Miracle-dz/UniFAR-FTUs huggingface dataset:
A functional framework for software and system of systems method

This paper focuses on large scale application software systems based on Internet of Things and cloud computing. It proposes framework methods to further describe systems' characteristics, as well as the refinement and formalization of the abstract description. It also discusses the functional frameworks and its applications in system disintegrations, system architecture, and stable intermediate forms. It points out that the frameworks contribute to improvement of building, deployment, and maintenance of these applications.
Evaluation of enzyme-linked immunosorbent assays performed on milk and serum samples for detection of paratuberculosis in lactating dairy cows.

OBJECTIVE To determine whether results obtained for milk and serum samples with ELISAs intended for diagnosis of paratuberculosis in dairy cows were comparable to results obtained by means of mycobacterial culture of fecal samples. DESIGN Cross-sectional study. ANIMALS 689 lactating dairy cows in 9 Ontario herds. PROCEDURE Milk, serum, and fecal samples were obtained from all cows. Fecal samples were submitted for mycobacterial culture. Serum samples were tested with a commercially available ELISA for antibodies against Mycobacterium paratuberculosis, and preserved milk samples were tested with an indirect ELISA for antibodies against M paratuberculosis. RESULTS Results were positive for 130 of the 689 (18.9%) serum samples, 77 of the 689 (11.1%) milk samples, and 72 of the 689 (10.4%) fecal samples. The level of agreement between results for milk and serum samples was only moderate. Proportions of positive results for serum and fecal samples were significantly different, but proportions of positive results for milk and fecal samples were not significantly different. In addition, results for milk samples had a higher level of agreement with results of mycobacterial culture than did results for serum samples. CONCLUSIONS AND CLINICAL RELEVANCE Results suggest that the indirect ELISA used on milk samples may be a convenient method of detecting paratuberculosis in dairy herds.
Thermal properties and miscibility of semi‐crystalline and amorphous PLA blends

The focus of this research is the study of the microstructures and miscibility at the interface between semi-crystalline and amorphous PLAs [poly (l-lactic acid)(PLLA) with poly (l,d-lactic acid)(PDLLA), respectively]. The blends are prepared through thermal processing (extrusion and hot-pressing). To increase the area of interface between PDLLA and PLLA, the fibers from PLLA and PDLLA are used. Thermal and microstructures of the blends were studied by differential scanning calorimetry (DSC), polarized optical microscopy (POM), dynamic thermogravimetric analysis(DMA), small-angle X-ray diffraction(SAXS) and wide-angle X-ray diffraction (WAXD). The two PLAs are miscible in molten state. However, phase separation is detected after various thermal treatments, with PDLLA being excluded from the regions of interlamellar PLLA regions when PDLLA content is low, as determined from X-ray diffraction studies. The compatibility between the two PLAs is not perfect in the molten state, since enthalpies of the various blends at Tg are lower than any pure PLA material. The semi-crystalline PLLA fiber can recrystallize alone in the molten amorphous PDLLA, and a higher nuclei density is observed at the interface. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 41205.
Detection of Arboviruses and Other Micro-Organisms in Experimentally Infected Mosquitoes Using Massively Parallel Sequencing

Human disease incidence attributed to arbovirus infection is increasing throughout the world, with effective control interventions limited by issues of sustainability, insecticide resistance and the lack of effective vaccines. Several promising control strategies are currently under development, such as the release of mosquitoes trans-infected with virus-blocking Wolbachia bacteria. Implementation of any control program is dependent on effective virus surveillance and a thorough understanding of virus-vector interactions. Massively parallel sequencing has enormous potential for providing comprehensive genomic information that can be used to assess many aspects of arbovirus ecology, as well as to evaluate novel control strategies. To demonstrate proof-of-principle, we analyzed Aedes aegypti or Aedes albopictus experimentally infected with dengue, yellow fever or chikungunya viruses. Random amplification was used to prepare sufficient template for sequencing on the Personal Genome Machine. Viral sequences were present in all infected mosquitoes. In addition, in most cases, we were also able to identify the mosquito species and mosquito micro-organisms, including the bacterial endosymbiont Wolbachia. Importantly, naturally occurring Wolbachia strains could be differentiated from strains that had been trans-infected into the mosquito. The method allowed us to assemble near full-length viral genomes and detect other micro-organisms without prior sequence knowledge, in a single reaction. This is a step toward the application of massively parallel sequencing as an arbovirus surveillance tool. It has the potential to provide insight into virus transmission dynamics, and has applicability to the post-release monitoring of Wolbachia in mosquito populations.
On-line frame-synchronous compensation of non-stationary noise

W present a frame-synchronous noise compensation algorithm that uses a stochastic matching approach to cope with time-varying unknown noise. This method proposes to estimate a simple mapping function in parallel with Viterbi alignment. The technique is entirely general since no assumption is made on the nature, level and variation of noise. Our algorithm is evaluated on the VODIS database recorded in a moving car. For various tasks, our technique outperforms significantly classical methods. For instance, using the affine transformation the proposed algorithm gives an error rate improvement of 13.3 % compared to parallel model combination (PMC), 15.5 % on spectral subtraction (SS) and 27.8 % on frame-synchronous mean cepstre removal (MCR) for the numbers recognition task in real noise.
DiscoverHistory: understanding the past in planning and execution

We consider the problem of automated planning and control for an execution agent operating in environments that are partially-observable with deterministic exogenous events. We describe a new formalism and a new algorithm, DiscoverHistory, that enables our agent, DHAgent, to proactively expand its knowledge of the environment during execution by forming explanations that reveal information about the world. We describe how DHAgent uses this information to improve the projections made during planning. Finally, we present an ablation study that examines the impact of explanation generation on execution performance. The results of this study demonstrate that our approach significantly increases the goal achievement success rate of DHAgent against an ablated version that does not perform explanation.
Multiscale keypoint analysis with triangular biorthogonal wavelets via redundant lifting

This paper presents an efficient approach for multiscale keypoint detection based on triangular biorthogonal wavelets. The detection scheme is simple and thus fast as only three isotropic directional components of an image obtained by multiscale decomposition with the triangular biorthogonal wavelets are used for keypoint localization at each scale. Redundant lifting is also considered and can be applied directly to calculate cumulative local energy distribution that is derived from the correction of the three directional components at each scale. This gives the efficient and accurate localization of keypoints including scale information. An experimental result shows that our method is better in the sense of the uniform distribution of keypoints compared with the conventional wavelet-based approach.
Gastrointestinal tolerability of etoricoxib in rheumatoid arthritis patients: results of the etoricoxib vs diclofenac sodium gastrointestinal tolerability and effectiveness trial (EDGE-II)

Objective: A randomised, double-blind study to compare the gastrointestinal (GI) tolerability, safety and efficacy of etoricoxib and diclofenac in patients with rheumatoid arthritis (RA). Patients and methods: A total of 4086 patients (mean age 60.8 years) diagnosed with RA were enrolled and received etoricoxib 90 mg daily (n = 2032) or diclofenac 75 mg twice daily (n = 2054). Use of gastroprotective agents and low-dose aspirin was allowed. The prespecified primary end point consisted of the cumulative rate of patient discontinuations due to clinical and laboratory GI adverse experiences (AEs). General safety was also assessed, including adjudicated thrombotic cardiovascular event data. Efficacy was evaluated using the Patient Global Assessment of Disease Status (PGADS; 0–4 point scale). Results: Mean (SD; maximum) duration of treatment was 19.3 (10.3; 32.9) and 19.1 (10.4; 33.1) months in the etoricoxib and diclofenac groups, respectively. The cumulative discontinuation rate due to GI AEs was significantly lower with etoricoxib than diclofenac (5.2 vs 8.5 events per 100 patient-years, respectively; hazard ratio 0.62 (95% CI: 0.47, 0.81; p⩽0.001)). The incidence of discontinuations for hypertension-related and oedema-related AEs were significantly higher with etoricoxib (2.5% and 1.1% respectively) compared with diclofenac (1.5% and 0.4% respectively; p<0.001 for hypertension and p<0.01 for oedema). Etoricoxib and diclofenac treatment resulted in similar efficacy (PGADS mean changes from baseline −0.62 vs −0.58, respectively). Conclusions: Etoricoxib 90 mg demonstrated a significantly lower risk for discontinuing treatment due to GI AEs compared with diclofenac 150 mg. Discontinuations from renovascular AEs, although less common than discontinuations from GI AEs, were significantly higher with etoricoxib.
TR-07-16 Visualization of Cosmological Point-Based Datasets

We describe our visualization process for a particle-based simulation of the formation of the first stars and their impact on cosmic history. The dataset consists of several hundred time-steps of point simulation data, each approximately 500MB in size. For each time-step, we interpolate the point data onto a regular grid using a method taken from the radiance estimate of photon mapping[7]. We import the resulting regular grid representation into ParaView[10], with which we extract isosurfaces across multiple variables. Our images provide insights into the evolution of the early universe, tracing the cosmic transition from an initially homogeneous state to one of increasing complexity. Specifically, our visualizations capture the build-up of regions of ionized gas around the first stars, their evolution, and their complex interactions with the surrounding matter. These phenomena were not clearly visible with other visualization techniques. These observations will guide the upcoming James Webb Space Telescope, the key astronomy mission of the next decade.
Fuzzy Brain Emotional Cerebellar Model Articulation Control System Design for Multi-Input Multi-Output Nonlinear

A brain emotional cerebellar model articulation controller (BECMAC) is developed, which is a mathematical model that approximates the judgmental and emotional activity of a brain. A fuzzy inference system is incorporated into the BECMAC, to give the novel fuzzy brain emotional cerebellar model articulation controller (FBECMAC) that is also proposed in this paper. The developed FBECMAC has the benefit of fuzzy inference and judgment and emotional activity, and it is used to control multi-input multi-output nonlinear systems. A 3-dimensional (3D) chaotic system and a mass spring damper mechanical system are simulated, to illustrate the effectiveness of the proposed control method. A comparison between the proposed FBECMAC and other controller shows that the proposed controller exercises better control than the other controllers.
Real-time method for counting unseen stacked objects in mobile

A novel method that automatically counts number of objects piled or stacked to each other in mobile device image is proposed. Distinct from other methods, the proposed method automatically determines the size and shape and detects the template of unknown to-be-counted objects. Such template is then used to perform fast template matching all over the input image to count the number of the same objects. The similarity function for determining the detected object has been proposed. The evaluation on speed and accuracy was performed by testing on images of various construction materials captured from on real site by the Android smart phone. The result suggests that the proposed method outperforms all baselines including the recent lattice detection based approach. The computation time is sufficiently fast for real-time use in mobile devices. It can also efficiently deal with the problem of information loss (i.e., lost edges) due to various unpredicted lighting condition. In term of time, the comparison of counting time was also done between the method and human.
The effect of background cuing on prey detection

Studies of prey detection have typically focused on how search image affects the capture of cryptic items. This study also considers how background vegetation influences cryptic prey detection. Blue jays, Cyanocitta cristata, searched digitized images for two Catocala moths: C. ilia, which is cryptic on oak, and C. relicta, which is cryptic on birch. Some images contained moths while others did not. The ability of blue jays to detect prey during repeated presentations of one prey type within a session was compared with their performance during randomly alternating presentations of both prey types within a session to examine search-image formation under two background conditions (informative and ambiguous). In the informative background condition, both trees in the image were of the same species and therefore, the background was a reliable indicator of which prey type might be present. In the ambiguous background condition, there was one tree of each species in the image and either prey type could be present. The results indicate that: (1) a search-image effect was observed only for the more cryptic prey type and only when the background was informative; (2) as accuracy on prey images (those with moths) increased, response latency remained unchanged; (3) performance on nonprey images (those without moths) was primarily determined by the difficulty of searching the background and not by the prey type in the accompanying prey images; and (4) search-image effects disappeared with extended practice. These results suggest that the ability to detect prey is influenced by background and that the presence of either multiple backgrounds or multiple prey types interferes with search-image formation. Copyright 1998 The Association for the Study of Animal Behaviour.
In-network cooperative spectrum sensing

This paper proposes a distributed average consensus algorithm in order to solve the cooperative spectrum sensing task without a cognitive base station. The proposed consensus algorithm converges to the optimal decision statistic in the limit. Since in practice the iteration number has to be finite, we derive high probability bounds on the iteration number at which all the CRs are at most ε away from the optimal decision statistic. Moreover, we compute the performance characteristics of the proposed in-network cooperative spectrum sensing at a given iteration.
Centrality Measures for Non-Contextual Graph-Based Unsupervised Single Document Keyword Extraction

The manner in which keywords fulfill the role of being central to a document is frustratingly still an open question. In this paper, we hope to shed some light on the essence of keywords in scientific articles and thereby motivate the graph-based approach to keyword extraction. We identify the document model captured by the text graph generated as input to a number of centrality metrics, and overview what these metrics say about keywords. In doing so, we achieve state-of-the-art results in unsupervised non-contextual single document keyword extraction. In this paper, we present a study on the essence of keywords in scientific articles and thereby motivate the graph-based approach to keyword extraction. We identify the document model captured by the text graph generated as input to a number of centrality metrics, and overview what these metrics say about keywords. In doing so, we achieve state-of- the-art results in non-contextual single document keyword extraction for the Inspec corpus, an NDCG score of 0.07578 ; we can affirm this, because the systems we compare here in terms of NDCG include re-implementations of the previous state-of-the-art. We identify two broad types of single document keyword extraction (SDKE). Contextual SDKE makes use of the document set to which the relevant document belongs, and in which there are similar documents ; other information outside of the document set may also be used in some types of contextual SDKE. Non-contextual SDKE makes use of only the relevant document with no other information. The latter does not necessarily make the assumption of independence of documents in general. Non-contextual SDKE is actually important for the case of isolated documents (not part of a document set), as well as for documents for which relevant supplementary information may be non-existent or unreliable. In addition, the study of non-contextual SDKE is a study of baselines in keyword extraction : before constructing complex methods using more information, it is important to understand what we can achieve with the document alone.
Information System Success: Individual and Organizational Determinants1

1 : We are grateful to the Associate Editor, the four anonymous reviewers, and the Department Editor for their insightful comments on previous versions of the paper. Their comments have been very helpful in improving the paper. The paper has also benefited from several suggestions the first author received from Abstract Despite considerable empirical research, results on the relationships among constructs related to information system (IS) success, as well as the determinants of IS success, are often inconsistent. A comprehensive understanding of IS success thus remains elusive. In an attempt to address this situation, which may partly be due to the exclusion of potentially important constructs from prior parsimonious models of IS success, we present and test a comprehensive theoretical model. This model explains interrelationships among four constructs representing the success of a specific information system (user satisfaction, system use, perceived usefulness, system quality), and the relationships of these IS success constructs with four user-related constructs (user experience with ISs, user training in ISs, user attitude towards ISs, and user participation in the development of the specific IS) and two constructs representing the context (top-management support for ISs and facilitating conditions for ISs). To test the model, we first used meta-analysis to compute a correlation matrix for the constructs in the model based on 612 findings from 121 studies published between 1980 and 2004, and then used this correlation matrix as input for a LISREL analysis of the model. Overall, we found excellent support for the theoretical model. The results underline the importance of user-related and contextual attributes in IS success and raise questions about some commonly believed relationships.
Green Resources, Environmental Technology Innovation and the Green Firm-Specific Advantage of High-Carbon Enterprises

This paper explains the mechanism that environmental technology innovation influences the green firm-specific advantage of high-carbon enterprises. The empirical analysis illustrates that green resources have a significant effect on the green firm-specific advantage of high-carbon enterprises, the relationship between green resources and green firm-specific advantage is partly mediated by environmental technology innovation, and the relationship between environmental technology innovation and green firm-specific advantage is partly mediated by environmental legitimacy.
Efficient Implementation of the K-SVD Algorithm using Batch Orthogonal Matching Pursuit

The K-SVD algorithm is a highly efiective method of training overcomplete dictionaries for sparse signal representation. In this report we discuss an e‐cient implementation of this algorithm, which both accelerates it and reduces its memory consumption. The two basic components of our implementation are the replacement of the exact SVD computation with a much quicker approximation, and the use of the Batch-OMP method for performing the sparse-coding operations. Batch-OMP, which we also present in this report, is an implementation of the Orthogonal Matching Pursuit (OMP) algorithm which is speciflcally optimized for sparse-coding large sets of signals over the same dictionary. The Batch-OMP implementation is useful for a variety of sparsity-based techniques which involve coding large numbers of signals. In the report, we discuss the Batch-OMP and K-SVD implementations and analyze their complexities. The report is accompanied by Matlab r toolboxes which implement these techniques, and can be downloaded at http://www.cs. technion.ac. il/~ronrubin/software.html.
The Precision of Single Neuron Responses in Cortical Area V1 during Stereoscopic Depth Judgments

The performance of single neurons in cortical area V1 of alert macaque monkeys was compared against the animals' psychophysical performance during a binocular disparity discrimination task. Performance was assessed with stimuli that consisted of a patch of dynamic random dots, whose disparity varied from trial to trial, surrounded by an annulus of similar dots at a fixed disparity. On each trial, the animals indicated whether the depth of the central patch was in front of or behind the annulus. For each disparity of the center patch, neural performance was assessed by calculating the probability that the response of the neuron was greater or less than the response when the center disparity was the same as that of the annulus. Initially the animals performed the task simultaneously with the neural recording. However, the range of disparities used, which was appropriate for the neuronal recording, may have affected performance, because the thresholds were substantially lower (2.6×) when the psychophysical measurements were repeated later. Average neuronal thresholds were ∼4× poorer than these behavioral thresholds, although the best neurons were marginally better than the animals' behavior. Thus, the well known precision of relative depth judgments can be supported with signals from a small number of V1 neurons. Interference with the relative depth information in the stimulus profoundly affected behavioral thresholds, which were ∼10× poorer when the surround was absent or contained binocularly uncorrelated dots. In this case, single V1 neurons consistently outperform the observer: presumably here, psychophysical thresholds are limited by other factors (such as uncertainty about vergence eye position).
Myosin VI lever arm rotation: Fixed or variable?

Two recent articles addressed the power-stroke of myosin VI molecules during stepping. Although both groups measured the angles of fluorescent probes attached on the myosin VI molecule lever arm using polarized fluorescence techniques, they differ about whether the myosin VI lever arm rotation is fixed1 or variable2. Here we discuss the causes of the discrepancy between the two studies and the implications for myosin VI processive motility.