Miracle-dz/UniFAR-FTUs huggingface dataset:
Topological flat bands, valley polarization, and interband superconductivity in magic-angle twisted bilayer graphene with proximitized spin-orbit couplings

We study theoretically the magic-angle twisted bilayer graphene with proximity-induced Ising and Rashba spin-orbit couplings on the top layer. We demonstrate topological flat bands and identify three distinct topological phases. Using a weak coupling analysis, we find that (partial) valley polarization prevails for a wide range of doping, suppressing the usual superconductivity with a pairing between time-reversal partners. Remarkably, we uncover that observable unconventional intervalley interband phonon-mediated superconductivity (with the highest $T_c\approx 1.2$K) can coexist with strong valley imbalance due to the approximate Fermi surface nesting between two flat bands not related by time-reversal symmetry, and the dominant pairing is an intersublattice Ising pairing, corresponding to a mixture of $p$- and $d$-waves. In contrast, the intrasublattice Ising phonon-mediated superconductivity with $s$- and $f$-wave mixing emerges in the absence of valley imbalance. Our work reveals a novel route of realizing unconventional superconductivity, and potentially explains the superconductivity phenomenology in existing experiments.
The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition

This paper describes the 6th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with IEEE CVPR 2024. The 6th ABAW Competition addresses contemporary challenges in understanding human emotions and behaviors, crucial for the development of human-centered technologies. In more detail, the Competition focuses on affect related benchmarking tasks and comprises of five sub-challenges: i) Valence-Arousal Estimation (the target is to estimate two continuous affect dimensions, valence and arousal), ii) Expression Recognition (the target is to recognise between the mutually exclusive classes of the 7 basic expressions and 'other'), iii) Action Unit Detection (the target is to detect 12 action units), iv) Compound Expression Recognition (the target is to recognise between the 7 mutually exclusive compound expression classes), and v) Emotional Mimicry Intensity Estimation (the target is to estimate six continuous emotion dimensions). In the paper, we present these Challenges, describe their respective datasets and challenge protocols (we outline the evaluation metrics) and present the baseline systems as well as their obtained performance. More information for the Competition can be found in: https://affective-behavior-analysis-in-the-wild.github. io/6th.
Listening to the Noise: Blind Denoising with Gibbs Diffusion

In recent years, denoising problems have become intertwined with the development of deep generative models. In particular, diffusion models are trained like denoisers, and the distribution they model coincide with denoising priors in the Bayesian picture. However, denoising through diffusion-based posterior sampling requires the noise level and covariance to be known, preventing blind denoising. We overcome this limitation by introducing Gibbs Diffusion (GDiff), a general methodology addressing posterior sampling of both the signal and the noise parameters. Assuming arbitrary parametric Gaussian noise, we develop a Gibbs algorithm that alternates sampling steps from a conditional diffusion model trained to map the signal prior to the family of noise distributions, and a Monte Carlo sampler to infer the noise parameters. Our theoretical analysis highlights potential pitfalls, guides diagnostic usage, and quantifies errors in the Gibbs stationary distribution caused by the diffusion model. We showcase our method for 1) blind denoising of natural images involving colored noises with unknown amplitude and spectral index, and 2) a cosmology problem, namely the analysis of cosmic microwave background data, where Bayesian inference of"noise"parameters means constraining models of the evolution of the Universe.
Equilibrium Analysis of Packet Forwarding Strategies in Wireless Ad Hoc Networks – the Dynamic Case

Ad hoc networks are expected to be used in a number of very different situations. But a common characteristic is that the nodes have to cooperate with each other. This problem is particularly crucial, if each node is its own authority. Reckoning the relevance of this issue, several groups of researchers have proposed different incentive mechanisms, in order to foster cooperation between the nodes, notably for packet forwarding. However, the need for these incentives was not formally justified. In this paper, we address the problem of cooperation without incentive mechanisms and propose a simple model based on game theory. We then prove several theorems about the equilibrium conditions in a simple scenario. We investigate by simulation a more realistic scenario, which includes a real network topology as well as a mobility model. We show that the level of contribution of the nodes to reach cooperation is much higher than in the theoretical model, and we quantify the relationship between mobility and cooperation. We conclude that spontaneous cooperation is easier to reach when mobility is higher.
Labour Index : Measuring the Online Gig Economy for Policy and Research

Labour markets are thought to be in the midst of a dramatic transformation, where standard employment is increasingly supplemented or substituted by temporary gig work mediated by online platforms. Yet the scale and scope of these changes is hard to assess, because conventional labour market statistics and economic indicators are ill-suited to measuring online gig work. We present the Online Labour Index (OLI), a new economic indicator that provides the online gig economy equivalent of conventional labour market statistics. It measures the utilization of online labour across countries and occupations by tracking the number of projects and tasks posted on platforms in near-real time. We describe how the OLI is constructed and demonstrate how it can be used to address previously unanswered questions about the online gig economy; in particular, we show that the online gig economy grew at an annualized rate of 14 percent. To benefit policymakers, labour market researchers, and the general public, the index is available as an open data set and interactive online visualization, which are automatically updated daily.
A Tariff Agent : Interacting with a Future Smart Energy System at Home

Smart systems are becoming increasingly ubiquitous, and consequently transforming our lives. The level of system autonomy plays a vital role in the development of smart systems as it profoundly affects how people and these systems interact with each other. However, to date, there are very few studies on human interaction with such systems. This article presents findings from two field studies where two different prototypes for automating energy tariff-switching were developed and evaluated in the wild. Both prototypes offer flexible autonomy by which users can shift the system’s level of autonomy among three options: suggestion-only, semi-autonomy and full autonomy, whenever they like. Our findings based on thematic analysis show that flexible autonomy is a promising way to sustain users’ engagement with smart systems, despite their occasional mistakes. The findings also suggest that users take responsibility for the undesired outcomes of automated actions when delegation of autonomy can be adjusted flexibly.
Effects of temperature, pH, and ionic strength on the Henry's law constant of triethylamine

The Henry's law constants (KH) of triethylamine (TEA) in pure water and in 1‐octanol were measured for the temperatures pertinent to the lower troposphere (278–298 K) using a bubble column system coupled to a Fourier transform infrared spectrometer. The KH values of TEA in water and 1‐octanol at 298 K are 5.75 ± 0.86 mol L−1 atm−1 and 115.62 ± 5.78 mol L−1 atm−1. The KH values display strong dependence on temperature, pH, and ionic strength. The characteristic times for TEA to establish an equilibrium between gas and droplet with a size of 5.6 µm are ~33 s (298 K, pH = 5.6); ~8.9 × 102 s (278 K, pH = 5.6); ~1.3 × 103 s (298 K, pH = 4.0); and 3.6 × 104 s (278 K, pH = 4.0). The evaluation of TEA partitioning between gas phase and condensed phase implies that TEA predominantly resides in rainwater, and TEA loss to organic aerosol is negligible.
Federal Reserve Bank of San Francisco Working Paper Series Welfare-maximizing Monetary Policy under Parameter Uncertainty Board of Governors of the Federal Reserve System Welfare-maximizing Monetary Policy under Parameter Uncertainty

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 examines welfare-maximizing monetary policy in an estimated micro-founded general equilibrium model of the U.S. economy where the policymaker faces uncertainty about model parameters. Uncertainty about parameters describing preferences and technology implies not only uncertainty about the dynamics of the economy. It also implies uncertainty about the model's utility-based welfare criterion and about the economy's natural rate measures of interest and output. We analyze the characteristics and performance of alternative monetary policy rules given the estimated uncertainty regarding parameter estimates. We find that the natural rates of interest and output are imprecisely estimated. We then show that, relative to the case of known parameters , optimal policy under parameter uncertainty responds less to natural-rate terms and more to other variables, such as price and wage inflation and measures of tightness or slack that do not depend on natural rates. Universität Berlin, and the Federal Reserve Board for comments. The views expressed herein are those of the authors and do not necessarily reflect those of the Board of Governors of the Federal Reserve System, its staff, or the management of the Federal Reserve Bank of San Francisco.
the Society for Computation in Linguistics

Filler-gap dependencies are among the most challenging syntactic constructions for computational models at large. Recently, Wilcox et al. (2018) and Wilcox et al. (2019b) provide some evidence suggesting that large-scale general-purpose LSTM RNNs have learned such long-distance ﬁller-gap dependencies. In the present work we provide evidence that such models learn ﬁller-gap dependencies only very imperfectly, despite being trained on massive amounts of data. Finally, we compare the LSTM RNN models with more modern state-of-the-art Transformer models, and ﬁnd that these have poor-to-mixed degrees of success, despite their sheer size and low perplexity.
Spatial and temporal trends in winter deposition of Pb, Be, Cu and Zn in selected mountain areas of Central Europe

Bohdálková L. , Hruška J. 2017: Spatial and temporal trends in winter deposition of Pb, Be, Cu and Zn in selected mountain areas of Central Europe – Beskydy, 10 (1,2): 87–98 Atmospheric depositions of trace metals have been the focus of attention because of their potential toxicity to living organisms. In this paper, winter deposition rates of Pb, Be, Cu and Zn collected from 2009 to 2011 at 10 mountain-top localities in the border area of the Czech Republic were compared and summarized. Across the sites there were up to 7–8fold differences in Pb, Be and Zn deposition rates, and up to threefold differences in their Cu deposition rates. In all cases, rime contained higher amounts of Pb, Be, Cu and Zn compared to snow. More than 92 % of Pb, Cu and Zn occured in soluble (bioavailable) form, whereas only 34 % of Be was in soluble form. Recent trace metal concentrations in precipitation considerably decrease compared to those measured during the period of the highest atmospheric emissions in the 1980s. The industrial region in the northeast of the Czech Republic experienced moderate levels of Pb air pollution, while atmospheric Pb inputs in the rest of the country as well as overall inputs of Cu, Zn and Be were low, representing a low threat to human and ecosystem health. Between-site differences made it possible to classify sites into three categories according to their level of pollution load. A previously-mentioned north-south pollution gradient between the industrial north and rural south of the country was not observed. Sites in the northwest and in the south were among those with the lowest pollution loads. On the other hand, sites in the northeast were the most polluted due to their location near the industrial regions of southern Silesia (Poland) and Ostrava.
“ Sergey Brin is Batman ” : Google ’ s Project Glass & the instigation of computer adoption in popular culture

The emergence of Google Glass, a prototype for a transparent Heads-Up Display (HUD) worn over one eye, is significant. It is the first conceptualization of a mainstream augmented reality wearable eye display by a large company. This paper argues that Glass's birth is not only a marketing phenomenon heralding a technical prototype, it also argues and speculates that Glass's popularization is an instigator for the adoption of a new paradigm in human-computer interaction, the wearable eye display. Google Glass is deliberately framed in media as the brainchild of Google co-founder Sergey Brin. Glass's process of adoption operates in the context of mainstream and popular culture discourses, such as the Batman myth, a phenomenon that warrants attention. General Terms Human Factors Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
Robust Incremental Polygon Triangulation for Fast Surface Rendering

This paper presents a simple, robust and practical, yet fast algorithm for triangulation of trimmed Bézier surfaces. Points on the surface are input to our algorithm by a sampling scheme. A set of polygons (more generically, a planar straight-line graph, or PSLG) is formed from these samples, which are then triangulated. We also show how to update the triangulation when the samples, and hence the polygons, are updated. The output of the algorithm is a set of triangle strips. The algorithm avoids long and thin triangles. In addition, it also detects if the sampling of the trimming curve forms any non-simple polygons and corrects the triangulation by adding more samples. We report an implementation of the algorithm and its performance on extensive simulation.
Control in a Core Calculus of Dependency Mart́ın

The Dependency Core Calculus (DCC) is an extension of the computational lambda calculus that was designed in order to capture the notion of dependency that arises in information-flow control, partial evaluation, and other programming-language settings. We show that, unexpectedly, DCC can also be used as a calculus for access control in distributed systems. Initiating the study of DCC from this perspective, we explore some of its appealing properties.
Can I use this publicly available dataset to build commercial AI software?-A Case Study on Publicly Available Image Datasets

GOPI KRISHNAN RAJBAHADUR, Centre for Software Excellence, Huawei Canada, Canada ERIKA TUCK, Lassonde School of Engineering, York University, Canada LI ZI, Huawei China, Canada DAYI LIN, Centre for Software Excellence, Huawei Canada, Canada BOYUAN CHEN, Centre for Software Excellence, Huawei Canada, Canada ZHEN MING (JACK) JIANG, Lassonde School of Engineering, York University, Canada DANIEL MORALES GERMAN, University of Victoria, Canada
Multilevel Factor Analysis and Structural Equation Modeling of Daily Diary Coping Data : Modeling Trait and State Variation

To cite this Article Roesch, Scott C. , Aldridge, Arianna A. , Stocking, Stephanie N. , Villodas, Feion , Leung, Queenie , Bartley, Carrie E. and Black, Lisa J.(2010) 'Multilevel Factor Analysis and Structural Equation Modeling of Daily Diary Coping Data: Modeling Trait and State Variation', Multivariate Behavioral Research, 45: 5, 767 — 789 To link to this Article: DOI: 10.1080/00273171.2010. 519276 URL: http://dx.doi. org/10.1080/00273171.2010. 519276
High-rate codes with sublinear-time decoding

Locally decodable codes are error-correcting codes that admit efficient decoding algorithms; any bit of the original message can be recovered by looking at only a small number of locations of a corrupted codeword. The tradeoff between the rate of a code and the locality/efficiency of its decoding algorithms has been well studied, and it has widely been suspected that nontrivial locality must come at the price of low rate. A particular setting of potential interest in practice is codes of constant rate. For such codes, decoding algorithms with locality O(k∈) were known only for codes of rate ∈Ω(1/∈), where k is the length of the message. Furthermore, for codes of rate > 1/2, no nontrivial locality had been achieved. In this article, we construct a new family of locally decodable codes that have very efficient local decoding algorithms, and at the same time have rate approaching 1. We show that for every ∈ > 0 and α > 0, for infinitely many k, there exists a code C which encodes messages of length k with rate 1 − α, and is locally decodable from a constant fraction of errors using O(k∈) queries and time. These codes, which we call multiplicity codes, are based on evaluating multivariate polynomials and their derivatives. Multiplicity codes extend traditional multivariate polynomial codes; they inherit the local-decodability of these codes, and at the same time achieve better tradeoffs and flexibility in the rate and minimum distance.
Worst‐case execution time analysis for a Java processor

In this paper, we propose a solution for a worst‐case execution time (WCET) analyzable Java system: a combination of a time‐predictable Java processor and a tool that performs WCET analysis at Java bytecode level. We present a Java processor, called JOP, designed for time‐predictable execution of real‐time tasks. The execution time of bytecodes, the instructions of the Java virtual machine, is known to cycle accuracy for JOP. Therefore, JOP simplifies the low‐level WCET analysis. A method cache, which fills whole Java methods into the cache, simplifies cache analysis. The WCET analysis tool is based on integer linear programming. The tool performs the low‐level analysis at the bytecode level and integrates the method cache analysis. An integrated data‐flow analysis performs receiver‐type analysis for dynamic method dispatches and loop‐bound analysis. Furthermore, a model checking approach to WCET analysis is presented where the method cache can be exactly simulated. The combination of the time‐predictable Java processor and the WCET analysis tool is evaluated with standard WCET benchmarks and three real‐time applications. The WCET friendly architecture of JOP and the integrated method cache analysis yield tight WCET bounds. Comparing the exact, but expensive, model checking‐based analysis of the method cache with the static approach demonstrates that the static approximation of the method cache is sufficiently tight for practical purposes. Copyright © 2010 John Wiley & Sons, Ltd.
Do Older Workers Lower IT-Enabled Productivity? Firm-Level Evidence from Germany By Irene Bertschek and Jenny Meyer www.druid.dk Do Older Workers Lower IT-Enabled Productivity? Firm-Level Evidence from Germany

The paper provides empirical evidence for the question whether firms’ ITenabled labour productivity is affected by the age structure of the workforce. We apply a production function approach with heterogenous labour to firmlevel data from German manufacturing and services industries. We find that workers older than 49 are not significantly less productive than prime age workers, whereas workers younger than 30 are significantly less productive than prime age workers. Older workers using a computer are significantly more productive than older non-computer users. The positive and significant relationship between labour productivity and IT intensity is not affected by the proportion of older workers.
Glacial reduction of the North American Monsoon via surface cooling and atmospheric ventilation

The North American Monsoon (NAM) provides critical water resources to the U.S. southwest and northwestern Mexico. Despite its importance to regional hydrology, the mechanisms that shape this monsoon are not fully understood. In this paper, we use model simulations of the Last Glacial Maximum (LGM, 21 ka B.P.) to assess the sensitivity of the NAM to glacial boundary conditions and shed light on its fundamental dynamics. We find that atmospheric changes induced by ice sheet albedo reduce NAM intensity at the LGM. The high albedo of the Laurentide ice sheet cools the surface and drives anomalous northwesterly winds that reduce the monsoon circulation and import cold, dry air into the core NAM region. Our work emphasizes the role of ice sheet albedo rather than topography in driving the atmospheric changes that modulate the glacial NAM, and ties our understanding of the NAM to broader theories of monsoon systems.
Wavelet analysis-based projection pursuit autoregression model and its application in the runoff forecasting of Li Xiangjiang basin

ABSTRACT The wavelet analysis technique was combined in this study with the projection pursuit autoregression (PPAR) model, and a new mid- and long-term runoff forecasting model, the wavelet analysis-based PPAR (PPAR-WA) is proposed, which realizes runoff forecasting from the perspective of the internal mechanism of a sequence. The runoff forecasting of the leading hydropower station in the Li Xianjiang cascade reservoirs in China was carried out to test the performance of the proposed model, and the accuracy and stability of the forecasting results were evaluated and analysed. The results show that the average relative error of the forecasting period can reach 9.6%, and the best relative error is less than 5% in some years. In addition, compared with PPAR, a back-propagation neural network and autoregression moving average model through three evaluation indexes, the results of PPAR-WA have higher accuracy and stronger stability. So, it has a certain value of popularization and application.
in Computer

—There are numerous attacks taking place at MAC layer in both wired and wireless networks at exuberant rate because this layer is very sensitive and most compromised layer in connectivity. So as a result of that many Intrusion Detection Systems have also come in existence from a long time till now for the detection of number of vulnerable attacks. Intrusion Detection Systems (IDS) are the tools and techniques which analyze and detect the abnormal data patterns coming from the unauthorized network. These abnormal patterns are known as attacks which are send through the intruder to harm as well as gain the confidential information. In this paper we are discussing the ARP Spoofing attack taking place at MAC layer which is affecting the propagation of data the most and soiling the resources at surplus level. In addition to that our proposed work illustrates the scenarioof hybrid network. In the process of intrusion detection we mean that whenever attack is occurred, in a network, it should be detected. Basically detection process is done by the Authenticated Token. In the current paper we have presented the Authenticated Token field used with ARP. We have presented that attack has been cancelled if the node has no information for Authenticated Token Field.