Miracle-dz/UniFAR-FTUs huggingface dataset:
Systemic Deliberation, Social Dialogue and Contractual Learning: The Case of Terminal 5

Material drawn from an in-depth case study, the construction of Terminal 5 (T5) in London’s Heathrow Airport, is deployed to examine the development and impact of learning both within and between the subsystems of corporate governance, utilities regulation, multi-firm contracting and industrial relations in large construction projects. We develop a theoretical model, drawing on systems theory, which clarifies the role played by social dialogue and deliberation in generating collective learning in the context of contractual relations. The T5 case study demonstrates how innovation in contractual design can improve performance outcomes in large, complex projects, but it also highlights the dangers of excessive reliance on formal contractual mechanisms as a solution to coordination problems, and the corresponding importance of social dialogue as a basis for learning.
Schwarzschild–anti-de Sitter black holes within isothermal cavity: Thermodynamics, phase transitions, and the Dirichlet problem

The thermodynamics of Schwarzschild black holes within spherical isothermal cavities in anti\char21{}de Sitter (AdS) space is studied for arbitrary dimensions in the semiclassical approximation of the Euclidean path integral of quantum gravity. For such boundary conditions, known classical solutions are a hot AdS and two or no Schwarzschild-AdS depending on whether or not the wall-temperature of the cavity is above or below a minimum value. Earlier work in four dimensions with such boundary conditions showed that the larger and smaller holes have positive and negative specific heats and hence are locally thermodynamically stable and unstable, respectively. The standard area-law of entropy was known to hold too. We derive the area-law for arbitrary dimensions and show that qualitative behavior of local stability remains the same. Then using a careful analysis of the associated Dirichlet boundary-value problem we address global issues. We find that for wall-temperatures above a critical value a phase transition takes hot AdS to the larger Schwarzschild-AdS. The larger hole thus can be globally thermodynamically stable. We find that the smaller the cavity the higher the critical temperature for phase transition is and it always remains above the minimum temperature needed for the classical existence of the holes in that cavity. In the infinite limit of cavity this picture reduces to that considered by Hawking and Page. All these hold for arbitrary dimensions, however the case of five dimensions turns out to be special in that the Dirichlet problem can be solved exactly giving exact analytic expressions for the black-hole masses as functions of boundary variables (cavity-radius and temperature). This makes it possible to compute the on-shell Euclidean action as a function of boundary variables too from which other quantities of interest can be evaluated. In particular, we obtain the minimum temperature (for the holes to exist classically) and the critical temperature (for phase transition) as functions of the cavity-radius in five dimensions.
A distributed, value-oriented XML store

This paper presents and evaluates XML Store, a distributed and highly scalable storage system for XML documents that builds on the Chord peer-to-peer protocol developed at MIT. The interface (API) to the storage system is simple and value-oriented, permitting no destructive updates, which permits simple solutions to replication, caching, and transaction management. Our experimental implementation of XML Store and the Chord protocol in Java performs satisfactorily and demonstrates the advantages of value-oriented programming.
Characterization of the argA Gene Required for Arginine Biosynthesis and Syringomycin Production by Pseudomonas syringae pv. syringae

ABSTRACT Two types of necrosis-inducing lipodepsipeptide toxins, called syringomycin and syringopeptin, are major virulence factors of Pseudomonas syringae pv. syringae strain B301D. A previous study showed that a locus, called syrA, was required for both syringomycin production and plant pathogenicity, and the syrA locus was speculated to encode a regulator of toxin production. In this study, sequence analysis of the 8-kb genomic DNA fragment that complements the syrA phenotype revealed high conservation among a broad spectrum of fluorescent pseudomonads. The putative protein encoded by open reading frame 4 (ORF4) (1,299 bp) in the syrA locus region exhibited 85% identity to ArgA, which is involved in arginine biosynthesis in Pseudomonas aeruginosa. Growth of strain W4S2545, the syrA mutant, required supplementation of N minimal medium with arginine. Similarly, syringomycin production of syrA mutant W4S2545 was restored by the addition of arginine to culture media. Furthermore, the insertion of Tn5 in the genome of the syrA mutant W4S2545 was localized between nucleotides 146 and 147 in ORF4, and syringomycin production was complemented in trans with the wild-type DNA fragment containing intact ORF4. These results demonstrate that the syrA locus is the argA gene of P. syringae pv. syringae and that argA is directly involved in arginine biosynthesis and therefore indirectly affects syringomycin production because of arginine deficiency.
T A New Tool for Classification of Satellite Images Available from Google Maps : Efficient Implementation in Graphics Processing Units

implementation of the k-means unsupervised clustering algorithm for commodity graphic processing units (GPUs), and further evaluate the performance of this newly developed algorithm in the task of classifying (in unsupervised fashion) satellite imagery available from Google Maps engine. With the ultimate goal of evaluating the classification precision of the newly developed algorithm, we have analyzed the consensus or agreement in the classification achieved by our implementation and an alternative implementation of the algorithm available in commercial software. Our experimental results, conducted using satellite images obtained from Google Maps engine over different locations around the Earth, indicate that the classification agreement between our parallel version and the k-means algorithm available in commercial software is very high. In addition, the GPU version (developed using the CUDA language available from NVidia TM) is much faster that the serial one (speedup above 30), thus indicating that our proposed implementation allows for larger scale processing of high-dimensional image databases such as those available in the Google Maps engine.
Control of the circular cylinder wake by Trust-Region methods and POD Reduced-Order Models

In this report we investigate the optimal control approach for the active control of the laminar circular cylinder wake flow (Re = 200). The objective is the minimization of the mean total drag where the control function is the time harmonic angular velocity of the rotating cylinder. When the Navier-Stokes equations are used as state equations, the discretization of the optimality system leads to large scale discretized optimization problems that represent a tremendous computational task. In order to reduce the number of state variables during the optimization process, a Proper Orthogonal Decomposition (POD) Reduced-Order Model (ROM) is then derived to be used as state equation. Since the range of validity of the POD ROM is generally limited to the vicinity of the design parameters in the control parameter space, we propose to use the Trust-Region Proper Orthogonal Decomposition (TRPOD) approach to update the reduced-order models during the optimization process. Benefiting from the trust-region philosophy, rigorous convergence results guarantee that the iterates produced by the TRPOD algorithm will converge to the solution of the original optimization problem defined with the Navier-Stokes equations. A lot of computational work is indeed saved because the optimization process is now based only on low order models. The key enablers to an accurate and robust POD ROM for the pressure and velocity fields are the extension of the POD basis functions to the pressure data, the introduction of eddy-viscosity estimated for each POD mode as the solution of an auxiliary optimization problem, and the inclusion of different non-equilibrium modes. When the TRPOD algorithm is applied to the wake flow configuration, this approach converges to the minimum predicted by an open-loop control approach and leads to a relative mean drag reduction of $30\%$ for reduced numerical costs.
An Interaction Network Monitor For Amoeba

The interaction network has been proposed as a way of representing interactive processing in a distributed system, and an interaction network monitor for SunOS was developed in earlier work. This paper describes development of an interaction network monitor for Amoeba, the rst interaction network monitor for a distributed operating system. Case studies are used to show some of the types of information the monitor can capture, and to show that the monitor is a valuable tool for monitoring complex modern systems.
On quark masses in holographic QCD

Recently certain nonlocal operators were proposed to provide quark masses for the holographic model of QCD developed by Sakai and Sugimoto. The properties of these operators at strong coupling are examined in detail using holographic techniques. We find the renormalization procedure for these operators is modified by the running of the five-dimensional gauge coupling. We explicitly evaluate the chiral condensate characterized by these operators.
View reconstruction for 3-D video entertainment: issues, algorithms and applications

Significant advances in stereoscopic imaging have lead to viable applications in medicine, teleoperation and in entertainment. Although the stereoscopic technology is still mostly analog, the migration to the digital domain is inevitable. Such a migration creates new challenges for stereoscopic video entertainment, but at the same time offers new opportunities. One particular challenge is the reconstruction of intermediate views (between the left and right cameras), that finds various applications. Several algorithms aiming at high-quality view reconstruction, developed at INRS, are described, and their relative merits are discussed. Since a practical implementation requires low complexity, results of a study of various models and parameters aiming at computational simplicity are reported.
Robots that Learn to Communicate: A Developmental Approach to Personally and Physically Situated Human-Robot Conversations

This paper summarizes the online machine learning method LCore, which enables robots to learn to communicate with users from scratch through verbal and behavioral interaction in the physical world. LCore combines speech, visual, and tactile information obtained through the interaction, and enables robots to learn beliefs regarding speech units, words, the concepts of objects, motions, grammar, and pragmatic and communicative capabilities. The overall belief system is represented by a dynamic graphical model in an integrated way. Experimental results show that through a small, practical number of learning episodes with a user, the robot was eventually able to understand even fragmental and ambiguous utterances, respond to them with confirmation questions and/or actions, generate directive utterances, and answer questions, appropriately for the given situation. This paper discusses the importance of a developmental approach to realize personally and physically situated human-robot conversations.
Empowerment as a Key Construct for Understanding Corporate Community Engagement

ABSTRACT This article explores the place for empowerment in community relations programs. Descriptions of 97 corporate community programs are analyzed to determine how these companies articulate community engagement and the importance given to community empowerment in their work. Empowerment is proposed as a key construct for understanding a company’s role in the community because it places the community and its members at the center of the process, and allows for the evaluation of how these programs contribute to the long-term benefit of the people who have participated in, or have been beneficiaries of, these programs.
Formation of Galactic Disk Globular Clusters in Early Dissipative Minor Merging

The origin of metal-rich, highly flattened, and rapidly rotating disk globular cluster systems in the Galaxy is one of long-standing issues in the context of the Galaxy formation. Our numerical simulations suggest a new, twofold scenario in which the disk globular clusters are first formed in the high-pressure, dense central region of a gas-rich dwarf galaxy, as induced during the tidal interaction with the pre-existing, young, thin disk of the Galaxy, and then dispersed into the disk region owing to the final tidal destruction of the merging dwarf. We also demonstrate that spatial distribution, total number, and metallicity distribution of the clusters formed in this minor merging depend on the mass ratio of the host to dwarf galaxy and the orbital configuration of merging. Based on these results, we discuss whether a minor merging event about 10 Gyr ago can explain both the Galactic thick disk and disk globular clusters. Several other implications for the possible relation between the properties of disk galaxies and their disk globular clusters are also discussed.
ENGAGE: Guided Activity-Based Gaming in Neurorehabilitation after Stroke: A Pilot Study

Introduction. Stroke is a leading cause of disability in healthy adults. The purpose of this pilot study was to assess the feasibility and outcomes of a novel video gaming repetitive practice paradigm, (ENGAGE) enhanced neurorehabilitation: guided activity-based gaming exercise. Methods. Sixteen individuals at least three months after stroke served as participants. All participants received concurrent outpatient therapy or took part in a stroke exercise class and completed at least 500 minutes of gaming. Primary baseline and posttest outcome measures included the Wolf motor function test (WMFT) and the Fugl-Meyer assessment (FMA). ENGAGE uses a game selection algorithm providing focused, graded activity-based repetitive practice that is highly individualized and directed. The Wilcoxon signed ranks test was used to determine statistical significance. Results. There were improvements in the WMFT (P = 0.003) and the FMA (P = 0.002) that exceeded established values of minimal clinically important difference. Conclusions. ENGAGE was feasible and an effective adjunct to concurrent therapy after stroke.
A general model-based slicing framework

Slicing is used to reduce the size of programs by removing those statements that do not contribute to the values of specified variables at a given program location. Slicing aids program understanding, debugging and verification. Slicing could be a useful technique to address problems arising from the size and complexity of industrial scale models; however there is no precise definition that can be used to specify a model slice. Model slices are achieved using model transformations, and since models are usually instances of multiple heterogeneous meta-models, model slicing must involve the composition of multiple transformations. This paper proposes a framework that can be used to define both program and model slicing. The framework is used to construct slices of a simple model written in a UML-like language
Successful aging and well-being: self-rated compared with Rowe and Kahn.

PURPOSE This research evaluates the utility of two different definitions of successful aging in predicting well-being. DESIGN AND METHODS We assessed the definitions of (a) self-rating and (b) Rowe and Kahn's criteria of absence of disease, disability, and risk factors; maintaining physical and mental functioning; and active engagement with life. We made associations with well-being for each definition using data from 867 Alameda County Study participants aged 65-99 years. RESULTS The percentage of those rating themselves as aging successfully was 50.3% compared with 18.8% classified according to Rowe and Kahn's criteria. Although absence of chronic conditions and maintaining functioning were positively associated with successful aging for both definitions, many participants with chronic conditions and with functional difficulties still rated themselves as aging successfully; none were so classified according to Rowe and Kahn's criteria. On 14 of 15 measures, self-rated successful aging resulted in sharper contrasts for well-being. IMPLICATIONS Understanding criteria used by older persons to assess their own successful aging should enhance the conceptualization and measurement of this elusive concept.
A Glycine-Dependent Riboswitch That Uses Cooperative Binding to Control Gene Expression

We identified a previously unknown riboswitch class in bacteria that is selectively triggered by glycine. A representative of these glycine-sensing RNAs from Bacillus subtilis operates as a rare genetic on switch for the gcvT operon, which codes for proteins that form the glycine cleavage system. Most glycine riboswitches integrate two ligand-binding domains that function cooperatively to more closely approximate a two-state genetic switch. This advanced form of riboswitch may have evolved to ensure that excess glycine is efficiently used to provide carbon flux through the citric acid cycle and maintain adequate amounts of the amino acid for protein synthesis. Thus, riboswitches perform key regulatory roles and exhibit complex performance characteristics that previously had been observed only with protein factors.
TrendTracker: Modelling the Motion of Trends in Space and Time

Both the current trends in technology such as smart phones, general mobile devices, stationary sensors and satellites as well as a new user mentality of utilizing this technology to voluntarily share information produce a huge flood of geo-textual data. Such data includes microblogging platforms such as Twitter, social networks such as Facebook, and data from news stations. Such geo-textual data allows to immediately detect and react to new and emerging trends. A trend is a set of keywords associated with a time interval where the frequency of these keywords is increased significantly. In this paper, we investigate the dissemination of trends over space and time. For this purpose, we employ a four-step framework. In the first step, we employ existing solutions to mine a large number of trends. Second, for each trend we create a spatio-temporal dissemination model, which describes the motion of this trend over space and time. To model this dissemination, we employ a (flow-source, flow-destination, time, trend) tensor. In the third step, we cluster these trend-tensors, to identify groups of archetype trends. For each archetype, we aggregate all tensors of the same archetype, and employ a tensor factorization approach to describe this archetype by its latent features. As the fourth step, we propose an algorithm which can classify the trend-archetype of a new trend, in order to predict the future dissemination of this trend. In our experiments, we are able to show that the space of trends does exhibit clusters, each corresponding to a trend-archetype such as political trends, disaster trends and celebrity trends. We show that by identifying the trend-archetype of a trend, we caneffectively predict the future of this trend.
An Unsupervised Approach to Analyze Users Opinion on Products using Customer Reviews

Opinions are very much essential for any organization’s development and success. It affects the quality of various products in a great way and will indicate how much the customer has satisfied with the product along with its strength and weakness. There are a number of ways of collecting opinions; it may be through a feedback register, or through forums and other online feedback survey facilities. The opinions are monitored and are used for improving the productivity of the product on which the opinion is received. After collecting opinions, it is important to analyze them. So we need a proper automated tool that can actually read through the comments and classify them according to the needs. The tool should be capable of going through a large set of comments in a short time and should be efficient enough to recognize almost any sentence we can throw at it.
THE UNIVERSITY OF IMICHIGAN COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING Radiation Laboratory Low Frequency Solution of Three-Dimensional Scattering Problems by RE KLEiNMAN ?

A deficiency is pointed out in Stevenson's method of reducing the solution of electromagnetic scattering problems to a succession of standard potential problems whose solutions determine terms in the low frequency expansion of the scattered field. An alternate approach is presented, for perfectly conducting scatterers, which not only removes the difficulty but also is simpler and more explicit than Stevenson's method. The details of the analogous, though simpler, scalar scattering problems are also presented.
A spherical robot based on all programmable SoC and 3-D printing

As the competition and exploration on marine is going more intense, intelligent underwater robots or autonomous underwater vehicles have become important tools to accomplish tasks such as ocean geologic survey, mineral exploration, victims rescue, military reconnaissance, etc. The mechanical structure and electronic control module design, which have long been research hotspots in this field, are in direct relation to the performance, reliability, maintainability and deployment ability of underwater robots. Existing designs commonly develop the body of robots with a large quantity of components or parts and realize information processing and motion control by using multiple kinds of electronic devices. This paper proposed a novel technical solution for underwater robots design. 3-D printing technology was adopted to construct the body of our spherical amphibious robots directly, which eliminated manufacturing difficulty, shortened the production cycle and improved water-tightness. Xilinx Zynq-7000 All Programmable SoC was used to integrate motor control, sensor management, data acquisition and other functional units or circuits into a single chip. Moreover, a universal FMC slot for high speed board and four PMod sockets for low speed modules were provided on the mother board of the electronic control module to expand functions, upgrade hardware or install scientific instruments for special missions. By introducing 3-D printing and latest SoC technologies, the system complexity of the spherical robot was significantly reduced, which improved reliability. Meanwhile, the design room for intelligent robots was broadened with modular design and all programmable SoC. The design in this paper may have reference value for multipurpose underwater robots or vehicles.
Bayesian Nonparametric Kernel-Learning

Kernel methods are ubiquitous tools in machine learning. However, there is often little reason for the common practice of selecting a kernel a priori. Even if a universal approximating kernel is selected, the quality of the finite sample estimator may be greatly affected by the choice of kernel. Furthermore, when directly applying kernel methods, one typically needs to compute a $N \times N$ Gram matrix of pairwise kernel evaluations to work with a dataset of $N$ instances. The computation of this Gram matrix precludes the direct application of kernel methods on large datasets, and makes kernel learning especially difficult. In this paper we introduce Bayesian nonparmetric kernel-learning (BaNK), a generic, data-driven framework for scalable learning of kernels. BaNK places a nonparametric prior on the spectral distribution of random frequencies allowing it to both learn kernels and scale to large datasets. We show that this framework can be used for large scale regression and classification tasks. Furthermore, we show that BaNK outperforms several other scalable approaches for kernel learning on a variety of real world datasets.