Miracle-dz/UniFAR-FTUs huggingface dataset:
Activity Preferences of Persons With Dementia

Older adults prefer to engage in a variety of leisure and recreational activities. These activities vary in type depending on the older adult's level of physical and mental ability. There is little empirical evidence documenting the preferred activities of older adults with dementia. The present study examines the self-reported activity preferences of 216 persons with dementia and the relationship of these activities to demographic characteristics and well-being outcomes. Results demonstrate hypothesized demographic differences and reinforce the importance of engaging persons with dementia in activities that they find meaningful.
Modelling and simulation of human behavioural and emotional dynamics during emergencies: a review of the state-of-the-art

Research works on human behaviour modelling and simulation continue to increase in recent years. Indeed, emotion and personality are among the most important human characteristics that influence behaviour. Particularly, during emergencies, emotional dynamics have a major influence on individual and collective behaviours. In this paper, we aim to provide an integrated review on this challenging and multidisciplinary field. We give first an overview of computational models of emotions and personalities. Then, we expose and discuss emotional and behavioural models. An emphasis is given to the role of internal and external emotional dynamics in the production of realistic behaviours during emergencies. Internal emotional dynamics affect cognitive processes at an individual level. However, external emotional dynamics, studied through phenomena such as empathy or emotional contagion, are essential to simulate collective emotional dynamics.
GENSOFNN-YAGER: A Novel Hippocampus-like Learning Memory System Realizing Yager Inference

Recent advances in cognitive neuroscience have revealed the role of hippocampal region as a mediator for explicit memory, which is crucial for human cognitive processes and for developing machine intelligence. This paper presents the novel Generic Self-organizing Fuzzy Neural Network realizing Yager inference (GENSOFNN-YAGER) that is built specifically to model the functional aspects of hippocampus as explicit memory and to emulate human decision making abilities. The main feature of the Yager inference is that, when the input matches the rule antecedent exactly, the resultant output matches the consequent exactly, in a way similar to that of human reasoning. The presented experimental results show the effectiveness of the proposed system.
Decision Tree Grafting

This paper extends recent work on decision tree grafting. Grafting is an inductive process that adds nodes to inferred decision trees. This process is demonstrated to frequently improve predictive accuracy. Superficial analysis might suggest that decision tree grafting is the direct reverse of pruning. To the contrary, it is argued that the two processes are complementary. This is because, like standard tree growing techniques, pruning uses only local information, whereas grafting uses non-local information. The use of both pruning and grafting in conjunction is demonstrated to provide the best general predictive accuracy over a representative selection of learning tasks.
The B-book - assigning programs to meanings

Tribute Foreword Introduction Part I. Mathematics: 1. Mathematical reasoning 2. Set notation 3. Mathematical objects Part II. Abstract Machines: 4. Introduction to abstract machines 5. Formal definition of abstract machines 6. Theory of abstract machines 7. Constructing large abstract machines 8. Examples of abstract machines Part III. Programming: 9. Sequencing and loop 10. Programming examples Part IV. Refinement: 11. Refinement 12. Constructing large software systems 13. Examples of refinement Appendixes Index.
Recasting subjectivity through the lenses: new forms of environmental mobilisation in China

Visual imagery in environmental politics can be an effective way to engage the public. However, research based on 21 interviewees with activists from nine environmental non-governmental organisations (ENGOs) in China suggests that the value of images in promoting environmental initiatives is not limited to the exhibition of them, but is also seen in the making of them. Increasingly in China, ENGOs are offering free natural photographic tutoring to the public. Camera lenses are seen as conduits to recast self-nature relations, which has the potential to raise environmental awareness and promote ENGO membership. Drawing on both theories of social movements and contemporary Chinese subaltern political sociology, this paper provides new insights into grass-roots environmental mobilisation in China.
EFEITO DE EXERCÍCIOS CONTRA-RESISTÊNCIA NA POSTURA DE MULHERES

Posture problems hit a big portion of world population, causing relative slight discomforts and even serious injuries. To maintain a proper posture, musculoskeletal balance is essential. Since this balance may be positively influenced by muscular strengthening, the purpose of the present study was to assess the possible posture changes caused by 16-week resistance training. Twelve women, college students, sedentary or moderately active (regular physical activity < 2 times per week) took part of the sample. They had not participated in regular weight training programs over 6 months prior to the beginning of the experiments. Posture assessment involved observational analysis of sagital and dorsal plans, using a simetrograph. Data were treated, at first, by descriptive proceedings. Comparisons between the moments of study were analyzed by ratio comparison test (p ≤ 0,05). The segments that apparently got more improvement with the resistance training were head/neck, abdomen e ankle. Thus, we can conclude that apparently, for this group, the resistance training is efficient to the improvement of these segments.Posture. Physical education and training. Measures.
A Hollywood View of Christian Mis-Education

Abstract Saved! is the first Hollywood movie to focus on private religious education and is therefore a significant milestone in popular culture. The movie is critical of the school along the very dimensions of concern to Brighouse (2006): undermining personal autonomy, fostering social divisiveness, and promoting anti-democratic values. This article is a close reading of the film's illiberal representation of Christian education, including a discussion of whether liberalism may legitimately require traditional schools to privilege autonomy over obedience. The reading focuses on the issues the film highlights (and avoids): gender identity, sexual freedom, and abortion. Finally, the film is placed within the genre of anti-private school films, which valorize individualism over loyalty to group norms.
SemEval-2012 Task 1: English Lexical Simplification

We describe the English Lexical Simplification task at SemEval-2012. This is the first time such a shared task has been organized and its goal is to provide a framework for the evaluation of systems for lexical simplification and foster research on context-aware lexical simplification approaches. The task requires that annotators and systems rank a number of alternative substitutes -- all deemed adequate -- for a target word in context, according to how "simple" these substitutes are. The notion of simplicity is biased towards non-native speakers of English. Out of nine participating systems, the best scoring ones combine context-dependent and context-independent information, with the strongest individual contribution given by the frequency of the substitute regardless of its context.
Enabling My Robot To Play Pictionary: Recurrent Neural Networks For Sketch Recognition

Freehand sketching is an inherently sequential process. Yet, most approaches for hand-drawn sketch recognition either ignore this sequential aspect or exploit it in an ad-hoc manner. In our work, we propose a recurrent neural network architecture for sketch object recognition which exploits the long-term sequential and structural regularities in stroke data in a scalable manner. Specifically, we introduce a Gated Recurrent Unit based framework which leverages deep sketch features and weighted per-timestep loss to achieve state-of-the-art results on a large database of freehand object sketches across a large number of object categories. The inherently online nature of our framework is especially suited for on-the-fly recognition of objects as they are being drawn. Thus, our framework can enable interesting applications such as camera-equipped robots playing the popular party game Pictionary with human players and generating sparsified yet recognizable sketches of objects.
An ovine transgenic Huntington's disease model.

Huntington's disease (HD) is an inherited autosomal dominant neurodegenerative disorder caused by an expansion of a CAG trinucleotide repeat in the huntingtin (HTT) gene [Huntington's Disease Collaborative Research Group (1993) A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. The Huntington's Disease Collaborative Research Group. Cell, 72, 971-983]. Despite identification of the gene in 1993, the underlying life-long disease process and effective treatments to prevent or delay it remain elusive. In an effort to fast-track treatment strategies for HD into clinical trials, we have developed a new large-animal HD transgenic ovine model. Sheep, Ovis aries L. , were selected because the developmental pattern of the ovine basal ganglia and cortex (the regions primarily affected in HD) is similar to the analogous regions of the human brain. Microinjection of a full-length human HTT cDNA containing 73 polyglutamine repeats under the control of the human promotor resulted in six transgenic founders varying in copy number of the transgene. Analysis of offspring (at 1 and 7 months of age) from one of the founders showed robust expression of the full-length human HTT protein in both CNS and non-CNS tissue. Further, preliminary immunohistochemical analysis demonstrated the organization of the caudate nucleus and putamen and revealed decreased expression of medium size spiny neuron marker DARPP-32 at 7 months of age. It is anticipated that this novel transgenic animal will represent a practical model for drug/clinical trials and surgical interventions especially aimed at delaying or preventing HD initiation. New sequence accession number for ovine HTT mRNA: FJ457100.
Tumor size predicts prognosis of head and neck synovial cell sarcoma

Head and neck synoviosarcoma (HNSS) is uncommon. To the best of our knowledge, the specific clinicopathological characteristics, treatment outcome and prognostic factors of HNSS were uninvestigated at the time of writing, so a meta-analysis was performed. An online data collection was carried out using PubMed and Google Scholar. Studies that reported primary HNSS and the treatment, follow-up time and outcome were chosen for the present study. In total, 93 cases from 26 studies were included for analysis. The study sample consisted of 55 males and 38 females and the median age was 32.1 years (range, 4–76 years). The median follow-up period was 62.1 months (range, 1–373 months). The tumor size was correlated with local recurrence and metastasis of HNSS, as well as with mortality (P=0.001, P<0.0001 and P<0.0001, respectively). The three-year, five-year and 10-year survival rates were 82.1, 80.4 and 78.2% for treatment with surgery alone, and 88.5, 85.5 and 82% for treatment with surgery plus radiotherapy, respectively. A significant tumor size-dependent difference was found between the overall survival (OS) rates (P<0.0001), as tumors that were >5.0 cm in diameter were associated with a worse OS rate (hazard ratio, 6.460; 95% confidence interval, 206–18.917; P=0.001). The tumor size was found to be an independent adverse prognostic factor for the OS of HNSS patients. In conclusion, surgical excision is a mainstream treatment of HNSS and post-operative adjuvant radiotherapy improves the OS rate of HNSS patients.
Texture-dependent frequency selective reconstruction of non-regularly sampled images

There exist many scenarios where pixel information is available only on a non-regular subset of pixel positions. For further processing, however, it is required to reconstruct such images on a regular grid. Besides many other algorithms, frequency selective reconstruction can be applied for this task. It performs a block-wise generation of a sparse signal model as an iterative superposition of Fourier basis functions and uses this model to replace missing or corrupted pixels in an image. In this paper, it is shown that it is not required to spend the same amount of iterations on both homogeneous and heterogeneous regions. Hence, a new texture-dependent approach for frequency selective reconstruction is introduced that distributes the number of iterations depending on the texture of the regions to be reconstructed. Compared to the original frequency selective reconstruction and depending on the number of iterations, visually noticeable gains in PSNR of up to 1.47 dB can be achieved.
Subsurface fluid distribution and possible seismic precursory signal at the Salse di Nirano mud volcanic field, Italy

Mud volcanoes are geological systems often characterized by elevated fluid pressures at depth deviating from hydrostatic conditions. This near-critical state makes mud volcanoes particularly sensitive to external forcing induced by natural or man-made perturbations. We used the Nirano mud volcanic field as a natural laboratory to test pre- and post-seismic effects generated by distant earthquakes. We first characterized the subsurface structure of the Nirano mud volcanic field with a geoelectrical study. Next, we deployed a broad-band seismic station in the area to understand the typical seismic signal generated by the mud volcano. Seismic records show a background noise below 2 s, sometimes interrupted by pulses of drumbeat-like high-frequency signals lasting from several minutes to hours. To date this is the first observation of drumbeat signal observed in mud volcanoes. In 2013 June we recorded a M4.7 earthquake, that occurred approximately 60 km far from our seismic station. According to empirical estimations the Nirano mud volcanic field should not have been affected by the M4.7 earthquake. Yet, before the seismic event we recorded an increasing amplitude of the signal in the 10–20 Hz frequency band. The signal emerged approximately two hours before the earthquake and lasted for about three hours. Our statistical analysis suggests the presence of a possible precursory signal about 10 min before the earthquake.
Successful Catheter Ablation as a Substitute for Cardiac Resynchronization Therapy in Patient with an Accessory Pathway-induced Cardiomyopathy

A 50-year-old man presented with exertional dyspnea and orthopnea. An electrocardiogram showed a delta wave and a wide QRS complex, similar to left bundle branch block. Cardiac echocardiography revealed diffuse severe hypokinesis and dyssynchrony. The patient was diagnosed with congestive heart failure. We considered that the patient's condition was caused by an accessory pathway-induced cardiomyopathy after heart failure compensation with guideline-oriented medical therapy. We therefore performed catheter ablation for right-sided pre-excitation syndrome as cardiac resynchronization therapy. The left ventricular dyssynchrony was resolved immediately after the procedure, and the patient's ventricular contraction improved, with a reduced cardiac volume at 6 months after the procedure-thus suggesting that the accessory pathway had affected the patient's cardiac function.
Reversibility of graft rejection following a short cyclosporin‐a administration 5 days after grafting

The aim of this research was to investigate whether cyclosporin‐A (Cy‐A) could exert its action on graft rejection in progress. For this purpose, heartlung grafting was performed in a strong hystoincompatible combination of rats (BN/LEW). In one group of animals, Cy‐A was administered at the dose of 15 mg/kg daily for 10 days starting on the 5th day after grafting. In a control group only olive oil was administered. Five of six animals treated with Cy‐A showed a graft survival over 4 weeks and in two cases it was over 2 months when they were killed.
How to win friends and influence people, truthfully: influence maximization mechanisms for social networks

Throughout the past decade there has been extensive research on algorithmic and data mining techniques for solving the problem of influence maximization in social networks: if one can incentivize a subset of individuals to become early adopters of a new technology, which subset should be selected so that the word-of-mouth effect in the social network is maximized? Despite the progress in modeling and techniques, the incomplete information aspect of the problem has been largely overlooked. While data can often provide the network structure and influence patterns may be observable, the inherent cost individuals have to become early adopters is difficult to extract. In this paper we introduce mechanisms that elicit individuals' costs while providing desirable approximation guarantees in some of the most well-studied models of social network influence. We follow the mechanism design framework which advocates for allocation and payment schemes that incentivize individuals to report their true information. We also performed experiments using the Mechanical Turk platform and social network data to provide evidence of the framework's effectiveness in practice.
Industry Recommendations: Characteristics, Investment Value, and Relation to Firm Recommendations *

In addition to firm recommendations, brokers also issue recommendations for industries. We study these recommendations using data newly available from IBES. First, we find that the distribution of industry recommendations is quite balanced. Brokers tend to issue optimistic recommendations to industries that show high levels of R&D intensity, past profitability and past returns, as well as to industries in which they are active in providing underwriting services. Second, industry recommendations appear to have investment value: portfolios long in industries about which analysts are optimistic and short in industries about which analysts are pessimistic generate significant abnormal returns. Finally, we find that industry recommendations contain information that is orthogonal to that included in firm recommendations. This evidence sheds new light on the interpretation and investment value of firm recommendations. It suggests that analysts typically benchmark their firm recommendations to industry peers, even when they proclaim to be using a market benchmark. In line with this view, we show that the investment value of analysts’ recommendations is enhanced when both industry and firm recommendations are used jointly.
Association between Urinary Excretion of Cortisol and Markers of Oxidatively Damaged DNA and RNA in Humans

Chronic psychological stress is associated with accelerated aging, but the underlying biological mechanisms are not known. Prolonged elevations of the stress hormone cortisol is suspected to play a critical role. Through its actions, cortisol may potentially induce oxidatively generated damage to cellular constituents such as DNA and RNA, a phenomenon which has been implicated in aging processes. We investigated the relationship between 24 h excretion of urinary cortisol and markers of oxidatively generated DNA and RNA damage, 8-oxo-7,8-dihydro-2′-deoxyguanosine and 8-oxo-7,8-dihydroguanosine, in a sample of 220 elderly men and women (age 65 – 83 years). We found a robust association between the excretion of cortisol and the oxidation markers (R2 = 0.15, P<0.001 for both markers). Individuals in the highest quartile of cortisol excretion had a 57% and 61% higher median excretion of the DNA and RNA oxidation marker, respectively, than individuals in the lowest quartile. The finding adds support to the hypothesis that cortisol-induced damage to DNA/RNA is an explanatory factor in the complex relation between stress, aging and disease.
Learning Distinctions and Rules in a Continuous World through Active Exploration

We present a method that allows an agent through active exploration to autonomously build a useful representation of its environment. The agent builds the representation by iteratively learning distinctions and predictive rules using those distinctions. We build on earlier work in which we showed that by motor babbling an agent could learn a representation and predictive rules that by inspection appeared reasonable. In this paper we add active learning and show that the agent can build a representation that allows it to learn predictive rules to reliably control its hand and to achieve a simple goal.
Access control enforcement for conversation-based web services

Service Oriented Computing is emerging as the main approach to build distributed enterprise applications on the Web. The widespread use of Web services is hindered by the lack of adequate security and privacy support. In this paper, we present a novel framework for enforcing access control in conversation-based Web services. Our approach takes into account the conversational nature of Web services. This is in contrast with existing approaches to access control enforcement that assume a Web service as a set of independent operations. Furthermore, our approach achieves a tradeoff between the need to protect Web service's access control policies and the need to disclose to clients the portion of access control policies related to the conversations they are interested in. This is important to avoid situations where the client cannot progress in the conversation due to the lack of required security requirements. We introduce the concept of k-trustworthiness that defines the conversations for which a client can provide credentials maximizing the likelihood that it will eventually hit a final state.
An Exact Solution to a Three Dimensional Ising Model and Dimensional Reductions

A high temperature expansion is employed to map some complex anisotropic nonhermitian three and four dimensional Ising models with algebraic long range interactions into a solvable two dimensional variant. We also address the dimensional reductions for anisotropic two dimensional XY and other models. For the latter and related systems it is possible to have an effective reduction in the dimension without the need of compactifying some dimensions. Some solutions are presented. This framework further allows for some very simple general observations. It will be seen that the absence of a ``phase interference'' effect plays an important role in high dimensional problems. A very forbidding purely algebraic recursive series solution to the three dimensional nearest neighbor Ising model will be given. In the aftermath, the full-blown three dimensional nearest neighbor Ising model is exactly mapped onto a single spin 1/2 particle with nontrivial dynamics. All this allows for a formal high dimensional Bosonization.
A Correspondence-Based Software Toolkit for Image Registration

This paper presents a correspondence-based toolkit for image registration. Written in C++, the toolkit complements the capabilities of the insight toolkit (ITK). Major components include features, feature sets, match generators, error scale estimators, robust transformation estimators, and convergence testers, all combined and controlled by several different registration engines. Correspondence-based algorithms which can be implemented using the toolkit extend from ICP to hybrids of intensity-based and feature-based registration. The toolkit is being used both as an education tool and the foundation for developing new algorithms.