Miracle-dz/UniFAR-FTUs huggingface dataset:
Uniication-based Glossing

We present an approach to syntax-based machine translation that combines uniication-style interpretation with statistical processing. This approach enables us to translate any Japanese newspaper article into English, with quality far better than a word-for-word translation. Novel ideas include the use of feature structures to encode word lattices and the use of uniication to compose and manipulate lattices. Uniication also allows us to specify abstract features that delay target-language synthesis until enough source-language information is assembled. Our statistical component enables us to search eeciently among competing translations and locate those with high English uency. 1 Background JAPANGLOSS Knight et al., 1994; 1995] is a project whose goals are to scale up knowledge-based machine translation (KBMT) techniques to handle Japanese-English newspaper MT, to achieve higher quality output than is currently available, and to develop techniques for rapidly constructing MT systems. We built the rst version of JAPANGLOSS in nine months and recently participated in an ARPA evaluation of MT quality White and O'Connell, 1994]. JAPANGLOSS is an eeort within the larger PANGLOSS NMSU/CRL et al., 1995] MT project. Our approach is to use a KBMT framework, but to fall back on statistical methods when knowledge gaps arise (as they inevitably will). We syntactically analyze Japanese text, map it to a semantic representation, then generate English. Figure 1 shows a sample translation. Parsing is bottom-up, driven by an augmented context-free grammar whose format is roughly like that of Shieber, 1986]. Our grammar rules look like this: OUTPUT: The new company plans to establish in February. The semantic representation contains conceptual tokens drawn from the 70,000-term SENSUS ontology Knight and Luk, 1994]. Semantic analysis proceeds as a bottom-up walk of the parse tree, in the style of Mon-tague and Moore Dowty et al., 1981; Moore, 1989]. Semantics is compositional, with each parse tree node assigned a meaning based on the meanings of its children. Leaf node meanings are retrieved from a semantic lexicon , while meaning composition rules handle internal nodes. Semantic rules and lexical entries are sensitive to syntactic structure,
Investigating the Construct of Health Literacy Assessment: A Cross-Validation Approach

ii ACKNOWLEDGMENTS . iv DEDICATION . v LIST OF TABLES . ix LIST OF ILLUSTRATIONS . x LIST OF ABBREVIATIONS . xi CHAPTER I INTRODUCTION . 1 Statement of the Problem . 8 Purpose of the Study . 10 Research Questions . 10 Definition of Terms. 10 Delimitations . 11 Assumptions . 12 Significance of the Study . 12 Conclusion . 13 CHAPTER II – THEORECTICAL FOUNDATIONS AND LITERATURE REVIEW . 14 Introduction . 14 Theoretical Foundations. 15 Social Cognitive Theory and Self-efficacy . 15 vii The Health Belief Model . 16 The Promotion Model . 17 Reasoned Action . 19 Literature Review. 19 Summary and Conclusions . 36 CHAPTER III METHODOLOGY . 37 Instruments . 37 The Newest Vital Sign . 38 Health Literacy Skills Instrument . 39 Demographic Questionnaire . 39 Data Collection Procedure . 39 Data Analysis . 40 CHAPTER IV– ANALYSIS OF DATA . 41 Research Study. 41 Sample. 42 CHAPTER V– DISCUSSION . 49 Appendix A– Informed Consent . 59 Appendix B– IRB Approval Letter . 61 Appendix C– Short Test for Functional Literacy . 62 Appendix D– Newest Vital Sign. 67 viii Appendix E– Demographic Questionnaire . 68 Appendix F– Health Literacy Skills Instrument . 70 Lactose intolerance: Why does milk bother me? 77 Risk of heart attack calculator . 80 http://www.healthwise. net/rti/Content/StdDocument.aspx? DOCHWID=te795 0 . 80 Obstructive sleep apnea – what happens? 86 Appendix G– Tables . 93 HLSI Descriptive Statistics . 93 REFERENCES . 113
Global Convergence Rates of B-SplineM-Estimators in Nonparametric

To compensate for lack of robustness in using regression splines via the least squares principle, a robust data smoothing procedure is proposed for obtaining a robust regression spline estimator of an unknown regression function, g 0 , of a one-dimensional measurement variable. This robust regression spline estimator is computed by using the usual M-type iteration procedures proposed for linear models. A simulation study is carried out and numerical examples are given to illustrate the utility of the proposed method. Assume that g 0 is smoothed up to order r > 1=2 and denote the derivative of g 0 of order l by g (l) 0. Let b g (l) n denote an M-type regression spline estimator of g (l) 0 based on a training sample of size n. Under appropriate regularity conditions, it is shown that the proposed estimator, b g (l) n , achieves the optimal rate, n ? (r? l)=(2r+1) (0 l < r), of convergence of estimators for nonparametric regression when the spline knots are deterministically given.
On selecting feature-value pairs on smart phones for activity inferences

Prior works have been elaborated on activity inferences from context information sensed on smart phones. Most of sensing computations are performed on CPU of smart phones. Thus, Sensor Hub is designed to avoid CPU involvement. However, Sensor Hub has several limitations, such as limited memory space and computation power. Since activity inference is a classification problem, prior works have already proposed some classifiers on smart phones. However, if one would like to build a classifier model in Sensor Hub, one challenging issue is to reduce the model size. One approach to reduce the model size of classifiers is feature selection. Feature selection reduces the model size by removing features in the feature set. Nonetheless, because sensor space is limited, removing features could reduce accuracy of classifier algorithm significantly. Therefore we explore feature-value selection concept, which considers the value rather than the feature to reduce the model size while preserving accuracy of classifiers. In this paper, we propose three feature-value selection methods, which consider confusion and redundancy among the feature-value. Due to the nature of feature-values, discretization of sensor data is important. We design a discretization method, LGD (Length Gini Discretization) and compare it with another method, MDLP (Minimum Description Length Discretization), to discretize sensor data using confusion metric to choose the cut point. Extensive experiments are conducted to evaluate our proposed feature-value selection methods. Feature-value removal allows us to reduce up to 80% of the model size and maintain average accuracy performance to 86%.
RELEVANCE FEEDBACK FOR CONTENT BASED IMAGE RETRIEVAL BASED ON MULTITEXTON HISTOGRAM AND MICROSTRUCTURE DESCRIPTOR

Image retrieval is an important topic in the field of pattern recognition and artificial intelligence. There are three categories of image retrieval methods: text-based, content-based and semantic-based. In CBIR, images are indexed by their visual content, such as color, texture, shapes. A new image feature detector and descriptor, namely the micro-structure descriptor [1] (MSD) is discussed to describe image features via micro-structures. The micro-structure is defined based on the edge orientation similarity, and the MSD is built based on the underlying colors in micro-structures with similar edge orientation. Content-based image retrieval (CBIR) is the mainstay of image retrieval systems. To be more profitable relevance feedback techniques are incorporated into CBIR such that more precise results can be obtained by taking user‟s feedbacks into account. The semantic gap between low-level features and high-level concepts handled by the user is one of the main problems in image retrieval. On the other hand, the relevance feedback has been used on many CBIR systems such as an effective solution to reduce the semantic gap. The gap is reduced by using the Multitexton Histogram descriptor [2]. In this paper, a novel framework method called Relevance Feedback is used to achieve high efficiency and effectiveness of CBIR in coping with the large-scale image data. For that reason this paper proposes a method of relevance feedback based on Multitexton Histogram descriptor to represents the effective feature representations, and the Microstructure descriptor (MSD) for efficient feature extraction of an image. By using this method, high quality of image retrieval on Relevance Feedback can be achieved in a small number of feedbacks. In terms of efficiency, iteration of feedback is reduced substantially by using the navigation patterns discovered from the user query log, which reduce the computational processing time.
Application of FEC based Multiple Description Coding to Internet Video Streaming and Multicast

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An effort based social diffusion approach for mobile encounter networks

Mobile information systems use publish-subscribe mechanisms to distribute content between users. Unfortunately, content that is close to the user is not necessarily accessible unless users have specified so earlier. Mobile encounter networks (MENs) represent an alternative, which spread content in a spatial diffusion process. A drawback of MENs is their high resource usage. Some researchers have proposed diffusion methods that utilize knowledge about the social network behind the user community. Such approaches work well in the wired Internet since robust bandwidths exist. This, however, cannot be assumed for MENs where the bandwidth is determined by the encounter duration. We use an effort based knowledge diffusion approach to solve this problem. Effort based diffusion mechanisms differentiate between simple and complex content types and adapt content exchanges to the capabilities of involved peers. We emulate content diffusion between humans with an urban simulator. During the simulation we obtain data about content exchanges and cached contents. Results show that the least effort theory outperforms traditional approaches. Being aware of content transfer efforts, such routing approaches increase the overall transparency of large scale urban communities and to the same time enable richer content exchanges within friend networks.
The relationship between CDC light‐trap and human‐bait catches of endophagic sandflies (Diptera: Psychodidae) in the Peruvian Andes

Abstract. A study was carried out in the Peruvian Andes to test the suitability of CDC light traps for monitoring changes in the human‐landing rate of endophagic phlebotomine sandflies, following house‐spraying with pyrethroid insecticide. On four pairs of consecutive nights, sandflies were caught inside eight sprayed and eight unsprayed houses, either by human bait or by CDC light traps. The sandflies collected were Lutzomyia verrucarum (97%) and Lu. peruensis (3%), both probable vectors of Leishmania peruviana, and the species composition was unaffected by house‐spraying. A non‐linear relationship was detected between light‐trap and human‐bait catches, but the relationship did not diverge significantly from linearity within the range of sandfly abundance found in most houses in the endemic area (i.e. between 3 and 200 sandflies/house‐night), and did not differ significantly between sprayed and unsprayed houses. However, light trap catches had a significantly lower proportion of blood‐fed females in sprayed than in unsprayed houses, probably due to an insecticidal effect on post‐blood‐feeding behaviour. The proportion of Lu. verrucarum was significantly higher in light trap than in human bait catches, indicating that Lu. peruensis is either more anthropophilic or less phototropic than Lu. verrucarum.
Constructing employability as higher education practice – a reflective and reflexive account via an examination of my role as Director of the Centre for Excellence for Employability at Sheffield Hallam University, 2005-10

The theme of my context statement (CS) is ‘constructing employability as higher education (HE) practice’. The notion of ‘constructing’ is seen as pivotal. In 2005 employability was an emerging agenda in UK HE, one which many universities were deepening their engagement with. It was, however, a contested one, where scholarship and critique was expanding. For many who were sympathetic to the idea that universities should pay more attention to the notion of employability, a question often posed and encountered was: ‘what is it and how do you do it? ’ This was the challenge for the Centre for Excellence for Employability (e3i) at Sheffield Hallam University between 2005-10, and for me in my role of Director of the Centre. In reflecting upon my experiences, and in reviewing my selected public works (PWs), I have found that my actions resulted in the construction of employability as a range of ideas, values, and a set of practices within the context of a specific academic and organisational culture. Employability, via my PWs, is formulated as social and cultural practice within a specific organisational and sectoral context. My roles of academic, educational developer, and Centre Director are explored reflectively and reflexively to re-construct my identity and agency as one of Academic Development Leader. My understanding is that educational developers and academic leaders in universities operate within the complex spaces and discourses constituted by the values and practices of academics as members of disciplinary subject communities, the processes of institutional strategic management, managerial decision-making and formal governance regimes. My reflection upon my PWs has created both a perspective on how to create and embed employability as a learning experience/learning outcome within a HE context, and also a re-appraisal of my identity and agency as an Academic Development Leader, with associated implications for my ongoing practice.
Who have I been talking to?

One of the most frequently used ways to communicate with others is email. We have created "Who Have I Been Talking To? ", a visualization of the users' email that can provide insights about their relationships with others how one relation has evolved over time (reflected by the number of messages exchanged); the nature of the relationship (comparing the subjects of messages and how asymmetric is the ratio between sent and received email); and allowing users to compare their relationships with different people. We found that a variant of a stacked bar chart over an interactive timeline allowed all of those goals to be achieved. User studies showed that the users were able to understand the visualization and gain meaningful insights about their electronic communications with others.
Xanthones from roots of Calophyllum thwaitesii and their bioactivity

Extracts from three Calophyllum species endemic to Sri Lanka were tested for antifungal and antioxidant activities. Of them, only the root methanol extract of Calophyllum thwaitesii showed activity, and the active extract on activity guided fractionation yielded four antifungal active and three inactive xanthones. Antifungal active xanthones were identified as 1,6-dihydroxy-5-methoxyxanthone, 1-hydroxy-5,6-dimethoxyxanthone, 1-hydroxy-5-methoxyxanthone and 1-methoxy-5-hydroxyxanthone, using spectroscopic methods and comparison with literature data. Inactive compounds were identified as 1-hydroxy-7-methoxyxanthone, 1,5-dihydroxy-6-methoxyxanthone and 1,7-dihydroxy xanthone. This is the first report of above xanthones except the latter from C. thwaitesii. Further, five of the above xanthones along with thwaitesixanthone and calothwaitesixanthone, which have been previously reported from the root bark of the same species, showed free radical scavenging properties when tested with DPPH. Further, this is the first report of methylated xanthones from C. thwaitesii. Previous work on stem bark, root bark and the stem of the same species yielded only nonmethylated xanthones, indicating the absence of methylating enzymes in the plant. However, this new finding suggests the presence of methylating enzymes in the root stem of C. thwaitesii.
Premalignant alterations in the lipid composition and fluidity of colonic brush border membranes of rats administered 1,2 dimethylhydrazine.

Dimethylhydrazine (DMH) is a potent procarcinogen with selectivity for the colon. To determine whether alterations in the lipid composition and fluidity of rat colonic brush border membranes existed before the development of DMH-induced colon cancer, rats were injected s.c. with this agent (20 mg/kg body weight per wk) or diluent for 5, 10, and 15 wk. Animals were killed at these time periods and brush border membranes were prepared from proximal and distal colonocytes of each group. The "static" and "dynamic" components of fluidity of each membrane were then assessed, by steady-state fluorescence polarization techniques using limiting hindered fluorescence anisotropy and order parameter values of the fluorophore 1,6 diphenyl-1,3,5-hexatriene (DPH) and fluorescence anisotropy values of DL-2-(9-anthroyl) stearic acid and DL-12-(9-anthroyl) stearic acid, respectively. Membrane lipids were extracted and analyzed by thin-layer chromatography and gas-liquid chromatography. Phospholipid methylation activity in these membranes was also measured using S-adenosyl-L-methionine as the methyl donor. The results of these studies demonstrate that: the lipid composition and both components of fluidity of proximal DMH-treated and control membranes and their liposomes were similar at all time periods examined; at 5, 10, and 15 wk the "dynamic component of fluidity" of distal DMH-treated membranes and their liposomes was found to be higher, similar, and lower, respectively, than their control counterparts; the "static component of fluidity" of distal DMH-treated membranes and their liposomes, however, was similar to control preparations at all three time periods; and alterations in the lipid composition and phospholipid methylation activities appeared to be responsible for these differences in the "dynamic component of fluidity" at these various time periods.
A procedure for calculation of monitor units for passively scattered proton radiotherapy beams.

The purpose of this study is to validate a monitor unit (MU) calculation procedure for passively scattered proton therapy beams. The output dose per MU (d/MU) of a therapeutic radiation beam is traditionally calibrated under specific reference conditions. These conditions include beam energy, field size, suitable depth in water or water equivalent phantom in a low dose gradient region with known relative depth dose, and source to point of calibration distance. Treatment field settings usually differ from these reference conditions leading to a different d/MU that needs to be determined for delivering the prescribed dose. For passively scattered proton beams, the proton specific parameters, which need to be defined, are related to the energy, lateral scatterers, range modulating wheel, spread out Bragg peak (SOBP) width, thickness of any range shifter, the depth dose value relative to the normalization point in the SOBP, and scatter both from the range compensator and inhomogeneity in the patient. Following the custom for photons or electrons, a set of proton dosimetry factors, representing the changes in the d/MU relative to a reference condition, can be defined as the relative output factor (ROF), SOBP factor (SOBPF), range shifter factor (RSF), SOBP off-center factor (SOBPOCF), off-center ratio (OCR), inverse square factor (ISF), field size factor (FSF), and compensator and patient scatter factor (CPSF). The ROF, SOBPF, and RSF are the major contributors to the d/MU and were measured using an ion chamber in water tank during the clinical commissioning of each beam to create a dosimetry beam data table to be used for calculating the monitor units. The following simple formula is found to provide an independent method to determine the d/MU at the point of interest (POI) in the patient, namely, (d/MU) = ROF SOBPF. RSF SOBPOCF.OCR. FSF.ISF. CPSF. The monitor units for delivering the intended dose (D) to the POI can be obtained from MU = D / (d/MU). The accuracy and robustness of the above formula were validated by calculating the d/MU in water for many different combinations of beam parameters and comparing it with the corresponding measured d/MU by an ion chamber in a water or water/plastic phantom. This procedure has been in use for MU calculation for patient treatment fields at our facility since May 2006. The differences in the calculated and measured values of the d/MU for 623 distinct fields used for patient treatment during the period of May 2006 to February 2007 are within 2% for 99% of these fields. The authors conclude that an intuitive formula similar to the one used for monitor unit calculation of therapeutic photon beams can be used to compute the monitor units of passively scattered proton therapy beams.
Ego-clustering based propagation prediction of time series in social networks

Online social networks are now recognized as an important platform for propagating information. Recently, a lot of efforts are made to predict the popularity of social information, to help the government and companies effectively control and guide public opinions. Information propagation in social networks exist many different temporal patterns, which are useful reference for predicting the future spreading of news. Considering temporal patterns are related to the network structure and information content, some researchers formulated a time series clustering problem to obtain tem­poral patterns in social networks. Previous clustering based algorithms take each cluster center as a typical propagation pattern, and then classify prediction object into its nearest-neighbor cluster. However, the nearest pattern can not fit the prediction object very precisely. This paper proposes a novel E-CTPM (Ego-Clustering based Temporal Prediction Model). E-CTPM utilizes the prediction object itself as a fixed cluster center, which can attract the most similar time series into one cluster and generate an ego-pattern for the prediction object. The tailored pattern fits the prediction object well, so it is suitable to indicate the future propagation. Experiments are carried on twitter and phrase datasets, with the results that E-CTPM outperforms the existing algorithms by achieving lower prediction bias and prediction variance. Meanwhile, E-CTPM has general applicability, which is able to work with multiple clustering methods and avoids the prediction difference resulting from classification methods.