Miracle-dz/UniFAR-FTUs huggingface dataset:
BROKER BASED QoS CENTRIC RESOURCE PROVISIONING FRAMEWORK WITH FINANCIAL OPTIONS

Cloud computing has grasped the attention of scientific community and business industry towards the provisioning of computing resources as a utility and software as a service over a network. Access to software or hardware resources are seamless to cloud consumers in a way that provider of the service could be anywhere in the world by providing services in nebulous cloud. Most of the research studies have focused on the benefits associated with single cloud provider by provisioning and managing resources at provider’s end. This has led to the problems associated with pricing and quality of the services that cloud provider guarantees in SLA to their consumers. To tackle this issue, financial options theory in cloud computing economics has been introduced in the recent past where options can be bought in advance so that these may be utilized when required. However, QoS factors, that are vital for a cloud provider in order to accommodate cloud consumer trust, are not yet been addressed. We propose a federated cloud resource provisioning framework based on financial options theory to address the issue of job denial during peaks by leasing spare capacity from other cloud providers as well as satisfying cost and QoS requirements. We assess cloud providers based on the services they provide and best-fit selection is made while purchasing options to meet service level objectives. Also the issue of VM placement across multiple clouds is addressed to provide a resource sharing platform where the objectives of avoiding resource rejection and efficient service level agreement management are incorporated in the proposed framework. Using CloudSim simulator, various workloads were used to test our proposed framework. Results indicate that our broker based cloud federation framework provides a win-win scenario for both cloud providers and consumers by avoiding job denial and achieving better SLA management and resource utilization.
Dips in the diffuse supernova neutrino background

Scalar (fermion) dark matter with mass in the MeV range coupled to ordinary neutrinos and another fermion (scalar) is motivated by scenarios that establish a link between radiatively generated neutrino masses and the dark matter relic density. With such a coupling, cosmic supernova neutrinos, on their way to us, could resonantly interact with the background dark matter particles, giving rise to a dip in their redshift-integrated spectra. Current and future neutrino detectors, such as Super-Kamiokande, LENA and Hyper-Kamiokande, could be able to detect this distortion.
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As the Internet of Things (IoT) continues to proliferate, diagnosing incorrect behavior within increasinglyautomated homes becomes considerably more difficult. Devices and apps may be chained together in long sequences of triggeraction rules to the point that from an observable symptom (e.g., an unlocked door) it may be impossible to identify the distantly removed root cause (e.g., a malicious app). This is because, at present, IoT audit logs are siloed on individual devices, and hence cannot be used to reconstruct the causal relationships of complex workflows. In this work, we present ProvThings, a platform-centric approach to centralized auditing in the Internet of Things. ProvThings performs efficient automated instrumentation of IoT apps and device APIs in order to generate data provenance that provides a holistic explanation of system activities, including malicious behaviors. We prototype ProvThings for the Samsung SmartThings platform, and benchmark the efficacy of our approach against a corpus of 26 IoT attacks. Through the introduction of a selective code instrumentation optimization, we demonstrate in evaluation that ProvThings imposes just 5% overhead on physical IoT devices while enabling real time querying of system behaviors, and further consider how ProvThings can be leveraged to meet the needs of a variety of stakeholders in the IoT ecosystem.
Tackling the Problem of Self Selection in the Integration of Different Data Collection Techniques.

A lot of studies are showing an increased tendency to use more than one mode of administration to collect data for a particular analysis ([10];[1];[16];[9]). Thus, understand if different data collection methods influence answers becomes a concern. The problem of self selection into different interview modes demands attention especially when the assignment to one or another collection method is not randomly controlled and respondents might self select in one data collection method over another. This paper shows an empirical case concerning the evalua- tion of two different data collection method: the CAWI (Computer Assisted Web Interview) method and the CATI (Computer Assisted Telephone Interview) method. If self-selection exists both mode of data collection and characteristics of the re- spondents influence answers. Hence, the mode effect may be confounded. In order to estimate an unbiased mode effect, this paper proposes a data driven multivariate approach to monitor self-selection that allows to disentangle interview’s modes ef- fects on answers from the effect of self-selection. We will work through the use of the monitoring system with an empirical case. In particular, we will use AlmaLaurea data and compare results of our approach to PS adjustment method that AlmaLaurea usually applies to control data quality as documented in various reports and analysis conducted by the AlmaLaurea Consortium .
Profiling farm systems according to their sustainable performance: the Irish livestock sector

Sustainable farming systems are those that are economically profitable, environmentally protective and socially efficient through time, therefor the importance of farm sustainable performance is highly acknowledged, and there are various methods for its measurement and assessment at different spatial levels. The aim of this study is to profile and classify Irish livestock farms according to their performance using farm-level data on profitability, environmental efficiency and social integration derived from the Teagasc National Farm Survey. In contrast to previous research that assesses Irish farms’ sustainable performance at farm level, this study is attempting to create a farm system typology based on farm performance and characteristics. Economic, social and environmental performance indicators are determined and aggregated to be used as the conceptual framework to identify and classify types of farms. A combination of multivariate analysis techniques is developed for the aggregation of indicators and for the creation of farm systems typologies. The results indicate the relation between economic, ecological and social performance of Irish farms and establish a typology of livestock farms that can prove useful for future policy design.
The Relative Importance of Luck and Technical Efficiency in a Fishery

The study of productive efficiency has not been a traditional field of research in fisheries economics. However, recent papers have dealt with testing what it is known as “the good captain hypothesis”, according to which differences in catches among vessels can be explained in terms of skipper skill (efficiency). These papers introduce an interesting research issue: the distinction between luck and efficiency. In this paper we try to shed more light on this topic using a panel dataset on the hake fishery in Northern Spain. In particular, we are interested in separating efficiency not only from luck but also from other time invariant variables, such as vessel characteristics, which sometimes are confounded with efficiency. In contrast to the other papers that deal with this topic, we find that luck is more important than technical efficiency in explaining catches. We argue this can be explained by the fact that other papers use data at a higher level of temporal aggregation. Over longer periods of time, skill persists while luck averages away.
Efficient Compression of Video using Distributed Source Coding

Current video standards based on the principle of predictive coding exploits temporal redundancy between the adjacent frames. Although such schemes promise good rate-distortion performance, encoder complexity is much higher. This paper looks into a new video paradigm based on principle of distributed source coding which supports a simple low complexity encoder by shifting the complexity to the decoder. Such a codec attempts to achieve the compression efficiency of interframe coding. This paper presents some simulation results of a video codec working on the principles of distributed source coding.
Canopy traits in rye , triticale and wheat under varying N supply

Information on growth of rye (Secale cereale L.) and triticale (X Triticosecale Wittmark) are scarce. In 2007/08 and 2008/09, winter rye, winter triticale and winter wheat (Triticum aestivum L.) were simultaneously grown in combination with 4 nitrogen (N) treatments (0/0, 40/40, 80/80 and 120/120 kg N ha) at the Hohenschulen Experimental Farm in northern Germany allowing for a comparison of the resource capture and biomass accumulation during spring growth. Several canopy traits (e.g. green area index (GAI), specific leaf area (SLA), light use efficiency (LUE)) as well as N dilution curves of the whole shoots, leaves and stems were determined. Triticale achieved highest GAI in throughout both growth periods. An extended growth period of wheat partly compensated for a lower GAI, thus the differences in the amount of intercepted photosynthetically active radiation (Q) between the crops remained small. In general, rye leaves were thinner (higher SLA) compared to wheat and triticale showing similar SLA, except at ear emergence in both years. Total above-ground dry matter accumulation at dough ripening was lowest in wheat mainly due to a lower LUE which in turn may be the result of a lower specific leaf area. The N dilution curves revealed a clear reduction of stem N concentration with increasing dry matter accumulation, whereas leaf N concentration only slightly decreased presumably in order to maintain optimal photosynthesis. The presented results enhance the understanding of the growth of rye and triticale and allow improving crop growth modeling of both crops.
Accounting for the stochastic nature of sound symbolism using Maximum Entropy model

Abstract Sound symbolism refers to stochastic and systematic associations between sounds and meanings. Sound symbolism has not received much serious attention in the generative phonology literature, perhaps because most if not all sound symbolic patterns are probabilistic. Building on the recent proposal to analyze sound symbolic patterns within a formal phonological framework (Alderete and Kochetov 2017), this paper shows that MaxEnt grammars allow us to model stochastic sound symbolic patterns in a very natural way. The analyses presented in the paper show that sound symbolic relationships can be modeled in the same way that we model phonological patterns. We suggest that there is nothing fundamental that prohibits formal phonologists from analyzing sound symbolic patterns, and that studying sound symbolism using a formal framework may open up a new, interesting research domain. The current study also reports two hitherto unnoticed cases of sound symbolism, thereby expanding the empirical scope of sound symbolic patterns in natural languages.
The Sensitivity of Physiological Measures to Phobic and Nonphobic Fear Intensity

We investigated whether amygdala activation, autonomic responses, respiratory responses, and facial muscle activity (measured over the brow and cheek [fear grin] regions) are all sensitive to phobic versus nonphobic fear and, more importantly, whether effects in these variables vary as a function of both phobic and nonphobic fear intensity. Spider-phobic and comparably low spider-fearful control participants imagined encountering different animals and rated their subjective fear while their central and peripheral nervous system activity was measured. All measures included in our study were sensitive to variations in subjective fear, but were related to different ranges and positions on the subjective fear level continuum. Left amygdala activation, heart rate, and facial muscle activity over the cheek region captured fear intensity variations even within narrowly described regions on the fear level continuum (here within extremely low levels of fear and within considerable phobic fear). Skin conductance an.
Space and time evolution of the Abruzzo precipitation

This study assesses the climate trends of precipitation in a large number of locations in the Abruzzo region for the period 1951-2009. It highlights the reduction of annual precipitation, starting in 1980, due to a significant decrease in winter rainfall amount. This phenomenon seems to be the mesoscale realisation of a more general process that concerns the European area as the result of the new configuration of the Atlantic circulation that has been established through the '80 years of the 20th century.
individual variation in cooperative behaviour Evolutionary causes and consequences of consistent

References http://rstb.royalsocietypublishing. org/content/365/1553/2751.full. html#ref-list-1 This article cites 145 articles, 28 of which can be accessed free Rapid response http://rstb.royalsocietypublishing. org/letters/submit/royptb;365/1553/2751 Respond to this article Subject collections (1886 articles) evolution (1634 articles) ecology (1389 articles) behaviour Articles on similar topics can be found in the following collections
STUDY OF ANTIOXIDANT POTENTIAL OF CADABA FRUTICOSA BY USING VARIOUS IN VITRO MODELS

To investigate the antioxidant potential, total flavonoid and phenolic content in a variety of extracts of aerial parts of Cadaba fruticosa (L) Druce. The samples such as ethyl acetate and ethanolic extracts were tested using six in vitro models such as DPPH, Nitric oxide radical, Iron chelating, Hydroxyl radical, Superoxide radical scavenging activity and Total antioxidant activity to evaluate the in vitro antioxidant potential of C. fruticosa by spectrophotometrically. Total flavonoid and phenolic content in sample were estimated using aluminium chloride colorimetric and Folin-Ciocalteu method. The results were analyzed statistically by the regression method. IC 50 (Half maximal inhibitory concentration) of the ethanolic extract was found to be 577μg/mL (DPPH), 583μg/mL (NO ● ), 545μg/mL (Iron chelating), 596μg/mL (OH ● ), 568μg/mL (O2–•) and 556μg/mL (TAC). Furthermore, the TFC and TPC of the ethanolic extract were found to be 2.54mg gallic acid equivalent per gram of extract and 1.92mg quercetin equivalent per gram of extract respectively. In all the testing, a significant correlation existed between concentrations of the extract and percentage inhibition of free radicals. The results of the present comprehensive analysis demonstrated that C. fruticosa possess potent anti oxidant activity, high flavonoid and phenolic content. The antioxidant property may be related to the polyphenols and flavonoids present in the extract. These results clearly indicated that C. fruticosa is effective against free radical mediated diseases as a natural antioxidant.
Neural Networks for Measurement-based Bandwidth Estimation

The dispersion that arises when packets traverse a network carries information that can reveal relevant network characteristics. Using a fluid-flow model of a bottleneck link with first-in first-out multiplexing, accepted probing tools measure the packet dispersion to estimate the available bandwidth, i.e., the residual capacity that is left over by other traffic. Difficulties arise, however, if the dispersion is distorted compared to the model, e.g., by non-fluid traffic, multiple bottlenecks, clustering of packets due to interrupt coalescing, and inaccurate time-stamping in general. It is recognized that modeling these effects is cumbersome if not intractable. This motivates us to explore the use of machine learning in bandwidth estimation. We train a neural network using vectors of the packet dispersion that is characteristic of the available bandwidth. Our testing results reveal that even a shallow neural network identifies the available bandwidth with high precision. We also apply the neural network under a variety of notoriously difficult conditions that have not been included in the training, such as heavy traffic burstiness, and multiple bottleneck links. Compared to two state-of-the-art model-based techniques, the neural network approach shows improved performance. Further, the neural network can effectively control the estimation procedure in an iterative implementation.
ATHLETIC IDENTITY PROFILE IN PEOPLE WITH PHYSICAL DISABILITIES

This study examined the perceived athletic identity and the effect factors that personal and disability-related characteristics (gender, age, family status (married, unmarried), education, occupational status, disability (congenital, acquired), type of disability (e.g., spinal cord injury) form of exercise, type of sport, experience, and form of games) in the formation of the athletic identity people with physical disabilities (n = 140). The participants completed a 7-item, 3-factor model of the Athletic Identity Measure Scale (AIMS; Brewer & Cornelius, 2001). The participants reported (a) a moderate social and exclusivity identity, and (b) strong negative affectivity identity. Additionally, they indicated that factors as family status, level education, disability, form of exercise, athletic experience and type of games affect significantly the formation of the athletic identity dimensions. Article visualizations:
Fault detection using seismic attributes and visual saliency

In order to detect accurately faults in seismic inline sections, we propose a new bottom-up saliency based approach using different seismic attributes such as coherence, curvature, dip, and gradient in parallel. Each attribute is calculated independently from the original seismic section. The saliency maps of aforementioned attributes are computed using covariance matrix, which are later combined to form a consolidated saliency map that highlights the seismic fault regions. The covariance matrix is used to characterize the seismic patches and captures local structures. By thresholding the variance maps and optimizing the binary points for curve fitting, the proposed workflow yields good results for faults labeling.
Semiarid Riparian Vegetation Water Demand and Its Influence to Compute the Sonora River Basin Water Availability

During the last decade, the riparian zones have received considerable attention in order to restore and manage them since they have an important role to plan water resources and land, among other functions in the ecosystem. The riparian zones are mainly located in the floodplain where the soil is characterised to be alluvial. However, arid zones channels and their floodplain are transitories and subject to frequent and rapid changes (Graf 1988a,b), thus there is not a clear distinction from where the channel finish and the floodplain starts. This condition could be disadvantageous to the vegetation settled in the floodplain which is subject to the floods’ force, the wood debris and eroded sediments carried by. Conversely, this vegetation has the advantage to receive organic matter from the debris and minerals from the eroded soil resulting in a straightforward species capable to survive at adversely conditions (Bendix and Hupp, 2000). The adaptation of this vegetation generates species drought and flood resistant. In the first case, plants develop long roots in order to access groundwater and be wet. In the second case, plants can afford inundation since the modification of the hydraulic roughness reduces the flood velocity and spread seeds increasing the moisture and nutrients availability in the area (Bendix and Hupp, 2000). However, the access of the riparian vegetation to groundwater produces high rates of transpiration and a high evaporative demand of the atmosphere. This is because water requirements are bigger in arid and semiarid regions, where rainfall is less and the vapour pressure deficit on the air is large. This implies great water consumption by this vegetation becoming as one of the components to be considered in the groundwater balance. Particularly, in semiarid sites where groundwater is the main water demand source, since water surface resources are highly compromised, temporal and spatially. Scott et al. (2003) observed that as groundwater is used to provide water among the different users, there is a depletion of the water levels that affects directly the riparian zones and, in consequence, modify ecological and hydrologically the watershed. Scott et al. (2003) pointed out that in order to compute riparian water requirements it is common to use hydrological models that compute it as the residual discharge resulted after calibrated against known inputs, groundwater levels and discharges. This procedure could over or underestimate the groundwater balance in the basin, thus a better understanding of
Quality of Education and Its Evaluation: An Analysis of the Russian Academic Discussion

The article describes and critically analyzes how Russian education researchers approached the topic of quality evaluation in education between 1990 and 2014. Evaluation and quality have grown into major policy issues in education across the world, simultaneously acting as powerful steering mechanisms on national and transnational levels. Russia is no exception to this global phenomenon, but little is known about how Russian education researchers discuss the topic in national academic journals. This article discusses four major periods, each characterized by a shift in the focus of discussion and/or the introduction of a completely new agenda. These periods capture the dominant themes, titled “effective management and customization of education,” “the rise of broad-scale assessments,” “systemic approach to quality evaluation,” and “toward a more nuanced usage of evaluation data. ” We interpret the findings within two intertwined conceptual frameworks: governance at a distance and New Public Management. How these frames help us understand the academic discussion on quality evaluation in Russian school education is also discussed.
High temperature and stress corrosion cracking of 310S austenitic stainless steel in wet chloride corrosive environment

T. Pornpibunsompop, P. Thanakijkasem, Division of Materials Technology, School of Energy, Environment and Materials, King Mongkut’s University of Technology Thonburi, Thailand, Email, tosapolporn.p@dti.or. th, purit.tha@kmutt.ac. th High temperature corrosion and stress corrosion cracking of 310S austenitic stainless steel in wet chloride environment at a high temperature was investigated. The result showed that high temperature corrosion products mostly consisted of ferrous oxides and chromium oxides. Chloride ions attacked a chromium passive film and strongly reacted with iron and chromium. As a result of metal chlorides being volatized, tunnel of pores inside corrosion layer existed. Intergranular stress corrosion cracking was observed. The oxide originated on surface could act as a crack initiator and a crack propagation would progress along grain boundaries and particularly along tunnel of pores.