Miracle-dz/UniFAR-FTUs huggingface dataset:
Mirror Models for Pervasive Computing : Just-inTime Reasoning about Device Ecologies

In pervasive computing environments, users will need to interact with collections of devices surrounding them (such as the “system” of smart devices in a user’s home), which we metaphorically term device ecologies. A user can interact with these devices with embedded software and hardware, either directly via the device’s own interface, or automated through scripts executed by a central coordinator. For the latter, we employ a workflow abstraction for the collective operation of devices, which we call decoflow. While executable formal models are typically used at specification time, we maintain and use such models, calling them mirror models, to record the on-going states of devices, their relationships, and the effects that such devices have on the environment. Users effectively update a mirror model of the devices s/he interacts with. The model can be used to predict the effects of decoflows just before execution. Generalizing from mirror models for device ecologies, we propose the novel paradigm of continually updated mirror models for ongoing tracking and reasoning about pervasive computing systems which cohabitates with the user.
Initial Conditions of Planet Formation: Lifetimes of Primordial Disks

The statistical properties of circumstellar disks around young stars are important for constraining theoretical models for the formation and early evolution of planetary systems. In this brief review, I survey the literature related to ground‐based and Spitzer‐based infrared (IR) studies of young stellar clusters, with particular emphasis on tracing the evolution of primordial (“protoplanetary”) disks through spectroscopic and photometric diagnostics. The available data demonstrate that the fraction of young stars with optically thick primordial disks and/or those which show spectroscopic evidence for accretion appears to approximately follow an exponential decay with characteristic time ∼2.5 Myr (half‐life ∼1.7 Myr). Large IR surveys of ∼2–5 Myr‐old stellar samples show that there is real cluster‐by‐cluster scatter in the observed disk fractions as a function of age. Recent Spitzer surveys have found convincing evidence that disk evolution varies by stellar mass and environment (binarity, proximity to ma.
Tissue geometry patterns epithelial–mesenchymal transition via intercellular mechanotransduction

Epithelial–mesenchymal transition (EMT) is a phenotypic change in which epithelial cells detach from their neighbors and become motile. Whereas soluble signals such as growth factors and cytokines are responsible for stimulating EMT, here we show that gradients of mechanical stress define the spatial locations at which EMT occurs. When treated with transforming growth factor (TGF)‐β, cells at the corners and edges of square mammary epithelial sheets expressed EMT markers, whereas those in the center did not. Changing the shape of the epithelial sheet altered the spatial pattern of EMT. Traction force microscopy and finite element modeling demonstrated that EMT‐permissive regions experienced the highest mechanical stress. Myocardin‐related transcription factor (MRTF)‐A was localized to the nuclei of cells located in high‐stress regions, and inhibiting cytoskeletal tension or MRTF‐A expression abrogated the spatial patterning of EMT. These data suggest a causal role for tissue geometry and endogenous mechanical stresses in the spatial patterning of EMT. J. Cell. Biochem. 110: 44–51, 2010. © 2010 Wiley‐Liss, Inc.
A taxonomy of computer architecture visualizations

In the domain of software visualizations, taxonomies have been built to classify and evaluate environments for algorithm and program visualization. Taxonomies are valuable too, in the development phase of new environment. The field of computer architecture and assembly language that is at the border of the software and hardware domains has been neglected. In this paper I present a taxonomy focusing on this field with emphasis on the didactic and cognitive aspect of the visualization environment. The ECPU learning environment was developed to teach computer architecture and assembly language at introductory level. The considerations that were taken in account during the ECPU development are presented in the context of the taxonomy.
Needs Assessment of the Appalachian Region: Results of Think Tank and Survey. Final Report, Part Three of Three.

A project report describes a Tennessee State University planning project for an educational laboratory serving the Appalachian states of Kentucky, Tennessee, Virginia, and West Virginia. A needs assessment and think tank session were conducted to identify educational problems, gather data on educational strengths/weaknesses in each state, generate ideas for educational improvement, explore research options of educators, suggest new programs/research topics, identify strategies for educational laboratory operations/services, and explore potential relationships with other Appalachian educational organizations. Regional problems were analyzed from state, regional, and national perspectives. Educational trends for the Appalachian region were discussed. Educational research, development, dissemination, assistance, and training capabilities of organizations in the region were assessed and their effectiveness evaluated. An organizational design for the regional educational laboratory was proposed. Capabilities of Tennessee State University to establish a laboratory were described, including staff, research/development activities, facilities, equipment, library resources, and satellite institutions. Strategies for governance, management, planning, and evaluation systems for the laboratory were presented. Extensive appendices list survey and think tank participants, related research projects of Tennessee State University and its satellites, and recurring educational problems identified in the think tank session. A bibliography with 169 references is included. (LFL) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ***********************************************************************
Schedulability analysis of Multi-Frame messages over Controller Area Networks with mixed-queues

The Controller Area Network (CAN) is one of the most widely utilized real-time communication networks, which has plenty of applications especially in automotive industry. Many works have been proposed regarding the CAN schedulability analysis which is very important for guaranteeing the safety and reliability of hard real-time systems. Most of the existing analysis methods assume a periodic message model, and some of them take sporadic messages into account. However, for some applications, message transmissions may follow a specific pattern instead of repeating the same transmission period by period, where applying the existing methods may include much pessimism. In this paper, we apply the Multi-Frame task model, which is first proposed by Mok and Chen in [1], on messages over a CAN-based system with mixed message queues. In this preliminary work, the analysis is based on some specific assumptions. A more general analysis will be investigated in our later works.
Likelihood-based estimation of continuous-time epidemic models from time-series data: application to measles transmission in London

We present a new statistical approach to analyse epidemic time-series data. A major difficulty for inference is that (i) the latent transmission process is partially observed and (ii) observed quantities are further aggregated temporally. We develop a data augmentation strategy to tackle these problems and introduce a diffusion process that mimicks the susceptible–infectious–removed (SIR) epidemic process, but that is more tractable analytically. While methods based on discrete-time models require epidemic and data collection processes to have similar time scales, our approach, based on a continuous-time model, is free of such constraint. Using simulated data, we found that all parameters of the SIR model, including the generation time, were estimated accurately if the observation interval was less than 2.5 times the generation time of the disease. Previous discrete-time TSIR models have been unable to estimate generation times, given that they assume the generation time is equal to the observation interval. However, we were unable to estimate the generation time of measles accurately from historical data. This indicates that simple models assuming homogenous mixing (even with age structure) of the type which are standard in mathematical epidemiology miss key features of epidemics in large populations.
Evaluating the Outcomes of Plans: Theory, Practice, and Methodology

Despite calls for performance-oriented and evidence-based planning, the outcomes of land use and environmental plans are rarely monitored or assessed ex post facto (that is, post implementation). As a result, planners cannot know whether or why plans achieve their goals, or learn from the results of past interventions to improve planning practice. This evaluation gap is caused by a lack of methodology to evaluate the outcomes of plans and the difficulty of attributing changes to planning activities. We address this gap by proposing and testing a plan-outcome evaluation (POE) methodology. We demonstrate its broad applicability and usefulness in the context of local plans in New Zealand. The POE methodology will be useful to practitioners and academics seeking to assess the outcomes of plans in countries with western planning traditions.
Automatic Topic(s) Identification from Learning Material: An Ontological Approach

The ability to judge the relevance of topics and related sources in information-rich environments is a key to success when scanning online learning environments. A Learner may be looking for learning materials explaining given topic or exercises on the topic. Any learning material may cover multiple topics related to multiple subject domains. This paper presents ontological approach for identifying major topics, covered in the learning material. Along with the topics, the subject and discipline to which those topics belongs to and relevance of the topic in the learning material as compared to other topics present in the same document are also discovered. Domain ontology is developed to retrieve the topics covered in the document. We present an evaluation against a manually categorized topics as well as author’s judgment of relevance of the topics discovered by our system. Evaluation results show that the technique presented by us is effective in identifying topics and subtopics covered in a single learning document. This work is part of research conducted on developing a web service for automatic semantic annotation of learning material.
New techniques to model reverberant instrument body responses

In this study we introduce new methods to design and realize computationally efficient models for musical instrument bodies. The methods take into account the time-frequency resolution of the human auditory system. First we present a method where the body response (or the low-frequency-part of it) is represented as a single digital filter structure which is known as a Kautz filter. Secondly we divide an instrument body response into lowand high-frequency parts and consider how to implement these sections more efficiently. The low-frequency region is modeled as separate modal resonances. The high-frequency part can be implemented as a reverb algorithm that is designed to match the target response both spectrally and by temporal decay based on auditory resolution criteria. The crossover frequency and the needed spectral and temporal accuracy is determined by formal listening tests. The methods are examined through case studies with guitar and violin responses.
Enhancing Traffic Intersection Control with Intelligent Objects

Traffic control is an old and ever growing problem in cities throughout the world. Within many cities, intersections represent bottlenecks in the flow of traffic. Evaluating intersections control is complex and difficult. Given this, intersection management is both costly and time consuming. This paper considers the potential benefits of enhancing the traffic intersection with the use of intelligent objects in vehicles. We present, compare and demonstrate a novel Vehicle Back-Off Protocol against a classical Timed Traffic Control system. Our protocol uses ad-ho c messaging, collision avoidance and shared journey plans as a means by which to reduce delay, adapt a journey and maximise the efficient usage of a traffic intersection. We use simulation to model and evaluate intersection control.
A New Lean Paradigm in Higher Education: A Case Study.

Purpose – This case study aims to demonstrate that lean principles and practices utilized in industry can be successfully applied to improve higher education administrative processes through an innovative and engaging learning experience involving undergraduate students.Design/methodology/approach – This is a first‐hand account by the instructor of a small group of undergraduate students in a seminar course working as a team to identify waste and redesign the university's grade change administrative process.Findings – This case study found that a small group of undergraduate students can quickly learn basic lean principles, tools and practices, and reinforce that learning by applying them in a team effort to significantly improve a university administrative process.Practical implications – With the changing higher education environment, where efficiency and effectiveness have become more imperative due to increasing budget constraints and competition for students, this case study shows that students can p.
Assessment of major and daily stressful events during adolescence: the Adolescent Perceived Events Scale.

Four studies were conducted to develop a measure of major and daily stressful events during adolescence, the Adolescent Perceived Events Scale (APES). Study I identified an item pool of events that were drawn from the open-ended reports of adolescents. In Study 2, multidimensional scaling analysis was used to identify the salient features of stressful events that were cognitively appraised by adolescents. Study 3 examined the test-retest reliability of the APES, and Study 4 examined the concurrent validity of the measure among older adolescents. Subsequent research is summarized that has shown the APES to be significantly related to behavior problems and psychological symptomatology in a wide age range of adolescents, and directions for future research are outlined. The stressful life events encountered by individuals consti
Challenging Diversity: Steering Effects of Buzzwords in Projectified Health Care

This article discusses the effects of two trends in contemporary biomedicine that have so far been largely addressed separately: the steering of fields through programmatic “buzzwords” and the projectified nature of contemporary health research, care, and promotion. Drawing on a case study of an Austrian diversity-sensitive health promotion project related to obesity prevention, we show how the articulation of these trends—governance by buzzwords and projectification—often leads to not unproblematic and often paradoxical outcomes. Buzzwords such as “diversity” become especially important in an innovation-driven environment encouraging a promissory rhetoric. At the same time, the project form shapes and restricts how buzzwords (as typically vague terms that need to be fleshed out) are articulated and translated into a specific project design. In our case study of an obesity prevention program, the need to translate diversity into a “doable” project encouraged the identification of seemingly clearly delineated target groups and thus promoted a rather narrow understanding of diversity, which stands in tension with much more fluid and context-sensitive ways of performing “diversity. ” We show how actors grapple with these paradoxes. This restricts the full power a buzzword such as diversity could achieve in terms of social justice.
Evolution of evasive malwares: A survey

The threat of malware is perpetual in digital computing systems. To counter the infection, malware industries and analysts have been coming with cutting-edge solutions and preventive measures for various categories of malware threats. At the same time malware authors are putting consistent efforts to evade security solutions and prevention systems. In this paper we will discuss about indispensable need to study and analyze the effects of evasive malwares on analysis systems. Malicious intention of malware authors can be to harm the systems without being detected such that their malware can reside into the system for longer duration. This paper discusses number of techniques which has been found in evasive malwares to elude the malware solutions. We will discuss about piles of evasive technique that might be possible in next generation malwares. Also this paper can assists to build the hardened malware analysis environments such that chances of elusion by the evasive malwares can be diminished.
Deregulation, Financial Development and Economic Growth in Mexico: Long-Term Effects and Causality

The literature on finance and economic growth establishes that a deregulated financial system increases economic growth in the long run. Mexican financial institutions have endured through two great stages: regulation until 1988 and liberalization after this date until today. Under this framework, it is investigated if in the long run financial development in Mexico has improved productive activity. Specifically, by using a cointegration model, two long-run effects are examined: 1) financial regulation has a negative effect on economic growth, and 2) financial intermediation has a positive impact on productive activity. Moreover, with a short-run causality test based on an error correction model, it is found that neither financial development nor regulation affects the dynamics of GDP; however, regulation does have a negative effect on financial development.
European Urinalysis Guidelines

Urinalysis should always be performed on the basis of medical need, and appropriate examinations for various clinical populations and presentations should be determined by cost/ bene®t analysis. On this basis, selection indications for urinalysis are suggested for detecting diseases of the kidneys or urinary tract (Page 6). The referral for detailed urine examinations should include an adequate description of the specimen type, and should inform the laboratory of the clinical need in order to facilitate correct selection of examination procedures and interpretation of results (Page 6). This medical information is mandatory when the choice is being made between minimum and optimum procedures for different specimens. The minimum information needed is outlined (Page 48). Requirements for computerized information systems are discussed (Page 49).
Using Exponential Lévy Models to Study Implied Volatility patterns for Electricity Options

German electricity European options on futures using Lévy processes for the underlying asset are examined. Implied volatility evolution, under each of the considered models, is discussed after calibrating for the Merton jump diffusion (MJD), variance gamma (VG), normal inverse Gaussian (NIG), Carr, Geman, Madan and Yor (CGMY) and the Black and Scholes (B&S) model. Implied volatility is examined for the entire sample period, revealing some curious features about market evolution, where data fitting performances of the five models are compared. It is shown that variance gamma processes provide relatively better results and that implied volatility shows significant differences through time, having increasingly evolved. Volatility changes for changed uncertainty, or else, increasing futures prices and there is evidence for the need to account for seasonality when modelling both electricity spot/futures prices and volatility. Keywords—Calibration, Electricity Markets, Implied Volatility, Lévy Models, Options on Futures, Pricing
Transport Theory for Cationic Zeolites: Diffusion of Benzene in Na-Y

We have modeled benzene diffusion in Na-Y zeolite (%:A1 = 2.0) over the temperature range 100-500 K. We apply the kinetic Monte Carlo random walk model, with activation energies derived from a new zeolitehydrocarbon potential energy surface (PES). An Arrhenius fit yields the apparent activation energy E, = 41 kJ mol-’, as compared with the previously determined experimental values 14-27 kJ mol-’. Minimum energy paths from the new PES demonstrate “cartwheel” and “skateboard” hopping mechanisms for benzene in Na-Y. Analysis of the results suggests that activation energies from long length scale diffusion measurements, e.g. pulsed field gradient NMR, should be interpreted as site-to-window activation energies, whereas those from short length scale experiments, e.g. spin-lattice relaxation NMR, correspond to intracage site-to-site activation energies. I. Introduction The structural, thermochemical, and dynamical properties of adsorbed hydrocarbons play a central role in catalytic processes that take place within the cavities of zeolites and other shapeselective, microporous catalysts. Selectivity, for example, may be strongly influenced by the diffusivities of reactant and product molecules. Computational studies have made a significant impact in this area during the last 10 years, helping to elucidate zeolite framework structure,’ hydrocarbon sorbate dynamics: and catalytic
Planning an Automated Aspect Mining Tool

Software systems are growing in size and complexity. Increased complexity often leads to decresed mainainability and bad modularity, and re-engineering tasks is often performed in order to increase the key qualities of the system. With the incentive of a growing attention to aspect-oriented programming, the eﬀorts to devise new techniques for refactoring legacy system into an aspect-oriented design have multiplied. Aspect mining tries to identify possible cross-cutting concerns in software systems and thus support this kind of refactoring. In this paper, we present a tentative approach to automated aspect mining analysis aiming at ﬁnding cross-cutting concerns that can be easily refactored to aspect-oriented artifacts.