Miracle-dz/UniFAR-FTUs huggingface dataset:
S0021859618000618jra 547..556

A collection of 45 isolates was created based on bacteria isolated from maize, broad bean, wheat, rye and wild plants such as horsetail and burdock. The aim of the current study was to isolate the bacteria, and then identify and assess the degree of genomic diversity. The molecular identification of microsymbionts isolated from the endosphere (root and stem) of plants grown in agricultural soils was performed using 16S rRNA gene sequencing. To evaluate the genomic diversity between strains that occurred in multiple host plants, 18 bacterial isolates representing four species were subjected to denaturing gradient gel electrophoresis. The 16S rDNA analysis assigned all bacterial isolates to ten genera, from which Rhizobium was represented by 19 isolates, Delftia by 11, Agrobacterium by five, Stenotrophomonas by three, Brevundimonas by two and Novosphingobium, Variovorax, Collimonas, Achromobacter and Comamonas by only one isolate. Furthermore, the genomic diversity of the 11 isolates of Delftia sp. was assessed using the BOX – polymerase chain reaction (BOX-PCR) and enterobacterial repetitive intergenic consensus – PCR (ERIC-PCR) methods. Typing patterns and analysis using BOX-PCR and ERIC-PCR data demonstrated similarities among the tested isolates. In general, the results obtained with BOX-PCR and ERIC-PCR were in good agreement. However, a greater degree of differentiation patterns of the genomic DNA was obtained in the ERIC-PCR method.
Strategies for Visuospatial Reasoning: Experiments in Suf ﬁ ciency and Diversity

In this paper, we present the Visuospatial Reasoning Environment for Experimentation (VREE). VREE provides a simulated environment where intelligent agents interact with virtual objects while solving different visuospatial reasoning tasks. This paper shows how VREE is valuable for studying the suf ﬁ ciency of visual imagery approaches for a large number of visuospatial reasoning tasks as well as how diverse strategies can be represented and studied within a single task. We present results from computational experiments using VREE on the block design task and on numerous subtests from the Leiter-R test battery on nonverbal intelligence
Current applications and prospects of nanoparticles for antifungal drug delivery

Currently, the significance of fungi as human pathogens is not medically concealed in the world. Consequently, suitable recognition and treatment of such infections are of great importance and necessitate the need for comprehensive information in this regard. The introduction of new antifungals and their use today, especially in the last two decades, have revolutionized the treatment of fungal infections. On the other hand, increasing drug resistance in the world has overshadowed such developments. The use of NPs results in the treatment of fungal infections and owing to their specific properties, these particles, unlike the pure antibiotics, can exert a greater inhibitory power although with less concentration compared with conventional drugs. Important reasons that have led to the use of antifungal drugs in delivery systems include reduced drug efficacy, limited penetration through tissue, poor aqueous solubility, decreased bioavailability, and poor drug pharmacokinetics. It is therefore hoped that unfavorable properties of antifungal drugs be mitigated via their incorporation into different types of NPs. This review summarizes the different types of NPs as delivery systems of antifungal as well as their advantages over pure drugs.
Adaptive Entry Point Discovery for Web Vulnerability Scanning

Entry point collection is crucial to web vulnerability scanning since the collected entry points may contain serious web vulnerabilities such as SQL injection and Cross-Site Scripting (XSS). Most Web Vulnerability Scanners (WVSs) are equipped with crawlers to collect and locate the web pages for testing. The crawlers are intended to discover all links of the web applications being tested. However, exhaustive crawling may not be feasible when time and computation resources are limited, especially for large websites with rapidly and dynamically generated new content. Research studies regarding generic selection policies for web crawlers have been attempted. However, these studies are neither suitable for the search of entry points, nor for WVSs given that their selection policies are intended for content comparison, not for maximizing the test coverage and diversity of functionalities. In this paper, an adaptive entry point crawler named VulCrawl is proposed for WVSs to discover web pages distinct in terms of functionality and code-wise structure. VulCrawl extends the entry point collection and improves WVS code coverage of a target web application. The effectiveness and efficiency of VulCrawl are evaluated using two famous websites. In the experiments, VulCrawl found 2 to 3 times more distinct entry points than those crawled by the web crawler without adopting the adaptive entry point crawling. The results indicate that the proposed selection policy enables web crawling to discover more entry points suitable for WVSs.
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis

This paper investigates a model-free algorithm of broad interest in reinforcement learning, namely, Q-learning. Whereas substantial progress had been made toward understanding the sample efficiency of Q-learning in recent years, it remained largely unclear whether Q-learning is sample-optimal and how to sharpen the sample complexity analysis of Q-learning. In this paper, we settle these questions: (1) When there is only a single action, we show that Q-learning (or, equivalently, TD learning) is provably minimax optimal. (2) When there are at least two actions, our theory unveils the strict suboptimality of Q-learning and rigorizes the negative impact of overestimation in Q-learning. Our theory accommodates both the synchronous case (i.e., the case in which independent samples are drawn) and the asynchronous case (i.e., the case in which one only has access to a single Markovian trajectory).
The Rise and Fall of Fake News sites: A Traffic Analysis

Over the past decade, we have witnessed the rise of misinformation on the Internet, with online users constantly falling victims of fake news. A multitude of past studies have analyzed fake news diffusion mechanics and detection and mitigation techniques. However, there are still open questions about their operational behavior such as: How old are fake news websites? Do they typically stay online for long periods of time? Do such websites synchronize with each other their up and down time? Do they share similar content through time? Which third-parties support their operations? How much user traffic do they attract, in comparison to mainstream or real news websites? In this paper, we perform a first of its kind investigation to answer such questions regarding the online presence of fake news websites and characterize their behavior in comparison to real news websites. Based on our findings, we build a content-agnostic ML classifier for automatic detection of fake news websites (i.e., F1 score up to 0.942 and AUC of ROC up to 0.976) that are not yet included in manually curated blacklists.
Duets: A Dataset of Reproducible Pairs of Java Library-Clients

Software engineering researchers look for software artifacts to study their characteristics or to evaluate new techniques. In this paper, we introduce Duets, a new dataset of software libraries and their clients. This dataset can be exploited to gain many different insights, such as API usage, usage inputs, or novel observations about the test suites of clients and libraries. Duets is meant to support both static and dynamic analysis. This means that the libraries and the clients compile correctly, they are executable and their test suites pass. The dataset is composed of open-source projects that have more than five stars on GitHub. The final dataset contains 395 libraries and 2,874 clients. Additionally, we provide the raw data that we use to create this dataset, such as 34,560 pom.xml files or the complete file list from 34,560 projects. This dataset can be used to study how libraries are used by their clients or as a list of software projects that successfully build. The client’s test suite can be used as an additional verification step for code transformation techniques that modify the libraries.
First-principles Calculation of the Lattice Parameters of Graphite at High Temperature and High Pressure

The lattice parameters of graphite at high temperature and high pressure were computed using ab initio density-functional theory with the generalized gradient approximation and the local density approximation respectively. Good agreement was achieved between the calculated and experimental results in lattice parameters a, with the maximum relative differences being 1.2%. Meanwhile, the calculated lattice parameters c were also reasonably consistent with the experimental results with the maximum relative difference being 8.9%. It was also found that both a and c/a increased slowly with temperature, but decreased dramatically with pressure, indicating the greater impact of pressure on the lattice parameters.
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition

Handwriting recognition is of crucial importance to both Human Computer Interaction (HCI) and paperwork digitization. In the general field of Optical Character Recognition (OCR), handwritten Chinese character recognition faces tremendous challenges due to the enormously large character sets and the amazing diversity of writing styles. Learning an appropriate distance metric to measure the difference between data inputs is the foundation of accurate handwritten character recognition. Existing distance metric learning approaches either produce unacceptable error rates, or provide little interpretability in the results. In this paper, we propose an interpretable distance metric learning approach for handwritten Chinese character recognition. The learned metric is a linear combination of intelligible base metrics, and thus provides meaningful insights to ordinary users. Our experimental results on a benchmark dataset demonstrate the superior efficiency, accuracy and interpretability of our proposed approach.
Variable-Length Sparse Feedback Codes for Point-to-Point, Multiple Access, and Random Access Channels

This paper investigates variable-length stop-feedback codes for memoryless channels in point-to-point, multiple access, and random access communication scenarios. The proposed codes employ <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> decoding times <inline-formula> <tex-math notation="LaTeX">$n_{1}, n_{2}, {\dots }, n_{L}$ </tex-math></inline-formula> for the point-to-point and multiple access channels and <inline-formula> <tex-math notation="LaTeX">$KL + 1$ </tex-math></inline-formula> decoding times for the random access channel with at most <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> active transmitters. In the point-to-point and multiple access channels, the decoder uses the observed channel outputs to decide whether to decode at each of the allowed decoding times <inline-formula> <tex-math notation="LaTeX">$n_{1}, {\dots }, n_{L}$ </tex-math></inline-formula>, at each time telling the encoder whether or not to stop transmitting using a single bit of feedback. In the random access scenario, the decoder estimates the number of active transmitters at time <inline-formula> <tex-math notation="LaTeX">$n_{0}$ </tex-math></inline-formula> and then chooses among decoding times <inline-formula> <tex-math notation="LaTeX">$n_{k, 1}, {\dots }, n_{k, L}$ </tex-math></inline-formula> if it believes that there are <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> active transmitters. In all cases, the choice of allowed decoding times is part of the code design; given fixed value <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>, allowed decoding times are chosen to minimize the expected decoding time for a given codebook size and target average error probability. The number <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> in each scenario is assumed to be constant even when the blocklength is allowed to grow; the resulting code therefore requires only sparse feedback. The central results are asymptotic approximations of achievable rates as a function of the error probability, the expected decoding time, and the number of decoding times. A converse for variable-length stop-feedback codes with uniformly-spaced decoding times is included for the point-to-point channel.
Towards Automated Metamorphic Test Identification for Ocean System Models

Metamorphic testing seeks to verify software in the absence of test oracles. Our application domain is ocean system modeling, where test oracles rarely exist, but where symmetries of the simulated physical systems are known. The input data set is large owing to the requirements of the application domain.This paper presents work in progress for the automated generation of metamorphic test scenarios using machine learning. We extended our previously proposed method [1] to identify metamorphic relations with reduced computational complexity. Initially, we represent metamorphic relations as identity maps. We construct a cost function that minimizes for identifying a metamorphic relation orthogonal to previously found metamorphic relations and penalize for the identity map. A machine learning algorithm is used to identify all possible metamorphic relations minimizing the defined cost function. We propose applying dimensionality reduction techniques to identify attributes in the input which have high variance among the identified metamorphic relations. We apply mutation on these selected attributes to identify distinct metamorphic relations with reduced computational complexity. For experimental evaluation, we subject the two implementations of an ocean-modeling application to the proposed method to present the use of metamorphic relations to test the two implementations of this application.
Understanding Barriers to Internal Startups in Large Organizations: Evidence from a Globally Distributed Company

Large global companies need to speed up their innovation activities to increase competitive advantage. However, such companies’ organizational structures impede their ability to capture trends they are well aware of due to bureaucracy, slow decision-making, distributed departments, and distributed processes. One way to strengthen the innovation capability is through fostering internal startups. We report findings from an embedded multiple-case study of five internal startups in a globally distributed company to identify barriers for software product innovation: late involvement of software developers, executive sponsor is missing or not clarified, yearly budgeting and planning, unclear decision-making authority, lack of digital infrastructure for experimentation and access to data from external actors. Drawing on the framework of continuous software engineering proposed by Fitzgerald and Stol, we discuss the role of BizDev in software product innovation. We suggest that lack of continuity, rather than the lack of speed, is an ultimate challenge for internal startups in large global companies.
Dry deposition of particles: Implications and recommendations for mapping of deposition over Europe

This paper assesses current knowledge about the dry deposition of particles with a focus on implications for Europe. General aspects of sources, physical characteristics and concentration data of particles in the atmosphere are considered. Current modelling approaches for calculating the dry deposition of small and coarse particles are reviewed. Shortcomings and uncertainties of these models are presented. Measurements of small- and large-particle deposition with various techniques are summarized together with their limitations. Finally, implications of scale aspects of particle dry deposition are treated with an emphasis on Europe. The overall conclusion is that knowledge on particle dry deposition is still insufficient, both experimentally and theoretically, undermining reliable estimates of deposition fluxes over Europe.
Accuracy Gains from Privacy Amplification Through Sampling for Differential Privacy

Recent research in differential privacy demonstrated that (sub)sampling can amplify the level of protection. For example, for $\epsilon$-differential privacy and simple random sampling with sampling rate $r$, the actual privacy guarantee is approximately $r\epsilon$, if a value of $\epsilon$ is used to protect the output from the sample. In this paper, we study whether this amplification effect can be exploited systematically to improve the accuracy of the privatized estimate. Specifically, assuming the agency has information for the full population, we ask under which circumstances accuracy gains could be expected, if the privatized estimate would be computed on a random sample instead of the full population. We find that accuracy gains can be achieved for certain regimes. However, gains can typically only be expected, if the sensitivity of the output with respect to small changes in the database does not depend too strongly on the size of the database. We only focus on algorithms that achieve differential privacy by adding noise to the final output and illustrate the accuracy implications for two commonly used statistics: the mean and the median. We see our research as a first step towards understanding the conditions required for accuracy gains in practice and we hope that these findings will stimulate further research broadening the scope of differential privacy algorithms and outputs considered.
Phosphorus-Sorption Characteristics and Phosphorus Buffer Coefficients of Some Important Soils in Lao PDR

An estimated 97 percent of the soils in Laos are characterized by low phosphorus (P). This characteristic, together with high acidity, constrains food crop production. The P status, sorption, and associated properties were evaluated for fifteen important agricultural soils from the uplands. Soil pH values ranged from 4.5 to 5.9. Soil organic carbon (C) varied from 7.0 to 22.9 g kg−1. Soil clay varied from 179 to 709 g kg−1. The cation exchange capacity (CEC) also varied from 4.30 to 32.1 cmolc kg−1. Extractable P levels of thirteen of the fifteen soils were P deficient with medium to very high P sorption, indicating substantial fertilizer P requirements. Dithionite and oxalate aluminum and iron predicted P sorbed at 0.2 mg P L−1. The extractable P increase per unit added P, P buffer coefficient (PBC), was low, also indicating high P sorption. Field studies are needed to confirm predictions of P requirements.
Moroccan Dialect -Darija- Open Dataset

Darija Open Dataset (DODa) is an open-source project for the Moroccan dialect. With more than 10,000 entries DODa is arguably the largest open-source collaborative project for Darija-English translation built for Natural Language Processing purposes. In fact, besides semantic categorization, DODa also adopts a syntactic one, presents words under different spellings, offers verb-to-noun and masculine-to-feminine correspondences, contains the conjugation of hundreds of verbs in different tenses, and many other subsets to help researchers better understand and study Moroccan dialect. This data paper presents a description of DODa, its features, how it was collected, as well as a first application in Image Classification using ImageNet labels translated to Darija. This collaborative project is hosted on GitHub platform under MIT's Open-Source license and aims to be a standard resource for researchers, students, and anyone who is interested in Moroccan Dialect
AndroidCompass: A Dataset of Android Compatibility Checks in Code Repositories

Many developers and organizations implement apps for Android, the most widely used operating system for mobile devices. Common problems developers face are the various hardware devices, customized Android variants, and frequent updates, forcing them to implement workarounds for the different versions and variants of Android APIs used in practice. In this paper, we contribute the Android Compatibility checkS dataSet (AndroidCompass) that comprises changes to compatibility checks developers use to enforce workarounds for specific Android versions in their apps. We extracted 80,324 changes to compatibility checks from 1,394 apps by analyzing the version histories of 2,399 projects from the F-Droid catalog. With AndroidCompass, we aim to provide data on when and how developers introduced or evolved workarounds to handle Android incompatibilities. We hope that AndroidCompass fosters research to deal with version incompatibilities, address potential design flaws, identify security concerns, and help derive solutions for other developers, among others—helping researchers to develop and evaluate novel techniques, and Android app as well as operating-system developers in engineering their software.
Improved Constructions for Secure Multi-Party Batch Matrix Multiplication

This paper investigates the problem of Secure Multi-party Batch Matrix Multiplication (SMBMM), where a user aims to compute the pairwise products <inline-formula> <tex-math notation="LaTeX">$\mathbf {A}\divideontimes \mathbf {B}\triangleq (\mathbf {A}^{(1)}\mathbf {B}^{(1)},\ldots,\mathbf {A}^{(M)}\mathbf {B}^{(M)})$ </tex-math></inline-formula> of two batch of massive matrices <inline-formula> <tex-math notation="LaTeX">$\mathbf {A}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\mathbf {B}$ </tex-math></inline-formula> that are generated from two sources, through <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> honest but curious servers which share some common randomness. The matrices <inline-formula> <tex-math notation="LaTeX">$\mathbf {A}$ </tex-math></inline-formula> (resp. <inline-formula> <tex-math notation="LaTeX">$\mathbf {B}$ </tex-math></inline-formula>) must be kept secure from any subset of up to <inline-formula> <tex-math notation="LaTeX">$X_{\mathbf {A}}$ </tex-math></inline-formula> (resp. <inline-formula> <tex-math notation="LaTeX">$X_{\mathbf {B}}$ </tex-math></inline-formula>) servers even if they collude, and the user must not obtain any information about <inline-formula> <tex-math notation="LaTeX">$(\mathbf {A},\mathbf {B})$ </tex-math></inline-formula> beyond the products <inline-formula> <tex-math notation="LaTeX">$\mathbf {A}\divideontimes \mathbf {B}$ </tex-math></inline-formula>. A novel computation strategy for single secure matrix multiplication problem (i.e., the case <inline-formula> <tex-math notation="LaTeX">$M=1$ </tex-math></inline-formula>) is first proposed, and then is generalized to the strategy for SMBMM by means of cross subspace alignment. The SMBMM strategy focuses on the tradeoff between recovery threshold (the number of successful computing servers that the user needs to wait for), system cost (upload cost, the amount of common randomness, and download cost) and system complexity (encoding, computing, and decoding complexities). Notably, compared with the known result by Chen <italic>et al.</italic>, the strategy for the degraded case <inline-formula> <tex-math notation="LaTeX">$X= X_{\mathbf {A}}=X_{\mathbf {B}}$ </tex-math></inline-formula> achieves better recovery threshold, amount of common randomness, download cost and decoding complexity when <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> is less than some parameter threshold, while the performance with respect to other measures remain identical.