Miracle-dz/UniFAR-FTUs huggingface dataset:
Texture-modified foods and thickened fluids as used for individuals with dysphagia: Australian standardised labels and definitions

Thickened fluids and texture-modified foods are provided for the therapeutic treatment of dysphagia. Review of the literature indicated that numerous labels are applied to a small number of food textures and fluid thickness levels. The consequences of inconsistent terminology affect patient safety and the efficiency of communication. A joint project of the Dietitians Association of Australia and The Speech Pathology Association of Australia Limited (Speech Pathology Australia) was undertaken to develop consensus standards for number of levels, labels and definitions of thickened fluids and texture-modified foods within the Australian context. A project officer and multidisciplinary advisory committee were appointed by competitive process to carry out and oversee the project. The project determined that there were 39 different labels in use for thickened fluids and 95 different labels in use for texture-modified foods used in Australia. Dietitians and speech pathologists demonstrated overwhelming support for a standardised labelling and terminology system (99.2% of respondents). A national consultative process encompassing the views of more than 580 clinicians helped to formulate the final standards. A scale for modified fluids and a scale for texture-modified foods were developed and consensus was achieved between the Dietitians Association of Australia and Speech Pathology Australia. The standards are now recommended for use throughout Australia.
Unrolling and Simplifying Expressions with Template Haskell

We introdu e a handful of modules for manipulating Template Haskell datastru tures, building up to modules that allow simpli ation and re ursion unrolling of Haskell ode. To illustrate their use, and to demonstrate the performan e improvements that motivate this work, we also dis uss an example appli ation Fraskell [5℄, showing how we an get more than an order of magnitude performan e in rease with minimal hanges to the sour e.
Female Sexual Dysfunction Among Malaysian Women in A Primary Care Setting: Does The Frequency of Sexual Activity Matter?

The aim of the study was to compare sexual functioning among Malaysian women in a primary care setting between those with a low and high frequency sexual intercourse.Across-sectional study on 230 married Malaysian women in a primary-care setting was conducted at the Bandar Tun Razak Clinic, Cheras. A validated Malay version of Female Sexual Function Index questionnaire (MVFSFI) was used to assess the sexual functioning profiles among women with low and high sexual activity. The percentage of women who had sexual intercourse 3-4 times a week, 1-2 times a week and < 1-2 times a month were 13.4%, 44.3 % and 42.4 % respectively. Women with a low frequency of sexual intercourse (Low SI) tended to suffer from more sexual dysfunction, (χ²=28.98, p < 0.001) compared to those with a high frequency of sexual intercourse (High SI) group. Women who were less sexually active (having low frequency intercourse, ie. ≤ 1 – 2 times per week) were found to be less sexually aroused (χ²= 25.9, p< 0.001), less orgasmic (χ²=19.8, p< 0.001), less lubricated during sexual activity (χ²=11.1, p< 0.001), complain of sexual pain (χ²=4.3, p = 0.033) and feels less satisfied sexually (χ²=12.6, p< 0.001). The problem of female sexual dysfunction (FSD) in the Malaysian primary care population with low sexual activity needs to be addressed
Defining the Pulmonary Disease and Disability from Lung Dysfunction in Cutis Laxa

Cutis laxa is a heterogeneous group of disorders characterized by loose, lax, and inelastic skin. Other complications include lung, cardiovascular, musculoskeletal, gastrointestinal, and genitourinary disease. Cutis laxa (CL) can be congenital or acquired, with the congenital forms resulting from mutations in numerous genes. Chronic obstructive pulmonary disease (COPD) is a major contributor to morbidity and mortality in CL, making it a subject of public health importance. This purpose of this analysis is to determine quantitative differences between CL onset, congenital and acquired, and CL diagnosis, CL versus CL carrier in regard to pulmonary function and disability that results from lung dysfunction. An odds ratio determined that the cutis population has an increased risk for COPD and t-test analysis determined that COPD severity was the same between congenital and acquired subjects, but significantly different between CL and CL carriers. Multiple people with a previous asthma diagnosis were determined to actually have COPD. Additionally, the SGRQ total score was found to be highly correlated with FEV1/FVC and CT visual emphysema score. Further studies are warranted to more clearly determine genotype-phenotype correlations and assess longitudinal changes.
The end of theory: The data deluge makes the scientific method obsolete

Illustration: Marian Bantjes The Petabyte Age: Sensors everywhere. Infinite storage. Clouds of processors. Our ability to capture, warehouse, and understand massive amounts of data is changing science, medicine, business, and technology. As our collection of facts and figures grows, so will the opportunity to find answers to fundamental questions. Because in the era of big data, more isn't just more. More is different. The End of Theory: Essay: The Data Deluge Makes the Scientific Method Obsolete
Enhancing educator development through an online simulation

This paper presents an approach to educator development through games and simulations. The goal of our project was to help pre-service teachers more effectively bridge the gap, between the theory and practice of teaching. Some criteria for success used were the facilitation a professional dialogue, evidence of an emerging understanding of content delivery and the articulation of workplace culture in the teaching profession. We discuss the theory underpinning of the design, the research approaches used and summarise the findings of our research. In particular, we explain how cognitive load theory was applied to the design of many features of this virtual learning environment. We also briefly summarise six years of research that has consistently found that the virtual learning environment of ClassSim provides an effective way of introducing pre-service teachers to their future work in classrooms.
Efficient image transmission using transform-based compression techniques

We present a system for still image transmission over noisy satellite channels. The system couples image compression together with error control codes to improve the received image quality while maintaining its bandwidth requirements. In this paper we extend our previous work on Discrete Cosine Transform (DCT) based image compression in noisy channels. We evaluate the performance of Discrete Wavelet Transform (DWT) based image compression and compare it to its equivalent DCT-based. We show how DWT-based image compression outperforms DCT-based both in noise-free and noisy channels. We also show how using a class of Forward Error Correction called Parallel Concatenated Gallager Codes (PCGC) can significantly improve the quality of the transmitted image in noisy channels. Despite the bandwidth expansion caused by introducing PCGC, the protected image occupies a smaller bandwidth now by compressing the image before applying PCGC. Evaluation results show improvement in the over-all system including bandwidth requirements compared to similar systems with different coding schemes.
Use and analysis of student response systems in two summer courses

The clickers are used in the courses in order to increase the interaction between the teacher and the students with the aim to better adapt the teaching to the level of the students in alignment with e.g. the Zone of Proximal Development (Vygotsky, 1978) and learning theories building on conceptual change (Entwistle, 2007; Posner, Strike, Hewson, & Gertzog, 1982) and threshold concepts (Meyer & Land, 2006; Zander et al., 2008). The idea is also to enhance the communication between the students as a way to increase their activation level, something that is seen as promoting learning.
Social media and health: implications for primary health care providers

This report is the second deliverable of the 'Digital Inclusion and Social Knowledge Media for Health: Frameworks and Roadmaps' project. The first discussed the concept of social and digital exclusion whilst this report focuses on the emerging phenomenon of social media. The report outlines current knowledge on the users and usages of social media for health and goes on to discuss social media in the context of a continuing focus (ref. D1.1) on the areas of mental health, smoking cessation and teenage lifestyles. The report concludes with an outline of an approach to a 'social media strategy' and with suggestions for directions for future research.
Travel Time Prediction with Non-Linear Time Series

This paper focuses on a specific application of Advanced Traveler Information Systems (ATIS), which is the posting of travel time predictions on Changeable Message Signs (CMS). The objective is to influence travelers' route choice. One of the statistical techniques that has strong potential for on-line implementation is the non-linear time series with multifractal analysis. In this paper, a new approach for predicting travel times is developed and tested with travel time data for five incident free days with the goal of predicting recurrent congestion. The prediction errors were found to have the greatest magnitude at the temporal boundaries of congestion Refining the prediction algorithm through the smoothing of the input data and setting a threshold on the minimum speed predictions improved results by abating the influence of the temporal boundaries of congestion. Thus, the new approach produced reasonable errors for short-term (5-minute) travel time predictions.
Dynamic decision models for managing the major complications of diabetes

Diabetes is the sixth-leading cause of death and a major cause of cardiovascular and renal diseases in the U.S. In this dissertation, we consider the major complications of diabetes and develop dynamic decision models for two important timing problems: Transplantation in prearranged paired kidney exchanges (PKEs) and statin initiation. Transplantation is the most viable renal replacement therapy for end-stage renal disease (ESRD) patients, but there is a severe disparity between the demand and supply of kidneys for transplantation. PKE, a cross-exchange of kidneys between incompatible patient-donor pairs, overcomes many difficulties in matching patients with incompatible donors. In a typical PKE, transplantation surgeries take place simultaneously so that no donor may renege after her intended recipient receives the kidney. We consider two autonomous patients with probabilistically evolving health statuses in a PKE, and model their transplant timing decisions as a discrete-time non-zero-sum stochastic game. We explore necessary and sufficient conditions for patients' decisions to form a stationary-perfect equilibrium, and formulate a mixed-integer linear programming (MIP) representation of equilibrium constraints to characterize a socially optimal stationary-perfect equilibrium. We calibrate our model using large scale clinical data. We quantify the social welfare loss due to patient autonomy and demonstrate that the objective of maximizing the number of transplants may be undesirable. Patients with Type 2 diabetes have higher risk of heart attack and stroke, and if not treated these risks are confounded by lipid abnormalities. Statins can be used to treat such abnormalities, but their use may lead to adverse outcomes. We consider the question of when to initiate statin therapy for patients with Type 2 diabetes. We formulate a Markov decision process (MDP) to maximize the patient's quality-adjusted life years (QALYs) prior to the first heart attack or stroke. We derive sufficient conditions for the optimality of control-limit policies with respect to patient's lipid-ratio (LR) levels and age and parameterize our model using clinical data. We compute the optimal treatment policies and illustrate the importance of individualized treatment factors by comparing their performance to those of the guidelines in use in the U.S.
Book Review: Handbook of Natural Language Processing (second edition) edited by Nitin Indurkhya and Fred J. Damerau

The Handbook of Natural Language Processing is a revised edition of an earlier handbook (Dale, Moisl, and Somers 2000). This second edition was prepared by Nitin Indurkhya, a researcher at the University of New South Wales, and the late text processing pioneer Fred J. Damerau of the IBM T. J. Watson Research Center (d. 27 January 2009), whose 1964 paper introduced a version of what is now known as the Damerau-Levenshtein distance, a metric of the similarity between two strings and a dynamic programming algorithm to compute it efficiently (Damerau 1964). Damerau also invented automatic hyphenation (Damerau 1970) and worked on early question-answering systems. Indurkhya, who is also affiliatedwith a consulting company, Data-Miner Pty Ltd., maintains a companion wiki for the book.1 The book has three parts, totaling 26 chapters. The first part, Classical Approaches, essentially covers techniques that were known prior to the statistical revolution, that is, before natural language processing people in the mainstream embraced techniques that speech engineers were already using successfully for awhile. The second part, Empirical and Statistical Approaches, covers state-of-the-art data-driven models.2 Part three, Applications, shows some techniques closer to applications. If you are talking to a computational linguist, information extraction is seen as an application, but if you are talking to business people, they will see it as a general technology area, from which many application products and services can be built. The handbook “aims to cater to the needs of NLP practitioners and language-engineering professionals in academia as well as in industry. The prototypical reader is interested in the practical aspects of building NLP systems and may also be interested in working with languages other than English” (p. xxii). Hence it would have been nice to introduce some descriptions of actual products that generate revenue (even if this meant that this particular part of the handbook would become outdated more quickly) in order to demonstrate how the NLP parts are embedded in non-NLP technology, and how these products are embedded in the businesses that use them. For example, the application chapter “Information Retrieval” does not describe how the topics in other parts were applied in Web search engines or enterprise search products, as one might have expected. Rather, it basically is another technical chapter—and its probabilistic IR material could just as well have been presented in part two (statistical techniques).
Administração de medicamentos por via parenteral: uma revisão

Introdução: A administração de medicamentos é uma das atividades mais sérias e de maior responsabilidade da Enfermagem. Para sua execução, exige-se competência, conhecimentos, habilidades e aplicação de princípios científicos no que diz respeito ao preparo, às vias de administração e aos eventos adversos. Objetivo: Esse artigo teve como objetivo realizar uma revisão bibliográfica sobre a administração de medicamentos por via parenteral direta, no que diz respeito ao local de aplicação, material utilizado e à técnica descrita na literatura. Metodologia: A metodologia utilizada foi a busca e leitura exploratória, seletiva, analítica e interpretativa de artigos publicados em periódicos científicos considerando as vias de administração intradérmica, subcutânea, intramuscular e intravenosa; local de aplicação, material utilizado e técnica. Através desse estudo, é possível ressaltar a importância da difusão de conhecimentos por meio da educação continuada dos profissionais responsáveis pela administração de medicamentos.
Escaping Plato's Cave using Adversarial Training: 3D Shape From Unstructured 2D Image Collections

We introduce PlatonicGAN to discover the 3D structure of an object class from an unstructured collection of 2D images, i.e. neither any relation between the images is available nor additional information about the images is known. The key idea is to train a deep neural network to generate 3D shapes which rendered to images are indistinguishable from ground truth images (for a discriminator) under various camera models (i.e. rendering layers) and camera poses. Discriminating 2D images instead of 3D shapes allows tapping into unstructured 2D photo collections instead of relying on curated (e.g., aligned, annotated, etc.) 3D data sets. To establish constraints between 2D image observation and their 3D interpretation, we suggest a family of rendering layers that are effectively differentiable. This family includes visual hull, absorption-only (akin to x-ray), and emission-absorption. We can successfully reconstruct 3D shapes from unstructured 2D images and extensively evaluate PlatonicGAN on a range of synthetic and real data sets achieving consistent improvements over baseline methods. We can also show that our method with additional 3D supervision further improves result quality and even surpasses the performance of 3D supervised methods.
Integrated software platform for parallel global optimization

The paper is concerned with global optimization techniques and their parallel implementation. We describe an integrated software platform GOOL–PV (Global Optimization Object-oriented Library–Parallel Version) that provides the tools for solving complex optimization problems on parallel and multi-core computers or computer clusters. Finally, we present the comparative study of sequential and parallel global optimization algorithms based on numerical results for a standard set of multimodal functions.
Automating algorithm design within a general architecture for intelligence

Turning the dream of "automatic programming" into reality will involve, among other things, getting computers to design algorithms. For human algorithm designers, two abilities seem critical for success: (1) the ability to make design decisions based on diverse types of knowledge, and (2) the ability to improve performance by learning from experience. This thesis reports on three systems--all based on the Soar problem-solving and learning architecture--that advance the state of the art in automatic algorithm design along these two dimensions. Two non-Soar automatic algorithm designers were first partially reimplemented in Soar to produce Designer-Meets-Soar and Cypress-Soar. Features from these two systems were then combined in the current system, Designer-Soar, which designs several simple generate-and-test and divide-and-conquer algorithms. The thesis draws on the experiences in constructing these systems in developing a theory of the algorithm design process, summarized in the following propositions: (1) Design takes place in multiple problem spaces. A subset of these spaces embodies the target model of computation, and another set embodies the application domain model. (2) The task of design is to use knowledge of the application domain to build a procedure for computing the desired output in the computational spaces. (3) The computational spaces have functional operators corresponding to steps in an algorithm, at whatever level of abstraction is necessary for the design. (4) Means-end analysis on the results of execution drives the design, with the resulting series of execution passes in a design session exhibiting the pattern of progressive deepening. (5) Any part of the knowledge necessary for accomplishing the design task may be acquired by learning. The algorithm itself is represented as learned knowledge for navigating through the computational spaces. The purpose of the theory is to present a set of mechanisms that are sufficient to enable an intelligent agent (not necessarily a human) to design algorithms, assuming that it must cope with the diversity of the task environment and its own bounded rationality. Such assumptions hold not only in real algorithm design situations, but in any complex intellectual task, providing support for the claim that a general architecture such as Soar is an appropriate vehicle for this type of research.
Preliminary Implementation of Text-to-scene System

Text-to-scene is a new technology used in many fields. It provides approaches to convert natural language into virtual scene. People can also use this technology to show text information using the visual method without professional knowledge. This paper attempted to provide a route of text-to-scene implementation. The researches related to text-to-scene were reviewed in brief and then a preliminary implementation of text-to-scene was proposed. The implementation contains lexical, syntactic, semantic library. Furthermore, the composition, function and work mechanism of each sub-modules constituting the text-to-scene implementation were discussed by integrating text processing and graphic processing respectively. In this article, the researches provided a route for applications of text-to-scene.
Electromagnetic Imaging System for Weapon Detection and Classification

The detection of concealed weapons is one of the biggest challenges facing the security community. It has been shown that each weapon can have a unique fingerprint, which is an electromagnetic signal determined by its size, shape, and physical composition. Extracting the signature of each weapon is one of the major tasks of any detection system. This paper addresses the issue of identifying conductive objects based on their response to electromagnetic fields. A system developed at Newcastle University using a walk-through metal detector with a giant magneto-resistive sensor array to measure the spatial magnetic field is used in the study. Threat and non-threat objects have been tested. Image visualization and feature extraction of the electromagnetic field were carried out. Classification was performed using cross correlation. Promising results indicating the feasibility of using electromagnetic imaging to identify objects have been found.
SP 800-142. Practical Combinatorial Testing

Combinatorial testing can help detect problems like this early in the testing life cycle. The key insight underlying t-way combinatorial testing is that not every parameter contributes to every fault and most faults are caused by interactions between a relatively small number of parameters. This publication provides a self-contained tutorial on using combinatorial testing for real-world software, including how to use it effectively for system and software assurance. It introduces the key concepts and methods, explains use of software tools for generating combinatorial tests (freely available on the NIST web site csrc.nist.gov/acts), and discusses advanced topics such as the use of formal models of software to determine the expected results for each set of test inputs. With each topic, a section on costs and practical considerations explains tradeoffs and limitations that may impact resources or funding. The material is accessible to an undergraduate student of computer science or engineering, and includes an extensive set of references to papers that provide more depth on each topic.