Miracle-dz/UniFAR-FTUs huggingface dataset:
Australian Lasioglossum + Homalictus form a monophyletic group: resolving the "Australian enigma".

The bee genus Lasioglossum includes > 1,000 species of bees distributed on all continents except Antarctica. Lasioglossum is a major component of the bee fauna in the Holarctic, Ethiopian, and Asian regions and is an important group for investigating the evolution of social behavior in bees. Given its cosmopolitan distribution, the historical biogeography of the genus is of considerable interest. We reconstructed phylogenetic relationships among the subgenera and species within Lasioglossum s.s. , using DNA sequence data from a slowly evolving nuclear gene, elongation factor-1 alpha. The entire data set includes > 1,604 aligned nucleotide sites (including three exons plus two introns) for 89 species (17 outgroups plus 72 ingroups). Parsimony and maximum likelihood analyses provide strong evidence that the primarily Indoaustralian subgenera (Homalictus, Chilalictus, Parasphecodes) form a monophyletic group. Bootstrap support for the Australian clade ranged from 73% to 77%, depending on the method of analysis. Monophyly of the Australian Lasioglossum suggests that a single colonization event (by way of Southeast Asia and New Guinea) gave rise to a lineage of > 350 native Indoaustralian bees. We discuss the implications of Australian monophyly for resolving the "Australian enigma"--the similarity in social behavior among the Australian halictine bees relative to that of Holarctic groups.
Towards enabling privacy preserving smart city apps

Smart city applications are increasingly relying on personally identifiable data. A disclosure of such a data to a platform provider and possible 3rd parties represents a risk to the privacy of the application users. To mitigate the privacy risk, two-layer privacy-preserving platform architecture is introduced, wherein the personally identifiable information is dealt with at the inner layer (executed in a trusted environment), whereas only generic and personally unidentifiable information is made available to the apps at the outer layer of the architecture - e.g., in a form of app-specific events. The essential requirements for the platform are described, and the architectural implications of these requirements are considered in the paper. The ongoing prototype implementation and planned evaluation are discussed.
The Engineering Cost Evaluation Based on IPSO

The rough set theory was used to reduce the factors affecting construction engineering cost and optimize input variables of BP neural network. Then, the improved particle swarm algorithm with constriction factors is adopted to optimize the initial weights and thresholds. An engineering project in a city of Hunan is selected to make empirical analysis. It shows that based on the features of engineering, this new model enjoys a high practical value as it can be applied to make scientific evaluation of costs of construction engineering.
Women's responses to screening for domestic violence in a health-care setting.

BACKGROUND interest in the health impact of domestic violence is increasing and routine screening for violence in health settings has been recommended. However, there are limited data about how women feel about such screening. AIM to investigate women's responses to being screened for domestic violence during a routine clinic visit. METHOD a cross-sectional cohort study. Women (1500) from five Queensland hospitals were asked to complete a self-report questionnaire during the visit following the consultation at which they had been screened for domestic violence. Sealable envelopes and a 'posting box' were provided to ensure anonymity of returned envelopes. FINDINGS of the 1313 respondents, 98% believed it was a 'good idea' to screen for domestic violence. Over 96% felt 'OK' during the process and 77% of the 30 women who felt uncomfortable still agreed that it was a good idea to screen. Women from rural and remote areas of Queensland had similar responses to those of their city counterparts. CONCLUSION women in Queensland found screening for domestic violence acceptable and, where health providers are suitably educated, it should be included when taking a routine health history.
A Topic-Independent Method for Automatically Scoring Essay Content Rivaling Topic-Dependent Methods

This paper proposes a topic-independent method for automatically scoring essay content. Unlike conventional topic-dependent methods, it predicts the human score of a given essay without training essays written to the same topic as the target essay. To achieve this, this paper introduces a new measure called MIDF that measures how important and relevant a word is in a given essay. The proposed method predicts the score relying on the distribution of MIDF. Surprisingly, experiments show that the proposed method achieves an accuracy of 0.848 and performs as well as or even better than conventional topic-dependent methods.
Effects Of Communication Latency, Overhead, And Bandwidth In A Cluster Architecture

This work provides a systematic study of the impact of communication performance on parallel applications in a high performance network of workstations. We develop an experimental system in which the communication latency, overhead, and bandwidth can be independently varied to observe the effects on a wide range of applications. Our results indicate that current efforts to improve cluster communication performance to that of tightly integrated parallel machines results in significantly improved application performance. We show that applications demonstrate strong sensitivity to overhead, slowing down by a factor of 60 on 32 processors when overhead is increased from 3 to 103 &micro;s. Applications in this study are also sensitive to per-message bandwidth, but are surprisingly tolerant of increased latency and lower per-byte bandwidth. Finally, most applications demonstrate a highly linear dependence to both overhead and per-message bandwidth, indicating that further improvements in communication performance will continue to improve application performance.
Building Secure SGX Enclaves using F ∗ , C + + and X 64 Presentation Proposal for PRISC ’ 18

Intel SGX offers hardware mechanisms to isolate code and data running within enclaves from the rest of the platform. This enables security verification on a relatively small software TCB, but the task still involves complex low-level code. Relying on the Everest verification toolchain, we use F∗ for developing specifications, code, and proofs; and then safely compile F∗ code to standalone C code. However, this does not account for all code running within the enclave, which also includes trusted C and assembly code for bootstrapping and for core libraries. Besides, we cannot expect all enclave applications to be rewritten in F∗, so we also compile legacy C++ defensively, using variants of /guard that dynamically enforce their safety at runtime. To reason about enclave security, we thus compose different sorts of code and verification styles, from fine-grained statically-verified F∗ to dynamically-monitored C++ and custom SGX instructions. This involves two related program semantics: most of the verification is conducted within F∗ using the target semantics of Kremlin—a fragment of C with a structured memory—whereas SGX features and dynamic checks embedded by defensive C++ compilers require lowerlevel X64 code, for which we use the verified assembly language for Everest (VALE) and its embedding in F∗.
TFP During a Credit Crunch

The financial crisis of 2008 was followed by sharp contractions in aggregate output and employment and an unusual increase in aggregate total factor productivity (TFP). This paper attempts to explain these facts by modeling the creation and destruction of jobs in the presence of heterogeneity in firm productivity and frictional credit and labor markets. The aggregate level of TFP is determined by both the underlying distribution of firm productivity and the structures of the credit and labor markets. Adverse shocks to credit markets destroy the least productive jobs and slow job creation, thus raising aggregate TFP and unemployment, and reducing output.
INVESTMENT ELASTICITY OF OUTPUT : EVIDENCE FROM INDIAN MANUFACTURING FIRMS

This paper presents evidence from Indian manufacturing firms, which suggests that besides the direct contribution that physical capital accumulation confers to the growth of a firm, such investments also generate a positive externality and complementarities for a firm. It is argued that the industry-wide capital stock positively affects growth of capital-intensive industries and that physical capital investment complements a shift towards a higher skilled workforce and research and development (R&D), both of which augment growth.
Probabilistically-constrained approaches to the design of the multiple antenna downlink

We consider the downlink of a cellular system in which the base station is equipped with multiple antennas and each user has a single antenna. We study the design of linear precoders with probabilistically-constrained quality of service (QoS) requirements for each user, in scenarios with uncertain channel state information (CSI) at the transmitter. Our goal is to design the precoder so as to minimize the total transmitted power subject to the satisfaction of the QoS constraints with a maximum allowed outage probability. We consider two stochastic models for the uncertainty in the channel coefficients of each user. The first is a Gaussian model that is appropriate for uncertainty that results from estimation errors. The second one is uniform model that is appropriate for the quantization errors in systems with quantized feedback of channel state information. We formulate the design problem as a chance constrained optimization problem, in which each chance constraint involves randomly perturbed second order cone constraints. We adopt a conservative approach that yields (deterministic) convex and efficiently-solvable design formulations that guarantee the satisfaction of the probabilistic QoS constraints. Furthermore, based on these convex formulations, we propose computationally-efficient algorithms that can reduce the level of conservatism in the initial formulations. Our simulations indicate that the proposed methods can significantly expands the range of QoS requirements that can be satisfied in the presence of uncertainty in the CSI.
Speech and Text Analysis for Multimodal Addressee Detection in Human-Human-Computer Interaction

The necessity of addressee detection arises in multiparty spoken dialogue systems which deal with human-human-computer interaction. In order to cope with this kind of interaction, such a system is supposed to determine whether the user is addressing the system or another human. The present study is focused on multimodal addressee detection and describes three levels of speech and text analysis: acoustical, syntactical, and lexical. We define the connection between different levels of analysis and the classification performance for different categories of speech and determine the dependence of addressee detection performance on speech recognition accuracy. We also compare the obtained results with the results of the original research performed by the authors of the Smart Video Corpus which we use in our computations. Our most effective meta-classifier working with acoustical, syntactical, and lexical features reaches an unweighted average recall equal to 0.917 showing almost a nine percent advantage over the best baseline model, though this baseline classifier additionally uses head orientation data. We also propose a universal meta-model based on acoustical and syntactical analysis, which may theoretically be applied in different domains.
SEAgle: Effortless Software Evolution Analysis

The analysis of software evolution by means of mining public repositories has been established as one of the dominant approaches for empirical studies in software engineering. However, even the investigation of the simplest research question demands a mazy process involving installation and configuration of tools, climbing their learning curve and tedious collection of desired information. Acknowledging the need for effortless querying of remote repositories we introduce a Web-based 'one-click approach' to perform software evolution analysis of Git projects.
In Situ Microbial Community Succession on Mild Steel in Estuarine and Marine Environments: Exploring the Role of Iron-Oxidizing Bacteria

Microbiologically influenced corrosion (MIC) is a complex biogeochemical process involving interactions between microbes, metals, minerals, and their environment. We hypothesized that sediment-derived iron-oxidizing bacteria (FeOB) would colonize and become numerically abundant on steel surfaces incubated in coastal marine environments. To test this, steel coupons were incubated on sediments over 40 days, and samples were taken at regular intervals to examine microbial community succession. The experiments were conducted at two locations: (1) a brackish salt marsh stream and (2) a coastal marine bay. We analyzed DNA extracted from the MIC biofilms for bacterial diversity using high-throughput amplicon sequencing of the SSU rRNA gene, and two coupons from the coastal site were single cell sorted and screened for the SSU rRNA gene. We quantified communities of Zetaproteobacteria, sulfate-reducing bacteria (SRB), and total bacteria and archaea using qPCR analyses. Zetaproteobacteria and SRB were identified in the sequencing data and qPCR analyses for samples collected throughout the incubations and were also present in adjacent sediments. At the brackish site, the diversity of Zetaproteobacteria was lower on the steel compared to sediments, consistent with the expected enrichment of FeOB on steel. Their numbers increased rapidly over the first 10 days. At the marine site, Zetaproteobacteria and other known FeOB were not detected in sediments; however, the numbers of Zetaproteobacteria increased dramatically within 10 days on the steel surface, although their diversity was nearly clonal. Iron oxyhydroxide stalk biosignatures were observed on the steel and in earlier enrichment culture studies; this is evidence that the Zetaproteobacteria identified in the qPCR, pyrosequencing, and single cell data were likely FeOB. In the brackish environment, members of freshwater FeOB were also present, but were absent in the fully marine site. This work indicates there is a successional pattern in the colonization of steel surfaces with FeOB being early colonizers; over time the MIC community matures to include other members that may help accelerate corrosion. This work also shows there is a reservoir for Zetaproteobacteria in coastal sediment habitats, where they may influence the coastal iron cycle, and can rapidly colonize steel surfaces or other sources of Fe(II) when available.
Exploring robustness of DNN/RNN for extracting speaker baum-welch statistics in mismatched conditions

This work explores the use of DNN/RNN for extracting Baum-Welch sufﬁcient statistics in place of the conventional GMM-UBM in speaker recognition. In this framework, the DNN/RNN is trained for automatic speech recognition (ASR) and each of the output unit corresponds to a component of GMM-UBM. Then the outputs of network are combined with acoustic features to calculate sufﬁcient statistics for speaker recognition. We evaluate and analyze the performance of networks with different conﬁgurations and training corpuses in this paper. Experimental results on text-independent SRE NIST 2008 and text-dependent RSR2015 speaker veriﬁcation tasks show the robustness of DNN/RNN for extracting statistics in mismatched evaluation conditions compared with GMM-UBM system. Particularly, Long Short-Term Memory (LSTM) RNN realized in this work outperforms traditional DNN and GMM-UBM in most mismatched conditions.
Disseminated microsporidiosis in a renal transplant recipient

Abstract: Disseminated microsporidiosis is diagnosed uncommonly in patients not infected with human immunodeficiency virus (HIV). We present a case of disseminated microsporidiosis in a renal transplant recipient who was seronegative for HIV. Chromotrope‐based stains were positive for microsporidia in urine, stools, sputum, and conjunctival scrapings. Electron microscopy, immunofluorescence, polymerase chain reaction, and cultures of renal tissue identified the organism as Encephalitozoon cuniculi. The patient was treated with oral albendazole and topical fumagillin with clinical improvement. In addition, she underwent a transplant nephrectomy and immunosuppressive therapy was withdrawn. Follow‐up samples were negative for microsporidia. However, the patient developed central nervous system manifestations and died. An autopsy brain tissue specimen demonstrated E. cuniculi by immunofluorescent staining. Disseminated microsporidiosis must be considered in the differential diagnosis of multiorgan involvement in renal allograft recipients.
CADY : Compromised Account Detector for Yammer Apoorva Dornadula

Social media account compromise not only puts the compromised user at risk, but also affects other users using the platform. Phishing and spamming are just two of the many consequences of an account being compromised. As social media platforms are entering the corporate workspace, it is very important to be able to detect when an account has been compromised. In this paper, we introduce, CADY, a Compromised Account Detector for Yammer. Yammer is a platform where employees can increase collaboration and effective communication in their workplace. Some of its features such as groups, a home page, and making public or private posts make it similar to Facebook. CADY uses machine learning to analyze a variety of introversive and extroversive behaviors to determine whether an account has been compromised. Logistic regression and multilayered perceptron classifiers achieve around a 92% accuracy with a false positive rate as low as 3% for some classifiers.
An adaptive SLA-based data flow mechanism for stream processing engines

With the upsurge in the volume of data and profuse cloud applications, big data analytics becomes very popular in the research communities in industry as well as in academia. This led to the emergence of real-time distributed stream processing systems such as Flink, Storm, Spark, and Samza. These systems sanction complex queries on streaming data to be distributed across multiple worker nodes in a cluster. Some of the stream processing systems provide basic supports for controlling the latency and throughput of the system as well as correctness of the results. We present an intelligent and efficient adaptive watermarking and dynamic buffering timeout mechanism for modern distributed stream processing engines. It is designed to increase the overall throughput by making the watermarks of the system adaptive according to incoming workload streams, and dynamically scale the buffering timeout for every task tracker on the fly while maintaining the SLA-based end-to-end latency of the system. Apache Flink is used as testing distributed processing engine in the paper. However, the proposed mechanism can be applied to other streaming frameworks. Our preliminary results indicate that the proposed system outperforms the existing stream processing framework.
Morse Decomposition of 3D Piecewise Linear Vector Fields

Morse decomposition has been shown a reliable way to compute and represent vector field topology. Its computation first converts the original vector field into a directed graph representation, so that flow recurrent dynamics (i.e., Morse sets) can be identified as some strongly connected components of the graph. In this paper, we present a framework that enables the user to efficiently compute Morse decompositions of 3D piecewise linear vector fields defined on regular grids. Specifically, we extend the 2D adaptive edge sampling technique to 3D for the outer approximation computation of the image of any 3D cell for the construction of the directed graph. To achieve finer decomposition, a hierarchical refinement framework is applied to procedurally increase the integration steps and subdivide the underlying grids that contain certain Morse sets. To improve the computational performance, we implement our Morse decomposition framework using CUDA. We have applied our framework to a number of analytic and real-world 3D steady vector fields to demonstrate its utility.
Eukaryotic microorganisms in cold environments: examples from Pyrenean glaciers

Little is known about the viability of eukaryotic microorganisms preserved in icy regions. Here we report on the diversity of microbial eukaryotes in ice samples derived from four Pyrenean glaciers. The species composition of eukaryotic communities in these glaciers is unknown mostly because of the presence of a multi-year ice cap, and it is not clear whether they harbor the same populations. The recent deglaciation of these areas is allowing an easy access to glacial layers that correspond to the “Little Ice Age” although some isolated deposits are attributed to previous glacial cycles. In this study, we use molecular 18S rRNA-based approaches to characterize some of the microbial eukaryotic populations associated with Pyrenean glaciers. Firstly, we performed a chemical and microscopical characterization of ice samples. Secondly, molecular analyses revealed interesting protist genetic diversity in glaciers. In order to understand the microbial composition of the ice samples the eukaryotic communities resident in the glacial samples were examined by amplifying community DNA and constructing clone libraries with 18S rRNA primers. After removal of potential chimeric sequences and dereplication of identical sequences, phylogenetic analysis demonstrated that several different protists could be identified. Protist diversity was more phylum rich in Aneto and Monte Perdido glaciers. The dominant taxonomic groups across all samples (>1% of all sequences) were Viridiplantae and Rhizaria. Significant variations in relative abundances of protist phyla between higher and lower glaciers were observed. At the genus level, significant differences were also recorded for the dominant genera Chloromonas, Raphidonema, Heteromita, Koliella, and Bodomorpha. In addition, protist community structure showed significant differences between glaciers. The relative abundances of protist groups at different taxonomic levels correlated with the altitude and area of glaciers and with pH of ice, but little or no relationships to other chemical characteristics were found.
Puzzles in the Chinese Stock Market

Many companies on China's stock markets have traditionally had separate, restricted classes of shares for domestic residents and foreigners. These shares are identical other than for who can own them, but foreigners have generally paid only about one-quarter the price paid by domestic residents. We argue that the generally higher level (and volatility) of domestic share prices is consistent with the simplest asset pricing model, assuming plausible differences-about four percentage points-in expected rates of return by foreign and domestic investors. We attribute low Chinese expected returns to the limited alternative investments available in China. We then estimate how various company characteristics (including capital asset pricing model (CAPM) betas, company size, market liquidity, and other characteristics) affect the relative price paid by foreigners in a panel of companies. We find, for example, that foreigners pay a lower relative price for companies with a higher proportion owned by the state-reflecting, surprisingly, a higher absolute price paid by both foreigners and domestic residents.