Miracle-dz/UniFAR-FTUs huggingface dataset:
Bootstrapping structure into language : alignment-based learning

refined and abstract meanings largely grow out of more concrete meanings. Bloomfield (1933) This thesis introduces a new unsupervised learning framework, called Alignment-Based Learning, which is based on the alignment of sentences and Harris's (1951) notion of substitutability . Instances of the framework can be applied to an untagged, unstructured corpus of natural language sentences, resulting in a labelled, bracketed version of that corpus. Firstly, the framework aligns all sentences in the corpus in pairs, resulting in a partition of the sentences consisting of parts of the sentences that are equal in both sentences and parts that are unequal. Unequal parts of sen tences can be seen as being substitutable for each other, since substituting one unequal part for the other results in another valid sentence. The unequal parts of the sentences are thus considered to be possible (possibly overlapping) constituents, called hypotheses. Secondly , the selection learning phase considers all hypotheses found by the alignment learning phase and selects the best of these. The hypotheses are selected based on the order in which they were found, or based on a probabilistic function. The framework can be extended with a grammar extraction phase. This extended framework is called parseABL. Instead of returning a structured version of the unstructured input corpus, like the ABL system, this system also returns a stochastic context-free or tree substitution grammar. Different instances of the framework have been tested on the English ATIS corpus, the Dutch OVIS corpus and the Wall Street Journal corpus. One of the interesting results, apart from the encouraging numerical results, is that all instances can (and do) learn recursive structures.
Investigation on log-linear interpolation of multi-domain neural network language model

Inspired by the success of multi-task training in acoustic modeling, this paper investigates a new architecture for a multi-domain neural network based language model (NNLM). The proposed model has several shared hidden layers and domain-specific output layers. As will be shown, the log-linear interpolation of the multi-domain outputs and the optimization of interpolation weights fit naturally in the framework of NNLM. The resulting model can be expressed as a single NNLM. As an initial study of such an architecture, this paper focuses on deep feed-forward neural networks (DNNs). We also re-investigate the potential of long context up to 30-grams, and depth up to 5 hidden layers in DNN-LM. Our final feed-forward multidomain NNLM is trained on 3.1B running words across 11 domains for English broadcast news and conversations large vocabulary continuous speech recognition task. After log-linear interpolation and fine-tuning, we measured improvements in terms of perplexity and word error rate over the models trained on 50M running words of in-domain news resources. The final multi-domain feed-forward LM outperformed our previous best LSTM-RNN LM trained on the 50M in-domain corpus, even after linear interpolation with large count models.
Stability of smeared black branes and the Gubser-Mitra conjecture

Recently, it was suggested that the system of smeared black branes might provide a counter example to the Gubser-Mitra conjecture. Concerning to this issue, we have investigated the s-wave perturbation analysis to see how the stability of such system behaves. Some partial results are reported in this meeting.
Bearing fault diagnosis using Radial Basis Function network and adaptive neuro fuzzy classifier

This paper is focused on the rolling element bearing fault diagnosis using radial basis function (RBF) network and adaptive neuro fuzzy classifier (ANFC). Defect considered for the study are inner race defect, outer race defect and ball defect. Vibration data for healthy bearing is used as baseline data. Multi scale permutation entropy (MPE) is applied to extract feature from the vibration signals. Then, attribute selection is done by best first search algorithm. A comparative study is carried out using ANFC and RBF network. Result shows that these methods has potential in diagnosis of incipient bearing defects and can be used for reliable fault diagnosis.
The H i content of Fornax dwarf elliptical galaxies: FCC032 and FCC336

We present H I21-cm line observations, obtained with the Australia Telescope Compact Array, of two dwarf elliptical galaxies (dEs) in the Fomax cluster: FCC032 and FCC336. The optical positions and velocities of these galaxies place them well within the Fornax cluster. FCC032 was detected at the 3σ significance level with a total HI flux density of 0.66 ± 0.22 Jy km s -1 or an HI mass of 5.0 ± 1.7 x 10 7 h -2 75 M ○. Based on our deep Ha + [N II] narrow-band images, obtained with FORS2 mounted on the Very Large Telescope, this dE was already known to contain 600 -1800 h -2 75 M ○. of ionized hydrogen (depending on the relative strengths of the Hα and [N II] emission lines). Hence, this is the first study of the complex, multiphase interstellar medium of a dE outside the Local Group. FCC336 was detected at the same significance level: 0.37 ± 0.10 Jy km s -1 or a total H I mass of 2.8 ± 0.7 x 10 7 h -2 75 M ○. Using a compilation of H I data of dwarf galaxies, we find that the observed high HI mass boundary of the distribution of dwarf irregulars, blue compact dwarfs and dwarf ellipticals in a log L B versus log M HI diagram is in good agreement with a simple chemical evolution model with continuous star formation. The existence of many gas-poor dEs (undetected at 21 cm) suggests that the environment (or, more particularly, a galaxy's orbit within a cluster) also plays a crucial role in determining the amount of gas in present-day dEs; for example, FCC032 and FCC336 are located in the sparsely populated outskirts of the Fomax cluster. This is in agreement with H I surveys of dEs in the Virgo cluster, and an Ha survey of the Fornax cluster, which also tend to place gas-rich dwarf galaxies in the cluster periphery.
Los círculos y clubes católicos del Partido Unión Católica (1890-1894)

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Antitrust Policy During the Clinton Administration

Antitrust Policy During the Clinton Administration ∗ Robert E. Litan and Carl Shapiro † July 2001 1. Introduction For at least twenty years, a broad, bi-partisan consensus has prevailed regarding the goal of U.S. antitrust policy: to foster competitive markets and to control monopoly power, not to protect smaller firms from tough competition by larger corporations. The interests of consumers in lower prices and improved products are paramount. When these interests are served by large, efficient firms, even firms with substantial shares of well-defined markets, the consensus view is that antitrust policy should applaud, not stand in the way. However, when those large and powerful firms wield their power to exclude rivals in unreasonable ways, antitrust policy should act to preserve competition, both on prices and regarding product improvements stemming from innovation. Since the 1970s, these principles have been widely accepted, and antitrust law and policy have fundamentally been about economics – promoting competition and consumer benefits – not about broader social objectives such as favoring domestic firms, preserving employment, or protecting small businesses. Within these confines, antitrust policy turned more activist during the Clinton years than in the prior Bush Administration, and sharply more active than during the Reagan Administration. To the general public, the most visible symbol of this activism was surely the Microsoft antitrust trial, which led in May 2000 to a dramatic court order (reversed on appeal in June 2001) that Microsoft be broken up. To practicing antitrust lawyers and academicians who specialize in the field, the upturn in antitrust activity was evident in many more ways: in challenges to several large corporate mergers, in the uncovering and prosecution of some large Litan and Shapiro on Antitrust Policy, Page 1
Cell biology and clinical promise of G-CSF: immunomodulation and neuroprotection

• Introduction • The immunomodulation of G‐CSF in adaptive immunity – G‐CSF as a regulator of T cell responses – G‐CSF as an inducer of tolerogenic dendritic cells (DC) – Mechanisms of action of G‐CSF in immunomodulation – Therapeutic potential of G‐CSF in autoimmune diseases • The neuroprotection of G‐CSF in cerebral ischemia and neurodegeneration – The expression of G‐CSF and G‐CSF receptor in central nervous system – Penetration of the blood‐brain barrier – Mechanisms of G‐CSF in neuroprotection – G‐CSF mobilizes haematopoietic stem cells to the injured brain – G‐CSF activates anti‐apoptotic pathway – G‐CSF drives neuronal differentiation – G‐CSF enhances angiogenesis – Evidence for neuroprotection of G‐CSF • G‐CSF‐Bridge between immunomodulation and neuroprotection • Weighing G‐CSF in immunomodulation and neuroprotection • Conclusion and perspectives
Building a Better Term Paper: Integrating Scaffolded Writing and Peer Review

This paper presents a method for teaching undergraduate students how to write better term papers in philosophy. The method integrates two key assignment components: scaffolding and peer review. We explain these components and how they can be effectively combined within a single term paper assignment. We then present the results of our multi-year research study on the integrated method. Professor observations, quantitative measures, and qualitative feedback indicate that student writing improves when philosophy term paper assignments are designed to generate multiple rounds of drafting and review. Undergraduates today write more than ever before, though seldom at length. They contribute to discussion boards, write short papers, and answer exam questions. Above all, they compose enormous quantities of text messages, emails, and social media postings. Such writing enables the development of some important abilities, but it does not teach students the crucial critical thinking skills associated with researching and developing an extended philosophical argument. We have developed a method for teaching students how to write better term papers. To ensure broad applicability, the first author, a philosopher, worked with two sociologists (second and third authors). The resulting method is well suited for lower as well as upper division courses, large as well as small courses. It is comprised of two integrated components. First, the term paper assignment is scaffolded, meaning that students draft and revise their papers in progressive stages, focusing upon different writing skills at each stage. Second, students work together throughout the term in peer writing groups that include students of diverse abilities. Within these groups, students practice 482 PADGETT WALSH, PROKOS, AND BIRD specific skills and receive feedback from their peers while writing their papers. This integrated method combines the pedagogical virtues of scaffolding and peer review. And it leads to improved student writing, as indicated by our multi-year study. Our findings are two-fold: First, student writing performance improved across the board, but especially amongst students who initially had low writing grades. Second, students, especially those in their junior and senior years, perceived significant improvements in their writing abilities over the course of the term. Taken together, these findings suggest that the method of combining scaffolded term paper assignments with peer review is effective in helping students become better writers.
Hormone-Dependent Bacterial Growth, Persistence and Biofilm Formation – A Pilot Study Investigating Human Follicular Fluid Collected during IVF Cycles

Human follicular fluid, considered sterile, is aspirated as part of an in vitro fertilization (IVF) cycle. However, it is easily contaminated by the trans-vaginal collection route and little information exists in its potential to support the growth of microorganisms. The objectives of this study were to determine whether human follicular fluid can support bacterial growth over time, whether the steroid hormones estradiol and progesterone (present at high levels within follicular fluid) contribute to the in vitro growth of bacterial species, and whether species isolated from follicular fluid form biofilms. We found that bacteria in follicular fluid could persist for at least 28 weeks in vitro and that the steroid hormones stimulated the growth of some bacterial species, specifically Lactobacillus spp. , Bifidobacterium spp. Streptococcus spp. and E. coli. Several species, Lactobacillus spp. , Propionibacterium spp. , and Streptococcus spp. , formed biofilms when incubated in native follicular fluids in vitro (18/24, 75%). We conclude that bacteria aspirated along with follicular fluid during IVF cycles demonstrate a persistent pattern of growth. This discovery is important since it can offer a new avenue for investigation in infertile couples.
Pilot tone selection in OFDM amplified-and-forward relay system

Channel estimation for OFDM amplify-and-forward relay system requires transmission of pilot tones in source node, and different pilot tones can be derived according to different channel estimation algorithms and OFDM scenarios. This paper derives two different pilot tones with different scenarios: 1) no virtual subcarrier is applied in OFDM system and LS algorithm is used in channel estimation; 2) virtual subcarriers are applied in OFDM system and RLS algorithm is used in channel estimation.
Incentive-compatible online auctions for digital goods

Goldberg et al. [6] recently began the study of incentive-compatible auctions for digital goods, that is, goods which are available in unlimited supply. Many digital goods, however, such as books, music, and software, are sold continuously, rather than in a single round, as is the case for traditional auctions. Hence, it is important to consider what happens in the online version of such auctions. We define a model for online auctions for digital goods, and within this model, we examine auctions in which bidders have an incentive to bid their true valuations, that is, incentive-compatible auctions. Since the best offline auctions achieve revenue comparable to the revenue of the optimal fixed pricing scheme, we use the latter as our benchmark. We show that deterministic auctions perform poorly relative to this benchmark, but we give a randomized auction which is within a factor O(exp√log log h) of the benchmark, where h is the ratio between the highest and lowest bids. As part of this result, we also give a new offline auction, which improves upon the previously best auction in a certain class of auctions for digital goods. We also give lower bounds for both randomized and deterministic online auctions for digital goods.
Design of active inputs for set-based fault diagnosis

Effective fault diagnosis depends on the detectability of the faults in the measurements, which can be improved by a suitable input signal. This article presents a deterministic method for computing the set of inputs that guarantee fault diagnosis, referred to as separating inputs. The process of interest is described, under nominal and various faulty conditions, by linear discrete-time models subject to bounded process and measurement noise. It is shown that the set of separating inputs can be efficiently computed in terms of the complement of one or several zonotopes, depending on the number of fault models. In practice, it is essential to choose elements from this set that are minimally harmful with respect to other control objectives. It is shown that this can be done efficiently through the solution of a mixed-integer quadratic program. The method is demonstrated for a numerical example.
On the compression of locational and environmental data in multi-vehicle missions: a control systems approach

Mobile agents that take part in multi-vehicle missions usually need to share environmental and locational information with other agents and with control stations through a communication channel. In real scenarios, the agents have to deal with different communication issues, such as interference, loss of connectivity and unexpected reduction of available bandwidth. One way to overcome these issues is by minimising the amount of data in the communication channel, which not only speeds up the sharing of information, but would also avoid the loss of data. We propose a control systems approach that allows the compression of the shared information. Given some problem-dependent mathematical assumptions, our method aims to simplify the calculation of the stationary errors by computing the sign of the errors rather than their exact values and the control law may then be used to stabilise the system. The approach allows for the compression of the outputs involved in the calculation of the errors as such outputs represent the shared information among agents. We carry out the theoretical analysis of our approach and apply it to two case studies, namely a formation control and a coverage control with consensus. We finally validate our theoretical results through simulations in Matlab.
Comparison of Sun-Induced Chlorophyll Fluorescence Estimates Obtained from Four Portable Field Spectroradiometers

Remote Sensing of Sun-Induced Chlorophyll Fluorescence (SIF) is a research field of growing interest because it offers the potential to quantify actual photosynthesis and to monitor plant status. New satellite missions from the European Space Agency, such as the Earth Explorer 8 FLuorescence EXplorer (FLEX) mission—scheduled to launch in 2022 and aiming at SIF mapping—and from the National Aeronautics and Space Administration (NASA) such as the Orbiting Carbon Observatory-2 (OCO-2) sampling mission launched in July 2014, provide the capability to estimate SIF from space. The detection of the SIF signal from airborne and satellite platform is difficult and reliable ground level data are needed for calibration/validation. Several commercially available spectroradiometers are currently used to retrieve SIF in the field. This study presents a comparison exercise for evaluating the capability of four spectroradiometers to retrieve SIF. The results show that an accurate far-red SIF estimation can be achieved using spectroradiometers with an ultrafine resolution (less than 1 nm), while the red SIF estimation requires even higher spectral resolution (less than 0.5 nm). Moreover, it is shown that the Signal to Noise Ratio (SNR) plays a significant role in the precision of the far-red SIF measurements.
Scalable and Privacy-Preserving Variants of the Austrian Electronic Mandate System in the Public Cloud

The current Austrian electronic mandate system, which allows citizens to act as representatives for other citizens or companies in e-Government services, relies on a centralized deployment approach. Thereby, a trusted central service generates and issues electronic mandates on the fly for service providers. The usage of this service is continuously increasing and high loads can be expected in the near future. In order to mitigate the associated scalability issues, this service could be moved into the public cloud. However, a move of a trusted service into the public cloud brings up new obstacles, especially with respect to citizens' privacy. In this paper we propose two approaches how this move could be successfully realized by preserving citizens' privacy and still being compliant to national law. The main objectives we focus on are minimal data disclosure to untrusted entities by still keeping the existing infrastructure nearly untouched. We present both approaches in detail and evaluate their capabilities with respect to citizens' privacy protection as well as their practicability and conclude that both approaches are entirely practical.
Decision tree state clustering with word and syllable features

In large vocabulary continuous speech recognition, decision trees are widely used to cluster triphone states. In addition to commonly used phonetically based questions, others have proposed additional questions such as phone position within word or syllable. This paper examines using the word or syllable context itself as a feature in the decision tree, providing an elegant way of introducing word- or syllable-specific models into the system. Positive results are reported on two state-of-the-art systems: voicemail transcription and a search by voice tasks across av ariety of acoustic model and training set sizes. Index Terms :d ecision tree state clustering, large vocabulary continuous speech recognition, tagged clustering.
An updated catalogue of salivary gland transcripts in the adult female mosquito, Anopheles gambiae

SUMMARY Salivary glands of blood-sucking arthropods contain a variety of compounds that prevent platelet and clotting functions and modify inflammatory and immunological reactions in the vertebrate host. In mosquitoes, only the adult female takes blood meals, while both sexes take sugar meals. With the recent description of the Anopheles gambiae genome, and with a set of∼ 3000 expressed sequence tags from a salivary gland cDNA library from adult female mosquitoes, we attempted a comprehensive description of the salivary transcriptome of this most important vector of malaria transmission. In addition to many transcripts associated with housekeeping functions, we found an active transposable element, a set of Wolbachia-like proteins, several transcription factors, including Forkhead, Hairy and doublesex, extracellular matrix components and 71 genes coding for putative secreted proteins. Fourteen of these 71 proteins had matching Edman degradation sequences obtained from SDS-PAGE experiments. Overall, 33 transcripts are reported for the first time as coding for salivary proteins. The tissue and sex specificity of these protein-coding transcripts were analyzed by RT–PCR and microarray experiments for insight into their possible function. Notably, two gene products appeared to be differentially spliced in the adult female salivary glands, whereas 13 contigs matched predicted intronic regions and may include additional alternatively spliced transcripts. Most An. gambiae salivary proteins represent novel protein families of unknown function, potentially coding for pharmacologically or microbiologically active substances. Supplemental data to this work can be found at http://www.ncbi. nlm.nih. gov/projects/omes/index.html#Ag2.
A Novel Hybrid FPGA Architecture

In this paper, a new hybrid field programmable gate array (FPGA) architecture is proposed. The logic tile, which consists of a logic cluster and related connection boxes (CBs), can be configured as either programmable logic arrays (PLAs) or look-up tables (LUTs). This architecture can be classified as AND-LUT array. PLAs are suitable for the implementation of large fan-in logic circuits, while LUTs are used to implement low fan-in logic circuits. As a result, the proposed hybrid FPGA architecture (HFA) is more flexible to improve logic density. Experimental results based on MCNC benchmark circuits were performed between the hybrid architecture and conventional LUT-based symmetrical FPGA architecture in term of area consumption. Preliminary results indicate that 46% chip area is reduced using the new architecture