Miracle-dz/UniFAR-FTUs huggingface dataset:
ACL 2006 Multiword Expressions : Identifying and Exploiting Underlying Properties

This paper reports on an experiment in which we explore a new approach to the automatic measurement of multi-word expression (MWE) compositionality. We propose an algorithm which ranks MWEs by their compositionality relative to a semantic field taxonomy based on the Lancaster English semantic lexicon (Piao et al., 2005a). The semantic information provided by the lexicon is used for measuring the semantic distance between a MWE and its constituent words. The algorithm is evaluated both on 89 manually ranked MWEs and on McCarthy et al’s (2003) manually ranked phrasal verbs. We compared the output of our tool with human judgments using Spearman’s rank-order correlation coefficient. Our evaluation shows that the automatic ranking of the majority of our test data (86.52%) has strong to moderate correlation with the manual ranking while wide discrepancy is found for a small number of MWEs. Our algorithm also obtained a correlation of 0.3544 with manual ranking on McCarthy et al’s test data, which is comparable or better than most of the measures they tested. This experiment demonstrates that a semantic lexicon can assist in MWE compositionality measurement in addition to statistical algorithms.
Towards Accurate Histogram Publication under Differential Privacy

Histograms are the workhorse of data mining and analysis. This paper considers the problem of publishing histograms under differential privacy, one of the strongest privacy models. Existing differentially private histogram publication schemes have shown that clustering (or grouping) is a promising idea to improve the accuracy of sanitized histograms. However, none of them fully exploits the benefit of clustering. In this paper, we introduce a new clustering framework. It features a sophisticated evaluation of the trade-off between the approximation error due to clustering and the Laplace error due to Laplace noise injected, which is normally overlooked in prior work. In particular, we propose three clustering strategies with different orders of run-time complexities. We prove the superiority of our approach by theoretical utility comparisons with the competitors. Our extensive experiments over various standard real-life and synthetic datasets confirm that our technique consistently outperforms existing competitors.
Dynamic Influence Networks for Rule-Based Models

We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the data produced by KaSim, an open source stochastic simulator of rule-based models written in the Kappa language, DINs provide a node-link diagram that represents the influence that each rule has on the other rules. That is, rather than representing individual biological components or types, we instead represent the rules about them (as nodes) and the current influence of these rules (as links). Using our interactive DIN-Viz software tool, researchers are able to query this dynamic network to find meaningful patterns about biological processes, and to identify salient aspects of complex rule-based models. To evaluate the effectiveness of our approach, we investigate a simulation of a circadian clock model that illustrates the oscillatory behavior of the KaiC protein phosphorylation cycle.
Modified Low-Dose Triiodo-L-thyronine Therapy Safely Improves Function Following Myocardial Ischemia-Reperfusion Injury

Background: We have shown that thyroid hormones (THs) are cardioprotective and can be potentially used as safe therapeutic agents for diabetic cardiomyopathy and permanent infarction. However, no reliable, clinically translatable protocol exists for TH treatment of myocardial ischemia-reperfusion (IR) injury. We hypothesized that modified low-dose triiodo-L-thyronine (T3) therapy would confer safe therapeutic benefits against IR injury. Methods: Adult female rats underwent left coronary artery ligation for 60 min or sham surgeries. At 2 months following surgery and T3 treatment (described below), the rats were subjected to functional, morphological, and molecular examination. Results: Following surgery, the rats were treated with T3 (8 μg/kg/day) or vehicle in drinking water ad libitum following IR for 2 months. Oral T3 significantly improved left ventricular (LV) contractility, relaxation, and relaxation time constant, and decreased beta-myosin heavy chain gene expression. As it takes rats ~6 h post-surgery to begin drinking water, we then investigated whether modified T3 dosing initiated immediately upon reperfusion confers additional improvement. We injected an intraperitoneal bolus of T3 (12 μg/kg) upon reperfusion, along with low-dose oral T3 (4.5 μg/kg/day) in drinking water for 2 months. Continuous T3 therapy (bolus + low-dose oral) enhanced LV contractility compared with oral T3 alone. Relaxation parameters were also improved compared to vehicle. Importantly, these were accomplished without significant increases in hypertrophy, serum free T3 levels, or blood pressure. Conclusions: This is the first study to provide a safe cardiac therapeutic window and optimized, clinically translatable treatment-monitoring protocol for myocardial IR using commercially available and inexpensive T3. Low-dose oral T3 therapy supplemented with bolus treatment initiated upon reperfusion is safer and more efficacious.
Using multiple imputation to simulate time series

Multiple Imputation is a Markov chain Monte Carlo technique developed to work out missing data problems. This paper proposes a different point of view to use this technique with time series. The authors' idea consists on an endogenous construction of the database to avoid noise in the simulations and reach the right convergence of the limit distribution of the chain. New computer code was designed to carry out all the simulations.
Probabilistic Labeling Cost for High-Accuracy Multi-view Reconstruction

In this paper, we propose a novel labeling cost for multi- view reconstruction. Existing approaches use data terms with specific weaknesses that are vulnerable to common challenges, such as low-textured regions or specularities. Our new probabilistic method implicitly discards outliers and can be shown to become more exact the closer we get to the true object surface. Our approach achieves top results among all published methods on the Middlebury DINO SPARSE dataset and also delivers accurate results on several other datasets with widely varying challenges, for which it works in unchanged form.
Smart Powder Processing for Advanced Materials

Recently, various novel powder processing techniques were rapidly developed for advanced material production due to the growing of high-tech industry, especially in consideration of energy consumption and the environmental issues such as the recycling of waste materials. Smart powder processing stands for novel powder processing techniques that create advanced materials with minimal energy consumption and environmental impacts. Particle bonding technology is a typical smart powder processing technique to make advanced composites. The technology has two main unique features. Firstly, it creates direct bonding between particles without any heat support or binders of any kind in the dry phase. The bonding is achieved through the enhanced particle surface activation induced by mechanical energy, in addition to the intrinsic high surface reactivity of nanoparticles. Using this feature, desired composite particles can Abstract
Second-order signature: a tool for specifying data models, query processing, and optimization

We propose a framework for the specification of extensible database systems. A particular goal is to implement a software component for parsing and rule-based optimization that can be used with widely varying data models and query languages as well as representation and query processing systems. The key idea is to use second-order signature (and algebra), a system of two coupled many-sorted signatures, where the top-level signature offers kinds and type constructors and the bottom-level signature provides polymorphic operations over the types defined as terms of the top level. Hence the top level can be used to define a data or representation model and the bottom level to describe a query algebra or a query processing algebra. We show the applicability of this framework by examples drawn from relational modeling and query processing.
Production of Monoclonal Antibodies against the Major Capsid Protein of the Lactococcus Bacteriophage ul36 and Development of an Enzyme-Linked Immunosorbent Assay for Direct Phage Detection in Whey and Milk

The only major structural protein (35 kDa) of the lactococcal small isometric-headed bacteriophage ul36, a member of the P335 species, was isolated from a preparative sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis. Monoclonal antibodies (MAbs) were raised against the denatured 35-kDa protein. Six MAbs were selected and characterized. Western blots (immunoblots) showed that all MAbs recognized the 35 kDa but also a 45 kDa that is in lower concentration in the phage structure. Binding inhibition assays identified five families of MAbs that recognized nonoverlapping epitopes of the 35- and 45-kDa proteins. Immunoelectron microscopy showed that these two proteins are localized within the phage head, therefore indicating that the 35 kDa is a major capsid protein of ul36 and that the 45 kDa is a minor capsid protein. With two MAbs, a sandwich enzyme-linked immunosorbent assay (ELISA) was developed for direct detection of lactococcal phages in whey and milk samples. Whey and milk components, however, interfered with the conduct of the assay. Partial denaturation of milk samples by heat treatment in the presence of SDS and β-mercaptoethanol removed the masking effect and increased the sensitivity of the assay by 100-fold. With the method used here, 107 PFU/ml were detected by the ELISA within 2 h without any steps to enrich or isolate bacteriophages.
Low-Power Reconfigurable Network Architecture for On-Chip Photonic Interconnects

Photonic Networks-On-Chip have emerged as a viable solution for interconnecting multicore computer architectures in a power-efficient manner. Current architectures focus on large messages, however, which are not compatible with the coherence traffic found on chip multiprocessor networks. In this paper, we introduce a reconfigurable optical interconnect in which the topology is adapted automatically to the evolving traffic situation. This allows a large fraction of the (short) coherence messages to use the optical links, making our technique a better match for CMP networks when compared to existing solutions. We also evaluate the performance and power efficiency of our architecture using an assumed physical implementation based on ultra-low power optical switching devices and under realistic traffic load conditions.
Oscillatory Activity in the Infant Brain and the Representation of Small Numbers

Gamma-band oscillatory activity (GBA) is an established neural signature of sustained occluded object representation in infants and adults. However, it is not yet known whether the magnitude of GBA in the infant brain reflects the quantity of occluded items held in memory. To examine this, we compared GBA of 6–8 month-old infants during occlusion periods after the representation of two objects vs. that of one object. We found that maintaining a representation of two objects during occlusion resulted in significantly greater GBA relative to maintaining a single object. Further, this enhancement was located in the right occipital region, which is consistent with previous object representation research in adults and infants. We conclude that enhanced GBA reflects neural processes underlying infants’ representation of small numbers.
On the Expansion of the Giant Component in Percolated (n, d,λ) Graphs

Let d ≥ d0 be a sufficiently large constant. An $(n, d, c \sqrt{d})$ graph G is a d-regular graph over n vertices whose second-largest (in absolute value) eigenvalue is at most $c \sqrt{d}$. For any 0<p<1, Gp is the graph induced by retaining each edge of G with probability p. It is known that for $p>\frac{1}{d}$ the graph Gp almost surely contains a unique giant component (a connected component with linear number vertices). We show that for $p \geq \frac{5c}{\sqrt{d}}$ the giant component of Gp almost surely has an edge expansion of at least $\frac{1}{\log n}$.
Morphology and tensile properties of bast fibers extracted from cotton stalks

Bast fiber contained in cotton stalk, a residue from the growth of cotton fiber, is available in very large quantities, estimated at more than 15 million tonnes annually. The stalk is currently burnt or buried into soil. In this study, bast fibers were extracted from cotton stalk using a mechanical decortication method. The morphology of single bast fibers, also known as ultimates or ultimate fibers, were characterized by an effective diameter and a cell wall thickening factor (maturity) derived from a concentric circle model reconstructed using an image analysis technique. Fiber cells within the same plant are quite consistent in diameter but can vary considerably in maturity depending on their position in the plant. Eighty percent of the bast fibers were contained in the lower half of the stalk where the fiber maturity was high. Cotton bast fibers are as strong as other bast fibers, such as jute and hemp, and can be used as reinforcement for polymer composite materials.
Amelioration of iron overload-induced liver toxicity by a potent antioxidant and iron chelator, Emblica officinalis Gaertn

In liver, the major site of iron storage, iron overload is associated with oxidative damage of protein, lipid, and DNA and causes protein oxidation, lipid peroxidation, and rupture of hepatocytes, leading to cell death. Serum ferritin and liver iron content are the main forecasters of moderate to severe iron overload in the liver. The sequels of excess iron deposition in the liver are fibrosis and enhanced levels of serum enzymes and bilirubin markers. Emblica officinalis (EO) fruit extract was found efficient in lessening intraperitoneally injected iron dextran-induced liver toxicity in Swiss albino mice. Mice administered with different doses of 70% methanol extract of EO (50, 100, and 200 mg kg−1 body weight) showed significant decrease in liver iron, serum ferritin, and serum enzyme levels, along with the decrease in lipid peroxidation, protein oxidation, and collagen content. The activity was further supported by its considerable iron chelation with half-maximal inhibitory concentration of 70.24 ± 2.74 μg ml−1 and the protection on ferrous ion-mediated DNA breakdown with 50% protection ([P]50) of 1.04 ± 0.01 μg ml−1. Simultaneously, the extract effectively induced the antioxidant enzyme levels and also exhibited the potential activity of reductive release of ferritin iron. These findings suggest that the EO extract may be used as a potent drug for the treatment of pathological sequences arisen in the iron overload-induced liver damage.
Impact of Social Networking Services on the Performance and Scalability of Web Server Infrastructures

The last generation of Web is characterized by social networking services where users exchange a growing amount of multimedia content. The impact of these novel services on the underlying Web infrastructures is significantly different from traditional Web-based services and has not yet been widely studied.This paper presents a scalability and bottleneck analysis of a Web system supporting social networking services for different scenarios of user interaction patterns, amount of multimedia content and network characteristics.Our study demonstrates that for some social networking services the user interaction patterns may play a fundamental role in the definition of the bottleneck resource and must be considered in the design of systems supporting novel services.
Combined oral contraceptives plus spironolactone compared with metformin in women with polycystic ovary syndrome: a one-year randomized clinical trial.

OBJECTIVE We aimed to compare a combined oral contraceptive (COC) plus the antiandrogen spironolactone with the insulin sensitizer metformin in women with polycystic ovary syndrome (PCOS). DESIGN We conducted a randomized, parallel, open-label, clinical trial comparing COC (30 μg of ethinylestradiol and 150 μg of desogestrel) plus spironolactone (100 mg/day) with metformin (850 mg b.i.d.) for one year in women with PCOS (EudraCT2008-004531-38). METHODS The composite primary outcome included efficacy (amelioration of hirsutism, androgen excess and menstrual dysfunction) and cardiometabolic safety (changes in the frequencies of disorders of glucose tolerance, dyslipidemia and hypertension). A complete anthropometric, biochemical, hormonal and metabolic evaluation was conducted every three months and data were submitted to intention-to-treat analyses. RESULTS Twenty-four patients were assigned to COC plus spironolactone and 22 patients to metformin. Compared with metformin, COC plus spironolactone caused larger decreases in hirsutism score (mean difference 4.6 points, 95% CI: 2.6-6.7), total testosterone (1.1 nmol/L, 0.4-1.7), free testosterone (25 pmol/L, 12-39), androstenedione (5.5 nmol/L, 1.8-9.2) and dehydroepiandrosterone sulfate (2.7 μmol/L, 1.4-4.0). Menstrual dysfunction was less frequent with COC plus spironolactone (OR: 0.06, 95% CI: 0.02-0.23). No differences were found in frequencies of abnormal glucose tolerance (OR: 1.7, 95% CI: 0.7-4.4), dyslipidemia (OR: 0.6, 95% CI: 0.2-1.8) or hypertension (OR: 0.3, 95% CI: 0.5-2.0). No major adverse events occurred and biochemical markers were similarly safe with both treatments. CONCLUSIONS COC plus spironolactone was more effective than metformin for symptoms of PCOS showing similar safety and overall neutral effects on cardiometabolic risk factors.
A high-performance direct 2-D transform coding IP design for MPEG-4AVC/H.264

This paper proposes a high-performance direct two-dimensional transform coding IP design for MPEG-4 AVC/H.264 video coding standard. Because four kinds of 4 /spl times/ 4 transforms, i.e., forward, inverse, forward-Hadamard, and inverse-Hadamard transforms are required in a H.264 encoding system, a high-performance multitransform accelerator is inevitable to compute these transforms simultaneously for fitting real-time processing requirement. Accordingly, this paper proposes a direct 2-D transform algorithm which suitably arranges the data processing sequences adopted in row and column transforms of H.264 CODEC systems to finish the data transposition on-the-fly. The induced new transform architecture greatly increases the data processing rate up to 8 pixels/cycle. In addition, an interlaced I/O schedule is disclosed to balance the data I/O rate and the data processing rate of the proposed multitransform design when integrated with H.264 systems. Using a 0.18-/spl mu/m CMOS technology, the optimum operating clock frequency of the proposed multitransform design is 100 MHz which achieves 800 Mpixels/s data throughput rate with the cost of 6482 gates. This performance can achieve the real-time multitransform processing of digital cinema video (4096 /spl times/ 4 2048@30 Hz). When the data throughput rate per unit area is adopted as the comparison index in hardware efficiency, the proposed design is at least 1.94 times more efficient than the existing designs. Moreover, the proposed multitransform design can achieve HDTV 720p, 1080i, digital cinema video processing requirements by consuming only 0.58, 2.91, and 24.18 mW when operated at 22, 50, and 100 MHz with 0.7, 1.0, and 1.8 V power supplies, respectively.
Socially assistive child-robot interaction in physical exercise coaching

The main contribution of this study is the design and implementation of an autonomous human robot interaction system to engage children in performing several physical exercise motions by providing real-time feedback and guidance. The system is designed after several preliminary experiments with children and exercise coaches. In order to test the feasibility and the effectiveness of the exercise system across a variety of performance and evaluation measures, an experimental study was conducted with 19 healthy children. The results of the study validate the effectiveness of the system in motivating and helping children to complete physical exercises. The children engaged in physical exercise throughout the interaction sessions and rated the interaction highly in terms of enjoyableness, and rated the robot exercise coach highly in terms of social attraction, social presence, and companionship via a questionnaire answered after each session.
Who Believes in the Giant Skeleton Myth? An Examination of Individual Difference Correlates

This study examined individual difference correlates of belief in a narrative about the discovery of giant skeletal remains that contravenes mainstream scientific explanations. A total of 364 participants from Central Europe completed a survey that asked them to rate their agreement with a short excerpt describing the giant skeleton myth. Participants also completed measures of the Big Five personality factors, New Age orientation, anti-scientific attitudes, superstitious beliefs, and religiosity. Results showed that women, as compared with men, and respondents with lower educational qualifications were significantly more likely to believe in the giant skeleton myth, although effect sizes were small. Correlational analysis showed that stronger belief in the giant skeleton myth was significantly associated with greater anti-scientific attitudes, stronger New Age orientation, greater religiosity, stronger superstitious beliefs, lower Openness to Experience scores, and higher Neuroticism scores. However, a multiple regression showed that the only significant predictors of belief in myth were Openness, New Age orientation, and anti-scientific attitudes. These results are discussed in relation to the potential negative consequences of belief in myths.
Is knowing always feeling?

gence. However, as in Gage’s case, the patients frequently demonstrate poor decision-making behavior, and family members and friends often complain of something amiss in the patient’s postinjury personality (6). The patients are described by phrases such as ‘‘emotionally flat,’’ ‘‘decides against his best interest,’’ ‘‘doesn’t learn from his mistakes,’’ ‘‘is impulsive,’’ ‘‘decisions lead to negative consequences,’’ and so on. Although these are useful observations, as yet it has proven difficult to convert them into firm behavioral and theoretical concepts.