Miracle-dz/UniFAR-FTUs huggingface dataset:
Enterobacter sakazakii Invasion in Human Intestinal Caco-2 Cells Requires the Host Cell Cytoskeleton and Is Enhanced by Disruption of Tight Junction

ABSTRACT Enterobacter sakazakii is an opportunistic pathogen that causes systemic bacteremia and meningitis with high mortality, and powdered infant formula is a frequent source of this bacterium. However, the mechanisms that this organism uses to invade and translocate through the intestinal barrier are unknown. Using Caco-2 epithelial cells, we were able to demonstrate penetration of E. sakazakii and to determine invasion-associated properties. We found that E. sakazakii entry and invasion were dependent on the exposure time and multiplicity of infection and required bacterial de novo protein synthesis but was independent of cell polarity in the presence of tight junctions. Moreover, the presence of actin filaments and microtubule structures was required, and disruption of the tight junction significantly enhanced the initial association with Caco-2 cells and the efficiency of invasion, which provides a possible explanation for the preferential occurrence of this infection in babies and neonates. This is the first description of E. sakazakii invasion of host intestinal cells, and our findings suggest that this emerging pathogen employs a novel invasion mechanism for development of systemic infection.
On the use of COSMO-SkyMed SAR data and Numerical Weather Models for interferometric DEM generation

The present study is aimed at investigating the potentialities of the COSMO/SkyMed (CSK) constellation for ground elevation measurement with particular attention devoted to the impact of the improved spatial resolution wrt the previous SAR sensors. Assuming no movement and successful orbital error removal, the main problem in height computation through InSAR techniques derives from the interferometric phase artifacts related to the interaction between microwave and the lower layers of the atmosphere (APS, Atmospheric Phase Screen). Different strategies can be adopted to filter out this signal, ranging from the exploitation of the well-known spatial and temporal statistics of the APS to the estimation of independent APS measurements through Numerical Weather Prediction (NWP) models. Their feasibility and the achievable accuracies are discussed here.
Assessment of work-integrated learning: comparison of the usage of a grading rubric by supervising radiographers and teachers

Professional work‐integrated learning (WIL) that integrates the academic experience with off‐campus professional experience placements is an integral part of many tertiary courses. Issues with the reliability and validity of assessment grades in these placements suggest that there is a need to strengthen the level of academic rigour of placements in these programmes. This study aims to compare the attitudes to the usage of assessment rubrics of radiographers supervising medical imaging students and teachers supervising pre‐service teachers.
Transactions a la carte - Implementation and Performance Evaluation of Transactional Support on Top of Amazon S3

Most providers of Cloud-based database services favor availability and processing performance over consistency and hence provide only limited transaction support. Guaranteeing strict consistency is left to application developers. In this paper, we present a flexible transactional framework built on top of Amazon S3. It is intended for processing structured data under consideration of user-defined ACID guarantees ranging from non-transactional data querying and updating to full transactional data processing ensuring strict ACID properties. It supports the development of Cloud-based database applications without explicitly writing code for transactions. Instead, transactional semantics are weaved-in automatically using aspect-oriented programming techniques. In this way, application developers as well as end-users profit from transactional guarantees without having to care about them.
Correlated energy landscape model for finite, random heteropolymers.

In this paper, we study the role of correlations in the energy landscape of a finite random heteropolymer by developing the mapping onto the generalized random energy model ~GREM! proposed by Derrida and Gardner @J. Phys. C19, 2253~1986! # in the context of spin glasses. After obtaining the joint distribution for energies of pairs of configurations, and by calculating the entropy of the polymer subject to weak and strong topological constraints, the model yields thermodynamic quantities such as ground-state energy, entropy per thermodynamic basin, and glass transition temperature as functions of the polymer length and packing density. These are found to be very close to the uncorrelated landscape or random energy model ~REM! estimates. A tricritical point is obtained where behavior of the order parameter q changes from first order with a discrete jump at the transition, to second-order continuous. While the thermodynamic quantities obtained from the free energy are close to the REM values, the Levinthal entropy describing the number of basins which must be searched at the glass transition is significantly modified by correlations. @S1063-651X~96! 02406-3#
SimEnv: Understanding and supporting the creation of outcome-driven simulations

Immersive computer-based training environments and computer games share many similarities; both require an interactive environment populated with believable characters where users' decisions affect the outcome of future events. The main problem in constructing these complex environments is that any sufficiently complex environment that offers users choices has to allow the users to pursue varied paths through the system and provide guidance for all these paths. Managing the multitude of paths is known as the branching storyline problem. Currently, this is addressed by hand-coding and testing all paths which increases production costs and artificially limiting user choices which damages believability and user experience. This project explores an alternative approach, using characters that rely on case-based reasoning for decision-making to provide flexibility in interacting with player, coupled with a story manager to manage and coordinate the characters by observing all user interactions to achieve the intended outcomes. The techniques developed are applicable for training environments as well as next-generation computer games.
Low voltage, low power, compact, high accuracy, high precision PTAT temperature sensor for deep sub-micron CMOS systems

Temperature measurement is becoming increasingly important in integrated circuits and microsystems; nevertheless, existing techniques for the integration of high accuracy, high precision temperature sensors are not optimal for deep sub-micron CMOS processes. Here we describe a low voltage, low power, compact, high accuracy, high precision temperature sensor for deep sub-micron CMOS systems; our approach takes advantage of charge balancing and charge sharing for low current consumption, does not use resistors for compactness, and takes advantage of both PTAT and autozero techniques for high accuracy and high precision; the circuit can be operated at low supply voltages. As a proof of concept, we report transistor level simulations in a standard 0.13 mum process; the sensor only sinks about 6 muA from a 1.2 V supply voltage, achieving a power dissipation as low as 7.2 muW.
TID Effect in SOI Technology

In this paper, a brief overview of TID effect in SOI technology is presented. The introduction of buried oxide(BOX) adds vulnerability to TID effect in SOI transistors because of its large thickness. Also the BOX introduces special charge traps, the delocalized spin centers, which in most cases are positive. The charge buildup in BOX could increase the leakage current in front gate transistor in partially depleted devices and result in the threshold voltage shift and leakage current increase in fully depleted front gate transistor in planar SOI transistors. While in non-planar transistors, the better gate control over the channel introduces higher TID tolerance, especially the  shaped gate SOI transistor. Complicated physical mechanisms, band to band tunneling and impact ionization, that are responsible for the front gate leakage current increase even in negative gate bias in FD devices are examined. Also the TID effect shows bias dependence in SOI transistor. This dependence is reduced with increasing gate length. Several hardening techniques of BOX are presented, such as the process techniques and the device design, BUSFET as an example, showing enhancement in TID tolerance.
3D-PMDC: A parallelized morphological wavelet codec for 3D medical datasets and teleradiology applications

Modern medical imaging modalities produce increasingly large datasets. This trend can be in contrast with the computation and transmission time requirements coming from critical teleradiology applications. Multidimensional image compression techniques can be considered as enabling solutions on condition that they are able to guarantee a suitable combination of rate-distortion and computational performance which fulfill all the application domain requirements. In this work, we present a parallel version of our 3D Embedded Morphological Dilation Coding algorithm that allows a significant reduction of computation costs and the concurrent conservation of coding performance and of other relevant bitstream properties. A comparison with the recently released JPEG2000 part 10 (JP3D) standard put in evidence the value of the proposed solution, especially for teleradiology applications over heterogeneous networks.
Simulation and execution of event-driven robot teaching in a virtual environment

One of the most widely used robot working paradigms is surely the teaching-playback. Conventional teaching process is very tedious and time-consuming, even dangerous. This paper presents a new development method for event-driven robot teaching in a virtual environment. By using agent-oriented programming scripts, the prior knowledge from task world and the new knowledge from sensors during the real-time execution are both integrated to the virtual workcell. With the help of event based control, a safe and efficient teaching system is developed. Simulation and execution experiment results with a MOTOMAN-k10s welding robot show that the method is effective.
Influence of Imperfect Carrier Signal Recovery on Performance of SC Receiver of BPSK Signals Transmitted over α-μ Fading Channel

This paper presents the analysis of the reception of binary phase-shift keying (BPSK) signals transmitted over the generalized α-μ fading channel. The selective combining (SC) and then demodulation and detection of the input signal are performed in the receiver while the estimation of the received signal phase is imperfect. We determine the BER dependence on the simultaneous influences of the imperfect reference signal recovery, number of diversity branches, fading severity and average signal-to-noise ratio in the channel.
Flexible Page-level Memory Access Monitoring Based on Virtualization Hardware

Page protection is often used to achieve memory access monitoring in many applications, dealing with program-analysis, checkpoint-based failure recovery, and garbage collection in managed runtime systems. Typically, low overhead access monitoring is limited by the relatively large page-level granularity of memory management unit hardware support for virtual memory protection. In this paper, we improve upon traditional page-level mechanisms by additionally using hardware support for virtualization in order to achieve fine and flexible granularities that can be smaller than a page. We first introduce a memory allocator based on page protection that can achieve fine-grained monitoring. Second, we explain how virtualization hardware support can be used to achieve dynamic adjustment of the monitoring granularity. In all, we propose a process-level virtual machine to achieve dynamic and fine-grained monitoring. Any application can run on our process-level virtual machine without modification. Experimental results for an incremental checkpoint tool provide a use-case to demonstrate our work. Comparing with traditional page-based checkpoint, our work can effectively reduce the amount of checkpoint data and improve performance.
Clotho: an elastic MapReduce workload/runtime co-design

The resource management of a multi-tenant MapReduce cluster can be hard given unpredictable user demands. Conventional resource management scheme would inevitably create a fair amount of spare resource fragments in the system. On the other hand, MapReduce workloads are prone to have a bottleneck stage in the execution pipeline. To address these two issues under a coherent framework, this paper presents Clotho, a MapReduce workload and runtime co-design that can opportunistically utilize the spare resource fragments in the system to alleviate the bottleneck stage of MapReduce workloads while honoring the SLAs of existing systems. We describe the design and the implementation of Clotho, evaluate it with benchmarks drawn from real MapReduce applications, and demonstrate that it can effectively utilize the spare CPU resource fragments and meanwhile improve the performance of user programs if there is potential to speed up the bottleneck stage of the entire MapReduce execution pipeline.
Criteria for static equilibrium in particulate mechanics computations

The underlying physics of granular matter can be clearly solved using particulate mechanics methods, e.g. the discrete element method (DEM) that is inherently discontinuous and heterogeneous. To solve static problems, explicit schemes using dynamic relaxation procedures have been widely employed, in which naturally dynamic material parameters are typically adapted into pure numerical artifacts with the sole purpose of attaining meaningful results. In discrete computations using these explicit schemes, algorithmic calibration is demanded under general conditions in order to achieve quasi‐static states. Until now, procedures for algorithmic calibration have remained rather heuristic. This paper presents two criteria, using the concept of homogenized stresses, for evaluating equilibrium in quasi‐static applications of particulate mechanics methods. It is shown, by way of numerical examples, that the criteria for static equilibrium can be applied successfully to obtain quasi‐static solutions in explicit DEM codes through algorithmic calibrations. A general procedure is proposed herein for carrying out the algorithmic calibration effectively and efficiently. Copyright © 2008 John Wiley & Sons, Ltd.
Individualism or complementarity? The effect of digital personal networks on face-to-face personal networks

ABSTRACT Information and communication technologies (ICTs) are affecting ways of networking in advanced societies. This study analyzes the interaction of face-to-face social networks and digital social networks in Spain, a Mediterranean country characterized by significant sociability in every social sphere. Our aim is to contrast this with the hypothesis that new forms of networking can lead to isolation or individualization. This study uses two surveys carried out by the Centro de Investigaciones Sociológicas [Center for Sociological Research] in 2014 and 2016, involving 4922 people over 18 years of age who were asked about these two types of networks (face-to-face and digital) and other topics related to demographics, family, social position, and personality traits. The results indicate complementarity between networks: digital networks served to enrich face-to-face networks, especially when people described themselves as extraverted. However, nuances were observed in relation to rural or urban habitat and forms of coexistence among those interviewed.
Content- and Graph-based Tag Recommendation: Two Variations

We describe two variants of our approach to tackle the task 1 & 2 of the ECML PKDD Discovery Challenge 2009 where each contenter had to identify up to 5 tags for each resource of a given set of either bibtex-like references to publications or bookmarks. The quality of the results was measured against the tags that users of the data source (www.bibsonomy.org) had originally assigned to the resources (F1 measure). In our approach, we either generate tags (from the content of the given resource data or after crawling additional resources) or we request tags from tagging services. We call each of this tag sources a tag recommender. We then combine the results of the tag recommenders based on weighting factors. The weighting factors are determined experimentally by comparing generated and expected tags based on the available training data. This general idea is also used for the graph-based approach required to solve task 2. Here again, the final tag recommendations are computed from the individual results of the different tag-recommending algorithms. In the preliminary result list, we ranked second for task 1 (Group 2) and nineth for task 2 (Group 1).
Situationally independent prosodic phrasing

A series of speech production and categorization experiments demonstrates that naïve speakers and listeners reliably use correspondences between prosodic phrasing and syntactic constituent structure to resolve standing and temporary ambiguity. Materials obtained from a co-operative gameboard task show that prosodic phrasing effects (e.g., the location of the strongest break in an utterance) are independent of discourse factors that might be expected to influence the impact of syntactic ambiguity, including the availability of visual referents for the meanings of ambiguous utterances and the use of utterances as instructions versus confirmations of instructions. These effects hold across two dialects of English, spoken in the American Midwest, and New Zealand. Results from PP-attachment and verb transitivity ambiguities indicate clearly that the production of prosody-syntax correspondences is not conditional upon situational disambiguation of syntactic structure, but is rather more directly tied to grammatical constraints on the production of prosodic and syntactic form. Differences between our results and those reported elsewhere are best explained in terms of differences in task demands.
Adolescents’ perceptions of school climate: Exploring its protective role in times of economic recession

The aim of the study is to explore the way Greek junior high school students perceive school climate as a protective factor against the adversities due to the ongoing economic recession. The randomly selected sample consisted of 746 students from junior high schools (Gymnasia) in the broader area of Athens. The California School Climate Survey (2009), the Questionnaire of Subjective Well-Being/Youth Form (Grob et al., 1991) and the Economic Crisis Difficulties Questionnaire (LSP, 2011) were used for data collection. The findings indicated the existence of statistically significant relations between the effects of economic recession, subjective well-being and school climate. School climate moderated the interaction between economic recession and students’ subjective well-being. Results provide a better understanding of adolescents’ needs during unsettling times contributing to the development of effective evidence-based intervention programs in school communities.
Dynamic Action Recognition: A convolutional neural network model for temporally organized joint location data

Motivation: Recognizing human actions in a video is a challenging task which has applications in various fields. Previous works in this area have either used images from a 2D or 3D camera. Few have used the idea that human actions can be easily identified by the movement of the joints in the 3D space and instead used a Recurrent Neural Network (RNN) for modeling. Convolutional neural networks (CNN) have the ability to recognise even the complex patterns in data which makes it suitable for detecting human actions. Thus, we modeled a CNN which can predict the human activity using the joint data. Furthermore, using the joint data representation has the benefit of lower dimensionality than image or video representations. This makes our model simpler and faster than the RNN models. In this study, we have developed a six layer convolutional network, which reduces each input feature vector of the form 15x1961x4 to an one dimensional binary vector which gives us the predicted activity. Results: Our model is able to recognise an activity correctly upto 87% accuracy. Joint data is taken from the Cornell Activity Datasets which have day to day activities like talking, relaxing, eating, cooking etc.
Propagating Regular Counting Constraints

Constraints over finite sequences of variables are ubiquitous in sequencing and timetabling. This led to general modelling techniques and generic propagators, often based on deterministic finite automata (DFA) and their extensions. We consider counter-DFAs (cDFA), which provide concise models for regular counting constraints, that is constraints over the number of times a regular-language pattern occurs in a sequence. We show how to enforce domain consistency in polynomial time for at-most and at-least regular counting constraints based on the frequent case of a cDFA with only accepting states and a single counter that can be increased by transitions. We also show that the satisfaction of exact regular counting constraints is NP-hard and that an incomplete propagator for exact regular counting constraints is faster and provides more pruning than the existing propagator from (Beldiceanu, Carlsson, and Petit 2004). Finally, by avoiding the unrolling of the cDFA used by COSTREGULAR, the space complexity reduces from O(n · |Σ| · |Q|) to O(n · (|Σ| + |Q|)), where Σ is the alphabet and Q the state set of the cDFA.
Assigning Hybrid-Weight for Feature Attribute in Naïve Bayesian Classifier

Department of Information Science and Technology, Xingtai University, Xingtai 054001, China Abstract. In this paper, a novel naïve Bayesian classifier based on the hybrid-weight feature attributes (short of “NBCHWFA”) is proposed. NBCHWFA arranges a hybrid weight for each feature attribute by merging the effectiveness of feature attribute on classification and the dependence between feature attribute and class attribute. In order to demonstrate the feasibility and effectiveness of proposed NBCHWFA, we experimentally compare our method with standard naïve Bayesian classifier (NBC), NBC with gain ratio weight (NBCGR), and NBC with correlation coefficient weight (NBCCC) on 10 UCI datasets. And, a statistical analysis is also given. The final results show that NBCHWFA can obtain the statistically best classification accuracy.
A novel approach for ensuring high end-to-end availability: The spine concept

Telecommunications networks need to guarantee that all node pairs involved in critical service communications are highly available. Typically only a small fraction of traffic and users needs high levels of availability but this traffic often drives the network design to over engineering. In this paper we adopt a novel approach to the problem of how to provide high levels of availability in an efficient manner. The basic idea is to embed a high availability set of links and nodes (termed the spine) in the network topology and leverage protection and routing to provide differentiated classes of resilience with varying levels of availability. In this paper we first explore the spine concept through a simple example illustrating the potential benefits of the approach. Then we study how the structural properties of a network topology can be used to determine heuristics to select a suitable spine and compare this with the case where all network components have the same availability. This is followed by a numerical based study comparing the heuristics with all possible spanning tree based spines for sample topologies. Our results are a step along the path of how to best design a physical network to support protection methods in achieving high levels of availability cost efficiently.