Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Visual Analysis of Complex Scientific Data as Families of Data Surfaces

The widespread use of computational simulation in science and engineering provides challenging research opportunities. Multiple independent variables are considered and large and complex data are computed, especially in the case of multi-run simulation. Classical visualization techniques deal well with 2D or 3D data and also with time-dependent data. Additional independent dimensions, however, provide interesting new challenges. We present an advanced visual analysis approach that enables a thorough investigation of families of data surfaces, i.e., datasets, with respect to pairs of independent dimensions. While it is almost trivial to visualize one such data surface, the visual exploration and analysis of many such data surfaces is a grand challenge, stressing the users' perception and cognition. We propose an approach that integrates projections and aggregations of the data surfaces at different levels (one scalar aggregate per surface, a 1D profile per surface, or the surface as such). We demonstrate the necessity for a flexible visual analysis system that integrates many different (linked) views for making sense of this highly complex data. To demonstrate its usefulness, we exemplify our approach in the context of a meteorological multi-run simulation data case and in the context of the engineering domain, where our collaborators are working with the simulation of elastohydrodynamic (EHD) lubrication bearing in the automotive industry.
Guilt by Design: Structuring Organizations to Elicit Guilt as an Affective Reaction to Failure

In this article, we outline a model of how organizations can effectively shape employees’ affective reactions to failure. We do not suggest that organizations eliminate the experience of negative affect following performance failures—instead, we propose that they encourage a more constructive form of negative affect guilt instead of a destructive one shame. We argue that guilt responses prompt employees to take corrective action in response to mistakes, whereas shame responses are likely to elicit more detrimental effects of negative affect. Furthermore, we suggest that organizations can play a role in influencing employees’ discrete emotional reactions to the benefit of both employees and the organization. We describe the necessary antecedents for encouraging guilt responses without simultaneously eliciting shame. In essence, employees are more likely to experience guilt but not shame if they feel they had control over a specific negative event and the event resulted in a negative outcome for others. Given these necessary preconditions, we identify a set of organizational characteristics—autonomy, specificity of performance feedback, and outcome interdependence—that can be modified to make the experience of guilt more likely than that of shame in the workplace. The ethical and practical limits of shaping employees’ emotional experiences within a negative affective domain are also addressed.
Globalised tuberculosis control in local worlds

Despite a steady global decline in the incidence of tuberculosis (TB), progress towards health targets has been slow and a crisis of drug-resistant strains of TB continues unabated. The United Nations high-level meeting on TB in September 2018 resulted in a renewed push to invest in drugs, diagnostics and vaccines to “reach” those most vulnerable to the disease. Yet, an overriding focus on biomedical technologies to manage TB at the expense of meaningful engagement with the social threatens to further consolidate its reputation as a “silent killer. ” Drawing on anthropological contributions from South Africa and one from neighbouring Zimbabwe, this special issue explores how human action produces, shapes, names, experiences and resists the disease in its fullest breadth within local conditions. The articles recognise TB as a “global” object of biomedical knowledge and intervention, on the one hand, and as intricately tied to a legacy of colonial and apartheid governance, on the other. Each article deals with different aspects of understanding the interface between global and national policies and their unintended effects in local worlds.
Controlling of Quadrotor UAV Using a Fuzzy System for Tuning the PID Gains in Hovering Mode

The studies in UAV modeling and control have been increased rapidly recently. This paper presents the modeling and control of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as quadrotor aircraft. The modeling of the quadrotor will be described by using Euler-Newton equations. In order to stable the quadrotor and control the attitude of that, classical PID controller and a fuzzy system that adjusts the PID controller gains, have been designed. Although fuzzy control of various dynamical systems has been presented in literature, application of this technology to quadrotor helicopter control is quite new. A quadrotor has nonlinear characteristics where classical control methods are not adequate for stabilize that. On the other hand, fuzzy control is nonlinear and it is thus suitable for nonlinear system control. Matlab Simulink has been used to test, analyze and compare the performance of the controllers in simulations. This study showed that although, both of the classical PID and the fuzzy self-tuning PID controllers, can control the system properly, the second controller performed better than the classical PID controller. Key words—Quadrotor, Fuzzy control, Modeling, Attitude control, PID controller, MATLAB / Simulink .
A modified direction feature for cursive character recognition

This paper describes a neural network-based technique for cursive character recognition applicable to segmentation-based word recognition systems. The proposed research builds on a novel feature extraction technique that extracts direction information from the structure of character contours. This principal is extended so that the direction information is integrated with a technique for detecting transitions between background and foreground pixels in the character image. The proposed technique is compared with the standard direction feature extraction technique, providing promising results using segmented characters from the CEDAR benchmark database.
Applying Database Dependency Theory to Software Engineering

We describe the use of database dependency theory for investigating software designs. Dependency theory captures some of the essential constraints implicit in a system, and focuses attention on its update properties. The fundamental choice between redundancy and normalization is directly related to the issue of reuse. We show how dependency theory can be applied to the design of text editors and spreadsheet systems, and discuss its implications for object-oriented programming.
Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models

A key problem in computational neuroscience is to find simple, tractable models that are nevertheless flexible enough to capture the response properties of real neurons. Here we examine the capabilities of recurrent point process models known as Poisson generalized linear models (GLMs). These models are defined by a set of linear filters and a point nonlinearity and are conditionally Poisson spiking. They have desirable statistical properties for fitting and have been widely used to analyze spike trains from electrophysiological recordings. However, the dynamical repertoire of GLMs has not been systematically compared to that of real neurons. Here we show that GLMs can reproduce a comprehensive suite of canonical neural response behaviors, including tonic and phasic spiking, bursting, spike rate adaptation, type I and type II excitation, and two forms of bistability. GLMs can also capture stimulus-dependent changes in spike timing precision and reliability that mimic those observed in real neurons, and can exhibit varying degrees of stochasticity, from virtually deterministic responses to greater-than-Poisson variability. These results show that Poisson GLMs can exhibit a wide range of dynamic spiking behaviors found in real neurons, making them well suited for qualitative dynamical as well as quantitative statistical studies of single-neuron and population response properties.
Determination of APTT factor sensitivity – the misguiding guideline

The Clinical and Laboratory Standards Institute (CLSI) has produced a guideline detailing how to determine the activated partial thromboplastin time's (APTT) sensitivity to clotting factor deficiencies, by mixing normal and deficient plasmas. Using the guideline, we determined the factor sensitivity of two APTT reagents.
A π-calculus based model for web services composition

Composition of Web services into distributed applications recently becomes a hot topic in computer science. In this paper a pi-calculus based model for Web service composition is presented in which the event process, signal notification and construct of transaction are added. The operational semantics of the model is interpreted. Further the expressiveness of the model is discussed, and a typical case study is explored. Finally, some comments are made
Cancellation and Uncertainty Aversion on Limit Order Books

This paper models limit order books where each trader is uncertain of the underlying distribution in the asset's value to others. If this uncertainty is rapidly resolved, fleeting limit orders are submitted and quickly cancelled. This enhances liquidity supply, but leaves intact established comparative statics results on spreads. However, risk neutral liquidity suppliers are averse to persistent uncertainty due to concavity in the function describing limit order utility, and spreads widen. This helps explain wide spreads in the morning.The model describes traders who in equilibrium correctly anticipate market orders' endogenous stochastic intensities. It highlights how limit orders queue for execution.
Studying purchasing Behavior of Tunisian Olive Oil Consumers

This paper is, to our best knowledge, a first investigation of Tunisian olive oil consumer behaviour by the use of the conjoint analysis technique. A face to face questionnaire was designed and administered in Tunis City, to conduct the conjoint experiment with regard to the following attributes: olive oil type, taste, colour, packaging, region of origin, and price. Three econometric models were used in the analysis: Conditional Logit (CL), Ordered Logit (OL), and Rank Ordered Logit (ROL). Based on the models estimates, willingness to pay (WTP) for product attributes were evaluated. The main results indicate that OL model followed by ROL model show better estimates in comparison to the traditional CL model. Regarding the olive oil type, consumers have higher preferences for extra-virgin olive oil, followed by virgin and then olive pomace oil. Tunisian consumers have higher probabilities to buy a green coloured olive oil with strong flavoured taste. Consumers, however, were found to prefer buying bulk rather than bottled olive oil. The region of origin attribute did not show significant effect in consumers’ purchasing decision. WTP estimates indicate that consumers are willing to pay more than 2.5 dinars/litre (1.5 euro/litre) to switch from olive pomace oil to extra-virgin olive oil, and about 2 dinars/litre (1.13 euro/litre) to switch from olive pomace oil to virgin oil.
Design of a Robust Sliding Mode Controller using Multirate Output Feedback

This paper considers a robust sliding mode control scheme using multirate output feedback. Using different plant output rates including the former plant output information, sampling error at multiple sampling interval is considered to discrete-time output feedback control design. As a result, control performance can be improved. Meanwhile, the multirate output feedback can also guarantee closed-loop system stability.
Distribution of symptoms of attention deficit-hyperactivity disorder in schoolchildren of Shiraz, south of Iran.

BACKGROUND This study was conducted to study the prevalence rate of attention deficit hyperactivity disorder symptoms and differences between subtypes in school age children of Shiraz, south of Iran. METHODS A random sample of 2000 school age children from both genders was selected. A parent-completed, DSM-IV-referenced rating scale of attention deficit hyperactivity symptoms was used. RESULTS About 10.1% of participants obtained screening cutoff scores for attention deficit hyperactivity; 13.6% in boys and 6.5% in girls. The most common type of probable attention deficit hyperactivity in boys and girls was the hyperactive-impulsive type of attention deficit hyperactivity and the least frequent type was the combined type of attention deficit hyperactivity. CONCLUSION The rate of probable attention deficit hyperactivity in Shiraz, southern Iran is very similar to other counties and it is more common in boys than girls.
Preclinical Safety Evaluation of Intravenously Administered SAL200 Containing the Recombinant Phage Endolysin SAL-1 as a Pharmaceutical Ingredient

ABSTRACT Phage endolysins have received increasing attention as potent antibacterial agents. However, although safety evaluation is a prerequisite for the drug development process, a good laboratory practice (GLP)-compliant safety evaluation has not been reported for phage endolysins. A safety evaluation of intravenously administered SAL200 (containing phage endolysin SAL-1) was conducted according to GLP standards. No animals died in any of the safety evaluation studies. In general toxicity studies, intravenously administered SAL200 showed no sign of toxicity in rodent single- and repeated-dose toxicity studies. In the dog repeated-dose toxicity test, there were no abnormal findings, with the exception of transient abnormal clinical signs that were observed in some dogs when daily injection of SAL200 was continued for more than 1 week. In safety pharmacology studies, there were also no signs of toxicity in the central nervous and respiratory system function tests. In the cardiovascular function test, there were no abnormal findings in all tested dogs after the first and second administrations, but transient abnormalities were observed after the third and fourth administrations (2 or 3 weeks after the initial administration). All abnormal findings observed in these safety evaluation studies were slight to mild, were apparent only transiently after injection, and resolved quickly. The safety evaluation results for SAL200 support the implementation of an exploratory phase I clinical trial and underscore the potential of SAL200 as a new drug. We have designed an appropriate phase I clinical trial based on the results of this study.
Code-Grouping of Spectrally Phase Encoded OCDMA based on Walsh-Decomposition of Hadamard Codes

We propose a novel optical networking concept enabling the routing of groups of spectrally phase encoded (SPE) optical code division multiple access (OCDMA) signals. This code grouping is based on particular properties of the Hadamard sequences, i.e. the existence of a multiplicative basis based on Walsh sequences. We describe here how this code grouping concept permits groups of SPE codes to be passively "labeled" and routed as groups on the basis of those labels and provide simulation results demonstrating the process. The ability to deal with groups of codes has important implications for routing and for the overall signal obscurity provided by OCDMA.
Digital channel modeling and capacity calculation for multi-relay multi-hop wireless sensor networks

This paper presents a new approach for the channel capacity calculation of a multi-relay multi-hop communication system. For the channel model based on Markov chains theory, the exact formula for the channel capacity, which is expressed as a function of packet error rate and number of relays, is derived. The expression of the overall packet error rate is derived in its closed form. The presented theory is supported by numerical analysis.
Online Topic Evolution Modeling Based on Hierarchical Dirichlet Process

This paper presents a model based on Hierarchical Dirichlet Process (HDP), that automatically captures the evolutionary thematic patterns in texts. Our approach allows HDP to work in an online fashion, such that it can build an up-to-date model for new documents given the old model, without accessing historic data. Since exact calculation is infeasible, we turn to Gibbs sampling to carry out approximate posterior inference. After the topics are found, we can analyze the evolution relationships between time-adjacent topics. Experiments on a real world dataset (Reuters-21578) validate the effectiveness of the model quantitatively, showing its advantage over both OLDA and plain HDP in modeling topic evolution.
Flexible structured sparse representation for robust visual tracking

In this work, we propose a robust and flexible appearance model based on the structured sparse representation framework. In our method, we model the complex nonlinear appearance manifold and occlusions as a sparse linear combination of structured union of subspaces in a basis library consisting of multiple learned low dimensional subspaces and a partitioned occlusion template set. In order to enhance the discriminative power of the model, a number of clustered background subspaces are also added into the basis library and updated during tracking. With the Block Orthogonal Matching Pursuit (BOMP) algorithm, we show that the new structured sparse representation based appearance model facilitates the tracking performance compared with the prototype model and other state of the art tracking algorithms.
Image denoising based on steepest descent OMP and K-SVD

Noise suppression is one of the key problems in image processing. In recent years, sparse representation theory is applied in image denoising successfully. The primary idea is to denoise an image via over-complete dictionary trained by K-SVD algorithm based on OMP (Orthogonal Matching Pursuit) algorithm. This method receives good performance on the quality of image denoising but slow computation speed because of high computational complexity. In order to speed up the computation while keeping image quality. This paper discusses a denoising method via the adaptive over-complete dictionary trained from noisy image using improved K-SVD algorithm and the steepest descent OMP algorithm. In this work, we replace OMP with the steepest descent OMP. Simulation results show this method leads to a better balance between denoising quality and the computation speed, and can improve performance than other methods. The PSNR values are used to measure the denoising quality, and it has been proven the PSNR values can be increased by our method meanwhile the running time can also be reduced to some extent.
The Alexander and Jones Polynomials Through Representations of Rook Algebras

In the 1920's Artin defined the braid group in an attempt to understand knots in a more algebraic setting. A braid is a certain arrangement of strings in three-dimensional space. It is a celebrated theorem of Alexander that every knot is obtainable from a braid by identifying the endpoints of each string. Because of this correspondence, the Jones and Alexander polynomials, two of the most important knot invariants, can be described completely using the braid group. There has been a recent growth of interest in other diagrammatic algebras, whose elements have a similar topological flavor to the braid group. These have wide ranging applications in areas including representation theory and quantum computation. We consider representations of the braid group when passed through another diagrammatic algebra, the planar rook algebra. By studying traces of these matrices, we recover both the Jones and Alexander polynomials.
Estimating user interaction strength in online networks

Online networks like Facebook and BitTorrent are based on user interactions such as wall posts and content exchange. In such systems, user relationships can be used to enhance security and promote cooperation, but in order to be meaningful, these relationships should be based on user interaction strength instead of “binary” friendships. To date, several theoretical, centralized schemes for estimating user interaction strength have been proposed. Here we present the design, deployment, and analysis of the UISE scheme for User Interaction Strength Estimation for both centralized and decentralized online networks. Among the strong points of UISE is that it captures direct and indirect user interactions, that it scales with only partial information dissemination in decentralized systems, and that it provides disincentives for malicious user behaviors. We apply UISE to detect user interaction patterns based on wall posts in Facebook, which resemble those observed in the offline human society. We further apply UISE to online time estimation based on rendezvous as user interactions in Tribler, an online network for media and social applications like file sharing, streaming, and voting. We demonstrate the accuracy and scalability of UISE with different information dissemination protocols and user behaviors using simulations, emulations, and a real-world deployment.
Students mobility, gender and polycentrism in Europe

This paper underline the need for a more critical approach to classic understanding of the European spatial integration that give to much importance to the concepts of hierarchy and areas of influence. The study shows that the the student mobility between the cities is polycentric and balanced i.e. that no city or pair of city dominates the network of exchanges. In a European context where 61% of migrating students are female, this work highlights moreover the fact that migratory behaviour of females go further to questioning the neo-classic models of spatial mobility than do those of male students.
A cross-layer optimization design for implanted BAN communication system

Energy minimization is an important goal in implanted BAN communication system design, and cross-layer optimization is an available approach by optimizing parameters in different layers of OSI model, thus, the system could be energy efficient. In many state-of-the-art communication transceivers, RF and analog section can consume more energy compared to the digital part. In this paper, we establish a system level accurate energy consumption model and choose a suitable modulation scheme first; consider an accurate channel model for implanted BAN communication system design; analysis the relationship between PHY parameters and MAC parameters, then, a cross-layer optimization method for energy-efficient design is proposed. Simulation results reveal that adaptive duty cycle to minimize the energy consumption of the implanted BAN communication system is implemented based on accurate energy consumption model and channel model. Simulation results show relationship crossing layers and good performance on energy saving.
Modeling user's preference in folksonomy for personalized search

Personalized search based on the users' preference has been extensively studied in the field of information retrieval. As a typical representative of web2.0, social tagging not only allows users to better describe and manage web resources, but also provides a great opportunity for the personalized search research, since it contains abundant public personal information. In this paper we propose a user preferences model based on tag clustering. This model is inspired by the Data Field theory. It can depict users' different aspects of interests and dynamically generate users' preferences against different search queries. We apply this model in the data set of flickr. The final ranked pictures are the combination of keywords and users' preference matching. The experiment proves that our method is better than both non-personalization method and common personalization method.