Miracle-dz/UniFAR-FTUs huggingface dataset:
KAM: A System for Intelligently Guiding Numerical Experimentation by Computer

Part 1 Introduction: goal - automate part of a scientist's work Henon's area preserving map - an illustration what KAM does how KAM does it what does KAM build on? the rest of the story. Part 2 Overview of KAM: a session with KAM design criteria KAM overview - structure and processes. Part 3 Orbit recognition: what is orbit recognition? core idea - shape from minimal spanning trees implementation experiment - main illustration another experiment - orbit on the surface of a Torus evaluating the performance. Part 4 Phase space searching: what is phase space searching? core idea - consistency of neighbouring orbits rotation number - continuity of discrete flows orbit compatibility implementation experiment - main illustration other experiments a concise phase portrait description evaluating the performance. Part 5 Parameter space searching: what are bifurcations? core idea - structural stability generic bifurcations of fixed points phase portrait compatibility implementation experiment evaluating the performance executive summary of numerical experiments. Part 6 Exploring an open problem: scenario standing waves in a rectangular tank mathematical formulation numerical findings - making a Poincare section applying an analytical approximation method comparing analytical predictions with numerical findings how physical parameters affect chaos what have we learned? Part 7 Conclusion: what does KAM do? why does KAM work? what are the contributions what's next - enhancing KAM, a workbench approach to scientific computing user manual. (Part contents).
Disappearing Democrats: Rethinking Partisanship Within Pennsylvania's Electorate

Pennsylvania has more registered Democrats than Republicans, yet Repub licans cOlltrol most 0/ the slalewide elecled offices and oath ella/llbers uf lhe biute legislature. How is it possible that the Democrats' registration advantage does not lead to more Democratic electoral success? Using a random survey ofPeT1n sylvania voters and comparative questions on party orientation and party regis tration, this article finds that many of the state's voters identify with a political party that is different from the party in which they are actually registered. Party identification is important because it is a better predictor of voting behavior than is party registration. The article finds that more registered Democrats in Pennsylvania ident~fy with the Republican Party than vice versa, making the Democrats'registration advantage an advantage i11 name only.
Freak wave events in 2005–2021: statistics and analysis of favourable wave and wind conditions

Abstract. Freak or rogue waves are unexpectedly and abnormally large waves in seas and oceans, which can cause loss of human lives and damage to ships, oil platforms, and coastal structures. Evidence of such waves is widely spread around the globe. The present paper is devoted to analysis of the unified collection of freak wave events from different chronicles and catalogues from 2005 to 2021. The considered rogue waves are not measured in situ data, but their descriptions, which have been found in mass media sources and scientific articles, are the data used. All of them resulted in damage to ships or coastal/offshore structures and/or human losses. The collection accounts for 429 events. First, the analysis based on their characteristics taken from the descriptions of the events (including locations, water depth, damages) is carried out. Second, the analysis of wave parameters taken from the climate reanalysis ERA5 is performed. Thus, the most probable background wave parameters at the time of the freak event (including wind speed, gusts, significant wave height, maximum wave height, peak wave period, skewness, excess kurtosis, Benjamin–Feir instability (BFI), and wave spectral directional width) for each freak wave event are determined.
UCF-System for TRECVID-2021 ActEV challenge

Activity detection has wide-reaching applications in video surveillance, sports, and behavior analysis. The existing literature in activity detection has mainly focused on benchmarks like AVA, AVA-Kinetics, UCF101-24, and JHMDB-21. However, these datasets fail to address all issues of real-world surveillance camera videos like untrimmed nature, tiny actor bounding boxes, multi-label nature of the actions, etc. In this work, we propose a real-time, online, action detection system which can generalize robustly on any unknown facility surveillance videos. Our real-time system mainly consists of tracklet generation, tracklet activity classification, and prediction refinement using the proposed post-processing algorithm. We tackle the challenging nature of action classification problem in various aspects like handling the class-imbalance training using PLM method and learning multi-label action correlations using LSEP loss. In order to improve the computational efficiency of the system, we utilize knowledge distillation. Our approach gets second place in TRECVID 2021 ActEV challenge. Project Webpage: www.crcv. ucf.edu/ research/projects/gabriellav2/
Impact of formulations of the nucleation rate on ice nucleation events

Ice formation in cold temperature regimes is most probably dominated by homogeneous freezing of aqueous solution droplets. The nucleation rate as derived from laboratory experiments can be represented as a function of water activity. For idealized nucleation events as modelled with a state-of-the-art ice microphysics, the impact of different approximations of the nucleation rate on the resulting ice crystal number concentrations and maximum supersaturation ratios is investigated. The nucleation events are sensitive to the slope of the nucleation rate but only weakly affected by changes in its absolute value. 5 This leads to the conclusion that details of the nucleation rate are less important for simulating ice nucleation in bulk models, if the main feature of the nucleation rate (i.e. its slope) is represented sufﬁciently. The weak sensitivity on the absolute values of the nucleation rate suggests that the amount of available solution droplets also does not crucially affect nucleation events. The use of just one distinct nucleation threshold for analysis and model parameterisation should be reinvestigated. The frequently used thresholds corresponding to a very high nucleation rate value is not reached in many nucleation events with low vertical 10 updrafts. In contrast, the maximum supersaturation and thus the nucleation thresholds reached during an ice nucleation event depend on the vertical updraft velocity or cooling rate. This feature might explain some high supersaturation values during nucleation events in cloud chambers and suggests a reformulation of ice nucleation schemes used in coarse models based on a ﬁxed nucleation threshold.
Estimation of internal wave velocity in the shallow South China Sea using single and multiple satellite images

This paper presents results on the estimation of the phase velocity of internal waves (IWs) in the shallow waters of the South China Sea in terms of the water depth using satellite data. To calculate the phase velocity, two methods are considered. The first is based on the different positions of IW images acquired by Environmental Satellite-advanced synthetic aperture radar (ASAR) and Terra–Moderate Resolution Imaging Spectroradiometer (MODIS) in a very short time interval, and the second method uses the images of several packets of IWs associated with semidiurnal tidal period in either a single ASAR or MODIS image. The former is termed as the multitemporal images (MTI) method, and the latter is referred to as the tidal period images (TPI) method. The results show that the wave velocities estimated by the MTI method have strong correlation with those derived from a depth-dependent IW propagation theory, while those by the TPI method have moderate correlation. Both the methods can be used to estimate the IW phase velocity but with reduced accuracy by the TPI method. The main reason of this reduced accuracy is the long tidal period during which the characteristics of IWs change as they propagate over long distance in the water of variable currents and/or bottom topography.
Enhancing the H2O Megamaser Detection Rate Using Optical and Mid-infrared Photometry

Water megamasers from circumnuclear disks in galaxy centers provide the most accurate measurements of supermassive black hole masses and uniquely probe the subparsec accretion processes. At the same time, these systems offer independent crucial constraints of the Hubble constant in the nearby universe, and thus, the arguably best single constraint on the nature of dark energy. The chances of finding these golden standards are, however, abysmally low, at ≲3% overall for any level of water maser emission detected at 22 GHz and ≲1% for those exhibiting disk-like configuration. We provide here a thorough summary of the current state of detection of water megamaser disks along with a novel investigation of the likelihood of increasing their detection rates based on a multivariate parameter analysis of the optical and mid-infrared (mid-IR) photometric properties of the largest database of galaxies surveyed for 22 GHz emission. We find that galaxies with water megamaser emission tend to be associated with strong emission in all Wide-field Infrared Survey Explorer mid-IR wavelengths, with the strongest enhancement in the W4 band, at 22 μm, as well as with previously proposed and newly found indicators of active galactic nucleus strength in the mid-IR, such as red W1 − W2 and W1 − W4 colors, and the integrated mid-IR luminosity of the host galaxy. These trends offer a potential boost of the megamaser detection rates to 6%–15%, or a factor of 2–8 relative to the current rates, depending on the chosen sample selection criteria, while fostering real chances for discovering ≳20 new megamaser disks.
On the spectrum and polarization of magnetar flare emission

Bursts and flares are among the distinctive observational manifestations of magnetars, isolated neutron stars endowed with an ultra-strong magnetic field (B ≈ 1014–1015 G). It is believed that these events arise in a hot electron-positron plasma, injected in the magnetosphere, due to a magnetic field instability, which remains trapped within the closed magnetic field lines (the “trapped-fireball” model). We have developed a simple radiative transfer model to simulate magnetar flare emission in the case of a steady trapped fireball. We assume that magnetic Thomson scattering is the dominant source of opacity in the fireball medium, and neglect contributions from second-order radiative processes. The spectra we obtained in the 1–100 keV energy range are in broad agreement with those of available observations. The large degree of polarization (≳ 80%) predicted by our model should be easily measured by new-generation X-ray polarimeters, like IXPE, XIPE and eXTP, allowing one to confirm the model predictions.
Scenario and Model Dependence of Strategic Solar Climate Intervention in CESM

Model dependence in simulated responses to stratospheric aerosol injection (SAI) is a major uncertainty surrounding the potential implementation of this solar climate intervention strategy. We identify large differences in the aerosol mass latitudinal distributions between two recently produced climate model SAI large ensembles, despite using similar climate targets and controller algorithms, with the goal of understanding the drivers of such differences. Using a hierarchy of recently 10 produced simulations, we identify three main contributors including: 1) the rapid adjustment of clouds and rainfall to elevated levels of carbon dioxide, 2) the associated low-frequency dynamical responses in the Atlantic Meridional Overturning Circulation, and 3) the contrasts in future climate forcing scenarios. Each uncertainty is unlikely to be significantly narrowed over the likely timeframe of a potential SAI deployment if a 1.5 C target is to be met. The results thus suggest the need for significant flexibility in climate intervention deployment to account for these large uncertainties in the climate system response.
Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.
Scaling relation for low energy states in a single‐slip model in finite crystal plasticity

We derive a scaling‐relation, for the infimum of the energy for small ϵ,δ > 0, where p, q ≥ 1, u: Ω → ℝ2 is a deformation with suitable affine boundary conditions and γ: Ω → ℝ is a suitable slip variable. This model is motivated by a two‐dimensional single‐slip model in finite crystal plasticity. We show, that the infimum of the energy Jϵ,δ scales as . This scaling‐relation is attained by an asymptotically self‐similar branching construction.
Performance comparison of cross correlation and filled aperture imaging riometers

In striving for ever greater angular resolution in riometer (relative ionospheric opacity meter) observations it is tempting to try to use a nonfilled array to reduce the cost of antenna elements. We analyze as an example the Mills Cross configuration, compare its performance as a riometer with that of a filled square array of the same angular resolution and inquire about the penalty of using a sparsely filled array. We find that the susceptibility to interference from sources in the sidelobes is greater than in the filled array, that strong point sources in the sidelobes can cause both positive and negative excursions in the output and that the noise performance is inferior and requires longer integration times for a given rms error than the filled array.
Vortex line in a neutral finite-temperature superfluid Fermi gas

The structure of an isolated vortex in a dilute two-component neutral superfluid Fermi gas is studied within the context of self-consistent Bogoliubov-de Gennes theory. Various thermodynamic properties are calculated, andthe shift in the critical temperature due to the presence of the vortex is analyzed. The gapless excitations inside the vortex core are studied, and a scheme to detect these states and thus the presence of the vortex is examined. The numerical results are compared with various analytical expressions when appropriate.
Prediction and analysis of high velocity oxy fuel (HVOF) sprayed coating using artificial neural network

: Thermal spray comprises a group of coating processes for coating manufacturing in which metallic or nonmetallic materials are deposited in a molten or semi-molten condition. Most often, the coating properties are significantly influenced by the operating parameters. However, obtaining a comprehensive modeling or analytical analysis of the thermal spray process is too difficult to be practical due to the complex chemical and thermodynamic reactions. Accordingly, the present study aims at applying an artiﬁcial neural network (ANN) model to predict the HVOF sprayed Cr3C2−25NiCr coatings and analyze the influence of operating parameters regardless of the intermediate process. The process parameters, which were automatically recorded by the homemade HVOF spray system during the spray process, were served as the inputs for the ANN model. Then, the porosity, microhardness and wear rate of coatings were measured and considered as targets for the ANN model. After configuring and training procedure of the model, the predicted results were compared to the results of experimental data. The good consistency found between these results permits to verify the reliability and accuracy of the trained ANN model. Additionally, the mean impact value (MIV) analysis was conducted to quantitatively explore the relative significance of each input variable for improving the effective prediction.
Reply to anonymous referee 1

As explained in the introduction section, this study is motivated by the large uncertainties in the global methane budget. More specifically, a mismatch of 160 Tg/yr between top down and bottom up in the GCP budgets is mentioned. The procedure for specifying prior uncertainties, however, adds up globally to 7% (40 Tg/yr) which doesn’t quite reflect this uncertainty. The difference may be more than a factor 4, as the prior budget uncertainty probably reflects only a single year. The setup of prior fluxes mentions a rescaling to make sure that the prior budget is consistent with the observed trend. In sensitivity tests also alternative rescaling is applied to restore the source-sink balance in the a priori budget. It is unclear why this is needed, given that the measurements used in the inversion contain this information (strictly speaking measurement information is double counted in the setup that is used). My guess is that the division of the full time series into blocks and the initialization of these blocks requires the rescaling. If the prior is over constrained for methodological reasons this raises the question how the choice of rescaling might have steered the solution in the direction of the main outcomes and how suitable the proposed time splitting methodology is.
MINI-REVIEW Machine-Learning e Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance

Assessment of intratumoral heterogeneity and tumor-host interaction within the tumor microenvironment is becoming increasingly important for innovative cancer therapy decisions because of the unique information it can generate about the state of the disease. However, its assessment and quanti ﬁ cation are limited by ambiguous de ﬁ nitions of the tumor-host interface and by human cognitive capacity in current pathology practice. Advances in machine learning and arti ﬁ cial intelligence have opened the ﬁ eld of digital pathology to novel tissue image analytics and feature extraction for generation of high-capacity computational disease management models. A particular bene ﬁ t is expected from machine-learning applications that can perform extraction and quanti ﬁ cation of subvisual features of both intratumoral heterogeneity and tumor microenvironment aspects. These methods generate information about cancer cell subpopulation heterogeneity, potential tumor-host
Efficient and Universally Composable Non-Interactive Zero-Knowledge Proofs of Knowledge with Security Against Adaptive Corruptions

Non-interactive zero-knowledge proofs of knowledge (NIZK-PoK) serve as a key building block in many important cryptographic constructions. Achieving universally composable NIZKPoK secure against adaptive corruptions was a long-standing open problem, recently solved by Canetti, Sarkar, and Wang (Asiacrypt’22). This sole known construction requires heavy cryptographic machinery such as correlation-intractable hash functions, and is not ready for use in practice. In this paper, we give constructions of adaptively secure universally composable NIZKPoK in the global random-oracle model; we consider both the programmable and the non-programmable versions of the model. For many practical NIZK proof systems, our constructions incur only a polylogarithmic slowdown factor compared to stand-alone security.
Predicted and Observed Changes in Summertime Biogenic and Total Organic 1 Aerosol in the Southeast United States from 2001 to 2010 2

15 Biogenic secondary organic aerosol (bSOA) is a major component of atmospheric particulate 16 matter (PM 2.5 ) in the southeast United States especially during the summer, when emissions of 17 biogenic volatile organic compound (VOCs) are high and emissions from anthropogenic sources 18 enhance the formation of secondary particulate matter. We evaluate the performance of PM 2.5 19 organic aerosol predictions by a chemical transport model (PMCAMx) in response to significant 20 changes in anthropogenic emissions during the summers of 2001 and 2010. Average predicted 21 bSOA concentrations in the southeast US did not change appreciably from the summer of 2001 to 22 the summer of 2010, while the anthropogenic SOA decreased by 45%. As a result, the biogenic 23 fraction of total OA increased from 0.46 in 2001 to 0.63 in 2010. Partitioning effects due to reduced 24 anthropogenic OA from 2001 resulted in 0.4 µg m -3 less biogenic OA on average in the southeast 25 US in the summer of 2010. This was offset by biogenic SOA increases due to higher biogenic 26 vapor emissions in the warmer 2010 summer. Little noticeable difference was observed in OA 27 prediction performance in the southeast US between the two summer simulation periods. The 28 fractional error of OA predictions remained practically the same analysis suggests that the changes in biogenic OA in this forested relatively polluted region appear 35 to be dominated by the partitioning effects and the NO x effects on SOA yields.
Strong particle production and condensational growth in the upper troposphere sustained by biogenic VOCs from the canopy of the Amazon Basin

Abstract. Nucleation and condensation associated with biogenic volatile organic compounds (BVOCs) are important aerosol formation pathways, yet their contribution to the upper-tropospheric aerosols remains inconclusive, hindering the understanding of aerosol climate effects. Here, we develop new schemes describing these organic aerosol formation processes in the WRF-Chem model and investigate their impact on the abundance of cloud condensation nuclei (CCN) in the upper troposphere (UT) over the Amazon Basin. We find that the new schemes significantly increase the simulated CCN number concentrations in the UT (e.g., up to ∼ 400 cm−3 at 0.52 % supersaturation) and greatly improve the agreement with the aircraft observations. Organic condensation enhances the simulated CCN concentration by 90 % through promoting particle growth, while organic nucleation, by replenishing new particles, contributes an additional 14 %. Deep convection determines the rate of these organic aerosol formation processes in the UT through controlling the upward transport of biogenic precursors (i.e., BVOCs). This finding emphasizes the importance of the biosphere–atmosphere coupling in regulating upper-tropospheric aerosol concentrations over the tropical forest and calls for attention to its potential role in anthropogenic climate change.