Miracle-dz/UniFAR-FTUs huggingface dataset:
zkay v0.2: Practical Data Privacy for Smart Contracts

Recent work introduces zkay, a system for specifying and enforcing data privacy in smart contracts. While the original prototype implementation of zkay (v0.1) demonstrates the feasibility of the approach, its proof-of-concept implementation suffers from severe limitations such as insecure encryption and lack of important language features. In this report, we present zkay v0.2, which addresses its predecessor's limitations. The new implementation significantly improves security, usability, modularity, and performance of the system. In particular, zkay v0.2 supports state-of-the-art asymmetric and hybrid encryption, introduces many new language features (such as function calls, private control flow, and extended type support), allows for different zk-SNARKs backends, and reduces both compilation time and on-chain costs.
Integrating sibship data for mapping quantitative trait loci

Sibship methods have been shown to be more powerful than traditional sib‐pair methods in mapping quantative trait loci. We propose a statistical procedure which integrates data on sibships into a so‐called ‘contrast function’, a natural extension of the classical squared sib‐pair trait difference proposed by Haseman & Elston (1972). We also develop a combined mean and contrast function which provides more information on linkage compared to the contrast function. Our method is extended to multiple, epistatically interacting trait loci. Monte‐Carlo simulations are included to compare the efficiencies of the proposed procedures with some currently used methods. An application of our proposed method is presented using data on alcohol dependence.
Does scarring prevent ergodicity

Classically chaotic systems are ergodic, that is after a long time, any trajectory will be arbitrarily close to any point of the available phase space, filling it uniformly. Using Born's rules to connect quantum states with probabilities, one might then expect that all chaotic quantum states should be uniformly distributed in phase space. This simplified picture was shaken by the discovery of quantum scarring, where some eigenstates are concentrated along unstable periodic orbits. Despite of that, it is consensus that most eigenstates of chaotic models are indeed ergodic. Our results show instead that all eigenstates of the chaotic Dicke model are actually scarred. Even the most random states of this interacting atom-photon system never occupy more than half of the available phase space. Quantum ergodicity is achieved only as an ensemble property, after temporal averages are performed covering the phase space.
Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

L'analyse predictive permet d'estimer les tendances des evenements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes predictions. Cependant, pour chaque type de probleme donne, il est necessaire de choisir l'architecture optimale. Dans cet article, les modeles Stack-LSTM, CNN-LSTM et ConvLSTM sont appliques a une serie temporelle d'images radar sentinel-1, le but etant de predire la prochaine occurrence dans une sequence. Les resultats experimentaux evalues a l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarite SSIM, montrent que chacune des trois architectures peut produire de bons resultats en fonction des parametres utilises.
Privacy-Preserving Distributed Processing: Metrics, Bounds and Algorithms

Privacy-preserving distributed processing has recently attracted considerable attention. It aims to design solutions for conducting signal processing tasks over networks in a decentralized fashion without violating privacy. Many existing algorithms can be adopted to solve this problem such as differential privacy, secure multiparty computation, and the recently proposed distributed optimization based subspace perturbation algorithms. However, since each of them is derived from a different context and has different metrics and assumptions, it is hard to choose or design an appropriate algorithm in the context of distributed processing. In order to address this problem, we first propose general mutual information based information-theoretical metrics that are able to compare and relate these existing algorithms in terms of two key aspects: output utility and individual privacy. We consider two widely-used adversary models, the passive and eavesdropping adversary. Moreover, we derive a lower bound on individual privacy which helps to understand the nature of the problem and provides insights on which algorithm is preferred given different conditions. To validate the above claims, we investigate a concrete example and compare a number of state-of-the-art approaches in terms of the concerned aspects using not only theoretical analysis but also numerical validation. Finally, we discuss and provide principles for designing appropriate algorithms for different applications.
Syntheses of Isobornyl Acetate Catalyzed by MoO_3/ZrO_2

Esterification of camphene with acetic acid catalyzed by home-made MoO_3/ZrO_2 solid superacid was studied.Main factors affecting the reaction were investigated.The effect of temperature,calcinations temperature of catalyst,amount of catalyst,reaction time and the amount of acetic acid on the products was examined.The suitable experiment conditions for the esterification reaction were as follows: acetic acid dosage was 150%(mol percent of camphene),catalyst dosage was 4%(weight percent of camphene),the calcination temperature of catalyst was 700 ℃,the reaction temperature was 80℃,the reaction time was 8 hours.The yield of the main product isobornyl acetate reached 74.7%.
Skyrmion-antiskyrmion droplets in a chiral ferromagnet

We find numerically skyrmionic textures with skyrmion number Q = 0 in ferromagnets with the Dzyaloshinskii-Moriya interaction and perpendicular anisotropy. These have the form of a skyrmionantiskyrmion pair and may be called chiral droplets. They are stable in an infinite film as well as in disc-shaped magnetic elements. Droplets are found for values of the parameters close to the transition from the ferromagnetic to the spiral phase. We study their motion under spin-transfer torque. They move in the direction of the spin flow and, thus, their dynamics are drastically different than the Hall dynamics of the standard Q = 1 skyrmion.
Closure under Coupling of Cellular-DEVS for the Optimization of Memory Resource: Wildfire Spread Case Study

The present work aims to show one of the advantages of using the property of closure under coupling in the DEVS specification. The advantage concerned in this paper attempts to address the need for memory resources during the simulation of systems by cellular-DEVS. This improvement of performance is based on the usage of the property closure under coupling in the DEVS formalism. With this property and taking account of the iterative behavior of each cellular-DEVS atomic model, we provide simulation of many models simultaneously. The method starts with the specification of the cellular-DEVS coupled model which is then converted into its equivalent DEVS atomic model. Thus, the goal of this conversion is to transform large quantities of atomic models coupled together, which require huge computational resources, into one DEVS atomic model. A case study is presented at the end of the work on modeling and simulation of forest fire propagation using DEVS and cellular-DEVS. A specification by cellular-DEVS of the forest fire model and its non-modular equivalent DEVS atomic model are presented. Finally, a comparison between both methods is presented in term of consumption of resources.
3D Facial Geometry Recovery from a Depth View with Attention Guided Generative Adversarial Network

We present to recover the complete 3D facial geometry from a single depth view by proposing an Attention Guided Generative Adversarial Networks (AGGAN). In contrast to existing work which normally requires two or more depth views to recover a full 3D facial geometry, the proposed AGGAN is able to generate a dense 3D voxel grid of the face from a single unconstrained depth view. Specifically, AGGAN encodes the 3D facial geometry within a voxel space and utilizes an attention-guided GAN to model the illposed 2.5D depth-3D mapping. Multiple loss functions, which enforce the 3D facial geometry consistency, together with a prior distribution of facial surface points in voxel space are incorporated to guide the training process. Both qualitative and quantitative comparisons show that AGGAN recovers a more complete and smoother 3D facial shape, with the capability to handle a much wider range of view angles and resist to noise in the depth view than conventional methods
Symmetric orbifold theories from little string residues

We study a class of Little String Theories (LSTs) of A type, described by $N$ parallel M5-branes spread out on a circle and which in the low energy regime engineer supersymmetric gauge theories with $U(N)$ gauge group. The BPS states in this setting correspond to M2-branes stretched between the M5-branes. Generalising an observation made in arXiv:1706.04425, we provide evidence that the BPS counting functions of special subsectors of the latter exhibit a Hecke structure in the Nekrasov-Shatashvili (NS) limit, i.e. the different orders in an instanton expansion of the supersymmetric gauge theory are related through the action of Hecke operators. We extract $N$ distinct such reduced BPS counting functions from the full free energy of the LST with the help of contour integrals with respect to the gauge parameters of the $U(N)$ gauge group. Physically, the states captured by these functions correspond to configurations where the same number of M2-branes is stretched between some of these neighbouring M5-branes, while the remaining M5-branes are collapsed on top of each other and a particular singular contribution is extracted. The Hecke structures suggest that these BPS states form the spectra of symmetric orbifold CFTs. We furthermore show that to leading instanton order (in the NS-limit) the reduced BPS counting functions factorise into simpler building blocks. These building blocks are the expansion coefficients of the free energy for $N=1$ and the expansion of a particular function, which governs the counting of BPS states of a single M5-brane with single M2-branes ending on it on either side. To higher orders in the instanton expansion, we observe new elements appearing in this decomposition, whose coefficients are related through a holomorphic anomaly equation.
CLEAR: Paschen-β Star Formation Rates and Dust Attenuation of Low-redshift Galaxies

We use Paschen-β (Paβ; 1282 nm) observations from the Hubble Space Telescope G141 grism to study the star formation and dust-attenuation properties of a sample of 29 low-redshift (z < 0.287) galaxies in the CANDELS Lyα Emission at Reionization survey. We first compare the nebular attenuation from Paβ/Hα with the stellar attenuation inferred from the spectral energy distribution, finding that the galaxies in our sample are consistent with an average ratio of the continuum attenuation to the nebular gas of 0.44, but with a large amount of excess scatter beyond the observational uncertainties. Much of this scatter is linked to a large variation between the nebular dust attenuation as measured by (space-based) Paβ to (ground-based) Hα to that from (ground-based) Hα/Hβ. This implies there are important differences between attenuation measured from grism-based/wide-aperture Paβ fluxes and the ground-based/slit-measured Balmer decrement. We next compare star formation rates (SFRs) from Paβ to those from dust-corrected UV. We perform a survival analysis to infer a census of Paβ emission implied by both detections and nondetections. We find evidence that galaxies with lower stellar mass have more scatter in their ratio of Paβ to attenuation-corrected UV SFRs. When considering our Paβ detection limits, this observation supports the idea that lower-mass galaxies experience “burstier” star formation histories. Together, these results show that Paβ is a valuable tracer of a galaxy’s SFR, probing different timescales of star formation and potentially revealing star formation that is otherwise missed by UV and optical tracers.
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models

In recent years, the proliferation of so-called “fake news” has caused much disruptions in society and weakened the news ecosystem. Therefore, to mitigate such problems, researchers have developed state-of-the-art (SOTA) models to autodetect fake news on social media using sophisticated data science and machine learning techniques. In this work, then, we ask “what if adversaries attempt to attack such detection models? ” and investigate related issues by (i) proposing a novel attack scenario against fake news detectors, in which adversaries can post malicious comments toward news articles to mislead SOTA fake news detectors, and (ii) developing Malcom, an end-to-end adversarial comment generation framework to achieve such an attack. Through a comprehensive evaluation, we demonstrate that about 94% and 93.5% of the time on average Malcom can successfully mislead five of the latest neural detection models to always output targeted real and fake news labels. Furthermore, Malcom can also fool black box fake news detectors to always output real news labels 90% of the time on average. We also compare our attack model with four baselines across two real-world datasets, not only on attack performance but also on generated quality, coherency, transferability, and robustness. We release the source code of Malcom at https://github.com/lethaiq/MALCOM1.
Covid 19 and A Wavelet Analysis of the Total Deaths per Month in Brazil since 2015.

We investigate the historical series of the total number of deaths per month in Brazil since 2015 using the wavelet transform, in order to assess whether the COVID-19 pandemic caused any change point in that series. Our wavelet analysis shows that the series has a change point in the variance. However, it occurred long before the pandemic began.
covid19.analytics: An R Package to Obtain, Analyze and Visualize Data from the Corona Virus Disease Pandemic

With the emergence of a new pandemic worldwide, a novel strategy to approach it has emerged. Several initiatives under the umbrella of "open science" are contributing to tackle this unprecedented situation. In particular, the "R Language and Environment for Statistical Computing" offers an excellent tool and ecosystem for approaches focusing on open science and reproducible results. Hence it is not surprising that with the onset of the pandemic, a large number of R packages and resources were made available for researches working in the pandemic. In this paper, we present an R package that allows users to access and analyze worldwide data from resources publicly available. We will introduce the covid19.analytics package, focusing in its capabilities and presenting a particular study case where we describe how to deploy the "COVID19.ANALYTICS Dashboard Explorer".
First record of Huarpea wagneriella (Hymenoptera: Sapygidae) as a cleptoparasite of large carpenter bees (Hymenoptera: Apidae, Xylocopinae)

ABSTRACT The species Huarpea wagneriella (Hymenoptera: Sapygidae), a cleptoparasite of nests of bees of the genera Xylocopa Latreille and Megachile Latreille (Hymenoptera: Apoidea), is reported for the first time as a cleptoparasite of Xylocopa ciliata Burmeister (Hymenoptera: Apidae) in Buenos Aires, Argentina. Biological notes on species of Xylocopa and a morphological characterization of Huarpea are given.
Seasonal Periods of Surface Inactivity of the Pocket Gopher

An ecological study of the pocket gopher ( Thomomys talpoides tenellus Goldman) made during the summer of 1952 in the Jackson Hole region of Wyoming revealed two periods of apparent inactivity of the gophers. One of the periods when no soil was brought to the surface of the ground was noted on the main floor of Jackson Hole (elevation 6,750 feet). This period was three to four weeks in duration, from the second week in August until shortly after the first week in September. Two plots had been previously laid out to measure the amount of soil brought to the surface by the gophers. Observations disclosed that only a very small amount of soil was brought to the surface of these plots during this period compared to the amount of soil in any similar period earlier in the summer. No soil at all was brought …
Face Image Quality Assessment: A Literature Survey

The performance of face analysis and recognition systems depends on the quality of the acquired face data, which is influenced by numerous factors. Automatically assessing the quality of face data in terms of biometric utility can thus be useful to detect low-quality data and make decisions accordingly. This survey provides an overview of the face image quality assessment literature, which predominantly focuses on visible wavelength face image input. A trend towards deep learning-based methods is observed, including notable conceptual differences among the recent approaches, such as the integration of quality assessment into face recognition models. Besides image selection, face image quality assessment can also be used in a variety of other application scenarios, which are discussed herein. Open issues and challenges are pointed out, i.a. , highlighting the importance of comparability for algorithm evaluations and the challenge for future work to create deep learning approaches that are interpretable in addition to providing accurate utility predictions.
Comparison of TCP Variants Over Self-Similar Traffic

Network traffic of Internet will continue to expand in terms of both volume and users, and transmission congestion protocol (TCP) is accounting for more than 90% the Internet traffic. In addition to this, it is well known that Internet traffic exhibits self-similarity, which cannot be described by traditional Markovian models such as the Poisson process. In this paper we focus on experimental quantitative comparisons of four TCP variants namely Tahoe, NewReno, Vegas, and SACK running over self-similar traffic. With the aid of network simulator, NS2, aggregated network traffic of self-similarity behavior is simulated and will act as the background traffic. The impact of one TCP microflow will be observed, and data analysis such as congestion window, round trip time, throughput, and the behavior of the data received over time is analyzed. In measuring the degree of self-similarity we employed optimization method to determine Hurst parameter. From our analysis, TCP variants tend to demonstrate self-similar traffic flow even though initially the departure rate of TCP packets is constant With respect to performance, TCP-NewReno outperform other TCP variants with higher throughput and efficacy. In addition, we have also investigate the LAN traffic behavior of FSKSM, UTM, and proved that Internet Protocol (IP) dominated the total traffic where 90% is TCP and has a Hurst value of 0.88.
Cross-Utterance Language Models with Acoustic Error Sampling

The effective exploitation of richer contextual information in language models (LMs) is a long-standing research problem for automatic speech recognition (ASR). A cross-utterance LM (CULM) is proposed in this paper, which augments the input to a standard long short-term memory (LSTM) LM with a context vector derived from past and future utterances using an extraction network. The extraction network uses another LSTM to encode surrounding utterances into vectors which are integrated into a context vector using either a projection of LSTM final hidden states, or a multi-head self-attentive layer. In addition, an acoustic error sampling technique is proposed to reduce the mismatch between training and test-time. This is achieved by considering possible ASR errors into the model training procedure, and can therefore improve the word error rate (WER). Experiments performed on both AMI and Switchboard datasets show that CULMs outperform the LSTM LM baseline WER. In particular, the CULM with a self-attentive layer-based extraction network and acoustic error sampling achieves 0.6% absolute WER reduction on AMI, 0.3% WER reduction on the Switchboard part and 0.9% WER reduction on the Callhome part of Eval2000 test set over the respective baselines.
Java Cryptography Uses in the Wild

[Background] Previous research has shown that developers commonly misuse cryptography APIs. [Aim] We have conducted an exploratory study to find out how crypto APIs are used in open-source Java projects, what types of misuses exist, and why developers make such mistakes. [Method] We used a static analysis tool to analyze hundreds of open-source Java projects that rely on Java Cryptography Architecture, and manually inspected half of the analysis results to assess the tool results. We also contacted the maintainers of these projects by creating an issue on the GitHub repository of each project, and discussed the misuses with developers. [Results] We learned that 85% of Cryptography APIs are misused, however, not every misuse has severe consequences. Developer feedback showed that security caveats in the documentation of crypto APIs are rare, developers may overlook misuses that originate in third-party code, and the context where a Crypto API is used should be taken into account. [Conclusion] We conclude that using Crypto APIs is still problematic for developers but blindly blaming them for such misuses may lead to erroneous conclusions.
The Relation Between Pyorrhea Alveolaris and H2S Producing Bacteria in Human Mouth

A medium which detects H2S produced by bacteria was newly designed by Onisi and Tachibana, being consisted of agar 2%, peptone 2%, meat extract 1%, NaCl 0.2%, sodium thiosulf ate 0.008%, sodium sulfite 0.04%, lead acetate 0.3%, glucose 0.1%, adjusted at pH 6.8. Dental scrapping from 195 apparently healthy tooth surfaces, and from 112 cavities, and pathological exudates from 150 pyorrhea pockets were inoculated in the media in order to find incidence of H2S activity of these three different categories of specimens.The positive reaction was found at 86.7% of pyorrhea specimens, at 66, 9% of cavity deposits and at 60% of healthy scrappings. The differences between pyorrhea and the rest were estimated to be significant.The positive cultures were been plated on the same medium to identify the organisms corresponding to the H2S production there in, i.e., 29 Veillonella, 7 Escherichia, 4 Bacteria, 5 Neisseria, 6 aerobic Micrococci, 2 anaerobic Micrococci, 2 Kurthia, one Corynebacteria and one Diplococcus were resulted, but neither Fusobacteria nor Treponema which may possibly major H2S producers in the pyorrhea pocket. Veillonella, the majority of the genera showing positive reaction, Gram negative rods, the most intensive producers of H2S, Fusobacteria and Treponema would be summarized to be dominant genera of H2S production in the case of pyorrhea alveolaris. As the relation between pyorrhea and bacterial hydrogen sulfide, it is considered that the reducing action of the latter may affect the keratin layer of the gingival epithelium to create the S-S linkage in it.
3+1
 formulation of the standard model extension gravity sector

We present a $3+1$ formulation of the effective field theory framework called the standard model extension in the gravitational sector. The explicit local Lorentz and diffeomorphism symmetry breaking assumption is adopted, and we perform a Dirac-Hamiltonian analysis. We show that the structure of the dynamics presents significant differences from general relativity and other modified gravity models. We explore Hamilton's equations for some special choices of the coefficients. Our main application is cosmology, and we present the modified Friedmann equations for this case. The results show some intriguing modifications to standard cosmology. In addition, we compare our results to existing frameworks and models, and we comment on the potential impact to other areas of gravitational theory and phenomenology.