Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-stage Flows-based Generative Modeling for Traceable Urban Planning

Urban planning, which aims to design feasible land-use configurations for target areas, has become increasingly essential due to the high-speed urbanization process in the modern era. However, the traditional urban planning conducted by human designers can be a complex and onerous task. Thanks to the advancement of deep learning algorithms, researchers have started to develop automated planning techniques. While these models have exhibited promising results, they still grapple with a couple of unresolved limitations: 1) Ignoring the relationship between urban functional zones and configurations and failing to capture the relationship among different functional zones. 2) Less interpretable and stable generation process. To overcome these limitations, we propose a novel generative framework based on normalizing flows, namely Dual-stage Urban Flows (DSUF) framework. Specifically, the first stage is to utilize zone-level urban planning flows to generate urban functional zones based on given surrounding contexts and human guidance. Then we employ an Information Fusion Module to capture the relationship among functional zones and fuse the information of different aspects. The second stage is to use configuration-level urban planning flows to obtain land-use configurations derived from fused information. We design several experiments to indicate that our framework can outperform compared to other generative models for the urban planning task.
Deuterium component of the global molecular hydrogen cycle

The deuterium (D) component of the global molecular hydrogen (H 2 ) cycle is discussed. Field measurements of the fractionation effect during soil uptake of atmospheric H 2 (α soil ) were made using an in situ static flux chamber, and an α soil of 0.943±0.024 (±1σ) was determined. The δD of H 2 emitted during combustion of pine needles and pine branches was experimentally measured at -330±50‰ (versus Vienna SMOW) and was 230±60‰ lower than the δD of the plant matter combusted. This hydrogen isotope fractionation effect yielded an estimate of -290±60‰ for the δD of H 2 emitted during global biomass burning. The 8D of H 2 emitted by fossil fuel combustion in the Seattle, Washington, urban area was -196±10‰. On the basis of a global H 2 budget calculation, a 8D of +130±70‰ is required for the photochemical H 2 source in order for the available isotopic measurements to agree with the global H 2 budget. A possible mechanism for a significant enrichment in the deuterium content of H 2 produced by the photochemical destruction of methane is given. We suggest that the currently available isotopic measurements are not in disagreement with the current view of the global H 2 budget.
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space

Based on the theory of homogeneous spaces we derive geometrically optimal edge attributes to be used within the flexible message-passing framework. We formalize the notion of weight sharing in convolutional networks as the sharing of message functions over point-pairs that should be treated equally. We define equivalence classes of point-pairs that are identical up to a transformation in the group and derive attributes that uniquely identify these classes. Weight sharing is then obtained by conditioning message functions on these attributes. As an application of the theory, we develop an efficient equivariant group convolutional network for processing 3D point clouds. The theory of homogeneous spaces tells us how to do group convolutions with feature maps over the homogeneous space of positions $\mathbb{R}^3$, position and orientations $\mathbb{R}^3 {\times} S^2$, and the group $SE(3)$ itself. Among these, $\mathbb{R}^3 {\times} S^2$ is an optimal choice due to the ability to represent directional information, which $\mathbb{R}^3$ methods cannot, and it significantly enhances computational efficiency compared to indexing features on the full $SE(3)$ group. We support this claim with state-of-the-art results -- in accuracy and speed -- on five different benchmarks in 2D and 3D, including interatomic potential energy prediction, trajectory forecasting in N-body systems, and generating molecules via equivariant diffusion models.
Community Archetypes: An Empirical Framework for Guiding Research Methodologies to Reflect User Experiences of Sense of Virtual Community

Humans need a sense of community (SOC), and social media platforms afford opportunities to address this need by providing users with a sense of virtual community (SOVC). This paper explores SOVC on Reddit and is motivated by two goals: (1) providing researchers with an excellent resource for methodological decisions in studies of Reddit communities; and (2) creating the foundation for a new class of research methods and community support tools that reflect users' experiences of SOVC. To ensure that methods are respectfully and ethically designed in service and accountability to impacted communities, our work takes a qualitative, community-centered approach by engaging with two key stakeholder groups. First, we interviewed 21 researchers to understand how they study"community"on Reddit. Second, we surveyed 12 subreddits to gain insight into user experiences of SOVC. Results show that some research methods can broadly reflect users' SOVC regardless of the topic or type of subreddit. However, user responses also evidenced the existence of five distinct Community Archetypes: Topical Q&A, Learning&Perspective Broadening, Social Support, Content Generation, and Affiliation with an Entity. We offer the Community Archetypes framework to support future work in designing methods that align more closely with user experiences of SOVC and to create community support tools that can meaningfully nourish the human need for SOC/SOVC in our modern world.
Meander dynamics: A reduced‐order nonlinear model without curvature restrictions for flow and bed morphology

Reduced‐order models remain essential tools for meander modeling, especially for processes at large length scales and long time scales, probabilistic simulations, rapid assessments, or when input data are scarce or uncertain. Present reduced‐order meander models consider their dependent variables either as small‐amplitude variations compared to a basic state (linearity) or as varying gradually in a spatial sense (gradual variation). In a prequel, Blanckaert and de Vriend ( ) derived a nonlinear reduced‐order hydrodynamic model without curvature restrictions and showed that linearity or gradual curvature variations assumptions do not hold in strongly curved channels. Moreover, in strongly curved channels, a nonlinear feedback mechanism causes the secondary flow strength to be smaller than its linear mild‐curvature equivalent. In the limit of mild‐amplitude variations and mild curvature, their nonlinear meander flow model simplifies to a well‐known linear formulation. The present paper extends this nonlinear modeling to the bed morphology in strongly curved bends, making use of Exner's sediment conservation principle. Furthermore, the model quantifying the relative influence of the downslope gravitational force is refined by considering nonlinear effects. The coupled nonlinear flow and bed morphology model yields satisfactory results for the bed topography, whereas the corresponding linear model strongly overpredicts the magnitude of the transverse bed slope. Analysis of the forcing mechanisms indicate that this erroneous behavior is caused by an overestimation of the upslope drag force due to the secondary flow.
Reflecting Perfection for Finite Dimensional Differential Graded Algebras

We generalise two facts about finite dimensional algebras to finite dimensional differential graded algebras. The first is the Nakayama Lemma and the second is that the simples can detect finite projective dimension. We prove two dual versions which relate to Gorenstein differential graded algebras and Koszul duality respectively. As an application, we prove a corepresentability result for finite dimensional differential graded algebras.
Attention-based Multi-task Learning for Base Editor Outcome Prediction

Human genetic diseases often arise from point mutations, emphasizing the critical need for precise genome editing techniques. Among these, base editing stands out as it allows targeted alterations at the single nucleotide level. However, its clinical application is hindered by low editing efficiency and unintended mutations, necessitating extensive trial-and-error experimentation in the laboratory. To speed up this process, we present an attention-based two-stage machine learning model that learns to predict the likelihood of all possible editing outcomes for a given genomic target sequence. We further propose a multi-task learning schema to jointly learn multiple base editors (i.e. variants) at once. Our model's predictions consistently demonstrated a strong correlation with the actual experimental results on multiple datasets and base editor variants. These results provide further validation for the models' capacity to enhance and accelerate the process of refining base editing designs.
Modeling the impact of ethanol on the persistence of benzene in gasoline‐contaminated groundwater

The effect of ethanol on the persistence of benzene in gasoline‐contaminated aquifers is simulated using a multicomponent reactive transport model. The conceptual model includes a residual gasoline source which is dissolving at the water table into an aquifer containing a limited amount of dissolved oxygen. The coupled processes include nonaqueous phase liquid (NAPL) source dissolution, transport of the dissolved components, and competitive aerobic biodegradation. Comparisons are made between dissolved benzene plumes from a gasoline spill and those from an otherwise equivalent spill containing 10% ethanol (gasohol). Simulations have shown that under some conditions a 10% ethanol component in gasoline can extend the travel distance of a benzene plume by up to 150% relative to that from an equivalent ethanol‐free gasoline spill. The increase occurs because ethanol preferentially consumes oxygen, which reduces the biodegradation rate of benzene. The impact is limited, however, because sufficient oxygen disperses behind the ethanol plume into the slightly retarded benzene plume. A sensitivity analysis for two common spill scenarios showed that background oxygen concentrations and benzene retardation have the most significant influence on ethanol‐induced benzene persistence. The results are highly relevant in light of the increasing use of ethanol‐enhanced fuels throughout the world and the forthcoming ban of methyl tertiary‐butyl‐ether (MTBE) in California and its probable replacement by ethanol by the end of 2002.
Multi-resolution HuBERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction

Existing Self-Supervised Learning (SSL) models for speech typically process speech signals at a fixed resolution of 20 milliseconds. This approach overlooks the varying informational content present at different resolutions in speech signals. In contrast, this paper aims to incorporate multi-resolution information into speech self-supervised representation learning. We introduce a SSL model that leverages a hierarchical Transformer architecture, complemented by HuBERT-style masked prediction objectives, to process speech at multiple resolutions. Experimental results indicate that the proposed model not only achieves more efficient inference but also exhibits superior or comparable performance to the original HuBERT model over various tasks. Specifically, significant performance improvements over the original HuBERT have been observed in fine-tuning experiments on the LibriSpeech speech recognition benchmark as well as in evaluations using the Speech Universal PERformance Benchmark (SUPERB) and Multilingual SUPERB (ML-SUPERB).
Simulated unsaturated flow processes after wildfire and interactions with slope aspect

A series of virtual experiments were conducted using a one‐dimensional numerical model of unsaturated flow (Hydrus‐1D) to investigate the factors responsible for shifts in subsurface hydrologic response following wildfire. These virtual experiments used a series of well‐characterized experimental plots in the area affected by the 2010 Fourmile Canyon Fire near Boulder, CO, USA, that cover north and south facing slope aspects for plots both affected and unaffected by wildfire. Inverse estimation of soil‐hydraulic parameters allowed establishing “foundation simulations” that served as the basis for virtual experiments to test findings from interpretation of field and laboratory data and extend understanding beyond what could be gleaned from data alone. The numerical model virtual experiments showed that loss of transpiration because of vegetation combustion/mortality caused soils to be wetter at depths greater than 5 cm on both north and south facing slopes, which agrees with field observations. Loss of tree canopy interception contributed to wetter subsurface conditions and loss of litter/duff increased evaporation, drying soils, in the top few cm on north facing slopes. On south facing slopes, at depths shallower than 3 cm, the simulations did not reproduce the observed trends of drier soils after wildfire, which suggests that more robust methods are needed to simulate evaporation and soil‐water retention at soil‐water contents less than 0.05 cm3 cm−3. Simulated bottom boundary flux, a proxy for groundwater recharge, was greater in north facing burned plots by a factor of 3.5–5.2 and greater on south facing plots by a factor of 10.6–12.7, relative to unburned plots.
Parallel trends in organic and inorganic carbon isotopes across the Permian/Triassic boundary

Stable carbon isotope ratios in both inorganic and organic reservoirs have been widely applied to model environmental and sedimentological changes on a global scale. Most studies dealing with major extinction events have used the record of inorganic carbon. In this paper the authors report the relation between shifts in carbon-13 content of organic matter and coexisting carbonate fractions at a major extinction event, the Permian/Triassic boundary. They found that both [delta][sup 13]C[sub carb] and [delta][sup 13]C[sub org] of the surface ocean varied dramatically across the boundary, but the fractionation [Delta][sup 13]C between organic matter and carbonate remained constant. This result appreciably restricts the interpretation of changes in the carbon cycle during this critical interval. The new data are best explained by a combination of two mechanisms for variation in [delta][sup 13]C[sub carb]: (1) burial and erosion of organic carbon, with a long time constant; and (2) sequestration of organic carbon into shallow and deep oceanic reservoirs, with a shorter time constant. For application to their case, the first mechanism is limited by possible buildup of marine pCO[sub 2], which would increase the isotopic fractionation factor. The second mechanism is limited in application to short-term transient variations in [delta][sup 13]C. Modelingmore » of the carbon cycle and its variations of [delta][sup 13]C must take both mechanisms into account. « less
Long term fault slip rates, distributed deformation rates and forecast of seismicity in the Iranian Plateau

In this paper, the long‐term crustal flow of the Iranian Plateau is computed using a kinematic finite‐element model (NeoKinema software). Based on the iterated weighted least squares method, the models are fitted to the newest data set of Iran including updated fault traces, geologic fault offset rates, geodetic benchmark velocities, principal stress directions, and velocity boundary conditions. We are successful to find the best kinematic model, in which geological slip rates, geodetic velocities, and interpolated stress directions are fitted at levels of 0.35, 1.0, and 1.0 datum standard deviation, respectively. The best fitted model, for the first time, provides long‐term fault slip rates, velocity, and anelastic strain rate field in the Iranian Plateau from all available kinematic data. In order to verify the model, the estimates of fault slip rates are compared to slip rates from merely analyzing geodetic benchmark velocities or paleoseismological studies or published geological rates which have not been used in the model. Our estimated rates are all in the range of geodetic rates and are even more consistent with geological rates than previous GPS‐based estimates. Using the selected model, long‐term average seismicity maps and long‐term moment rates are produced on the basis of the SHIFT hypothesis and previous global calibrations. Our kinematic model also provides a new constraint on ratio of seismic deformation to total deformation for different seismic zones of Iran. The resulting slip rates and the proposed seismic fraction of deformation provide the necessary input data for future time‐dependent hazard studies in Iran. Moreover, spatial distribution and total number of strong (M > 6) and major (M > 7) earthquakes, which dominate the seismic hazard, are all compatible with the regional seismic catalog.
Analysis of fault slip inversions: Do they constrain stress or strain rate?

Fault slip data commonly are used to infer the orientations and relative magnitudes of either the principal stresses or the principal strain rates, which are not necessarily parallel or equal. At the local scale of an individual fault, the shear plane and slip direction define the orientations of the local principal strain rate axes but not, in general, the local principal stress axes. At a large scale, the orientations of P and T axes maxima for sets of fault slip data do not provide accurate inversion solutions for either strain rate or stress. The quantitative inversion of such fault slip data, however, provides direct constraints on the orientations and relative magnitudes of the global principal strain rates. To interpret the inversion solution as constraining the global principal stresses requires that (1) the fault slip pattern must have a characteristic symmetry no lower than orthorhombic; (2) the material must be mechanically isotropic; and (3) there must be a linear constitutive relationship between the global stress and the global strain rate. Isotropic linear elastic constitutive equations are appropriate to describe the local deformation surrounding an individual slip discontinuity. Fault slip inversions, however, constrain the characteristics of a large-scale cataclastic flow, which is described by constitutive equations that are probably, but to an unknown degree, anisotropic and nonlinear. Such material behavior would not strictly satisfy the requirements for the stress interpretation. Thus, at the present state of knowledge, fault slip inversion solutions are most reliably interpreted as constraining the principal strain rates.
PD-1 blockade in combination with dasatinib potentiates induction of anti-acute lymphocytic leukemia immunity

Immunotherapy, in the form of hematopoietic stem cell transplantation (HSCT), has been part of the standard of care in the treatment of acute leukemia for over 40 years. Trials evaluating novel immunotherapeutic approaches, such as targeting the programmed death-1 (PD-1) pathway, have unfortunately not yielded comparable results to those seen in solid tumors. Major histocompatibility complex (MHC) proteins are cell surface proteins essential for the adaptive immune system to recognize self versus non-self. MHC typing is used to determine donor compatibility when evaluating patients for HSCT. Recently, loss of MHC class II (MHC II) was shown to be a mechanism of immune escape in patients with acute myeloid leukemia after HSCT. Here we report that treatment with the tyrosine kinase inhibitor, dasatinib, and an anti-PD-1 antibody in preclinical models of Philadelphia chromosome positive B-cell acute lymphoblastic leukemia is highly active. The dasatinib and anti-PD-1 combination reduces tumor burden, is efficacious, and extends survival. Mechanistically, we found that treatment with dasatinib significantly increased MHC II expression on the surface of antigen-presenting cells (APC) in a tumor microenvironment-independent fashion and caused influx of APC cells into the leukemic bone marrow. Finally, the induction of MHC II may potentiate immune memory by impairing leukemic engraftment in mice previously cured with dasatinib, after re-inoculation of leukemia cells. In summary, our data suggests that anti-PD-1 therapy may enhance the killing ability of dasatinib via dasatinib driven APC growth and expansion and upregulation of MHC II expression, leading to antileukemic immune rewiring.
Sediment supply and local scouring at bed sills in high‐gradient streams

This paper presents the results of an experimental study about the pattern of local scouring generated at the toe of bed sills, which are commonly built in steep, gravel bed mountain streams. The aim of this study is to evaluate the effect of upstream sediment supply on the scour depth and shape. The experiments simulated conditions of a steady upstream sediment supply which had the same grain size composition as the sediment deposit placed on the bed of the flume. The geometric characteristics of three scour holes developed under conditions of steady flow discharge and steady upstream sediment supply were measured during 48 different tests. This provided a data set containing measurements of 144 scour holes. Three different sediment feed rates were used, and tests were also performed with clear water conditions. Geometric interference between sills was not observed. A natural river gravel with a limited grain size was used. The collected data were analyzed using nondimensional groups developed in previous clear water studies. It is shown that the imposed sediment transport does not require the introduction of new dimensionless parameters into existing scour depth and length prediction formula. The effects of sediment feed are shown to be incorporated in the existing dimensionless parameters. The new data set was used to recalibrate existing scour depth formula. The influence of jet erosion on scour geometry is also discussed. Inspection of the data indicates a possible two‐stage behavior, with the threshold between behaviors related to the ratio of the value of the morphological jump created at a scour hole and the flow specific energy at the bed sill.
Tree chemistry database (version 1.0)

The Tree Chemistry Database is a relational database of C, N, P, K, Ca, Mg, Mn, and Al concentrations in bole bark, bole wood, branches, twigs, and foliage. Compiled from data in 218 articles and publications, the database contains reported nutrient and biomass values for tree species in the Northeastern United States. Nutrient data can be sorted on parameters such as stand age, sample year, region, and glaciation. This report documents database development and provides instructions for use of the database. Tree Chemistry Database Read Me (36 KB) Tree Chemistry Database v.1 (Access 2000) (2.5 MB) Tree Chemistry Database v.1 (Access 2002) (2.5 MB) Tree Chemistry Database v.1 (Access 97) (2.4 MB)