Miracle-dz/UniFAR-FTUs huggingface dataset:
Meces: Latency-efficient Rescaling via Prioritized State Migration for Stateful Distributed Stream Processing Systems

Stateful distributed stream processing engines (SPEs) usually call for dynamic rescaling due to varying workloads. How-ever, existing state migration approaches suffer from latency spikes, or high resource usage, or major disruptions as they ig-nore the order of state migration during rescaling. This paper reveals the importance of state migration order to the latency performance in SPEs. Based on that, we propose Meces, an on-the-fly state migration mechanism which prioritizes the state migration of hot keys (those being processed or about to be processed by downstream operator tasks) to achieve smooth rescaling. Meces leverages a fetch-on-demand design which migrates operator states at record-granularity for state consistency. We further devise a hierarchical state data structure and gradual strategy for migration efficiency. Meces is implemented on Apache Flink and evaluated with diversified benchmarks and scenarios. Compared to state-of-the-art approaches, Meces improves stream processing performance in terms of latency and throughput during rescaling by orders of magnitude, with negligible overhead and no disruption to non-rescaling periods. Abstract Meces is implemented on Apache Flink. It also relies on Kafka and Redis to function properly. We prepare the pro-grams, assemble a workflow of Meces and package the artifact into a Docker image.
Strategy and artificial intelligence

: Given the rapid development over the past decade of methods qualified as “artificial intelligence” (AI), questions arise about how these methods might fit into a firm’s strategies, or even replace them. This view overlooks the aspects of strategy-making that are marked with a high degree of uncertainty and many an ambiguity. The limitation inherent in building tools for decision-making that massively rely on sets of data restricts somewhat the possibilities. Although it is unlikely that AI will eventually steer a firm’s strategic decisions, its use in corporate strategies is already a reality that is modifying the architecture of resources and qualifications within firms. This new architecture of the creation of value requires an internal reorganization for it to be deployed in business process strategies. Given the nature of the decisions automated by AI, it is imperative for firms to set up a body of governance that will define the doctrine for using such a technology.
Xponge: A Python package to perform pre- and post-processing of molecular simulations

Xponge is a lightweight and easy to customize Python package to perform preand postprocessing of molecular simulations. It is mainly designed for the MD program SPONGE (Huang et al., 2022), but it can also process common format files and therefore it should also be useful for other simulation packages such as GROMACS (Abraham et al., 2015) and LAMMPS (Thompson et al., 2022). Xponge includes three major categories of functionality, namely, the simulation system construction, simulation data transformation and analysis, and automated workflows for complex simulations. For the construction of simulation systems, Xponge can generate 3-dimensional molecular structures or read structures downloaded from online databases such as RCSB (Berman et al., 2000) and PubChem (Sayers et al., 2021), and perform force field parameterization. The current force fields supported by Xponge include CHARMM27 (MacKerell et al., 1998; Mackerell Jr. et al., 2004), ff14SB (Maier et al., 2015), ff19SB (Tian et al., 2020) for proteins, lipid14 (Dickson et al., 2014) and lipid17 for lipids, GAFF (Wang et al., 2004) for small organic molecules and SPC/E (Berendsen et al., 1987), TIP3P (Jorgensen et al., 1983), TIP4P-Ew (Horn et al., 2004), OPC (Izadi et al., 2014) for water. Simulation data transformation is the process of changing the format, structure, or values of the simulation data such as molecular dynamics trajectories and coordinates from any frame of a simulation. For both simulation data transformation and analysis, Xponge is combined with the Python package MDAnalysis (Gowers et al., 2016; Michaud-Agrawal et al., 2011) for processing. Xponge has an integrated workflow for free energy perturbation calculations with dual topology construction, facilitating calculations on hydration and binding free energies. At the same time, Xponge itself is highly modular and easily customizable, enabling simple extensions that mimic existing modules to develop one’s own force fields, data analytics, and workflows.
The assimilation of horizontal line‐of‐sight wind information into the ECMWF data assimilation and forecasting system. Part II: The impact of degraded wind observations

Single‐component wind observations have been assimilated into the ECMWF data assimilation system. Various Observing System Experiments have been performed in order to estimate the impact of such information in numerical weather prediction. The investigations on the impact of the horizontal line‐of‐sight wind on the ECMWF analysis and forecast system is described in a two‐part article. Part I evaluates the impact of wind observations with respect to mass observations and the impact of assimilating different single wind components versus wind vector information. Part II assesses the forecast system performance in the presence of varying levels of random and systematic error in the line‐of‐sight wind measurements. The aim is to understand the sensitivity of weather forecasts with respect to possible observation error scenarios of the Doppler Wind Lidar (DWL) measurements from the Aeolus mission. It was found that even small wind observation biases (of the order of 1 m s−1) can deteriorate the forecast quality by 3–4% in terms of mean integrated total energy of the 24 h forecast error. This is particularly true for observation biases in the Tropics, in the upper troposphere and lower stratosphere. A 2 m s−1 bias degrades the forecasts by 15%. The increase of the line‐of‐sight random errors (from 25 to 100%) adds only 1–2% forecast skill degradation.
The convergence of a neuromuscular impulse response towards a lognormal, from theory to practice

Lognormal functions have been found among the best descriptors of the impulse response of neuromuscular systems under various experimental conditions. This arises from the fact that lognormal patterns automatically emerge when a large number of coupled systems interact to produce a response. This paper evaluates the error of convergence towards a lognormal. Under the umbrella of the Central Limit Theorem, the error functions for lognormal and delta-lognormal equations are derived and analyzed. It is shown that these errors can be computed from the estimated values of the lognormal parameters, without any explicit reference to the number of subsystems involved. The resulting theoretical framework is then exploited in three applications: the comparative benchmarking of parameter extraction algorithms, the validation of the results in analysis-by-synthesis experiments and the estimation of the range of acceptable movement times in tests involving rapid movements.
A proposed update to the solar irradiance spectrum used in LOWTRAN and MODTRAN

The calibrated upwelling radiance spectra measured by AVIRIS are increasingly being analyzed with radiative transfer codes. Analysis of AVIRIS data with the LOWTRAN and MODTRAN radiative transfer codes has led to indications of an error in the solar irradiance spectra used by these codes. This paper presents evidence for the error and proposed update to the solar irradiance spectra used by LOWTRAN and MODTRAN.
Building an Interoperable Distributed Image Database Management System

The DISIMA project addresses the development of a distributed, interoperable image database management system enabling content-based querying. The aim of this project is to add an interoperability feature to the existing prototype. As object-oriented distributed computing platforms, OMA and, in particular, CORBA, can be helpful for database interoperability in terms of managing heterogeneity of platform and communication levels. The complete distributed architecture will involve homogeneous systems and heterogeneous systems. In this project, the goal is to develop a middleware on top of CORBA for homogeneous systems. In the simplest scenario, we can assume all the systems involved are DISIMA sites, and that they have the same schema with different database instances. This technical report thus describes the development of such simpler (but not trivial) scenario. We also highlight and justify some design decisions made as the project was developed.
Docking-Based Virtual Screening Ascertaining β-Sitosterol-Induced Alterations in the Helicoverpa armigera Hübner Gut Enzymes

Present investigation attempts to study binding of β-sitosterol with Helicoverpa armigera midgut enzymes; alanine aminotransaminase (ALT), aspartate aminotransaminase (AST) and alkaline phosphatase (ALP); through docking-based virtual screening. Extraction of the protein sequence of the enzymes revealed a respective linear chain of 535, 522 and 430 amino acids for ALP, ALT and AST. The binding energy for ALT-ligand complex was lowest as compared to the AST and ALP-docked complexes. The ALT-docked complex had ligand efficiency of (-) 0.32 with an inhibition constant of 104.01, more hydrogen bonds and hydrophobic interactions leading to a more stable complex. However, unfavored bumps in AST and ALP complexes may have led to comparatively unstable complexes. The dietary β-sitosterol exhibits differential binding with midgut enzymes of H. armigera larvae. The strong binding of β-sitosterol with ALT indicates the highest inhibition of ALT activity due to the activity-stability trade-off. The enzymes, AST and ALP exhibited relatively higher activity as a resultant of lesser stabilization of the β-sitosterol-enzyme complex. In silico studies have indicated that β-sitosterol can be used an effective control agent against H. armigera.
Detecting Multiple Transitions in Literary Texts

Identifying the high level structure of texts provides important information when performing distant reading analysis. The structure of texts is not necessarily linear, as transitions, such as changes in the scenery or flashbacks, can be present. As a first step in identifying this structure, we aim to identify transitions in texts. Previous work (Heyns and van Zaanen, 2021) proposed a system that can successfully identify one transition in literary texts. The text is split in snippets and LDA is applied, resulting in a sequence of topics. A transition is introduced at the point that separates the topics (before and after the point) best. In this article, we extend the existing system such that it can detect multiple transitions. Additionally, we introduce a new system that inherently handles multiple transitions in texts. The new system also relies on LDA information, but is more robust than the previous system. We apply these systems to texts with known transitions (as they are constructed by concatenating text snippets stemming from different source texts) and evaluation both systems on texts with one transition and texts with two transitions. As both systems rely on LDA to identify transitions between snippets, we also show the impact of varying the number of LDA topics on the results as well. The new system consistently outperforms the previous system, not only on texts with multiple transitions, but also on single boundary texts.
EVALUATION ON TURBULENT MODEL IN LARGE EDDY SIMULATION OF TURBULENT FLOW AROUND A WALL-MOUNTED CUBE IN A CHANNEL

In engineering application of large eddy simulation, there are still questions as follows grid dependency on numerical results, the effect of upwind scheme against a calculation instability, appropriate boundary conditions dealing with turbulence fluctuation and the performance of SGS models. In this study, in order to develop the LES to the engineering application, large eddy simulation was carried out to investigate the effect of upwind scheme, turbulent subgrid model and the grid dependancy of the flow around a wall-mounted cube in a channel at Re=40,000 based on cubic height and bulk mean velocity. The computed velocities, turbulence quantities, separation and reattachment length were evaluated compared with the experimental results of R. Matinuzzi and C. Tropea.
Incorporating LIWC in Neural Networks to Improve Human Trait and Behavior Analysis in Low Resource Scenarios

Psycholinguistic knowledge resources have been widely used in constructing features for text-based human trait and behavior analysis. Recently, deep neural network (NN)-based text analysis methods have gained dominance due to their high prediction performance. However, NN-based methods may not perform well in low resource scenarios where the ground truth data is limited (e.g., only a few hundred labeled training instances are available). In this research, we investigate diverse methods to incorporate Linguistic Inquiry and Word Count (LIWC), a widely-used psycholinguistic lexicon, in NN models to improve human trait and behavior analysis in low resource scenarios. We evaluate the proposed methods in two tasks: predicting delay discounting and predicting drug use based on social media posts. The results demonstrate that our methods perform significantly better than baselines that use only LIWC or only NN-based feature learning methods. They also performed significantly better than published results on the same dataset.
Synthetic Data is King: How to Improve Performance in 3 . 14 × 10 2 Easy Steps

The biggest challenges for effective object detection are the resources required for image sourcing and labeling training. For a drone vs drone scenario this is especially difficult, as few videos exist where drones are filmed from the sky, and fewer are annotated. This paper seeks to address the lack of labeled data sets through an approach that combines synthetically generated data and existing data sets. It will discuss the effectiveness of various methods for generating and training on synthetic data
Face Descry System in Exams Committees

: The main objective of the proposed face descry system is to use the face in the exams committees as a password to authenticate the students during exams periods. In such places, more security is needed than only the existing of the person. Different applications for this work can be applied for example, authentication for the persons using their faces in front of ATM instead of using password and Person verification for self-serviced clearance using E-passport is another important typical application. All these application can be considered as cooperative user scenarios in which the user is willing to be cooperative by presenting his/her face in a proper way (for example, in a frontal pose with neutral expression and eyes open) in order to be granted the access or privilege. Face recognition has several advantages over other biometric modalities such as fingerprint and iris: besides being natural and nonintrusive, the most important advantage of face is that it can be captured at a distance and in a covert manner. In this paper, face recognition is used to face verification (or authentication) which involves a one-to-one match that compares a query face image against an enrollment face image whose identity is being claimed. The proposed system consists of four phases. The first phase is the pre-processing phase. The second phase is the face detection based on Viola-Jones method. The third phase is the proposed Moving Average Window conversion. The last phase is the face verification phase, in this phase the similarity between the query face image and the enrollment face image whose identity is being claimed is calculated and the decision is taken depending on two classification parameters (Structural Similarity Measure (SSIM) and Color Measurement Committee (CMC) distance. The experimental results were viewed and compared.
S2: How to use the hMRI toolbox to generate uncertainty maps, error maps, mSNR maps and robust combinations

Robust combination and two-repeat multi-parameter mapping protocol This section elaborates on the sensitivity of the robust combination to outliers and its dependence on the k-parameter of the Fermi function. Moreover, the heuristic selection criteria that was employed to determine the optimal k-parameter for this study is explained. Both are illustrated for the MTsat contrast depicted in Figure S1.1.
Effects of the low lying Dirac modes on the spectrum of ground state mesons

The lowest eigenmodes of the Dirac operator are related to the dynamical breaking of the chiral symmetry in Quantum Chromodynamics (QCD). In our work we construct quark propagators which exclude a varying number of the lowest Dirac eigenmodes and study the influence thereof on meson correlators and the meson spectrum. That procedure partially restores the chiral symmetry (in the valence sector) and we observe degeneracies in the spectrum while confinement seems not to be affected.
Light scattering by a disperse layer of closely packed two- layered spherical particles

Light scattering by natural and artificial media with a high concentration of particles has drawn the attention of researchers recently [1]. For a strict description of scattering in densely packed media it is necessary to use the theory of multiple scattering of waves (MSW) [2]. Because of the complexity and cumbersomeness of the mathematical apparatus of the MSW theory, complete solutions are obtained in rare instances. The effects caused by ordered arrangements of optically soft particles in large concentrations are referred to such instances. In the present work the interference approximation is used to study light scattering by a system of spherical particles of the core-shell type.
Remarks on the Gibbs measures for nonlinear dispersive equations

We show, by the means of several examples, how we can use Gibbs measures to construct global solutions to dispersive equations at low regularity. The construction relies on the Prokhorov compactness theorem combined with the Skorokhod convergence theorem. To begin with, we consider the non linear Schr\"odinger equation (NLS) on the tri-dimensional sphere. Then we focus on the Benjamin-Ono equation and on the derivative nonlinear Schr\"odinger equation on the circle. Next, we construct a Gibbs measure and global solutions to the so-called periodic half-wave equation. Finally, we consider the cubic 2d defocusing NLS on an arbitrary spatial domain and we construct global solutions on the support of the associated Gibbs measure.
05 09 19 7 v 1 2 8 Se p 20 05 Effective Spin Quantum Phases in Systems of Trapped Ions

A system of trapped ions under the action of off–resonant standing–waves can be used to simulate a variety of quantum spin models. In this work, we describe theoretically quantum phases that can be observed in the simplest realization of this idea: quantum Ising and XY models. Our numerical calculations with the Density Matrix Renormalization Group method show that experiments with ion traps should allow one to access general properties of quantum critical systems. On the other hand, ion trap quantum spin models show a few novel features due to the peculiarities of induced effective spin–spin interactions which lead to interesting effects like long–range quantum correlations and the coexistence of different spin phases.
Unzipping graphene: Extendend defects by ion irradiation

Many of the proposed future applications of graphene require the controlled introduction of defects into its perfect lattice. Energetic ions provide one way of achieving this challenging goal. Single heavy ions with kinetic energies in the 100 MeV range will produce nanometer-sized defects on dielectric but generally not on crystalline metal surfaces. In a metal the ion-induced electronic excitations are efficiently dissipated by the conduction electrons before the transfer of energy to the lattice atoms sets in. Therefore, graphene is not expected to be irradiation sensitive beyond the creation of point defects. Here we show that graphene on a dielectric substrate sustains major modifications if irradiated under oblique angles. Due to a combination of defect creation in the graphene layer and hillock creation in the substrate, graphene is split and folded along the ion track yielding double layer nanoribbons. Our results indicate that the radiation hardness of graphene devices is questionable but also open up a new way of introducing extended low-dimensional defects in a controlled way.
High precision measurement of surface cracks using an optical system

In this contribution an advanced technique to measure the width of surface cracks in concrete is presented. The goal is to provide a system for laboratory applications with a high resolution in order to be able to estimate the stabilization of surface cracks in the range of 0–250 µm during laboratory loading tests. Using digital imaging and suitable image processing algorithms, an automated system for the determination of crack widths was developed. A 4 megapixel monochrome digital camera was used in combination with a special telecentric lens, in order to achieve a resolution of 1 µm per pixel. The main challenge in this work was to develop a robust image processing algorithm, which determines the surface crack width under changing environmental conditions, especially in terms of ambient light.
A semiparametric frequency domain approach of modelling the real output with fractional integration

We propose in this article the use of the Quasi Maximum Likelihood Estimate of Robinson (QMLE, 1995a) for estimating the fractional differencing parameter in the real output and in the growth rate series of France, Italy and the U.K. This method is semiparametric and is robust to the different types of I(0) disturbances. The results indicate that the orders of integration of the real output are, in the three series, higher than 1 but smaller than 1.5, implying that their first differences are stationary but with long memory behaviour. However, the growth rates appear to be I(0) for the three countries. This may appear contradictory at first sight but it is explained by the non-linear log-transform involved. As a conclusion, the results show that the log-transformed series should be the data used in a multivariate framework when relating the real output with other variables in a cointegrating system.
Lorentzian Beltrami-Euler formula and generalized Lorentzian Lamarle formila in R_1^n

In this paper, the sectional curvature of non-degenerate tangent sections of time-like ruled surface with the central ruled surface in n-dimensional Minkowski space, R_1^n is studied. The relationship between normal sectional curvature and the principal sectional curvatures of non-degenerate tangent sections of time-like ruled surfaces is obtained andcalled as Lorentzian Beltrami-Euler formula. Moreover, the relationship between the Gaussian curvature and the principal distribution parameter of the non-degenerate tangent sections of time-like ruled surfaces is obtained and called as generalized Lorentzian Lamarle formula.
American Option Valuation: New Bounds, Approximations, and a Comparison of Existing Methods

We develop lower and upper bounds on the prices of American call and put options written on a dividend-paying asset. We provide two option price approximations, one based on the lower bound (termed LBA) and one based on both bounds (termed LUBA). The LUBA approximation has an average accuracy comparable to a 1,000-step binomial tree with a computation speed comparable to a 50-step binomial tree. We introduce a modification of the binomial method (termed BBSR) that is very simple to implement and performs remarkable well. We also conduct a careful large-scale evaluation of many recent methods for computing American option prices. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.