Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Node Failures in Cloud Computing Using Empirical Data

Cloud has emerged as a new computing paradigm that promises to move into computing-as-utility era. Desktop Cloud is a new type of Cloud computing introduced to further achieve this ambition with an aim to reduce costs. It merges two computing models: Cloud computing and volunteer computing. The aim of Desktop Cloud is to provide Cloud services out of infrastructure that is not made for this purpose, like PCs and laptops. Such computing resources lead to a high level of volatility as a result of the fact that they can leave without prior knowledge. This paper studies the impact of node failures using evaluation metrics based on real data collected from public archive to simulate failure events in the infrastructure of a Desktop Cloud. The contribution of this paper is: (i) analysing the failure events, (ii) proposing metrics to evaluate Desktop Clouds, and (iii) evaluating several VM allocation mechanisms in the presence of node failures.
Scalable, accurate multicore simulation in the 1000-core era

We present HORNET, a parallel, highly configurable, cycle-level multicore simulator based on an ingress-queued worm-hole router NoC architecture. The parallel simulation engine offers cycle-accurate as well as periodic synchronization; while preserving functional accuracy, this permits tradeoffs between perfect timing accuracy and high speed with very good accuracy. When run on 6 separate physical cores on a single die, speedups can exceed a factor of over 5, and when run on a two-die 12-core system with 2-way hyperthreading, speedups exceed 11 ×. Most hardware parameters are configurable, including memory hierarchy, interconnect geometry, bandwidth, crossbar dimensions, and parameters driving power and thermal effects. A highly parametrized table-based NoC design allows a variety of routing and virtual channel allocation algorithms out of the box, ranging from simple DOR routing to complex Valiant, ROMM, or PROM schemes, BSOR, and adaptive routing. HORNET can run in network-only mode using synthetic traffic or traces, directly emulate a MIPS-based multicore, or function as the memory subsystem for native applications executed under the Pin instrumentation tool. HORNET is freely available under the open-source MIT license at http://csg.csail. mit.edu/hornet/.
Computational fluid dynamics in congenital heart disease*

Abstract Computational fluid dynamics has been applied to the design, refinement, and assessment of surgical procedures and medical devices. This tool calculates flow patterns and pressure changes within a virtual model of the cardiovascular system. In the field of paediatric cardiac surgery, computational fluid dynamics is being used to elucidate the optimal approach to staged reconstruction of specific defects and study the haemodynamics of the resulting anatomical configurations after reconstructive or palliative surgery. In this paper, we review the techniques and principal findings of computational fluid dynamics studies as applied to a few representative forms of congenital heart disease.
Weight loss and proteinuria: systematic review of clinical trials and comparative cohorts.

BACKGROUND Obesity is a risk factor for the progression of chronic kidney disease (CKD). The impact of weight loss on proteinuria and renal function is less clear. We aimed to determine the effect of intentional weight loss on proteinuria and kidney function. METHODS Three bibliographic databases including Medline, Cochrane and SCUPOS as well as reference list of articles were searched. We included randomized and non-randomized controlled trials as well as single-arm trials published in English through May 2009 which examined urinary protein among obese or overweight adults before and after weight loss interventions including dietary restriction, exercise, anti-obesity medications and bariatric surgery. Study characteristics and methodological quality of trials were assessed. RESULTS Five hundred twenty-two subjects from five controlled and eight uncontrolled trials were included. Weight loss interventions were associated with decreased proteinuria and microalbuminuria by 1.7 g [95% confidence interval (95% CI), 0.7 to 2.6 g] and 14 mg (95% CI, 11 to 17 mg), respectively (P < 0.05). Meta-regression showed that, independent of decline in mean arterial pressure, each 1 kg weight loss was associated with 110 mg (95% CI, 60 to 160 mg, P < 0.001) decrease in proteinuria and 1.1 mg (95% CI, 0.5 to 2.4 mg, P = 0.011) decrease in microalbuminuria, respectively. The decrease was observed across different designs and methods of weight loss. Only bariatric surgery resulted in a significant decrease in creatinine clearance. CONCLUSIONS Weight loss is associated with decreased proteinuria and microalbuminuria. There were no data evaluating the durability of this decrease or the effect of weight loss on CKD progression.
Analysis of the major factors affecting Macao's economy

As one of the few mini-economic systems in the world, Macao's economic development exhibits not only the common characteristics of the mini-economic system (e.g., sensibility to the external environment), but also its own unique characteristics (e.g., relying on the support of the mainland). Since the return of Macao to China in 1999, Macao's economy has been developing rapidly. Therefore, the influential factors that affect Macao's economy have also been changed. This paper applies the beta regression model to establish Macao's economic growth model. Based on the quarterly data of 2001~2011, this paper estimates the probability distribution of Macao's GDP growth rates. And according to the model, this paper analyzes the major factors affecting Macao's economic growth.
The role of sensation seeking and need for cognition on web-site evaluations : a resource-matching perspective

The Internet theoretically enables marketers to personalize a Website to an individual consumer. This article examines optimal Website design from the perspective of personality trait theory and resource-matching theory. The influence of two traits relevant to Internet Web-site processing—sensation seeking and need for cognition— were studied in the context of resource matching and different levels of Web-site complexity. Data were collected at two points of time: personality-trait data and a laboratory experiment using constructed Web sites. Results reveal that (a) subjects prefer Web sites of a medium level of complexity, rather than high or low complexity; (b)high sensation seekers prefer complex visual designs, and low sensation seekers simple visual designs, both in Web sites of medium complexity; and (c) high need-for-cognition subjects evaluated Web sites with high verbal and low visual complexity more favourably.
A New Mapping Method between Driver's Preference and Music Genre for Automatic Music Providing System on Vehicle

While we are driving a car, we are able to listen to musics by two ways: by selecting (manipulating) what we want and by just playing as they are given (in CD). These methods make a driver tired while he is driving or it means that a music which is provided is not concerned with a driver's preference. To improve these problems, there have been many studies about the automatic music providing systems based on driver's emotion. However, these studies have some difficult problems: the first one is that it is not easy to determine driver's emotion, and the other one is that it is hard to recommend and play the suitable music corresponding to the determined user's emotion. In this paper, to overcome the second problem mentioned above, a new mapping method between driver's emotion and music genre for automatic music providing system on vehicle is presented and two experiments are examined for the validation of the proposed method. The experimental results and discussions are explored to show the effectiveness and validity of the proposed method.
Output regulation for a class of switched stochastic delay systems based on dissipativity

In this paper, we focus on the output regulation problem with dissipative property for a class of switched stochastic delay systems via average dwell time (ADT) approach. Dissipativity reduces the conservatism by considering the energy change of external input. A auxiliary matrix is introduced to weaken the general constraint on dissipativity parameter matrixes. Less conservative conditions are established when the state is measurable and unmeasurable, respectively. Finally, one numerical example is presented to verify the feasibility and validity of our conditions.
Approach for defining relevance in the ontology-based information retrieval

One of the vital problems in the searching for information is the ranking of the retrieved results, because users make typically very short queries (2-3 terms) and tend to consider only the first ten results. In traditional IR approaches the relevance of the results is determined only by analysing the underlying information repository (content and hyperlink structure), which leads to the weak relevance model. On the other hand, in the ontology-based IR the querying process is supported by an ontology such that other important sources for determining the relevance of results can be considered: the structure of the underlying domain and the characteristics of the searching process. In this paper we present a novel approach for determining relevance in ontology-based searching for information, which exploits the "full potential" of the semantics of such a semantically-based link structure.
Profitability of Western European Banking Systems: Panel Evidence on Structural and Cyclical Determinants

This paper analyses structural and cyclical determinants of banking profitability in 16 Western European countries. We find that financial structure matters, particularly through the beneficial effect of the capital market orientation in the respective national financial system. Furthermore, higher diversification regarding banks' income sources shows a positive effect. The industry concentration of national banking systems, though, does not significantly affect aggregate profitability. Business cycle effects, in particular lagged GDP growth, display a substantial procyclical impact on bank profits. These results are obtained in a single equation panel framework using the Hausman-Taylor instrument variable estimator. The data set comprises aggregate annual country data and banking group data (commercial banks, cooperative banks and savings banks) over the period 1979-2003.
Analysis of two-dimensional and three-dimensional wakes of long circular cylinders

The wake behind a bluff body constitutes an intrinsically three-dimensional flow and it is known that two-dimensional simulations yield to an unphysical prediction of the body forces because of the nature of the two-dimensional Navier-Stokes equations. However, three-dimensional simulations are too computationally expensive for cases such as marine risers, which have very large aspect ratios and are exposed to a high Reynolds number flow. A quantitative and qualitative study has been performed to investigate the fundamental differences on the wake of two-dimensional and three-dimensional fixed spanwise periodic cylinders for a Reynolds number of 104. A very fine unifrom grid (503M points) has been used for the near and mid wake range, and it is shown that the wake presents very different vortical structures when the spanwise dimensionality is omitted. In this case, forces such as lift and drag are overpredicted. The kinetic energy spectra of the flow is also investigated to further discuss the physics inherent of each case together and it is found that the contribution of the spanwise velocity on the large wavenumbers is significantly smaller than the other velocity components.
An Optimal Approach to derive Disjunctive Positive and Negative Rules from Association Rule Mining using Genetic Algorithm

Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases. Association rule mining is one of the most important techniques of data mining that aims to induce associations among sets of items in transaction databases or other data repositories. There are various Algorithms developed and customized to derive the effective rules to improve the business. Amongst all, Apriori algorithms and FP Growth Algorithms play a vital role in finding out frequent item set and subsequently deriving rule sets based on business constraints. However there are few shortfalls in these conventional Algorithms. They are i) candidate items generation consumes lot of time in the case of large datasets ii) It supports majorly the conjunctive nature of association rules iii) The single minimum support factor not suffice to generate the effective rules iv) 'support/confident' alone not helping to validate the rules generated and v) Negative rules are not addressed effectively. Points from i) to iv) were addressed in the earlier works (10)(13) . However identifying and deriving negative rules are still a challenge. The proposed work is considered to be the extended version of our earlier work (13). It focuses how effectively negative rules can be derived with the help of logical rules sets which was not addressed in our earlier work. For this exercise the earlier work has been taken as the reference and the appropriate modifications and additions are updated into it where ever applicable. Hence by using this approach conjunctive & disjunctive; positive& negative rules can be generated effectively in an optimized manner.
BoltzRank: learning to maximize expected ranking gain

Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to optimize, as ranking performance is typically judged by metrics that are not smooth. In this paper we propose a new listwise approach to learning to rank. Our method creates a conditional probability distribution over rankings assigned to documents for a given query, which permits gradient ascent optimization of the expected value of some performance measure. The rank probabilities take the form of a Boltzmann distribution, based on an energy function that depends on a scoring function composed of individual and pairwise potentials. Including pairwise potentials is a novel contribution, allowing the model to encode regularities in the relative scores of documents; existing models assign scores at test time based only on individual documents, with no pairwise constraints between documents. Experimental results on the LETOR3.0 data set show that our method out-performs existing learning approaches to ranking.
Mirror me: Imitative responses in adults with autism

Dysfunctions of the human mirror neuron system have been postulated to underlie some deficits in autism spectrum disorders including poor imitative performance and impaired social skills. Using three reaction time experiments addressing mirror neuron system functions under simple and complex conditions, we examined 20 adult autism spectrum disorder participants and 20 healthy controls matched for age, gender and education. Participants performed simple finger-lifting movements in response to (1) biological finger and non-biological dot movement stimuli, (2) acoustic stimuli and (3) combined visual-acoustic stimuli with different contextual (compatible/incompatible) and temporal (simultaneous/asynchronous) relation. Mixed model analyses revealed slower reaction times in autism spectrum disorder. Both groups responded faster to biological compared to non-biological stimuli (Experiment 1) implying intact processing advantage for biological stimuli in autism spectrum disorder. In Experiment 3, both groups had similar ‘interference effects’ when stimuli were presented simultaneously. However, autism spectrum disorder participants had abnormally slow responses particularly when incompatible stimuli were presented consecutively. Our results suggest imitative control deficits rather than global imitative system impairments.
Parallel Evolutionary Computation in Very Large Scale Eigenvalue Problems

The history of research on eigenvalue problems is rich with many outstanding contributions. Nonetheless, the rapidly increasing size of data sets requires new algorithms for old problems in the context of extremely large matrix dimensions. This paper reports on a new method for finding eigenvalues of very large matrices by a synthesis of evolutionary computation, parallel programming, and empirical stochastic search. The direct design of our method has the added advantage that it could be adapted to extend many algorithmic variants of solutions of generalized eigenvalue problems to improve the accuracy of our algorithms. The preliminary evaluation results are encouraging and demonstrate the method's efficiency and practicality.
Differential regulation of the transcriptional repressor NRG1 accounts for altered host‐cell interactions in Candida albicans and Candida dubliniensis

Candida dubliniensis is genetically closely related to Candida albicans, but causes fewer infections in humans and exhibits reduced virulence and filamentation in animal models of infection. We investigated the role of the C. dubliniensis transcriptional repressor‐encoding gene CdNRG1 in regulating this phenotype. Deletion of both copies of CdNRG1 increased the formation of true hyphae by C. dubliniensis in response to serum, exogenous cAMP and CO2. In addition, deletion of CdNRG1 greatly enhanced filamentation and survival of C. dubliniensis in co‐culture with murine macrophages. In the reconstituted human oral epithelium infection model, the nrg1Δ mutant caused increased tissue damage relative to the wild‐type strain. However, deletion of CdNRG1 did not change the virulence of C. dubliniensis in the systemic mouse model of infection. The increased rate of hypha formation in C. albicans relative to C. dubliniensis in response to phagocytosis by macrophages and serum was associated with rapid downregulation of NRG1 expression in C. albicans. This study demonstrates that the reduced virulence and host cell damage elicited by C. dubliniensis may in part be due to the inability of this species to modulate NRG1 expression in response to the same environmental signals that promote filamentation in C. albicans.
The directionality of conversion in English : a dia-synchronic study

This book describes three of the main problems that the word-formation process known as conversion presents, namely those related to its definition, its delimitation, and its directionality. The latter constitutes, however, the main focus of the study, which is based on a corpus of over seven hundred lexical units and, more specifically, on 231 actual noun-verb conversion pairs. Considering that directionality is intrinsic to conversion, the main question is whether it is always possible to establish the direction of conversion or whether it is possible to do so only in some cases. Moreover, the study reveals what 'type' of directionality is involved, that is, whether the process is unidirectional, bidirectional or multi-directional. In order to answer these questions, both diachronic (etymology and dates of first records) and synchronic criteria (semantic dependence, restriction of usage, semantic range, semantic pattern, phonetic shape, morphologic type, stress, and the principle of relative markedness) are analysed and assessed.
Towards Omnia: A Monitoring Factory for Quality-Aware DevOps

Modern DevOps pipelines entail extreme automation and speed as paramount assets for continuous application improvement. Likewise, monitoring is required to assess the quality of service and user-experience such that applications can continuously evolve towards use-centric excellence. In this scenario however, it is increasingly difficult to pull up and maintain efficient monitoring infrastructures which are frictionless, i.e., they do not introduce any slowdown neither in the DevOps pipeline nor in the DevOps organizational and social structure comprising multiple roles and responsibilities. Using an experimental prototype, this paper elaborates Omnia an approach for structured monitoring configuration and rollout based around a monitoring factory, i.e., a re-interpretation of the factory design-pattern for building and managing ad-hoc monitoring platforms. Comparing with practitioner surveys and the state of the art, we observed that Omnia shows the promise of delivering an effective solution that tackles the steep learning curve and entry costs needed to embrace cloud monitoring and monitoring-based DevOps continuous improvement.
On the nature of the H I infrared emission lines of Scorpii

We present H ,H ei 2.058 m and 6 hydrogen Brackett and Pfund lines of Sco (B0.2V) obtained using the ground-based INT and UKIRT instruments as well as satellite data from ISO. The infrared lines all show core emission. We have investigated the formation of these lines using sophisti- cated non-LTE models. The observed emission in the most pronounced hydrogen lines, such as Br and Pf, is stronger than predicted by our models. The velocities of peak emission are blue-shifted by 5-10 kms 1 with respect to the stellar velocity. This together with the surprisingly strong width of Br and the peculiar profile of He i 2.058 suggests that shock-induced turbulent velocity fields may be present in or somewhat above the stellar photo- sphere, as has already been suggested from analysis of optical and ultraviolet data. We derive Te =3 22 kK from the infrared data alone, a value consistent with previous optical analysis. The good agreement indicates that quantitative analysis of infrared lines alone (e.g. for hot stars in regions of high extinction) can be used to characterize photospheres accurately. We also inves- tigate the mass loss of Sco and find an upper-limit of 6 10 9 Myr 1 . A parameter study of the infrared hydrogen and helium lines indicates that emission may be expected in Br and Pf for stars with Te > 16 kK and will dominate the profiles of these lines for Te > 31 and 26 kK, respectively. He i 2.058 will be in emission for 20 33 kK. The effect of surface gravity on these values is small.
Floating car and camera data fusion for non-parametric route travel time estimation

The paper proposes a non-parametric route travel time estimation method based on fusion of floating car data (FCD) and automated number plate recognition (ANPR) data. Today's traffic management utilizes heterogeneous data collection systems which can be stationary or mobile. Each data collection system has its own advantages and disadvantages. Stationary sensors usually have less measurement noise than mobile sensors but their network coverage is limited. On the other hand, mobile sensors, commonly installed in fleet vehicles, cover relatively wider areas of the network but they suffer from low penetration rate and low sampling frequency. Traffic state estimations can benefit from fusion of data collected by various sources as they complement each other. The proposed estimation method is implemented using FCD from taxis and the ANPR data from Stockholm, Sweden. The results suggest that the fusion increases the robustness of the estimation, meaning that the fused estimates are always better than the worst of the two (FCD or ANPR), and it sometimes outperforms the two single sources.