Miracle-dz/UniFAR-FTUs huggingface dataset:
Schadenfreude and product failures: the role of product deservingness and product status

ABSTRACT This article examines the influence of product considerations on the experience of schadenfreude – taking pleasure in the suffering of another consumer. We examine how schadenfreude is affected by the extent to which the person suffering a product failure deserves to own the product and the status of the failed product. This work also explicitly considers how these factors interact with those of the person observing the misfortune. These ideas are tested across three experiments. The results show that high product status increases schadenfreude via its exacerbating effects on envy and that a lack of perceived product deservingness increases schadenfreude via both envy and deservingness. These effects differ based on the corresponding factors of the observer where the observer’s own deservingness and lack of product status are found to exacerbate schadenfreude via envy.
Multi-Channel Cognitive Radio Networks: Modeling, Analysis and Synthesis

In this contribution, we establish a model for multi-channel cognitive radio networks (CRNs) using the theory of priority queues. This model enables us to conduct a performance analysis in the most general form by the derivation of the probability mass function (PMF) of queue length at the secondary users (SUs). In the second part, a reverse problem is considered to answer the important top-down question of whether a service requirement can be satisfied in a multi-channel CRN knowing the network parameters and traffic situation with respect to the SUs and the primary users (PUs). Terming this problem as the network synthesis, a precise conservation law is obtained, which relates the packet waiting times of both types of users, and based on which the achievable region of the network is also determined. Lastly, by the introduction of a mixed strategy, the conditions for the existence of an optimal trade-off between the interference onto the PUs and the quality-of-service of the SUs is shown, and the optimal mixed strategy is obtained when those conditions are satisfied.
Particle-based fluid flow visualization on meshes

This paper presents a new method for animating particles on an arbitrary triangular mesh starting from a fluid flow velocity field. The velocity field visualization with particles allows for the production of new special effects. An attraction constraint is introduced to correct a particle's velocity so its trajectory remains near the surface. A repulsion constraint is also used to ensure a better distribution of particles on the surface. Our velocity field is obtained by physically-based heuristics, implemented with a chain model. Our method is robust and yields good results, in particular for interactive simulations, even for systems with several thousand particles.
Rapid and Robust Transgenic High-Grade Glioma Mouse Models for Therapy Intervention Studies

Purpose: To develop a transgenic mouse model of glioma that can be conveniently used for testing therapy intervention strategies. High-grade glioma is a devastating and uniformly fatal disease for which better therapy is urgently needed. Typical for high-grade glioma is that glioma cells infiltrate extensively into surrounding pivotal brain structures, thereby rendering current treatments largely ineffective. Evaluation of novel therapies requires the availability of appropriate glioma mouse models. Experimental Design: High-grade gliomas were induced by stereotactic intracranial injection of lentiviral GFAP-Cre or CMV-Cre vectors into compound LoxP-conditional mice, resulting in K-Rasv12 expression and loss of p16Ink4a/p19Arf with or without concomitant loss of p53 or Pten. Results: Tumors reproduced many of the features that are characteristic for human high-grade gliomas, including invasiveness and blood-brain barrier functionality. Especially, CMV-Cre injection into p53;Ink4a/Arf;K-Rasv12 mice resulted in high-grade glioma with a short tumor latency (2-3 weeks) and full penetrance. Early detection and follow-up was accomplished by noninvasive bioluminescence imaging, and the practical utility for therapy intervention was shown in a study with temozolomide. Conclusion: We have developed a realistic high-grade glioma model that can be used with almost the same convenience as traditional xenograft models, thus allowing its implementation at the forefront of preclinical evaluation of new treatments. Clin Cancer Res; 16(13); 3431–41. ©2010 AACR.
In Search of the Neural Circuits of Intrinsic Motivation

Children seem to acquire new know-how in a continuous and open-ended manner. In this paper, we hypothesize that an intrinsic motivation to progress in learning is at the origins of the remarkable structure of children's developmental trajectories. In this view, children engage in exploratory and playful activities for their own sake, not as steps toward other extrinsic goals. The central hypothesis of this paper is that intrinsically motivating activities correspond to expected decrease in prediction error. This motivation system pushes the infant to avoid both predictable and unpredictable situations in order to focus on the ones that are expected to maximize progress in learning. Based on a computational model and a series of robotic experiments, we show how this principle can lead to organized sequences of behavior of increasing complexity characteristic of several behavioral and developmental patterns observed in humans. We then discuss the putative circuitry underlying such an intrinsic motivation system in the brain and formulate two novel hypotheses. The first one is that tonic dopamine acts as a learning progress signal. The second is that this progress signal is directly computed through a hierarchy of microcortical circuits that act both as prediction and metaprediction systems.
A New Method on the Segm

In this paper, we propose a new segmentation and recognition of Chinese ch circular and elliptical seals for automatic Chi retrieval. The seal identification system comp image with its model seal. However, the mod found manually, which costs quite a lot o manual stage has become the bottleneck o identification. In addition, traditional aut which were designed for circular seal imprin work well for elliptical seal images. In order t shortcomings, our method first fits the conto and then automatically classifies them into ei shape or elliptical seal shape. After that, w methods for Chinese character segmenta correction with circular and elliptical se respectively. Finally, we use our classifier com to recognize the Chinese characters on Chi Once optical character recognition (OCR) is d imprint corresponding to its input sampl retrieved for verification from the seal im Experimental results show that our me performance than traditional ones. Keywordsseal image; ellipse fi segmentation; skew correction; OCR; classifier
Filtering patent maps for visualization of diversification paths of inventors and organizations

In the information science literature, recent studies have used patent databases and patent classification information to construct network maps of patent technology classes. In such a patent technology map, almost all pairs of technology classes are connected, whereas most of the connections between them are extremely weak. This observation suggests the possibility of filtering the patent network map by removing weak links. However, removing links may reduce the explanatory power of the network on inventor or organization diversification. The network links may explain the patent portfolio diversification paths of inventors and inventing organizations. We measure the diversification explanatory power of the patent network map, and present a method to objectively choose an optimal tradeoff between explanatory power and removing weak links. We show that this method can remove a degree of arbitrariness compared with previous filtering methods based on arbitrary thresholds, and also identify previous filtering methods that created filters outside the optimal tradeoff. The filtered map aims to aid in network visualization analyses of the technological diversification of inventors, organizations, and other innovation agents, and potential foresight analysis. Such applications to a prolific inventor (Leonard Forbes) and company (Google) are demonstrated.
Cytokine-induced killer cells co-cultured with dendritic cells loaded with the protein lysate produced by radiofrequency ablation induce a specific antitumor response

Radiofrequency ablation (RFA) causes coagulative necrosis of tumor tissue and the production of local tumor protein debris. These fragments of tumor protein debris contain a large number of various antigens, which can stimulate a specific cellular immune response. In the present study, dendritic cells (DCs) were loaded with tumor protein lysate antigens that were produced in situ by RFA, and were used to treat murine colon carcinoma in combination with cytokine-induced killer (CIK) cells. Subsequent to the treatment of murine colon carcinoma by RFA, the in situ supernatant of tumor lysis was collected and the DCs were loaded with the lysate antigen to generate Ag-DCs. CIK cells induced from the spleen cells of mice were co-cultured with Ag-DCs to generate Ag-DC-CIK cells. The results revealed that the Ag-DC-CIK cells exhibited strong antitumor activity in vitro and in vivo. The morphology and immunophenotypes of these cells were determined using microscopy and flow cytometry, respectively. The cytotoxic activity of Ag-DC-CIK cells was determined using a CCK-8 assay. To establish a mouse model, mice were randomized into Ag-DC-CIK, DC-CIK, CIK and PBS control groups and monitored for tumor growth and survival time. ANOVA was used to compare the trends in the three groups for implanted tumor volumes. The log-rank test was used to compare the survival time. The present findings indicated that DCs loaded with the protein lysate antigens of tumors, produced in situ by RFA, combined with CIK cells may be a novel strategy for cancer treatment.
Enhancing GJK: computing minimum and penetration distances between convex polyhedra

The problem of tracking the distance between two convex polyhedra is finding applications in many areas of robotics, including intersection detection, collision detection, and path planning. We present new results that confirm an almost-constant time complexity for an enhanced version of Gilbert, Johnson and Keerthi's (GJK) algorithm, and also describe modifications to the algorithm to compute measures of penetration distance.
Surfactant-mediated Biodegradation of Polycyclic Aromatic Hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are toxic environmental pollutants that are known or suspected carcinogens or mutagens. Bioremediation has been used as a general way to eliminate them from the contaminated sites or aquifers, but their biodegradation is rather limited due to their low bioavailability because of their sparingly soluble nature. Surfactant-mediated biodegradation is a promising alternative. The presence of surfactants can increase the solubility of PAHs and hence potentially increase their bioavailability. However, inconclusive results have been reported on the effects of surfactant on the biodegradation of PAHs. In this work, surfactant-mediated biodegradation of PAHs is reviewed.
Meta‐analysis of continuous outcome data from individual patients

Meta‐analyses using individual patient data are becoming increasingly common and have several advantages over meta‐analyses of summary statistics. We explore the use of multilevel or hierarchical models for the meta‐analysis of continuous individual patient outcome data from clinical trials. A general framework is developed which encompasses traditional meta‐analysis, as well as meta‐regression and the inclusion of patient‐level covariates for investigation of heterogeneity. Unexplained variation in treatment differences between trials is considered as random. We focus on models with fixed trial effects, although an extension to a random effect for trial is described. The methods are illustrated on an example in Alzheimer's disease in a classical framework using SAS PROC MIXED and MLwiN, and in a Bayesian framework using BUGS. Relative merits of the three software packages for such meta‐analyses are discussed, as are the assessment of model assumptions and extensions to incorporate more than two treatments. Copyright © 2001 John Wiley & Sons, Ltd.
Niche dynamics of alien species do not differ among sexual and apomictic flowering plants

Summary Biological invasions can be associated with shifts of the species’ climatic niches but the incidence of such shifts is under debate. The reproductive system might be a key factor controlling such shifts because it influences a species’ evolutionary flexibility. However, the link between reproductive systems and niche dynamics in plant invasions has been little studied so far. We compiled global occurrence data sets of 13 congeneric sexual and apomictic species pairs, and used principal components analysis (PCA) and kernel smoothers to compare changes in climatic niche optima, breadths and unfilling/expansion between native and alien ranges. Niche change metrics were compared between sexual and apomictic species. All 26 species showed changes in niche optima and/or breadth and 14 species significantly expanded their climatic niches. However, we found no effect of the reproductive system on niche dynamics. Instead, species with narrower native niches showed higher rates of niche expansion in the alien ranges. Our results suggest that niche shifts are frequent in plant invasions but evolutionary potential may not be of major importance for such shifts. Niche dynamics rather appear to be driven by changes of the realized niche without adaptive change of the fundamental climatic niche.
Adaptive Learning Resources Sequencing in Educational Hypermedia Systems

Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have been reported in literature aiming to support the Adaptation Model design by providing AEHS designers direct guidance or semi-automatic mechanisms for making the design process less demanding, still it requires significant effort to overcome the problems of inconsistency, confluence and insufficiency, introduced by the use of rules. Due to the problems of inconsistency and insufficiency of the defined rule sets in the Adaptation Model, conceptual “holes” can be generated in the produced learning resource sequences (or learning paths). In this paper, we address the design problem of the Adaptation Model in AEHS proposing an alternative sequencing method that, instead of generating the learning path by populating a concept sequence with available learning resources based on pre-defined adaptation rules, it first generates all possible learning paths that match the learning goal in hand, and then, adaptively selects the desired one, based on the use of a decision model that estimates the suitability of learning resources for a targeted learner. In our simulations we compare the learning paths generated by the proposed methodology with ideal ones produced by a simulated perfect rule-based AEHS. The simulation results provide evidence that the proposed methodology can generate almost accurate learning paths avoiding the need for defining complex rule sets in the Adaptation Model of AEHS.
Performance Measurement of DEVS Dynamic Structure on Forest Fire Spreading Simulation

--Traditional simulation methodology supports only changes in models’ state variables. Dynamic structure modeling allows to model both changes in state variables and changes in structure and has been applied to different applications. This paper focuses on the performance issue of dynamic structure implemented in the DEVS modeling and simulation environment. Six performance measurement metrics are defined. Measurement results and analysis are provided to evaluate the advantages and limitations of dynamic structure modeling in the context of forest fire spreading simulation.
Memory efficient adjacent triangle connectivity of a vertex using triangle strips

We often need to refer to adjacent elements (e.g., vertices, edges and triangles) in triangle meshes for rendering, mesh simplification and other processes. It is, however, sometimes impossible to prepare the enormous memory needed to represent element connectivity in gigantic triangle meshes. This paper proposes a new scheme for referring to adjacent triangles around a vertex in nonmanifold triangle meshes. First, we introduce the constraints to allow random access to a triangle in a sequence of triangle strips. Then, for each vertex, we construct a list of references to its adjacent strips as a representation of triangle connectivity. Experimental results show that, compared to conventional methods, our scheme can reduce the total size of a triangle mesh and adjacent triangle connectivity to about 50%
Laissez-faire localism: Features and emergent themes presented in a case study University Technical College

Education policy reform in England, as enabled by successive governments, has supported the liberalization and supply of an increasing number and diverse range of provision with varying structures and governance models. As such, these reforms have generated a portfolio for parents to exercise school choice. This article explores the discourses surrounding the liberalization of education provision and its implications for technical education, by adopting Hodgson and Spours’ (2012) conceptualization of localism as a lens through which to empirically research one of the former government’s flagship technical institutions – the University Technical College (UTC). Drawing on a series of interviews, the study examines and analyses the concept of localism within the context of a UTC and identifies emergent themes. Importantly, the study’s findings challenge the assumption that institutions will, of their own volition, come together and put aside institutional self-interest for the greater good of the learner and the local and regional skills agenda. The study concludes with recommendations for further research to determine whether the tensions, competitive practices and competition identified at a single institution may be indicative of those experienced more widely across UTCs.
Learning programming with erlang

This paper presents an interactive framework for pupils to learn the basic concepts of programming by means of the functional programming language Erlang. Beside the idea of the framework we also sketch the different learning targets and exercises to deepen programming skills. The framework was successfully utilized in a programming course for pupils in their last three school years.
Thomson scattering of chiral tensors and scalars against a self-dual string

We give a non-technical outline of a program to study the (2,0) theories in six space-time dimensions. Away from the origin of their moduli space, these theories describe the interactions of tensor multiplets and self-dual spinning strings. We argue that if the ratio between the square of the energy of a process and the string tension is taken to be small, it should be possible to study the dynamics of such a system perturbatively in this parameter. As a first step in this direction, we perform a classical computation of the amplitude for scattering chiral tensor and scalar fields (i.e. the bosonic part of a tensor multiplet) against a self-dual spinnless string.
Generation of qualitative spatio-temporal representations from visual input

The simultaneous interpretation of object behaviour from real world image sequences is a highly desirable goal in machine vision. Although this is rather a sophisticated task, one method for reducing the complexity in stylized domains is to provide a context specific spatial model of that domain. Such a model of space is particularly useful when considering spatial event detection where the location of an object could indicated the behaviour of that object within the domain. To date, this approach has suffered the drawback of having to generate the spatial representation by hand for each new domain. An algorithm, complete with experimental results, is described for the automatic generation of a hierarchical region based on context specific model of space for strongly stylized domains from the observation of objects moving within that domain over extended periods. The highest (hierarchical) level of region describes areas of behavioural significance or the paths followed by moving objects. An extension to the region generation algorithm allows these regions to tbe further sub-divided into equi-temporal regions (where it takes an object approximately the same time to traverse each sub-division) that can be used by an attention control mechanism to identify interacting objects. By using a region based model, it becomes possible to convert the quantitative object locations into qualitative locations which then enables the use of the rich family of qualitative logics for real-world surveillance. To demonstrate the effectiveness of the spatio-temporal model combined with qualitative object representations, an event learning strategy is demonstrated that allows the automatic generation of contextually relevant event models, which are usually provided as part of the a priori system knowledge.
Exemplifying Moldable Development

Developing and evolving software requires developers to continuously make decisions about how to steer the design and implementation of their applications. To make informed decisions developers commonly formulate detailed and domain-specific questions about their software systems and use tools to explore available information and answer those questions. Development tools however focus on generic programming tasks while program comprehension and analysis tools typically are not tightly integrated with their development tools and environments. This has a negative effect on program comprehension as it increases the effort and the time needed to obtain an answer. To improve program comprehension we propose that developers build software using development tools tailored to their specific application domains, as this can directly answer domain-specific questions. We introduce moldable development as an approach for developing software in which developers evolve development tools together with their applications. In this paper we sketch the idea of moldable development and give examples to illustrate how it can be applied in practice. Through these examples we show that given a low cost for extending development tools, developers can create relevant and useful customizations to help them evolve their own applications.
A spindle model for contextual object detection

Recent progresses on visual object detection manifest the significance of context information (e.g., scene semantic, object interactions, geometric cues, etc.) for boosting the recognition performance. Particularly, the object pose information has been widely exploited as important contextual cue in human-object interactions (HOIs). This paper proposes a spindle model to utilize pose information in multi-class object interactions, which is not limited to HOIs, for contextual object detection. The structural support vector machine (SSVM) algorithm is induced to learn the proposed structured model. Moreover, we present an efficient method based on K-L divergence (KLD) to refine the pose context features from potentially huge number of dimensions. The experimental results on PASCAL VOC 2007 dataset demonstrate that the proposed model can effectively improve performance w.r. t. the state-of-the-art methods for object detection tasks.