Miracle-dz/UniFAR-FTUs huggingface dataset:
An adaptive anonymous authentication for cloud environment

Preserving identity privacy is a significant challenge for the security in cloud services. Indeed, an important barrier to the adoption of cloud services is user fear of privacy loss in the cloud. One interesting issue from a privacy perspective is to hide user's usage behavior or meta-information which includes access patterns and frequencies when accessing services. Users may not want the cloud provider to learn which resources they access and how often they use a service by making them anonymous. In this paper, we will propose an adaptive and flexible approach to protect the identity privacy through an anonymous authentication scheme.
THE USE OF MODEL CONSTRAINTS AS IMPRECISE SOFTWARE TEST ORACLES

Many software test generation techniques target on generating software test data. Only a few of them provide automatic way to verify if software behaves correctly using generated test data. We propose a testing technique, which uses UML modeling language extension OCL as imprecise test oracle. Imprecise OCL constraints can be viewed as expressions which define expected results within some ranges of possible values. When software is executed using generated test data the output is verified against imprecise OCL constraints. If output invalidates imprecise OCL constraints, a tester can assume with some probability that software has bugs.
Assessment of consonant articulation in glossectomee speech by dynamic MRI

For the speech ability assessment of glossectomee patients, dynamic MRT was used in order to obtain real time imaging of articulatory movements. At the present state, the method is best suited for continuous consonants, but it can be used for the evaluation of any speech sound. In this study, preand postoperative consonant articulation of eight patients with cancer of the oral cavity is compered by means of acoustic analysis and real-time MRI.
Use of physical modelling to study how to increase the production capacity by implementing a novel oblong AOD converter

There is no known example of an AOD converter with oblong cross sections in the literature. Changing the geometry of the converter vessel, from the traditional circular cross sections, to increase converter volume could potentially influence the performance of the converter and in particular the decarburisation rate. To study the feasibility of implementing an oblong converter, physical modelling was used to study the fluid flow of the proposed converter configuration, geometry and number of tuyeres, and the potential influence on the decarburisation rate. Two water models were employed using water containing NaOH and gas injected through six or eight tuyeres as fluids. In the model, CO2 gas was injected and the reaction of CO2 and NaOH was indirectly measured by detecting the pH value of the water. The mixing time is considered to be a good indicator of the decarburisation as kinetics will be diffusion controlled in the latter period of the process. The following three configurations were studied: (i) a circular converter with six tuyeres, (ii) an oblong converter with six tuyeres, and (iii) an oblong converter with eight tuyeres. The mixing time can be used to evaluate the different converter configurations. The average CO2 concentrations based on several experiments, differed by less than 5% between the circular and oblong models after 165 s of injection of air and CO2. The results also showed that no difference in mixing time could be found when using 6 and 8 tuyeres, respectively in the oblong model, where the CO2 concentrations differed by less than 2% after 165 s of injection time of air and CO2. Based on the findings, it has been observed that the influence of converter geometry on mixing time is small, it was concluded that decarburisation rate is likely to be the same irrespectively of converter geometry.
Vehicle lateral and longitudinal velocity estimation based on Adaptive Kalman Filter

In order to meet the requirements of lateral velocity (vy) and longitudinal velocity (vx) in vehicle active safety control systems, and to modify the impact of noise change on the estimation accuracy, a novel method based on Adaptive Kalman Filter (AKF) is proposed for estimation of vy and vx in this paper by updating the mean and covariance of noise online. This method is evaluated under a variety of driving conditions and the estimation values are compared with simulator values from CarSim. The results demonstrate that the proposed method is robust and can improve the estimation accuracy of vy and vx.
A novel interface paradigm for supporting product design

This work presents the design and implementation of an interactive free-form 3D sketching paradigm to support creative designs. This work builds on advances in a large number of related technologies such as multi-screen displays, constraint-based assembly modelling, deformable modelling and state-of-the-art multi-sensory interfaces. This work presents the current design and implementation features of the proposed design paradigm.
Sequential amplitude estimation in multiuser communications

The authors consider the problem of multiuser amplitude estimation, i.e., the problem of estimating the amplitudes of several digital communications signals superimposed in the same channel. This problem is of importance in communications environments such as spread-spectrum radio networks, in which nonorthogonal multiplexing is used. Multiuser amplitude estimation is a critical prerequisite to the optimum demodulation of such signals using, for example, Verdu's algorithm. Here, a sequential detection-estimation approach to this problem is adopted, and several estimation paradigms are considered, including the method of moments and likelihood-based estimators. The consistency, asymptotic variance, and complexity of these estimators are examined. It is seen that detector-estimators that use these estimators in Verdu's algorithm result, asymptotically, in (known-amplitude) optimum error probabilities, with little relative increase in complexity per demodulated bit. <<ETX>>
Models for microquasars

I review current models used to interpret the spectra and variability of microquasars. Among other things, I discuss the structure of the accretion flow and its dependence on mass accretion rate, the intrinsic connection between hot comptonizing corona and compact radio jet in the hard state, as well as possible models for the spectral hysteresis observed during outbursts of transient sources. Finally I comment on several models for the non-poissonian X-ray noise in black hole binaries which, at least in some instances, is suspected to be associated with some form of coupling between disc and jet activity.
Isometric Embedding of Facial Surfaces into S 3

The problem of isometry-invariant representation and comparison of surfaces is of cardinal importance in pattern recognition applications dealing with deformable objects. Particularly, in threedimensional face recognition treating facial expressions as isometries of the facial surface allows to perform robust recognition insensitive to expressions. Isometry-invariant representation of surfaces can be constructed by isometrically embedding them into some convenient space, and carrying out the comparison in that space. Presented here is a discussion on isometric embedding into S, which appears to be superior over the previously used Euclidean space in sense of the representation accuracy.
Atomic force microscopy dynamic modes for the quantification of nanomechanical properties: From polymers to membrane proteins

The thesis focused on the development of new AFM techniques for the quantification of nanomechanical properties of different materials in air and liquid environments. A novel AFM technique, bimodal AFM, was implemented to determine and record the elastic modulus and viscosity maps of membrane proteins, biomolecules and polymers with atomic and molecular resolution. Other AFM techniques were applied to study the mechanical properties of proteins by means of the protein stress-strain curve at the nanoscale.
Critical assessment of methods of protein structure prediction (CASP) — round x

This article is an introduction to the special issue of the journal PROTEINS, dedicated to the tenth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. The 10 CASP experiments span almost 20 years of progress in the field of protein structure modeling, and there have been enormous advances in methods and model accuracy in that period. Notable in this round is the first sustained improvement of models with refinement methods, using molecular dynamics. For the first time, we tested the ability of modeling methods to make use of sparse experimental three‐dimensional contact information, such as may be obtained from new experimental techniques, with encouraging results. On the other hand, new contact prediction methods, though holding considerable promise, have yet to make an impact in CASP testing. The nature of CASP targets has been changing in recent CASPs, reflecting shifts in experimental structural biology, with more irregular structures, more multi‐domain and multi‐subunit structures, and less standard versions of known folds. When allowance is made for these factors, we continue to see steady progress in the overall accuracy of models, particularly resulting from improvement of non‐template regions. Proteins 2014; 82(Suppl 2):1–6. © 2013 Wiley Periodicals, Inc.
Human Neuroscience

Performing an action with an object involves different spatial transformations, such as coding the location of an object, generating a movement plan to grasp the object, and specifying the fi nal posture the effectors will take after the movement. Behavioral studies suggest an automatic activation of low-level motor programs when objects are perceived (Tucker and Ellis, 2001). In addition, several studies have shown that the mere observation of object pictures or names referring to objects results in the activation of premotor and inferior parietal brain areas (Grafton et al. These brain areas are likely involved in the visuo-motor transformations required for grasping that are mediated by a fronto-parietal network (for review, see Andersen and Cui, 2009). Many studies have implicated a special role for the posterior parietal cortex (PPC) in sensorimotor integration. For instance, neurons in the anterior intraparietal sulcus (AIP) are selectively involved in coding specifi c types of grasps directed at objects of a particular size, shape and orientation (Murata et al., 2000). In addition, the parietal reach region is involved in planning reaching movements and the lateral intraparietal area (LIP) plans upcoming saccadic eye movements (Cohen and Andersen, 2002). Interestingly, neuronal activity in these regions represents upcoming actions in a common eye-centered reference frame (Batista et al., 1999) and is primarily related to the type of movement being planned (i.e. the action intention; Snyder et al., 1997). The PPC contains massive connections to frontal lobe areas, such as the frontal eye fi eld and the premotor cortex, thereby enabling the planning and control
Model checking performability properties

Model checking has been introduced as an automated technique to verify whether functional properties, expressed in a formal logic like computational tree logic (CTL), do hold in a formally-specified system. We present a number of computational procedures to perform model checking of continuous stochastic reward logic (CSRL) over finite Markov reward models, thereby stressing their computational complexity (time and space) and applicability from a practical point of view (accuracy, stability). A case study in the area of ad hoc mobile computing under power constraints shows the merits of CSRL and the new computational procedures.
Analyzing Engineering Design through the Lens of Computation

Learning analytics and educational data mining are introducing a number of new techniques and frameworks for studying learning. The scalability and complexity of these novel techniques has afforded new ways for enacting education research and has helped scholars gain new insights into human cognition and learning. Nonetheless, there remain some domains for which pure computational analysis is currently infeasible. One such area, which is particularly important today, is open-ended, hands-on, engineering design tasks. These open-ended tasks are becoming increasingly prevalent in both K–12 and post-secondary learning institutions, as educators are adopting this approach in order to teach students real-world science and engineering skills (e.g., the “Maker Movement”). This paper highlights findings from a combined human–computer analysis of students as they complete a short engineering design task. The study uncovers novel insights and serves to advance the field’s understanding of engineering design patterns. More specifically, this paper uses machine learning on hand-coded video data to identify general patterns in engineering design and develop a fine-grained representation of how experience relates to engineering practices. Finally, the paper concludes with ideas on how the specific findings from this study can be used to improve engineering education and the nascent field of “making” and digital fabrication in education. We also discuss how human–computer collaborative analyses can grow the learning analytics community and make learning analytics more central to education research.
Development of Electrical Impedance Methods for 3D Cell Cultures

We present a universal protocol for quick and reproducible conductivity determinations in bioapplications using electrochemical impedance spectroscopy (EIS), electrode modification and automated spectral analysis. Two-terminal EIS measurements may be acquired using any standard impedance analyser adjusting the applied sinusoidal potential and frequency range for spectral analysis. An implemented Matlab algorithm displays the acquired spectra, automatically identifies the frequency at which the phase angle (φ) is closest to 0 and determines the impedance magnitude, i.e. the solution resistance (RS). The corresponding conductivity value is immediately calculated as the ratio of the conductivity cell constant ( ), determined based on calibration, and RS. This protocol eliminates the need for evaluating a specific equivalent circuit followed by non-linear regression based curve fitting that is generally required in EIS-based conductivity determinations. The protocol is applicable to conductivity determinations using different conductivity cell configurations in any electrolyte solution regardless of its composition, i.e. in solutions with or without electroactive species that give rise to faradaic interface impedance. Conducted measurements showed high reproducibility in good agreement with a commercial conductometer in a wide range of ionic strengths up to five times that of physiological PBS. Since measurements in cell culture medium with bare gold electrodes indicated the need for recalibration to counteract the effect of biomolecule physisorption, the validity of the protocol was further extended using a protein-repellent coating of poly(ethylene glycol) methyl ether thiol self-assembled monolayer. This effectively eliminated electrode fouling, facilitating high reproducibility in repeated conductivity determinations in the presence of proteins. © 2015 Elsevier B.V. All rights reserved.
Plasma 25-Hydroxyvitamin D and 1,25-Dihydroxyvitamin D and Risk of Breast Cancer

Several lines of evidence suggest that vitamin D may reduce incidence of breast cancer, but few epidemiologic studies have addressed the relation of plasma vitamin D metabolites to the risk of this disease. We prospectively examined the relationship between plasma levels of 25-hydroxyvitamin D [25(OH)D] and 1,25-dihydroxyvitamin D [1,25(OH)2D] and risk of breast cancer in a case-control study nested within the Nurses' Health Study cohort. Blood samples were collected from study participants in 1989-1990. Breast cancer cases developing between blood collection and June 1, 1996, were matched to cancer-free controls on the basis of age, menopausal status, and other factors. Stored plasma samples from 701 cases and 724 controls were available for metabolite analysis. Cases had a lower mean 25(OH)D level than controls (P = 0.01), but mean 1,25(OH)2D levels were similar (P = 0.49). High levels of both metabolites were associated with a nonsignificant lower risk of breast cancer. Women in the highest quintile of 25(OH)D had a relative risk of 0.73 (95% confidence interval = 0.49-1.07; Ptrend = 0.06) compared with those in the lowest quintile. For 1,25(OH)2D, the comparable relative risk was 0.76 (95% confidence interval = 0.52-1.11; Ptrend = 0.39). For both metabolites, the association was stronger in women ages 60 years and older, but results were not statistically significant. Our findings suggest that high levels of 25(OH)D, and perhaps 1,25(OH)2D, may be modestly associated with reduced risk of breast cancer.
Modular and Hierarchical Modelling Concept for Large Biological Petri Nets Applied to Nociception

Here, we introduce a modular and hierarchical modeling concept for large biological Petri nets. This modeling concept suggests representing every functional system component of a molecular network by an autonomous and self-contained Petri net, so-called module. Due to the specific architecture of the modules, they need to fulfill certain properties important for biological Petri nets to be valid. The entire network is build-up by connecting the modules via common places corresponding to shared molecular components. The individual modules are coupled in a way that the structural properties that are common to all modules apply to the composed network as well. We applied this modeling concept on nociceptive signaling in DRG-neurons to compose a model describing pain on a molecular level for the first time. We verified the applicability of our modeling concept for very complex components and confirmed preservation of the properties after module coupling.
Performance evaluation of the manhattan mobility model in vehicular ad-hoc networks for high mobility vehicle

Vehicular ad-hoc network is a part of MANET in which the road topology and traffic regulations must take into considerations for the movement factors. VANET is supported by fixed infrastructure in a crucial points which can help with a few services, such as a warning messages. It also can connect the network to stationary network. The Manhattan mobility model is a mobility model that can generate the map pattern of the Manhattan city, which resembles a complex traffic. In this model, there is a Traffic Light Model (TLM) algorithm that can control the mobile node movement in intersection. In this work, we evaluate the implementation based on NS-2.34 for an application to control the packet data sending. VanetMobiSim 1.1 is used as an application to generate the movement model from the Manhattan mobility model. The simulation result shows that the end to end delay depends on the node congestion, average hop in one route and congestion window. The results shows that the Manhattan mobility model can reach 140 ms end to end delay on 190 m wireless range. The packet delivery ratio of Manhattan mobility model can reach the value of between 90% - 99% in 190 m wireless range. The average number of hop is between 2.5 - 5 in the 150 m wireless range. Using this model, the throughput which can be achieved is almost 12 kbps.
Object-based and image-based object representations

An overview is presented of object-based and image-based representations of objects by their interiors. The representations are distinguished by the manner in which they can be used to answer two fundamental queries in database applications: (1) Feature query: given an object, determine its constituent cells (i.e., their locations in space). (2) Location query: given a cell (i.e., a location in space), determine the identity of the object (or objects) of which it is a member as well as the remaining constituent cells of the object (or objects). Regardless of the representation that is used, the generation of responses to the feature and location queries is facilitated by building an index (i.e., the result of a sort) either on the objects or on their locations in space, and implementing it using an access structure that correlates the objects with the locations. Assuming the presence of an access structure, implicit (i.e., image-based) representations are described that are good for finding the objects associated with a particular location or cell (i.e., the location query), while requiring that all cells be examined when determining the locations associated with a particular object (i.e., the feature query). In contrast, explicit (i.e., object-based) representations are good for the feature query, while requiring that all objects be examined when trying to respond to the location query. The goal is to be able to answer both types of queries with one representation and without possibly having to examine every cell. Representations are presented that achieve this goal by imposing containment hierarchies on either space (i.e., the cells in the space in which the objects are found), or objects. In the former case, space is aggregated into successively larger-sized chunks (i.e., blocks), while in the latter, objects are aggregated into successively larger groups (in terms of the number of objects that they contain). The former is applicable to image-based interior-based representations of which the space pyramid is an example. The latter is applicable to object-based interior-based representations of which the R-tree is an example. The actual mechanics of many of these representations are demonstrated in the VASCO JAVA applets found at http://www.cs. umd.edu/˜hjs/quadtree/index.html.
Evaluating Universal Quantification in XML

Queries posed to database systems often involve universal quantification. Such queries are typically expensive to evaluate. Although they can be handled by basic access methods, for selection, grouping, and so forth, new access methods specifically tailored to evaluate universal quantification can greatly decrease the computational cost. In this paper, we study the efficient evaluation of universal quantification in an XML database. Specifically, we develop a small taxonomy of universal quantification types and define a family of algorithms suitable for handling each. We experimentally demonstrate the performance benefits of the new family of algorithms.
P-cresylsulphate, the main in vivo metabolite of p-cresol, activates leucocyte free radical production.

BACKGROUND Chronic renal insufficiency is associated with the retention of solutes normally excreted by healthy kidneys. P-cresol, a prototype protein-bound uraemic retention solute, has been shown to exert toxic effects in vitro. Recently, however, it has been demonstrated that p-cresol in the human body is conjugated, with p-cresylsulphate as the main metabolite. METHODS The present study evaluates the effect of p-cresylsulphate on the respiratory burst activity of leucocytes. RESULTS P-cresylsulphate significantly increased the percentage of leucocytes displaying oxidative burst activity at baseline. Oxidative burst activity of stimulated leucocytes was however not affected. In contrast, p-cresol had no effect on the leucocytes at baseline, but inhibited leucocytes burst activity after stimulation. CONCLUSION The present study demonstrates, for the first time, that p-cresylsulphate, the main in vivo metabolite of p-cresol, has a pro-inflammatory effect on unstimulated leucocytes. This effect could contribute to the propensity to vascular disease in the uraemic population.