Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel vorticity formulation for calculating lift and drag on bluff bodies in a free stream

A parallel vorticity code is developed to study flows over bluff bodies in a free stream. The vorticity method has certain advantages over primitive variable methods for incompressible flows including a reduced equation set through the elimination of the pressure variable. However, because pressure is eliminated, the calculation of aerodynamic coefficients such as lift and drag must be performed in postprocessing. In the current research, an efficient method for recovering the pressure field locally on a body in a free stream is developed, In order to analyze large wake regions, a parallel implementation of the vorticity code is developed. The vorticity code is based on a three-step algorithm. The first step involves determining vortex sheet strengths on the surface of the body which yields Neumann boundary conditions for the vorticity equation, The second step involves determining the interior velocity field using the generalized Helmholtz de- composition representing the flow kinematics. The third step involves solv- ing the vorticity equation, Each step requires a separate parallel strategy. The parallel efficiency of the overall algorithm is evaluated by considering the benchmark problem of flow over a cylinder.
TP-FRL: An Efficient and Adaptive Trajectory Prediction Method Based on the Rule and Learning-Based Frameworks Fusion

Effective trajectory prediction is of great significance for the design of intelligent driving systems. To overcome the problems of low algorithm efficiency and insufficient scenario adaptation in urban environments, this article proposes a trajectory prediction framework based on the rule and learning-based frameworks fusion (TP-FRL). By augmenting the observed trajectory under the guidance of a physically possible trajectory set, the proposed framework improves algorithmic adaptation in the presence of disturbed trajectory observations. Meanwhile, rule-based spatio-temporal semantic corridors are used to vectorize agent trajectory-related regions, which improves the rationality of each agent region division and enhances the adaptability in different scenarios. Finally, based on the trajectory-related region modeling of each agent, the interest region of the central agent is learned by a graph convolutional network, and only the scenario elements in the interest region are encoded to improve the trajectory prediction efficiency of the transformer multi-head attention network. Traffic data from Argoverse and ApolloScape datasets are used to evaluate the performance of the TP-FRL model. Specifically, the TP-FRL model shows efficient performance and strong adaptability on datasets from two countries, which shows the promise of predicting trajectories under various scenarios.
Three-dimensional instabilities in the boundary-layer flow over a long rectangular plate

A detailed numerical study of the separating and reattaching flow over a square leading-edge plate is presented, examining the instability modes governing transition from two- to three-dimensional flow. Under the influence of background noise, experiments show that the transition scenario typically is incompletely described by either global stability analysis or the transient growth of dominant optimal perturbation modes. Instead two-dimensional transition effectively can be triggered by the convective Kelvin–Helmholtz (KH) shear-layer instability; although it may be possible that this could be described alternatively in terms of higher-order optimal perturbation modes. At least in some experiments, observed transition occurs by either: (i) KH vortices shedding downstream directly and then almost immediately undergoing three-dimensional transition or (ii) at higher Reynolds numbers, larger vortical structures are shed that are also three-dimensionally unstable. These two paths lead to distinctly different three-dimensional arrangements of vortical flow structures. This paper focuses on the mechanisms underlying these three-dimensional transitions. Floquet analysis of weakly periodically forced flow, mimicking the observed two-dimensional quasi-periodic base flow, indicates that the two-dimensional vortex rollers shed from the recirculation region become globally three-dimensionally unstable at a Reynolds number of approximately 380. This transition Reynolds number and the predicted wavelength and flow symmetries match well with those of the experiments. The instability appears to be elliptical in nature with the perturbation field mainly restricted to the cores of the shed rollers and showing the spatial vorticity distribution expected for that instability type. Indeed an estimate of the theoretical predicted wavelength is also a good match to the prediction from Floquet analysis and theoretical estimates indicate the growth rate is positive. Fully three-dimensional simulations are also undertaken to explore the nonlinear development of the three-dimensional instability. These show the development of the characteristic upright hairpins observed in the experimental dye visualisations. The three-dimensional instability that manifests at lower Reynolds numbers is shown to be consistent with an elliptic instability of the KH shear-layer vortices in both symmetry and spanwise wavelength.
Understanding barriers to adoption of sustainable nitrogen management practices in California

Achieving sustainability in agricultural nitrogen (N) management relies on farmers’ decisions to reduce fertilizer inputs and adopt conservation management practices. Understanding the drivers and barriers to farmers’ adoption of improved N management practices is critical to developing effective management and policy approaches on this intractable challenge. Existing research on farmer behavior has assumed that any barrier to adoption will result in lower practice adoption rates, without fully understanding how barriers may vary across different management practices, farm and farmer types, and stages of adoption. By leveraging two farmer survey data sets (total n > 1,900), this study diagnoses key barriers to adoption across 11 different N management practices and a large diversity of farmer and farm types across the California Central Valley. We find resource constraints, technical knowledge, and uncertainty emerge as key barrier types that differentially affect farmers at various stages of adoption. On a practice-by-practice basis, uncertainty barriers appear greatest for nonadopters of a practice, whereas practice adopters are more likely to report resource barriers. Across management practices at the farm level, farmers with higher self-reported conservation orientations are more likely to report being affected by all barrier types, as compared to their peers with lower self-reported conservation orientations. Our findings demonstrate that barriers to adoption are more complex than simply the factors that predict lower adoption, as both adopters and nonadopters experience barriers. Furthermore, factors that typically predict higher adoption, such as conservation motivation, do not insulate a farmer from facing barriers to adoption. We consider how adopters are likely to go through a learning process while moving from considering to fully implementing a new practice, during which different barriers to behavior change may be encountered. We argue that interventions intended to motivate farmer adoption of improved management practices need to take more nuanced approaches to understanding how barriers to adoption are likely to vary across stages of adoption, farm and farmer type, and specific management practices.
Stokes flows past gaps in a wall

This paper presents a conformal mapping approach to the study of planar Stokes flows near a wall with either one or two gaps. The technique reproduces, in a unified fashion, analytical solutions for various Stokes flows past a single gap in a wall found by previous authors using different methods. These include purely pressure-driven flows, shear flows and stagnation point flows near a gap in a wall. It is then shown how the conformal mapping method can be generalized to find new analytical solutions for the analogous flows when there are two gaps in the wall. Features of the new two-gap solutions are studied in detail.
Exploring the effects of virtual hand appearance on midair typing efficiency

Midair typing has gradually become the potential mainstream of virtual reality (VR) typing, as it eliminates the setup of additional hardware devices and provides convenience for portable head‐mounted displays (HMDs). In midair typing, users type on a virtual keyboard while using their virtual hands. In addition to the lack of a dominant method for VR‐based midair typing, we still do not know the impact that different appearances of virtual hands could have on text input in VR. Thus, we picked a widely used midair typing method (i.e., the VR‐rendered QWERTY keyboard) and conducted a VR study to explore the effects of three hand appearances (i.e., abstract, mannequin, realistic hands) on typing efficiency in terms of typing accuracy, typing speed, and task load. Our within‐group study revealed that (1) the mannequin hand caused significantly higher performance on typing speed than the abstract and realistic hands, (2) the abstract hand caused significantly lower performance (more typing errors) on typing accuracy compared to the mannequin and realistic hands, and (3) participants rated the task load of using the abstract hand significantly higher than the mannequin and realistic hands.
Joint Learning of Image Deblurring and Depth Estimation Through Adversarial Multi-Task Network

Self-supervised monocular depth estimation methods have achieved remarkable results on natural clear images. However, it is still a serious challenge to directly recover depth information from blurred images caused by long-time exposure while camera fast moving. To address this issue, we propose a unified framework for simultaneous deblurring and depth estimation (SDDE), which has higher coupling performance and flexibility compared with the simple concatenation strategy of deblurring model and depth estimation model. This framework mainly benefits from three features: 1) a novel Task-aware Fusion Module (TFM) to adaptively select the most relevant intermediate shared features for the dual decoder network by aggregating multi-scale features, 2) a unique Spatial Interaction Module (SIM) to learn higher-order representation in the encoder stage to better describe complex boundaries of different classes in high-dimensional space, and focuses on the task-related region by modeling the pairwise spatial correlation of the holistic tensor, 3) a Priors-Based Composite Regularization term to jointly optimize the shared encoder-dual decoder network. This work was evaluated on multiple datasets, including: Stereo blur, KITTI,NYUv2, REDS and our own large-scale stereo blur dataset, resulting in state-of-the-art results for depth estimation and image deblurring, respectively.
Attenuation Calibration of an X-Band Weather Radar Using a Microwave Link

Abstract The attenuation of a radar signal is a serious problem facing meteorologists and hydrologists. In heavy rain, reflectivity information can be completely lost from large portions of a radar scan. The problem is particularly acute for X-band radars. Current methods of correcting for attenuation face many difficulties, mainly because the actual amount of attenuation at any given time is unknown. In this paper a backward-iterative attenuation-correction algorithm is presented that uses the attenuation measured by a microwave link with its receiver collocated with an X-band weather radar in Essen, Germany. Data are also available from a network of rain gauges located in the vicinity of the link path. This network provides a measure of “ground truth” rainfall against which radar estimates can be compared. The results show that the algorithm can recover much of the reflectivity information that is lost due to attenuation of the radar beam. The method is seen to be particularly effective in convective co.
Numerical analysis of variational problems in atomistic interaction models

The present thesis consists of two parts. The first part is devoted to the analysis of discretizations of a class of basic electronic density functionals. In the second part we suggest and analyze Quasicontinuum Methods for an atomistic interaction potential that is based on a field. We begin by formulating and analyzing a model for the study of finite clusters of atoms or localized defects in infinite crystals based on a version of the classical Thomas{Fermi{Dirac{von Weizs? acker density functional. We show that the resulting constrained optimization problem has a minimizer and we provide a careful analysis of the solvability of the associated Euler{Lagrange equation. Based on these results, and using tools from saddle-point theory and nonlinear analysis, we then show that a Galerkin discretization has a solution that converges to the correct limit (in the case of Dirichlet as well as periodic boundary conditions). Furthermore, we investigate the issue of optimal convergence rates. Using appropriate dual problems, we can show faster convergence for the energy, the Lagrange multiplier of the underlying minimization problem, and the L2-errors of the solutions. We also look at the dependence of the density functional on the nucleus coordinates and show a convergence result for minimizing nucleus configurations. These results are subsequently generalized to the case of discretizations with numerical integration. Existence and convergence of solutions, as well as optimal convergence rates can be established if quadrature rules of sufficiently high order are applied. In the second part of the thesis we consider an atomistic interaction potential in one dimension given through a minimization problem, which gives rise to a field. The forces on atoms are in this case given by local expressions involving this field. A convenient feature of this model is the existence of a weak formulation for the forces, which provides a natural connection point for the coupling with a continuum model. We suggest Quasicontinuum-like coupling mechanisms that are based on a decomposition of the domain into an atomistic and a continuum region. In the continuum region we use an approximation based on the Cauchy{ Born rule. In the atomistic subdomain a version of the atomistic model with Dirichlet boundary conditions is applied. Special attention has to be paid to the dependence of the atomistic subproblem on the boundary and the boundary conditions. Applying concepts from nonlinear analysis we show existence and convergence of solutions to the Quasicontinuum approximation.
Trends and Outcomes in Lung Transplantation in Patients with and without Idiopathic Pulmonary Fibrosis in Spain during the Period 2016–2020

(1) Background: This paper aims to assess temporal trends (2016–2020) in incidence, patient’s characteristics, complications, length of hospital stay (LOHS) and in-hospital mortality (IHM) among patients with and without idiopathic pulmonary fibrosis (IPF) undergoing lung transplantation (LTx). We also analyse the effect of the COVID-19 pandemic on LTx in these populations. (2) Methods: A retrospective, population-based observational study was conducted using the Spanish National Hospital Discharge Database. Multivariable adjustment was conducted with logistic regression to analyse the IHM. (3) Results: We identified 1777 admissions for LTx during the study period, of which 573 (32.2%) were performed in patients with IPF. The number of hospital admissions for LTx rose from 2016 to 2020, both in patients with and without IPF, but a marked reduction was observed from year 2019 to year 2020. Over time, the proportion of single LTx decreased and bilateral LTx increased significantly in both groups. The incidence of LTx complications increased significantly over time along with the increase in the incidence of IPF. No significant differences in the incidence of complications or in the IHM between patients with and without IPF were found. Suffering any complication of the LTx and pulmonary hypertension were conditions positively associated with IHM in patients with and without IPF. The IHM remained stable from 2016 to 2020 in both study populations and was not affected by the COVID pandemic. (4) Conclusions: Patients with IPF account for almost a third of all lung transplants. The number of LTx increased over time in patients with and without IPF, but a marked reduction was observed from 2019 to 2020. Although the proportion of LTx complications increased significantly over time in both groups, the IHM did not change. IPF was not associated with increased complications or IHM after LTx.
Three-Year Clinical Outcomes Based on Pre-Percutaneous Coronary Intervention Coronary Blood Flow Grade and Symptom-to-Balloon Time in Patients with Non-ST-Segment Elevation Myocardial Infarction

We compared the 3-year clinical outcomes according to the degree of pre-percutaneous coronary intervention thrombolysis in myocardial infarction flow grade (pre-PCI TIMI) and symptom-to-balloon time (SBT) individuals who underwent successful stent implantation with a diagnosis of non-ST-segment elevation myocardial infarction (NSTEMI). A total of 4910 patients with NSTEMI were divided into two groups: pre-PCI TIMI 0/1 (SBT < 48 h: n = 1328, SBT ≥ 48 h: n = 558) and pre-PCI TIMI 2/3 (SBT < 48 h: n = 1965, SBT ≥ 48 h: n = 1059). The primary outcome was a 3-year all-cause death rate, and the secondary outcome was the composite endpoint of 3-year all-cause death, recurrent MI, or any repeat revascularization rate. After adjustment, in the pre-PCI TIMI 0/1 group, the 3-year all-cause death (p = 0.003), cardiac death (CD, p < 0.001), and secondary outcome (p = 0.030) values were significantly higher in the SBT ≥ 48 h group than in the SBT < 48 h group. However, patients with pre-PCI TIMI 2/3 had similar primary and secondary outcomes, regardless of the SBT group. Within the SBT < 48 h group, the pre-PCI TIMI 2/3 group exhibited significantly higher rates of 3-year all-cause death, CD, recurrent MI, and secondary outcome values than the pre-PCI TIMI 0/1 group. Patients in the SBT ≥ 48 h group with either pre-PCI TIMI 0/1 or TIMI 2/3 had similar primary and secondary outcomes. Our results suggest that shortening the SBT may confer a survival benefit in patients with NSTEMI and those in the pre-PCI TIMI 0/1 group compared to those in the pre-PCI TIMI 2/3 group.
Lesion characterization using spectral mammography

We present a novel method for characterizing mammographic findings using spectral imaging without the use of contrast agent. Within a statistical framework, suspicious findings are analyzed to determine if they are likely to be benign cystic lesions or malignant tissue. To evaluate the method, we have designed a phantom where combinations of different tissue types are realized by decomposition into the material bases aluminum and polyethylene. The results indicate that the lesion size limit for reliable characterization is below 10 mm diameter, when quantum noise is the only considered source of uncertainty. Furthermore, preliminary results using clinical images are encouraging, but allow no conclusions with significance.
Milk Composition of Creole Goats Raised at Different Altitudes in an Extensive Production System in Northeast Mexico

Simple Summary Creole goat milk is a valuable product for human consumption. Its physicochemical characteristics could be influenced by altitude and lactation stage. In this work, we evaluated several chemical and physical conditions of Creole goat milk in semiarid rangeland. The main results indicated that protein and density are influenced by altitude, while fat, freezing point, and pH are influenced by the lactation stage. One of the most nutritional values of goat milk is the type and concentration of fatty acids. In this work, we found that the effect of the agroecological region was minimal on their concentration. The lactation stage affected the composition of medium-chain fatty acids and linoelaidic acid. We concluded that nutrition by altitude and goat genetic background could contribute to milk composition. Abstract Goat milk composition is affected by feeding, and in semiarid rangeland, information on Creole goat milk physicochemical composition is lacking. For the fulfillment of this objective, three agroecological regions (AR) considering altitude (lowland 87, highland 779, and mountain 1309 m above sea level) with different botanical compositions were chosen. Every AR analyzed accounted for 30 goat herds, with a total of 90 herds. The results demonstrated that altitude had an influence mainly on density and protein. Milk density increases as altitude increases; conversely, milk protein increases as altitude decreases. On the other hand, in the mountain and lowland ARs, the salts and solids not fat (SNF) percentages were higher compared to that of the highland AR (p < 0.05). The freezing point (FP) was higher at highland altitudes compared to that of mountain and lowland ARs (p < 0.01). In the milk fatty acids (FA) profile, only the C14:1 value was affected by altitude, whereas goat milk at lowland and mountain altitudes had higher values compared to that at highland altitudes (p < 0.05). Additionally, late lactation stage fat, FP, and pH values were higher compared to early lactation values. The opposite effect was observed for salts and SNF. In the FA profile, late lactation values were higher for C10:0 and C8:0 compared to early lactation values. The opposite trend was observed for C18:2n6t. The thrombogenic index was significantly higher at lowland altitudes compared to highland altitudes, and similar to the mountain AR. These goat milk characteristics could be explained as a consequence of animal nutrition, as well as the goat’s meat-type phenotype.
Decentralized Finance (DeFi) Assurance: Audit Adoption and Capital Markets Effects

Decentralized finance (DeFi) represents a large capital market where users conduct transactions primarily through digital smart contracts. These contracts are susceptible to cyber-attacks and coding errors that can result in significant financial losses, which has led to the emergence of smart contract audits to reduce information asymmetry and foster trust among DeFi service providers and users. Using a large hand-collected sample of these audit reports from DeFi service providers, we provide some of the first evidence showing that (1) these audits are pervasive, (2) the audit firm market is predominantly composed of new technical audit firms, (3) the scope of these audits can span a variety of contract features, and (4) the market reacts positively to the release of these audit reports, suggesting that these reports are value relevant. These findings highlight the demand for novel assurance services driven by blockchain technology.
Weighing the importance of surface forcing on sea ice: a September 2007 modelling study

The sea ice minimum of September 2007 is represented in a 50‐year simulation using the Los Alamos Sea Ice Model, CICE, in spite of the fact that only four atmospheric forcing fields vary interannually in the model simulation; all other atmospheric and oceanic forcing data are monthly mean climatologies. Simulation results support prior conclusions that an anomalous pressure pattern, ice‐ocean albedo feedback effects on sea surface temperature, and the long‐term sea ice thinning trend are primarily responsible for the sea ice minimum of 2007. In addition, the simulation indicates that cloudiness, precipitation, and other forcing quantities were of secondary importance.