit of M theory compactified on T ~(6). We present an algebraic study of these multiplets and their possible embedding into the framework of exceptional field theory, finding in particular that the six-dimensional momenta do not correspond to a conventional space-time section. When compactified on a circle, the six-dimensional multiplets give rise to the same degrees of freedom as five-dimensional supergravity theories with the same number of supersymmetries. However, by considering anomalies (computed using the product multiplets construction) and the generation of Chern-Simons couplings, we find reason to doubt that their dynamics will agree with the five-dimensional gravity theories. We propose an alternative picture, similar to F-theory, in which particular fixed-volume T ~(3)-fibered space-times play a central role, suggesting that only on compactification to three-dimensions will one make contact with the dynamics of supergravity.
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Automated Driving Systems (ADS) have made great achievements in recent years thanks to the efforts from both academia and industry. A typical ADS is composed of multiple modules, including sensing, perception, planning, and contro...
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Automated Driving Systems (ADS) have made great achievements in recent years thanks to the efforts from both academia and industry. A typical ADS is composed of multiple modules, including sensing, perception, planning, and control, which brings together the latest advances in different domains. Despite these achievements, safety assurance of ADS is of great significance, since unsafe behavior of ADS can bring catastrophic consequences. Testing has been recognized as an important system validation approach that aims to expose unsafe system behavior; however, in the context of ADS, it is extremely challenging to devise effective testing techniques, due to the high complexity and multidisciplinarity of the systems. There has been great much literature that focuses on the testing of ADS, and a number of surveys have also emerged to summarize the technical advances. Most of the surveys focus on the system-level testing performed within software simulators, and they thereby ignore the distinct features of different modules. In this article, we provide a comprehensive survey on the existing ADS testing literature, which takes into account both module-level and system-level testing. Specifically, we make the following contributions:(1) We survey the module-level testing techniques for ADS and highlight the technical differences affected by the features of different modules; (2) we also survey the system-level testing techniques, with focuses on the empirical studies that summarize the issues occurring in system development or deployment, the problems due to the collaborations between different modules, and the gap between ADS testing in simulators and the real world; and (3) we identify the challenges and opportunities in ADS testing, which pave the path to the future research in this field.
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Nanotechnology is having a tremendous impact on our society. However, societal concerns about human safety under nanoparticle exposure may derail the broad application of this promising technology. Nanoparticles may enter the huma...
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Nanotechnology is having a tremendous impact on our society. However, societal concerns about human safety under nanoparticle exposure may derail the broad application of this promising technology. Nanoparticles may enter the human body via various routes, including respiratory pathways, the digestive tract, skin contact, intravenous injection, and implantation. After absorption, nanoparticles are carried to distal organs by the bloodstream and the lymphatic system. During this process, they interact with biological molecules and perturb physiological systems. Although some ingested or absorbed nanoparticles are eliminated, others remain in the body for a long time. The human body is composed of multiple systems that work together to maintain physiological homeostasis. The unexpected invasion of these systems by nanoparticles disturbs normal cell signaling, impairs cell and organ functions, and may even cause pathological disorders. This review examines the comprehensive health risks of exposure to nanoparticles by discussing how nanoparticles perturb various physiological systems as revealed by animal studies. The potential toxicity of nanoparticles to each physiological system and the implications of disrupting the balance among systems are emphasized.
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Buildings inevitably absorb solar (thermal) radiation through the envelope, i.e., window, roof and wall, whose characteristics, in terms of material, thickness, area etc., affects the performance of space cooling, thereby inducing...
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Buildings inevitably absorb solar (thermal) radiation through the envelope, i.e., window, roof and wall, whose characteristics, in terms of material, thickness, area etc., affects the performance of space cooling, thereby inducing energy wastage by air-conditioning system to maintain satisfied indoor thermal comfort. Metropolises with congested-built architectures and humid climates consume tremendous energy in space cooling, contributing to massive carbon emissions. Space cooling has been the most soaring electricity end-user and its increasing carbon emission amplifies global warming, which in turn increases occupants' dependence on artificial cooling, especially in hot climates. The urgency of the climate crisis has put passive cooling technologies, which can efficiently manage heat transfer of buildings, to the forefront of research. Thermochromic smart windows, daytime radiative coolers and reflective paints are three prominent technologies that have drawn industries' attention. These technologies respond to incident sunlight and thermal radiation differently, compared to conventional building envelope, and can passively mitigate solar radiation absorbed at the building envelope, reducing electricity consumption for air-conditioning. This review article comprehensively discusses the characteristics of the three passive energy-efficient techniques that can be integrated with building facade (window, roof and wall), and their feasibility in building cooling applications through thermal analyses. Through this review, the ideal spectral properties of these technologies will be distinguished. Although the properties of these technologies have been abundantly explored, the research on their long-term cooling performance under the influence of weatherability and aging remains scarce. Further, their cost-effectiveness is essential for realizing commercialization and reducing hesitancy in adopting these novel passive cooling technologies for taking a significant leap towards carbon neutrality.
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We consider the problem of online prediction in a marginally stable linear dynamical system subject to bounded adversarial or (non-isotropic) stochastic perturbations. This poses two challenges. Firstly, the system is in general u...
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We consider the problem of online prediction in a marginally stable linear dynamical system subject to bounded adversarial or (non-isotropic) stochastic perturbations. This poses two challenges. Firstly, the system is in general unidentifiable, so recent and classical results on parameter recovery do not apply. Secondly, because we allow the system to be marginally stable, the state can grow polynomially with time; this causes standard regret bounds in online convex optimization to be vacuous. In spite of these challenges, we show that the online least-squares algorithm achieves sublinear regret (improvable to polylogarithmic in the stochastic setting), with polynomial dependence on the system’s parameters. This requires a refined regret analysis, including a structural lemma showing the current state of the system to be a small linear combination of past states, even if the state grows polynomially. By applying our techniques to learning an autoregressive filter, we also achieve logarithmic regret in the partially observed setting under Gaussian noise, with polynomial dependence on the memory of the associated Kalman filter.
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Oil processing industry has long been a pillar industry. How to utilise the precious petroleum resource, to re-recognise and re-match resources, catalysts, and processes, and achieve maximum resource value at minimum costs in a gr...
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Oil processing industry has long been a pillar industry. How to utilise the precious petroleum resource, to re-recognise and re-match resources, catalysts, and processes, and achieve maximum resource value at minimum costs in a green, efficient, and highly selective manner, have been a critical topic. Based on above mentioned points, 'molecular engineering and management for petroleum' has attracted more and more attention from industrial and academic community. The molecular engineering and management should be framework of many key techniques, which include the following aspects: 1) the molecular level characterisation of petroleum and its fractions; 2) informational description of oil molecule information; 3) the correlation between oil molecule information and reactivity and the establishment of molecular dynamics model; 4) simulation and optimisation to maximise the value of oil resources and assets. Meanwhile, the molecular engineering and management should focus on the simulation and computing techniques, such as molecular type homologous series matrix (MTHS), Monte Carlo, lumping and refactoring of entropy maximum (REM), et al. Many examples of the application in research and production and operations management were also introduced in this paper. [Received: March 16, 2019; Accepted: September 29, 2019].
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Abstract Polymerase chain reaction (PCR)‐based nucleic acid testing has played a critical role in disease diagnostics, pathogen surveillance, and many more. However, this method requires a long turnaround time, expensive equipmen...
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Abstract Polymerase chain reaction (PCR)‐based nucleic acid testing has played a critical role in disease diagnostics, pathogen surveillance, and many more. However, this method requires a long turnaround time, expensive equipment, and trained personnel, limiting its widespread availability and diagnostic capacity. On the other hand, the clustered regularly interspaced short palindromic repeats (CRISPR) technology has recently demonstrated capability for nucleic acid detection with high sensitivity and specificity. CRISPR‐mediated biosensing holds great promise for revolutionizing nucleic acid testing procedures and developing point‐of‐care diagnostics. This review focuses on recent developments in both fundamental CRISPR biochemistry and CRISPR‐based nucleic acid detection techniques. Four ongoing research hotspots in molecular diagnostics‐target preamplification‐free detection, microRNA (miRNA) testing, non‐nucleic‐acid detection, and SARS‐CoV‐2 detection‐are also covered.
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