Miracle-dz/UniFAR-FTUs huggingface dataset:
Study epitaxially strained KNbO3/NaNbO3 superlattice using first-principle's calculations

The changes of crystal structure, zone-center phonon, polarization and dielectric constant with epitaxial strain in KNbO3/NaNbO3 (KNO/NNO) superlattice have been studied using density functional theory (DFT) within the local-density approximation (LDA). Strain induced structural phase transitions have been identified from tetragonal to monoclinic then to orthorhombic when the in plane misfit strain changes from −1.25% to −0.1%. The polarization amplitude is the highest in the orthorhombic phase, reaching more than 70µC/cm2, and the dielectric constant peaks at the phase boundaries.
ASIdE: Using Autocorrelation-Based Size Estimation for Scheduling Bursty Workloads

Temporal dependence in workloads creates peak congestion that can make service unavailable and reduce system performance. To improve system performability under conditions of temporal dependence, a server should quickly process bursts of requests that may need large service demands. In this paper, we propose and evaluateASIdE, an Autocorrelation-based SIze Estimation, that selectively delays requests which contribute to the workload temporal dependence. ASIdE implicitly approximates the shortest job first (SJF) scheduling policy but without any prior knowledge of job service times. Extensive experiments show that (1) ASIdE achieves good service time estimates from the temporal dependence structure of the workload to implicitly approximate the behavior of SJF; and (2) ASIdE successfully counteracts peak congestion in the workload and improves system performability under a wide variety of settings. Specifically, we show that system capacity under ASIdE is largely increased compared to the first-come first-served (FCFS) scheduling policy and is highly-competitive with SJF.
Application-based review of GaN HFETs

Normally-off GaN-on-Si heterojunction field-effect transistors (HFETs) have been developed with up to 650 V blocking capability, fast switching, and low conduction losses in commercial devices. The natively depletion-mode device can be modified to be normally-off using a variety of techniques. For a power electronics engineer accustomed to Si-based converter design, there is inherent benefit to understanding the unique characteristics and challenges that distinguish GaN HFETs from Si MOSFETs. Dynamic Rds-on self-commutated reverse conduction, gate voltage and current requirements, and the effects of very fast switching are explained from an applications perspective. This paper reviews available literature on commercial and near-commercial GaN HFETs, to prepare engineers with Si-based power electronics experience to effectively design GaN-based converters.
Nanjing Normal University Segmenter for the Fourth SIGHAN Bakeoff

This paper expounds a Chinese word segmentation system built for the Fourth SIGHAN Bakeoff. The system participates in six tracks, namely the CityU Closed, CKIP Closed, CTB Closed, CTB Open, SXU Closed and SXU Open tracks. The model of Conditional Random Field is used as a basic approach in the system, with attention focused on the construction of feature templates and Chinese character categorization. The system is also augmented with some post-processing approaches such as the Extended Word String, model integration and others. The system performs fairly well on the 5 tracks of the Bakeoff.
A dataset for pull-based development research

Pull requests form a new method for collaborating in distributed software development. To study the pull request distributed development model, we constructed a dataset of almost 900 projects and 350,000 pull requests, including some of the largest users of pull requests on Github. In this paper, we describe how the project selection was done, we analyze the selected features and present a machine learning tool set for the R statistics environment.
Protesting to protect “us” and/or “them”? Explaining why members of third groups are willing to engage in collective action

In three studies we test whether three key predictors of collective action (i.e., group identification, anger, and efficacy) also predict whether and how members of third groups are willing to undertake collective action. Little is known about this, particularly about whether and how third-group members may engage in collective action to protect their own group and/or to protect an outgroup in need. In three studies that employed different three-group contexts, we found that the three predictors contributed to third-group members’ collective action intentions aimed at protecting the ingroup as well as those aimed at protecting the outgroup. Study 1 found this among Latvians (N = 89) in response to the Russian annexation of Ukrainian territory; Study 2 found this among residents of a Dutch village (N = 98) located nearby a gas-extraction-related earthquake region, in response to authorities’ inadequate protection of the residents of that region; and Study 3 found this among Latino Americans (N = 278) in response to police brutality against Black Americans. Moving beyond replication and application of previous work, our set of studies show first evidence for ingroup and outgroup protection as motives of third-group members’ collective action. We discuss the implications of our findings for the broader social psychology of collective action literature.
LOD 2 Deliverable D 5 . 1 . 1 : Initial release faceted spatial-semantic browsing component

This prototype deliverable consists of a software release of JavaScript widgets for faceted spatial-semantic browsing and an accompanying deliverable report. The software is open source and can be downloaded at https://github. com/ AKSW/SpatialSemanticBrowsingWidgets. The widgets are being used in the LinkedGeoData project. This deliverable describes these widgets in more detail. Collaborative Project LOD2 Creating Knowledge out of Interlinked Data Project Number: 257943 Start Date of Project: 01/09/2010 Duration: 48 months
A Color-Coded Tape for Uterine Height Measurement: A Tool to Identify Preterm Pregnancies in Low Resource Settings

Introduction Neonatal mortality associated with preterm birth can be reduced with antenatal corticosteroids (ACS), yet <10% of eligible pregnant women in low-middle income countries. The inability to accurately determine gestational age (GA) leads to under-identification of high-risk women who could receive ACS or other interventions. To facilitate better identification in low-resource settings, we developed a color-coded tape for uterine height (UH) measurement and estimated its accuracy identifying preterm pregnancies. Methods We designed a series of colored-coded tapes with segments corresponding to UH measurements for 20–23.6 weeks, 24.0–35.6 weeks, and >36.0 weeks GA. In phase 1, UH measurements were collected prospectively in the Democratic Republic of Congo, India and Pakistan, using distinct tapes to address variation across regions and ethnicities. In phase 2, we tested accuracy in 250 pregnant women with known GA from early ultrasound enrolled at prenatal clinics in Argentina, India, Pakistan and Zambia. Providers masked to the ultrasound GA measured UH. Receiver operating characteristics (ROC) analysis was conducted. Results 1,029 pregnant women were enrolled. In all countries the tapes were most effective identifying pregnancies between 20.0–35.6 weeks, compared to the other GAs. The ROC areas under the curves and 95% confidence intervals were: Argentina 0.69 (0.63, 0.74); Zambia 0.72 (0.66, 0.78), India 0.84 (0.80, 0.89), and Pakistan 0.83 (0.78, 0.87). The sensitivity and specificity (and 95% confidence intervals) for identifying pregnancies between 20.0–35.6 weeks, respectively, were: Argentina 87% (82%–92%) and 51% (42%–61%); Zambia 91% (86%–95%) and 50% (40%–60%); India 78% (71%–85%) and 89% (83%–94%); Pakistan 63% (55%–70%) and 94% (89%–99%). Conclusions We observed moderate-good accuracy identifying pregnancies ≤35.6 weeks gestation, with potential usefulness at the community level in low-middle income countries to facilitate the preterm identification and interventions to reduce preterm neonatal mortality. Further research is needed to validate these findings on a population basis.
Evaluaton of regional cerebral blood flow alterations by limbic activation in patients with schizophrenia

The aim of study is to evaluate the functions of limbic system in schizophrenia by performing procaine administration and using single photon emission computed tomography (SPECT). 22 patients and 19 controls were included in the study. Patients were evaluated with Positive and Negative Syndrome Scale (PANSS), Brief Psychiatric Rating Scale (BPRS), Hamilton Rating Scale for Depression (HAM-D) and Hamilton Rating Scale for Anxiety (HAM-A), Calgary Depression Rating Scale for Schizophrenia (CDSS) and the controls were evaluated with BPRS, HAM-D and HAM-A. The regional cerebral blood flow (rCBF) values were measured by SPECT. The rCBF following placebo and the alteration ratios of the rCBF following procaine of patients compared to controls. The rCBF following placebo in bilateral frontal, bilateral superior temporal, bilateral parahippocampus, thalamus, insula and alteration ratios of rCBF following procaine in bilateral anterior cingulate cortex (ACC) and left thalamus of patients were lower. Poor limbic activation to procaine was observed in the ACC and left thalamus of patients with schizophrenia. These findings support that the ACC and thalamus are crucial role in pathophysiology of schizophrenia.
Method Matters: An Empirical Study of Impact in Cognitive Neuroscience

A major thrust of cognitive neuroscience is the elucidation of structure-function relationships in the human brain. Over the last several years, functional neuroimaging has risen in prominence relative to the lesion studies that formed the historical core of work in this field. These two methods have different strengths and weaknesses. Among these is a crucial difference in the nature of evidence each can provide. Lesion studies can provide evidence for necessity claims, whereas functional neuroimaging studies do not. We hypothesized that lesion studies will continue to have greater scientific impact even as the relative proportion of such studies in the cognitive neuroscience literature declines. Using methods drawn from systematic literature review, we identified a set of original cognitive neuroscience articles that employed either functional imaging or lesion techniques, published at one of two time points in the 1990s, and assessed the effect of the method used on each article's impact across the decade. Functional neuro-imaging studies were cited three times more often than lesion studies throughout the time span we examined. This effect was in large part due to differences in the influence of the journals publishing the two methods; functional neuroimaging studies appeared disproportionately more often in higher impact journals. There were also differences in the degree to which articles using one method cited articles using the other method. Functional neuroimaging articles were less likely to include such cross-method citations.
A Component Composition and Customization Language for the Liberty Simulation Environment

To build efficient hardware, designers must be able to rapidly construct simulators for a wide range of candidate designs. Fortunately, different hardware designs utilize many similar hardware blocks, and thus a good library of reusable components can greatly ease the task of constructing a simulator. Unfortunately, existing simulator construction methodologies do not facilitate construction of such libraries. The Liberty Simulation Environment (LSE) addresses this gap in simulator construction technology. LSE consists of a user-extensible library of reusable components, the Liberty Structural Specification (LSS) language, and a tool that generates an executable simulator from an LSS program and the component library. This paper discusses the design and implementation of the LSS language. The LSS programming language is unique in that it is designed not to specify the execution behavior of a simulator, but rather, to specify how components from the library should be composed and customized to form new components or to build a complete system model. LSS allows the designer to specify an arbitrarily deep hierarchical description of components in an intuitive fashion. Furthermore, the designer can use component parameters and system connectivity in one level of the hierarchy to determine the structure of lower levels in the hierarchy. To allow this u e-based specialization, the LSS language uses novel evaluation semantics, an algorithmic specification of structure, and several programming language techniques including type inference and aspect oriented programming.
A new instrument for measuring pre-service biology teachers' pedagogical content knowledge: The PCK-IBI

Teachers' pedagogical content knowledge (PCK) is highly important for effective design and implementation of school teaching. Thus, the current status, development and efficacy of this knowledge, its relationships with teaching quality parameters, and its impact on students' learning processes and success, require rigorous examination. Thoroughly validated, objective and reliable test instruments that are highly sensitive to changes in variables of proven knowledge‐related relevance in teacher education are also required. Previous attempts to design such instruments for assessing science teachers' PCK have largely focused on mathematical content. Therefore, here we present an instrument (the pedagogical content knowledge in biology inventory, PCK‐IBI), based on conceptualizations of teachers' professional competence, for assessing secondary school pre‐service biology teachers' PCK. In a series of three evaluations and refinements it was tested with samples of N = 274 and N = 432 German pre‐service as well as one sample of n = 65 German pre‐service and n = 35 German in‐service biology teachers. Item analysis, scale analysis and empirically obtained indicators of validity suggest that the final 34‐item‐version of the PCK‐IBI is unidimensional, provides objective test scores and enables reliable and valid registration of pre‐service biology teachers' PCK. Thus, hypotheses regarding specific aspects of the model on which the PCK‐IBI's construction is based on are empirically supported. The results of our study provide empirical support for the instrument's potential utility.
Floating control: examining factors affecting the management of the civil society sector in authoritarian China

Abstract Civil society organisations can both assist and threaten autocracies’ monopoly of power. Pre-emptive measures have thus been strategically adopted by nondemocratic regimes to harness and manage the civil society sector. One tacit sanctioning strategy observable from a macro-institutional perspective is to mediate the institutional space for civil society organisations. This study explores how the Chinese authoritarian state manipulates such institutional space according to the changing internal and external environments, especially domestic crises and international movement waves. The study uses a 31 × 17 panel data-set about China’s social organisations covering 31 administrative units (excluding Hong Kong, Macau and Taiwan) during the period of 1998 to 2014 to gain insight into the management pattern. The results show that economic performance, natural disaster, social instability and political instability are critical factors affecting regulatory dynamics.
Real-Time Monitoring of Passenger's Psychological Stress

This article addresses the question of passengers’ experience through different transport modes. It presents the main results of a pilot study, for which stress levels experienced by a traveller were assessed and predicted over two long journeys. Accelerometer measures and several physiological signals (electrodermal activity, blood volume pulse and skin temperature) were recorded using a smart wristband while travelling from Grenoble to Bilbao. Based on user’s feedback, three events of high stress and one period of moderate activity with low stress were identified offline. Over these periods, feature extraction and machine learning were performed from the collected sensor data to build a personalized regressive model, with user’s stress levels as output. A smartphone application has been developed on its basis, in order to record and visualize a timely estimated stress level using traveler’s physiological signals. This setting was put on test during another travel from Grenoble to Brussels, where the same user’s stress levels were predicted in real time by the smartphone application. The number of correctly classified stress-less time windows ranged from 92.6% to 100%, depending on participant’s level of activity. By design, this study represents a first step for real-life, ambulatory monitoring of passenger’s stress while travelling.
Using crowd-sourced viewing statistics to save energy in wireless video streaming

Video streaming on smartphones is one of the most popular but also most energy hungry services today. Using mobile video services results in two contradictory sources of energy waste for smartphones: i) energy waste because of excessively aggressive prefetching of content that the user will not watch because of abandoning the session, and ii) excessive amount of tail energy, which is energy wasted by keeping the wireless interface powered on after receiving a chunk of content; this is caused by prefetching chunks that are too small. To remedy this, we propose a novel download scheduling algorithm based on crowd-sourced video viewing statistics. Our algorithm judiciously evaluates the probability of a user interrupting a video viewing in order to perform the right amount of prefetching. In this way, the algorithm balances the amount of the two above-mentioned kinds of energy waste. By simulations, we show that our scheduler cuts the energy waste to half compared to existing download strategies. We have also developed an Android prototype that implements the download scheduler together with a novel downloader that speeds up the download by exploiting the Fast Start technique. The prototype exhibits the desired properties of the scheduler, and its faster downloading mechanism yields further energy savings of up to 80% compared to the default Android YouTube app.
Bit Error Rate Minimizing Channel Shortening Equalizers for Multicarrier Systems

Multicarrier systems first became widely used for digital subscriber lines (DSL). In DSL, the performance metric is the bit rate that can be provided without exceeding a given bit error rate (BER). Wireless multicarrier systems are becoming more popular, and in such systems the appropriate performance metric is the BER for a given bit rate. Multicarrier systems are robust to multipath provided that the channel delay spread is shorter than the guard interval between blocks. If this condition is not met, a channel shortening equalizer can be used. Previous work on channel shortening has focussed on maximizing the bit rate for DSL. We propose and evaluate a channel shortener that attempts to directly minimize the BER of a wireless multicarrier system
Volitional down-regulation of the primary auditory cortex via directed attention mediated by real-time fMRI neurofeedback

The present work assessed the efficacy of training volitional down-regulation of the primary auditory cortex (A1) based on real-time functional magnetic resonance imaging neurofeedback (fMRI-NFT). A1 has been shown to be hyperactive in chronic tinnitus patients, and has been implicated as a potential source for the tinnitus percept. 27 healthy volunteers with normal hearing underwent 5 fMRI-NFT sessions: 18 received real neurofeedback and 9 sham neurofeedback. Each session was composed of a simple auditory fMRI followed by 2 runs of A1 fMRI-NFT. The auditory fMRI alternated periods of no auditory with periods of white noise stimulation at 90 dB. A1 activity, defined from a region using the activity during the preceding auditory run, was continuously updated during fMRI-NFT using a simple bar plot, and was accompanied by white noise (90 dB) stimulation for the duration of the scan. Each fMRI-NFT run alternated “relax” periods with “lower” periods. Subjects were instructed to watch the bar during the relax condition and actively reduce the bar by decreasing A1 activation during the lower condition. Average A1 de-activation, representative of the ability to volitionally down-regulate A1, was extracted from each fMRI-NFT run. A1 de-activation was found to increase significantly across training and to be higher in those receiving real neurofeedback. A1 de-activation in sessions 2 and 5 were found to be significantly greater than session 1 in only the group receiving real neurofeedback. The most successful subjects reportedly adopted mindfulness tasks associated with directed attention. For the first time, fMRI-NFT has been applied to teach volitional control of A1 de-activation magnitude over more than 1 session. These are important findings for therapeutic development as the magnitude of A1 activity is altered in tinnitus populations and it is unlikely a single fMRI-NFT session will reverse the effects of tinnitus.
A dynamic dataflow architecture using partial reconfigurable hardware as an option for multiple cores

Different from traditional processors, Moores Law was one of the reasons to duplicate cores, and at least until today it is the solution for safe consumption and operation of systems using millions of transistors. In terms of software, parallelism will be a tendency over the coming years. One of the challenges is to create tools for programmers who use HLL (High Level Language) producing hardware directly. These tools should use the utmost experience of the programmers and the flexibility of FPGA (Field Programmable Gate Array). The main aspect of the existing tools which directly convert HLL into hardware is dependence graphics. On the other hand, a dynamic dataflow architecture has implicit parallelism. ChipCflow is a tool to convert C directly into hardware that uses FPGA as a partial reconfiguration based on a dynamic dataflow architecture. In this paper, the relation between traditional dataflow architecture and contemporary architecture, as well as the main characteristics of the ChipCflow project will be presented.
Acid Tolerance of Biofilm Cells of Streptococcus mutans

ABSTRACT Streptococcus mutans, a member of the dental plaque community, has been shown to be involved in the carious process. Cells of S. mutans induce an acid tolerance response (ATR) when exposed to sublethal pH values that enhances their survival at a lower pH. Mature biofilm cells are more resistant to acid stress than planktonic cells. We were interested in studying the acid tolerance and ATR-inducing ability of newly adhered biofilm cells of S. mutans. All experiments were carried out using flow-cell systems, with acid tolerance tested by exposing 3-h biofilm cells to pH 3.0 for 2 h and counting the number of survivors by plating on blood agar. Acid adaptability experiments were conducted by exposing biofilm cells to pH 5.5 for 3 h and then lowering the pH to 3.5 for 30 min. The viability of the cells was assessed by staining the cells with LIVE/DEAD BacLight viability stain. Three-hour biofilm cells of three different strains of S. mutans were between 820- and 70,000-fold more acid tolerant than corresponding planktonic cells. These strains also induced an ATR that enhanced the viability at pH 3.5. The presence of fluoride (0.5 M) inhibited the induction of an ATR, with 77% fewer viable cells at pH 3.5 as a consequence. Our data suggest that adhesion to a surface is an important step in the development of acid tolerance in biofilm cells and that different strains of S. mutans possess different degrees of acid tolerance and ability to induce an ATR.