Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Implementing Family-centered Empowerment Model on the Quality of Life in School-age Children Diagnosed with Rheumatoid Arthritis

Background: Rheumatoid arthritis is the most prevalent chronic rheumatologic disease of children. The quality of life (QOL) in these individuals is affected by physical pain, discomfort, treatment complications, and frequent absences from school leading to academic failure. No research similar to the present investigation was performed in this area. Aim: We aimed to evaluate the problems of children with rheumatoid arthritis. Moreover, we assessed the effect of family-centered empowerment on the QOL of these children. Method: This randomized clinical trial was performed on 60 children aged 8-12 years diagnosed with rheumatoid arthritis in Akbar Pediatrics Hospital, Mashhad, Iran in 2018. The subjects were divided into test and control groups. The four stages of family-centered empowerment model, namely improvement of knowledge, self-efficacy, self-esteem, and assessment were executed for the test group. After a month, the inventory of pediatric quality of life was completed again. Data analysis was performed by Mann-Whitney U test, independent t-test, and paired t-test using SPSS version 16. Results: No significant difference was observed between the groups regarding age (P=0.351). In addition, the post-intervention QOL of the test group was significantly higher than the control group (P=0.004). There was a significant difference between the pre- and post-intervention QOL in the test group (P < 0.001). Implications for Practice: This study indicated the effect of family-centered empowerment model on the physical, emotional, educational, and social dimensions of QOL of children aged 8-12 years diagnosed with rheumatoid arthritis. As a result, this model is recommended to empower the children with this disease or other chronic diseases and their caregivers.
Building (Timely) bridges between learning analytics, educational data mining and core learning sciences perspectives

: Despite the exponential growth of the research on Learning Analytics (LA) and Educational Data Mining (EDM) over the last few years, the work has been still distant from the core Learning Sciences methods, theoretical constructs, and literature. At the same time, over the last 15 years, Learning Sciences as a field has been quite innovative, eclectic, and effective in incorporating new methodological stances, such as micro-genetic methods, micro-ethnographies, and design-based research. It seems that the time has come to build sound connections between these traditions. The goal of this symposium is to bring together researchers coming from different academic perspectives, to explore and examine common LA/EDM methodological and theoretical threads with wide applicability within the Learning Sciences. The papers presented explore text mining in clinical interviews, moment-by-moment learning curves
Designing Display Ecologies for Visual Analysis

The current proliferation of connected displays and mobile devices—from smart phones and tablets to wall-sized displays—presents a number of exciting opportunities for information visualization and visual analytics. When a user employs heterogeneous displays collaboratively to achieve a goal, they form what is known as a display ecology. The display ecology enables multiple displays to function in concert within a broader technological environment to accomplish tasks and goals. However, since information and tasks are scattered and disconnected among separate displays, one of the inherent challenges associated with visual analysis in display ecologies is enabling users to seamlessly coordinate and subsequently connect and integrate information across displays. This research primarily addresses these challenges through the creation of interaction and visualization techniques and systems for display ecologies in order to support sensemaking with visual analysis. This dissertation explores essential visual analysis activities and design considerations for visual analysis in order to inform the new design of display ecologies for visual analysis. Based on identified design considerations, we then designed and developed two visual analysis systems. First, VisPorter supports intuitive gesture interactions for sharing and integrating information in a display ecology. Second, the Spatially Aware Visual Links (SAViL) presents a cross-display visual link technique capable of guiding the user’s attention to relevant information across displays. It also enables the user to visually connect related information over displays in order to facilitate synthesizing information scattered over separate displays and devices. The various aspects associated with the techniques described herein help users to transform and empower the multiple displays in a display ecology for enhanced visual analysis and sensemaking.
Optimization of Internally Finned Tubes for Solar Receivers

SUNSPOT proposes a gas turbine cycle with air as wo rking fluid. Although freely available, air is a p oor heat transfer fluid. Metals are the preferred choi e for the receiver, as they are relatively cheap a nd easy to machine. High heat fluxes from the heliostat field will result in high material temperatures, and pos sible tube failures. This paper explores heat transfer enhanc ement through triangular fins on the inside of the receiver tubes. The internal heat transfer in the receiver tube depends on the tube diameter, wall thickness, number of fins, gap between fins and helical angle for a fixe d flow velocity and tube material. Computational f luid dynamics were used to evaluate the target function and its gradient. The bulk of the heat is transfer red by convection to the working fluid. The tube loses he at to the environment through thermal radiation. T he optimization routine of choice use sequential conve x quadratic approximates of the target function. Preliminary results for a steel tube indicate that the maximum metal temperature can be reduced substantially. Rather high temperature differences across the tube suggest that thermal stresses may be significant.
Performance Analysis of Mimo-Scma Systems for 5 G Communications

Recently, sparse code multiple access (SCMA) is proposed as one of the important candidacies for the fifth generation (5G) radio access technique. SCMA is a non-orthogonal multiple access (NOMA) technique which allows multiple users share the same radio resource and thus increase spectral efficiency largely. In SCMA, a set of binary coded bits is mapped directly into a complex vector by use of a predefined multi-dimensional codebook. The sparsity of the codewords makes the near-optimal detection feasible through iterative message passing algorithm (MPA). The pursuit of higher spectral efficiency motivates us to study the performance of multiple-input-multiple-output (MIMO) SCMA system in this paper. Simulation results show that compared with the conventional MIMO-OFDM system, MIMO-SCMA can provide a gain up to 50% in data throughput with the aid of MPA technique.
Excitation Control for Damping Inter-Area Oscillations through Recurrent Neural Networks

In order to effectively restrain inter-area oscillations in power systems, a local measurement based neural excitation controller is proposed to generate global stable signal. This is to replace the global measurement based power system stabilizer (GPSS). The proposed neural controller is constructed by two recurrent neural networks: a recurrent neural identifier (RNID) and a recurrent neural controller (RNCT). Non-measurable global dynamics in large-scale multi-machine power systems is estimated by the RNID and is provided to RNCT in order to generate global stable signals for a higher hierarchy of supplementary excitation control. Simulation results based on Kundur’s 2-area 4-machine power system model proved the effectiveness of the proposed local signal based neural identifier and controller in damping inter-area oscillations.
Towards Understanding the Genetic Basis of Apple Acidity

Fruit acidity greatly affects overall eating quality and flavor. The major organic acid in mature apple fruit is malic acid although citric, quinic and other acids are also detectable. Because of its importance in determining fruit flavor and quality, fruit acidity has been a subject of genetic investigations. An early inheritance study conducted on fruit acidity (Nybom 1959) based on pH measurements, reported several important findings: 1) Apple varieties can be categorized into two groups: an acid/sub-acid group with a fruit pH<3.8 and a sweet group of pH about or over 4.0. 2) The acid/sub-acid group is much more prevalent than the sweet group in cultivated apples. 3) The sweet flavor is determined by one recessive gene present in 80-90% of apple varieties studied. These findings were independently confirmed in later studies based on fruit pH (Visser and Verhaegh 1978) as well as malic acid concentration (Brown and Harvey 1971). The major gene governing fruit acidity was designated Ma with the Ma allele (an variant of the Ma gene) representing the dominant high and medium acid, and the ma allele for low acid (Visser and Verhaegh 1978). The Ma gene has been mapped to the distal end of linkage group (syn. chromosome) 16 in a presumably Mama × Mama cross (‘Prima’ × ‘Fiesta’) (Maliepaard et al. 1998). In this study, fruit acidity was evaluated with pH indicator paper and the progeny were classified into two categories of three genotypes based on fruit pH, i.e. MaMa/Mama (pH<3.8) and mama (pH>3.8). Using QTL (quantitative trait locus) based approaches, a major QTL for fruit titratable acidity (TA) was detected in the Ma region (Kenis et al. 2008; Liebhard et al. 2003). In the cross ‘Fiesta’ × ‘Discovery’, the major QTL was linked closely to marker CH05e04z in ‘Fiesta’ and accounted for 36% of fruit acidity variation (Liebhard et al. 2003). In the cross ‘Telamon’ × ‘Braeburn’, it was mapped to an interval between markers CH05e04z and CH05c06 and explained 20 to 34% of the observed variance (Kenis et al. 2008). In addition to the major QTL in the Ma region, another major QTL (explaining 33% of the variance) for TA was reported on linkage group 8 in ‘Fiesta’ × ‘Discovery’ (Liebhard et al. 2003). But this second major QTL could only be identified as one of the six minor QTLs in the ‘Telamon’ Towards Understanding the Genetic Basis of Apple Acidity
“ You Had to Be There ” : Convention Attendance and Well-Being in Anime Fans

We examined the differences between participants completing measures of wellbeing at an anime convention and participants completing the same measures online and tested possible mediators of differences between the two groups. Participants, all self-identified anime fans, completed measures of anime convention attendance, of the nature of their engagement with anime, well-being, and loneliness, and did so either while at an anime convention or online. Participants sampled at the convention reported greater well-being, more interactions with others, and lower loneliness than participants in the online sample. Mediation analyses suggest that the association between sample source and well-being is mediated both by face-toface interaction and loneliness. Taken together, the results suggest the importance of face-to-face interaction with like-minded others as one of the means through which convention attendance may prove beneficial for fans.
Hybrid systems : computation and control : 7th International Workshop, HSCC 2004, Philadelphia, PA, USA, March 25-27, 2004 : proceedings

Regular Papers. - Lazy Rectangular Hybrid Automata. - Affine Hybrid Systems. - Abstraction by Projection and Application to Multi-affine Systems. - Observability of Switched Linear Systems. - Inference Methods for Autonomous Stochastic Linear Hybrid Systems. - Synthesis for Idle Speed Control of an Automotive Engine. - Network Congestion Alleviation Using Adjoint Hybrid Control: Application to Highways. - Understanding the Bacterial Stringent Response Using Reachability Analysis of Hybrid Systems. - A SAT-Based Hybrid Solver for Optimal Control of Hybrid Systems. - Incremental Search Methods for Reachability Analysis of Continuous and Hybrid Systems. - Discrete and Hybrid Nonholonomy. - Approximations of the Rate of Growth of Switched Linear Systems. - The Hybrid Guaranteed Capture Basin Algorithm in Economics. - Staying Alive as Cheaply as Possible. - On O-Minimal Hybrid Systems. - Extended Stochastic Hybrid Systems and Their Reachability Problem. - On the Controllability of Bimodal Piecewise Linear Systems. - Observability of Piecewise-Affine Hybrid Systems. - Non-deterministic Temporal Logics for General Flow Systems. - Almost ASAP Semantics: From Timed Models to Timed Implementations. - Discrete State Estimators for a Class of Hybrid Systems on a Lattice. - Benchmarks for Hybrid Systems Verification. - On the Optimal Control of Switch-Mode DC-DC Converters. - Event-Driven Programming with Logical Execution Times. - A Stochastic Hybrid Model for Air Traffic Control Simulation. - Stochastic Hybrid Systems: Application to Communication Networks. - Rigorous Modeling of Hybrid Systems Using Interval Arithmetic Constraints. - Modeling Subtilin Production in Bacillus subtilis Using Stochastic Hybrid Systems. - Sound Code Generation from Communicating Hybrid Models. - Multi-Parametric Toolbox (MPT). - Dynamic Partitioning of Large Discrete Event Biological Systems for Hybrid Simulation and Analysis. - Safety Verification of Hybrid Systems Using Barrier Certificates. - Piecewise-Linear Output-Error Methods for Parameter Estimation in Direction-Dependent Processes. - A Spatial Logic for the Hybrid ? -Calculus. - Full Paper Sheet Control Using Hybrid Automata. - Constructing Invariants for Hybrid Systems. - Bisimulation of Dynamical Systems. - Control Design for a Hybrid Dynamic System: A NASA Life Support System. - Non-concurrent Error Detection and Correction in Switched Linear Controllers. - Nonlinear Systems: Approximating Reach Sets. - On Practical Stability and Stabilization of Hybrid and Switched Systems. - A Numerical Technique for Stability Analysis of Linear Switched Systems. - Asymptotic Stability and Boundedness of Delay Switching Diffusions. - Invited Contribution. - Symbolic Systems Biology: Hybrid Modeling and Analysis of Biological Networks.
How does learning orientation generate product innovativeness and superior firm performance ?

This paper attempts to shed light on the role of learning orientations of firms on two dependent variables: product innovativeness and firm performance. Hierarchical regressions were run with data from a random sample of 121 firms operating in Turkey. Findings indicate that internally-focused learning and market-focused learning have significant effects on product innovativeness. When firm performance is included as the eventual outcome variable into the analysis, internally-focused learning and product innovativeness emerge as its main predictors. In fast-paced, highly unpredictable market environments, managers can make use of these findings to their benefit in terms of elevating their firms’ innovativeness and performance levels.
A Region-Based Trimmed feature Matching Approach to Content-Based Image Retrieval

This paper proposes a trimmed filter approach, TIRM ( trimmed integration region matching ), for region-based image retrieval. In our retrieval approach, an image is segmented into a set of regions by using Expectation-Maximization (EM) algorithm, a full automatic segmentation algorithm, has been run on 1000 natural images. For each of region, which is characterized by a parameter-trimmed feature vector (trimmed vector) reflecting color, texture, and shape properties. As a result, an image is associated with a family of trimmed features corresponding to regions. Parameter-trimmed for describing region, which applies the notion of trimmed operation (or filter) on local sets by combining individual feature vector or region using a special filtering operation to generate robust region representation that can eliminate the adverse effect of segmentation algorithm. The resemblance of two images is then defined as the overall similarity between two sets of trimmed average features and quantified by a similarity measure, TIRM (trimmed integration region matching), which is the soft similarity measure by integrating properties of all the regions in the images. Compared with retrieval-based on individual regions, the TIRM reduces the influence of inaccurate segmentation and provides a very intuitive quantification. The approach is tested on an image database of 1000 general-purpose images with a better result. Key-Words: Content-based image retrieval, image segmentation, trimmed region feature, similarity measure.
Drought and salinity stresses in barley: Consequences and mitigation strategies

Recent trends show reductions in crop productivity worldwide due to severe climatic change. Different abiotic stresses significantly affect the growth and development of plants, leading to decreased crop yields. Salinity and drought stresses are the most common abiotic stresses, especially in arid and semi–arid regions, and are major constraints for barley production. The present review attempts to provide comprehensive information related to barley plant responses and adaptations to drought and salinity stresses, including physiological and agronomic, in order to alleviate the adverse effect of stresses in barley. These stresses reduce assimilation rates, as they decrease stomatal conductance, disrupt photosynthetic pigments, reduce gas exchange, enhance production of reactive oxygen species, and lead to decreased plant growth and productivity. This review focuses on the strategies plants use to respond and adapt to drought and salinity stress. Plants utilize a range of physiological and biochemical mechanisms such as adaptation strategies, through which the adverse effects can be mitigated. These include soil management practices, crop establishment, as well as foliar application of anti-oxidants and growth regulators that maintain an appropriate level of water in the leaves to facilitate adjustment of osmotic and stomatal performance. The present review highlighted the adverse effect of drought and salinity stresses barley and their mitigation strategies for sustainable barley production under changing climate. They review also underscored that exogenous application of different antioxidants could play a significant role in the alleviation of salinity and drought stress in plant systems.
An Analysis of Bayesian Inverse Shape Acoustic Scatterings with Gaussian priors

We present an infinite dimensional Bayesian inversion formulation for inverse shape acoustic scattering problems. Given a Gaussian prior measure on the shape space, whose covariance operator is the inverse of the Laplacian, the Bayesian solution of the inverse problem is the posterior measure given by the Radon-Nikodym derivative with respect to the Gaussian prior measure. The well-posedness of the Bayesian formulation is proved, including the justification of the RadonNikodym derivative and the continuous dependence of the posterior measure on the observation data via the Hellinger distance. At the heart of the proving technique is the shape parametrization in a Banach space setting and the regularity of the forward solution with respect to the smoothness of the shape. This paves the way for Lipschitz continuity of the observation operator with respect to the scatterer shape via the shape derivative of the forward solution. Next, finite dimensional approximation to the Bayesian posterior is proposed and the corresponding approximation error is quantified. The approximation strategy involves a Nyström scheme for approximating the forward equation and a Karhunen-Loève truncation approach for approximating the prior measure. Weak convergence and convergence of the resulting finite dimensional approximation in the Hellinger distance are investigated. In particular, we provide the convergence rate as a function of the number of Nyström quadrature points and the number of truncated terms in the Karhunen-Loève series. Finally, we estimate the error between the exact posterior moments, e.g. posterior mean and variance, and their finite dimensional approximate counterparts in terms of the errors due to forward equation approximation and prior approximation.
European Conference on Information Systems ( ECIS ) 2008 Unveiling Collaboration Structures in Software Development Projects

We investigate the structures of collaboration in software development groups by analyzing the data derived from the versioning system SVN (subversion) for software projects of different types and sizes. Our research is part of the project “Economics of Networks in Information Systems” (EONIS) which aims to investigate the impact of network structures on the effectiveness of infrastructures, organizations and processes in the domain of information systems. The goal of this subproject in EONIS is to reveal the network topology of collaboration groups for development projects connected with proprietary software in industry as well as in open source software projects. For this purpose we have developed a software tool that is able to analyze the update data in SVN systems with respect to the changes in the software code and defined a collaboration coefficient that is able to express the strength of their relationship in terms of collaboration in the network. We present the first results from the analysis of an open source project with about 126 software developers by constructing a weighted network from a matrix representation of the collaboration coefficients that have been calculated for each pair of software developers.
STRESS AND SEISMICITY IN AREAS OF RELIC DESCENDING LITHOSPHERIC SLABS : THE SOUTHEASTERN CARPATHIANS

Recent findings from regional seismic tomography and refraction studies and from GPS studies on vertical movements together with extremely high intermediate-depth seismicity in the Vrancea region (Romania) point towards the interpretation that the lithospheric slab, descending beneath the SE-Carpathians, approaches a stage of break-off or even it is already delaminated from the crust. To understand processes of stress generation due to the descending slab, we analyse tectonic stress, induced by the slab sinking in the mantle, by means of analytical and numerical modelling. We find that the maximum shear stress migrates from the upper surface of the slab to its lower surface in the course of changes in slab dynamics from its active subduction through roll-back movements to sinking solely due to gravity. The changes in stress distribution can explain the location of hypocentres of Vrancea events at the side of the slab adjacent to the Eastern European craton. To analyse a process of slab delamination, we develop a twodimensional thermomechanical finite-element model of a slab sinking in the mantle due to gravity and overlain by the continental crust. The model predicts lateral compression in the slab as inferred from the stress axes of earthquakes and its thinning and necking. The maximum stress occurs in the depth range of 80 km to 200 km, and the minimum stress falls into the depth range of 40 km to 80 km. The area of maximum shear stress coincides with the region of high seismicity, and minimum shear stress in the model is associated with the lower viscosity zone. Uplift of the crust starts before the slab detachment. Just after the detachment the tectonic stress in the slab is still high enough to lead to a seismic activity, and the stress decreases significantly in several million years.