Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding model evolution through semantically lifting model differences with SiLift

In model-based software development, models are primary artifacts which iteratively evolve and which have many versions during their lifetime. A clear representation of the changes between different versions of a model is the key to understanding and successfully managing the evolution of a model-based system. However, model comparison tools currently available display model differences on a low level of abstraction, namely in terms of basic graph operations on the abstract syntax graph of a model. These low-level model differences are often hard or even impossible to understand for normal tool users who are not familiar with meta-models. In this paper we present SiLift, a generic tool environment which is able to semantically lift low-level differences of EMF-based models into representations of user-level edit operations.
TBox Reasoning in the Probabilistic Description Logic SHIQp

One shortcoming of classic Descriptions Logics, DLs, is their inability to encode probabilistic knowledge and reason over it. This is, however, a strong demand of some modern applications, e.g. in biology and healthcare. Therefore, probabilistic extensions of DLs are attracting attention nowadays. We introduce the probabilistic DL SHIQP which extends a known probabilistic DL. We investigate two reasoning problems for TBoxes: deciding consistency and computing tight probability bounds. It turns out that both problems are not harder than reasoning in the classic counterpart SHIQ. We gain insight into complexity sources.
On Delsarte's linear programming bounds for binary codes

We prove two results about the value of Delsarte 's linear program for binary codes. Our main result is a new lower bound on the value of the program, which, in particular, is nearly tight for low rate codes. We also give an easy proof of a (known) upper bound, which coincides with the best known bound for a wide range of parameters.
Articulatory features for expressive speech synthesis

This paper describes some of the results from the project entitled “New Parameterization for Emotional Speech Synthesis” held at the Summer 2011 JHU CLSP workshop. We describe experiments on how to use articulatory features as a meaningful intermediate representation for speech synthesis. This parameterization not only allows us to reproduce natural sounding speech but also allows us to generate stylistically varying speech.
Play at Work: An Integrative Review and Agenda for Future Research

Play has gained increasing interest among progressive-minded managers as an important driver of motivation and productivity in work contexts. Despite its popularity in contemporary organizations, there is little consensus in the academic literature about the role of play in the workplace. This review organizes and synthesizes the current state of knowledge of play at work in order to gain a more comprehensive understanding of what play at work is, when individuals engage in play at work, and the effects of workplace play on work outcomes. First, we review existing definitions of play and their limitations. We then introduce a recent conceptualization of play in adulthood that defines play based on three core features and discuss its relevance in the workplace. Second, we review theoretical perspectives on play and extant empirical research on the antecedents and consequences of play at work, organizing it according to three levels of analysis. Third, we propose a promising agenda for future research by focusing on a number of important issues that have emerged from our review of existing work. These issues are organized into two sections: refining and extending the current research on play, and generating novel ideas and new research directions on unexplored areas of inquiry. We believe this review makes important and timely contributions to the research on play at work by providing comprehensive analysis of the diverse and fragmented literature on play in the workplace.
Cytoarchitectonic similarity is a wiring principle of the human connectome

Understanding the wiring diagram of the human cerebral cortex is a fundamental challenge in neuroscience. Elemental aspects of its organization remain elusive. Here we examine which structural traits of cortical regions, particularly their cytoarchitecture and thickness, relate to the existence and strength of inter-regional connections. We use the architecture data from the classic work of von Economo and Koskinas and state-of-the-art diffusion-based connectivity data from the Human Connectome Project. Our results reveal a prominent role of the cytoarchitectonic similarity of supragranular layers for predicting the existence and strength of connections. In contrast, cortical thickness similarity was not related to the existence or strength of connections. These results are in line with findings for non-human mammalian cerebral cortices, suggesting overarching wiring principles of the mammalian cerebral cortex. The results invite hypotheses about evolutionary conserved neurobiological mechanisms that give rise to the relation of cytoarchitecture and connectivity in the human cerebral cortex.
A design and evaluation of Ethernet links bundling systems

With the number of users wanting to share and access data across enterprise networks and the Internet is increasing dramatically, network administrators now find that their server and network backbones lack the capacity to handle the increased traffic. To achieve highly efficient connectivity between backbones and servers, and higher bandwidth of server network interface, we provide a method named as Ethernet links bundling technology (EIB). It is a high-speed networking solution that builds upon fast Ethernet technology to provide a dramatic increase in network performance. The implementation methods of the EIB technology are given and performance experiments are conducted. The results show that the network bandwidth can be scaled by the bundling of multiple Ethernet links and more reliable network connectivity can be guaranteed. And we also demonstrated that the EIB technology can be practically used in real applications such as FTP and SAMBA.
Intron evolution as a population-genetic process

Debate over the mechanisms responsible for the phylogenetic and genomic distribution of introns has proceeded largely without consideration of the population-genetic forces influencing the establishment and retention of novel genetic elements. However, a simple model incorporating random genetic drift and weak mutation pressure against intron-containing alleles yields predictions consistent with a diversity of observations: (i) the rarity of introns in unicellular organisms with large population sizes, and their expansion after the origin of multicellular organisms with reduced population sizes; (ii) the relationship between intron abundance and the stringency of splice-site requirements; (iii) the tendency for introns to be more numerous and longer in regions of low recombination; and (iv) the bias toward phase-0 introns. This study provides a second example of a mechanism whereby genomic complexity originates passively as a “pathological” response to small population size, and raises difficulties for the idea that ancient introns played a major role in the origin of genes by exon shuffling.
Wireless Static Hand Gesture Recognition with Accelerometers-The Acceleration Sensing Glove

Seth Hollar, John Kangchun Perng, Kristofer S. J. Pister shollar@bsac.eecs. berkeley.edu Berkeley Sensor & Actuator Center University of California, Berkeley 497 Cory Hall Berkeley, CA 94720 (510) 643-2236 Abstract A glove with six 2-axis accelerometers on the finger tips and back of the hand is demonstrated using commercial-off-the-shelf components. With an RF transmitter, the glove can act as a wireless input device to a computer. With gravity-induced acceleration offsets, we have developed a text editor where each hand gesture refers to a letter of the alphabet. Twenty-eight static hand gestures are recognizable with acquisition times of up to 1 characters/second. The glove is a prototype device for cubic millimeter systems for application on the fingernails of the user.
LEAST-SQUARES ERROR BEAMFORMING USING MINIMUM STATISTICS AND MULTICHANNEL FREQUENCY-DOMAIN ADAPTIVE FILTERING

In this paper we introduce a novel adaptive beamformer which also copes with incoherent background noise. After derivation of the optimum filter based on a weighted time-domain least-squares error criterion we present an efficient realization by applying a multichannel frequency-domain algorithm exhibiting RLS-like convergence. For the computation of this algorithm a simultaneous estimation of the power spectral density matrices of both, the noise signal and the noisy speech signal is necessary. Hence, we propose to use a novel approach based on minimum statistics to achieve this simultaneous estimation. Furthermore, the necessary estimate of a desired signal is generated by using single-channel spectral subtraction. The musical noise is avoided in our approach due to the inherent temporal and spatial averaging of our proposed beamformer. Experimental results show that the algorithm is well-suited for diffuse noise environments (e.g. car noise). Moreover, subjective listening tests confirm that a high speech quality can be obtained.
Transformation of filamentous fungi by electroporation.

Transformation systems have been reported for a number of filamentous fungi (1) based on the procedure perfected for Neurospora crassa by Case et al. employing sphaeroplasts (2). While efficient transformation is achieved with sphaeroplasts, their preparation demands a careful monitoring of the individual steps, along with optimization of conditions for each batch of cell wall-degrading enzymes. Therefore, a new efficient transformation system was developed involving direct electroporation of germinating conidia of N. crassa. Initially we employed a recombinant plasmid harboring the qa-2+ gene, encoding the catabolic dehydroquinase (2) in conjunction with a double mutant (qa-2 arom-9) recipient strain, devoid of both the biosynthetic and catabolic dehydroquinase activities. Fifteenday-old conidia were grown in 0.5 xFries' medium (3) with aromatic amino acid supplements, for 4 h at 30°C, while shaking. Germinated conidia were washed and suspended in 1 mM HEPES buffer (pH 7.0)-5O mM mannitol and 100-/il (6x 10) samples were mixed with 2 to 7 /ig of plasmid DNA and subjected to electroporation using the Bio-Rad Gene Pulser apparatus. After electroporation, 1 ml Vogel's minimal medium, Vm (3) was added and incubation resumed at 30°C for 3 h. Transformants were selected by plating on Vm-1.0% sorbose-0.1% glucose-0.1% fructose-1.5% agar.
Practical and effective symbolic analysis for buffer overflow detection

Although buffer overflow detection has been studied for more than 20 years, it is still the most common source of security vulnerabilities in systems code. Different approaches using symbolic analysis have been proposed to detect this vulnerability. However, existing symbolic analysis techniques are either too complex to scale to millions of lines of code (MLOC), or too simple to effectively handle loops and complex program structures. In this paper, we present a novel symbolic analysis algorithm for buffer overflow detection that applies simple rules to solve relevant control and data dependencies. Our approach is path-sensitive and effectively handles loops and complex program structures. Scalability is achieved by using a simple symbolic value representation, filtering out irrelevant dependencies in symbolic value computation and computing symbolic values on demand. Evaluation of our approach shows that it is both practical and effective:the analysis runs over 8.6 MLOC of the OpenSolarisTM Operating system/Networking (ON)codebase in 11 minutes and finds hundreds of buffer overflows with a false positive rate of less than 10%.
Vibration Analysis of Industrial Drive for Broken Bearing Detection Using Probabilistic Wavelet Neural Network

A reliable monitoring of industrial drives plays a vital role to prevent from the performance degradation of machinery. Today’s fault detection system mechanism uses wavelet transform for proper detection of faults, however it required more attention on detecting higher fault rates with lower execution time. Existence of faults on industrial drives leads to higher current flow rate and the broken bearing detected system determined the number of unhealthy bearings but need to develop a faster system with constant frequency domain. Vibration data acquisition was used in our proposed work to detect broken bearing faults in induction machine. To generate an effective fault detection of industrial drives, Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system was proposed in this paper. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate and execution time.
Low complexity adaptive MIMO-OFDM system for transmission under correlated frequency-selective channels

Existing works on MIMO systems have been restricted to either uncorrelated frequency-selective channels or correlated non frequency-selective channels. Practical MIMO systems however, suffers from the effects of frequency selectivity and channel correlation due to the high transmission rate and proximity of the transmit antennas. This paper presents a low complexity adaptive MIMO-OFDM system. The system exploits the time, frequency and spatial dimensions to provide high data rate and robust signal transmission in frequency selective channels with varying correlation levels. Compared to existing MIMO-OFDM systems, the proposed system provides up to 2-3 dB gains under low channel correlations and more than 5 dB gains in highly correlated channel.
Context Based Modeling of Planar Shapes

This study proposes a new way of modeling 2-dimensional shapes based on divergence matrix that captures contextual information within each shape and serves as its numerical descriptor. The framework proposes a standardized representation of shapes, based on their spatial profiles, leading to objective quantification of inter-shape likeness. When applied to real world problems, the approach leads to promising results which have 89% correlation with human judgment.
Species-Dependent Functionality of the Human Cytolytic Fusion Proteins Granzyme B-H22 (scFv) and H22

Human cytolytic fusion proteins (hCFPs) are comprised of a specific cell-surface-binding moiety and an effector molecule of human origin. In contrast to common immunotoxins, including bacterial or plant toxins, they are considered not to be immunogenic. Two examples for human pro-apoptotic effector proteins are the serine protease Granzyme B and the RNase Angiogenin. Pre-clinical testing of functionality in in vitro and in vivo studies is essential for therapeutics. Establishing relevant animal models that have predictive value for therapeutic success is a great challenge in biomedical research. In this study, we investigated the species-dependent cytotoxic activity of two hCFPs prior to their application in a murine inflammation model. We found that in vitro and ex vivo either hCFP was able to kill human cells only, leaving murine cells unaffected. In contrast, no species-dependency was found for the bacterial Pseudomonas exotoxin A based immunotoxin H22(scFv)-ETA'. This species-dependent functioning has to be
Epigenetic inactivation of RASSF1A in head and neck cancer.

PURPOSE RASSF1A, a recently identified candidate tumor suppressor gene, was found to be inactivated in lung cancer and other tumor types. We sought to understand the role of RASSF1A in head and neck cancer. EXPERIMENTAL DESIGN We analyzed the status of RASSF1A and presence of high-risk human papilloma virus (HPV) in head and neck cancer squamous cell carcinoma (HNSCC) cell lines and primary tumors. We used methylation-specific PCR to detect promoter hypermethylation and direct sequence analysis to detect point mutations in primary tumors and cell lines. 5-aza-2-deoxycytidine was used to demethylate the RASSF1A promoter in cell lines. RESULTS Promoter methylation of RASSF1A was detected in 42.9% (3 of 7) cell lines and 15% (7 of 46) primary tumors but not in the normal control DNA. Direct sequence analysis revealed a point mutation in a cell line and another in a primary HNSCC. After treatment with 5-aza-2-deoxycytidine, re-expression and demethylation of RASSF1A gene were detected in cell lines with promoter hypermethylation. HPV DNA was detected in 34.7% (16 of 46) primary HNSCC. We found a significant inverse correlation between RASSF1A promoter methylation and HPV infection (P = 0.038). CONCLUSIONS Our results suggest that RASSF1A is inactivated in a subset of HNSCC primary tumors. Moreover, an inverse correlation between RASSF1A and HPV supports a biological mechanism in which both RASSF1A promoter methylation and HPV infection abrogate the same pathway in tumorigenesis.
How teachers in different educational systems value central concepts of computer science

The 16 German states exhibit substantial differences regarding the organization as well as the substantial focus of computer science education at their schools. This empirical study investigates how teachers from two German states with different educational systems assess the value of central concepts of computer science. We asked 120 teachers in each country to complete our questionnaire, received 38 responses and applied a specific split-plot design to evaluate the results. The findings show that the assessments by the two groups differ regarding the content concepts model, system, computer, and information. Additionally, we detected differences in the rating of some individual process concepts (analyzing, classifying, finding relationships, generalizing, comparing, and ordering) in relation to the content concept model. These results are consistent with the differences in the focus of the curricula as well as with the content of the teacher education programs in the two states.
Mass-Spring Model Deformation Simulation Based on Weight Vector

Human soft tissue simulation is an important problem in computer graphics. This paper presents a human soft tissue simulation method based on mass-spring model. Applied weight vector into Euler integration method, the dynamic equation is worked out, then the process of deformation can be expressed. Experimental results show that the model creates realistic simulations and has a fast speed.
Comparative study of routing strategies in software defined networking

Conventional routing protocols such as BGP and OSPF are mature paradigm for dealing inter-domain internet routing. However, distributed nature of these protocols creates scalability, security and policy enforcement issues in Autonomous Systems. Software Defined Networks (SDN), new emerging networking concept, is seen as a solution of existing issues. In SDNs, network core is now being thought as composed of two separate planes: the control plane and the data plane. In SDN, routing is a generally implemented on the control plane in a centralized way. Information are exchanged between centralized controller and distributed data path for the calculation of routing paths and taking routing decision on the base of shared information. In this paper, we focus on the commonly used strategies for routing in SDN, in addition, we also discuss their implication in today's network.
A preference modelling approach to support intelligibility in pervasive applications

Context-aware applications do not always adapt their behaviours in ways that users expect due to a variety of reasons. Applications that lack intelligibility are often incapable of offering explanations to users as to why they decided to adapt their behaviours in certain ways, and providing feedback mechanisms for users to take control of any unwanted adaptation. This can lead to loss of user trust, satisfaction and acceptance of these applications. However, providing intelligibility and user control in applications are non-trivial; it involves exposing internal working components that influence the adaptation decisions, rendering them understandable to non-technical users, and enabling user modifications to those components to correct unexpected adaptations. This paper describes a user preference model regarding application adaptations. The goal is to support intelligibility in applications by facilitating users in generation of clear mental models that enable them to understand the links between particular contextual situations and various adaptive actions. It also aims to support user control of application behaviours by assisting developers in the creation of appropriate feedback mechanisms. These are essential in preventing user frustration at erratic application behaviours.
Neurobiology and computational structure of decision-making in addiction

An increasing wealth of experimental detail is becoming available about the development and nature of addiction. Critical issues such as the varying vulnerabilities of individuals who develop addiction are being illuminated across levels of phenomenological, psychological and neurobiological detail. Furthermore, a rich theoretical understanding is emerging in the field of neural reinforcement learning, with glimmers as to how this might be related to the subjective experience of those individuals affected. In this chapter, we consider some particuarly pressing current issues in the interface between experiment and theory, notably the so-called “compulsive” phase of drug taking.
A New Algorithm of Topical Crawler

The generic crawler provides more help to people for finding information in WWW. However, it has some drawback in terms of precision and efficiency because of its generality and no specialty. In this paper, we address two issues of the topical web crawler. One is how to make the definition of the topic; the other is how to sort of links to be downloaded in the queue efficiently. It aims to visit only relevant pages, and get a great scale of hyperlinks which link to the relevant pages. The crawl method in this paper is a novel one, which is based on the semi-structured features of the website and content information. The results of experiment show that it is a very effective method for focused crawler.