Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-Related Differences in Plausibility-Checking Strategies During Arithmetic Problem Verification Tasks.

OBJECTIVES We examined whether older adults use plausibility-checking strategies while verifying arithmetic problems. We also tested trial-to-trial modulations of plausibility-checking strategies, and aging effects on these sequential modulations. METHOD We asked young and older adults to verify arithmetic problems that violated or respected arithmetic rules (i.e., 5×16 = 87. True/False? ). RESULTS Both young and older adults solved problems violating parity rule and five rule more quickly than problems violating no rule. We also found that both age groups had better performance when both five rule and parity rule are violated than when only one or no rules are violated. These results suggest age invariance in using rule-violation checking strategies and a smaller, but still efficient, strategy combination in older adults. Finally, for young adults only, strategy combination was larger following problems violating rules than after problems respecting rules. DISCUSSION These findings have important implications regarding mechanisms underlying age-related differences in using rule-violation checking strategies to verify arithmetic problems and in combining two strategies into a single, more efficient one.
Enhancing FreeLing Rule-Based Dependency Grammars with Subcategorization Frames

Despite the recent advances in parsing, significant efforts are needed to improve the current parsers performance, such as the enhancement of the argument/adjunct recognition. There is evidence that verb subcategorization frames can contribute to parser accuracy, but a number of issues remain open. The main aim of this paper is to show how subcategorization frames acquired from a syntactically annotated corpus and organized into fine-grained classes can improve the performance of two rulebased dependency grammars.
Driving simulator fidelity and training effectiveness

This paper elaborates on the role of fidelity on the effectiveness of simulation-based driver training. The use of visual stereo presentations in driving simulators is used as a case study. A literature review indicates that a stereo presentation is associated with possible advantages and disadvantages. Possible advantages are that it can provide a relevant cue for near-distant driving tasks, induce positive reactions amongst participants, improve validity and credibility of data, improve performance and learning, and create new possibilities for augmented stereo instructions. Possible disadvantages are that it can increase costs, increase simulator sickness, increase distraction, and induce performance reduction in case of display artefacts. Additionally, complicating factors due to the complexity of human perception, human psychology, and individual differences, make it difficult to predict effects of fidelity on training outcome. It is concluded that changes in fidelity ambiguously affect training effectiveness. Exploitation of non-fidelity aspects, such as the didactical possibilities of driving simulators, might be a more obvious means of improving training.
A neural network application for attack detection in computer networks

This work presents a network intrusion detection method, created to identify and classify illegitimate information in TCP/IP packet payload based on the Snort signature set that represents possible attacks to a network. For this development, a type of neural network named Hamming net was used. The choice of this network is based on the interest to investigate its adequacy to classify network events in real-time, due to its capability to learn faster than other neural network models, such as, multilayer perceptrons with backpropagation and Kohonen maps. A Hamming net does not require exhaustive training to learn. TCP/IP packet payloads were used as input pattern to the Hamming net and Snort signature as exemplar patterns. The challenges faced in modeling the input and exemplar data and the strategies adopted to capture and scan relevant data in TCP/IP packets and in Snort signatures are described in this paper. In addition, the application architecture, the processing stages and some test results are presented.
La géothermie profonde « n’est pas mature » : parcours d’une formule-argument à l’Eurométropole de Strasbourg

Les enquetes publiques realisees dans l’Eurometropole de Strasbourg au printemps 2015 au sujet de quatre projets de geothermie profonde ont cristallise une vive controverse. Les opposants avancaient comme argument – entre autres – que la (technologie de la) geothermie profonde « n’est pas mature ». L’expression, empruntee au discours d’un scientifique, circule dans differents textes relatifs aux enquetes publiques. Cet article analyse le parcours et les enjeux de l’expression qui devient une formule-argument.
A Qualitative Interview Study Investigating the Role of Transport Information Systems in Road Haulage Firms

Recent advances in mobile and wireless technology have made possible new types of information systems supporting key activities in transport organizations. By including mobile actors and equipment, such technology is a key enabler for realizing the vision of enterprise system support in this context. This paper focuses on a particular type of transport organization, that of road haulage firms. The term Transport Information Systems (TIS) is used to discuss a specific type of enterprise technology, incorporating support for critical mobile aspects of road haulage firms and relevant functionality of conventional enterprise systems. To capture expectations of enterprise support in road haulage business, a qualitative interview study including 18 Swedish road haulage firms was performed. Building on the results of the study, this paper contributes a set of sociotechnical challenges important for successful implementation of TIS in road haulage firms. In addition, this paper outlines implications for future research on enterprise systems in transport
A Survey On Various Defense Mechanisms Against Application Layer Distributed Denial Of Service Attack

The severity of application layer Distributed Denial of Service attack has become a major threat to network operators nowadays. Application layer Distributed Denial of Service attack causes unavailability of resources, revenue loss, and customer churns etc and is one of the most difficult problems to defend against in the internet. The goal of paper is to understand various techniques proposed recently to defend against specifically application layer Distributed Denial of Service attack. The next step in the path would be to come up with a better solution to solve this problem. Undoubtedly the following discussed techniques are extremely good. A collaborative approach using few of them can be a better solution. Keywords-component; DDoS (Distributed Denial of Service attack), Kalman filter, K-means,
Establishment of a Non-Invasive Semi-Quantitative Bioluminescent Imaging Method for Monitoring of an Orthotopic Esophageal Cancer Mouse Model

Orthotopic models of various types of tumors are widely used in anti-tumor therapeutic experiments in preclinical studies. However, there are few ways to appropriately monitor therapeutic effect in orthotopic tumor models, especially for tumors invisible from the outside. In this study we aimed to establish a non-invasive semi-quantitative bioluminescent imaging method of monitoring an orthotopic esophageal cancer mouse model. We confirmed that the TE8 esophageal cancer cell line implanted orthotopically into the abdominal esophagus of nu/nu mice (n = 5) developed not only a main tumor at the implanted site, but also local lymph node metastases and peritoneal disseminations within 6 weeks after inoculation. We established a TE8 cell line that stably expressed the firefly luciferase gene (TE8-Luc). We showed that TE8-Luc cells implanted subcutaneously into nu/nu mice (n = 5) grew over time until 5 weeks after inoculation. Tumor volume was strongly correlated with luminescent intensity emitted from the tumor, which was quantified using the IVIS imaging system. We then showed that TE8-Luc cells implanted orthotopically into the mouse abdominal esophagus (n = 8) also formed a tumor and that the luminescent intensity of such a tumor, as detected by IVIS, increased over time until 7 weeks after inoculation and was therefore likely to reflect tumor progression. We therefore propose that this orthotopic esophageal cancer model, monitored using the non-invasive semi-quantitative IVIS imaging system, will be useful for in vivo therapeutic experiments against esophageal cancer. This experimental setting is expected to contribute to the development of novel therapeutic technologies for esophageal cancer in preclinical studies.
Dynamic path planning and execution using B-Splines

This paper presents a technique for generating a continuous trajectory from a series of waypoints which represent a static path. Furthermore, a method is described for efficiently altering this trajectory in response to a dynamic environment. This is achieved by applying an interpolated B- spline to the waypoints which is only altered in the area local to the obstacle.
Regulation of Apoptosis by the Ft1 Protein, a New Modulator of Protein Kinase B/Akt

ABSTRACT The serine/threonine kinase protein kinase B (PKB)/Akt plays a central role in many cellular processes, including cell growth, glucose metabolism, and apoptosis. However, the identification and validation of novel regulators or effectors is key to future advances in understanding the multiple functions of PKB. Here we report the identification of a novel PKB binding protein, called Ft1, from a cDNA library screen using a green fluorescent protein-based protein-fragment complementation assay. We show that the Ft1 protein interacts directly with PKB, enhancing the phosphorylation of both of its regulatory sites by promoting its interaction with the upstream kinase PDK1. Further, the modulation of PKB activity by Ft1 has a strong effect on the apoptosis susceptibility of T lymphocytes treated with glucocorticoids. We demonstrate that this phenomenon occurs via a PDK1/PKB/GSK3/NF-ATc signaling cascade that controls the production of the proapoptotic hormone Fas ligand. The wide distribution of Ft1 in adult tissues suggests that it could be a general regulator of PKB activity in the control of differentiation, proliferation, and apoptosis in many cell types.
Adaptively quadratic (AQua) image interpolation

Image interpolation is a key aspect of digital image processing. This paper presents a novel interpolation method based on optimal recovery and adaptively determining the quadratic signal class from the local image behavior. The advantages of the new interpolation method are the ability to interpolate directly by any factor and to model properties of the data acquisition system into the algorithm itself. Through comparisons with other algorithms it is shown that the new interpolation is not only mathematically optimal with respect to the underlying image model, but visually it is very efficient at reducing jagged edges, a place where most other interpolation algorithms fail.
Design control of DC/AC converter for a grid connected PV systems with maximum power tracking using Matlab/Simulink

Maximization of power from a solar photovoltaic module is of special interest as the efficiency of the solar PV module is very low. A peak power tracker is used for extracting the maximum power from the solar PV module. In the present work we analyze the design and the simulation of the maximum power point tracker (MPPT) for the solar PV array connected to three phase grid. In our studies, we conceived a PV system where the PV generator is the panel NA-901(WQ). The MPPT system has been tested on Solar PV Module (Micro-amorphous silicon thin-film) rated 90Wpeak at 49.3V, 1.83A at 25 degree Celsius and 1000W/m2 (STC). The simulation studies are carried out in MATLAB /SIMULINK.
Motion estimation using second order gradient methods

Gradient based motion estimation techniques (GM) are considered to be in the heart of state-of-the-art registration algorithms, being able to account for both pixel and subpixel registration and to handle various motion models (translation, rotation, affine, projective). These methods estimate the motion between two images using a first order Taylor expansion of the registered images. This paper offers two main contributions: First, we improve the convergence rate and range of the GM using a formulation based on a second order Taylor expansion. Second, we extend the second order algorithm using a symmetrical formulation which further improves the convergence properties. The results are verified by theoretical analysis and experimental trials.
A Peculiar Linear Radio Feature in the Supernova Remnant N206

We present images of the supernova remnant N206 in the Large Magellanic Cloud taken with the Australia Telescope Compact Array at wavelengths of 3 and 6 cm. Based on our data and previously published flux densities, the spectral index of N206 is -0.20 ± 0.07. The 6 cm radio morphology shows a filled center. Most interesting is the discovery of a peculiar linear feature previously undetected at any wavelength. The feature lies to the east of the center of the remnant, stretching from about to of the remnant's radius. It is wedge-shaped, with a steady opening angle from an apex on the eastern side. The feature resembles the disturbance expected from an object moving through the material supersonically at about 800 km s-1. We present arguments suggesting that the linear feature might have been produced by a low-mass star or compact object ejected from a binary system that may have led to a Type Ic supernova.
Design of Compensation Coils for EMI Suppression in Magnetostrictive Linear Position Sensors

This paper presents recent development on magnetostrictive linear position sensors (MLPS). A new compensation coil structure improves the EMI suppression and accuracy considerably. Furthermore, experimental results indicate that the new structure can improve the accuracy to ±0.13 mm nearly double the ±0.2 mm obtained with traditional structures. As another design continuation after the differential waveguide structure, this new structure is a practical and reliable implementation technique for the commercialization of MLPS.
Effect of Internal Flows on Sunyaev-Zeldovich Measurements of Cluster Peculiar Velocities

Galaxy clusters are potentially powerful probes of the large-scale velocity field in the universe because their peculiar velocity can be estimated directly via the kinematic Sunyaev-Zeldovich effect (kSZ). Using high-resolution cosmological simulations of an evolving cluster of galaxies, we evaluate how well the average velocity obtained via a kSZ measurement reflects the actual cluster peculiar velocity. We find that the internal velocities in the intracluster gas are comparable to the overall cluster peculiar velocity: 20%-30% of the sound speed even when a cluster is relatively relaxed. Nevertheless, the velocity averaged over the kSZ map inside a circular aperture matched to the cluster virial region provides an unbiased estimate of a cluster's radial peculiar velocity with a dispersion of 50-100 km s-1, depending on the line of sight and dynamical state of the cluster. This dispersion puts a lower limit on the accuracy with which cluster peculiar velocity can be measured. Although the dispersion of the average is relatively small, the velocity distribution is broad; regions of low signal must be treated with care to avoid bias. We discuss the extent to which systematic errors might be modeled and the resulting limitations on using galaxy clusters as cosmological velocity tracers.
Joint lp- and l2,p-norm minimization for subspace clustering with outlier pursuit

In most sparse coding based subspace clustering problems, using the non-convex lp-norm minimization (0 <; p <; 1) can often deliver better results than using the convex l1-norm minimization. In this paper, we propose a sparse subspace clustering via joint lp-norm and l2,p-norm minimization, where the lp-norm imposed on sparse representations can achieve more sparsity for clustering while l2,p-norm imposed on reconstructed error can handle outlier pursuit. We also propose an iterative solution to solve the proposed problem based on Iterative Shrinkage/Thresholding (IST) method. In addition, to the best knowledge, utilizing IST for solving l2,p-norm minimization problem can be the first work in our paper and there is no such work before. Finally, to demonstrate the improved performance of the proposed method, comparative study was performed on benchmark problems of image clustering. Thoroughly experimental studies on real world datasets show that the method can significantly outperform other state-of-the-art methods.
Ferroelectric Rashba semiconductors as a novel class of multifunctional materials

The discovery of novel properties, effects or microscopic mechanisms in modern materials science is often driven by the quest for combining, into a single compound, several functionalities: not only the juxtaposition of the latter functionalities, but especially their coupling, can open new horizons in basic condensed matter physics as well as in technology. Semiconductor spintronics makes no exception. In this context, we have discovered by means of density-functional simulations that, when a sizeable spin-orbit coupling is combined with ferroelectricity, such as in GeTe, one obtains novel multifunctional materials - called Ferro-Electric Rashba Semi-Conductors (FERSC) - where, thanks to a giant Rashba spin-splitting, the spin texture is controllable and switchable via an electric field. This peculiar spin-electric coupling can find a natural playground in small-gap insulators, such as chalcogenides, and can bring brand new assets into the field of electrically-controlled semiconductor spintronics.
The La Bastida fortification: new light and new questions on Early Bronze Age societies in the western Mediterranean

Recent excavations at La Bastida in south-eastern Spain have revealed an impressive stone-built fortification system dating to 2200–2100 cal BC that protected one of the main economic and political centres of Argaric Early Bronze Age society. It consists of parallel walls with projecting towers flanking a narrow entrance passage. The defensive character of these structures appears beyond question and their design suggests they were a response to significant changes in warfare and weaponry in this period. This sophisticated fortification system raises once again the question of possible Mediterranean contacts, along with social change and the role of physical violence in the rise of Argaric society.
Scaling relationships based on partition coefficients and body sizes have similarities and interactions

The LC50 of compounds with a similar biological effect, at a given exposure period, is frequently plotted log–log against the octanol–water partition coefficient and a straight line is fitted for interpolation purposes. This is also frequently done for physiological properties, such as the weight-specific respiration rate, as function of the body weight of individuals. This paper focuses on the remarkable observation that theoretical explanations for these relationships also have strong similarities. Both can be understood as result of the covariation of the values of parameters of models of a particular type for the underlying processes, while this covariation follows logically from the model structure. The one-compartment model for the uptake and elimination of compounds by organisms is basic to the BioConcentration Factor (BCF), or the partition coefficient; the standard Dynamic Energy Budget model is basic to the (ultimate) body size. The BCF is the ratio of the uptake and the elimination rates; the maximum body length is the ratio of the assimilation (i.e. uptake of resources) and the maintenance (i.e. use of resources) rates. This paper discusses some shortcomings of descriptive approaches and conceptual aspects of theoretical explanations. The strength of the theory is in the combination of why metabolic transformation depends both on the BCF and the body size. We illustrate the application of the theory with several data sets from the literature. †Presented at the 12th International Workshop on Quantitative Structure–Activity Relationships in Environment Toxicology (QSAR2006), 8–12 May 2006, Lyon, France.
Green extension of OpenFlow

Today's network architectures are not able to cope with the Future Internet requirements, as they are too inefficient, power hungry, and ossified on the TCP/IP paradigm. In order to promote a viable evolution towards new protocols and paradigms, modern network routers should become programmable to allow a flexible management of both traffic flows and power states. In this respect, Software Defined Networking (SDN) can represent the perfect support for the allocation of traffic flows and, at the same time, the management of the power states of the single nodes. To this purpose, this paper proposes to use the Green ion Layer (GAL) to integrate the exchange of power management data among network elements and the application of control strategies inside the SDN paradigm. Moreover, in order to clarify how our study would help overcoming scalability issues and promote energy efficiency at the same time, this paper defines and solves a consolidation problem where the network is described in terms of allocation of packet handling resources and power states.
Estimating ToE Risk Level Using CVSS

Security management is about calculated risk and requires continuous evaluation to ensure cost, time and resource effectiveness. Parts of which is to make future-oriented, cost-benefit investments in security. Security investments must adhere to healthy business principles where both security and financial aspects play an important role. Information on the current and potential risk level is essential to successfully trade-off security and financial aspects. Risk level is the combination of the frequency and impact of a potential unwanted event, often referred to as a security threat or misuse. The paper presents a risk level estimation model that derives risk level as a conditional probability over frequency and impact estimates. The frequency and impact estimates are derived from a set of attributes specified in the Common Vulnerability Scoring System (CVSS). The model works on the level of vulnerabilities (just as the CVSS) and is able to compose vulnerabilities into service levels. The service levels define the potential risk levels and are modelled as a Markov process, which are then used to predict the risk level at a particular time.