Miracle-dz/UniFAR-FTUs huggingface dataset:
Parsing in Parallel on Multiple Cores and GPUs

This paper examines the ways in which parallelism can be used to speed the parsing of dense PCFGs. We focus on two kinds of parallelism here: Symmetric Multi-Processing (SMP) parallelism on shared-memory multicore CPUs, and Single-Instruction MultipleThread (SIMT) parallelism on GPUs. We describe how to achieve speed-ups over an already very efficient baseline parser using both kinds of technology. For our dense PCFG parsing task we obtained a 60×speed-up using SMP and SSE parallelism coupled with a cache-sensitive algorithm design, parsing section 24 of the Penn WSJ treebank in a little over 2 secs.
Put IT in its Place - Integrating Behavioral inertia into established is Post-Adoption Models

Individual-level inertia exists if users stick to incumbent technologies even if better alternatives are available. Thus, inertial behavior fosters the continued use of current information systems rather than the adoption of new ones. Despite the growing research interest in inertia in recent years and its importance for users’ post-adoption decisions, there is still no common ground or procedure to examine these psychological effects. Foremost, although there is strong theoretical proximity, inertia is still neglected in established continuance and switching models. To close this research gap and to provide a consolidated basis for future research, we integrate inertia into both UTAUT2 and the PPM framework and investigate their adequacy empirically. We find that PPM exhibits higher overall goodness-of-fit, while UTAUT2 is more appropriate for inertia integration concerning reliability criteria and explanatory power. We further derive recommendations on adapting UTAUT2 to continuance contexts and on conceptualizing inertia for different research approaches.
TIIM: technology-independent interference mitigation for low-power wireless networks

The rise of heterogeneity in wireless technologies operating in the unlicensed bands has been shown to adversely affect the performance of low-power wireless networks. Cross-Technology Interference (CTI) is highly uncertain and raises the need for agile methods that assess the channel conditions and apply actions maximizing communication success. In this paper, we present TIIM, a lightweight Technology-Independent Interference Mitigation solution that detects, quantifies, and reacts to CTI in realtime. TIIM employs a lightweight machine learning classifier to (i) decide whether communication is viable over the interfered link, (ii) characterize the ambient conditions and apply the best coexistence mitigation strategy. We present an in-depth experimental characterization of the effect of CTI on 802.15. 4 links, which motivated and influenced the design of TIIM. Our evaluation shows that TIIM, while exposed to extensive and heterogeneous interference, can achieve a total PRR improvement of 30% with an additional transmission overhead of 5.6%.
Tumor Suppressor Pten Inhibits Nuclear Accumulation of β-Catenin and T Cell/Lymphoid Enhancer Factor 1–Mediated Transcriptional Activation

β-Catenin is a protein that plays a role in intercellular adhesion as well as in the regulation of gene expression. The latter role of β-catenin is associated with its oncogenic properties due to the loss of expression or inactivation of the tumor suppressor adenomatous polyposis coli (APC) or mutations in β-catenin itself. We now demonstrate that another tumor suppressor, PTEN, is also involved in the regulation of nuclear β-catenin accumulation and T cell factor (TCF) transcriptional activation in an APC-independent manner. We show that nuclear β-catenin expression is constitutively elevated in PTEN null cells and this elevated expression is reduced upon reexpression of PTEN. TCF promoter/luciferase reporter assays and gel mobility shift analysis demonstrate that PTEN also suppresses TCF transcriptional activity. Furthermore, the constitutively elevated expression of cyclin D1, a β-catenin/TCF–regulated gene, is also suppressed upon reexpression of PTEN. Mechanistically, PTEN increases the phosphorylation of β-catenin and enhances its rate of degradation. We define a pathway that involves mainly integrin-linked kinase and glycogen synthase kinase 3 in the PTEN-dependent regulation of β-catenin stability, nuclear β-catenin expression, and transcriptional activity. Our data indicate that β-catenin/TCF–mediated gene transcription is regulated by PTEN, and this may represent a key mechanism by which PTEN suppresses tumor progression.
ADMM for maximum correntropy criterion

The correntropy provides a robust criterion for outlier-insensitive machine learning, and its maximisation has been increasingly investigated in signal and image processing. In this paper, we investigate the problem of unmixing hyperspectral images, namely decomposing each pixel/spectrum of a given image as a linear combination of other pixels/spectra called endmembers. The coefficients of the combination need to be estimated subject to the nonnegativity and the sum-to-one constraints. In practice, some spectral bands suffer from low signal-to-noise ratio due to acquisition noise and atmospheric effects, thus requiring robust techniques for the unmixing problem. In this work, we cast the unmixing problem as the maximization of a correntropy criterion, and provide a relevant solution using the alternating direction method of multipliers (ADMM) method. Finally, the relevance of the proposed approach is validated on synthetic and real hyperspectral images, demonstrating that the correntropy-based unmixing is robust to outlier bands.
Analysis of first-come-first-serve parallel job scheduling

Uwe Schwiegelshohnt This paper analyzes job scheduling for parallel computers by using theoretical and experimental means. Based on existing architectures we first present a machine and a job model. Then, we propose a simple on-line algorithm employing job preemption without migration and derive theoretical bounds for the performance of the algorithm. The algorithm is experimentally evaluated with trace data from a large computing facility. These experiments show that the algorithm is highly sensitive on parameter selection and that substantial performance improvements over existing (non-preemptive) scheduling methods are possible.
Observer Based Control of a Class of Nonlinear Fractional Order Systems Using LMI

Design of an observer based controller for a class of fractional order systems has been done. Fractional order mathematics is used to express the system and the proposed observer. Fractional order Lyapunov theorem is used to derive the closed-loop asymptotic stability. The gains of the observer and observer based controller are derived systematically using the linear matrix inequality approach. Finally, the simulation results demonstrate validity and effectiveness of the proposed observer based controller.
Phonics Versus Look-Say: Transfer to New Words.

TRANSFER OF skills to new tasks is the epitome of successful learning? do beginning reading approaches differ in providing for transfer? Jeffrey and Samuels (1967), who replicated and extended research conducted by Silberman (1964) and Bishop (1964), compared sounds (phonic) and word (look-say) beginning reading approaches and reported higher transfer scores with the sounds approach. The study I report on here also compares teaching of "sounds" vs. "words" and addresses some concerns raised by Jeffrey and Samuels about the generalizability of their findings. The letters presented in the Jeffrey and Samuels experiment had a one to-one grapheme-phoneme correspondence. Jeffrey and Sam uels cautioned that positive transfer effects may not extend to irregular words that lack this one-to-one cor respondence. Therefore, in the cur rent study, transfer from sounds and word training to irregular as well as regular words was measured. A second concern of Jeffrey and Samuels was the limited
Separation and determination synchronously by multichannel mode‐filtered light capillary electrochromatography

Mode‐filtered light capillary electrophoresis (CE) was developed for capillary electrochromatography (CEC) by applying annular columns of different size (250, 320, and 530 μm) and a bovine serum albumin (BSA)‐modified chiral stationary phase. BSA was encapsulated on the pretreated surface of an optic fiber and the inner wall of a capillary using sol‐gel technique with a resultant larger active stationary phase area. The coating was examined by atomic force microscopy (AFM) and Fourier transform infrared (FT‐IR). The separation of DL‐tryptophan (10 mM) was investigated under different voltage/current conditions.
Anisotropic diffusion of surfaces and functions on surfaces

We present a unified anisotropic geometric diffusion PDE model for smoothing (fairing) out noise both in triangulated two-manifold surface meshes in IR3 and functions defined on these surface meshes, while enhancing curve features on both by careful choice of an anisotropic diffusion tensor. We combine the C1 limit representation of Loop's subdivision for triangular surface meshes and vector functions on the surface mesh with the established diffusion model to arrive at a discretized version of the diffusion problem in the spatial direction. The time direction discretization then leads to a sparse linear system of equations. Iteratively solving the sparse linear system yields a sequence of faired (smoothed) meshes as well as faired functions.
Biological sequence analysis through the one-dimensional percolation transform and its enhanced version

MOTIVATION The necessity to characterize the spatial uniformity (or lack of it) of symbols in biological sequences, given its implications for identification of the properties of the structures associated with the sequences. METHODS A one-dimensional version of a recently introduced percolation-based approach is presented, which allows the accurate quantification of symbol distributions even in the presence of co-existing densities. An enhanced version of this methodology, which uses an agglomerative process to organize hierarchically the sequence into subsequences, is also proposed and illustrated. 3. RESULTS The potential of the proposed methodology is illustrated with respect to synthetic and real data (1881 zebrafish and 1200 Xenopus proteins) and compared to two alternative multiscale methodologies, with encouraging results including the possibility to identify particularly remarkable amino acid arrangements in proteins. 4. CONTACT luciano@if.sc. usp.br.
Adaptive dynamic surface tracking control of underactuated surface vessels with unknown disturbances

This paper aims at accomplish the trajectory tracking control of an underactuated surface vessel (USV) with unknown disturbances. An adaptive dynamic surface control (ADSC) scheme for the USV is proposed in this paper. And an adaptive method is employed to approximate unknown disturbances. The tracking error dynamic system is divided into two cascaded subsystems, then we can separately design the control laws for two independent inputs of an USV by using the ADSC method. Dynamic surface control is including or using the backstepping technique, and avoid derivation of virtual control signals and the curse of dimension, thereby resulting in global asymptotic stability. Simulation studies demonstrate that proposed ADSC scheme is effective.
Comparison of 7.2% hypertonic saline - 6% hydroxyethyl starch solution and 6% hydroxyethyl starch solution after the induction of anesthesia in patients undergoing elective neurosurgical procedures

OBJECTIVE: The ideal solution for fluid management during neurosurgical procedures remains controversial. The aim of this study was to compare the effects of a 7.2% hypertonic saline - 6% hydroxyethyl starch (HS-HES) solution and a 6% hydroxyethyl starch (HES) solution on clinical, hemodynamic and laboratory variables during elective neurosurgical procedures. METHODS: Forty patients scheduled for elective neurosurgical procedures were randomly assigned to the HS-HES group or the HES group. After the induction of anesthesia, patients in the HS-HES group received 250 mL of HS-HES (500 mL/h), whereas the patients in the HES group received 1,000 mL of HES (1000 mL/h). The monitored variables included clinical, hemodynamic and laboratory parameters. Chictr.org: ChiCTR-TRC-12002357 RESULTS: The patients who received the HS-HES solution had a significant decrease in the intraoperative total fluid input (p<0.01), the volume of Ringer's solution required (p<0.05), the fluid balance (p<0.01) and their dural tension scores (p<0.05). The total urine output, blood loss, bleeding severity scores, operation duration and hemodynamic variables were similar in both groups (p>0.05). Moreover, compared with the HES group, the HS-HES group had significantly higher plasma concentrations of sodium and chloride, increasing the osmolality (p<0.01). CONCLUSION: Our results suggest that HS-HES reduced the volume of intraoperative fluid required to maintain the patients undergoing surgery and led to a decrease in the intraoperative fluid balance. Moreover, HS-HES improved the dural tension scores and provided satisfactory brain relaxation. Our results indicate that HS-HES may represent a new avenue for volume therapy during elective neurosurgical procedures.
Memory-based active learning for French broadcast news

Stochastic dependency parsers can achieve very good results when they are trained on large corpora that have been manually annotated. Active learning is a procedure that aims at reducing this annotation cost by selecting as few sentences as possible that will produce the best possible parser. We propose a new selective sampling function for Active Learning that exploits two memory-based distances to find a good compromise between parser uncertainty and sentence representativeness. The reduced dependency between both parsing and selection models opens interesting perspectives for future models combination. The approach is validated on a French broadcast news corpus creation task dedicated to dependency parsing. It outperforms the baseline uncertainty entropy-based selective sampling on this task. We plan to extend this work with self- and co-training methods in order to enlarge this corpus and produce the first French broadcast news Tree Bank.
A Topological Framework for Interactive Queries on 3D Models in the Web

Several technologies exist to create 3D content for the web. With X3D, WebGL, and X3DOM, it is possible to visualize and interact with 3D models in a web browser. Frequently, three-dimensional objects are stored using the X3D file format for the web. However, there is no explicit topological information, which makes it difficult to design fast algorithms for applications that require adjacency and incidence data. This paper presents a new open source toolkit TopTri (Topological model for Triangle meshes) for Web3D servers that builds the topological model for triangular meshes of manifold or nonmanifold models. Web3D client applications using this toolkit make queries to the web server to get adjacent and incidence information of vertices, edges, and faces. This paper shows the application of the topological information to get minimal local points and iso-lines in a 3D mesh in a web browser. As an application, we present also the interactive identification of stalactites in a cave chamber in a 3D web browser. Several tests show that even for large triangular meshes with millions of triangles, the adjacency and incidence information is returned in real time making the presented toolkit appropriate for interactive Web3D applications.
The 2.2-Kilobase Latency-Associated Transcript of Herpes Simplex Virus Type 2 Does Not Modulate Viral Replication, Reactivation, or Establishment of Latency in Transgenic Mice

ABSTRACT To better understand the mechanisms responsible for the observed effects of deletions in the promoter region of the latency-associated transcript (LAT) gene in impairing herpes simplex virus (HSV) reactivation, we generated mice transgenic for a 5.5-kb HSV type 2 (HSV-2) genomic fragment spanning the major LAT, along with the LAT promoter and flanking regions, in the C57BL/6 background. The mice expressed abundant 2.2-kb major LATs in trigeminal ganglia (TG) and other tissues. The effects of the transgene on HSV-2 infection, latency, and reactivation were assessed. When infected with wild-type (WT) HSV-2 or its LAT promoter deletion (LAT−) mutant, primary lung fibroblast lines established from normal C57BL/6 and transgenic mice supported virus growth equally well. The replication of these viruses in the mouse eye and their spread to TG and brains were similar. The quantities of latent viral DNA in TG of transgenic and normal mice, as determined by real-time PCR, were comparable. UV light-induced reactivation of the LAT− mutant from transgenic mice (0 to 7%) was no more frequent than that from normal mice (0 to 14%), while WT virus was reactivated from 13 to 54% of normal mice and 22 to 54% of transgenic mice. The cumulative data indicate that, when expressed transgenically, the HSV-2 major LAT cannot influence HSV-2 infection or latency and cannot complement the defect in reactivation of the LAT− mutant. These results imply that the phenotype of reduced reactivation associated with the LAT− mutant is related to a function encoded in the LAT promoter but not to the major LAT itself.
Comparative evaluation of Fuzzy-PI and PI control methods for a three phase grid connected inverter

This research addresses the issue of power electronics control scheme for grid integration of a distribution generation unit. For the improvement of the current control and DC bus voltage control, the application of the PI and Fizzy-PI controller is investigated. Theoretical and mathematical analysis of the internal structure of the PI and Fuzzy-PI controller is carried out. Using the software Matlab/Simulink, the behavior of the controllers for DC bus voltage and current control is investigated. A comparative evaluation of the controllers both in steady state and transient response is presented. Furthermore the PI and Fuzzy-PI controller are compared based on THDi index of the inverter's current. The ability of the inverter to provide ancillary services to the electric power system though the uninterrupted compensation of the reactive power of the load is studied, as well.
Determinants Of Jobs Seekers’ Intention In Using E-Recruitments: Insight From Indonesia

In a digital world, job seekers prefer to use e-recruitment in looking for a vacancy. Thus, the explanation of the determinants of their attitude in using this technology is left unobserved. This article reports the result of a survey study on how users utilize e-recruitment to search for works. Three hundred eighty-five just-graduated undergraduate students answered questions regarding their intention of using the e-recruitment under Technology Acceptance Model. We propose Perceived Usefulness, Perceived Ease of Use, and Perceived of Enjoyment as the determinants of the job seekers intention. Results showed that those three variables influence the decision making of job seekers. We found also Perceived Usefulness is the mediating effect for jobs seekers in easy-to-use and enjoy feeling. This article provides evidence that e-recruitment has to be friendly user and fun to use to attract job seekers intention. Keywords: E-Recruitment, Perceived Usefulness, Perceived Ease of Use, Perceived of Enjoyment, Job Seekers
Scheduling with soft constraints

In a behavioral synthesis system, a typical approach used to guide the scheduler is to impose hard constraints on the relative timing between operations considering performance, area, power, etc., so that the resulting RTL design is favorable in these aspects. The mechanism is often flawed in practice because many such constraints are actually soft constraints which are not necessary, and the constraint system may become inconsistent when many hard constraints are added for different purposes. This paper describes a scheduler that distinguishes soft constraints from hard constraints when exploring the design space. We propose a special class of soft constraints called integer-difference soft constraints, which lead to a totally unimodular constraint matrix in an integer linear programming formulation. By exploiting the total unimodularity, the problem can be solved optimally and efficiently using a linear programming relaxation without expensive branch and bound procedures. We also show how the proposed method can be used to support a variety of design considerations. As an example application, we apply the method to the problem of low-power synthesis with operation gating. In a set of experiments on real-world designs, our method achieves an average of 33.9% reduction in total power; it outperforms a previous method by 17.1% on average and gives close-to-optimal solutions on several designs.
A computationally-efficient single-channel speech enhancement algorithm for monaural hearing aids

A computationally-efficient single-channel speech enhancement algorithm to improve intelligibility in monaural hearing aids is presented in this paper. The algorithm combines a novel set of features with a simple supervised machine learning technique to estimate the frequency-domain Wiener filter for noise reduction, using extremely low computational resources. Results show a noticeable intelligibility improvement in terms of PESQ score and SNRESI, even for low input SNR, using only a 7% of the computational resources available in a state-of-the-art commercial hearing aid. The performance of the algorithm is comparable to the performance of current algorithms that use more computationally complex features and learning schemas.
Assessment of broadband SNR estimation for hearing aid applications

An accurate estimation of the broadband input signal-to-noise ratio (SNR) is a prerequisite for many hearing-aid algorithms. An extensive comparison of three SNR estimation algorithms was performed. Moreover, the influence of the duration of the analysis window on the SNR estimation performance was systematically investigated. The most accurate approach utilized an estimation of the clean speech power spectral density (PSD) and the noisy speech power across a sliding window of 1280 ms and achieved an total SNR estimation error below 3 dB across a wide variety of background noises and input SNRs.
Delay tolerant routing protocol for heterogeneous marine vehicular mobile ad-hoc network

Delay tolerant networks (DTN) are characterized by lack of end-to-end communications and stable infrastructures. This paper deals with DTN networks consisting of a number of heterogeneous mobile fishing vessels where some nodes, referred to as adaptive nodes, are capable of communicating through long-range Wi-Fi whereas other nodes are having simple Wi-Fi access network. The nodes form different clusters consisting of adaptive nodes and access nodes. Message routing in this heterogeneous network happens through adaptive nodes if the source and destination nodes belong to different clusters. Real data from field study reflects that mobile nodes in this network follow Gaussian-Markov mobility model and may have high inter-meeting arrival time based on deployment and node density. Our proposed DTN routing protocol incorporates simple encounter-based message forwarding and achieves lower latency and high delivery probability in the range of 90–98% for most of the scenarios. The proposed protocol is verified through a realistic mobile ad-hoc wireless simulator.