Miracle-dz/UniFAR-FTUs huggingface dataset:
Anomalous Lightning Behavior During the 26–27 August 2007 Northern Great Plains Severe Weather Event

Positive polarity lightning strokes can be useful indicators of thunderstorm behavior. A combination of National Lightning Detection Network and Next Generation Radar retrievals is used to analyze the anomalous positive cloud‐to‐ground (CG) lightning behavior of a rare, late summer severe weather event that occurred on 26–27 August 2007 in the Northern Great Plains region of the United States and southern Canada. Seven discrete supercells (SC1–SC7) exhibiting frequent and intense lightning were responsible for numerous reports of severe weather (e.g., severe hail and 16 tornadoes) including catastrophic damage to the town of Northwood, North Dakota, caused by SC2. Biomass burning smoke from wildfires in Idaho and Montana was present prior to convective initiation. A positive CG lightning stroke rate of nearly 30 strokes per minute was observed 10 min before the EF4 tornado struck Northwood. SC2 was also responsible for all the reports of tornadoes exceeding an EF2 rating. The strongest peak currents (>200 kA) were observed in SC1–SC4 with SC2 having a maximum value of 280 kA. SC2 dominated the statistics of the line of supercells accounting for 27% of all CG lightning strokes. Positive CG lightning accounted for over 40% of all CG lightning strokes in SC4–SC7 on average, and the maximum exceeded 90% in SC6 and SC7. Increasing positive CG lightning dominance was correlated with an increasing northward gradient of smoke aerosol loading in addition to severe weather being reported before the maximum in positive CG lighting stroke rate (SC5 and SC6). This suggests that a complex combination of synoptic forcing and aerosol perturbation likely led to the observed anomalous positive CG lightning behavior in the supercells.
Human Choice Prediction in Language-based Non-Cooperative Games: Simulation-based Off-Policy Evaluation

Persuasion games have been fundamental in economics and AI research, and have significant practical applications. Recent works in this area have started to incorporate natural language, moving beyond the traditional stylized message setting. However, previous research has focused on on-policy prediction, where the train and test data have the same distribution, which is not representative of real-life scenarios. In this paper, we tackle the challenging problem of off-policy evaluation (OPE) in language-based persuasion games. To address the inherent difficulty of human data collection in this setup, we propose a novel approach which combines real and simulated human-bot interaction data. Our simulated data is created by an exogenous model assuming decision makers (DMs) start with a mixture of random and decision-theoretic based behaviors and improve over time. We present a deep learning training algorithm that effectively integrates real interaction and simulated data, substantially improving over models that train only with interaction data. Our results demonstrate the potential of real interaction and simulation mixtures as a cost-effective and scalable solution for OPE in language-based persuasion games. 1
Evaluation of Vegetation Responses to Climatic Factors and Global Vegetation Trends using GLASS LAI from 1982 to 2010

Abstract Vegetation growth has been profoundly affected by global climate change. It is important to investigate vegetation responses to climatic factors and vegetation trends with remote sensing data. In this study, we explored the responses of global vegetation to 3 climatic factors (temperature, precipitation, and solar radiation) and global vegetation trends based on the Global Land Surface Satellite (GLASS) Leaf Area Index (LAI) dataset from 1982 to 2010. The main findings are: (i) the vegetation responses to temperature and precipitation have no apparent time-lag and the vegetation response to the solar radiation has a time-lag of 1 month in most places in the northern hemisphere; (ii) the driving factor of the growth of vegetation was air temperature, followed by precipitation and solar radiation; (iii) the closest relationships between vegetation and climatic factors were observed in mixed forest, deciduous needleleaf forest, and shrublands at northern mid- and high-latitude; (iv) a map of global vegetation trends from 1982 to 2010 was derived, and showed that the proportion of vegetated pixels with significant increasing and decreasing trends was 34.73% and 6.59% (p < 0.05), respectively; (v) more reasonable vegetation trends can be obtained from the GLASS LAI dataset in the perennial cloud-covered regions.
Sensitivity of glacier volume change estimation to DEM void interpolation

Abstract. Glacier mass balance has been estimated on individual glacier and regional scales using repeat digital elevation models (DEMs). DEMs often have gaps in coverage (“voids”), the properties of which depend on the nature of the sensor used and the surface being measured. The way that these voids are accounted for has a direct impact on the estimate of geodetic glacier mass balance, though a systematic comparison of different proposed methods has been heretofore lacking. In this study, we determine the impact and sensitivity of void interpolation methods on estimates of volume change. Using two spatially complete, high-resolution DEMs over southeast Alaska, USA, we artificially generate voids in one of the DEMs using correlation values derived from photogrammetric processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes. We then compare 11 different void interpolation methods on a glacier-by-glacier and regional basis. We find that a few methods introduce biases of up to 20 % in the regional results, while other methods give results very close (<1 % difference) to the true, non-voided volume change estimates. By comparing results from a few of the best-performing methods, an estimate of the uncertainty introduced by interpolating voids can be obtained. Finally, by increasing the number of voids, we show that with these best-performing methods, reliable estimates of glacier-wide volume change can be obtained, even with sparse DEM coverage.
Generalized Methods and Solvers for Noise Removal from Piecewise Constant Signals

Removing noise from signals which are piecewise constant (PWC) is a challenging signal processing problem that arises in many practical scientific and engineering contexts. For example, in exploration geosciences, noisy drill hole records must be separated into constant stratigraphic zones, and in biophysics, the jumps between states and dwells of a molecular structure need to be determined from noisy fluorescence microscopy signals. This problem is one for which conventional linear signal processing methods are fundamentally unsuited. A wide range of PWC denoising methods exists, including total variation regularization, mean shift clustering, stepwise jump placement, running median filtering, convex clustering shrinkage, bilateral filtering, wavelet shrinkage and hidden Markov models. This paper builds on results from the image processing community to show that the majority of these algorithms, and more proposed in the wider literature, are each associated with a special case of a generalized functional, that, when minimized, solves the PWC denoising problem. We show how the minimizer can be obtained by a range of computational solver algorithms, including stepwise jump placement, quadratic or linear programming, finite differences with and without adaptive step size, iterated running medians, least angle regression, piecewise-linear regularization path following, or coordinate descent. Using this generalized functional, we introduce several novel PWC denoising methods, which, for example, combine the global behaviour of mean shift clustering with the local smoothing of total variation diffusion, and show example solver algorithms for these new methods. Head-to-head comparisons between these methods are performed on synthetic data, revealing that our new methods have a useful role to play. Finally, overlaps between the generalized methods of this paper and others such as wavelet shrinkage, hidden Markov models, and piecewise smooth filtering are touched on.
Federal Reserve Bank of San Francisco Working Paper Series Evidence on the Costs and Benefits of Bond Ipos Evidence on the Costs and Benefits of Bond Ipos Evidence on the Costs and Benefits of Bond Ipos

The views in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Federal Reserve Bank of San Francisco or the Board of Governors of the Federal Reserve System. Abstract This paper investigates whether it is costly for non–financial firms to enter the public bond market, and whether firms benefit from their bond IPOs. We find that both gross spreads and ex-ante credit spreads are higher for IPO bonds, suggesting that firms pay higher underwriting costs on their first public bond. We also find that underpricing in the secondary market is higher for IPO bonds, further suggesting that it is costly to enter the public bond market. The costs of entering the public bond market are economically meaningful and are higher for risky firms. We investigate the benefits from entering the public bond market, by looking at the costs firms pay to raise external funding subsequently to their bond IPOs. Our results show that these benefits exist, but they accrue only to safe firms. These firms benefit from a reduction both in the interest rates they pay on bank loans and the costs they incur to issue private bonds after they enter the public bond market. Together with our the previous findings, these results lend support to the thesis that bond IPOs are unique.
A Time-Efficient CMOS-Memristive Programmable A Time-Efficient CMOS-Memristive Programmable Circuit Realizing Logic Functions in Generalized Circuit Realizing Logic Functions in Generalized AND-XOR Structures AND-XOR Structures

— This paper describes a CMOS-memristive Programmable Logic Device connected to CMOS XOR gates (mPLD-XOR) for realizing multi-output functions well-suited for two-level {NAND, AND, NOR, OR}-XOR based design. This structure is a generalized form of AND-XOR logic where any combination of NAND, AND, NOR, OR, and literals can replace the AND level. For mPLD-XOR, the computational delay, which is measured as the number of clock cycles, equals the maximum number of inputs to any output XOR gate of a function assuming that the number of XOR gates is large enough to calculate the outputs of the function simultaneously. The input levels of functions are implemented with novel programmable diode gates, which rely on the diode-like behavior of self-rectifying memristors, and the output levels of functions are realized with CMOS modulo-two counters. As an example, the circuit implementation of a 3-bit adder and a 3-bit multiplier are presented. The size and performance of the implemented circuits are estimated and compared with that of the equivalent circuits realized with stateful logic gates. Adding a feedback circuit to the mPLD-XOR allows the implementation of a multilevel XOR logic network with any combination of sums, products, XORs, and literals at the input of any XOR gate. The mPLD-XOR with feedback can reduce the size and number of computational steps (clock cycles) in realizing logic functions, which makes it well suited for use in communication and parallel computing systems where fast arithmetic operations are demanding.
Extreme Bounds of Democracy

What determines the emergence and survival of democracy? The authors apply extreme bounds analysis to test the robustness of fifty-nine factors proposed in the literature, evaluating over three million regressions with data from 165 countries from 1976 to 2002. The most robust determinants of the transition to democracy are gross domestic product (GDP) growth (a negative effect), past transitions (a positive effect), and Organisation for Economic Co-operation and Development membership (a positive effect). There is some evidence that fuel exporters and Muslim countries are less likely to see democracy emerge, although the latter finding is driven entirely by oil-producing Muslim countries. Regarding the survival of democracy, the most robust determinants are GDP per capita (a positive effect) and past transitions (a negative effect). There is some evidence that having a former military leader as the chief executive has a negative effect, while having other democracies as neighbors has a reinforcing effect.
The Persistence of Inflation in Switzerland: Evidence from Disaggregate Data

This paper investigates persistence of Swiss consumer price inflation using aggregate and disaggregate inflation data covering 1983-2008. We document that persistence of sectoral inflation rates is below persistence of aggregate inflation. Our main finding is that inflation persistence significantly declines in the early 1990s. An estimated factor model reveals that inflation persistence stems from a persistent component that is common to inflation rates across sectors. Both the relevance and the persistence of the common component decline over time. Depending on the sample period and aggregation level, 70 to 90 percent of the variance in sectoral inflation rates is accounted for by short-lived sectoral factors.
KOF Working Papers

This paper uses panel data of Swiss firms to analyze the impact of education‐level diversity in the workforce on innovation performance, addressing endogeneity by exploiting within‐firm variation as well as variation in labor supply across regions. We find that vertical educational diversity increases the extensive margin of R&D and product innovation, particularly new product innovation. However, the relationship with process innovation, R&D intensity, and product innovation intensity is insignificant or even negative. These results are in line with the idea that vertical educational diversity enhances the creative moment of the invention phase, while it might affect the commercialization phase negatively due to the dominance of coordination and communication costs relative to the gains in creativity.
Satellite-based salt marsh elevation, vegetation height, and species composition mapping using the superspectral WorldView-3 imagery

ABSTRACT Very high resolution (VHR) space-borne data are needed to finely and continuously map salt marshes. The WorldView-3 (WV-3) sensor leverages one panchromatic, eight optical, and eight shortwave infrared (SWIR) bands at 0.31, 1.24, and 7.5 m pixel size, respectively. Although eight optical bands have been previously pansharpened, no attempt to use the 16-band superspectral data set at VHR (0.31 m) has been yet reviewed. Here, we propose to reliably pan-sharpen the 16 WV-3 predictors so as to model (artificial neural network, ANN) salt marsh elevation and vegetation height and classify species composition at VHR using calibration/validation handheld vegetation height, airborne lidar elevation, and drone blue-green-red (BGR) responses. Three models have been created over a megatidal bay (Beaussais Bay, Brittany, France) provided with mud flats, salt marshes, and polders. VHR-screened WV-3 bands very satisfactorily predicted salt marsh elevation and vegetation height responses (r = 0.86, R2 = 0.71, root mean square error (RMSE) = 0.33 m and r = 0.88, R2 = 0.77, RMSE = 5.72 cm, respectively). The WV-3 superspectral data set outperformed the eight-band multispectral and four-band traditional data sets to classify 15 salt marsh habitats (OA = 95.47, 82.33, and 69.27%, respectively). Adding WV-3-based salt marsh elevation and vegetation height augmented the 15-class classification of the superspectral and traditional data sets (OA = 97.60 and 77.47%, respectively), but not for the multispectral one (OA = 81.93%).
Playing Online Games: Flow Experience

Playing MUDs (Multi-User Dungeons, or Multi-User Dimensions), text-only online gaming environments, may initiate flow experience. Online survey research was administered within the population of Russian MUDs players, using the specially designed questionnaire with 3 blocks of questions: demography and experience in playing MUDs; flow experience; interactive patterns. Replies of respondents (N = 347) fit a six factor model: F1 (Flow experience); F2 (Achievement); F3 (Activity/Passivity); F4 (Interaction); F5 (Thoughfulness/Spontaneity); F6 (Cognition). To analyse the data, structural equation modeling was done. All the correlations between the factors are significant (p < 0.05). The set of dimensions describing flow experience while playing MUDs was selected. Since players experience flow while MUDding, it was proposed that flow is one of the sources of MUDs' long-time attractiveness for players.
Higher education effects on regional growth in Poland: panel data estimates

In this paper, we have estimated determinants of real regional per capita growth, with the focus on higher education effects, using a balanced panel data set consisting of 16 Polish voivodships for the period from 2000 to 2015. Our results confirm a strong stimulating impact of the number of students on regional growth, but there is evidence (though rather weak) of a negative effect of the educational variable in changes. Such an outcome provides evidence in favor of the Nelson-Phelps approach, which stipulates positive growth effects of the human capital stock. We also find that higher employment accelerates regional growth, while evidence is rather ambiguous for investments in physical capital. Finally, our results offer evidence to support the convergence hypothesis in Poland
Active Faulting Geometry and Stress Pattern Near Complex Strike‐Slip Systems Along the Maghreb Region: Constraints on Active Convergence in the Western Mediterranean

The Maghreb region (from Tunisia to Gibraltar) is a key area in the western Mediterranean to study the active tectonics and stress pattern across the Africa‐Eurasia convergent plate boundary. In the present study, we compile comprehensive data set of well‐constrained crustal stress indicators (from single focal mechanism solutions, formal inversion of focal mechanism solutions, and young geologic fault slip data) based on our and published data analyses. Stress inversion of focal mechanisms reveals a first‐order transpression‐compatible stress field and a second‐order spatial variation of tectonic regime across the Maghreb region, with a relatively stable SHmax orientation from east to west. Therefore, the present‐day active contraction of the western Africa‐Eurasia plate boundary is accommodated by (1) E‐W strike‐slip faulting with reverse component along the Eastern Tell and Saharan‐Tunisian Atlas, (2) a predominantly NE trending thrust faulting with strike‐slip component in the Western Tell part, and (3) a conjugate strike‐slip faulting regime with normal component in the Alboran/Rif domain. This spatial variation of the present‐day stress field and faulting regime is relatively in agreement with the inferred stress information from neotectonic features. According to existing and newly proposed structural models, we highlight the role of main geometrically complex shear zones in the present‐day stress pattern of the Maghreb region. Then, different geometries of these major inherited strike‐slip faults and its related fractures (V‐shaped conjugate fractures, horsetail splays faults, and Riedel fractures) impose their component on the second‐ and third‐order stress regimes. Neotectonic and smoothed present‐day stress map (mean SHmax orientation) reveal that plate boundary forces acting on the Africa‐Eurasia collisional plates control the long wavelength of the stress field pattern in the Maghreb. The current tectonic deformations and the upper crustal stress field in the study area are governed by the interplay of the oblique plate convergence (i.e., Africa‐Eurasia), lithosphere‐mantle interaction, and preexisting tectonic weakness zones.
The Influence of Solar Wind and Geomagnetic Indices on Lower Band Chorus Emissions in the Inner Magnetosphere

Statistical wave models, describing the distribution of wave amplitudes as a function of location, geomagnetic activity, and other parameters, are needed as the basis to describe the wave‐particle interactions within numerical models of the radiation belts. In this study, we widen the scope of the statistical wave models by investigating which of the solar wind parameters or geomagnetic indices and their time lags have the greatest influence on the amplitudes of lower band chorus (LBC) waves in the inner magnetosphere. The solar wind parameters or geomagnetic indices with the greatest control over the waves were found using the error reduction ratio (ERR) analysis, which plays a key role in system identification modeling techniques. In this application, the LBC magnitudes at different locations are considered as the output data, while the lagged solar wind parameters are the input data. The ERR analysis automatically determines a set of the most influential parameters that explain the variations in the emissions. Both linear and nonlinear applications of the ERR analysis are compared using solar wind inputs and show that the linear ERR analysis can be misleading. The linear results show that the interplanetary magnetic field (IMF) factor has the most influence on at each magnetic local time (MLT) sector. However, the nonlinear ERR analysis shows that the IMF factor coupled with the solar wind velocity has the main contribution to the LBC wave magnitudes. When geomagnetic indices are included as inputs with the solar wind parameters to the nonlinear ERR analysis, the results show that the majority of the variation in emissions may be attributed to the Auroral Electrojet (AE) index. In the dawn sectors between 00 and 12 MLT and 5 < L < 7, the AE index multiplied by the solar wind velocity with zero time lag has the most influence on the amplitudes of LBC. For 5 < L < 7, the parameters with the highest ERR are the AE index multiplied by the solar wind velocity with a 2‐hr time lag at 12–16 MLT, the linear AE index with a 2‐hr time lag at 16–20 MLT, and AE index multiplied by the IMF factor with zero lag at 20–00 MLT. For 4 < L < 5, the parameters with the highest ERR are the AE index multiplied by the solar wind dynamic pressure with zero time lag at 00–04 MLT, the AE index multiplied by the solar wind velocity with zero time lag between 14 and 12 MLT, the AE index multiplied by the solar wind velocity with a 2‐hr time lag at 12–16 MLT, the Dst index with a 6‐hr time lag at 12–16 MLT, and the AE index multiplied by the IMF factor with zero lag at 20–00 MLT.
The Environmental Worldviews and Climate Change Mitigation Behaviors: Testing the New Ecological Scale in the Smallest Space Analysis for Chinese Samples

An online survey assessing the associations between people’s environmental worldviews and proenvironmental behaviors was conducted through the Qualtrics panel with 515 Mandarin-speaking residents from major Chinese cities. The Smallest Space Analysis (SSA) was adopted to test the validation of the New Ecological Paradigm (NEP) sub-dimensions generated by the factor analysis through the HUDAP (Hebrew University Data Analysis Package) software. 20 items of judging people’s mitigation behavior on climate change were treated as external variables to investigate their associations with environmental worldviews in this configuration produced by the NEP scale. Results indicated that the 2 dimension solution of the NEP scale is suggested by the exploratory factor analysis, but the 3 dimension solution is valid by the SSA. For the Chinese sample, all climate change mitigation behavior variables are located in the same region of the SSA plot, which is made by items of dimension ecocentrism.