48 research outputs found
Large genus asymptotics for lengths of separating closed geodesics on random surfaces
In this paper, we investigate basic geometric quantities of a random
hyperbolic surface of genus with respect to the Weil-Petersson measure on
the moduli space . We show that as goes to infinity, a
generic surface satisfies asymptotically: (1) the
separating systole of is about ; (2) there is a half-collar of
width about around a separating systolic curve of ; (3)
the length of shortest separating closed multi-geodesics of is about . As applications, we also discuss the asymptotic behavior of the extremal
separating systole, the non-simple systole and the expectation value of lengths
of shortest separating closed multi-geodesics as goes to infinity.Comment: 64 pages, 10 figure
The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing
We present a unified probabilistic formulation for diffusion-based image
editing, where a latent variable is edited in a task-specific manner and
generally deviates from the corresponding marginal distribution induced by the
original stochastic or ordinary differential equation (SDE or ODE). Instead, it
defines a corresponding SDE or ODE for editing. In the formulation, we prove
that the Kullback-Leibler divergence between the marginal distributions of the
two SDEs gradually decreases while that for the ODEs remains as the time
approaches zero, which shows the promise of SDE in image editing. Inspired by
it, we provide the SDE counterparts for widely used ODE baselines in various
tasks including inpainting and image-to-image translation, where SDE shows a
consistent and substantial improvement. Moreover, we propose SDE-Drag -- a
simple yet effective method built upon the SDE formulation for point-based
content dragging. We build a challenging benchmark (termed DragBench) with
open-set natural, art, and AI-generated images for evaluation. A user study on
DragBench indicates that SDE-Drag significantly outperforms our ODE baseline,
existing diffusion-based methods, and the renowned DragGAN. Our results
demonstrate the superiority and versatility of SDE in image editing and push
the boundary of diffusion-based editing methods
TextBox 2.0: A Text Generation Library with Pre-trained Language Models
To facilitate research on text generation, this paper presents a
comprehensive and unified library, TextBox 2.0, focusing on the use of
pre-trained language models (PLMs). To be comprehensive, our library covers
common text generation tasks and their corresponding datasets and
further incorporates PLMs covering general, translation, Chinese,
dialogue, controllable, distilled, prompting, and lightweight PLMs. We also
implement efficient training strategies and provide generation
objectives for pre-training new PLMs from scratch. To be unified, we design the
interfaces to support the entire research pipeline (from data loading to
training and evaluation), ensuring that each step can be fulfilled in a unified
way. Despite the rich functionality, it is easy to use our library, either
through the friendly Python API or command line. To validate the effectiveness
of our library, we conduct extensive experiments and exemplify four types of
research scenarios. The project is released at the link:
https://github.com/RUCAIBox/TextBox.Comment: Accepted by EMNLP 202
High-field immiscibility of electrons belonging to adjacent twinned bismuth crystals
Bulk bismuth has a complex Landau spectrum. The small effective masses and the large g-factors are anisotropic. The chemical potential drifts at high magnetic fields. Moreover, twin boundaries further complexify the interpretation of the data by producing extra anomalies in the extreme quantum limit. Here, we present a study of angle dependence of magnetoresistance up to 65 T in bismuth complemented with Nernst, ultrasound, and magneto-optic data. All observed anomalies can be explained in a single-particle picture of a sample consisting of two twinned crystals tilted by 108° and with two adjacent crystals keeping their own chemical potentials despite a shift between chemical potentials as large as 68 meV at 65 T. This implies an energy barrier between adjacent twinned crystals reminiscent of a metal- semiconductor Schottky barrier or a p-n junction. We argue that this barrier is built by accumulating charge carriers of opposite signs across a twin boundary
High-field immiscibility of electrons belonging to adjacent twinned bismuth crystals
Bulk bismuth has a complex Landau spectrum. The small effective masses and
the large g-factors are anisotropic. Moreover, at a high magnetic field, when
only the lowest Landau levels remain occupied, the chemical potential does not
stay constant. An added complexity arises from the existence of twin
boundaries, which, by producing extra anomalies, further complexify the
interpretation of the data in the extreme quantum limit. Here, we present an
extensive study of low-temperature angle-dependence of magnetoresistance up to
65 T together with measurements of Nernst effect, ultrasound, and
magneto-optics in bismuth. We found that all observed anomalies can be
explained in a single-particle picture of a sample consisting of two twinned
crystals tilted by 108. We show that a quantitative agreement between
theory and experiment can be achieved only if one assumes that the two adjacent
twinned crystals keep their own chemical potentials at a high magnetic field,
despite a shift between chemical potentials as large as 68 meV at 65 T. This
implies the existence of an energy barrier between adjacent twinned crystals
reminiscent of a Schottky barrier between a metal and a semiconductor. We argue
that this barrier is built by accumulating charge carriers of opposite signs
across a twin boundary.Comment: 11 pages, 7 figure
Life cycle and techno-economic assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia
Biofuels from hydrothermal liquefaction (HTL) of abundantly available forest residues in British Columbia (BC) can potentially make great contributions to reduce the greenhouse gas (GHG) emissions from the transportation sector. Life cycle and techno-economic assessment are conducted to evaluate the environmental and economic performance of a hypothetic 100 million liters per year (MLPY) HTL biofuel system in the Coast Region of BC based on three different supply chain designs.
The life cycle GHG emission of HTL biofuels ranges from 17.0-20.5 g CO₂-eq/MJ, corresponding to 78%-82% reduction compared with petroleum fuels. A further reduction of 6.8 g CO₂-eq/MJ can be achieved when by-product biochar is applied for soil amendment. The conversion stage dominates the total GHG emissions, making up more than 50%. The process emitting most GHGs over the life cycle of HTL biofuels is HTL buffer production. Transportation emissions can be lowered by 83% if forest residues are converted to bio-oil before transportation. Process performance parameters (e.g., HTL energy requirement and biofuel yield) and the location specific parameter (e.g., electricity mix) have significant influence on the GHG emissions of HTL biofuels.
The economic analysis shows that the minimum selling price (MSP) of HTL biofuels ranges from 0.90 per liter of gasoline equivalent, which is about 63%-80% higher than that of petroleum fuels. Converting forest residues to bio-oil and wood pellets before transportation can significantly lower the variable operating cost but not the MSP of HTL biofuels, due to the considerable increase in capital investment. Bio-oil and biofuel yield can significantly influence the MSP of HTL biofuels. Therefore, technology advancement is needed to bring down the production cost of HTL biofuels, otherwise, a high carbon tax can be applied to make HTL biofuels competitive with petroleum fuels.Applied Science, Faculty ofChemical and Biological Engineering, Department ofGraduat
Life-cycle assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia
Background:
Biofuels from hydrothermal liquefaction (HTL) of abundantly available forest residues in British Columbia (BC) can potentially make great contributions to reduce the greenhouse gas (GHG) emissions from the transportation sector. A life-cycle assessment was conducted to quantify the GHG emissions of a hypothetic 100 million liters per year HTL biofuel system in the Coast Region of BC. Three scenarios were defined and investigated, namely, supply of bulky forest residues for conversion in a central integrated refinery (Fr-CIR), HTL of forest residues to bio-oil in distributed biorefineries and subsequent upgrading in a central oil refinery (Bo-DBR), and densification of forest residues in distributed pellet plants and conversion in a central integrated refinery (Wp-CIR).
Results:
The life-cycle GHG emissions of HTL biofuels is 20.5, 17.0, and 19.5 g CO2-eq/MJ for Fr-CIR, Bo-DBR, and Wp-CIR scenarios, respectively, corresponding to 78–82% reduction compared with petroleum fuels. The conversion stage dominates the total GHG emissions, making up more than 50%. The process emitting most GHGs over the life cycle of HTL biofuels is HTL buffer production. Transportation emission, accounting for 25% of Fr-CIR, can be lowered by 83% if forest residues are converted to bio-oil before transportation. When the credit from biochar applied for soil amendment is considered, a further reduction of 6.8 g CO2-eq/MJ can be achieved.
Conclusions:
Converting forest residues to bio-oil and wood pellets before transportation can significantly lower the transportation emission and contribute to a considerable reduction of the life-cycle GHG emissions. Process performance parameters (e.g., HTL energy requirement and biofuel yield) and the location specific parameter (e.g., electricity mix) have significant influence on the GHG emissions of HTL biofuels. Besides, the recycling of the HTL buffer needs to be investigated to further improve the environmental performance of HTL biofuels.Applied Science, Faculty ofOther UBCChemical and Biological Engineering, Department ofReviewedFacult
Resident risk attitude analysis in the decision-making management of waste incineration construction
Environmental pollutants generated by waste incineration plants, such as heavy metals and dioxin, make sur-rounding residents very sensitive to the construction of such facilities. This sensitivity and anxiety of residents may induce group events, which further leads to the emergence of social risks. Based on risk perception theory, a total of 320 questionnaires was designed and handed out to residents neighboring to Jiangqiao Waste Inciner-ation Plant in Shanghai, China to detect the factors affecting risk attitude toward such plants. Using ordered logit model, it is found that there are four decisive factors including impact on health, information cognitive, objective characteristics, and the attitude of the neighbors. These factors have different influence on resident risk attitudes, in which the attitude of the neighbors is of most significance, followed by the economic-geography characteristics of residents, the information cognitive has minimal impact
luxS contributes to intramacrophage survival of Streptococcus agalactiae by positively affecting the expression of fruRKI operon
Abstract The LuxS quorum sensing system is a widespread system employed by many bacteria for cell-to-cell communication. The luxS gene has been demonstrated to play a crucial role in intramacrophage survival of piscine Streptococcus agalactiae, but the underlying mechanism remains largely unknown. In this study, transcriptome analysis, followed by the luxS gene deletion and subsequent functional studies, confirmed that impaired bacterial survival inside macrophages due to the inactivation of luxS was associated with reduced transcription of the fruRKI operon, encoding the fructose-specific phosphotransferase system. Further, luxS was determined not to enhance the transcription of fruRKI operon by binding its promoter, but to upregulate the expression of this operon via affecting the binding ability of catabolite control protein A (CcpA) to the catabolite responsive element (cre) in the promoter of fruRKI. Collectively, our study identifies a novel and previously unappreciated role for luxS in bacterial intracellular survival, which may give a more thorough understanding of the immune evasion mechanism in S. agalactiae
Advances in solar forecasting: Computer vision with deep learning
Renewable energy forecasting is crucial for integrating variable energy sources into the grid. It allows power systems to address the intermittency of the energy supply at different spatiotemporal scales. To anticipate the future impact of cloud displacements on the energy generated by solar facilities, conventional modeling methods rely on numerical weather prediction or physical models, which have difficulties in assimilating cloud information and learning systematic biases. Augmenting computer vision with machine learning overcomes some of these limitations by fusing real-time cloud cover observations with surface measurements acquired from multiple sources. This Review summarizes recent progress in solar forecasting from multisensor Earth observations with a focus on deep learning, which provides the necessary theoretical framework to develop architectures capable of extracting relevant information from data generated by ground-level sky cameras, satellites, weather stations, and sensor networks. Overall, machine learning has the potential to significantly improve the accuracy and robustness of solar energy meteorology; however, more research is necessary to realize this potential and address its limitations