Miracle-dz/UniFAR-FTUs huggingface dataset:
A General Architecture for an Emotion-aware Content-based Recommender System

Emotions play a crucial role in the decision making process. Frequently, choices are strongly influenced by the mood of the moment, and the same person could take different decisions at different time on the same topic. Recommender systems, that are definitively recognized as tools for supporting the decision making process, demonstrated to be more accurate exploiting emotive labels in several work. For this reason a large number of researchers are focusing their attention on the analysis of the emotions by exploiting data that users daily disseminate on the Web (e.g.: Social Networks, Blogs, Forums, etc.). In this paper we propose a general architecture for implementing an emotion-aware content-based recommender system. Furthermore, we developed a web service that researchers can freely exploit for their own implementations. We carried out a user study on the domain of music recommendation, particularly influenced by the user emotion, and results are very promising.
Scanning electronmicroscopy of hypertrophic and keloid scar

The scanning electronmicroscopic appearances of hypertrophic and keloid scar before and after treatment, mature scar and normal skin have been investigated. There is a graduation of features such as collagen orientation and fibre size which accompanies the clinical maturation from the active hypertrophic state into mature scar, a process which is hastened but not materially altered by treatment with steroid or compression-occlusion.
Ca 2+ - activated K + Channels in Murine Endothelial Cells: Block by Intracellular Calcium and Magnesium

The intermediate (IK Ca ) and small (SK Ca ) conductance Ca 2+ -sensitive K + channels in endothelial cells (ECs) modulate vascular diameter through regulation of EC membrane potential. However, contribution of IK Ca and SK Ca channels to membrane current and potential in native endothelial cells remains unclear. In freshly isolated endothelial cells from mouse aorta dialyzed with 3 (cid:2) M free [Ca 2+ ] i and 1 mM free [Mg 2+ ] i , membrane currents reversed at the potassium equilibrium potential and exhibited an inward rectifi cation at positive membrane potentials. Blockers of large-conductance, Ca 2+ -sensitive potassium (BK Ca ) and strong inward rectifi er potassium (K ir ) channels did not affect the membrane current. However, blockers of IK Ca channels, charybdotoxin (ChTX), and of SK Ca channels, apamin (Ap), signifi cantly reduced the whole-cell current. Although IK Ca and SK Ca channels are in-trinsically voltage independent, ChTX- and Ap-sensitive currents decreased steeply with membrane potential depolarization. Removal of intracellular Mg 2+ signifi cantly increased these currents. Moreover, concomitant reduction of the [Ca 2+ ] i to 1 (cid:2) M caused an additional increase in ChTX- and Ap-sensitive currents so that the currents exhibited theoretical outward rectifi cation. Block of IK Ca and SK Ca channels caused a signifi cant endothelial membrane potential depolarization ( ≈ 11 mV) and decrease in [Ca 2+ ] i in mesenteric arteries in the absence of an agonist. These results indicate that [Ca 2+ ] i can both activate and block IK Ca and SK Ca channels in endothelial cells, and that these channels regulate the resting membrane potential and intracellular calcium in native endothelium. patch clamp technique at a sampling rate of 5 obtaining a gigaohm seal with a borosilicate micropipette (6 – 8 M Ω ) on the facing endothelium. The membrane potential recordings (perfo-rated patch) were performed without current injection (I = 0 mode). All in situ experiments were performed in the presence of nisoldipine (100 nM) to minimize the contraction of the smooth muscle to KCl and the impact of smooth muscle on endothelial membrane potential. 2+ to 1 mM. These experiments were performed at room temperature. For simultaneous membrane potential and Ca 2+ imaging experiments in intact endothelium of cut-open mesenteric arteries, a physiological salt solution was used with the following constitu-ents (in mM): NaCl 119, KCl 4.7, NaHCO 3 24, KH 2 PO 4 1.2, EDTA 0.0023, MgCl 2 1.2, glucose 11, and CaCl 2 1.6, and the following pipette solution for the simultaneous membrane potential recording (in mM): K-aspartate 110, NaCl 10, KCl 30, MgCl 2 1, HEPES 10 (pH 7.2), and EGTA 0.05. Amphotericin (200 μ g/ml) was used to achieve perforated patch. These experiments were performed at 30 ° C to minimize dye leakage. paired
Tuning Complex Systems by Sonifying Their Performance Data

In the modern computing landscape, the challenge of tuning software systems is exacerbated by the necessity to accommodate multiple divergent execution environments and stakeholders. Achieving optimal performance requires a different configuration for every combination of hardware setups and business requirements. In addition, the state of the art in system tuning can involve complex statistical models, which require deep expertise not commonly possessed by the average software developer. This paper presents a novel approach to tuning complex software systems by leveraging sound to convey performance information during execution. We conducted a scientific survey to determine which sound characteristics (e.g., loudness, panning, pitch, tempo, etc.) are most accurate to express information to the average programmer. As determined by the survey, the characteristics that scored the highest across all the participants were used to create a proof-of-concept demonstration. The demonstration showed that a programmer who is not an expert in either software tuning or enterprise computing can configure the parameters of a real world enterprise application server, so that its resulting performance surpasses that exhibited under the standard configuration. Our results indicate that sound-based tuning approaches can provide valuable solutions to the challenges of configuring complex computer systems.
A Model for Capacity Planning in Cassandra Data Data S Case Study on Ericsson ’ s Voucher System

Context: Cassandra is a NoSQL(Not only Structured Query Language) database which serves large amount of data with high availability . Cassandra data storage dimensioning also known as Cassandra capacity planning refers to predicting the amount of disk storage required when a particular product is deployed using Cassandra. This is an important phase in any product development lifecycle involving Cassandra data storage system. The capacity planning is based on many factors which are classified as Cassandra specific and Product specific. Objectives: This study is to identify the different Cassandra specific and product specific factors affecting the disk space in Cassandra data storage s ystem. Based on these factors a model is to be built which would predict the disk storage for Ericsson’s voucher system. Methods: A case-study is conducted on Ericsson’s voucher system and its Cassandra cluster. Interviews were conducted on different Cassandra users within Ericsson R&D to know their opinion on capacity planning approaches and factors affecting disk space for Cassandra. Responses from the interviews were transcribed and analyzed using grounded theory. Results: A total of 9 Cassandra specific factors and 3 product specific factors are identified and documented. Using these 12 factors a model was built. This model was used in predicting the disk space required for voucher system’s Cassandra. Conclusions: The factors affecting disk space for deploying Cassandra are now exhaustively identified. This makes the capacity planning process more efficient. Using these factors the Voucher system’s disk space for deployment is predicted successfully.
Smooth James-Stein model selection against erratic Stein unbiased risk estimate to select several regularization parameters

Smooth James-Stein thresholding-based estimators enjoy smoothness like ridge regression and perform variable selection like lasso. They have added ﬂexibility thanks to more than one regularization parameters (like adaptive lasso), and the ability to select these parameters well thanks to a unbiased and smooth estimation of the risk. The motivation is a gravitational wave burst detection problem from several concomitant high-frequency time series. A wavelet-based estimator is developed to combine information from all captors by block-thresholding multiresolution coeﬃcients. We derive a universal threshold, an information criterion and an oracle inequality for this estimator. Smooth James-Stein thresholding is then employed in parametric linear regression for which we derive a formula for unbiased risk estimation.
Humanized mice

Animal models have been instrumental in increasing the understanding of human physiology, particularly immunity. However, these animal models have been limited by practical considerations and genetic diversity. The creation of humanized mice that carry partial or complete human physiological systems may help overcome these obstacles. The National Institute of Allergy and Infectious Diseases convened a workshop on humanized mouse models for immunity in Bethesda, MD, on June 13–14, 2005, during which researchers discussed the benefits and limitations of existing animal models and offered insights into the development of future humanized mouse models.
An approximate dynamic programming approach for coordinated charging control at vehicle-to-grid aggregator

A vehicle-to-grid (V2G) aggregator is an agent between the power grid and plug-in hybrid electrical vehicles (PHEVs). This paper studies the coordinated charging control of a V2G aggregator, which aims at minimizing the charging cost and reducing the power losses incurred by the fluctuating load. On one hand, a lower cost of charging gives the owners of PHEVs an incentive to cooperate. On the other hand, with an increasing popularity of PHEVs, the impact on the power grid such as power losses should be of concern to the aggregator. As an inherent property of a V2G aggregator, we enable bidirectional electric power flows between PHEVs and the power grid. Given the planned schedules of all the vehicles that are managed by an aggregator, we formulate the coordinated charging control as a dynamic programming problem. Due to the curse of dimensionality, we apply an approximate dynamic programming approach, which reduces the dimensionality of both state space and control space, to obtain the control sequences. We conduct simulations given the 24-hour schedules of 100 vehicles. Simulation results show that coordinated charging control can reduce both the total cost of charging and power losses significantly, compared with the scheme where each vehicle starts charging as soon as it is connected to the grid.
ERP post-adoption: Value impact on firm performance: A survey study on Portuguese SMEs

Enterprise Resource Planning (ERP) systems and firms performance aspects are currently experiencing an increasing interest from both the academic and business communities. Based on the resource-based view (RBV) theory this paper develops a research model to measure and examine determinants of ERP value in regards to the impact on small and medium enterprise (SME) performance. The model gathers industry standards and literature of ERP, linking three determinants anchored on RBV to `ERP value' (usage, collaboration and analytics capabilities), on which three hypotheses are postulated. Testing was conducted thought structural equation modeling as implemented in partial least squares (PLS) on a data set web surveyed across Portuguese firms. Our findings show that collaboration and analytics capabilities, together with usage, will contribute to `ERP value'. This study contributes to the ERP literature, in particular how SMEs can exploit value from ERP. Unlike the typical focus on ERP adoption found in the literature, this study focuses on post-adoption stage, linking the ascendants of system value to firm performance.
The Rugby Players Association's Benevolent Fund : a sociological study of the development of a social integration discourse in rugby football

This thesis examines how player welfare and post-athletic retirement preparation is discussed by both professional rugby union athletes who play in the English Premiership and the Board of Trustees of the Rugby Players’ Association’s (RPA) Benevolent Fund, the non-profit division of the trade union which represents the employment and welfare interests of professional rugby union players in England. A career in professional sports is one that is uncertain and unpredictable (Roderick 2006a; McGillivray et al. 2005). A consequence of rugby union transitioning into a professional format on 26 August 1995 was that rugby union became a stand-alone career. Along with the transition in employment structure, the athlete became bigger, faster and stronger (Olds 2001; Norton and Olds 2000). This resulted in an increase of injury severity (Kaplan et al. 2008; Brooks and Kemp 2008; Bathgate et al. 2002; Garraway et al. 2000). In an effort to address the growing concern of injury severity and injury induced retirement, the RPA created the Benevolent Fund in 2001. The Foundation was given the remit to provide assistance to professional rugby union players during times of injury or illness, which included programmes that assisted with medical treatment, rehabilitation, counselling and direct financial assistance. To specifically address the growing numbers of players being forced to retire due to injury, the RPA commenced its ‘Life After Rugby’ programme, which provides educational opportunities that helps athletes to acquire alternative careers. The data gathered in this research shows, with the assistance of Levitas’s discourse models (2005, 2004, 1996a, 1996b, 1989), that there is a mixed level of involvement amongst rugby players in retirement preparation. It also underscores that players’ understanding of their risk of becoming ‘socially excluded’ – a prevailing concern of the RPA’s Benevolent Fund – is varied. The data shows that players who have spent more time as professional athletes are more likely to mirror the language used by the RPA to describe their policy objectives than those who have just recently started their professional sporting career. Early career rugby players are aware of the risk of injury, but they tend to ignore the possibility that it could happen to them personally. This research highlights the RPA’s successes with senior players but identifies the need for the RPA to modify their approach so as to encourage earlier adoption of the ‘Life After Rugby’ scheme by players just starting their career in professional sport.
A second-order globally convergent direct-search method and its worst-case complexity

Direct-search algorithms form one of the main classes of algorithms for smooth unconstrained derivative-free optimization, due to their simplicity and their well-established convergence results. They proceed by iteratively looking for improvement along some vectors or directions. In the presence of smoothness, first-order global convergence comes from the ability of the vectors to approximate the steepest descent direction, which can be quantified by a first-order criticality (cosine) measure. The use of a set of vectors with a positive cosine measure together with the imposition of a sufficient decrease condition to accept new iterates leads to a convergence result as well as a worst-case complexity bound. In this paper, we present a second-order study of a general class of direct-search methods. We start by proving a weak second-order convergence result related to a criticality measure defined along the directions used throughout the iterations. Extensions of this result to obtain a true second-order optimality one are discussed, one possibility being a method using approximate Hessian eigenvectors as directions (which is proved to be truly second-order globally convergent). Numerically guaranteeing such a convergence can be rather expensive to ensure, as it is indicated by the worst-case complexity analysis provided in this paper, but turns out to be appropriate for some pathological examples.
Predictive Accuracy and Explained Variation in Cox Regression

Summary. We suggest a new measure of the proportion of the variation of possibly censored survival times explained by a given proportional hazards model. The proposed measure, termed V, shares several favorable properties with an earlier V1 but also improves the handling of censoring. The statistic contrasts distance measures between individual 1/0 survival processes and fitted survival curves with and without covariate information. These distance measures, Dx and D, respectively, are themselves informative as summaries of absolute rather than relative predictive accuracy. We recommend graphical comparisons of survival curves for prognostic index groups to improve the understanding of obtained values for V, Dx, and D. Their use and interpretation is exemplified for a Yorkshire lung cancer study on survival. From this and an overview for several well‐known clinical data sets, we show that the likely amount of relative or absolute predictive accuracy is often low even if there are highly significant and relatively strong prognostic factors.
Production response to price risk and market liberalization of Nigerian major agricultural crops

This study models supply response for major agricultural crops in Nigeria which include the standard arguments and price risk. The data comes from Central Bank of Nigeria annual reports and statement of account, National Bureau of Statistics’ abstract of statistics and annual Agricultural survey manual. The data are analyzed using autoregressive distributed lag and cointegration and error correction models. The results indicate that producers are responsive not only to price but also to price risk and exchange rate.
When Excessive Consumption Is Rational

If average cost is everywhere above market demand, it is usually argued that the nondiscriminating firm will shut down, although the first-best outcome may dictate production. In this setting, it is shown that there is often a Nash equilibrium in consumption that will keep the firm producing. Selfish consumers engage in excessive (beyond demand) consumption to keep the firm in business and to protect their surpluses. This is shown to be true in a simple model with perfect information and also in a more realistic model in which consumers are uncertain about the firm's costs. Copyright 1991 by American Economic Association.
SoQr: sonically quantifying the content level inside containers

In this paper, we present SoQr, a sensor that can be attached to an external surface of a household item to estimate the amount of content inside it. The sensor consists of a speaker and a microphone. It outputs a short duration sine wave probing sound to excite a container and its content, and then records the container's impulse response. SoQr then extracts Mean Mel-Frequency Cepstral Coefficients from impulse response recordings of a container with different content levels and learns a support vector machine classifier. Results from a 10-fold cross validation of the prediction models on 19 common household items demonstrate that SoQr can correctly estimate the content level for these products with an average overall F-Measure above 0.96. We then further evaluated SoQr's robustness in different usage scenarios to gain an understanding of how the system performs and specific challenges that might arise when users interact with these products and the sensor.
Experiment design in system identification using fractional models

This paper tackles the problem of experiment design in system identification using elementary fractional models. It is based on a frequency domain approach and answers the question: what is the best sinusoidal input signal maximizing the D-optimality criterion of the Fisher information matrix in different contexts? First, a single parameter is assumed to be unknown (any of the parameters of the elementary transfer functions). Then multiple parameters and their combinations are supposed to be unknown.
Multi‐dimensional nature of service innovation: Operationalisation of the elevated service offerings construct in collaborative service organisations

Purpose – Innovation in services is thought to be multi‐dimensional in nature, and in this context the purpose of this paper is to present and operationalise the concept of “elevated service offerings” (ESO) in collaborating service organisations. ESO stands for new or enhanced service offerings which can only be eventuated as a result of partnering, and which could not be delivered on individual organisational merit. ESO helps us expand our understanding of service innovation to include a service network or service system's dimension.Design/methodology/approach – A structural equation model is specified and estimated based on constructs and relationships grounded in the literature, as well as self‐developed constructs, using empirical data from 449 respondents in an Australian telecommunications service provider (SP) and its partnering organisations.Findings – Results show that ESO is a multi‐dimensional construct which was operationalised and validated through an extensive literature review, exploratory.
Project Evaluation: An Integrated Financial and Economic Analysis

This book aims to be an introduction and support to the carrying out of financial and economic analysis of a country's projects. It uses a case study of a joint venture between domestic and foreign investors in a developing country to show how the theoretical analysis relates to real life. The financial and economic analyzes are systematically linked. All aspects which are considered significant are treated in separate steps, thereby simplifying the evaluation process for the reader.
Journal of the American Statistical Association an Integrative Bayesian Modeling Approach to Imaging Genetics an Integrative Bayesian Modeling Approach to Imaging Genetics

Taylor & Francis makes every effort to ensure the accuracy of all the information (the " Content ") contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. In this article we present a Bayesian hierarchical modeling approach for imaging genetics, where the interest lies in linking brain connectivity across multiple individuals to their genetic information. We have available data from a functional magnetic resonance imaging (fMRI) study on schizophrenia. Our goals are to identify brain regions of interest (ROIs) with discriminating activation patterns between schizophrenic patients and healthy controls, and to relate the ROIs' activations with available genetic information from single nucleotide polymorphisms (SNPs) on the subjects. For this task, we develop a hierarchical mixture model that includes several innovative characteristics: it incorporates the selection of ROIs that discriminate the subjects into separate groups; it allows the mixture components to depend on selected covariates; it includes prior models that capture structural dependencies among the ROIs. Applied to the schizophrenia dataset, the model leads to the simultaneous selection of a set of discriminatory ROIs and the relevant SNPs, together with the reconstruction of the correlation structure of the selected regions. To the best of our knowledge, our work represents the first attempt at a rigorous modeling strategy for imaging genetics data that incorporates all such features.