Miracle-dz/UniFAR-FTUs huggingface dataset:
Do POS Tags Help to Learn Better Morphological Segmentations?

The utility of using morphological features in part-of-speech (POS) tagging is well established in the literature. However, the usefulness of exploiting information about POS tags for morphological segmentation is less clear. In this paper we study the POS-dependent morphological segmentation in the Adaptor Grammars framework. We experiment with three different scenarios: without POS tags, with gold-standard tags and with automatically induced tags, and show that the segmentation F1-score improves when the tags are used. We show that the gold-standard tags lead to the biggest improvement as expected. However, using automatically induced tags also brings some improvement over the tag-independent baseline.
Reliability Estimates for the Immediate and Delayed Memory Tasks

The Immediate and Delayed Memory Tasks are variations of the Continuous Performance Test. While previous research with the tasks has focused on group performance across multiple blocks and sessions, reliability estimates have not been established. We estimated reliability (1) between blocks of a single testing session (N=106), (2) across four sessions within a single testing day (N=20), and (3) across sessions on four consecutive testing days (N=20). Analyses indicated that the primary variable of Interest, i.e., commission of errors, showed acceptable reliability within and across testing periods.
A Telepresence Mobile Robot Controlled With a Noninvasive Brain–Computer Interface

This paper reports an electroencephalogram-based brain-actuated telepresence system to provide a user with presence in remote environments through a mobile robot, with access to the Internet. This system relies on a P300-based brain-computer interface (BCI) and a mobile robot with autonomous navigation and camera orientation capabilities. The shared-control strategy is built by the BCI decoding of task-related orders (selection of visible target destinations or exploration areas), which can be autonomously executed by the robot. The system was evaluated using five healthy participants in two consecutive steps: 1) screening and training of participants and 2) preestablished navigation and visual exploration telepresence tasks. On the basis of the results, the following evaluation studies are reported: 1) technical evaluation of the device and its main functionalities and 2) the users' behavior study. The overall result was that all participants were able to complete the designed tasks, reporting no failures, which shows the robustness of the system and its feasibility to solve tasks in real settings where joint navigation and visual exploration were needed. Furthermore, the participants showed great adaptation to the telepresence system.
Mining for Social Skills: Minecraft in Home and Therapy for Neurodiverse Youth

The Minecraft game platform has widespread popularity among children, including neurodiverse children with Autism Spectrum Disorder and AttentionDeficit Disorder. A critical area of therapeutic focus for neurodiverse children is social learning to enhance their social connections. We conducted exploratory research to better understand the role of Minecraft in the lives of neurodiverse youth, from the perceptive of parents and clinics servicing this population. Via interviews and a focus group, we inquired into the perceptions and goals of clinics that have incorporated Minecraft into their services and parents of participating youth. Our findings are rich descriptions of the current social lives and gaming practices of neurodiverse children. Although parents and clinicians observe positive social interactions through Minecraft, parents grapple with their goals of supporting their children’s social lives and their reservations regarding online gaming communities. Parents and therapists desire more connections between virtual and face-to-face social relationships. Our findings point to the opportunity for clinicians, parents, and technology designers to facilitate social learning in online environments such as Minecraft due to its affordances to facilitate cooperation, modeling, joint attention, and performance in a safe, compelling environment.
Approximation Incremental Training Algorithm Based on a Changeable Training Set

The quick training algorithms and accurate solution procedure for incremental learning aim at improving the efficiency of training of SVR, whereas there are some disadvantages for them, i.e. the nonconvergence of the formers for changeable training set and the inefficiency of the latter for a massive dataset. In order to handle the problems, a new training algorithm for a changeable training set, named Approximation Incremental Training Algorithm (AITA), was proposed. This paper explored the reason of nonconvergence theoretically and discussed the realization of AITA, and finally demonstrated the benefits of AITA both on precision and efficiency. Keywords—support vector regression, incremental learning, changeable training set, quick training algorithm, accurate solution procedure
Compact decision trees with cluster validity for speech recognition

A decision tree is built by successively splitting the observation frames of a phonetic unit according to the best phonetic questions. To prevent over-large tree models, the stopping criterion is required to suppress tree growing. It is crucial to exploit the goodness-of-split criteria to choose the best questions for node splitting and test if the hypothesis of splitting should be terminated. The robust tree models could be established. In this study, we apply the Hubert's Γ statistic as the node splitting criterion and the T2-statistic as the stopping criterion. Hubert's Γ statistic is a cluster validity measure, which characterizes the degree of clustering in the available data. This measure is useful to select the best questions to unravel tree nodes. Further, we examine the population closeness of two child nodes with a significant level, T2-statistic is determined to validate whether the corresponding mean vectors are close together. The splitting is stopped when validated. In continuous speech recognition experiments, the proposed methods achieve better recognition rates with smaller tree models compared to the maximum likelihood and minimum description length criteria.
Means of self-preservation: how an intrinsically disordered ubiquitin-protein ligase averts self-destruction

Ubiquitin-protein ligases (E3s) are often in the precarious position of ubiquitinating themselves, mediating their own destruction. The intrinsically disordered E3 San1 prevents its own autoubiquitination and degradation by minimizing Lys residues and hydrophobic stretches in its disordered regions.
Rcs — a system for version control

An important problem in program development and maintenance is version control, i.e. the task of keeping a software system consisting of many versions and configurations well organized. The Revision Control System (RCS) is a software tool that assists with that task. RCS manages revisions of text documents, in particular source programs, documentation, and test data. It automates the storing, retrieval, logging and identification of revisions, and it provides selection mechanisms for composing configurations. This paper introduces basic version control concepts and discusses the practice of version control using RCS. For conserving space, RCS stores deltas, i.e. differences between successive revisions. Several delta storage methods are discussed. Usage statistics show that RCS's delta method is space and time efficient. The paper concludes with a detailed survey of version control tools.
Spontaneous Intracerebral and Intraventricular Hemorrhage: Advances in Minimally Invasive Surgery and Thrombolytic Evacuation, and Lessons Learned in Recent Trials.

Optimal management of spontaneous intracerebral hemorrhage (ICH) remains one of the highly debated areas in the field of neurosurgery. Earlier studies comparing open surgical intervention with best medical management failed to show a clear benefit. More recent experience with minimally invasive techniques has shown greater promise. Well-designed phase II trials have confirmed the safety and preliminary treatment effect of thrombolytic aspiration and clearance of spontaneous ICH and associated intraventricular obstructive hemorrhage. Those trials are reviewed, including respective protocols and technical nuances, and lessons learned regarding patient selection, the concept of hemorrhage stabilization, optimization of the surgical procedure, and thrombolytic dosing decisions. These concepts have been incorporated in the design of ongoing definite phase III randomized trials (MISTIE and CLEAR) funded by the National Institutes of Health. These are presented including the role of surgical leadership in the training and monitoring of the surgical task and quality assurance. The impact of these techniques on neurosurgical practice is discussed.
Influence of Friction Stir Welding Effects on the Compressive Strength of Aluminium Alloy Thin-Walled Structures

The main objective of the present work is to investigate the effect of the residual stresses originated by the friction stir welding (FSW) process in the compressive strength of aluminium alloy plates. The finite element method (FEM) is used to simulate the welding process and calculate the distribution of the residual stresses. The model is validated using a residual stress map obtained by means of the contour method from a friction stir welded AA2024-24 plate. The results from the welding simulation were then used to numerically assess the influence of the residual stresses on the collapse load of the plate.
Radiosity on graphics hardware

Radiosity is a widely used technique for global illumination. Typically the computation is performed offline and the result is viewed interactively. We present a technique for computing radiosity, including an adaptive subdivision of the model, using graphics hardware. Since our goal is to run at interactive rates, we exploit the computational power and programmability of modern graphics hardware. Using our system on current hardware, we have been able to compute and display a radiosity solution for a 10,000 element scene in less than one second.
Retargeting of a T cell line by anti MAGE-3/HLA-A2 alpha beta TCR gene transfer.

BACKGROUND The T cell receptor (TCR) is an heterodimeric protein on the cell membrane of cytotoxic T cells (CTLs). In CTLs TCRs mediate the recognition of target cells through interaction with specific, MHC class I presented peptides. MATERIALS AND METHODS As a model system to show proof of principle we chose the Jurkat/MA cell line and the HLA-A2.1 binding MAGE-3 derived peptide 271-279, as target specificity. RESULTS We show that this cell line can be successfully transduced with the dicistronic retroviral vector (LZRS) containing cDNAs encoding for the complete alpha and beta chains of the selected TCR. Following retroviral transduction, Jurkat/MA cells do express the anti-MAGE-3 TCR on their membrane. The transduced TCR is functional as travoductants are successfully triggered, upon stimulation with T2 cells or MAGE-3+ melanoma cells loaded with the MAGE-3 peptide. CONCLUSION We conclude that TCR gene transfer is possible and it represents a powerful therapeutic tool for the genetical modification of T calls of patients sullering from cancer.
Comparison of Aesthetic Breast Reconstruction After Skin-Sparing or Conventional Mastectomy in Patients Receiving Preoperative Radiation Therapy

Many options exist for the surgical treatment of breast cancer in terms of tumor extirpation and reconstruction. Skin-sparing mastectomy (SSM) with immediate reconstruction offers patients a superior result, but this can be jeopardized by preoperative radiotherapy. We compared the outcomes of reconstruction after SSM or conventional mastectomy (CM) in the previously irradiated breast. We evaluated 41 patients over an 8-year period, who were divided into 3 categories: preoperative radiotherapy prior to SSM (n = 8), CM after preoperative radiation therapy (n = 9), and no chest wall irradiation prior to SSM (n = 20). The first group demonstrated significantly higher frequency of native flap compromise and capsular contracture formation than the other 2 groups. SSM with TRAM or latissimus with implant reconstruction is an esthetically optimal option for the treatment of patients without previous radiotherapy. However, for patients with preoperative chest wall radiation, TRAM flap reconstruction was superior to latissimus flap with implant after SSM.
HOW WE LEARN ASK THE COGNITIVE SCIENTIST

AMERICAN FEDERATION OF TEACHERS 39 How does the mind work—and especially how does it learn? Teachers’ instructional decisions are based on a mix of theories learned in teacher education, trial and error, craft knowledge, and gut instinct. Such gut knowledge often serves us well, but is there anything sturdier to rely on? Cognitive science is an interdisciplinary field of researchers from psychology, neuroscience, linguistics, philosophy, computer science, and anthropology who seek to understand the mind. In this regular American Educator column, we consider findings from this field that are strong and clear enough to merit classroom application.
Many-Objective Sensor Selection in IoT Systems

The Internet of Things connects physical objects through sensor devices with multiple functionalities. At the planning stage of deploying an IoT system, we are concerned about sensor selection in the IoT system, which allocates predefined IoT services to multiple sensor devices so as to optimize one or more objectives associated with these allocations, under energy and distance constraints. The sensor selection problem that optimizes a utility function in other applications has been shown to be NP-hard, and the number of IoT services concerned is enormous in practice. Hence, it is suitable to apply evolutionary algorithms (EAs) for solving the large-scale problem with multiple objectives. Recently, the paradigm of multiple-objective EAs (which often address only two or three objectives) has advanced to many-objective EAs (which are intended to address four or more objectives that may be in conflict with each other in many cases). Therefore, this article considers many objectives of the sensor selection problem in the IoT system, including optimization of communication energy consumption, energy balancing on all devices, energy harvesting, green concerns, and QoS. The problem is resolved by a tailored many-objective EA based on decomposition to increase computational efficiency and solution quality. By simulation, the proposed EA is shown to be promising through scatter charts and parallel coordinates.
On supersymmetric Minkowski vacua in IIB orientifolds

Supersymmetric Minkowski vacua in IIB orientifold compactifications based on orbifolds with background fluxes and non-perturbative superpotentials are investigated. Especially, microscopic requirements and difficulties to obtain such vacua are discussed. We show that orbifold models with one and two complex structure moduli and supersymmetric 2-form flux can be successfully stabilized to such vacua. By taking additional gaugino condensation on fixed space-time filling D3-branes into account also models without complex structure can be consistently stabilized to Minkowski vacua.
Theoretical estimates of asperity-scale stresses in normally-oriented continuous fiber-reinforced composites

Fiber-reinforced polymer matrix composites represent a class of materials with enhanced mechanical and tribological capabilities over the non-reinforced matrices. Past studies have shown that fiber orientation in relation to the plane of contact has a significant effect on tribological performance. In general, when the fibers are oriented normal to the sliding interface, wear is minimized. In this study, stresses in the near-surface region to a depth on the scale of the asperity dimensions are estimated for normally-oriented continuous fiber-reinforced composites. The composite is treated as a transversely isotropic half-space whose properties are estimated from the micro-mechanical considerations of structural composites. Asperity contacts are represented by a hemispherical indentor on the transversely isotropic half space with a known sliding friction coefficient. The surface tensile stresses and their effect on wear are discussed in light of the results. Presented at the 47th Annual Meeting In Philadel.
Stabilized Finite Element Methods for Nonsymmetric, Noncoercive, and Ill-Posed Problems. Part II: Hyperbolic Equations

In this paper we consider stabilized finite element methods for hyperbolic transport equations without coercivity. Abstract conditions for the convergence of the methods are introduced and these conditions are shown to hold for three different stabilized methods: the Galerkin least squares method, the continuous interior penalty method, and the discontinuous Galerkin method. We consider both the standard stabilization methods and the optimization-based method introduced in [E. Burman, SIAM J. Sci. Comput. , 35 (2013), pp. A2752--A2780]. The main idea of the latter is to write the stabilized method in an optimization framework and select the discrete function for which a certain cost functional, in our case the stabilization term, is minimized. Some numerical examples illustrate the theoretical investigations.
Multiple UAV area decomposition and coverage

Multiple UAVs can be used to cover a region effectively. Area coverage involves two stages - area decomposition into cells and path planning inside the cells. The area is decomposed using sweeping technique. For path planning inside the cells, a novel method is developed where optimal number of lanes are generated to minimize the number of UAV turns to accomplish the mission in minimum time. Also to allow operator interaction and precedence in coverage, a novel lawnmower/Zamboni planner is designed. Simulation results are presented for multiple UAVs are presented and flight test results for one UAV performing a persistent mission is presented.
Rethinking the physical layer of data center networks of the next decade: using optics to enable efficient *-cast connectivity

Not only do big data applications impose heavy bandwidth demands, they also have diverse communication patterns denoted as *-cast) that mix together unicast, multicast, incast, and all-to-all-cast. Effectively supporting such traffic demands remains an open problem in data center networking. We propose an unconventional approach that leverages physical layer photonic technologies to build custom communication devices for accelerating each *-cast pattern, and integrates such devices into an application-driven, dynamically configurable photonics accelerated data center network. We present preliminary results from a multicast case study to highlight the potential benefits of this approach.
Information gain based dimensionality selection for classifying text documents

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.
Penumbral Microcirculatory Changes Associated With Peri-infarct Depolarizations in the Rat

Background and Purpose— This study was designed to investigate the influence of peri-infarct depolarization elicited by occlusion of the middle cerebral artery on the dynamics of the microcirculation. Methods— The microcirculation in the frontoparietal cortex of 9 rats was visualized in real time through a closed cranial window with the use of laser-scanning confocal fluorescence microscopy combined with intravenous fluorescein isothiocyanate (FITC)–dextran and FITC-labeled erythrocytes. The direct current potential/electrocorticogram was continuously monitored. Intraluminal focal ischemia was induced for 2 hours in 6 rats anesthetized with halothane and mechanically ventilated. Reperfusion was monitored for 1 hour. Three rats underwent sham operation. Brains were removed 24 hours after occlusion and processed for histology. Results— In control conditions, the velocity of fluorescent erythrocytes through capillaries was 0.51±0.19 mm/s (mean±SD), and the diameter of the arterioles studied was 33±12 &mgr;m. Under ischemia, erythrocyte velocity through capillaries was significantly decreased to 0.33±0.14 mm/s, while arteriole diameter did not change significantly. During spontaneous peri-infarct depolarizations, arteriole diameter was significantly increased (119±23% of baseline), while capillary erythrocyte velocity was further decreased by 14±34%. The direction of arteriolar blood flow episodically and transiently reversed during approximately half of the peri-infarct depolarizations. The decrease in capillary erythrocyte velocity was more pronounced (23±37%) in these cases. After reperfusion, the microcirculatory variables rapidly returned to baseline. All rats in the ischemic group had infarcts 24 hours after occlusion. Conclusions— Peri-infarct depolarization has an adverse influence on penumbral microcirculation, reducing capillary perfusion by erythrocytes, despite dilatation of arterioles. These findings suggest that a steal phenomenon contributes to the deleterious effect of these depolarizations.
Component based software development: A state of art

One of the goals of Software design is to model a system in such a way that it is reused. Actively reusing designs or code allows taking advantage of the investment made on reusable components. However development of domain specific components and its impact on effort in terms of cost and time is still a challenging issue. The component based technology has transformed over a period of time from a simple component to the domain specific components. This paper presents a state of art of the drastic change in component technology from component engineering to domain engineering.