Miracle-dz/UniFAR-FTUs huggingface dataset:
Creating Accessible Interactive Audio-Tactile Drawings using Spatial Augmented Reality

Interactive tactile graphics have shown a true potential for people with visual impairments, for instance for acquiring spatial knowledge. Until today, however, they are not well adopted in real-life settings (e.g. special education schools). One obstacle consists in the creation of these media, which requires specific skills, such as the use of vector-graphic software for drawing and inserting interactive zones, which is challenging for stakeholders (social workers, teachers, families of people with visual impairments, etc.). We explored how a Spatial Augmented Reality approach can enhance the creation of interactive tactile graphics by sighted users. We developed the system using a participatory design method. A user study showed that the augmented reality device allowed stakeholders (N=28) to create interactive tactile graphics more efficiently than with a regular vector-drawing software (baseline), independently of their technical background.
EXPERIENCED IN GAMBLING CONTEXTS & WHY DO INDIVIDUALS SELF-SELECT MUSIC TO ACCOMPANY GAMBLING ?

Music influences behaviours in everyday contexts (North & Hargreaves, 2008) and is a factor which can influence gambling behaviour (Griffiths & Parke, 2005; 2003). Experimenter-selected background music has been found to influence indices of gambling behaviour in laboratory gambling experiments (e.g. Spenwyn, Barrett & Griffiths, 2010; Noseworthy & Finlay, 2009; Dixon, Trigg & Griffiths, 2007; Marmurek et al., 2007). However, less is known about gamblers’ experience of music in real-life gambling contexts. To date research has considered music’s utilisation in gambling environments where fruit machines are located (Griffiths & Parke, 2005). Therefore further research is required to determine gamblers’ responses to music in different gambling environments and when playing other gambling activities. Opportunities for individuals to gamble have increased; gambling activities can be accessed in both traditional (e.g. casinos, bookmakers) and remote gambling environments. Remote gambling permits individuals to gamble using technological devices and the same can be observed for music, as listeners access music using sophisticated electronic equipment. It is therefore feasible that individuals self-select music to accompany gambling. In the present study an online questionnaire was administered to examine gamblers’ responses to music in traditional and remote gambling environments; the perceived functions and influences of music on gambling behaviour. This is the first study to examine gamblers’ motivations for self-selecting music to accompany gambling. Our findings will be presented at the conference, where we will discuss the implications of music listening for gamblers and consider how future research could further the understanding of why music influences gambling behaviour.
Entity-based coherence in statistical machine translation: a modelling and evaluation perspective

Natural language documents exhibit coherence and cohesion by means of interrelated structures both within and across sentences. Sentences do not stand in isolation from each other and only a coherent structure makes them understandable and sound natural to humans. In Statistical Machine Translation (SMT) only little research exists on translating a document from a source language into a coherent document in the target language. The dominant paradigm is still one that considers sentences independently from each other. There is both a need for a deeper understanding of how to handle specific discourse phenomena, and for automatic evaluation of how well these phenomena are handled in SMT. In this thesis we explore an approach how to treat sentences as dependent on each other by focussing on the problem of pronoun translation as an instance of a discourserelated non-local phenomenon. We direct our attention to pronoun translation in the form of cross-lingual pronoun prediction (CLPP) and develop a model to tackle this problem. We obtain state-of-the-art results exhibiting the benefit of having access to the antecedent of a pronoun for predicting the right translation of that pronoun. Experiments also showed that features from the target side are more informative than features from the source side, confirming linguistic knowledge that referential pronouns need to agree in gender and number with their target-side antecedent. We show our approach to be applicable across the two language pairs English-French and English-German. The experimental setting for CLPP is artificially restricted, both to enable automatic evaluation and to provide a controlled environment. This is a limitation which does not yet allow us to test the full potential of CLPP systems within a more realistic setting that is closer to a full SMT scenario. We provide an annotation scheme, a tool and a corpus that enable evaluation of pronoun prediction in a more realistic setting. The annotated corpus consists of parallel documents translated by a state-of-the-art neural machine translation (NMT) system, where the appropriate target-side pronouns have been chosen by annotators. With this corpus, we exhibit a weakness of our current CLPP systems in that they are outperformed by a state-of-the-art NMT system in this more realistic context. This corpus provides a basis for future CLPP shared tasks and allows the research community to further understand and test their methods. The lack of appropriate evaluation metrics that explicitly capture non-local phenomena is one of the main reasons why handling non-local phenomena has not yet been widely adopted in SMT. To overcome this obstacle and evaluate the coherence of translated documents, we define a bilingual model of entity-based coherence, inspired
Expression of WNT 5 A in Idiopathic Pulmonary Fibrosis and Its Control by TGF-β and WNT 7 B in Human Lung Fibroblasts

Idiopathic pulmonary fibrosis (IPF), or usual interstitial pneumonia (UIP), is a disease characterized by the failure of alveolar epithelial surfaces to repair effectively following damage of unknown origin. This results in epithelial hyperplasia, hypertrophy, and metaplasia, the expansion of a heterogeneous population of long-lived myofibroblast-like cells, and an expanded fibrous extracellular matrix (ECM) with advancing loss of normal pulmonary architecture and function (Schwartz et al. 1994; Green 2002). One of the key features of this disorganized restructuring are fibroblastic foci (FF), indicative of progressive disease, which have been shown to comprise a complex, interconnected reticulum extending from the pleural surface into the core of the lung parenchyma (Cool et al. 2006). FF are typically sub-epithelial and can be found near normal pulmonary tissue (Katzenstein and Myers 1998; Katzenstein et al. 2002). 617988 JHCXXX10.1369/0022155415617988Wnt5A IN IPFNewman et al. research-article2015
SYSTEMATIC REVIEW OF MOUNTAINEERS USING LORA

Mountaineering includes activities such asskiing, hiking, hill climbing and more. But, it becomes dangerous and involves high risks. Common accidents include altitude sickness, missing persons and accidental falling. Due to mountaineering activities lots of cases with heavy injuries and deaths are reported. There is a need for monitoring the mountaineer accidents and providing a rescue system. This issue is addressed and Wireless Sensor Networks along with Telehealth is seen as a promising solution. It can cut cost in power and wiring. Devices which is low poweris needed to transmit the data over very long distances were there are no network coverages. So Wireless technologies like Long Range (LoRa) which is a network being able to transmit over long distances without high power consumptions can be used under these conditions. A monitoring device is implemented which is used for monitoring the person for safety via LoRa technology. A cloud server is set up by using LoRa gateway combined with Internet of Things (IoT). This system provides anarchitecture system for monitoring, tracking and early rescue.
SmeNd and RbeSr studies of lherzolitic shergottite

The distribution pattern of the trace elements Rb, Sr, Nd and Sm for Yamato 984028 (Y984028) is consistent with its classification as a lherzolitic shergottite. The SmeNdmineral isochron of this lherzolitic shergottite defines its age to be 170 10 Ma for an initial 3Nd 1⁄4 þ11. 6 0.2. The corresponding RbeSr mineral isochron yields an identical age of 170 9 Ma and an initial Sr/Sr 1⁄4 0.710389 0.000029. The concordant SmeNd and RbeSr isochron ages suggest that Y984028 crystallized 170 7Ma ago contemporaneously with five other lherzolitic shergottites and ten enriched basaltic and olivine-phyric shergottites. The age, Srand Ndisotopic signatures further suggest that Y984028 and Y-793605, and also probably Y000097 could come from a single magmatic body. Using a two-stage evolution model, the time-averaged Rb/Sr-ratio for the mantle source of the parent magma of Y984028 is w0.182, within the range of 0.178e0. 182 that has been reported for other lherzolitic shergottites. The corresponding time-averaged Sm/Nd-ratio for the source mantle of its parent magma is super-chondritic atw0.217, implying its source was a depleted mafic part of the Martian mantle similar to that of diabasic shergottite Northwest Africa (NWA) 1460. Rb, Sr, Sm and Nd distributions in Y984028 are likely produced by pyroxene and olivine accumulation, probably from a NWA 1460like parental melt, in an intrusive magma body. 2010 Elsevier B.V. and NIPR. All rights reserved.
Adhesion molecule-modifi ed biomaterials for neural tissue engineering

Adhesion molecules (AMs) represent one class of biomolecules that promote central nervous system regeneration. These tethered molecules provide cues to regenerating neurons that recapitulate the native brain environment. Improving cell adhesive potential of non-adhesive biomaterials is therefore a common goal in neural tissue engineering. This review discusses common AMs used in neural biomaterials and the mechanism of cell attachment to these AMs. Methods to modify materials with AMs are discussed and compared. Additionally, patterning of AMs for achieving specifi c neuronal responses is explored.
Proximity labeling of protein complexes and cell type-1 specific organellar proteomes in Arabidopsis enabled by 2

16 17 Defining specific protein interactions and spatially or temporally restricted local proteomes 18 improves our understanding of all cellular processes, but obtaining such data is challenging, 19 especially for rare proteins, cell types, or events. Proximity labeling enables discovery of protein 20 neighborhoods defining functional complexes and/or organellar protein compositions. Recent 21 technological improvements, namely two highly active biotin ligase variants (TurboID and 22 miniTurbo), allowed us to address two challenging questions in plants: (1) what are in vivo 23 partners of a low abundant key developmental transcription factor and (2) what is the nuclear 24 proteome of a rare cell type? Proteins identified with FAMA-TurboID include known interactors 25 of this stomatal transcription factor and novel proteins that could facilitate its activator and 26 repressor functions. Directing TurboID to stomatal nuclei enabled purification of cell typeand 27
Approaching the religious patient in forensic psychiatry, with special focus on ethnic minority patients

ABSTRACT Ethnic minority patients are overrepresented in Danish forensic psychiatry and knowledge is needed on how these patients are approached in relation to religious and cultural issues. The aim of this study was to investigate how psychiatrists in Danish forensic psychiatry approach religious ethnic minority patients. The study revealed positive approach towards religious ethnic minority patients. However, unless religion features as part of the illness, the tendency is to not incorporate the patients’ religiosity in treatment. The study finds that the hospital chaplain is regarded by the psychiatrists as an important part of the ward and expressed the desire for a more formal cooperation with religious specialists to be developed. Finally, the study finds that religious practices such as Ramadan, common prayer, and Islamic edicts on food and unlawful touch are areas where more knowledge is needed, especially in relation to anxiety, potential stress, and conflict situations.
Augmenting a De-identification System for Swedish Clinical Text Using Open Resources and Deep Learning

Electronic patient records are produced in abundance every day and there is a demand to use them for research or management purposes. The records, however, contain information in the free text that can identify the patient and therefore tools are needed to identify this sensitive information. The aim is to compare two machine learning algorithms, Long Short-Term Memory (LSTM) and Conditional Random Fields (CRF) applied to a Swedish clinical data set annotated for de-identiﬁcation. The re-sults show that CRF performs better than deep learning with LSTM, with CRF giving the best results with an F 1 score of 0.91 when adding more data from within the same domain. Adding general open data did, on the other hand, not improve the re-sults.
A Survey on Recommendation Systems based on Online Social Communities

During the last two decades we have witnessed the tremendous amount of growth in e-commerce industry. People all over the world buy articles just by a click of mouse. Today recommendation system is an important part of almost every website. A user might not be able to find out all the desired articles and items from the endless information pool available on the internet. Recommender system suggests those items to the user which are most suitable to the user based on his data of items purchased and his ratings collected over a period of time, which helps to predict the buying behaviour of the user.Recommendation systems play an important role in suggesting relevant information to users. Community-wise social interactions as a new dimension for recommendations and a social recommendation system using trust-based collaborative filtering and community detection approaches is proposed. I will be using (i) community detection algorithm to extract friendship relations among users by analysing user-user social graph and (ii) trust-based collaborative filtering for rating prediction.
MARKET DISSIMILARITY , TECHNOLOGY COMPLEMENTARITY AND COLLABORATIVE INNOVATION PERFORMANCE : THE MODERATING EFFECTS OF IT ADOPTION

As collaborative innovation is becoming an important management issue, the lack of a holistic framework for collaborative partners’ resource heterogeneity and its different effects on firms’ innovation is becoming a critical research gap. So, one intension of our study is to differentiate two types of resource heterogeneity between collaborative partners, i.e. market dissimilarity and technology complementarity, and construct the model on the influence of that resource heterogeneity on firms’ collaborative innovation performance. Specifically, we differentiate two dimensions of innovation performance, which is innovation novelty and innovation efficiency. And another intension is to explore the boundary condition of the relationships mentioned above. Using the survey data on the collaboration between innovative firms, we tested our hypotheses using partial least squares. The results show that both market dissimilarity and technology complementarity between collaborative partners relate positively to a focal firm’s innovation performance in terms of both novelty and efficiency, while technology complementarity is more effective. Our results also indicate that IT adoption negatively moderates the relationship between market dissimilarity and collaborative innovation novelty/efficiency and that in the relationship between technology complementarity and innovation efficiency, in terms of the relationship between technology complementarity and innovation novelty, the moderating effect becomes significantly positive. This study provides a holistic framework for analysing different effects of partners’ resource heterogeneity. Second, this study constructs a contingency model by confirming empirically that IT adoption greatly moderate firms’ collaborative innovation process. Third, this study appears to challenge traditional IT theories by indicating that the moderating effects of IT adoption are actually nonlinear.
Modeling Capacity Investment under Competition using Game Theory

Globalization and competitiveness in current market environments force companies to explore new means to make better, safer and more complete decisions. In times of crisis or normal conditions, firms opt for collaboration or aggressiveness to ensure their safety and enhance their market position. Game Theory evolved from a simple mathematical tool to a strategic decision-making support. This paper uses game-theoretic principles to model and investigate the rational decision making process of two gas companies operating in an emerging market. A mathematical model is proposed for the non-cooperative strategic decision making process with a reflection on the numerical results.
Effect of Tiotropium Bromide on Airway Inflammation and Programmed Cell Death 5 in a Mouse Model of Ovalbumin-Induced Allergic Asthma

Rationale We previously demonstrated increased expression of programmed cell death 5 (PDCD5) in asthmatic patients and ovalbumin-induced allergic asthma. International guidelines (GINA 2019) have included the use of tiotropium bromide for chronic treatment of the most severe and frequently exacerbated asthma in patients ≥6 years old, who do not have good response to inhaled corticosteroids. Objective To explore the role of tiotropium and its effect on PDCD5 level in a mouse model of chronic asthma. Methods We divided 12 female mice into 2 groups: untreated asthma (n = 6) and tiotropium-treated asthma (n = 6). The impact of tiotropium was assessed by histology of lung tissue and morphometry. Pulmonary function was tested by using pressure sensors. The number of cells in bronchoalveolar lavage fluid (BALF) was detected. Levels of PDCD5, active caspase-3, and muscarinic acetylcholine receptors M2 (ChRM2) and M3 (ChRM3) were examined. Results Tiotropium treatment significantly reduced airway inflammation and remodeling in asthmatic mice and intensified the lung function. PDCD5 level was reduced with tiotropium (p < 0.05). Moreover, active caspase-3 level was decreased with tiotropium (p < 0.001), and ChRM3 level was increased. Conclusions Tiotropium treatment may alleviate the pathological changes with asthma by regulating apoptosis.
Evaluation of Standoff Distance and Explosion Weight for a Blast Resistant Structure

Manmade vibrations are most affected on the buildings due to the huge amount of external pressure. These vibrations are acted on the building which are near quarries due to the explosion of rock, due to the hydraulic drilling of the rock, heavy vehicular traffic etc. Among all the buildings which are nearer to quarries are most effected to vibration. In this study work is carried out to analyse the performance of the building for manmade vibrations caused by explosion of rock nearby construction site. In this regard a RCC building of size 18m x18m and modelled in ETABS13 for the analysis, it has been suggested the safe stand-off distance and safe explosion charge weight for the stability of the structure. The results obtained clearly mentions that for a building to be stable for blast load created by minor explosions at construction site, amount of charge weight should not be more than the specified weight respective to the specified stand-off distance.
Learning Disentangled Representations for CounterFactual Regression

We consider the challenge of estimating treatment effects from observational data; and point out that, in general, only some factors based on the observed covariates X contribute to selection of the treatment T, and only some to determining the outcomes Y. We model this by considering three underlying sources of {X, T, Y} and show that explicitly modeling these sources offers great insight to guide designing models that better handle selection bias. This paper is an attempt to conceptualize this line of thought and provide a path to explore it further. In this work, we propose an algorithm to (1) identify disentangled representations of the above-mentioned underlying factors from any given observational dataset D and (2) leverage this knowledge to reduce, as well as account for, the negative impact of selection bias on estimating the treatment effects from D. Our empirical results show that the proposed method (i) achieves state-of-the-art performance in both individual and population based evaluation measures and (ii) is highly robust under various data generating scenarios.
Secure & Dynamic Multi-Keyword Ranked Search and Storing Encrypted Data on Cloud

As the cloud computing technology emerged during the last decade, outsourcing data to cloud service for storage becomes an attractive trend, which benefits in careful efforts on heavy data maintenance. since the outsourced distributed storage is not fully reliable, it raises security worries on the most proficient method to acknowledge information identical in cloud while accomplishing honesty inspecting. In this work, we examine the issue of uprightness evaluating and secure bit duplication on cloud information. In particular, going for accomplishing both information honesty and deduplication in cloud, we propose two secure frameworks, to be specific SecCloud and SecCloud+. SecCloud presents a reviewing element with not keeping a MapReduce cloud, which helps the customers to produce information labels before transferring and in addition review the respectability of information have put away in cloud. Because of previous work the calculation by client in SecCloud is enormously decreased amid the document transferring and reviewing stages. SecCloud+ is outlined inspired by the way that customer dependably need to encode their information before transferring, and empowers respectability reviewing and secure deduplication on scrambled information.
Consumer shopping behaviour in organized retail outlet in Hyderabad Metropolitan City : An empirical study

The Indian retail sector is largely traditional, but stores in modern format are emerging. The contribution of organized retailing in the share of retail sales in India is currently very small. Based on an analysis of retail developments in countries such as Thailand, Brazil and Greece, and some experience in India, it is possible to conclude that modernization of retailing in India would be influenced by some important factors. These factors include economic development; improvements in civic situation; changes in consumer needs, attitudes' and behavior; changes in government policies; increased investment in retailing and rise in the power of organized retail. The development of modern retail will have several implications for managerial practice in manufacturing firms. In this paper an attempt is made to study determinates of store attributes and relationship between consumer demographics and retail format choice shopping. To achieves the objective of the study data is collected from 500 sample respondents base on convenience sampling. From the study it is found that there are three major determinates of store choice they are Store Atmospheric and Merchandise, Store Service and Store Convenience.
Lexicon information in neural sentiment analysis: a multi-task learning approach

This paper explores the use of multi-task learning (MTL) for incorporating external knowledge in neural models. Specifically, we show how MTL can enable a BiLSTM sentiment classifier to incorporate information from sentiment lexicons. Our MTL set-up is shown to improve model performance (compared to a single-task set-up) on both English and Norwegian sentence-level sentiment datasets. The paper also introduces a new sentiment lexicon for Norwegian.