Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised Neural Dependency Parsing

Unsupervised dependency parsing aims to learn a dependency grammar from text annotated with only POS tags. Various features and inductive biases are often used to incorporate prior knowledge into learning. One useful type of prior information is that there exist correlations between the parameters of grammar rules involving different POS tags. Previous work employed manually designed features or special prior distributions to encode such information. In this paper, we propose a novel approach to unsupervised dependency parsing that uses a neural model to predict grammar rule probabilities based on distributed representation of POS tags. The distributed representation is automatically learned from data and captures the correlations between POS tags. Our experiments show that our approach outperforms previous approaches utilizing POS correlations and is competitive with recent state-of-the-art approaches on nine different languages. © 2016 Association for Computational Linguistics
DATA MINING AND PROBABILISTIC NETWORK-BASED MECHANISM FOR DATA WAREHOUSING

A good multirmedia database managerment systerm (MDBMS) should be able to store, retrieve, and manage rich semantic data in multimedia database syst,ems. Due to the complexity of real-world applications, the number of databases and the volumes of data in databases have increased tremendously. With the explosive growth in the amount and complexity of data, how to effectively manage the network of databases and utilize the large amount of data becomes important. For this purpose, a probabilistic network-based mechanism for constructing a federation of data warehouses and speeding up information retrieval to facilitate the functionality of an MDBMS is proposed. Our solution procedure consists of three steps. First, we build the probabilistic network by reasoning the probability distributions and mining the generalized affinity-based associations from a set of historical data collected from the network of operational databases. By doing so, the summarized and useful knowledge can be discovered. Second, we derive a siirnilarity measure method to construct a federation of data warehouses so as to reduce the number of inter-warehouse accesses required for queries. Those databases with high similarity values are placed in the same data warehouse. The similarity value is measured via a stochastic process from the mined probability distributions. Third, a second stochastic process generates a list of possible paths with respect to a given query and specifies the particular media objects over the constructed data warehouses so as to speed up multimedia query processing and information retrieval.
A fast method for Transistor Circuit Voltage Range analysis using linear programming

This paper presents a method for fast, automated analysis of device constraints in analog CMOS circuits. A linearized operating point (LOP) model is proposed which allows device constraints like saturation conditions to be formulated as system of linear inequalities (linear program) with circuit node voltages as free variables. The LOP model parameters are obtained from device lookup tables (LUTs) from a single DC simulation. The linear program is solved to obtain valid voltage ranges of supply, input or biasing nodes. Practical examples show that this method provides fast analysis of device constraints with good accuracy over a wide range of CMOS technologies without numerous, time-consuming circuit simulations. Therefore it is well suited for analog design automation applications.
Serum Adiponectin Levels in Advanced-Stage Parkinson's Disease Patients

Patients with advanced Parkinson's disease (PD) experience body weight loss and reductions in the most common cardiovascular risk factors. At present, the pathogenetic mechanisms involved have not been elucidated. Increased serum concentrations of adiponectin, which possesses antiatherogenic and anti-inflammatory properties, are associated with a reduction in cardiovascular risk. The objective of this study was to determine adiponectin serum concentrations in PD patients. Thirty PD patients underwent a full nutritional status assessment, including the determination of adiponectin serum concentrations. Mean ± SD adiponectin concentrations were 9.59 ± 5.9 μg/mL (interquartile range: 5.92–12.9 μg/mL). In PD patients, adiponectin serum levels were similar to those in normal-weight, healthy, young subjects and significantly higher than that in an aged-matched group of morbidly obese subjects. Further studies are warranted to establish the role of adiponectin in the management of PD patients.
Portrayals of Masculinity in “Guy Movies”

Masculinity, an expression of sexual identity, is typically considered the enactment of male identity. The current analysis is a deductive summative content analysis of three popular “guy movies” using the Conformity to Masculine Norms Inventory (CMNI). Results indicated that Emotional Control, Risk-Taking, Violence, and Dominance were the most frequently represented CMNI factors. Winning, Self-Reliance, Playboy, Primacy of Work, Power Over Women, Disdain for Homosexuals, and Pursuit of Status were significantly less frequently displayed. Analysis of the four salient factors indicated that these qualities can be conceptualized as positive and prosocial masculine norms. This suggests that “guy movies” earn that title not because they display gratuitous and stereotypical masculinity but because they allow the viewer to identify with the positive qualities of his own masculinity. The concept of viewer–character dissonance is proposed as a possible explanation.
Data-Based Techniques Focused on Modern Industry: An Overview

This paper provides an overview of the recent developments in data-based techniques focused on modern industrial applications. As one of the hottest research topics for complicated processes, the data-based techniques have been rapidly developed over the past two decades and widely used in numerous industrial sectors nowadays. The core of data-based techniques is to take full advantage of the huge amounts of available process data, aiming to acquire the useful information within. Compared with the well-developed model-based approaches, data-based techniques provide efficient alternative solutions for different industrial issues under various operating conditions. The main objective of this paper is to review and summarize the recent achievements in data-based techniques, especially for complicated industrial applications, thus providing a referee for further study on the related topics both from academic and practical points of view. This paper begins with a brief evolutionary overview of data-based techniques in the last two decades. Then, the methodologies only based on process measurements and the model-data integrated techniques will be further introduced. The recent developments for modern industrial applications are, respectively, presented mainly from perspectives of monitoring and control. The new trends of data-based technique as well as potential application fields are finally discussed.
A Significant Population of Very Luminous Dust-Obscured Galaxies at Redshift z ~ 2

The Spitzer Space Telescope has revealed a significant population of high-redshift (z ∼ 2) dust-obscured galaxies with large mid-infrared to ultraviolet luminosity ratios. Due to their optical faintness, these galaxies have been previously missed in traditional optical studies of the distant universe. We present a simple method for selecting this high-redshift population based solely on the ratio of the observed mid-infrared 24 μm to optical R-band flux density. We apply this method to observations of the ≈8.6 deg2 NOAO Deep Wide-Field Survey Boötes field, and uncover ≈2600 dust-obscured galaxy candidates [i.e., 0.089 arcmin−2) with 24 μm flux densities F24 μ m ⩾ 0.3 mJy and (R − [ 24]) ⩾ 14 (i.e., Fν(24 μ m)/Fν(R) ≳ 1000]. These galaxies have no counterparts in the local universe. They represent 7% ± 0.6% of the 24 μm source population at F24 μ m ⩾ 1 mJy but increase to ≈13% ± 1% of the population at ≈0.3 mJy. These galaxies exhibit evidence of both star formation and AGN activity, with the brighter 24 μm sources being more AGN-dominated. We have measured spectroscopic redshifts for 86 of these galaxies, and find a broad redshift distribution centered at . The space density of this population is ΣDOG(F24μ m ⩾ 0.3 mJy) = (2.82 ± 0.05) × 10−5h370 Mpc −3, similar to that of bright submillimeter-selected galaxies at comparable redshifts. These redshifts imply large luminosities, with median ν Lν(8 μ m) ≈ 4 × 1011 L☉. The infrared luminosity density contributed by this relatively rare dust-obscured galaxy population is log (IRLD) ≈ 8.23+ 0.18−0.30. This is ≈60+ 40−15% of that contributed by z ∼ 2 ultraluminous infrared galaxies (ULIRGs, with LIR > 1012 L☉); our simple selection thus identifies a significant fraction of z ∼ 2 ULIRGs. This IRLD is ≈26% ± 14% of the total contributed by all z ∼ 2 galaxies. We suggest that these dust-obscured galaxies are the progenitors of luminous (~4L*) present-day galaxies, seen undergoing an extremely luminous, short-lived phase of both bulge and black hole growth. They may represent a brief evolutionary phase between submillimeter-selected galaxies and less obscured quasars or galaxies.
Ontology-Based Checking Method of Requirements Specification

SUMMARY This paper introduces an ontology-based method for checking requirements speciﬁcation. Requirements ontology is a knowledge structure that contains functional requirements (FR), attributes of FR and relations among FR. Requirements speciﬁcation is compared with functional nodes in the requirements ontology, then rules are used to ﬁnd errors in requirements. On the basis of the results, requirements team can ask questions to customers and correctly and e ﬃ ciently revise requirements. To support this method, an ontology-based checking tool for veriﬁcation of requirements has been developed. Finally, the requirements checking method is evaluated through an experiment.
Electrophysiological investigations of lexical ambiguity resolution

Electrophysiological techniques were used to assess the generalizability of concreteness effects on word processing across word class (nouns and verbs) and different types of lexical ambiguity (syntactic only and combined syntactic/semantic). The results replicated prior work in showing an enhanced N400 response and a sustained frontal negativity to concrete as compared with abstract nouns. The effect of concreteness on the N400 generalized to all word class and ambiguity conditions, whereas the frontal effect was present for all word types except for the syntactically and semantically ambiguous items when these were used as verbs. The dissociable ERP effects of concreteness revealed by these data suggest that concreteness may impact multiple aspects of neurocognitive processing.
Charity and terror in eighteenth-century Jamaica: The Kingston Hospital and Asylum for Deserted ‘Negroes’

ABSTRACT The Hospital and Asylum for Deserted Negroes in Kingston, Jamaica, was a major site of care for indigent blacks in one of the most densely populated urban centers on one of Britain's most valuable sugar islands. When the hospital opened, sometime after 1788, blacks outnumbered whites ten to one in Jamaica, and the island's whites continued to enact oppressive measures to control the colony's restive black population. This article shows how the Hospital and Asylum for Deserted Negroes became a strategic component in this scheme, joining an expansive network of workhouses and gaols the colonial government used to instill racialized law and order. From its early inception, one of the hospital's unspoken goals was to prevent lawlessness in a space marred by slave resistance. Finally, this article demonstrates how the early development of Jamaica's public health medical infrastructure was, in a large part, nurtured by the slave system.
Characterizing and curating conversation threads: expansion, focus, volume, re-entry

Discussion threads form a central part of the experience on many Web sites, including social networking sites such as Facebook and Google Plus and knowledge creation sites such as Wikipedia. To help users manage the challenge of allocating their attention among the discussions that are relevant to them, there has been a growing need for the algorithmic curation of on-line conversations --- the development of automated methods to select a subset of discussions to present to a user. Here we consider two key sub-problems inherent in conversational curation: length prediction --- predicting the number of comments a discussion thread will receive --- and the novel task of re-entry prediction --- predicting whether a user who has participated in a thread will later contribute another comment to it. The first of these sub-problems arises in estimating how interesting a thread is, in the sense of generating a lot of conversation; the second can help determine whether users should be kept notified of the progress of a thread to which they have already contributed. We develop and evaluate a range of approaches for these tasks, based on an analysis of the network structure and arrival pattern among the participants, as well as a novel dichotomy in the structure of long threads. We find that for both tasks, learning-based approaches using these sources of information.
Input Aggregated Network for Face Video Representation

Recently, deep neural network has shown promising performance in face image recognition. The inputs of most networks are face images, and there is hardly any work reported in literature on network with face videos as input. To sufficiently discover the useful information contained in face videos, we present a novel network architecture called input aggregated network which is able to learn fixed-length representations for variable-length face videos. To accomplish this goal, an aggregation unit is designed to model a face video with various frames as a point on a Riemannian manifold, and the mapping unit aims at mapping the point into high-dimensional space where face videos belonging to the same subject are close-by and others are distant. These two units together with the frame representation unit build an end-to-end learning system which can learn representations of face videos for the specific tasks. Experiments on two public face video datasets demonstrate the effectiveness of the proposed network.
Challenging assumptions about values, interests and power in further and higher education partnerships

This article raises questions that challenge assumptions about values, interests and power in further and higher education partnerships. These topics were explored in a series of semi-structured interviews with a sample of principals and senior higher education partnership managers of colleges spread across a single region in England. The data suggest that common assumptions evident in the literature and professional discourse about the hegemony of higher education institutions in partnerships with further education and sixth form colleges may be misplaced. Questions are also raised about an exclusive focus upon shared values in educational partnerships, and it is suggested that greater clarity about the focus of educational partnerships can explain how successful partnerships can negotiate which values and interests are shared and which are not – an approach that can be a useful modus operandi in the increasingly competitive educational markets in which universities and colleges operate.
The Child’s Experience of ADHD

Objective: This study aimed to investigate the agreement between parent- and child-reported quality of life (QoL) and the self-perceptions of children with ADHD. Method: A cross-sectional survey of school-aged children with ADHD and their parents was undertaken. Results: Parents reported their child’s QoL as lower than the children rated themselves in most QoL domains. Children reporting higher QoL than their parents had higher self-worth, than children who reported lower QoL. There was no difference in ADHD or oppositional symptoms or child age for children reporting higher versus lower QoL than their parents. Children reported experiencing ADHD symptoms and positive aspects in taking stimulant medication. Conclusion: It is important to elicit the report of both parents and children for understanding the functional impairment of children with ADHD. Children who report lower child QoL than their parents have lower overall self-worth; these children may be at risk for developing internalizing difficulties.
Work-environment and occupational stress: an analytical study among loco-pilots (railway drivers) in India

Abstract: Occupational stress is a contributing factor to organizational inefficiency, high staff turnover, absenteeism because of sickness, decreased quality and quantity of service, increased costs of health care, and decreased job satisfaction. Occupational Stress occurs in a wide range of work circumstances but is often made worse when employees feel they have little support from supervisors and colleagues and where they have little control over work or how they can cope with its demands and pressures. Occupational stress can be a real problem to the organization as far as its workers are concerned. The job of a railway driver requires lots of hard work, stamina, alertness of mind, adaptability to follow difficult time schedules. The main and remarkable, highly appreciable role of railway drivers is the only who works with full honesty, in day & night, in heavy cold, hot & rainy weather. The railway driver on whose sincerity the journey of a train depends. The purpose of this research study is to discuss the causal relationship between work environment and occupational stress among loco-pilots (railway drivers) in India. The current study is a pilot study and for the same data was collected through a pre-designed questionnaire filled by the participants from a sample of 60 loco pilots working in Chhapra under Varanasi Division, NER-Gorakhpur. Sample includes both married and unmarried employees over 20 years of age and currently working with an Indian railway as a railway driver for more than five years. The findings from this study suggest that contending with stressful situations is a common occurrence for the railway drivers leading to deterioration in their quality of work and life.
Liquid Democracy: An Analysis in Binary Aggregation and Diffusion

The paper proposes an analysis of liquid democracy (or, delegable proxy voting) from the perspective of binary aggregation and of binary diffusion models. We show how liquid democracy on binary issues can be embedded into the framework of binary aggregation with abstentions, enabling the transfer of known results about the latter---such as impossibility theorems---to the former. This embedding also sheds light on the relation between delegation cycles in liquid democracy and the probability of collective abstentions, as well as the issue of individual rationality in a delegable proxy voting setting. We then show how liquid democracy on binary issues can be modeled and analyzed also as a specific process of dynamics of binary opinions on networks. These processes---called Boolean DeGroot processes---are a special case of the DeGroot stochastic model of opinion diffusion. We establish the convergence conditions of such processes and show they provide some novel insights on how the effects of delegation cycles and individual rationality could be mitigated within liquid democracy. The study is a first attempt to provide theoretical foundations to the delgable proxy features of the liquid democracy voting system. Our analysis suggests recommendations on how the system may be modified to make it more resilient with respect to the handling of delegation cycles and of inconsistent majorities.
Perfectionism, coping, adjustment and achievement in Taiwanese culture

The present study examined the relationship among components of adaptive and maladaptive perfectionism, situation-specific collectivist coping, and both psychological and achievement functioning (i.e. depression, anxiety, self-esteem, and grade point average) among a sample of 225 Taiwanese undergraduate students. A series of path analyses indicated that models of perfectionism, coping, and human functioning that have been empirically supported within European American samples were not supported among this Taiwanese sample. However, congruent with the Taiwanese cultural context, avoidance and detachment coping predicted maladaptive perfectionism which in turn predicted impaired psychological functioning. Moreover, path models indicated that standards predicted acceptance, reframing, and striving, which in turn predicted improved psychological functioning. Finally, cultural and clinical implications of this study’s findings are discussed.
Fast and efficient exact synthesis of single-qubit unitaries generated by clifford and T gates

In this paper, we show the equivalence of the set of unitaries computable by the circuits over the Clifford and T library and the set of unitaries over the ring Z[1/√2, i], in the single-qubit case. We report an efficient synthesis algorithm, with an exact optimality guarantee on the number of Hadamard and T gates used. We conjecture that the equivalence of the sets of unitaries implementable by circuits over the Clifford and T library and unitaries over the ring Z[1/√2, i] holds in the n-qubit case.
Social media for disaster situations: Methods, opportunities and challenges

During disasters people start using social media as a platform to share and disseminate real-time disaster information to wider audiences. In order to understand the type of information that is being shared during disasters and how communities are using the technologies to respond to the disasters, we analyze two-different case studies on natural disasters using Twitter as a platform for gathering and sharing information. In both the case studies, we applied different content analysis methods, both manual and automated, to analyze the valuable information from the user-generated content produced during disaster situations. Based on our findings, we argue that social media platforms are facilitating collective level situation awareness among people and valuable information for disaster management agencies. However, in order to integrate social media in organizational work routines and processes, understanding the opportunities along with challenges is a key.