Miracle-dz/UniFAR-FTUs huggingface dataset:
HMVFS: A Hybrid Memory Versioning File System

The byte-addressable Non-Volatile Memory (NVM) offers fast, fine-grained access to persistent storage, and a large volume of recent researches are conducted on developing NVM-based in-memory file systems. However, existing approaches focus on low-overhead access to the memory and only guarantee the consistency between data and metadata. In this paper, we address the problem of maintaining consistency among continuous snapshots for NVM-based in-memory file systems. We propose a Hybrid Memory Versioning File System (HMVFS) that achieves fault tolerance efficiently and has low impact on I/O performance. Our results show that HMVFS provides better performance on snapshotting compared with the traditional versioning file systems for many workloads. Specifically, HMVFS has lower snapshotting overhead than BTRFS and NILFS2, improving by a factor of 9.7 and 6.6, respectively. Furthermore, HMVFS imposes minor performance overhead compared with the state-of-the-art in-memory file systems like PMFS.
The efficiency of indicator groups for the conservation of amphibians in the Brazilian Atlantic Forest

The adequate selection of indicator groups of biodiversity is an important aspect of the systematic conservation planning. However, these assessments differ in the spatial scales, in the methods used and in the groups considered to accomplish this task, which generally produces contradictory results. The quantification of the spatial congruence between species richness and complementarity among different taxonomic groups is a fundamental step to identify potential indicator groups. Using a constructive approach, the main purposes of this study were to evaluate the performance and efficiency of eight potential indicator groups representing amphibian diversity in the Brazilian Atlantic Forest. Data on the geographic range of amphibian species that occur in the Brazilian Atlantic Forest were overlapped to the full geographic extent of the biome, which was divided into a regular equal-area grid. Optimization routines based on the concept of complementarily were applied to verify the performance of each indicator group selected in relation to the representativeness of the amphibians in the Brazilian Atlantic Forest as a whole, which were solved by the algorithm “simulated annealing,” through the use of the software MARXAN. Some indicator groups were substantially more effective than others in regard to the representation of the taxonomic groups assessed, which was confirmed by the high significance of the data (F = 312.76; P < 0.01). Leiuperidae was considered as the best indicator group among the families analyzed, as it showed a good performance, representing 71% of amphibian species in the Brazilian Atlantic Forest (i.e., 290 species), which may be associated with the diffuse geographic distribution of their species. In this sense, this study promotes understanding of how the diversity standards of amphibians can be informative for systematic conservation planning on a regional scale.
Peer to peer feedback : a study on teachers’ feedback processes

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
A novel hybrid optimization algorithm for diferential-algebraic control problems

Abstract - Dynamic optimization problems can be numerically solved by direct, indirect and Hamilton-Jacobi-Bellman methods. In this paper, the differential-algebraic approach is incorporated into a hybrid method, extending the concepts of structural and differential indexes, consistent initialization analysis, index reduction and dynamic degrees of freedom to the optimal control problem. The resultant differential-algebraic optimal control problem is solved in the following steps: transformation of the original problem into a standard nonlinear programming problem that provides control and state variables, switching time estimates and costate variables profiles with the DIRCOL code; definition of the switching function and the automatically generated sequence of index-1 differential-algebraic boundary value problems from Pontryagin’s minimum principle by using the developed Otima code; and finally, application of the COLDAE code with the results of the direct method as an initial guess. The proposed hybrid method is illustrated with a pressure-constrained batch reactor optimization problem associated with the slack variable method.
Parallel Algorithms for Computational Biology

Bioinformatics algorithms are computationally demanding and most of them are compute intensive. Hence we require huge amount of computing power. High Performance Computing as been traditionally believed to be an expensive affair. In this paper we investigate techniques that have been used to parallelize conventional algorithms, coding patterns and architectural enhancements of platforms for better performance on Shared Memory and Distributed Memory architectures. 1 Sequence Comparison Sequence database searching is on of the most important tasks in Bioinformatics [RS00]. The Smith-Waterman Algorithm (SMA) is the best known algorithm and the only algorithm which guarantees the finding of the local alignment amongst given two sequences. But it is also known that it is one of the slowest of all algorithms too [Far07]. Since the actual algorithm is very slow, many heuristic based approaches like BLAST [AGM90] have been tried. But these approaches being based on heuristics, do not give exact results. Hence, there has been considerable effort amongst the researchers to find alternate ways of achieving faster yet accurate results. It is known that the size of the GenBank/EMBL/DDBJ nucleotide database doubles every 15 months [BKML00]. If this continues, there will be need for extraordinary amount of computing power for searching the databases. Several special purpose hardware
PhysioVR: A novel mobile virtual reality framework for physiological computing

Virtual Reality (VR) is morphing into a ubiquitous technology by leveraging of smartphones and screenless cases in order to provide highly immersive experiences at a low price point. The result of this shift in paradigm is now known as mobile VR (mVR). Although mVR offers numerous advantages over conventional immersive VR methods, one of the biggest limitations is related with the interaction pathways available for the mVR experiences. Using physiological computing principles, we created the PhysioVR framework, an Open-Source software tool developed to facilitate the integration of physiological signals measured through wearable devices in mVR applications. PhysioVR includes heart rate (HR) signals from Android wearables, electroencephalography (EEG) signals from a low-cost brain computer interface and electromyography (EMG) signals from a wireless armband. The physiological sensors are connected with a smartphone via Bluetooth and the PhysioVR facilitates the streaming of the data using UDP communication protocol, thus allowing a multicast transmission for a third party application such as the Unity3D game engine. Furthermore, the framework provides a bidirectional communication with the VR content allowing an external event triggering using a real-time control as well as data recording options. We developed a demo game project called EmoCat Rescue which encourage players to modulate HR levels in order to successfully complete the in-game mission. EmoCat Rescue is included in the PhysioVR project which can be freely downloaded. This framework simplifies the acquisition, streaming and recording of multiple physiological signals and parameters from wearable consumer devices providing a single and efficient interface to create novel physiologically-responsive mVR applications.
Comparison-Shopping Services and Agent Design : An Overview

This.chapter. provides.an. overview.of.comparison-shopping.services. Four.research. topics.are. covered:. How.to. design.a. good.shopbot? How.Shoppers. using.the. comparison-shopping.services? What.is.the. strategic.use. of.comparison-shopping.as. a.new. channel.by. online.vendors? And.what. is.the. impact.of. comparison-shopping.on. existing.price. equilibrium.and. electronic.market. structures? Emerging.research. topics.like. mobile.comparison. as.well. as.comparison. in.health. information.are. also.discussed.
Inter-industry Wage Differences and Individual Heterogeneity: How Competitive is Wage Setting in the UK?

There are two findings that are conspicuous in almost all studies of individual wage determination. First, standard cross-section wage equations rarely account for more than half of the total variance in earnings between individuals. Second, there are large and persistent inter-industry wage differentials and these are frequently attributed to non-competitive forces in wage determination. This paper explores these two issues using cross-section, pooled and panel data drawn from the first six waves of the British Household Panel Survey. We show that much of the residual variation in wages can be explained by significant unobserved differences between workers, perhaps reflecting innate ability or other characteristics of individuals not captured by observed data. Moreover, our wage equations explain a substantial proportion of the variation in earnings between individuals in terms of their observed and unobserved characteristics, and we find only a small role for job characteristics and almost no role for industry affiliation once we allow for unobserved individual heterogeneity. One interpretation of our findings is that wages are determined principally by individual characteristics - as human capital theory presupposes - rather than by compensating differentials or by non-competitive factors.
Are policy failures mobile? An investigation of the Advanced Metering Infrastructure Program in the State of Victoria, Australia

This article is about a case of policy failure and negative lesson drawing, namely the implementation of a mandatory smart metering programme – the Advanced Metering Infrastructure Program – in the State of Victoria, Australia, in the period 2009–2013. The article explores the framing of policy failure, and the ways in which failed polices might be mobile. The Advanced Metering Infrastructure Program provides an important empirical counterbalance to existing scholarship on policy learning, transfer and mobility, which is for the most part about positive best practice case studies, emulation and the travelling of ‘fast’ and (by implication) successful policy. There is evidence that the Victorian Advanced Metering Infrastructure Program circulated domestically within Australia and was influential in policy decision making, but that its international mobility was limited. The case is used to explore what gets left behind – or is immobile – in the telling of policy stories about failure. Science and Technology Studies scholarship on the inherent fragility of sociotechnical networks is drawn upon to consider how the concept of assemblage – a popular conceptual lens within policy mobility scholarship – might be applied to better understand instances of policy failure.
The Usability of Stacked-Block Overviews for Retrieval

Stacked-block overviews represent a large data set in a compact space by placing items in a closely-packed grid. As awareness displays, they provide a bird’seye view of state, activity, and change in a data set. However, stacked-block overviews have a distinct disad vantage when it comes to retrieval, because they provi de few clues to the identity of objects other than spa tial position. To investigate the usability of stacked-b lock overviews, we carried out two studies in which part icipants retrieved items from either an overview or a standard scrolling list. Retrieval performance with the stacked-block overview was much better than we initially expected (and at its best was significantly better than the scrolling list), and several people strong ly preferred the overview. However, the stacked-block rep resentation was unusable for nearly a quarter of the participants, and even those who succeeded with it required extensive training to reach a high level of performance. Despite these problems, our results show t at stacked-block overviews can in many cases be used a more than just awareness displays.
The impact of a game-based approach to Bourdieu on learners training to teach in post-compulsory education at an English University

The delivery of theory alongside practice in teacher education is inherently challenging and prone to failure, leaving trainees ill-prepared to problematise the social and cultural realities that shape their classrooms. Finding new and productive ways for trainees to engage with theoretical concepts is, therefore, an important educational and social outcome. This paper explores the use of a game-based approach to the teaching of Bourdieu's notions of field and habitus to two small groups, training with a University in the North of England to become teachers in post-compulsory education. Critical and learning theories are used to explain and justify the design decisions and strategies employed and critical participatory action research is used to evaluate the impact of the game. The paper reports encouraging findings and recommends extension and wider use of such strategies in the teaching of theory to resistant groups.
Lipschitz stability for hyperbolic inequalities in octants with the lateral Cauchy data and refocising in time reversal

Hyperbolic equations and inequalities in octants with the lateral Cauchy data at coordinate planes are considered. Lipschitz stability estimate is established in the case when both the inhomogeneous right hand side and (unknown) initial conditions at {t = 0} have a finite support. This is the first stability estimate for such a Cauchy problem in an infinite domain. Refocusing of time reversal fields in octants follows. It is shown that the modified Quasi-Reversibility Method can be applied for the numerical solution of such a Cauchy problem including computational time reversal.
Evidence for a magnetic neutron star in high mass X-ray binary 4U 2206+54 with INTEGRAL/IBIS observations

The hard X-ray source 4U 2206+54 is a peculiar high mass X-ray binary with a main-sequence donor star. Recent X-ray observations suggested that the compact object in 4U 2206+54 may be a neutron star. The X-ray emission comes from the accretion of stellar winds from the massive donor stars, and variability of luminosity may be due to the changes of its orbit phase. To further reveal the nature of compact object, we studied 4U 2206+54 with INTEGRAL/IBIS observations in two years, and found that in most time, 4U 2206+54 undergone a quiescent state and sometime an active state. In the quiescent state the spectrum can be fitted by a power-law model of $\Gamma\sim 2.1$ with a hard X-ray luminosity of $\sim 5\times 10^{34}$ erg s$^{-1}$ (20-- 100 keV). While in the active state, the 20-- 100 keV hard X-ray luminosity reaches $\sim 2\times 10^{35}$ erg s$^{-1}$ and the spectrum is fitted by a thermal bremmstrahlung model of $kT\sim 43$ keV plus two cyclotron absorption lines at $\sim$ 30 and 60 keV. Then we derived a magnetic field of 3.3$\times 10^{12}$ G for the compact object in 4U 2206+54. During the active state, we found a pulsation period of $\sim$ 5400 s in the light curve of 4U 2206+54. So the compact object in 4U 2206+54 should be a magnetic neutron star with a slow pulsation. Cyclotron absorption lines detected in the active state and non-detection in the quiescent state suggested that two different accretion states have possible different hard X-ray emission regions: surface of neutron star in the active state; the magnetic-accretion pressure equivalent point in the quiescent state. The re-analysis of the RXTE/ASM light curve found the modulation periods at $\sim 9.56$ days and 19.11 days, and the orbit period of 4U 2206+54 should be 19.11 days.
Spectral Modulation, or Ripple, in Retardation Plates for Linear and Circular Polarization

High‐resolution spectropolarimetry sometimes suffers from a spectral modulation in polarization and position angle. It is shown that this artifact can be attributed to multiple reflections within the plates of the wave plate assembly and that the effect is inherent to the use of wave plates except at the design wavelength. The treatment given applies to strictly plane‐parallel wave plate elements and complete coherence, and consequently the predicted ripple amplitudes are upper limits. It is possible that plates of poorer optical quality will not show this effect so prominently, but otherwise a simple modification to normal observing practice can be used to eliminate the ripple.
Correcting Biased Cohen’s Kappa in NVivo

ABSTRACT This study demonstrates that NVivo, a popular research tool for content analysis, produces biased Cohen’s kappa as it calculates the reliability statistic at the character level, which is unsuitable for most content-analytic studies adopting a higher unit of analysis (e.g., sentence, paragraph). Based on empirical data and a statistical simulation, this study proposes a method of bias correction applicable to situations where two independent raters conduct binary coding.
DBD: a transcription factor prediction database

Regulation of gene expression influences almost all biological processes in an organism; sequence-specific DNA-binding transcription factors are critical to this control. For most genomes, the repertoire of transcription factors is only partially known. Hitherto transcription factor identification has been largely based on genome annotation pipelines that use pairwise sequence comparisons, which detect only those factors similar to known genes, or on functional classification schemes that amalgamate many types of proteins into the category of ‘transcription factor’. Using a novel transcription factor identification method, the DBD transcription factor database fills this void, providing genome-wide transcription factor predictions for organisms from across the tree of life. The prediction method behind DBD identifies sequence-specific DNA-binding transcription factors through homology using profile hidden Markov models (HMMs) of domains. Thus, it is limited to factors that are homologus to those HMMs. The collection of HMMs is taken from two existing databases (Pfam and SUPERFAMILY), and is limited to models that exclusively detect transcription factors that specifically recognize DNA sequences. It does not include basal transcription factors or chromatin-associated proteins, for instance. Based on comparison with experimentally verified annotation, the prediction procedure is between 95% and 99% accurate. Between one quarter and one-half of our genome-wide predicted transcription factors represent previously uncharacterized proteins. The DBD () consists of predicted transcription factor repertoires for 150 completely sequenced genomes, their domain assignments and the hand curated list of DNA-binding domain HMMs. Users can browse, search or download the predictions by genome, domain family or sequence identifier, view families of transcription factors based on domain architecture and receive predictions for a protein sequence.
Multiphase Inverse Modeling: Review and iTOUGH2 Applications

Calibration of a numerical process model against laboratory or field data is often referred to as “inverse modeling. ” As the numerical simulation models become more complex, the number of parameters to be estimated generally increases, requiring new testing, modeling, and inversion strategies. The purpose of this survey is to review inverse modeling approaches for unsaturated and multiphase flow models. The discussion focuses on applications rather than theoretical considerations, which have been previously reviewed in the context of saturated flow and transport modeling. We also examine model parameterization issues, specifically the representation of heterogeneity through a limited number of variables that can be subjected to parameter estimation and uncertainty propagation analyses. Different parameterization strategies are illustrated using the multiphase flow simulation–optimization code iTOUGH2. A comprehensive inverse modeling package (such as iTOUGH2, which includes automatic model calibration followed by an extensive residual, error, and uncertainty propagation analysis) is an essential tool to improve test design and data analysis of complex multiphase flow systems.
Inverted Index Compression for Scalable Image Matching

To perform fast image matching against large databases, a Vocabulary Tree (VT) uses an inverted index that maps from each tree node to database images which have visited that node. The inverted index can require gigabytes of memory, which significantly slows down the database server. In this paper, we design, develop, and compare techniques for inverted index compression for image-based retrieval. We show that these techniques significantly reduce memory usage, by as much as 5x, without loss in recognition accuracy. Our work includes fast decoding methods, an offline database reordering scheme that exploits the similarity between images for additional memory savings, and a generalized coding scheme for soft-binned feature descriptor histograms. We also show that reduced index memory permits memory-intensive image matching techniques that boost recognition accuracy.
Approximate Bayesian Computation

Many of the statistical models that could provide an accurate, interesting, and testable explanation for the structure of a data set turn out to have intractable likelihood functions. The method of approximate Bayesian computation (ABC) has become a popular approach for tackling such models. This review gives an overview of the method and the main issues and challenges that are the subject of current research.
Changing Musical Emotion: A Computational Rule System for Modifying Score and Performance

When communicating emotion in music, composers and performers encode their expressive intentions through the control of basic musical features such as: pitch, loudness, timbre, mode, and articulation. The extent to which emotion can be controlled through the systematic manipulation of these features has not been fully examined. In this paper we present CMERS, a Computational Music Emotion Rule System for the control of perceived musical emotion that modifies features at the levels of score and performance in real-time. CMERS performance was evaluated in two rounds of perceptual testing. In experiment I, 20 participants continuously rated the perceived emotion of 15 music samples generated by CMERS. Three music works, each with five emotional variations were used (normal, happy, sad, angry, and tender). The intended emotion by CMERS was correctly identified 78% of the time, with significant shifts in valence and arousal also recorded, regardless of the works’ original emotion.