Miracle-dz/UniFAR-FTUs huggingface dataset:
Sublethal Effects of Wild-Type and a vIF-2α-Knockout Frog virus 3 on Post-Metamorphic Wood Frogs (Rana sylvatica)

Ranaviruses have been associated with rising numbers of mass die-offs in amphibian populations globally. With life-stages occupying different environments and presenting distinct physiologies, amphibian of different ages are likely to play an important role in pathogen persistence. To assess the potential role of post-metamorphic amphibians as a Ranavirus reservoir, we performed a bath-exposure study on wood frogs using environmentally relevant doses (~103 and ~104 PFU/mL) of wild-type (WT) and knockout Frog virus 3 (FV3), deficient for the vIF-2α immune-evasion gene, the effects of which have never been addressed in post-metamorphic anurans. We observed 42% infection prevalence and low mortality (10%) across the virus challenges, with half of the mortalities attributable to ranavirosis. Prevalence and viral loads followed a dose-dependent pattern. Notably, when exposed to the vIF-2α knockout (DvIF-2α) FV3, individuals exhibited significantly decreased growth and increased lethargy in comparison to WT FV3 treatments. Although 85% of individuals in the virus treatments exhibited stereotypic signs of ranavirosis throughout the experiment, at termination (40 days post exposure) most individuals were clear of signs of infection. Overall, this study provides evidence that even a single short time exposure to environmentally relevant doses of Ranavirus may cause sublethal infections in post-metamorphic amphibians, thus indicating their possible role as a reservoir for this pathogen.
An Analysis of the Behaviour of Commercial Real Estate Indices Paper Presented to the Faculty and Institute of Actuaries ' Investment Conference , June 2002

There has been criticism within the real estate professions that the lack of availability of good quality data has led actuarial professionals and academics to ignore real estate for modelling purposes. It has sometimes been asserted that this is one of the reasons for the decline in institutional investment in real estate, as asset allocation experts have ignored the asset class because of the difficulty in modelling it. In general, there is little discussion in the actuarial literature on the subject of real estate indices. The only published stochastic real estate investment model for actuarial use is that by Wilkie (1995) – this was an update of that produced by Daykin and Hey (1990), itself based on advice from Wilkie. In this paper, we discuss the availability of data for real estate stochastic modelling. There have been many developments in the collection, presentation and analysis of real estate data that have not found their way into the actuarial literature. We then review the Wilkie real estate model and use the research work done by real estate finance academics to inform a critique and development of that model. In developing the models different data sets are used, including data from valuation-based and unsmoothed indices in order to find appropriate parameter estimates. The significance (or otherwise) of the parameter estimates is tested for each of the fitted models and the differences between the fitted models examined.
Client Engagement with Homework: A Study of Cognitive Therapy for Depression

ii Acknowledgments . iii Vita. iv List of Tables . vi List of Figures . vii Chapter 1: Introduction.1 Homework Compliance as a Predictor of Treatment Outcome.4 Homework Compliance as a Predictor of Treatment Outcome in CT for Depression . 12 Expert Clinical Opinion on Factors that Predict Homework Compliance.17 Empirical Investigations of Predictors of Homework Compliance . 22 Empirical Investigations of Predictors of Homework Compliance in CT for Depression . 26 Empirical Investigations of Therapist Behaviors as a Predictor of Symptom Change in CT for Depression . 27 The Current Study.30 Chapter 2: Methods.32 vii Participants.32 Therapists.33 Measures . 34 Procedures.37 Chapter 3: Results . 40 Refinement of the HSTB Subscales.40 Refinement of the CT-Specific HE Scale . 41 Descriptive Statistics for Therapist Behaviors and Homework.42 Overall Analytic Strategy . 44 Hypothesis 1: Homework-Related Therapist Behaviors Will Predict Session-toSession Observer-Rated Homework Engagement . 46 Hypothesis 2: Homework-Related Therapist Behaviors Will Predict Session-toSession Client-Rated Homework Engagement . 48 Hypothesis 3: Observer-Rated Homework Engagement Will be Related to Concurrent Session-to-Session Depressive Symptom Change . 48 Hypothesis 4: Client-Rated Homework Engagement Will Be Related to Concurrent Session-to-Session Depressive Symptom Change . 49 Hypothesis 5: Homework-Related Therapist Behaviors Will Predict Session-toSession Depressive Symptom Change . 50 Exploratory Analyses: Relationships among Observer, Client, and Therapist Ratings of Homework Engagement . 50
Forecasting the unemployment rate when the forecast loss function is asymmetric

This paper studies forecasts when the forecast loss function is asymmetric, using Australian unemployment rates as an example. We focus on simple univariate models including autoregressive models and self-exciting threshold autoregressive models and we employ the same asymmetric quadratic loss function that is used for forecast evaluation at the model selection, model estimation and forecast combination stages. In particular, to incorporate the asymmetric loss function into model selection, we suggest the use of crossvalidation associated with the estimation methods that also incorporate the same loss function. Our forecasting results show considerable improvement when the same loss function is used for both estimation, combination and evaluation. However we do not observe gains from using the asymmetric loss function to select forecasting models compared with the conventional model selection methods based on squared-error loss. Forecast combination results show that using combination methods that account for asymmetric loss can attenuate the disadvantages of ignoring asymmetric loss when producing individual forecasts.
Assessing the inclusivity of three mainstream secondary schools in England: challenges and dilemmas

ABSTRACT The notion of inclusion has gained momentum worldwide, with most countries around the world embracing inclusive policies in their educational systems. However, there is still an ongoing debate as to what is inclusion and hence, the consequent challenge of coming up with an agreed definition, which could then be used to plan for and subsequently, evaluate, inclusion. This study adds to our understanding of inclusion by contrasting objective (i.e. School Census Statistics) and subjective (i.e. self-report questionnaire) measures of inclusivity in three mainstream secondary schools in England and by comparing the perceptions of school inclusivity of different groups of educational practitioners and pupils. The results of this study indicate that inclusion is a ‘slippery’ construct as the perception of inclusion of educational practitioners was found to be affected by their role at school while pupil perception on this matter depended upon their SEND category. However, despite these subjective differences in the way inclusion is perceived, there was also substantial agreement across the different categories of participants with regard to the relative ranking of inclusivity across the three schools suggesting that coming up with overarching themes on what is inclusion is achievable. The article ends with explaining the benefits of reaching an agreed definition at a national level.
Phylogeny of early Australopithecus: new fossil evidence from the Woranso-Mille (central Afar, Ethiopia)

The earliest evidence of Australopithecus goes back to ca 4.2 Ma with the first recorded appearance of Australopithecus ‘anamensis’ at Kanapoi, Kenya. Australopithecus afarensis is well documented between 3.6 and 3.0 Ma mainly from deposits at Laetoli (Tanzania) and Hadar (Ethiopia). The phylogenetic relationship of these two ‘species’ is hypothesized as ancestor–descendant. However, the lack of fossil evidence from the time between 3.6 and 3.9 Ma has been one of its weakest points. Recent fieldwork in the Woranso-Mille study area in the Afar region of Ethiopia has yielded fossil hominids dated between 3.6 and 3.8 Ma. These new fossils play a significant role in testing the proposed relationship between Au. anamensis and Au. afarensis. The Woranso-Mille hominids (3.6–3.8 Ma) show a mosaic of primitive, predominantly Au. anamensis-like, and some derived (Au. afarensis-like) dentognathic features. Furthermore, they show that, as currently known, there are no discrete and functionally significant anatomical differences between Au. anamensis and Au. afarensis. Based on the currently available evidence, it appears that there is no compelling evidence to falsify the hypothesis of ‘chronospecies pair’ or ancestor–descendant relationship between Au. anamensis and Au. afarensis. Most importantly, however, the temporally and morphologically intermediate Woranso-Mille hominids indicate that the species names Au. afarensis and Au. anamensis do not refer to two real species, but rather to earlier and later representatives of a single phyletically evolving lineage. However, if retaining these two names is necessary for communication purposes, the Woranso-Mille hominids are best referred to as Au. anamensis based on new dentognathic evidence.
Clustering for high dimensional categorical data based on text similarity

It is a well-known fact that a variety of cluster analysis techniques exist to group objects which have characteristics related to one another. But the fact of the matter is the implementation of many of these techniques poses a great challenge because of the fact that much of the data contained in today's database is categorical in nature. Despite the fact that there have been recent advances in algorithms for clustering categorical data, some are unable to handle uncertainty in the clustering process while others have stability issues. In this paper, it is intended to propose an effective method for text similarity based clustering technique. At first the relevant features are selected from the input dataset. Thus the relevant features are clustered based on the A Possibilistic Fuzzy C-Means Clustering Algorithm (PFCM). Here the features used for clustering will be the similarity between the categorical data. The similarity measure is presented namely SMTP (similarity measure for text processing) for the two categorical data. Clustering based proposed method has high probability of producing a useful subset and independent features. To improve the efficiency of the proposed method, construct the minimum spanning tree by an optimization algorithm. Here adaptive artificial bee colony algorithm (AABC) is used for the purpose of selecting the optimal features. The performance of the proposed technique is evaluated by clustering accuracy, Jaccard coefficient and Dice's coefficient. The proposed method will be implemented in MATLAB platform using machine learning repository.
The Effects of Computer-Supported Collaborative Learning on Sense of Connectedness, Sense of Learning, and Overall Sense of Community among High School Students Enrolled in a Marketing Course

3 Copyright Page.4 Dedication . 5 Acknowledgments.6 List of Tables . 11 List of Figures . 12 List of Abbreviations . 13 CHAPTER ONE: INTRODUCTION . 14 Overview . 14 Background . 14 Problem Statement . 17 Purpose Statement . 18 Significance of the Study . 19 Research Questions . 21 Hypotheses . 21 Definitions.22 CHAPTER TWO: LITERATURE REVIEW . 24 Overview . 24 Theoretical Framework . 24 Social Development Theory . 24 Connectivism . 27 Communities of Practice . 28
On international business intelligence Out-Of-Vocabulary processing based on sentence-aligned web corpus

International business intelligence processing is an important problem of cross-disciplinary research in artificial intelligence. The recognition of Out-Of-Vocabulary (OOV in short) in international commercial activities and its derivate OOV phrase brings challenge to widely used machine translation technology. Electronic dictionary with a fixed lexicon cannot catch up with the fast increase of international commercial OOV phrase. In this paper, we present a recognition and translation technology for OOV phrases in international business intelligence based on sentence-aligned web corpus. We first obtain the latest and most related textual resource from the Internet and build up a sentence-aligned corpus. Then calculate the relevancy of adjacent word string by Markov model to get a maximum likelihood of segmentation, and determine the OOV and OOV phrase in such business context. Then wipe off the redundancy and calculate the probabilities and weight of co-occurrence word pairs. Thus we have the OOV word pair and the translation of OOV phrase in business intelligence. Experiments show a good result in international business domain and timely update.
Normalized minimum-redundancy and maximum-relevancy based feature selection for speaker verification systems

In this paper, an information theoretical approach to select features for speaker recognition systems is proposed. Conventional approaches having a fixed interval of analysis frames are not appropriate to represent dynamically varying characteristics of speech signals. To maximize the speaker-related information varied by the characteristics of speech signals, we propose an information theory based feature selection method where features are selected to have minimum-redundancy with in selected features but maximumrelevancy to training speaker models. Experimental results verify that the proposed method reduces the error rates of speaker verification systems by 27.37 % in NIST 2002 database.
Improvised Levelset method for segmentation and grading of brain tumors in dynamic contrast susceptibility and apparent diffusion coefficient magnetic resonance images

A novel Neuro – level set algorithm is proposed and evaluated for simultaneous segmentation and grading of brain tumors. The algorithm utilizes vascular and cellular information provided by the reconstructed images of dynamic contrast susceptibility magnetic resonance images and apparent diffusion coefficient images. The reconstructed images are relative cerebral blood volume (rCBV) image, time to peak (TTP) image and percentage of base at peak (PBP) image along with apparent diffusion coefficient (ADC) maps. The proposed neural levelset algorithm utilizes a neural block to provide the speed image for the levelset methods. In this study, two different architectures of levelset method have been implemented and their results are compared. The results show that the proposed NeuroLevelset method performs better in differentiating the tumor, edema, necrosis in reconstructed images of dynamic contrast susceptibility magnetic resonance images and apparent diffusion coefficient MR images.
Model-Based Digit Analysis for Fraud Detection Overcomes Limitations of Benford Analysis

Benford Analysis is a statistical method used for detecting financial fraud. It compares the distribution of digits in data with the Benford Distribution. But there are often disadvantages ranging from uncomfortable rates of false positives up to total inapplicability of the method. We identified the inaccurate fit of typical data to the Benford Distribution as reason for these deficits. So we propose to use adaptive distributions of digits instead. For that we introduce a procedure which derives the distribution of digits from a ``model'' for the distribution of data. The term ``model'' means an abstract distribution which reflects basic properties of the data. This paper identifies different models and analyzes their relevance and performance. We show that model-based Digit Analysis provides a more reliable and more generally applicable tool for fraud detection to auditors.
The " Resource Curse " and Regional U.s. Development the " Resource Curse " and Regional U.s. Development the " Resource Curse " and Regional U.s. Development

The “Resource Curse” is a stylized fact that has been observed consistently in a number of development studies: countries that are relatively well-endowed with natural resources tend to grow more slowly than resource-poor economies. This paper documents evidence that the Resource Curse extends to the individual states of the U.S. Using a variety of specifications, regression of state GSP growth on resource abundance consistently shows a negative and significant relationship. There is strong evidence that resource-based economies are more volatile economies, and volatile economies may be less desirable to investors. SHSU ECONOMICS WORKING PAPER The “Resource Curse” and Regional U.S. Development
METHODS OF SEARCHING FOR TRAPPING SETS OF QUASI-CYCLIC LDPC CODES AND THEIR APPLICATIONS IN CODE CONSTRUCTION Graduate Student : Dung Viet Nguyen Advisors :

We present a methodology to search for harmful subgraphs in the Tanner graph of a regular column-weightthree low-density parity-check (LDPC) code. These harmful subgraphs, which are more commonly known under the name “trapping sets,” cause a degradation in the error correcting performance of LDPC codes in the high signal-to-noise ratio (SNR) region. Our method of searching for trapping sets utilizes the Trapping Set Ontology, a database in which trapping sets are arranged according to their topological relationships. Based on the topological relationships, larger trapping sets are searched for by expanding smaller ones. This reduces the complexity and the run-times of the search algorithms and allows large trapping sets to be searched for efficiently. Besides, if the LDPC code is quasi-cyclic then our search algorithms can be futher simplified. Our method of searching for trapping sets is useful in the performance analysis of LDPC codes and in the construction of good LDPC codes. In this paper, we demonstrate the use of the method in the construction of good LDPC codes.
Curriculum change in modern foreign languages education in England: barriers and possibilities

ABSTRACT This paper considers the languages on offer in secondary schools in England and the possibility of enacting curriculum change with a view to reducing the dominance of French, Spanish and, to a lesser extent, German as a possible way to increase take-up of modern foreign languages post-14. Questionnaires were completed by 666 students aged 14–15, 70 head teachers and 119 heads of modern languages in secondary schools throughout England, investigating students’ views as to the languages they would like to learn and their views of particular languages as well as the views of senior and middle leaders on the factors which impact on the teaching of modern languages. The paper concludes that students are interested in a wider range of languages than is currently available, for reasons primarily relating to usefulness. It also finds that schools are constrained by operational concerns preventing them fully considering the possibility of teaching a wider range of languages. Implications for national-level language policy and the culture of school accountability are discussed.
Translation without eIF2 Promoted by Poliovirus 2A Protease

Poliovirus RNA utilizes eIF2 for the initiation of translation in cell free systems. Remarkably, we now describe that poliovirus translation takes place at late times of infection when eIF2 is inactivated by phosphorylation. By contrast, translation directed by poliovirus RNA is blocked when eIF2 is inactivated at earlier times. Thus, poliovirus RNA translation exhibits a dual mechanism for the initiation of protein synthesis as regards to the requirement for eIF2. Analysis of individual poliovirus non-structural proteins indicates that the presence of 2Apro alone is sufficient to provide eIF2 independence for IRES-driven translation. This effect is not observed with a 2Apro variant unable to cleave eIF4G. The level of 2Apro synthesized in culture cells is crucial for obtaining eIF2 independence. Expression of the N-or C-terminus fragments of eIF4G did not stimulate IRES-driven translation, nor provide eIF2 independence, consistent with the idea that the presence of 2Apro at high concentrations is necessary. The finding that 2Apro provides eIF2-independent translation opens a new and unsuspected area of research in the field of picornavirus protein synthesis.
A Class of Region-preserving Space Transformations for Indexing High-dimensional Data

This study introduces a class of region preserving space transformation (RPST) schemes for accessing high-dimensional data. The access methods in this class differ with respect to their space-partitioning strategies. The study develops two new static partitioning schemes that can split each dimension of the space within linear space complexity. They also support an effective mechanism for handling skewed data in heavily sparse spaces. The techniques are experimentally compared to the Pyramid Technique, which is another example of static partitioning designed for high-dimensional data. On real high-dimensional data, the proposed RPST schemes outperform the Pyramid Technique by a significant margin.
Environment-mediated mobile computing

Environment-Mediated Communication (EMC) is introduced as new concept for computer-mediated human-to-human communication in mobile settings. EMC is based on highly mobile computing devices such as handhelds, palmtops and wearables, and on emerging technologies facilitating interaction of mobile devices with their physical surroundings. for instance smart environments and context-awareness. In EMC, communication between humans is mediated by an instance of the physical environment, at least conceptually if not physically. This short paper presents an analysis of the EMC design space, and reflects on potential applications.
Local Multi-Modal SIFT Features in Co-registered Range and Intensity Images

SIFT features have known limitations for matching features under changes in 3D pose of the object. We investigate the use of multimodal information from the range and intensity domains as an approach to mitigating the effects of changes in view point. In this investigation we outline an experimental procedure applied to range and intensity images of real-world objects captured using a stereo camera pair and calibrated turntable setup offering reliable ground truth for the 3D motion of surface locations. From our investigation we propose a novel surface descriptor, EC-SIFT, which shows a significant improvement on state of the art performance in the experiments we present.