Miracle-dz/UniFAR-FTUs huggingface dataset:
How Does Interactivity in a Video Game Render People Susceptible? A Mediating Role of Concrete-level Action Identity in Immersive Media

Action identification theory (Vallacher & Wegner, 2012) posits that individuals become open to new meanings of actions when the actions are represented in their minds as concrete details (i.e., understanding actions as concrete identities), rather than abstract meanings (i.e., understanding actions as abstract identities). Based on this, we predicted that video game interactivity renders players susceptible to new ideas of actions performed in a video game, by causing them to conceive the actions as concrete details. In a 2 (medium type: interactive vs. non-interactive) x 2 (meaning of hunting: beneficial vs. harmful) between-subjects experiment (N = 111), participants played or watched a hunting simulation game, then expressed their agreement on a news article reporting either the benefit or harm of hunting. The interactivity group, compared to the non-interactivity group, described their game experience as concrete actions, indicating that they construed actions as concrete identities. Further, these concrete identities led to greater agreement with the news article regardless whether benefit or harm of hunting was reported. These results suggest an indirect effect of interactivity on participants’ susceptibility to a new idea. Implications for using the mental representation approach in media-effect studies were discussed.
Analysis on Relevant Factors of Postoperative Delirium in Transurethral Resection of the Prostate

Objective To investigate the prevalence of delirium and perioperative factors after transurethral resection of the prostate(TURP). Methods Clinical data(including age,smoking history,drinking history,hypertension history,diabetes history,coronary heart disease history,operation history,history of taking sleeping pills,preoperative anxiety,postoperative analgesia,postoperative cystospasm,postoperative sleep disturbance and postoperative ischemia)of 412 benign prostatic hyperplasia patients underwent TURP in our hospital from January 2008 to October 2011 were retrospectively analyzed.Possible relevant factors for postoperative delirium were analyzed by using multiple factor logistic regression analysis. Results 27 patients had postoperative delirium with an occurrence rate of 6.6%(27/412). According to single factor analysis,age,history of drinking,history of hypertension,preoperative anxiety,postoperative analgesia,postoperative cystospasm,postoperative sleep disorder and postoperative ischemia all showed statistically significant differences(P0.20). Multiple factor unconditional Logistic regression analysis showed that age(OR=3.854,95%CI(1.601,9.279),P=0.003),history of hypertension(OR=3.732,95%CI(1.448,9.622),P=0.006),postoperative cystospasm(OR=4.450,95%CI(1.693,11.700),P=0.002),postoperative sleep disturbances(OR=3.122,95%CI(1.283,7.594),P=0.012),postoperative ischemia(OR=4.196,95%CI(1.330,13.237),P=0.014) entered the regression equation. Conclusion Postoperative cystospasm,senior age,the history of hypertension,postoperative sleep disturbances and postoperative ischemia are risk factors for postoperative delirium in transurethral resection of the prostate.
The Politics of Policy Development to End Obesity for Aboriginal Youth in the Educational Environment

Canada, a country of considerable wealth and resources, has one of the highest standards of living in the world. This country is politically organized as a democracy that is supportive of political and civil freedoms, yet inequalities among certain populations prevail. In general, Aboriginal people experience poorer economic, social, and environmental conditions than those of non-Aboriginal people (Canadian Population Health Initiative, 2005) and lower involvement in political and civil activity. This report also illustrates the inferior health status among Aboriginal people. Within the school system, an educational policy can serve to address an inequality. Hence, the purpose of the paper is to apply the tools outlined by Deborah Stone in her book, Policy Parodox: The Art of Political Decision Making (2002), to demonstrate why I believe school policies should be developed to prevent obesity among Aboriginal youth, to understand the politics of implementing these policies and to analyze and critique the ideas from hypothesized political opponents. Addressing these injustices provides recognition of the racism in present-day educational policy decision-making processes, which can result in more signiﬁcant progress toward an equal and just society which ensures the health of Aboriginal peoples and successive generations.
Bacterial Skin and Soft Tissue Infections

Hospital Physician March/April 2009 B acterial skin and soft tissue infections (SSTIs) are a common problem encountered in clinical practice, with approximately 14.2 million ambulatory care visits made for SSTIs in 2005.1,2 Bacterial SSTIs range from superficial epidermal infections to life-threatening necrotizing fasciitis. Although most SSTIs can be managed on an outpatient basis, physicians must remain alert for signs and symptoms indicative of a more serious infection requiring rapid evaluation and hospital admission. This article reviews the etiology, associated risk factors, and the general approach to diagnosis and treatment of SSTIs in immunocompetent outpatients, with a focus on SSTIs commonly seen in clinical practice.
Persistent memory view of in-system storage

Over the past few years of investigation into potential exascale systems, there is growing consensus that an exascale machine will have to incorporate in-system storage, a radical departure from current HPC architectures that relegate storage to a separate network with limited connectivity to compute resources. This architectural shift to include storage on or near compute nodes is driven by concerns of memory capacity and reliability at the exascale. A many-core compute node will have significantly smaller memory per core since the order of magnitude increase in number of cores will not be accompanied by a commensurate increase in node memory due to constrained power budget. Separately, it is expected that the failure rate will increase with increased component count, making defensive storage of state even more critical than in present-day systems. However, the three orders of magnitude increase in number of nodes will tax the I/O network to the point of non-functionality if traditional checkpoint methods are followed. In-system storage encompassing 1018 tightly coupled computing elements presents significant challenges to the OS and runtime stack. Even at the level of a single node, the OS file system management algorithms were designed when the average access time to storage was measured in milliseconds. High performance storage now has access time measured in microseconds, which necessitates a reevaluation of the existing buffering and I/O coalescing schemes. From the exascale perspective, there are many additional unanswered questions regarding how the global in-system storage resource should be managed. • On a single node (assuming node local storage), should the storage be organized as a POSIX file system, with full OS VFS support? As a collection of block devices managed by an application (library)? As a swap device? As a hybrid between a ram disk and a true external disk-like store? • How should the OS/R present a node’s storage to other nodes? • Should node local storage be managed as a cache to an external file system? If so, does that mean that all node local data must be mirrored in the external file system, or is there a need for multiple runtime libraries
A QUALITATIVE METHOD TO DETERMINE PROBLEMS IN TOURISM SECTOR: FOCUS GROUP INTERVIEWS

As being one of the most fragile sector; while planning tourism, planners have to fully understand the reasons of problems and develop solutions sensitively. In that scope, it is observed that, focus group interview technique has gained acceptance as a qualitative research method. There is increasing acknowledgement of the value of qualitative research approaches in social sciences. More recently, focus group methodology has gained considerable popularity as an alternative means of gathering qualitative data in the study of social sciences. Three successful focus group experience during the process of Istanbul Tourism Master Plan is subjected in article. A group of academician were responsible for the Master Plan and organised focus groups. The first part in article consists of the literature survey regarding with focus group interviews. The definitions, data analysis approaches, the ways of planning/organising groups are mentioned. Second part focuses on a sample study for Istanbul Tourism Sector. The details of three focus group organisation as a significant part of Istanbul Tourism Master Plan, analysis of focus group data and basic comparative findings of these three group interviews are presented. As a result; focus group participants’ contribution to Istanbul Tourism Master Plan is comparatively presented in terms of identifying problems and developing solutions.
IoT and Cloud Technology as Ubiquitous Computing in Case Study of Intelligent Household

Interest in Smart Homes is growing and this trend will not change in the coming years. More and more companies offer their own smart solutions. With this rising trend, there is also bigger need for the Internet of Things (IoT) devices that can communicate with each other, can be controlled remotely and that can provide added value to standard home appliance devices. Users want to know what is happening at their homes when they are away, they want to maintain control of their households at every time. This article describes some of the solutions that can be applied to the households and describe the building of the model house to test these solutions and to apply developed IoT devices. Moreover, there are described and tested different types of cloud services based on the location of the cloud servers. Our main aim was to create educational and research model for developing new network and control architecture via modern technology with IoT concept. Various control and communication architectures will be implemented using this model. We also describe some future plans and proposals for new ways of how to use and implement IoT devices. Key-Words: IoT, Cloud, HMI, M2P, remote control, Smart Home, Control as a Service, Arduino The authors are with the Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 042 00 Košice, SLOVAK REPUBLIC, peter.papcun@tuke.sk
Exergaming for stroke rehabilitation: Lessons learned for future implementation strategies

This study aimed to understand the perspectives of clinicians regarding an exergaming program to supplement stroke rehabilitation care, one year after its implementation. Semi-structured interviews were conducted with occupational and physical therapists who had referred their clients to an exergaming program. Transcribed verbatims were analyzed using inductive content analysis. Individual, organizational and technological factors influencing implementation and sustained use of an exergaming program were identified. The results stressed the need to target the key implementation factors.
Bidding on Price and Quality: An Experiment on the Complexity of Scoring Rule Auctions

We experimentally study procurement auctions when both quality and price matter. We compare two treatments where sellers compete on one dimension only (price or quality), with three treatments where sellers submit a price-quality bid and the winner is determined by a scoring rule that combines the two offers. We find that, in the scoring rule treatments, efficiency and buyer's utility are lower than predicted. Estimates from a Quantal Response Equilibrium model suggest that increasing the dimension of the strategy space imposes a complexity burden on sellers, so that a simpler mechanism like a quality-only auction may be preferable.
Saliency and Object Detection

Visual attention allows the human visual system to effectively deal with the huge flow of visual information acquired by the retina. Since the years 2000, the human visual system began to be modelled in computer vision and it became part of artificial intelligence: while learning focuses on repetitive data which can easily be modeled, computational attention focuses on abnormal, rare and surprising data which can hardly be learnt. Attention is a product of the continuous interaction between bottom-up and top-down information. While the bottom-up information has been extensively investigated through saliency models, top-down influence on visual attention has been less investigated. This paper intends to study the influence of objectbased (faces and text) top-down information on bottom-up saliency maps. It proposes a simple yet effective fusion scheme that can be applied on any bottom-up saliency model depending on the object detector effectiveness and the object size. The evaluation results show that it is possible to highly improve classical bottom-up saliency models with the arrival of better object detectors. In the future, such attention models can become as effective as deep-learning based attention models while keeping them more generic and avoiding underestimating bottom-up features. Keywords— saliency, top-down attention, bottom-up attention, visual attention, data fusion, eye-tracking, eye fixations.
Managing Developer Interruption

Society in general has several distracting elements on their daily routine. With so many devices and notifications showing in your screen or making sounds around you, it is not difficult to think that focus is something really hard to keep mainly when talking about cognitively-intense activities. Interruption occurs to individuals anytime someone or something takes their attention during focused activities. The high frequency of interruptions during cognitivelyintense activities can be annoying and detrimental to deadline-driven work, such as software development. Some researchers focused in how to avoid interruptions, the main focus of this thesis is in how to recover from them though. The main challenges in managing interruptions are: 1) Interruptions will occur even if all the notifications, phones and buzzers are turned off. 2) Interruptions are not just accidental but they can also be deliberate such as lunch, bathroom breaks or meetings. In this thesis, we propose a solution that addresses these challenges by focusing on the recovery of momentum based on the understanding that interruption recovery involves knowledge about the interrupted activity, the developer, as well as the context of the work.
A Formal Security Model for Verification of Automotive Embedded Applications

Intelligent Transport Systems (ITS) arose several years ago as a promising solution to decrease road casualties [1]. ITS are based upon heterogeneous wireless networks of vehicles and road side infrastructures. In such critical vehicular embedded systems, the safety is at stake, and so, the security of car-to-car and car-to-infrastructure communications shall be carefully taken into account, first for safety issues, but also for privacy issues. We propose a validation methodology that assists the design of such embedded systems, and based on a Formal Security Model that mainly targets model checking. If modeling of embedded in-car applications is a major issue due to system constraints and complexity, formal validation of such models shall offer a higher level of guarantee. Apart from its formal semantics, another strength of our approach relies on the decoupling between system design and security issues (e.g., attacks, requirements, and so on) whilst all are integrated in the same framework.
Methods of Software Integration of Alarm Systems

This article describes software integration methods of integrated alarm systems. The key output of the article is the proposal of classification of functions and methods of software integration for integrated alarm systems. The methods of software integration are based on linking of separate applications via a communication bus, and their control, management and visualization are providing by software products, which are installed on an external computer (server, client PC) or at unattended control centers equipped with the necessary software. Integration of the alarm systems is a modern way of using the current technological capability elements of intruder alarm system, camera systems, access control and hold-up alarm systems. Keywords—Software, closed circuit television, integrated alarm system, Integration, Intruder alarm system, non alarm application.
Do I Smell Coffee? The Tale of a 360º Mulsemedia Experience

One of the main challenges in current multimedia networking environments is to find solutions to help accommodate the next generation of mobile application classes with stringent Quality of Service (QoS) requirements whilst enabling Quality of Experience (QoE) provisioning for users. One such application class, featured in this paper, is 360o mulsemedia—multiple sensorial media—which enriches 360o video by adding sensory effects that stimulate human senses beyond those of sight and hearing, such as the tactile and olfactory ones. In this paper, we present a conceptual framework for 360o mulsemedia delivery and a 360o mulsemedia-based prototype that enables users to experience 360o mulsemedia content. User evaluations revealed that higher video resolutions do not necessarily lead to the highest QoE levels in our experimental setup. Therefore, bandwidth savings can be leveraged with no detrimental impact on QoE.
Cyber Threat Discovery from Dark Web

In the darknet, hackers are constantly sharing information with each other and learning from each other. These conversations in online forums for example can contain data that may help assist in the discovery of cyber threat intelligence. Cyber Threat Intelligence (CTI) is information or knowledge about threats that can help prevent security breaches in cyberspace. In addition, monitoring and analysis of this data manually is challenging because forum posts and other data on the darknet are high in volume and unstructured. This paper uses descriptive analytics and predicative analytics using machine learning on forum posts dataset from darknet to discover valuable cyber threat intelligence. The IBM Watson Analytics and WEKA machine learning tool were used. Watson Analytics showed trends and relationships in the data. WEKA provided machine learning models to classify the type of exploits targeted by hackers from the form posts. The results showed that Crypter, Password cracker and RATs (Remote Administration Tools), buffer overflow exploit tools, and Keylogger system exploits tools were the most common in the darknet and that there are influential authors who are frequent in the forums. In addition, machine learning helps build classifiers for exploit types. The Random Forest classifier provided a higher accuracy than the Random Tree and Naïve Bayes classifiers. Therefore, analyzing darknet forum posts can provide actionable information as well as machine learning is effective in building classifiers for prediction of exploit types. Predicting exploit types as well as knowing patterns and trends on hackers’ plan helps defend the cyberspace proactively.
OP-TOXS180186 51..64

Occupational exposure to diesel exhaust may cause lung cancer in humans. Mechanisms include DNA-damage and inflammatory responses. Here, the potential of NIST SRM2975 diesel exhaust particles (DEP) to transform human bronchial epithelial cells (HBEC3) in vitro was investigated. Long-term exposure of HBEC3 to DEP led to increased colony growth in soft agar. Several DEP-transformed cell lines were established and based on the expression of epithelial-to-mesenchymaltransition (EMT) marker genes, one of them (T2-HBEC3) was further characterized. T2-HBEC3 showed a mesenchymal/ fibroblast-like morphology, reduced expression of CDH1, and induction of CDH2 and VIM. T2-HBEC3 had reduced migration potential compared with HBEC3 and little invasion capacity. Gene expression profiling showed baseline differences between HBEC3 and T2-HBEC3 linked to lung carcinogenesis. Next, to assess differences in sensitivity to DEP between parental HBEC3 and T2-HBEC3, gene expression profiling was carried out after DEP short-term exposure. Results revealed changes in genes involved in metabolism of xenobiotics and lipids, as well as inflammation. HBEC3 displayed a higher steady state of IL1B gene expression and release of IL-1b compared with T2-HBEC3. HBEC3 and T2-HBEC3 showed similar susceptibility towards DEP-induced genotoxic effects. Liquid-chromatography-tandem-mass-spectrometry was used to measure secretion of eicosanoids. Generally, major prostaglandin species were released in higher concentrations from T2HBEC3 than from HBEC3 and several analytes were altered after DEP-exposure. In conclusion, long-term exposure to DEPtransformed human bronchial epithelial cells in vitro. Differences between HBEC3 and T2-HBEC3 regarding baseline levels and DEP-induced changes of particularly CYP1A1, IL-1b, PGE2, and PGF2a may have implications for acute inflammation and carcinogenesis. VC The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Toxicology. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/ licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com 51 TOXICOLOGICAL SCIENCES, 166(1), 2018, 51–64 doi: 10.1093/toxsci/kfy183 Advance Access Publication Date: July 16, 2018
Spiking neural networks: Model, learning algorithms and applications

Spiking neural network is the most biologically plausible neural network model, which is the core component of brain-inspired intelligence. Firstly, the most commonly used spiking neuron models and the structures of feedforward and recurrent spiking neural networks are introduced, and the temporal coding method of spiking neural networks is introduced. Then, the learning algorithms of spiking neural networks systematically, including the unsupervised learning and supervised learning algorithms are introduced. The supervised learning algorithm follows the gradient descent algorithm, the algorithm based on STDP rules and the algorithm based on spike trains convolution rules are introduced and summarized in details. Subsequently, this survey gives application examples of spiking neural networks in the fields of control, pattern recognition and brain-inspired intelligence. Some case studies of spiking neural networks and neuromorphic processor in various national brain initatives are presented. Finally, this survey discusses the current difficulties and challenges of spiking neural networks.