Miracle-dz/UniFAR-FTUs huggingface dataset:
The 7 th International Conference on Ambient Systems , Networks and Technologies ( ANT 2016 ) Using Service Clustering and Self-Adaptive MOPSO-CD for QoS-Aware Cloud Service Selection

A promising way to effectively manage the composition of services in a heterogeneous and dynamic environment is to make workflow management able to self-adapt at runtime to react to changes in its environment by autonomously reconfiguring itself. Most of the proposed methodologies address this issue as a QoS-aware service selection problem in which a web service broker can dynamically select the ”right” service that takes part in the composition, and adaptively change the bound service when the delivered QoS has changed. In this paper, we propose a self-organizing framework that uses a service clustering based discovery approach to effectively and efficiently support the selection of services in which runtime changes in the QoS of the services are taken into account. Two bioinspired algorithms are designed to support a QoS-aware dynamic service selection mechanism. An ant-based clustering algorithm enhanced with a template mechanism that guides the artificial ants to move data items to construct and maintain a specific topology is adopted as a method for efficient service discovery. As a consequence, services can dynamically be discovered in a shorter time and with lower network traffic. To select the actual concrete services that best meet the user QoS requirements a Self-Adaptive Multi-Objective Particle Swarm Optimization Algorithm using crowding distance technique (MOPSO-CD) is executed using the topological map generated by the ant algorithm. In the end, simulation results show the effectiveness of the method proposed. c © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Conference Program Chairs.
On generating FC3 fuzzy rule systems from data using evolution strategies

Sophisticated fuzzy rule systems are supposed to be flexible, complete, consistent and compact (FC(3)). Flexibility, and consistency are essential for fuzzy systems to exhibit an excellent performance and to have a clear physical meaning, while compactness is crucial when the number of the input variables increases. However, the completeness and consistency conditions are often violated if a fuzzy system is generated from data collected from real world applications. A systematic design paradigm is proposed using evolution strategies. The structure of the fuzzy rules, which determines the compactness of the fuzzy systems, is evolved along with the parameters of the fuzzy systems. Special attention has been paid to the completeness and consistency of the rule base. The completeness is guaranteed by checking the completeness of the fuzzy partitioning of input variables and the completeness of the rule structure. An index of inconsistency is suggested with the help of a fuzzy similarity which can prevent the algorithm from generating rules that seriously contradict with each other or with the heuristic knowledge. In addition, soft T-norm and BADD defuzzification are introduced and optimized to increase the flexibility of the fuzzy system. The proposed approach is applied to the design of a distance controller for cars. It is verified that a FC(3) fuzzy system works very well both, for training and test driving situations, especially when the training data are insufficient.
IFSA: incremental feature-set augmentation for reinforcement learning tasks

Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algorithms exist to learn effective policies in such problems, learning is often used to solve real world problems, which typically have large state spaces, and therefore suffer from the "curse of dimensionality. " One effective method for speeding-up reinforcement learning algorithms is to leverage expert knowledge. In this paper, we propose a method for dynamically augmenting the agent's feature set in order to speed up value-function-based reinforcement learning. The domain expert divides the feature set into a series of subsets such that a novel problem concept can be learned from each successive subset. Domain knowledge is also used to order the feature subsets in order of their importance for learning. Our algorithm uses the ordered feature subsets to learn tasks significantly faster than if the entire feature set is used from the start. Incremental Feature-Set Augmentation (IFSA) is fully implemented and tested in three different domains: Gridworld, Blackjack and RoboCup Soccer Keepaway. All experiments show that IFSA can significantly speed up learning and motivates the applicability of this novel RL method.
Why ‘Suitable’ In Vitro Methods, as Defined in the Final EU REACH Legislation, are an Inappropriate Basis for Risk Assessment

The final text of the REACH legislation, that has recently been published by the European Parliament, and which will come into force in the middle of 2007, implies that results obtained from so-called ‘suitable’ in vitro methods could be used for testing. It is also stated that a ‘suitable’ test is one that has been deemed to be ready to enter a validation study — for example, according to criteria specified by ECVAM. It is argued that, because the wording of the legal text is too vague and imprecise, it is totally unsatisfactory, mainly because it seems to endorse the application of non-validated methods for regulatory risk assessment. While their use might be suitable for providing information for classification in a weight-of-evidence approach, setting safe dose levels should only ever be based on the use of data from a properly validated test method. This concern, and other problems raised by the final legislation, is discussed, and recommendations are made which could avoid the premature use of potentially unsuitable methods for risk assessment, whilst ensuring that potentially suitable tests can be used for this purpose, once they have been formally validated.
Novel Real-Time PCR Assay for Simultaneous Detection and Differentiation of Clostridium chauvoei and Clostridium septicum in Clostridial Myonecrosis

ABSTRACT A real-time PCR assay based on the 16S rRNA gene sequence was designed for differentiation of blackleg-causing Clostridium chauvoei and Clostridium septicum, a phylogenetically closely related bacterium responsible for malignant edema. In order to exclude false-negative results, an internal amplification control was included in the assay. A set of three probes, one specific for C. chauvoei, one specific for C. septicum, and one specific for both species, permitted unequivocal detection of C. chauvoei in tests of 32 Clostridium sp. strains and 10 non-Clostridium strains. The assay proved to be sensitive, detecting one genome of C. chauvoei or C. septicum per PCR and 1.79 × 103 C. chauvoei cells/g artificially contaminated muscle tissue. In tests of 11 clinical specimens, the real-time PCR assay yielded the same results as an established conventional PCR method.
Cognitive and Linguistic Demands of Analytic Writing.

To investigate the thinking processes students employ and the text structures they produce in analytic writing, this study contrasted eleventh grade students' analytic and summary writing. Ten high and ten average ability writers each participated in two composing-aloud sessions, writing one analytic and one summary essay based on their reading of history passages. Think-aloud protocols were divided into individual communication units, which were analyzed for three categories representing underlying features of the writing process. Essays were examined for the genre conventions governing students' writing. Multivariate analysis of variance techniques explored results of the protocol and essay analyses. In analytic writing, students employed more varied and complex thinking operations than in summary writing, asking more complicated questions, making higher-level plans, and spending more time interpreting the readings and evaluating their own essays. Results suggest ways in which writing serves as a heuristic a tool for critical thinking about subject matter. In secondary school and beyond, a considerable portion of students' writing assignments can be characterized as analytic. Ranging from interpretations of literary works to discussions of historical, social, and scientific issues, these assignments involve moving beyond summary restatement of content to more focused examination of relations among ideas and events. In high school, the most common form of analytic writing is the thesis/support essay, where students employ a pattern of generalization and supporting detail to explain a point of view (Applebee, 1984; Durst, 1984). It has become a truism in the field of composition, and a central tenet of "writing across the curriculum" advocates (Fulwiler & Young, 1982; Martin, 1984), to say that such activities help develop critical reasoning skills. Yet despite a widespread belief in the heuristic value of analytic writing, we know little about how students actually approach such tasks. Two lines of research have studied analytic writing, the first focusing on students' written texts. Britton, Burgess, Martin, McCloud, and Rosen (1975) and Applebee (1981, 1984) examined school writing using an "abstractive scale" for expository prose. At the lower end of the scale are summaries of The author would like to thank Arthur Applebee, Judith Langer, and Siusan Durst for their help with this project. Research in the Teaching of English, Vol. 21, No. 4, December 1987
On-the-fly garbage collection: an exercise in cooperation

As an example of cooperation between sequential processes with very little mutual interference despite frequent manipulations of a large shared data space, a technique is developed which allows nearly all of the activity needed for garbage detection and collection to be performed by an additional processor operating concurrently with the processor devoted to the computation proper. Exclusion and synchronization constraints have been kept as weak as could be achieved; the severe complexities engendered by doing so are illustrated.
Valproic Acid Is Not a Substrate for P-glycoprotein or Multidrug Resistance Proteins 1 and 2 in a Number of in Vitro and in Vivo Transport Assays

The antiepileptic drug valproic acid (VPA) is widely used in the treatment of epilepsy, bipolar disorders, and migraine. However, rather high doses are required for the clinical effects of VPA, which is due to its relatively inefficient delivery to the brain. The poor brain distribution of VPA is thought to reflect an asymmetric transport system at the blood-brain barrier (BBB). Based on recent data from in vitro experiments, multidrug resistance proteins (MRPs) have been proposed to be involved in the efflux transport of VPA at the BBB. In the present study, we used different experimental in vitro and in vivo strategies to evaluate whether VPA is a substrate for MRPs or the efflux transporter P-glycoprotein (Pgp). In contrast to known Pgp or MRP substrates, such as cyclosporin A or vinblastine, no directional transport of VPA was observed in cell monolayer efflux assays using the kidney cell lines Madin Darby canine kidney II and LLC-PK1, which had been transfected with either human or mouse cDNAs for the genes encoding Pgp, MRP1, or MRP2. Likewise, no indication for efflux transport of VPA was obtained in a rat microdialysis model, using inhibitors of either Pgp or MRPs. Furthermore, a significant role of MRP2 in brain efflux of VPA was excluded by using MRP2-deficient rats. Our data do not support the hypothesis that MRP1 or MRP2 is involved in the efflux of VPA from the brain. Thus, the molecular identity of the putative transporter(s) mediating the active efflux of VPA from the brain remains to be elucidated.
Evaluation of genome coverage and fidelity of multiple displacement amplification from single cells by SNP array

The scarce amount of DNA contained in a singe cell is a limiting factor for clinical application of preimplantation genetic diagnosis mainly due to the risk of misdiagnosis caused by allele dropout and the difficulty in obtaining copy number variations in all 23 pairs of chromosomes. Multiple displacement amplification (MDA) has been reported to generate large quantity of products from small amount of templates. Here, we evaluated the fidelity of whole-genome amplification MDA from single or a few cells and determined the accuracy of chromosome copy number assessment on these MDA products using an Affymetrix 10K 2.0 SNP Mapping Array. An average coverage rate (86.2%) from single cells was obtained and the rates increased significantly when five or more cells were used as templates. Higher concordance for chromosome copy number from single cells could be achieved when the MDA amplified product was used as reference (93.1%) than when gDNA used as reference (82.8%). The present study indicates that satisfactory genome coverage can be obtained from single-cell MDA which may be used for studies where only a minute amount of genetic materials is available. Clinically, MDA coupled with SNP mapping array may provide a reliable and accurate method for chromosome copy number analysis and most likely for the detection of single-gene disorders as well.
Image Registration for Video Stabilization and Motion Detection

— A hybrid image registration method to stabilize a video captured by a moving camera and facilitate tracking of moving targets in the video is introduced. The following assumptions are made: 1) The provided video contains moving targets. 2) The camera capturing the video is sufﬁciently far from the scene so that variation in scene depth across an image is negligible compared to the distance of the camera to the scene. 3) The area covered by the moving targets in an image is only a small portion of the image. Various intensity-based and feature-based registration methods are evaluated and use of geometric constraints to stabilize a video is examined. Our experimental results show that a hybrid method that uses a combination of landmarks, image intensities, and geometric constraints best registers and stabilizes a video captured by a moving camera.
Leiomyosarcoma of the anus treated with sphincter‐preserving surgery and radiation therapy

The sixth published case of a leiomyosarcoma of the anus is reported and the previous literature reviewed. Treatment with successful preservation of anal sphincter function is described. Local excision of the tumor was followed by external beam radiation therapy and an Iridium‐192 implant. The details and rationale for this mode of therapy for resectable anal tumors are discussed.
Robust Fault Estimation Using Relative Information in Linear Multi-Agent Networks

In this technical note, a robust fault estimation method, based on sliding mode observers, is proposed for a collection of agents undertaking a shared task and exchanging only relative information over a communication network. Since the `system of systems' formed by the agents is not observable with respect to relative sensing information, by appropriate transformations and scalings of the inputs and outputs of the actual system, a meaningful observable subsystem is created. For this new subsystem, after modal decomposition based on the associated Laplacian, decoupled sliding mode observers, depending only on the individual node level dynamics of the network, can be created exploiting an existing design philosophy. These collectively form a centralized fault estimation scheme for the original system.
Mycobacterium leprae fails to stimulate phagocytic cell superoxide anion generation

Mycobacterium leprae is an intracellular pathogen that is ingested by and proliferates within cells of the monocyte/macrophage series. Mechanisms by which intracellular pathogens resist destruction may involve failure to elicit a phagocyte "respiratory burst" or resistance to toxic oxygen derivatives and lysosomal enzymes. We have studied the ability of M. leprae and Mycobacterium bovis BCG to stimulate the generation of superoxide anion (O2-) in vitro by human blood neutrophils and monocytes and murine peritoneal macrophages. M. leprae bacteria failed to stimulate significant O2- release except at high bacteria-to-cell ratios (greater than 50:1) whether or not they were pretreated with normal serum or serum from patients with lepromatous leprosy. Either viable or irradiated BCG; on the other hand, stimulated the three cell types to release significant amounts of O2- when challenged with as few as 10 organisms per cell. Serum pretreatment enhanced the release of O2- by the three cell types. Preincubation for 18 h with viable M. leprae did not inhibit the ability of monocytes to respond with an oxidative burst to phagocytic stimuli. The failure of M. leprae to stimulate phagocyte O2- generation may be an important factor in its pathogenicity.
Empirical gains achievable with low altitude remote radio heads in wireless urban links

We present empirical results on the achievable gains stemming from the use of wireless remote radio heads (RRH) in a typical urban environment. Our work is based on simultaneous path-loss measurements of the base station and RRH links to outdoor street level users. We statistically characterize the increase in received power, when a RRH is added to improve the coverage achieved by a base station. We consider diverse expected coverage areas for the mobile terminal, evaluating the effect of RRH position with respect to the intended users. We also compare the power gains that would be obtained in practice from combining the signals from the base with those of the RRH, using schemes such as selection combining and maximum ratio combining. We conclude that under practical conditions, the benefits of using RRHs will depend very strongly on the existence of line-of-sight links between the RRH and the intended users. For RRHs placed at low heights, below the clutter, only users in a street-canyon position with respect to the RRH will obtain a significant benefit. Our data also shows that the gains in signal-to-noise ratio achieved when using maximum ratio combining are only marginally better than those of the much simpler selection combining.
Analyzing the citation characteristics of books: edited books, book series and types of publishers in the Book Citation Index

This paper presents a first approach to analyzing the factors that determine the citation characteristics of books. For this we use the Thomson Reuters’ Book Citation Index, a novel multidisciplinary database launched in 2010 which offers bibliometric data of books. We analyze three possible factors which are considered to affect the citation impact of books: the presence of editors, the inclusion in series and the type of publisher. Also, we focus on highly cited books to see if these factors may affect them as well. We considered as highly cited books, those in the top 5% of the most highly cited ones of the database. We define these three aspects and we present the results for four major scientific areas in order to identify field-based differences (Science, Engineering & Technology, Social Sciences and Arts & Humanities). Finally we conclude observing that differences were noted for edited books and types of publishers. Although books included in series showed higher impact in two areas.
BMAT - A Binary Matching Tool for Stale Profile Propagation

A major challenge of applying profile-based optimization on large real-world applications is how to capture adequate profile information. A large program, especially a GUI-based application, may be used in a large variety of ways by different users on different machines. Extensive collection of profile data is necessary to fully characterize this type of program behavior. Unfortunately, in a realistic software production environment, many developers and testers need fast access to the latest build, leaving little time for collecting profiles. To address this dilemma, we would like to re-use stale profile information from a prior program build. In this paper we present BMAT, a fast and effective tool that matches two versions of a binary program without knowledge of source code changes. BMAT enables the propagation of profile information from an older, extensively profiled build to a newer build, thus greatly reducing or even eliminating the need for re-profiling. We use two metrics to evaluate the quality of the results using propagated profile information: static branch prediction and the accuracy of code coverage. These metrics measure how well the matching algorithm works for the frequently executed core code and across the whole program, respectively. Experiments on a set of large DLLs from Microsoft Windows 2000 and Internet Explorer show that compared to freshly collected profiles, propagated information using BMAT is typically over 99% as effective in branch prediction and over 98% as accurate in code coverage information.
We Real Cool: Black Men and Masculinity

1. Preface: about black men: don't believe the hype 2. chapter 1: plantation patriarchy 3. chapter 2: gangsta culture: a piece of the action 4. chapter 3: schooling black men 5. chapter 4: don't make me hurt you: black male violence 6. chapter 5: it's a dick thing: beyond sexual acting out 7. chapter 6: from angry boys to angry me 8. chapter 7: waiting for daddy to come home 9. chapter 8: doing the love do 10. chapter 9: healing the hurt 11. chapter 10: the coolness of being real
The Audio Abacus: Representing a Wide Range of Values with Accuracy and Precision

Point estimation is a relatively unexplored facet of sonfication. We present a new computer application, the Audio Abacus, designed to transform numbers into tones following the analogy of an abacus. As this is an entirely novel approach to sonifying exact data values, we have begun a systematic line of investigation into the application settings that work most effectively. Results are presented for an initial study. Users were able to perform relatively well with very little practice or training, boding well for this type of display. Further investigations are planned.
On calibration of language recognition scores

Recent publications have examined the topic of calibration of confidence scores in the field of (binary-hypothesis) speaker detection. We extend this topic to the case of multiple-hypothesis language recognition. We analyze the structure of multiple-hypothesis recognition problems to show that any such problem subsumes a multitude of derived sub-problems and that therefore the calibration of all of these problems are interrelated. We propose a simple global calibration metric that can be generally applied to a multiple-hypothesis problem and then demonstrate experimentally on some NIST-LRE-'05 data how this relates to the calibration of some of the derived binary-hypotheses sub-problems
Grid Based Image Scaling Technique

The growing interest in image scaling is mainly due to the availability of digital imaging devices such as, digital video cameras, digital camcorders, 3G mobile handsets, high definition monitors etc. Scaling a digital image is a demanding and very important area of research. The grid based image scaling technique is proposed, where grid size equals the new desired dimensions of digital image. Virtually the grid is placed on the image and the intensity value of each pixel of grid is computed by taking weighted average of all intensities which are part of the imaginary pixel. The proposed grid based scaling algorithm outperforms other standard and widely used scaling techniques like linear interpolation, B-spline with order 2, B-spline with order 3. The algorithm is capable of scaling both grey-scale and color images of any resolution in any scaling factor. MSE and PSNR comparisons for down-after-up image scaling proves that the proposed technique gives better quality scaled images over other methods.