Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Transfer in an English-French Spoken Language Translator

The paper argues the importance of high-quality translation for spoken language translation systems. It describes an architecture suitable for rapid development of high-quality limited-domain translation systems, which has been implemented within an advanced prototype English to French spoken language translator. The focus of the paper is the hybrid transfer model which combines unification-based rules and a set of trainable statistical preferences; roughly, rules encode domain-independent grammatical information and preferences encode domain-dependent distributional information. The preferences are trained from sets of examples produced by the system, which have been annotated by human judges as correct or incorrect. An experiment is described in which the model was tested on a 2000 utterance sample of previously unseen data.
When Does Social Network-Based Prediction Work? A Large Scale Analysis of Brand and TV audience engagement by Twitter Users

Social network-based prediction, more specifically targeting friends and contacts of existing customers, has proven successful in various domains like retail banking, telecommunications, and online advertising. However, little is known about for what types of product categories and brands social network-based marketing is especially effective at predicting brand engagement, both in absolute terms and compared to demographic targeting or collaborative filtering. In this work, we compare the performance of a social network-based recommendation engine against a product network-based recommendation engine of the kind used in collaborative filtering. We do so over 700 brands and 223,000 consumers a novel data set collected from Twitter. We compare the performance of the two approaches by product and user features. Preliminary results indicate that the variance in performance within and across methods is related to differences in brand and user popularity as well as brand audience. We believe that this is the first study to compare the effectiveness of social network-based marketing with traditional approaches to predict brand engagement over a large number of brands and product types.
Preparation and Conductive Mechanism of the Ink-Jet Printed Nanosilver Films for Flexible Display

Highly conductive films are crucial for the development of flexible electronics which are necessary components of flexible display device. In this work, the ink-jet printed nanosilver films were prepared with a relatively low sheet electrical-resistance of 0.96 Ω/ square after heat-treated at the temperature 200℃ for 30min. The conductive mechanism of the nanosilver films was studied under the observation of the microstructural evolution. It showed that the grown particle size, increased inter-particle contact area and desorption of the PVP layer were the three dominating factors responded to the conductivity of the nanosilver films.
Inhibitory Effects of Surfactant Protein A on Surfactant Phospholipid Hydrolysis by Secreted Phospholipases A21

Hydrolysis of surfactant phospholipids by secreted phospholipases A2 (sPLA2) contributes to surfactant dysfunction in acute respiratory distress syndrome. The present study demonstrates that sPLA2-IIA, sPLA2-V, and sPLA2-X efficiently hydrolyze surfactant phospholipids in vitro. In contrast, sPLA2-IIC, -IID, -IIE, and -IIF have no effect. Since purified surfactant protein A (SP-A) has been shown to inhibit sPLA2-IIA activity, we investigated the in vitro effect of SP-A on the other active sPLA2 and the consequences of sPLA2-IIA inhibition by SP-A on surfactant phospholipid hydrolysis. SP-A inhibits sPLA2-X activity, but fails to interfere with that of sPLA2-V. Moreover, in vitro inhibition of sPLA2-IIA-induces surfactant phospholipid hydrolysis correlates with the concentration of SP-A in surfactant. Intratracheal administration of sPLA2-IIA to mice causes hydrolysis of surfactant phosphatidylglycerol. Interestingly, such hydrolysis is significantly higher for SP-A gene-targeted mice, showing the in vivo inhibitory effect of SP-A on sPLA2-IIA activity. Administration of sPLA2-IIA also induces respiratory distress, which is more pronounced in SP-A gene-targeted mice than in wild-type mice. We conclude that SP-A inhibits sPLA2 activity, which may play a protective role by maintaining surfactant integrity during lung injury.
A REMOTE SENSING IMAGE SEGMENTATION METHOD BASED ON SPECTRAL AND STRUCTURE INFORMATION FUSION Qinling

The focus of this paper is on the segmentation algorithm for the high resolution multispectral imagery to get regions which are roughly corresponding to land cover types. We propose the combination of spectral features and spatial features by Gabor filter banks and a variable mean shift clustering algorithm in high dimension is employed to achieve feature fusion. Some issues on the measure metric of different features and standilzation are discussed. The whole algorithm is evaluated on the synthetic texture image, which are cropped from a QuickBird image with typical land–cover types. Compared with fixed bandwidth Mean Shift segmentation algorithm, our method has better performance in distinguishing the different land cover types with similar spectral surface. ∗ E-mail: corresponding author :wlgbain@gmail.com.
Memory Encryption for General-Purpose Processors

Intel's Software Guard Extensions allows general-purpose computing platforms to run software in a trustworthy manner and securely handle encrypted data. To satisfy the technology's security goals, the external system memory must be cryptographically protected. A new hardware unit added to the processor's memory controller - the Memory Encryption Engine (MEE) - was recently developed to protect the confidentiality, integrity, and freshness of this external memory traffic, against eavesdropping and tampering. The MEE is a successful feat of real-world cryptographic engineering: it's the first time such cryptographic memory protection has been added to a widely deployed general-purpose processor. This article explains the MEE threat model and security objectives, describe some of the difficulties encountered in building the MEE, and report concrete performance results.
An improved dynamic programming algorithm for coalition structure generation

Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of partitioning the set of agents into exhaustive and disjoint coalitions such that the social welfare is maximized. This coalition structure generation problem is extremely challenging due to the exponential number of partitions that need to be examined. Specifically, given n agents, there are O(nn) possible partitions. To date, the only algorithm that can find an optimal solution in O(3n) is the Dynamic Programming (DP) algorithm, due to Rothkopf et al. However, one of the main limitations of DP is that it requires a significant amount of memory. In this paper, we devise an Improved Dynamic Programming algorithm (IDP) that is proved to perform fewer operations than DP (e.g. 38.7% of the operations given 25 agents), and is shown to use only 33.3% of the memory in the best case, and 66.6% in the worst.
Realization of the Low Cost and High Performance MySQL Cloud Database

MySQL is a low cost, high performance, good reliability and open source database product, widely used in many Internet companies. For example, there are thousands of MySQL servers being used in Taobao. Although NoSQL developed very quickly in past two years, and new products emerged in endlessly, but in the actual business application of NoSQL, the requirements to developers are relatively high. Moreover, MySQL has many more mature middleware, maintenance tools and a benign ecological circle, so from this perspective, MySQL dominates in the whole situation, while NoSQL is as a supplement. We (the core system database team of Taobao) have done a lot of work in the filed of MySQL hosting platform, designed and implemented a UMP (Unified MySQL Platform) system, to provide a low cost and high performance MySQL cloud database service.
Chinese Named Entity Recognition with Inducted Context Patterns

Since whether or not a word is a name is determined mostly by the context of the word, the context pattern induction plays an important role in name entity recognition (NER). We present a NER method based on the context pattern induction. It induces high-precision context patterns in an unsupervised way starting with some entity seeds. Then it uses directly the matched context patterns, instead of extracted entities by inducted patterns, as the features of a CRF-based NER model. The experiments show that the proposed method improves the performance of the high quality named entity recognizer, and achieves higher accuracy and recall rate.
Examination of the Effects of Media Consumption on Mood and Body Dissatisfaction Using Ecological Momentary Assessment

The current study aimed to assess the effects of media consumption on body dissatisfaction and negative affect using Ecological Momentary Assessment, a method of assessment over time and in the participants’ naturalistic environment. Thirty undergraduate female participants were assessed randomly five times per day for five days via text messages sent to their phones. During each assessment, participants reported the number of minutes spent watching TV, reading a magazine, and using the internet, as well as their current levels of negative affect and body dissatisfaction. Results demonstrated that the total time spent consuming media was a significant predictor of guilty feelings. Further results demonstrated that internet use specifically is a significant predictor of guilty feelings. The results indicated that overall media consumption did not significantly predict body dissatisfaction. These findings are particularly interesting given the focus in recent years on developing media literacy interventions for negative body image and eating pathology. Further examinations comparing the effects of overall media consumption versus body-focused media consumption may identify which specific content area are causing the negative effects demonstrated in previous research. Future work should also further investigate the relationship between guilt and online media consumption to determine what role, if any, guilt may have in the development or exacerbation of body dissatisfaction over time.
Collective Spatial Perceptions of Men and Women Commuters: Linking Space, Jobs and Activity

Abstract This paper attempts to explore an overlooked aspect of gender-based commuting by integrating women’s and men’s perceptions of labor markets (LMs) as a primary predictor of the commuting behavior of employees according to gender. Perceptions of labor markets (LMPs) are an innovative, exploratory term defining employees’ preferences of “where to work” by using spatial symbols and has been found to vary across the genders. The data of a representative national sample of 723 Israeli employees indicated that women prefer to work in spaces they perceive as local, more proximate LMs while men favor positions in spaces perceived as more promising in terms of economic or professional advancement, or in segmented LMs, and that the LMPs of both men and women affect their commuting behaviors. The main contribution of this study has been in highlighting the influence on their commuting patterns of men’s and women’s dissimilar LMPs, which thus constitute a major factor underlying the disproportionate distribution of the genders in the labor force.
Blood corpuscles classification schemes for automated diagnosis of hepatitis Luminiţa STATE

The paper proposes three methods for automated diagnosis of hepatitis based on shape recognition and classification of blood corpuscles. The processed data are binary images of blood samples taken from positive diagnostic and negative diagnostic patients. The idea followed in the paper is to identify T-lymphocyte response (Danne corpuscles) using approximations of shape coefficients as perimeter, area and circularity. The automatic diagnosis is accomplished through an analysis process on the class of the most circular corpuscles identified in the image. A series of experimentally derived conclusions are supplied in the final part of the paper. 2000 Mathematics Subject Classification: Medical applications (general) ( 92C50), Pattern Recognition (68T10), Image processing (68U10).
Contour representations of sound

We consider how the continuity of form in natural sounds may be used to discover sparse time-frequency representations. To proceed, we describe a method to represent any sound as a collection of contours in the time-frequency plane. By analysing the signal in many time-scales, an over-complete set of shapes is generated for a given sound. From this redundant set of shapes the simplest, most parsimonious mathematical forms may be selected.
Dance Confidence, Age and Gender 1 Dance Confidence, Age and Gender

Dance Confidence, Age and Gender 2 ABSTRACT Dance Confidence is a measure of domain-specific self-esteem as applied to how a person feels about their social and recreational dance ability. This study is concerned with how dance confidence varies as a function of gender and age group. 13,715 people watched a video and then completed an on-line survey. The results show that dance confidence varies as a function of gender and age group, such that, in general, females have higher levels of dance confidence than males, and dance confidence changes at significant points in the developmental cycle. For females dance confidence levels start high in early adolescence, they drop significantly post 16 and then rise steadily through late-teens and early twenties before leveling off during mid-life. There is a significant drop in dance confidence for women when they reach their mid-late fifties. For men, dance confidence levels start low and then rise steadily during late teens and early twenties, before leveling off during mid-thirties. There is a significant increase in dance confidence for men when they reach their mid-sixties. The results, and the link between social dance and self-esteem, are discussed within the context of two theoretical models of self-esteem, the " Reflected Appraisal Model " and the " Competencies Model " .
Aspects of an internal logic for persistence

The foundational character of certain algebraic structures as Boolean al- gebras and Heyting algebras is rooted in their potential to model classical and con- structive logic, respectively. In this paper we discuss the contributions of algebraic logic to the study of persistence based on a new operation on the ordered structure of the input diagram of vector spaces and linear maps given by a ltration. Within the context of persistence theory, we give an analysis of the underlying algebra, derive universal properties and discuss new applications. We highlight the denition of the implication operation within this construction, as well as interpret its meaning within persistent homology, multidimensional persistence and zig-zag persistence.
Adrift in the Beaufort Gyre: A model intercomparison

Output from six regional sea ice‐ocean climate model simulations of the arctic seas is compared to investigate the models' ability to accurately reproduce the observed late winter mean sea surface salinity. The results indicate general agreement within the Nordic seas, strong differences on the arctic continental shelves, and the presence of a climate drift that leads to a high salinity bias in most models within the Beaufort Gyre. The latter is highly sensitive to the wind forcing and to the simulation of freshwater sources on the shelves and elsewhere.
Kriging-Assisted Multi-Objective Design of Permanent Magnet Motor for Position Sensorless Control

This paper presents a novel multi-objective evolutionary algorithm (MOEA) based on surrogate models. Kriging surrogate models are created and updated with the solutions from the MOEA for reducing the number of evaluations of the computationally expensive finite-element analysis models. The proposed method is applied to solve a multi-objective design problem of a surface-mounted permanent magnet motor in order to improve its sensorless control capability without comprising other performances, such as output torque and torque ripple. The Kriging-assisted MOEA is proved to have the potential of providing good solutions with a limited computation time budget.
Eco-Geographical Diversification of Bitter Taste Receptor Genes (TAS2Rs) among Subspecies of Chimpanzees (Pan troglodytes)

Chimpanzees (Pan troglodytes) have region-specific difference in dietary repertoires from East to West across tropical Africa. Such differences may result from different genetic backgrounds in addition to cultural variations. We analyzed the sequences of all bitter taste receptor genes (cTAS2Rs) in a total of 59 chimpanzees, including 4 putative subspecies. We identified genetic variations including single-nucleotide variations (SNVs), insertions and deletions (indels), gene-conversion variations, and copy-number variations (CNVs) in cTAS2Rs. Approximately two-thirds of all cTAS2R haplotypes in the amino acid sequence were unique to each subspecies. We analyzed the evolutionary backgrounds of natural selection behind such diversification. Our previous study concluded that diversification of cTAS2Rs in western chimpanzees (P. t. verus) may have resulted from balancing selection. In contrast, the present study found that purifying selection dominates as the evolutionary form of diversification of the so-called human cluster of cTAS2Rs in eastern chimpanzees (P. t. schweinfurthii) and that the other cTAS2Rs were under no obvious selection as a whole. Such marked diversification of cTAS2Rs with different evolutionary backgrounds among subspecies of chimpanzees probably reflects their subspecies-specific dietary repertoires.
Effect of dead-time in interleaved PWM for two parallel-connected inverters

Parallel-connected inverters are used for high power application. Due to the parallel-connection, there exists a circulating current which does not contribute to the ac side current. The analysis presented in the paper shows that the circulating current is affected by the dead-time. The effect of the dead time on the circulating current for the space vector pulse width modulation (PWM) and a discontinuous PWM is analyzed. The dead-time causes a dc value of the circulating current for the discontinuous PWM. A dead-time compensation technique is used for eliminating the dc component of the circulating current. Experimental results are presented to verify that.
The performance of current methods in ligand-protein docking

Computer-based methods for predicting the structure of ligand –protein complexes or docking algorithms have application in both drug design and the elucidation of biochemical pathways. The number of solved structures of ligand –protein complexes now permits the testing and validation of docking algo rithms, by comparison of predicted complexes with structures extracted from protein databases. This paper outlines the methodologies and compares their performance in predicting the structure of ligand – protein complexes. COMPUTER-aided methods for the identificat ion and characterization of ligand –protein interactions have undergone considerable advances in the past decade. Ligand docking and screening algorithms are now frequently used in the drug-design process, and have additional application in the elucidation of fundamental biochemical processes. There are several well-established docking algorithms which have been previously reviewed 1,2 , as well as many more recently introduced methods. The purpose of docking algorithms is now expanding beyond the original goal of fitting a given ligand into a specific protein structure. Newer applications include data base screening, lead generation and de novo drug design. Each of these applications can be used for the identi fication of novel protein inhi bitors. Lead generation and database screening search a large database of known che micals for compounds having a moderate to strong affinity for the target protein. The identified set of com pounds can be used for the construction of novel inhibi tors with high affinity and specificity for the target protein. De novo drug design is a computer-based method of designing potent inhibitors 3–6 , where possible inhibitors are assembled piecewise within a given binding pocket, from a set of chem ical fragments within a mole cular fragment library. While the methodology underlying single ligand–protein docking and database screening is quite similar, the criterion by which they are judged differs. A database search algorithm is required to be able to screen many thousands of possible ligands in a rea sonable time period, typically no more than several days. This entails an upper limit on each docking of no more than a few minutes. However, if a specific ligand –protein interaction is to be rigorousl y modelled, accuracy is the primary concern, with the algorithm execution time a secondary factor. Protein–protein docking methodology has considerable overlap with that of ligand –protein docking; however, differences between the two docking tasks have resulted in most algorithms being intended for either one purpose or the other. The methods discussed in detail here are generally intended for ligand–protein docking. The issues faced in designing docking algorithms have been revi ewed 2,7–9
Tailoring the AI for Robotics: Fine-tuning Predefined Deep Convolutional Neural Network Model for a Narrower Class of Objects

Object recognition has been one of the greatest challenges for robotic tasks particularly in indoor environments. In order to perform this task, so called hand-crafted features requiring high computational effort which rely on expert knowledge are used until achieving better results by learned features using convolutional neural networks. In this study, we have given a powerful object classification model with 2.72% top-1 error rate which is achieved by fine-tuning a predefined model for 10 classes. We built our model on top of VGG16 architecture (trained on a larger dataset which consists of 1000 classes) and froze the layers except the last classification layer which we trained for 10 classes. The training data consists of 10000 images (1000 per class) and there are 4000 images for validation (400 per class). The object classes in our dataset are book, bottle, bowl, cup, eyeglass, keyboard, laptop, monitor, teapot and vase which may exist on the desktop in an indoor environment.