Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of the Earthworm , Pheretima ( Metaphire ) hilgendorfi , in Terrestrial Ecosystem Nutrient Cycling

In the gut tissues and contents of the earthworm Pheretima (Metaphire) hilgendorfi, cellulase activity which contributes to the terrestrial ecosystem nutrient cycling has been detected. The origin of the cellulase production, whether it is the earthworm itself or the microorganisms, has not been established at the molecular level. In our study, a cellulase [endo-β-1,4glucanase (EGase), EC3.2. 1.4] gene was identified from the intestine tissue of earthworm P. (M.) hilgendorfi. The cDNA encoding EGase of P. (M.) hilgendorfi (phhEG) is 1,606 bp with an open reading frame of 449 bp, and belonging to glycoside hydrolase family (GHF) 9. The deduced amino acid sequences of the phhEG showed a 74% identity to another earthworm Eisenia andrei, and a 31% identity to the bacterium Thermobifida fusca. The recombinant phhEG produced by wheat germ cell-free protein synthesis system showed an enzymatic activity. The result of zymogram analysis of phhEG showed that the band of enzyme activity appears to have a molecular weight of 50 kDa, which is very similar to the value detected from the intestine tissues and contents extracts of P. (M.) hilgendorfi. These results suggested that the cellulolytic enzyme which functionally degrading cellulose is secreted by the earthworm themselves and not dependent on the symbiotic and ingested microorganisms.
Fully unsupervised small-vocabulary speech recognition using a segmental Bayesian model

Current supervised speech technology relies heavily on transcribed speech and pronunciation dictionaries. In settings where unlabelled speech data alone is available, unsupervised methods are required to discover categorical linguistic structure directly from the audio. We present a novel Bayesian model which segments unlabelled input speech into word-like units, resulting in a complete unsupervised transcription of the speech in terms of discovered word types. In our approach, a potential word segment (of arbitrary length) is embedded in a fixed-dimensional space; the model (implemented as a Gibbs sampler) then builds a whole-word acoustic model in this space while jointly doing segmentation. We report word error rates in a connected digit recognition task by mapping the unsupervised output to ground truth transcriptions. Our model outperforms a previously developed HMM-based system, even when the model is not constrained to discover only the 11 word types present in the data. Index Terms: unsupervised speech processing, word discovery, speech segmentation, unsupervised learning, segmental models
More D -brane bound states

The low-energy background field solutions corresponding to D-brane bound states which possess a difference in dimension of two are presented. These solutions are constructed using the T-duality map between the type IIA and IIB superstring theories. Since supersymmetry is preserved by T duality, the bound state solutions retain the supersymmetric properties of the initial (single) D-brane states from which they are produced; i.e., they preserve one-half of the supersymmetries. {copyright} {ital 1997} {ital The American Physical Society}
Extreme Mountain Ultra-Marathon Leads to Acute but Transient Increase in Cerebral Water Diffusivity and Plasma Biomarkers Levels Changes

Background: Pioneer studies demonstrate the impact of extreme sport load on the human brain, leading to threatening conditions for athlete's health such as cerebral edema. The investigation of brain water diffusivity, allowing the measurement of the intercellular water and the assessment of cerebral edema, can give a great contribution to the investigation of the effects of extreme sports on the brain. We therefore assessed the effect of supra-physiological effort (extreme distance and elevation changes) in mountain ultra-marathons (MUMs) athletes combining for the first time brain magnetic resonance imaging (MRI) and blood parameters. Methods:This longitudinal study included 19 volunteers (44.2 ± 9.5 years) finishing a MUM (330 km, elevation + 24000 m). Quantitative measurements of brain diffusion-weighted images (DWI) were performed at 3 time-points: Before the race, upon arrival and after 48 h. Multiple blood biomarkers were simultaneously investigated. Data analyses included brain apparent diffusion coefficient (ADC) and physiological data comparisons between three time-points. Results:The whole brain ADC significantly increased from baseline to arrival (p = 0.005) and then significantly decreased at recovery (p = 0.005) to lower values than at baseline (p = 0.005). While sodium, potassium, calcium, and chloride as well as hematocrit (HCT) changed over time, the serum osmolality remained constant. Significant correlations were found between whole brain ADC changes and osmolality (p = 0.01), cholesterol (p = 0.009), c-reactive protein (p = 0.04), sodium (p = 0.01), and chloride (p = 0.002) plasma level variations. Conclusions:These results suggest the relative increase of the inter-cellular volume upon arrival, and subsequently its reduction to lower values than at baseline, indicating that even after 48 h the brain has not fully recovered to its equilibrium state. Even though serum electrolytes may only indirectly indicate modifications at the brain level due to the blood brain barrier, the results concerning osmolality suggest that body water might directly influence the change in cerebral ADC. These findings establish therefore a direct link between general brain inter-cellular water content and physiological biomarkers modifications produced by extreme sport.
The sliding of the signified: multimodal sign operations in a youth-created experimental digital video

In this article, the author presents a multimodal discourse analysis of a digital video composed by five students (ages 11–12) in an urban, public-school classroom. The focal mockumentary video is distinctive in that it is difficult to interpret and has an artistic quality that turns the process of meaning-making back on itself, resisting the very idea of a single, determinable meaning. He examines this phenomenon as the sliding of the signified in the students’ video (as multimodal discourse), focusing on the ways in which the students tapped into discursive agencies that rupture meaning-making. In particular, he analyzes how visual and spoken signifiers are related or coordinated with one another across the film in the creation of multimodal discursive effects such as floating signifiers, networks of metonymic potential, and signifier condensation complexes. This study thus offers conceptualizations of multimodal discursive units that can be used to interpret and analyze the interactions of visual and spoken signifiers in films and digital videos.
Specific Simple Network Management Tools

The Simple Network Management Protocol (SNMP) has been around for more than a decade and is supported by most network devices and end systems. Despite this success, there is still a lack of simple to use network management applications.This paper describes the design of an SNMP management tool called scli which provides an easy and efficient to use SNMP command line interface. The software architecture has been designed to make it easy for C programmers without any special SNMP programming skills to extend the functionality provided by scli .
Linked Open Data Framework for Serendipity in History of Art Research

In this paper we outline the main lines of research for defining a framework based on Linked Open Data (LOD) for supporting knowledge creation in the Cultural Heritage (CH) field with a particular focus on History of Art research. We delineate the main challenges we need to deal with and we explore the state-of-the-art in LOD publishing systems, LOD citation and authority management. Furthermore, we introduce the idea of computer-aided serendipity in History of Art research with the purpose of contributing to the advancement of the field and to the definition of new methodologies for entity linking and retrieval.
A pre-computation scheme for speeding up public-key cryptosystems

This thesis presents fast and practical methods for generating randomly distributed pairs of the form (x; g x mod p) or (x; x e mod N), using precomputation. These generation schemes are of wide applicability for speeding-up public key systems that depend on exponentiation and ooer a smooth memory-speed trade-oo. The steps involving exponentiation in these systems can be reduced signiicantly in many cases. The schemes are most suited for server applications. The thesis also presents security analyses of the schemes using standard assumptions. The methods are novel in the sense that they identify and thoroughly exploit the randomness issues related to the instances generated in these public-key schemes. The constructions use random walks on Cayley (expander) graphs over Abelian groups. Acknowledgments I would like to start by expressing my deepest gratitude to Shaa Goldwasser, my thesis advisor, for her continued advice and fruitful discussions. She has been very helpful and supporting throughout my time at MIT, and I look forward to further work with her. The work for this thesis was performed in part at Bellcore under the direction of and in collaboration with Ramarathnam Venkatesan. I would like to thank Marcus Peinado for investigating the hidden subset sum problems related to our generators, and for collaborating on the conference version of our paper. I would also like to thank Ronald Rivest and Arjen Lenstra for their help, advice, and discussions. Finally, I would like to thank my parents for making me possible, and for their constant love and encouragement.
Molecular identification and chromosomal localization of new powdery mildew resistance gene Pm11 in oat Title: Multiple cryptic refugia of forest grass Bromus benekenii in Europe as revealed by ISSR fingerprinting and species distribution modelling

Despite not having been fully recognized, the cryptic northern refugia of temperate forest vegetation in Central and Western Europe are one of the most important in the Holocene history of the vegetation on the subcontinent. We have studied a forest grass Bromus benekenii in 39 populations in Central, Western and Southern Europe with the use of PCR-ISSR fingerprinting. The indices of genetic population diversity, multivariate, and Bayesian analyses, supplemented with species distribution modelling have enabled at least three putative cryptic northern refugial areas to be recognized: in Western Europe—the Central and Rhenish Massifs, in Central Europe—the Bohemia–Moravia region and in the Eastern/Western Carpathians. Central Poland is the regional genetic melting-pot where several migratory routes might have met. Southern Poland had a different postglacial history and was under the influence of an Eastern/Western Carpathian cryptic refugium. More forest species should be checked in a west–east gradient in Europe to corroborate the hypothesis on the Western European glacial refugia.
A Systematic Literature Review of Approaches to Reengineering for Multi-Channel Access

The increasing power of mobile devices means that companies and institutions can now look to exposing their systems to these devices. As part of a research project, we need to re-engineer a system to expose it 'as a service' in order to enable access by multiple devices. The aim of this study was to identify approaches to the re-engineering of systems to provide multichannel service-oriented access. A systematic literature review was performed to gather relevant information. We found fifteen methods of service-oriented re-engineering, two methods of re-engineering for multichannel access plus a set of problems that had been identified during the re-engineering activities. The two methods found did not meet our needs. The verbosity of Web-services and the limitations of mobile access is an issue that needs further investigation.
Experimental Studies on Stereo Vision Based Motion Recovery with Occlusions

The problem of motion recovery in the theory of machine vision is considered under perspective stereo vision. The object moving in space may be occluded from the cameras for some observation time intervals. First it is shown that the so-called motion parameters are identifiable generically in a normal stereo settings, where the object is visible from the two cameras simultaneously at least in a nonzero time interval. Then by developing an experimental stereo vision system and using extended Kalman filter for identification, we examined the validity experimentally.
Real-Time Distributed Visual Feature Extraction from Video in Sensor Networks

Enabling visual sensor networks to perform visual analysis tasks in real-time is challenging due to the computational complexity of detecting and extracting visual features. A promising approach to address this challenge is to distribute the detection and the extraction of local features among the sensor nodes, in which case the time to complete the visual analysis of an image is a function of the number of features found and of the distribution of the features in the image. In this paper we formulate the minimization of the time needed to complete the distributed visual analysis for a video sequence subject to a mean average precision requirement as a stochastic optimization problem. We propose a solution based on two composite predictors that reconstruct randomly missing data, and use a quantile-based linear approximation of the feature distribution and time series analysis methods. The composite predictors allow us to compute an approximate optimal solution through linear programming. We use two surveillance videos to evaluate the proposed algorithms, and show that prediction is essential for controlling the completion time. The results show that the last value predictor together with regular quantile-based distribution approximation provide a low complexity solution with very good performance.
Fully differential dual-band image reject receiver in SiGe BiCMOS

A fully differential, dual-band, image reject receiver chip is described. SiGe BiCMOS (ft=45 GHz) enables high dynamic range with NF=2.8/4.1 dB (900 MHz/1.8 GHz) including requisite balun loss, IIP3 >-17 dBm, Gp=22 dB, and image rejection >40 dB at 2.7V (87mW).
Minimum Density Hyperplanes

Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is central to many statistical and machine learning approaches to the classification of unlabelled data. We propose a novel hyperplane classifier for clustering and semi-supervised classification which is motivated by this objective. The proposed minimum density hyperplane minimises the integral of the empirical probability density function along it, thereby avoiding intersection with high density clusters. We show that the minimum density and the maximum margin hyperplanes are asymptotically equivalent, thus linking this approach to maximum margin clustering and semi-supervised support vector classifiers. We propose a projection pursuit formulation of the associated optimisation problem which allows us to find minimum density hyperplanes efficiently in practice, and evaluate its performance on a range of benchmark datasets. The proposed approach is found to be very competitive with state of the art methods for clustering and semi-supervised classification.
Number 1003 : April 2010 A Steplength Algorithm for Fitting ERGMs

Markov chain Monte Carlo methods can be used to approximate the intractable normalizing constants that arise in likelihood calculations for many exponential family random graph models for networks. However, in practice, the resulting approximations degrade as parameter values move away from the value used to define the Markov chain. Here, we introduce a method of moving toward a maximum likelihood estimator (MLE) from an arbitrary starting parameter value in a series of steps based on alternating between the canonical exponential family parameterization and the mean-value parameterization. This technique enables us to find an approximate MLE in many cases where this was previously not possible. We illustrate these methods on a transcriptional regulation network for E. Coli, an example where previous attempts to approximate an MLE had failed. These methods are implemented in the publicly available ergm package for R, and computer code to duplicate the results of this paper is included in the Supplementary Materials.
Personalized Academic Paper Recommendation System

Recommendation systems can take advantage of social media in various ways. One common example is combining social relationship into neighborhood-based recommendation systems, under the assumption that social relationship affects individuals’ interest or preference. Although this assumption may not be always true, this paper presents a realistic application, personalized academic paper recommendation system, which social relationship can be closely related to taste. There is an increasing number of academic papers being published each year, but most researchers rely on keyword-based search or browsing through proceedings of top conferences and journals to nd their related work. Personalized academic paper recommendation system is designed to reduce their workload. With a collaborative-lt eringbased approach, it recommends potentially preferred articles for each researcher in personalized manner. Both computational evaluation and user study demonstrate that our system recommends a useful set of research papers.
Type-2 fuzzy sets made simple

Type-2 fuzzy sets let us model and minimize the effects of uncertainties in rule-base fuzzy logic systems. However, they are difficult to understand for a variety of reasons which we enunciate. In this paper, we strive to overcome the difficulties by: (1) establishing a small set of terms that let us easily communicate about type-2 fuzzy sets and also let us define such sets very precisely, (2) presenting a new representation for type-2 fuzzy sets, and (3) using this new representation to derive formulas for union, intersection and complement of type-2 fuzzy sets without having to use the Extension Principle.
Long-term evolution of dim isolated neutron stars

TheX-raydimisolatedneutronstars(XDINs)haveperiodsinthesamerangeastheanomalous X-ray pulsars (AXPs) and the soft gamma-ray repeaters (SGRs). We apply the fallback disc model, which explains the period clustering and other properties of AXP/SGRs, to the six XDINswithmeasuredperiodsandperiodderivatives.PresentpropertiesofXDINsareobtained in evolutionary scenarios with surface dipole magnetic fields B0 ∼ 10 12 G. The XDINs have gone through an accretion epoch with rapid spin-down earlier, and have emerged in their current state, with the X-ray luminosity provided by neutron star cooling and no longer by accretion. Our results indicate that the known XDINs are not likely to be active radio pulsars, as the low B0, together with their long periods place these sources clearly below the 'death
Monetary Policy and Corporate Investment in France

Using a large panel of 6946 French manufacturing firms, this paper investigates the effect of sales, of the cost of capital and of liquidity constraint variables (cash flow or cash stock) on the stock of capital from 1990 to 1999. The user cost elasticity is at the most 0.26 in absolute terms for all the firms of the sample. Three groups of firms representing around 20 per cent of the sample (firms facing a high risk of bankruptcy, firms belonging to the capital goods sector, firms making extensive use of trade credit) are more sensitive to cash flow. Risky firms are less sensitive to sales, when cash stock replaces cash flow. Simulations following shocks of interest rate (related to monetary policy shocks), provides short run contemporaneous elasticities of investment with respect to interest rate through the user cost and through debt repayments taken into account in cash flow.
Trends in Topics at SE Conferences (1993-2013)

Using topic modeling, we analyse the titles and abstracts of nearly 10,000 papers from 20 years published in 11 top-ranked Software Engineering(SE) conferences between 1993 to 2013. Seven topics are identified as the dominant themes in modern software engineering. We show that these topics are not static, rather, some of them are becoming decidedly less prominent over time (modeling) while others are become very prominent indeed (defect analysis). By clustering conferences according to the topics they publish, we identify four large groups of SE conferences, e.g. ASE, FSE and ICSE publish mostly the same work (exceptions: there are more program analysis results in FSE than in ASE or ICSE). Using these results, we offer numerous recommendations including how to plan an individual's research program, when to make or merge conferences, and how to encourage a broader range of topics at SE conferences. An extended version of this paper, that analyzes more conferences and papers, is available on https://goo.gl/mVdyfj.
TEMPORALLY ENHANCED SPEECH IS MORE INTELLIGIBLE IN REVERBERANT ENVIRONMENTS

Reverberation causes degradation in speech comprehension, especially for elderly people, the hearing-impaired and non-native listeners. In order to prevent intelligibility degradation, we developed several pre-processing techniques, where signals are processed before being radiated through the loudspeakers of a public address system. The two main techniques are modulation filtering and steady-state suppression, both of which enhance the temporal dynamics of speech. Previously we had found that the important frequencies of temporal dynamics for speech perception, the modulation frequencies, lie between 1-16 Hz (Arai et al., 1999). Therefore, we configured the modulation filtering to emphasize these modulation frequencies (Kusumoto et al., 2005). In this paper, we mainly discussed steady-state suppression (Arai et al., 2001, 2002), which suppresses steady-state portions of speech to reduce overlap-masking and improve speech intelligibility for young, elderly, and non-native listeners in reverberant environments (Hodoshima et al., 2006a; Miyauchi et al., 2005; Hodoshima et al., 2006b). Especially, we discussed how the “pre-processing” technique, such as the steady-state suppression, is effective with recent results including speech-rate slowing with the steady-state suppression exceeding a simple speech-rate slowing approach (Arai et al., 2005).
A High-Performance Significand BCD Adder with IEEE 754-2008 Decimal Rounding

We present a new method and architecture to merge efficiently IEEE 754­-2008 decimal rounding with significand BCD addition and subtraction. This is a key component to improve several decimal floating-point operations such as addition, multiplication and fused multiply-add. The decimal rounding unit is based on a direct implementation of the IEEE 754­2008 round­ing modes. We show that the resultant implementations for IEEE 754-2008 Decimal64 (16 precision digits) and Decimal128 (34 precision digits) formats reduce significantly the area and latency required for significand BCD addition/subtraction and decimal rounding in previous high-performance decimal floating-point adders.
A Principled Approach to Version Control

Version control systems are essential for managing the distributed development of large software projects. We present a formal model for reasoning about version control. In particular, we give a general deﬁnition of patch . Patches abstract over the data on which they operate, making our framework equally suited for version control of everything from highly-structured XML ﬁles to blobs of bits. We model repositories as a multiset of patches. The mathematical deﬁnitions of patches and repositories enable us to reason about complicated issues such as conﬂicts and conﬂict resolution.