Miracle-dz/UniFAR-FTUs huggingface dataset:
Introduction to special issue on Forensic Linguistics: European Perspectives

This special issue of Nordic Journal of Linguistics is dedicated to the emerging field of forensic linguistics. There are competing definitions and delimitations of this term but here we will use it to refer to the investigation and elucidation of language evidence in a legal context. This includes the scrutiny of language data from different stages of the legal process, ranging from emergency calls to police interviews and courtroom interaction, as well as expert assessment and witness testimony in cases where the meaning or authorship of texts or utterances are questioned. While the analysis of authentic case data is often preferred or even required, access to such highly sensitive data types is naturally restricted by legal and ethical boundaries. An increasing amount of studies therefore employ experimental designs to test hypotheses and improve methodologies.
A Hybrid Overset Algorithm for Aerodynamic Problems with Moving Objects

A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper. Keywords— Moving mesh, Overset grid, Unsteady Euler, Relative motion.
Stability and Performance of SISO Control Systems With First-Order Reset Elements

We consider set-point regulation and L2 robust stability properties of a class of reset control systems consisting of a minimum-phase relative degree-one linear SISO plant controlled by a novel first-order reset element (FORE). These results rely on necessary and sufficient conditions for exponential and L2 finite gain stability of a class of planar reset systems consisting of a scalar linear plant controlled by the novel FORE. We show that the L2 gain of the planar reset system decreases to zero as the pole and/or the gain of the FORE are increased to infinity. A number of stability results, including Lyapunov conditions for Lp and exponential stability, for a larger class of reset and hybrid systems are presented and used to prove our main results.
Facial expression analysis and synthesis: A survey

Human facial expression analysis and synthesis play a central role in the social context, being investigated by many psychologists over the time. Moreover, an increased interest has been shown in developing an automated facial expression analyzer capable of recognizing, classifying and then synthesizing human expressions on synthetic “talking heads”. This paper surveys the state of the art in this area.
Unifying Functional Interpretations

The purpose of this article is to present a parametrised functional inter- pretation. Depending on the choice of the parameter relations one obtains well-known functional interpretations, such as Godel's Dialectica interpretation, Diller-Nahm's vari- ant of the Dialectica interpretation, Kohlenbach's monotone interpretations, Kreisel's modified realizability and Stein's family of functional interpretations. A functional in- terpretation consists of a formula translation and a proof translation. We show that all these interpretation only dier on two choices: firstly, on "how much" of the counter- examples for A became witnesses for ¬A when defining the formula translation, and, secondly, "how much" of the witnesses of A one is interested in when defining the proof translation.
Code-Aided Channel Tracking and Frequency Offset-Phase Noise Elimination for Multicarrier Systems

In this contribution, we propose a novel code-aided channel tracking and carrier frequency offset (CFO) and/or phase noise (PN) estimation algorithm for orthogonal frequency-division multiplexing (OFDM) systems. Starting from the maximum-likelihood (ML) principle, we derive a low complexity estimator based on the expectation-maximization (EM) algorithm. It turns out that the estimator receives soft information from the channel decoder to refine the CFO, PN, and channel estimates. Simulation results revealed that the proposed algorithm outperforms the conventional techniques in terms of bit-error rate (BER).
A Corpus-Based Morphological Disambiguation Tool for Basque

This paper presents the methodology followed in the construction of a surface-based morphosyntactic parsing grammar as well as the results obtained. It is based on the Constraint Grammar formalism which we find suitable for our project of analysing unrestricted texts. Besides, we will present a description of the main types of morphosyntactic ambiguity that we have identified for Basque and the disambiguation rules designed for their treatment. This work is the first step in the computational treatment of syntax.
Power reduction strategies for DRAM used in data centric applications

To catch up pace with development in processors, power consumption of a memory module is often amortized for higher bandwidth and lower latencies. As a result memory module consumes a major fraction of total power consumption in a system. This has led to low power design. This paper will evaluates three new DRAM interface, viz. MemBlaze, MemCorrect and MemDrowsy, developed at Stanford University, USA. Paper intends to extract out know-hows, tradeoffs incurred, and energy saving mode, hardware overheads and application area of the interfaces. All the three architectures work on reducing wakeup latencies of a Power-Up mode in DRAM, thus allowing the DRAM to use their Power-Down modes rigorously. The technique is capable of reducing the background power consumption up to 50%. The interface finds its application in the field which demands heavy memory usage like that of data centric applications, server memories, handling Big Data and Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP).
Classroom Process and Practices in Public Pre-K Programs: Describing and Predicting Educational Opportunities in the Early Learning Sector

ABSTRACT Research Findings: The present study used data from 117 publicly funded preschool classrooms within a large, diverse, suburban county to describe teacher practices and child engagement along with classroom activity settings and children’s exposure to instructional content. Practice or Policy: Results from this investigation revealed that children spent the largest share of the day in teacher-directed whole-group instruction and in free play and very little time was spent in individual and small-group settings. Although a 3rd of the school day was dedicated to academic activities, there were few opportunities for socioemotional learning, and children spent roughly a 3rd of the school day in routines/transitions and meals. Few differences emerged in the classroom observations across school- and community-based programs; however, more educated and experienced teachers spent more time teaching and in teacher-directed instruction.
Parental insights from three elite-level youth sports: implications for family life

ABSTRACT The purpose of this study was to examine parental values associated with children’s participation in organized sports, how these values are shaped by social class, race and age, and the influence of elite-level involvement in youth sport on family life. Data were collected by questionnaire in person from parents who were attending three youth sport events (Athletics (track and field) n = 102, Swimming n = 193, Synchronized Swimming n = 139). ANOVA, multiple regression, and thematic analysis were used to analyse the data. Values associated with the child/youth’s sport participation included fun, health, self-discipline, and competition. Multiple regression analysis showed that values differed by social class, age, and race, and child/youth’s age. For example, fun and self-discipline were rated higher for younger children while competition was valued more highly for older children. In particular, African-American parents rated self-discipline and competition as significantly higher. Parents across all sports reported the need to organize family activities around sport schedules with swimming and synchronized swimming cited as the most influential. Suggestions as to how Leisure Studies’ research foci on youth, family life, gender and time are well positioned to make valuable contributions to the study of youth sport in the context of family life are discussed.
Two touch system latency estimators: high accuracy and low overhead

The end-to-end latency of interactive systems is well known to degrade user's performance. Touch systems exhibit notable amount of latencies, but it is seldom characterized, probably because latency estimation is a difficult and time consuming undertaking. In this paper, we introduce two novel approaches to estimate the latency of touch systems. Both approaches require an operator to slide a finger on the touch surface, and provide automatic processing of the recorded data. The High Accuracy (HA) approach requires an external camera and careful calibration, but provides a large sample set of accurate latency estimations. The Low Overhead (LO) approach, while not offering as much accuracy as the HA approach, does not require any additional equipment and is implemented in a few lines of code. In a set of experiments, we show that the HA approach can generate a highly detailed picture of the latency distribution of the system, and that the LO approach provides average latency estimates no further than 4 ms from the HA estimate.
AUTOMATED APPLE STEM‐END/CALYX IDENTIFICATION

Machine vision methods are widely used in apple defect detection and quality grading applications. Currently, 2D near‐infrared (NIR) imaging technology is used to detect apple defects based on the difference in image intensity of defects from normal apple tissue. However, it is difficult to accurately differentiate an apple's stem‐end/calyx from a true defect due to their similar 2D NIR images, which presents a major technical challenge to the successful application of this machine vision technology. In this research, we used a novel two‐step 3D data analysis strategy to differentiate apple stem‐ends/calyxes from true defects according to their different 3D shape information. In the first step, a 2D NIR imaging was extended to a 3D reconstruction using a shape‐from‐shading (SFS) approach. After successfully obtaining 3D information, a quadratic facet model was introduced to conduct the 3D concave shape fitting such that the identification of apple stem‐ends and calyxes could be achieved based on their different 3D structures. Significant improvement in terms of the detection rate could be obtained based on 3D shape fitting in comparison to the traditional 2D intensity fitting approach. Samples of the reconstructed 3D apple surface maps as well as the identified stem‐ends/calyxes were shown in the results, and an overall 90.15% detection rate was achieved, compared to the 58.62% detection rate of the traditional 2D intensity fitting approach.
Mass Cytometry Study on the Heterogeneity in Cellular Association and Cytotoxicity of Silver Nanoparticles in Human Immune Cells

There have been many reports about the adverse effects of nanoparticles (NPs) on the environment and human health. Conventional toxicity assessments of NPs frequently assume uniform distribution of monodisperse NPs in homogeneous cell populations, and provide information on the relationships between the administered dose of NPs and cellular responses averaged for a large number of cells. They may have limitations in describing the wide heterogeneity of cell-NP interactions, caused by cell-to-cell and NP-to-NP variances. To achieve more detailed insight into the heterogeneity of cell-NP interactions, it is essential to understand the cellular association and adverse effects of NPs at single-cell level. In this study, we applied mass cytometry to investigate the interactions between silver nanoparticles (AgNPs) and primary human immune cells. High dimensionality of mass cytometry allowed us to identify various immune cell types and observe the cellular association and toxicity of AgNPs in each population. Our findings showed that AgNPs had higher affinity with phagocytic cells like monocytes and dendritic cells and caused more severe toxic effects than with T cells, B cells and NK cells. Multi-element detection capability of mass cytometry also enabled us to simultaneously monitor cellular AgNP dose and intracellular signaling of individual cells, and subsequently investigate the dose-response relationships of each immune population at single-cell level, which are often hidden in conventional toxicity assays at bulk-cell level. Our study will assist future development of single-cell dose-response models for various NPs and will provide key information for the safe use of nanomaterials for biomedical applications.
Syntactic Patterns Recognition Applied to the APF Analyses

The evolution of technology has enabled research in several areas, one is the software manufacturing cells planning. There are several techniques for the study of design patterns. This line of research and development, small scale production, has been offered some computer systems dedicated to of design patterns analysis. The aim of this paper is to present the software implementation that uses Grammar of design patterns to validate string of characters in valid design patterns.
Quadripartite Graph-based Clustering of Questions

In a Community Question Answering (CQA) service, each user interaction is different and since there are a variety of complex questions, identifying similar questions for reusing answers is difficult. This is mainly because of lexical mismatch problem. This research aims to develop a quadripartite graph-based clustering (QGC) approach by harnessing relationship of a question with common answers and associated users. It was found that QGC approach outperformed other baseline clustering techniques in identifying similar questions in CQA corpora. We believe that these findings can serve to guide future developments in the reuse of similar question in CQA services.
Enhancing health care via affective computing

Affective computing is a multidisciplinary field that studies the various ways by which computational processes are able to elicit, sense, and detect manifestations of human emotion. While the methods and technology delivered by affective computing have demonstrated very promising results across several domains, their adoption by healthcare is still at its initial stages. With that aim in mind, this commentary paper introduces affective computing to the readership of the journal and praises for the benefits of affect-enabled systems for prognostic, diagnostic and therapeutic purposes
Optimized composition of performance‐aware parallel components

We describe the principles of a novel framework for performance‐aware composition of sequential and explicitly parallel software components with implementation variants. Automatic composition results in a table‐driven implementation that, for each parallel call of a performance‐aware component, looks up the expected best implementation variant, processor allocation and schedule given the current problem, and processor group sizes. The dispatch tables are computed off‐line at component deployment time by an interleaved dynamic programming algorithm from time‐prediction meta‐code provided by the component supplier. Copyright © 2011 John Wiley & Sons, Ltd.
Essential Roles for the Tec Family Kinases Tec and Btk in M-CSF Receptor Signaling Pathways That Regulate Macrophage Survival1

Tec family kinases have important roles in lymphocytes; however, little is known about their function in monocytes/macrophages. In this study we report that Tec family kinases are essential for M-CSF (M-CSF)-induced signaling pathways that regulate macrophage survival. Compared with wild-type bone marrow-derived macrophage (BMM) cultures, Tec−/−Btk−/− BMM cultures displayed increased cell death that correlated with a severe drop in macrophage numbers. In addition, macrophages deficient in either Tec or Btk showed expression and activation of caspase-11. Elucidation of M-CSF receptor (M-CSFR) signaling pathways revealed that the total tyrosine phosphorylation pattern upon M-CSF stimulation was altered in Tec−/−Btk−/− macrophages despite normal expression and phosphorylation of the M-CSFR. Further, Tec and Btk are required for proper expression of the GM-CSF receptor α (GM-CSFRα) chain in macrophages but not dendritic cells, implicating Tec family kinases in the lineage-specific regulation of GM-CSFRα expression. Taken together, our study shows that Tec and Btk regulate M-CSFR signaling-induced macrophage survival and provides a novel link between Tec family kinases and the regulation of caspase-11 and GM-CSFRα expression.
Florch: Challenges on developing a new social network accessible for senescent users

Brazilian senescent population can grow three times the actual number in the next 20 years [18], being over 88 million people in 2035. This senescent growing number brings new challenges on quality of life for Brazilian society. How to promote digital inclusion to this profile of user is still a challenge in the literature. We believe that a social network focused on senescent users can enhance the digital inclusion for them. However, it's essential that the social network be designed for senescent users. This study aims to create a project with this characteristics. We analyzed a successful social network (WhatsApp) in order to propose a new one (Florch) for senescent users. We developed a high fidelity prototype of Florch and tested it. Our findings show usability and accessibility problems faced on the project's development. In addition, a Hierarchical Task Analysis of our social network showed that it has less and simpler tasks than the successful social network (WhatsApp).
Stopping Amplified DNS DDoS Attacks through Distributed Query Rate Sharing

An Amplified DNS DDoS (ADD) attack involves tens of thousands of DNS resolvers that send huge volumes of amplified DNS responses to a single victim host, quickly flooding the victim's network bandwidth. Because ADD attacks are distributed, it is difficult for individual DNS resolvers to detect them based on local DNS query rates alone. Even if a victim detects an ADD attack, it cannot stop the attacker from flooding its network bandwidth. To address this problem, we present a novel mitigation system called"Distributed Rate Sharing based Amplified DNS-DDoS Attack Mitigation" (DRS-ADAM). DRS-ADAM facilitates DNS query rate sharing between DNS resolvers that are involved in an attack to detect and completely stop an ADD attack. Each DNS resolver quickly builds the global DNS query rate for potential victims by accumulating the shared rate values, and uses that global rate to make mitigation decisions locally. DRS-ADAM can be easily deployed through a small software update on resolvers and victim hosts, and does not require any additional server component. Our simulation results show that DRS-ADAM can contain the peak attack rates close to a victim's acceptable threshold values (which are far smaller than their sustainable bandwidth) at all times, regardless of the number of resolvers involved in ADD attacks. ADD attacks can be fully mitigated within a few seconds.
Mechanisms of Optimizing MapReduce Framework on High Performance Computer

With the amount of data growing constantly and exponentially, the industry has encountered an unprecedented challenge of efficiently and reliably processing a tremendous amount of data. High performance computer has played a major role in the field of big data processing for its serious computational power and super-large storage. However, it remains some inevitable drawbacks to efficiently utilize the HPC due to its relatively lower availability and usability. We propose to implement MapReduce framework on HPC to solve above problems and extensively expand the application field of HPC. We design a workable plan to deploy Hadoop on HPC with a Lustre file system, and tune Lustre to a better performance based on the nature of data access in Hadoop. Virtual memory disk is proposed to efficiently buffer temporary data and store intermediate data. By taking advantage of high-speed interconnect system of HPC, the intermediate data can be transferred efficiently from map task to reduce task, which cannot be achieved in a Hadoop system on server cluster since the rate of data flow is bounded by the bandwidth of low-speed network, such as Ethernet. The evaluation driven by the standard benchmarks provided in Hadoop package shows that after applying the proposed optimization method, the Hadoop system on HPC gets better performance than Hadoop system on server cluster, especially when handle data-intensive applications.
Annotation Methodologies for Vision and Language Dataset Creation

Annotated datasets are commonly used in the training and evaluation of tasks involving natural language and vision (image description generation, action recognition and visual question answering). However, many of the existing datasets reflect problems that emerge in the process of data selection and annotation. Here we point out some of the difficulties and problems one confronts when creating and validating annotated vision and language datasets.
A new paradigm for channel coding in diffusion-based molecular communications: Molecular coding distance function

The emerging diffusion-based molecular communications is a promising scheme for nano-machine communications. Nevertheless, the Brownian motion model, which describes the behavior of molecules, makes the physical channel different from the channel in conventional wireless communications. In particular, the crossovers in time caused by the late arrivals of the molecules severely affect the communication reliability. In traditional communications, channel coding has long been used to enhance the reliability. Through our explorations, it is shown that the commonly used Hamming distance is no longer a good metric for the channel decoding in diffusion-based molecular communications. The conventional concepts of the channel code design cannot be straightforwardly applied. In this paper, the molecular coding (MoCo) distance function has been proposed, and shown to approach the optimum performance beyond the capability of using Hamming distance. This suggests that new paradigms can be developed upon the MoCo distance.
Distributed Multi-robot Dynamic Network Topology Control while Preserving Connectivity

The multi-robot network topology control and connectivity preserving problem is studied. We introduce the global message connectivity to represent the quality of service (QoS) of the network. A combined distributed algorithm of topology control and connectivity motion control is proposed. Simulation results show that the algorithm can improve the global message connectivity while keeping the network connected.