Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Framework for Enterprise Architecture Analytics

Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. This impedes the broad use of enterprise architecture methodologies. Furthermore, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. The increased availability of architectural data also improves the possibilities to verify the compliance of Enterprise Architectures. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.
Full-Length Sequence of Mouse Acupuncture-Induced 1-L (Aig1l) Gene Including Its Transcriptional Start Site

We have been investigating the molecular efficacy of electroacupuncture (EA), which is one type of acupuncture therapy. In our previous molecular biological study of acupuncture, we found an EA-induced gene, named acupuncture-induced 1-L (Aig1l), in mouse skeletal muscle. The aims of this study consisted of identification of the full-length cDNA sequence of Aig1l including the transcriptional start site, determination of the tissue distribution of Aig1l and analysis of the effect of EA on Aig1l gene expression. We determined the complete cDNA sequence including the transcriptional start site via cDNA cloning with the cap site hunting method. We then analyzed the tissue distribution of Aig1l by means of northern blot analysis and real-time quantitative polymerase chain reaction. We used the semiquantitative reverse transcriptase-polymerase chain reaction to examine the effect of EA on Aig1l gene expression. Our results showed that the complete cDNA sequence of Aig1l was 6073 bp long, and the putative protein consisted of 962 amino acids. All seven tissues that we analyzed expressed the Aig1l gene. In skeletal muscle, EA induced expression of the Aig1l gene, with high expression observed after 3 hours of EA. Our findings thus suggest that the Aig1l gene may play a key role in the molecular mechanisms of EA efficacy.
Some Topis Which Were Discussed in Greater Detail Were: Applications to Image Analysis Inverse Problems in Survival Analysis Curve Estimation under Constraints Problems in Tomography Statistical Aspects of Inverse Problems Deconvolution Techniques Algorithms for Inverse Problems

The conference was organized by F. Ruymgaart (Lubbock), W. Stute (Giessen) and Y. Vardi (New Brunswick). 43 participants attended the meeting, and 32 talks were given. The aim of the conference was to bring together experts working in the eld of inverse problems, with special emphasis on statistical methodology and applications. The unique facilities of the Oberwolfach institute provided an excellent opportunity for an exchange of ideas and signiicantly contributed to the success of the meeting.
Compact Modeling of Lateral Nonuniform Doping in High-Voltage MOSFETs

This paper reports on the detailed analysis and modeling of lateral nonuniform doping present in intrinsic MOS channel of high-voltage (HV) MOSFETs, e.g., vertical (VDMOS) and lateral diffused MOS (LDMOS). It is shown that conventional long-channel MOSFET models using uniform lateral doping can never correctly model the capacitance behavior of these devices. A new analytical compact model for lateral nonuniformly doped MOSFET is reported. The intrinsic nonuniformly doped MOS model is first validated on numerical simulation and then on measured characteristics of VDMOS and LDMOS transistors including the drift region. The model shows good results in the dc and, most importantly, in the ac regime, especially in simulating the peaks on CGD, CGS, and CGG capacitances. This new model improves the accuracy of HV MOS models, especially output characteristics and during transient response (i.e., amplitude and position of peaks, as well as slope of capacitances).
Linear Precoding Design Based on the Minimum Distance for Two-Way MIMO Physical Network Coding Systems

In this paper, we propose precoding methods for multiple input multiple output physical network coding systems, which employ the modulo operation. In our work, the transmit and receive filters are determined to maximize the minimum distance on the received constellations. Especially, to address non-concavity of the given problems, we change our problem into a concave one which can be optimized by an iterative method. Also, we propose a suboptimal non-iterative scheme whose performance is very close to the optimum iterative method. In our derivations, we prove that the modulo operation achieves the optimality in terms of the minimum distance. Finally, it is confirmed from the simulation results that the proposed systems outperform conventional schemes in terms of the error performance.
Crisis affect Chinese stock market returns ?

This paper aims at testing the influence of Subprime Crisis on Chinese stock market returns. By means of newly proposed time series spatial analysis methodology, we investigate the dominance behavior of daily returns on both Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index between before and after the crisis. Little spatial dominance could be found, even considering the appreciation of the RMB, no matter in short-term or long run investment. For rationale investors, there are no significant risk and preference changes about domestic stock market in the post Subprime Crisis era. JEL classification numbers: G01; G10; C58
Component Configuration Management

Component-based programming is nowadays widely recognized approach in software development. Still there are many open problems related to both technical and non-technical aspects of the components. In this paper, we point out the problem of component identification. Since the components are usually binary units deployed in the system at run-time, we do not have the same insight to their characteristics as for software units that we manage at development time. This problem could be solved if the components had built in this information together with the binary code, which can be achieved by defining a standardized identification interface. As such interfaces do not exist in standard component models today, this concept is possible to use only with components built in-house. For external components, extensive tests can, to some extent, compensate the lack of information. To perform an efficient and yet a successful testing we must limit the number of test cases. Which parts of our system can be affected by introduction of a component, or by its updating? We can answer this if we can keep track of changes introduced in the system and their impact on the system. These problems are similar to the problems at development-time solved by Software Configuration Management (SCM) disciplines. In this paper we point out these problems and make proposals for their utilization at run-time using SCM principles.
An Ultra-Short Dopamine Pathway Regulates Basal Ganglia Output

Substantia nigra pars reticulata (SNr) is a key basal ganglia output nucleus critical for movement control. Its GABA-containing projection neurons intermingle with nigral dopamine (DA) neuron dendrites. Here we show that SNr GABA neurons coexpress dopamine D1 and D5 receptor mRNAs and also mRNA for TRPC3 channels. Dopamine induced an inward current in these neurons and increased their firing frequency. These effects were mimicked by D1-like agonists, blocked by a D1-like antagonist. D1-like receptor blockade reduced SNr GABA neuron firing frequency and increased their firing irregularity. These D1-like effects were absent in D1 or D5 receptor knock-out mice and inhibited by intracellularly applied D1 or D5 receptor antibody. These D1-like effects were also inhibited when the tonically active TRPC3 channels were inhibited by intracellularly applied TRPC3 channel antibody. Furthermore, stimulation of DA neurons induced a direct inward current in SNr GABA neurons that was sensitive to D1-like blockade. Manipulation of DA neuron activity and DA release and inhibition of dopamine reuptake affected SNr GABA neuron activity in a D1-like receptor-dependent manner. Together, our findings indicate that dendritically released dopamine tonically excites SNr GABA neurons via D1–D5 receptor coactivation that enhances constitutively active TRPC3 channels, forming an ultra-short substantia nigra pars compacta → SNr dopamine pathway that regulates the firing intensity and pattern of these basal ganglia output neurons.
Profiling and Clustering Internet Hosts

Identifying groups of Internet hosts with a similar behavior is very useful for many applications of Internet security control, such as DDoS defense, worm and virus detection, detection of botnets, etc. There are two major difficulties for modeling host behavior correctly and efficiently: the huge number of overall entities, and the dynamics of each individual. In this paper, we present and formulate the Internet host profiling problem using the header data from public packet traces to select relevant features of frequently-seen hosts for profile creation, and using hierarchical clustering techniques on the profiles to build a dendrogram containing all the hosts. The well-known agglomerative algorithm is used to discover and combine similarly-behaved hosts into clusters, and domain-knowledge is used to analyze and evaluate clustering results. In this paper, we show the results of applying the proposed clustering approach to a data set from NLANRPMA Internet traffic archive with more than 60,000 active hosts. On this dataset, our approach successfully identifies clusters with significant and interpretable features. We next use the created host profiles to detect anomalous behavior during the Slammer worm spread. The experimental results show that our profiling and clustering approach can successfully detect Slammer outbreak and identify majority of infected hosts.
Generation of F0 contours using a model-constrained data-driven method

This paper introduces a novel model-constrained, data-driven method for generating fundamental frequency contours in Japanese text-to-speech synthesis. In the training phase, the parameters of a command-response F0 contour generation model are learned by a prediction module, which can be a neural network or a set of binary regression trees. The input features consist of linguistic information related to accentual phrases that can be automatically derived from text, such as the position of the accentual phrase in the utterance, number of morae, accent type, and parts-of-speech. In the synthesis phase, the prediction module is used to generate appropriate values of model parameters. The use of the parametric model restricts the degrees of freedom of the problem, facilitating data-driven learning. Experimental results show that the method makes it possible to generate quite natural F0 contours with a relatively small training database.
Rates of thiol-disulfide interchange reactions between mono- and dithiols and Ellman's reagent

The rate constants for thiol-disulfide interchange between 21 mono- and dithiols and Ellman's reagent correlate with the pKu's of the thiol groups with a Bronsted coefficient of p = 0.36. The maximum rates ofreduction are observed for thiols having pK, values close to the pH of the solution in which the reactions were carried out. In the dilute solutions examined (10-4-10-6 M in each reagent), the rate of the second, intramolecular interchange step in reactions of dithiols was faster than that of the first, intermolecular interchange, regardless of the size of the cyclic disulfide formed. A convenient synthesis of a mixture of diastereomers of 1,4-dimercapto-2,3-butanediol (i.e., of a mixture of dithiothreitol, DTT, and dithioerythritol, DTE) has been developed from 1,2:,4-diepoxybutane and thiolacetic acid.
A Discrete-time Observer Based on the Polynomial Approximation of the Inverse Observability Map

This paper investigates the problem of asymptotic state observation for analytic nonlinear discrete-time systems. A new technique for the observer construction, based on the Taylor polynomial approximation of the inverse of the observability map, is presented and discussed. The degree chosen for the approximation is the most important design parameter of the observer, in that it can be chosen such to ensure the convergence of the observation error at any desired exponential rate, in any prescribed convergence region (semiglobal exponential convergence).
Statin Therapy and the Development of Cerebral Amyloid Angiopathy—A Rodent in Vivo Approach

Background: Cerebral amyloid angiopathy (CAA) is characterized by vascular deposition of amyloid β (Aβ) with a higher incidence of cerebral microbleeds (cMBs) and spontaneous hemorrhage. Since statins are known for their benefit in vascular disease we tested for the effect on CAA. Methods: APP23-transgenic mice received atorvastatin-supplemented food starting at the age of eight months (n = 13), 12 months (n = 7), and 16 months (n = 6), respectively. Controls (n = 16) received standard food only. At 24 months of age cMBs were determined with T2*-weighted 9.4T magnetic resonance imaging and graded by size. Results: Control mice displayed an average of 35 ± 18.5 cMBs (mean ± standard deviation), compared to 29.3 ± 9.8 in mice with eight months (p = 0.49), 24.9 ± 21.3 with 12 months (p = 0.26), and 27.8 ± 15.4 with 16 months of atorvastatin treatment (p = 0.27). In combined analysis treated mice showed lower absolute numbers (27.4 ± 15.6, p = 0.16) compared to controls and also after adjustment for cMB size (p = 0.13). Conclusion: Despite to a non-significant trend towards fewer cMBs our results failed to provide evidence for beneficial effects of long-term atorvastatin treatment in the APP23-transgenic mouse model of CAA. A higher risk for bleeding complications was not observed.
Estimation under uncontrolled and controlled communications in Networked Control Systems

An LTI estimation framework is proposed for networked control systmes (NCS), in which local Kalman filter estimates are sent to the remote estimator. Both controlled and uncontrolled data communications are considered. For uncontrolled communication, minimum rate requirements are given for stochastic moment stability, which depend only on the least stable poles. For controlled communication. Sufficient stability conditions are formulated. The framework also makes it possible to improve the trade-off between estimation performance and communication cost.
Synthesis of Online Handwriting in Indian Languages

Synthesis of handwriting has a variety of applications including generation of personalized documents, study of writing styles, automatic generation of data for training recognizers, and matching of handwritten data for retrieval. Most of the existing algorithms for handwriting synthesis deal with English, where the spatial layout of the components are relatively simple, while the cursiveness of the script introduces many challenges. In this paper, we present a synthesis model for generating handwritten data for Indian languages, where the layout of characters is complex while the script is fundamentally non-cursive. The algorithm learns from annotated data and improves its representation with feedback.
Phos-tag analysis of Rab10 phosphorylation by LRRK2: a powerful assay for assessing kinase function and inhibitors

Autosomal dominant mutations that activate the leucine-rich repeat kinase 2 (LRRK2) cause inherited Parkinson's disease. Recent work has revealed that LRRK2 directly phosphorylates a conserved threonine/serine residue in the effector-binding switch-II motif of a number of Rab GTPase proteins, including Rab10. Here we describe a facile and robust method to assess phosphorylation of endogenous Rab10 in mouse embryonic fibroblasts (MEFs), lung and spleen-derived B-cells, based on the ability of the Phos-tag reagent to retard the electrophoretic mobility of LRRK2-phosphorylated Rab10. We exploit this assay to show that phosphorylation of Rab10 is ablated in kinase-inactive LRRK2[D2017A] knockin MEFs and mouse lung, demonstrating that LRRK2 is the major Rab10 kinase in these cells/tissue. We also establish that the Phos-tag assay can be deployed to monitor the impact that activating LRRK2 pathogenic (G2019S and R1441G) knockin mutations have on stimulating Rab10 phosphorylation. We show that upon addition of LRRK2 inhibitors, Rab10 is dephosphorylated within 1–2 min, markedly more rapidly than the Ser935 and Ser1292 biomarker sites that require 40–80 min. Furthermore, we find that phosphorylation of Rab10 is suppressed in LRRK2[S910A+S935A] knockin MEFs indicating that phosphorylation of Ser910 and Ser935 and potentially 14-3-3 binding play a role in facilitating the phosphorylation of Rab10 by LRRK2 in vivo. The Rab Phos-tag assay has the potential to significantly aid with evaluating the effect that inhibitors, mutations and other factors have on the LRRK2 signalling pathway.
Optimal Testing for Crowd Workers

Requesters on crowdsourcing platforms, such as Amazon Mechanical Turk, routinely insert gold questions to verify that a worker is diligent and is providing high-quality answers. However, there is no clear understanding of when and how many gold questions to insert. Typically, requesters mix a flat 10-30% of gold questions into the task stream of every worker. This static policy is arbitrary and wastes valuable budget --- the exact percentage is often chosen with little experimentation, and, more importantly, it does not adapt to individual workers, the current mixture of spamming vs. diligent workers, or the number of tasks workers perform before quitting. We formulate the problem of balancing between (1) testing workers to determine their accuracy and (2) actually getting work performed as a partially-observable Markov decision process (POMDP) and apply reinforcement learning to dynamically calculate the best policy. Evaluations on both synthetic data and with real Mechanical Turk workers show that our agent learns adaptive testing policies that produce up to 111% more reward than the non-adaptive policies used by most requesters. Furthermore, our method is fully automated, easy to apply, and runs mostly out of the box.
Why Have the Labour Force Participation Rates of Older Men Increased Since the Mid-1990 s ?

This paper seeks to explain the substantial increases in older men’s labour force participation rates that have been observed since the mid-1990s. Using data from the U.S. March Current Population Survey, the Canadian Labour Force Survey, and the U.K. Labour Force Survey, I investigate the hypothesis that husbands treat the leisure time of their wives as complementary to their own leisure at older ages. I exploit the cohort effects driving recent increases in older women’s participation rates to identify the effect of a wife’s participation decision on her husband’s participation decision. Given this complementarity in leisure time, a large portion of the increase in older men’s participation rates may be explained as a response to the recent increases in older women’s participation in the labour force. The methodology of Dinardo, Fortin, and Lemieux (1996) is used to decompose the changes in older married men’s participation rates, demonstrating that increases in wives’ participation in the labour force can explain roughly one quarter of the recent increase in participation in the U.S., almost one half of the recent increase in participation in Canada, and roughly one third of the recent increase in the U.K. Older men’s educational attainment is also an important factor explaining recent increases in participation, yet cannot be expected to drive further increases in participation rates. In contrast, expected increases in older wives’ participation over the next decade are expected to drive further increases in older men’s participation rates. I would like to thank Nicole Fortin, Thomas Lemieux, Kevin Milligan, and participants of the Empirical lunch series at the University of British Columbia for their comments and suggestions. Portions of the statistical analysis in this paper rely on Statistics Canada microdata, made available through the British Columbia Inter-University Research Data Centre. This study reflects the views of the author and does not reflect the views of Statistics Canada. Correspondence Tammy Schirle, Department of Economics, Wilfrid Laurier University, 75 University Ave W. , Waterloo, Ontario, Canada N2L 3C5 E-mail: tschirle@wlu.ca Tel: +1 (519) 884-0710 ext.3849
Adsorptive SPH for directable bleeding simulation

We build upon SPH to devise a directable scheme for bleeding simulation that realistically represents adherence onto and streak formation on the skin surface in real time. To ensure compatibility of expressiveness and space & time efficiency, we have judiciously designed four specific types of particles and their interactions and incorporated these elements into the SPH scheme. In-vivo particles obey a simple in-vivo blood flow model that can reflect both hemorrhage volume and blood pressure. The particles flowing out through the wound, called flow particles, manifest the primary behaviors of bleeding, including blood coagulation, blood adherence onto the skin surface, and streak formation on the skin surface. The scheme then involves transforming the flow particles adhered onto the skin surface into relatively small adhered particles and representing a thin, flat layer of adhered blood with anisotropic kernels. Guiding particles generated along user-input strokes play a distinct role in giving gravity, biased slightly by the guiding force, to the remaining flow particles and thereby allow the users to control the overall bleeding so that it follows the desirable traces.
Compressive imaging sensors

This paper describes a compressive sensing strategy developed under the Compressive Optical MONTAGE Photography Initiative. Multiplex and multi-channel measurements are generally necessary for compressive sensing. In a compressive imaging system described here, static focal plane coding is used with multiple image apertures for non-degenerate multiplexing and multiple channel sampling. According to classical analysis, one might expect the number of pixels in a reconstructed image to equal the total number of pixels across the sampling channels, but we demonstrate that the system can achieve up to 50% compression with conventional benchmarking images. In general, the compression rate depends on the compression potential of an image with respect to the coding and decoding schemes employed in the system.