Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining Opinions for Use in Bayesian Networks: A Measurement Error Approach

Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasingly popular in a range of fields including engineering, ecology, computational biology, medical diagnosis and forensics. In most of these cases, the BNs are quantified using information from experts or from users' opinions. While this quantification is straightforward for one expert, there is still debate about how to represent opinions from multiple experts in a BN. This paper proposes the use of a measurement error model to achieve this. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the loss of the conditional independence structure of the BN and the provision of only a point estimate for the consensus. The proposed model is applied to a subnetwork (the three final nodes) of a larger BN about wayfinding in airports. It is shown that the approach performs well than do existing methods of combining opinions.
Scope of Biomaterials in Conservative Dentistry and Endodontics

Biomaterials and their applications in medicine and dentistry has been recognized in regular clinical practice. In recent years lot of research is being done on its application in the field of medicine and particularly in restorative dentistry. These materials found to be successful for restoration of teeth in esthetic, function and to maintain the integrity of masticatory muscles. Some of the dental materials, the biocompatibility and application has been discussed and reviewed.
Work Smarter: How an Experimental Learning Management System (LMS) Supports Better Teaching

We developed an experimental learning management system (LMS), called Kat. We use Kat to support student-centered strategies in our course for pre-service teachers. Our strategies include practice teaching. We believe Kat and our strategies increase authenticity, engagement, critical thinking, and retention. We believe Kat illustrates principles that all teachers should reflect on, and potential directions for the design and use of LMSs. Kat increases our efficiency: we work smarter. We're starting formal research on Kat.
The Lambda Library: Lambda Abstraction in C++

The Lambda Library (LL) adds a form of lambda abstraction to C++. The LL is implemented as a template library using standard C++; thus no language extensions or preprocessing is required. The LL consists of a rich set of tools for defining unnamed functions. Particularly, these unnamed functions work seamlessly with the STL algorithms. The LL offers significant improvements, in terms of generality and ease of use, compared to the binders and functors in the C++ standard library.
Intelligent Urban Positioning using Multi-Constellation GNSS with 3D Mapping and NLOS Signal Detection

Reliable metres-level positioning in dense urban areas is difficult to achieve cost-effectively using a single method. The way forward is to combine multiple positioning techniques. This paper introduces the concept of intelligent urban positioning (IUP), which combines ? Multi-constellation GNSS; ? Multiple techniques for detecting non-line-of-sight (NLOS) signal propagation; and ? Multiple techniques using three-dimensional mapping. IUP may also be extended to incorporate other position-fixing and dead-reckoning sensors. The paper begins by explaining the limitations of conventional GNSS positioning in dense urban environments. It then introduces the potential ingredients of intelligent urban positioning, a mixture of new and established techniques, and discusses how they might be combined. 3D mapping may be used for conventional map matching, height aiding, NLOS signal detection, reflection prediction and shadow matching, a new method for determining position by comparing measured and predicted satellite visibility. NLOS reception may also be detected using consistency checking, C/N0 measurement, dual-polarization antenna technology, an antenna array and a sky-pointing camera. The results of a preliminary demonstration of the IUP concept using GPS and GLONASS data collected in London are then presented. In this test, conventional GNSS positioning, aided by consistency-based LOS detection is combined with shadow matching. In the example presented, a horizontal position error of less than 2m was obtained, compared to about 25m for conventional GNSS positioning. This clearly demonstrates the potential of the IUP approach. Note, however, that further research is needed to improve the reliability.
XCentric: A Logic-Programming Language for XML Processing.

In this paper we present the logic-programming language XCentric, discuss design issues, and show its adequacy for XML processing. Distinctive features of XCentric are a powerful unification algorithm for terms with functors of arbitrary arity (which correspond closely to XML documents) and a very rich type language that uses operators such as repetition (*), alternation, etc, as types allowing a compact representation of terms with functors with an arbitrary number of arguments (closely related to standard type languages for XML). This non-standard unification together with an appropriate use of types yields a substantial degree of flexibility in programming.
Evaluation of the Norwegian R&D Tax Credit Scheme

We find that the Norwegian R&D tax credit scheme introduced in 2002 mainly works as intended. The scheme is cost-effective and it is used by a large number of firms. It stimulates these firms to invest more in R&D, and, in particular, the effect is positive for small firms with little R&D experience. The returns on the R&D investments supported by the scheme are positive and generally not different from the returns to other R&D investments. We have found examples of what can be interpreted as tax motivated adjustments to the scheme, but to some extent this must be accepted as a cost to subsidy and support schemes intended for use by a large number of economic agents. This is particularly so when attempts are made to keep administrative expenditures and control routines at a low level.
Nocturnal enuresis: a review

Abstract Enuresis is a common problem affecting a large child population. Though not psychogenic in nature, it is often associated with psychosocial problems. Structural abnormalities as a cause are rare. Common causative factors include developmental delay, genetic factors, abnormalities of sleep-wake cycle and of anti-diuretic hormone secretion. Detailed history, physical examination and simple routine tests are usually sufficient to reach the diagnosis. Both pharmacological as well as non-pharmacological treatments alone or in combination have been used with varying success rates.
Chapter 1 Graph Pair Similarity

Meaning Representations (AMRs) are a way of modeling the semantics of a sentence. This graph-based structure focuses on capturing the concepts involved in a sentence and their relations to each other in order to provide a semantic representation. As such, an AMR graph has node labels corresponding to concepts and directed edge labels corresponding to relations between concepts. Both the set of concept labels and the set of edge labels come from PropBank [4]. The design of AMRs provide single-rooted directed acyclic graphs (DAGs) An example AMR can be seen in Figure 1.1. The edge labels seen in this example are ‘ARG0’ which represents the semantic role of agent and ‘ARG1’ which represents the semantic role of patient. In this example, six words in the source sentence become four nodes in the AMR graph. It is common for the number of nodes to be smaller than the number of words in the source sentence for a variety of reasons including ‘to believe’ being captured by a single concept node and both ‘John’ and ‘him’ referring to the same entity, thus sharing a single concept node. While each AMR graph is produced from a single source sentence, many different source sentences may produce the same AMR graph. This is intentional, since the same meaning (captured by the AMR) can be conveyed in various ways (captured by the source sentence(s)). There are several tasks which are of interest to the community when it comes to working with AMRs. Two of the most central tasks are:
Discriminative Training of Hidden Markov Models

Most modern speech recognition systems are based on hidden Markov models. Yet despite their widespread use many of their properties are not well understood. This work aims to increase our understanding about the training of hidden Markov models for classi cation. We rst examine the question of what is the best measure of hidden Markov model tness. Our research shows us that the principle that motivated many of the previous studies, the incorrect-model sub-optimality of maximum likelihood, is wrong. We further show that the identity of the best hidden Markov model tness measure or objective function depends on two outside factors, the model exibility and the size of the training set. These factors control the point at which training set performance or test set generalisation become the limiting factors. We conjecture that the major e ect controlling test set generalisation is the confusion environment in which the state probability density functions are trained. Based on this idea we introduce a new class of hidden Markov model, the frame discriminative hidden Markov model. We focus on zero memory frame discriminative hidden Markov models, these having the same generalisation ability as maximum likelihood hidden Markov models but better training set performance. We also study the optimisation of the frame discrimination objective function. A comparison of traditional learning techniques with modern machine learning ones shows that the machine learning ones are considerably faster. We also show that it is possible to increase the speed of learning by incorporating extra knowledge about the hessian structure of the tness surface. Taking these ideas together we obtain a general purpose and reasonably fast training algorithm, on-line Manhattan quick-prop. We then apply our zero memory frame discriminative objective function and on-line quickprop to two alphabet recognition tasks. The experimental results provide an empirical veri cation of the training set/test set performance of frame discriminative training. The results also show that compared to maximum likelihood hidden Markov models, we can produce considerable reductions in model size with frame discriminative hidden Markov models while maintaining the same accuracy. Lastly we present some ideas for future work.
Multi-site musculoskeletal pain among industrial workers: occurrence, determinants and consequences for work ability and sickness absence

Purpose Musculoskeletal pain at multiple sites is common among working-age people and greatly increases work disability risk. Little is known of the work-related physical and psychosocial factors contributing to multi-site pain. Methods Survey responses from 734 employees (518 blueand 216 white-collar; 65 % female) of a food processing company were collected twice, in 2005 and 2009. Information on musculoskeletal pain during the preceding week, and on environmental, biomechanical and psychosocial work exposures were obtained through a structured questionnaire. The association of multi-site pain with work exposures was estimated with logistic regression by gender and age group. Results At baseline, 54 % of informants reported pain in more than one area, and 50 % at 4-year follow-up. Forty percent of all employees had multi-site pain both at baseline and at follow-up. Among those with multi-site pain at baseline, 69 % had multi-site pain at follow-up. Both repetitive work and awkward work postures at baseline were associated with multi-site pain at follow-up. Psychosocial factors (low job satisfaction, low team spirit, and little opportunity to exert influence at work) also strongly predicted multi-site pain at follow-up, especially among younger workers and men. Conclusion This prospective study provides new evidence of the high occurrence and persistence of musculoskeletal pain at multiple body sites in an industrial population with a strong association between biomechanical and psychosocial exposures at work and multi-site pain. Prevention of multi-site pain with many-sided modification of work exposures is likely to reduce work disability.
Fuzzy Neural Network Learning Model for Image Recognition

An unsupervised fuzzy neural network classification algorithm has been developed and applied to perform feature abstraction and classify a large number of training instances into a small number of clusters. A fuzzy neural network learning model has been developed by integrating the unsupervised fuzzy neural network classification algorithm with a genetic algorithm and an adaptive conjugate gradient neural network learning algorithm. The learning model has been applied to the domain of image recognition. The performance of the model has been evaluated by applying it to a large-scale training example with 2304 training instances. An average computational speedup of eight is achieved by the new algorithm.
EMODnet physics : towards an European impulsive noise register

EMODnet Physics, one of the European Marine Observation and Data network thematic portals, which is is currently providing access physical parameters of the oceans, has recently started working on water noise with the aim of making available more operational data (in terms of parameters and format that are close to MSFD I.11 requirements), offer a single European entry point to impulsive noise registries (MSFD I.11.1) and work on (regional) sound maps.
NGHIÊN CỨU PHƯƠNG PHÁP HÌNH THỨC DỰA TRÊN LOGIC TRONG PHÂN TÍCH AN NINH MẠNG

Nowadays, with the continuous development of the Internet and the fields of information technology, hardware devices, software applications and Internet services have become very popular making the economy Of countries around the world growing. However, along with the rapid development there is always potential risks, causing the financial loss, reputation. for organizations or individuals to participate in the service. Therefore, the problem of ensuring safety and security of information in the process of transmitting information in the network environment is always a hot issue in research and practical application. Especially with an enterprise network, the problem of ensuring network security and information security is becoming increasingly difficult. Now with the spread of software vulnerabilities, system administrators are facing many challenges and difficulties in securing cybersecurity. This paper will present an approach of logic-based methodology in network security analysis to identify existing vulnerabilities in the system and possible attacks on the system. It helps security professionals and system administrators better manage the configuration of an enterprise network and can control the risks of network security.
Surgical Treatment of Intracranial Aneurysms in Elderly

Introduction: Twenty years ago, elderly patients who had a diagnosis of intracerebral aneurysms were considered to have a poor prognosis and, thus, were excluded of any kind of treatment. With the rapid aging of the population, there was a consistent increase on the prevalence of subarachnoid hemorrhage and, consequently, all of its complications. Delayed neurological deterioration from cerebral arterial vasospasm is a major cause of morbidity and mortality. Thus, specific treatment strategy for intracranial aneurysms in the elderly has been developed.
A comparison of physical activity and dietary behaviours of British Pakistani and White British girls aged 9 to 11 years living on Teesside

Introduction South Asian minority groups in the UK are at greater risk of heart disease and diabetes than the general White population. Physical activity and diet may play an important role in the onset of these diseases. Previous studies suggest levels of physical activity may be particularly low in British Pakistani girls. This mixed-method study aimed to test hypotheses that British Pakistani girls would be less active and more sedentary and would consume a greater proportion of energy from fat than White British girls. It also explored activity and dietary behaviours in the two groups. Methods Eighty-two British Pakistani and 82 White British girls, aged 9 to 11 years, were recruited from seven primary schools on Teesside, North-east England. Accelerometry was used to collect objective measurements of physical activity and sedentary time for four days. Three previous day physical activity recalls were used to determine participation in sport and exercise, outdoor play, screen-time and active modes of school transport. Food records and three previous day multiple-pass diet recalls were used to determine intake of energy and macro-nutrients and to characterise dietary habits. Parental interviews explored familial influences on children’s physical activity and dietary behaviour. Results British Pakistani girls accumulated: 148 (95% CI: 95, 201) fewer counts per minute per day; 19 (95% CI: 11, 26) fewer minutes in moderate-to vigorous physical activity and 5% (95% CI: 3, 7) more sedentary time, compared with White British girls. According to activity recalls British Pakistani girls accumulated: 14 (95% CI: 0.4, 28) fewer minutes per day in sport and exercise; 24 (95% CI: 13, 37) fewer minutes in outdoor play and 4 (95% CI: 0.1, 8.3) fewer minutes in active modes of school transport. There was no significant difference in screen time. British Pakistani girls gained an additional 1.7 (95% CI: 0.4, 3.3) per cent of their overall energy intake from fat, compared with White British girls. According to dietary recalls a greater proportion of British Pakistani girls consumed fast-food as an evening meal (p=0.034) and were more likely to consume food that had been deep fried (p=0.04) or shallow fried (p<0.001) during cooking. Conclusion The lower levels of physical activity and higher amounts of sedentary time, coupled with the higher intake of total fat found in British Pakistani compared with White British girls, may be associated with the increased cardiometabolic risk found in these populations, both in childhood and later in life.
Le territoire comme vecteur d’égalité professionnelle femmes/hommes

Les enjeux du developpement regional lies aux activites de recherche scientifique font l’objet d’une attention croissante de la part des decideurs publics comme des chercheurs. En effet, force est de constater que la diffusion et le transfert de connaissances academiques aux differents acteurs institutionnels et economiques sont encourages par le developpement de synergies entre les membres d’un meme ecosysteme.
Heterotopic ossification in the myasthenia gravis: A case report

ÖZET Heterotopik ossifikasyon, eklem çevresinde yeni kemik oluflumudur. Klinik önemi, potansiyel eklem hareket aral›¤› kayb› olmas›d›r. Genellikle kafa travmas›, medulla spinalis yaralanmas›, yan›k veya direkt kas dokusu travmas› olan hastalarda görülür. Bu çal›flmada kalça eklemlerinin hareket aral›¤›nda k›s›tl›l›k geliflen Myastenia Gravis’li 39 yafl›nda bir hasta sunuldu. Radyografi ve bilgisayarl› tomografide bilateral kalça eklemi etraf›nda yeni kemik oldu¤u gösterildi. Literatürde Myastenia Gravis’de heterotopik ossifikasyon saptanan ilk vakad›r. Muhtemelen kas paralizisinden dolay› uzun süreli total immobilizasyon hastada heterotopik ossifikasyon geliflmesinin nedeni olabilir.
Discovering local cooccurring patterns from aerial images

Developing a spatial searching engine to enhance the search capabilities of large spatial repositories for GIS update has attracted more and more attention. Existing methods are usually designed to extract limited types of objects and use only one aspect of features of images. In this paper, we propose to use the local cooccurring patterns to disclose the cooccurring relationships among each dominant local features and use this local cooccurring patterns to recognize an object from aerial images. For this purpose, we investigate three types of local features: colour-based features, texture-based features, and edgebased shape features. In order to facilitate the feature extraction procedure, we first use discontinuity-preserving smoothing methods to filter the input image. Two popular smoothing techniques are tested and compared. Experimental results are presented in this paper. Index Terms — Local cooccurring patterns, object detection, aerial images.
CANDELS: THE PROGENITORS OF COMPACT QUIESCENT GALAXIES AT z ∼ 2

We combine high-resolution Hubble Space Telescope/WFC3 images with multi-wavelength photometry to track the evolution of structure and activity of massive (M⋆ > 1010 M☉) galaxies at redshifts z = 1.4–3 in two fields of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey. We detect compact, star-forming galaxies (cSFGs) whose number densities, masses, sizes, and star formation rates (SFRs) qualify them as likely progenitors of compact, quiescent, massive galaxies (cQGs) at z = 1.5–3. At z ≳ 2, cSFGs present SFR = 100–200 M☉ yr−1, yet their specific star formation rates (sSFR ∼ 10−9 yr−1) are typically half that of other massive SFGs at the same epoch, and host X-ray luminous active galactic nuclei (AGNs) 30 times (∼30%) more frequently. These properties suggest that cSFGs are formed by gas-rich processes (mergers or disk-instabilities) that induce a compact starburst and feed an AGN, which, in turn, quench the star formation on dynamical timescales (few 108 yr). The cSFGs are continuously being formed at z = 2–3 and fade to cQGs down to z ∼ 1.5. After this epoch, cSFGs are rare, thereby truncating the formation of new cQGs. Meanwhile, down to z = 1, existing cQGs continue to enlarge to match local QGs in size, while less-gas-rich mergers and other secular mechanisms shepherd (larger) SFGs as later arrivals to the red sequence. In summary, we propose two evolutionary tracks of QG formation: an early (z ≳ 2), formation path of rapidly quenched cSFGs fading into cQGs that later enlarge within the quiescent phase, and a late-arrival (z ≲ 2) path in which larger SFGs form extended QGs without passing through a compact state.
4 Attitudes and Cognitive Consistency * The Role of Associative and Propositional Processes

Since the early 1950s, cognitive consistency has been a topic of continuing interest in social psychology. Notwithstanding some fundamental differences between different theories of cognitive consistency (Abelson, Aronson, McGuire, Newcomb, Rosenberg, & Tannenbaum, 1968), most of them share the assumption that cognitive inconsistency causes aversive feelings that, in turn, are assumed to have a powerful influence on judgments, decisions, and behavior. Research on cognitive dissonance (Festinger, 1957), for example, has repeatedly shown that people change their attitudes or their behavior in order to reduce the uncomfortable feeling caused by inconsistent cognitions (for an overview, see Harmon-Jones & Mills, 1999). Until recently, research investigating the impact of cognitive consistency on attitudes primarily employed explicit attitude measures. In these studies, participants were simply asked to report their attitude toward a given object. With the recent development of implicit attitude