Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost Estimation in Heterogeneous Cloud Environment using Fault Tolerance Services

Clouds have emerged as a computing infrastructure that enables rapid delivery of computing resources as utility in a dynamically scalable, Virtualized manner. Cloud computing provides virtually unlimited computational resources to its users, while letting them pay only for the resources they actually use at any given time. Cloud service providers offer resources to users on demand using various pricing schemes based on ondemand instances, reserved instances and spot instances. A data center in the cloud is a large distributed computing environment consisting of heterogeneous resources. The proposed strategy improves the resource provisioning mechanisms by introducing the E-Auction in which we provide the optimal bidding mechanism by considering the workload selection in terms of jobs deadline, average CPU time consumption, job submission and job remaining time. Also, in order to optimize or minimize the cost within the performance requirement, we present the workflow optimization logics.
The effect of size of personalised menus on user satisfaction

In this paper we investigate empirically the effects of menu size on the personalisation approaches. Therefore, we investigate empirically the use of different size of five different interactive menu conditions: adaptable, adaptive split, adaptive/adaptable highlighted, adaptive/adaptable minimised and mixed-initiative menus. The aim of the study is to find out the effect of menu sized on the user satisfaction of these five menus. Results shows that in overall, in small menus, the minimised condition was the most preferable one, followed by the adaptable, and highlighted menus. By contrast, the adaptive split and mixed-initiative approach were selected as the most undesirable menus. On the other hand, in large menus, the mixed-initiative condition was the most preferable one, followed by the minimised approach. In contrast, the adaptable menu was the most unwanted menu followed by the adaptive split menu.
Constitutive Model of Rock Uniaxial Damage Based on Rock Strength Statistics

Based on the assumption that rock strength follows the log normal distribution statistically, this paper establishes a damage constitutive model of rock under uniaxial stress conditions in combination with the Mohr–Coulomb strength criterion and damage mechanical theory. Experiments were carried out to investigate the damage evolution process of rock material, which can be categorized into nondamaging, accelerated growth, constant-speed, similar growth, and speed-reducing growth stages. The evolution process had a good corresponding relationship with the rock stress-strain curves. Based on the statistical damage constitutive model proposed in this paper, a numerical fitting analysis was conducted on the uniaxial compression testing data of laboratory sand rock and on experimental data from other literature, in order to validate the rationality of the constitutive equation and the determination of its parameters and to analyze the effect of internal friction variables on damage variables and compression strength. The research outcomes presented in this paper can provide useful reference for the theory of rock mechanics and for rock engineering.
Résumé L ’ allaitement et les femmes autochtones : validation de l ’ échelle de mesure de l ’ auto-efficacité en matière d ’ allaitement , version abrégée

L’objectif de cette enquête méthodologique, qui s’inscrit dans le cadre d’une étude de cohorte prospective, est d’évaluer la fiabilité et la validité de l’échelle de mesure de l’auto-efficacité en matière d’allaitement, version abrégée (BSESSF), chez les femmes autochtones. L’échantillon est composé de 130 femmes autochtones allaitantes ayant séjourné en salle postpartum dans un hôpital de soins tertiaires urbain ou un hôpital rural. Les femmes ont fourni des renseignements de base pendant leur hospitalisation et ont été contactées par téléphone à la quatrième et à la huitième semaine postpartum afin d’évaluer leur méthode pour allaiter leur nourrisson. Selon l’enquête, la BSES-SF est un outil valide et fiable pour évaluer l’auto-efficacité chez les femmes autochtones en matière d’allaite ment. Des différences importantes ont été constatées en ce qui a trait au score de la BSES-SF en milieu hospitalier, chez les femmes qui, à quatre semaines postpartum, nourrissaient leur nourrisson exclusivement au sein, avec une méthode mixte ou uniquement au biberon (F(2) = 7,31, p = 0,001). Les auteurs concluent que les femmes autochtones affichant une faible autoefficacité en début de période postpartum risquent d’arrêter d’allaiter de façon précoce et bénéficieraient d’un soutien supplémentaire en matière d’allaitement.
The Quest for BEC

Laser cooling of atoms was suggested in the 1970’s as a way to perform better laser spectroscopy. Since it has been very successful in producing cold, dense sample of atoms it is nowadays used in many atomic physics experiments. In this lecture note we will concentrate on those techniques, that are used to cool and trap atoms to phase space densities sufficient to observe a phase transition of the atoms to a Bose-Einstein condensation.
Feedforward Strategy for High-Power Three-Phase Grid-Connected Inverters based on the Simplified Repetitive Predictor. IEEE Transactions on Power

When faced with distorted grid voltage, more harmonics will appear in the output currents of the gridconnected inverters. The grid voltage feedforward strategy, as the most direct solution to compensate the harmonics, however, is seriously affected by the errors in the grid voltage feedforward loop, such as delays. This issue is more significant for high power inverters where the switching frequency is relatively low (<5kHz), and the grid-interface inductance is small (<0.5mH). The errors mainly include the signal distortion caused by the conditioning circuits, the control delay of the digital controller, and the zero-order hold (ZOH) characteristic of pulse width modulation (PWM). In this paper, several improvements have been made to reduce the signal distortion and compensate the delays. A second-order Butterworth low-pass filter in the conditioning circuit is carefully designed with the maximum flat magnitude response and the almost linear phase response to avoid distorting the measured grid voltage. Further, based on the conventional repetitive predictor, an open-loop simplified repetitive predictor is proposed to compensate the delays in the grid voltage feedforward loop. Three predictive steps are achieved by the open-loop simplified repetitive predictor to compensate the delays: one step for the delay caused by the conditioning circuit, the second step for the control delay of the digital controller, and the third step for the ZOH characteristic of PWM. The effectiveness of the improved grid voltage feedforward strategy are experimentally validated on a 250kVA solar power generation system, where the current harmonics are effectively attenuated. In addition, the inverter starting current is suppressed.
Frailty and Loss of Rectus Femoris Muscle Thickness in Hospitalized Elderly Patients with Community-Acquired Pneumonia – A Case-Control Study

Frailty is at the core of geriatric syndromes that are characterized by multiple morbidities and mobility limitations. The purpose of this case-control study was to assess the frailty scale and muscle mass on the acute phase in hospitalized elderly patients with community-acquired pneumonia (CAP). Thirty-two elderly patients, aged 75 years or older, who were hospitalized with CAP, and 32 control patients hospitalized without CAP were recruited. Frailty scale and muscle mass were assessed using the Reported Edmonton Frail Scale (REFS) and rectus femoris (RF) thickness by ultrasound, respectively. There was a significant increase in the frequency of frailty among CAP patients (50%), compared with control patients (22%). Frailty scale correlated inversely with RF thickness and activity status. Based upon the piece-wise linear regression analysis between REFS and RF thickness decreased rapidly with the pre-frailty status among CAP patients. Elderly patients with CAP exhibit a significant impairment of activity status with frailty due to decreased thickness of RF prior to admission.
A New Feature Extraction Algorithm Based on Entropy Cloud Characteristics of Communication Signals

Identifying communication signals under low SNR environment has become more difficult due to the increasingly complex communication environment. Most relevant literatures revolve around signal recognition under stable SNR, but not applicable under time-varying SNR environment. To solve this problem, we propose a new feature extraction method based on entropy cloud characteristics of communication modulation signals. The proposed algorithm extracts the Shannon entropy and index entropy characteristics of the signals first and then effectively combines the entropy theory and cloud model theory together. Compared with traditional feature extraction methods, instability distribution characteristics of the signals’ entropy characteristics can be further extracted from cloud model’s digital characteristics under low SNR environment by the proposed algorithm, which improves the signals’ recognition effects significantly. The results from the numerical simulations show that entropy cloud feature extraction algorithm can achieve better signal recognition effects, and even when the SNR is −11 dB, the signal recognition rate can still reach 100%.
Top-down control in the Simon task

The current study used precues in a Simon task to equip subjects with information about whether the upcoming trial would be of a corresponding or noncorresponding stimulus-response (S-R) location mapping. It was hypothesized that subjects could use the information to gradually alter their stimulus processing to be faster and more accurate if the cues were valid, but that these alterations would lead to more lags and errors when cues were invalid. The results supported the hypothesis. However, control over stimulus processing in this sense was highly limited when the preceding trial had been of a noncorresponding S-R mapping. Furthermore, the results were in line with proposals of a gating mechanism in which gradual adjustments in selection of stimulus features for processing is assumed to underlie control
Recommendation algorithm based on collaborative filtering under social network environment

A collaborative recommendation algorithm based on community found is proposed in this paper. The idea of community is introduced in collaborative recommendation, at the same time the scoring pre-treatment is joined, in order to solve some problems in the traditional collaborative filtering recommendation. Results demonstrate that algorithm proposed in this paper is better than the algorithms based on the Pearson similarity and Cosine similarity.
Modelling Cash Crop Growth in TN

Driven by climate change, the climate of the 21 century may be vastly different with changes in El Niño, the jet stream, thermohaline circulation, and other climate systems causing shifts in long term climates across the globe. Given the vulnerability of soybean, corn, and cotton to such factors and their predominance in Tennessee’s agriculture, evaluating climate’s historical influence on these cash crops’ yields may provide actionable information for current and future farms and farmers. This study applies linear regression, generalized additive models (GAM), and generalized linear mixed models (GLMM) to determine crop yield responses to evaporation, precipitation, and maximum, minimum, and average temperature in Tennessee from 1947-2015. The linear models do not meet the residual independence assumption of regression due to a temporal relationship between yield and year. Next, the GAMs incorporate a smoothing factor for year but fail to remove temporal autocorrelation. Finally using Bayesian statistical inference with Markov Chain Monte Carlo(MCMC) sampling, the GLMMs incorporate an autoregressive correlation structure of the residuals. The GLMMs are the preferred and final models though software restrictions prevent their full optimization. Model validation and evaluation of chain convergence, posterior distributions, and posterior predictive checking are presented in the appendix.
North Atlantic climate variability from a self-organizing map perspective

[1] North Atlantic variability in general, and the North Atlantic Oscillation (NAO) in particular, is a long-studied, very important but still not well-understood problem in climatology. The recent trend to a higher wintertime NAO index was accompanied by an additional increase in the Azores High not coupled to changes in the Icelandic Low, as shown by a self-organizing maps (SOMs) analysis of monthly mean DJF mean sea level pressure data from 1957 to 2002. SOMs are a nonlinear tool to optimally extract a user-specified number of patterns or icons from an input data set and to uniquely relate any input data field to an icon, allowing analyses of occurrence frequencies and transitions complementary to principal component analysis (PCA). SOMs analysis of ERA-40 data finds a North Atlantic ‘‘monopole’’ roughly colocated with the mean position of the Azores High, as well as the well-known NAO dipole involving the Icelandic Low and the subtropical high. Little trend is shown in December, but the Azores High increased along with the NAO in January and February over the study interval, with implications for storminess in northwestern Europe. In short, our SOM-based analyses of winter MSLP have both confirmed prior knowledge and expanded it through the relative ease of use and power with nonlinear systems of the SOM-based approach to climatological analysis.
REDES NEURAIS ARTIFICIAIS PARA PREVISÃO DE AÇÕES DA BOLSA DE VALORES BRASILEIRA

Neste trabalho será abordado o tema de previsão de séries históricas de ações da bolsa de valores do Brasil. Sabe-se que tais séries, muitas vezes, possuem um comportamento não regular, variando bastante ao longo do tempo, devido a diversos fatores. Para tais séries históricas, os métodos tradicionais de previsão não são aconselhados, visto que na maioria das vezes não possuem comportamento de tendência e/ou sazonalidade. Para então realizar a previsão de fechamento para o próximo dia de ações financeiras, será utilizada a metodologia de Redes Neurais Artificiais, que terá como parâmetro de entrada somente os dados de fechamento dos cinco dias anteriores das ações. Para comparação dos resultados, também será aplicada a técnica de Médias Móveis Simples e será utilizada análise de erros de previsão para escolha da melhor técnica. Em alguns estudos de caso, os resultados mostram que a técnica de Redes Neurais Artificiais pode ser promissora para tal aplicação.
The swelling pressure of bentonite and sand mixtures

The compacted bentonites are used as buffer and backfill materials for engineeringbarriers for high-level nuclear waste repositories located underground. For thispurpose, it is very important to evaluate the swelling characteristics of this clay.The swelling capacity is one of the most important properties of the bentonite clay. Theswelling behaviour is due two mechanisms, the crystalline swelling and the osmoticswelling. These mechanisms produce an increase in the distance between the layers ofmontmorillonite which is one component of bentonite.The result of the swelling capacity is the swelling pressure. It has been studied inseveral investigations. The results of experimental tests have been collected andcompared in this thesis, considering only the Na-dominant bentonite and sand anddistilled water as test solution.The experimental tests show that there is only an unique relation between differentbentonites in the Na-dominant bentonite and sand mixture swollen depending on itsfinal dry density. Also, the relation between the swelling pressure and the clay voidratio shows the mechanism of the swelling pressure.On the other hand, a mechanistic model is used to predict the swelling pressure of fullysaturated bentonite and sand mixture in distilled water. Firstly, it has been comparedwith the results of experimental tests and it should be pointed out that the model givesgood predictions.In addition, the model has been used to make sensitivity analysis with differentparameters of bentonite. The most important conclusions in this section show that theswelling pressure mainly depends on the distance among particles. Also, the sensitivityanalyses indicate which parameters should be fitted more carefully for future studies tovalidate this model with different bentonites.
Inhibition of Ascorbic Acid on Lotus Rhizome Polyphenol Oxidase: Inhibition Kinetics and Computational Simulation

Polyphenol oxidase(PPO) is widely known to be involved in enzymatic browning reaction in many fruits and vegetables including lotus rhizome with different catalytic mechanisms. In this study, the inhibitory effect and mechanisms of action of ascorbic acid (AA) on the lotus rhizome PPO were investigated using inhibition kinetics and computational simulation. The lotus rhizome PPO was extracted with PBS (pH 7.0), fractionated with ammonium sulphate, concentrated, and purified with DEAE-52(2.6×30 cm) and Sephadex G-75(2.6×60 cm) chromatography. The active fractions were pooled and the PPO activity was determined to be 2627.36Units/mg. AA exhibited inhibition on lotus rhizome PPO with residual activity of 13.79% at concentration of 0.08mM and IC 50 of 0.045mM. Kinetic analyses determined by Lineweaver-Burk plots showed that ascorbic acid was reversible and competitive inhibitor to the enzyme. The 3D structure of the lotus rhizome PPO was simulated by SWISS-MODEL program and molecular docking was performed between PPO and its ligands (catehol and AA) by SYBYL-X 2.0. Simulation results showed that AA and catechol compete with the binding site of the PPO active center for its stronger affinity with the enzyme. In conclusion, the AA was established as a competitive inhibitor of lotus rhizome PPO, which provides a theoretical basis for it as an anti-browning agent in storage and preservation of lotus rhizome. Keywords: Lotus rhizome, Polyphenol oxidase, Computational simulation, Inhibition mechanism
Effect of Some Plant Essential Oils on In vitro Ruminal Methane Production and on Fermentation Characteristics of a Mid-forage Diet

The objective of the present study was to investigate the effect of different doses of some 7 natural semi-arid medicinal plants’ essential oils on in vitro ruminal digestion and fermentation patterns of a mid-forage (alfalfa hay: concentrates, 1:1) diet. Treatments consisted of either basal diet alone (control) or added with 35, 70, 140 or 280 µl L -1 of coriander, oregano, caraway, cumin, cinnamon, pistachio hull and thyme essential oils, incubated for 24 hours at 38.7oC. The essential oils of cinnamon and pistachio applied as 280 µl L -1 and thyme applied at 140 and 280 µl L -1 caused a decrease in DM disappearance as compared with control. Thyme and pistachio essential oils (used at 280 µl L -1 ) resulted in a decrease of NDF disappearance, while caraway (70 µl L -1 ) and cumin (140 µl L -1 ) resulted in an increase in it (14.8% and +18.2%, respectively). Relative to control, the essential oils applied, did not significantly affect the medium N-NH 3 concentration (except thyme at 140 and 280 µl L -1 ), pH (except thyme and cumin essential oils, 6.41 and 6.22 vs. 6.3, respectively), gas produced (except thyme at 280 µl L -1 ) and Feed Fermentation Efficiency (FFE). Relative to control, addition of all the essential oils resulted in a decrease of CP disappearance and CH 4 (except for cumin) production as Mm -1 incubated. Findings revealed that these essential oils may allow manipulation of rumen microbial fermentation.
Analysis of Trends in Emission of Criteria Air Pollutants and Human Health in an Era of Regulation

Several studies have shown the environmental and health impacts of emission of criteria air pollutants such as SO2, NOx, PM, and VOCs. These pollutants are primarily associated with acid rain, ground level ozone or smog, and formation of inhalable particulate. The present study will examine trends in emissions of these pollutants, and selected indicators of human health affected by these pollutants over the past two decades. Furthermore, the study will implement a method called linear structural relationship or causal analysis to identify the impact of factors that may affect ambient concentration of pollutants and the human health. Finally, the study will determine whether or not the changes observed over the past two decades with respect to reduction in emissions, improvements in human health indicators, and environmental expenditures are statistically significant. The study is expected to make contribution towards identification of factors or issues that policy makers and regulators should focus on and whether or not regulations have made significant difference in influencing emissions, environmental and human health risk factors.
Extended Coulomb liquid of paired hardcore boson model on a pyrochlore lattice

There is a growing interest in the $U(1)$ Coulomb liquid in both quantum materials in pyrochlore ice and cluster Mott insulators and cold atom systems. We explore a paired hardcore boson model on a pyrochlore lattice. This model is equivalent to the XYZ spin model that was proposed for rare-earth pyrochlores with "dipole-octupole" doublets. Since this model has no sign problem for quantum Monte Carlo (QMC) simulations in a large parameter regime, we carry out both analytical and QMC calculations. We find that the $U(1)$ Coulomb liquid is quite stable and spans a rather large portion of the phase diagram with boson pairing. Moreover, we numerically find thermodynamic evidence that the boson pairing could induce a possible $\mathbb{Z}_2$ liquid in the vicinity of the phase boundary between Coulomb liquid and $\mathbb{Z}_2$ symmetry-broken phase. Besides the materials' relevance with quantum spin ice, we point to quantum simulation with cold atoms on optical lattices.
THE CORPORATE GOVERNANCE DRIVERS: WHAT RELATIONS WITH PERFORMANCE AND RISK? EMPIRICAL EVIDENCE FROM ITALIAN CONTEXT

Considering a sample of Italian firms and defining a good Governance index (gGI), we investigated if there is a relation between the gGI, the performance and the default risk and which governance determinants are most responsible of these effects. To deepen the analysis, the aforementioned relations are also observed by comparing family and non-family firms and the companies more or less active in M&A. We found that the Corporate Governance quality presents some correlations with performance and risk. The non-family companies are better structured, showing a positive correlation between some Corporate Governance drivers and performance and Z-score. Furthermore, the “welladvised” firms in external strategies are able to obtain a better correlation with performance and also a good relation with Z-score****.
Corporate Brands and Social Brands: Co-Branding GM-Free and UK Supermarkets

In this paper, we introduce the concept of "social brands" and examine the potential for co-branding between corporate brands and social brands to enhance or damage the value of corporate brands. Co-branding has been theorized in terms of the relationship between the brands of organizations, products, and services. However, from a discourse perspective, issues may also be understood to function as what we term "social brands" that may be incorporated in a co-branding strategy. We deploy Leitch and Richardson's (2003) brand web model to analyze the potential benefits and dangers of forming co-branded relationships with social brands. We draw on the case of co-branding between UK supermarket brands and the GM-free social brand to investigate this relationship in practice.