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 $g$ with respect to the Weil-Petersson measure on the moduli space $\mathcal{M}_g$. We show that as $g$ goes to infinity, a generic surface $X\in \mathcal{M}_g$ satisfies asymptotically: (1) the separating systole of $X$ is about $2\log g$; (2) there is a half-collar of width about $\frac{\log g}{2}$ around a separating systolic curve of $X$; (3) the length of shortest separating closed multi-geodesics of $X$ is about $2\log g$. 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 $g$ 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 $13$ common text generation tasks and their corresponding $83$ datasets and further incorporates $45$ PLMs covering general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight PLMs. We also implement $4$ efficient training strategies and provide $4$ 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. 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$^{\circ}$. 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 $0.82-$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

HPLC-DAD fingerprints combined with multivariate analysis of Epimedii Folium from major producing areas in Eastern Asia: effect of geographical origin and species

The growth location and plant variety may influence the active components and biological activities of plants used in phytomedicine. In this study, nine sets of different Epimedii Folium, from different representative cultivation locations and Epimedium species, were collected for comparison, using HPLC-DAD combined with multivariate analysis. The objective was to investigate the influence of geographical origin and Epimedium species on the quality of Epimedii Folium, and provide applicable guidance for cultivation and quality control of Epimedii Folium. Several Epimedium spp. sets were used to establish the HPLC-DAD fingerprints and 91 peaks (compounds) were selected for the multivariate analysis. Major compounds were analyzed by HPLC-DAD combined with principal component analysis (PCA). HPLC quantitative analysis of known bioactive compounds was performed. Application of PCA to HPLC data showed that Epimedium samples sharing the same geographical origin or species clustered together, indicating that both species and geographical origin have impacts on the quality of Epimedii Folium. The major bioactive flavonoid compounds, epimedin C, icariin and baohuoside I, were identified and quantified. The concentration of bioactive compounds was significantly influenced both by species and geographical origin. E. sagittatum from Sichuan showed the highest content of bioactive compounds. The results showed that both Epimedium species and geographical origin have strong impact into quality of Epimedii Folium. HPLC data combined with multivariate analysis is a suitable approach to inform the selection of cultivation areas and choose Epimedium spp. most suitable for different geographical areas, resulting in improved quality of Epimedii Folium.This work was supported by Incubation Project on State Key Laboratory of Biological Resources and Ecological Environment of Qinba Areas (SLGPT2019KF04-04), China, and the ERDF through the COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI), Portugal.info:eu-repo/semantics/publishedVersio