Miracle-dz/UniFAR-FTUs huggingface dataset:
Sticker: A 0.41-62.1 TOPS/W 8Bit Neural Network Processor with Multi-Sparsity Compatible Convolution Arrays and Online Tuning Acceleration for Fully Connected Layers

Neural Networks (NNs) have emerged as a fundamental technology for machine learning. The sparsity of weight and activation in NNs varies widely from 5%-90% and can potentially lower computation requirements. However, existing designs lack a universal solution to efficiently handle different sparsity in various layers and neural networks. This work, named STICKER, first systematically explores NN sparsity for inference and online tuning operations. Its major contributions are: 1) autonomous NN sparsity detector that switches the processor modes; 2) Multi-sparsity compatible Convolution (CONV) PE arrays that contain a multi-mode memory supporting different sparsity, and the set-associative PEs supporting both dense and sparse operations and reducing 92% memory area compared with previous hash memory banks; 3) Online tuning PE for sparse FCs that achieves 32.5x speedup compared with conventional CPU, using quantization center-based weight updating and Compressed Sparse Column (CSC) based back propagations. Peak energy efficiency of the 65nm STICKER chip is up to 62.1 TOPS/W at 8bit data length.
BLEU is Not Suitable for the Evaluation of Text Simplification

BLEU is widely considered to be an informative metric for text-to-text generation, including Text Simplification (TS). TS includes both lexical and structural aspects. In this paper we show that BLEU is not suitable for the evaluation of sentence splitting, the major structural simplification operation. We manually compiled a sentence splitting gold standard corpus containing multiple structural paraphrases, and performed a correlation analysis with human judgments. We find low or no correlation between BLEU and the grammaticality and meaning preservation parameters where sentence splitting is involved. Moreover, BLEU often negatively correlates with simplicity, essentially penalizing simpler sentences.
Determination of the Measurement Uncertainty of Direct and Indirect Efficiency Measurement Methods in Permanent Magnet Synchronous Machines

The use of permanent magnet synchronous machines to achieve high performance and high efficiency in the modern motor and generator industries has increased rapidly in recent years. The existing efficiency determining methods and standards do not however consider measurement uncertainties during loss and efficiency calculations of such machines. In this paper, the determination of the efficiency of permanent magnet synchronous machines using direct and indirect methods is presented and the measurement uncertainty is determined using the software called GUM Workbench “Guide to the Expression of Uncertainty in Measurement” while assessing the results of efficiency measurements.
Nondestructive Testing for Shallow Defect of Ferromagnetic Objects Based on Magnetic Probe Structure.

The Electromagnetic inspection technique plays an important role in the nondestructive testing (NDT) for many decades. Today, this NDT area is rather wide and significant. The magnetic flux leakage (MFL) technology is one of the most widely used electromagnetic nondestructive testing (NDT) techniques. MFL tools use permanent magnets to magnetize the detected object near to saturation flux density [1], [2]. Generally, the magnetizer mechanism of MFL are bulky and heavy. Although the shape of the opening and the depth profile of an arbitrary three-dimensional (3-D) defect from MFL measurements can be estimated [3], the inversion method is complicated and susceptible by the magnetization factors. For different shapes and different sizes of detected object, the magnetizer mechanism of MFL should be designed individually, and this requires a lot of time and experimentation. In this paper, a simple and portable magnetic detection device is designed with permanent magnets, magnetic probe structure and the Hall sensors. Compared with the magnetizer mechanism of MFL, the magnetic detection device is very light, low cost and easy to design and manufacture. The magnetic detection device can make qualitative, and quantitative evaluation for shallow defect of ferromagnetic objects.
Bot Conversations are Different: Leveraging Network Metrics for Bot Detection in Twitter

Automated social media bots have existed almost as long as the social media platforms they inhabit. Although efforts have long existed to detect and characterize these autonomous agents, these efforts have redoubled in the recent months following sophisticated deployment of bots by state and non-state actors. This research will study the differences between human and bot social communication networks by conducting an account snow ball data collection, and then evaluate features derived from this communication network in several bot detection machine learning models.
An Empirical Study on the Adequacy of MBPTA for Tasks Executed on a Complex Computer Architecture with Linux

In order to support the computational demand of Real-Time Systems' (RTSs‘) applications, the use of complex hardware will be fundamental. This fact makes analysis of software to derive Worst-Case Execution Time (WCET) an increasingly harder challenge. State-of-the-art WCET analysis techniques are hampered by the ever-growing cost and complexity of obtaining accurate knowledge of the internal operation of advanced processors, and by difficulties in reliably associating variable execution times with tasks' worst-case behaviour through measurement-based techniques. In this work, we performed an empirical assessment of the adequacy of Measurement-Based Probabilistic Timing Analysis (MBPTA) to estimate the pWCET - through Extreme Value Theory (EVT) - of a task executed on a complex computer architecture with Linux. The proposed evaluation has the objective of detecting whether EVT can be deemed suitable for determining pWCET estimates for tasks executed on complex computers.
Suppressing the Chills: Effects of Musical Manipulation on the Chills Response

Research on musical chills has linked the response to multiple musical features; however, there exists no study that has attempted to manipulate musical stimuli to enable causal inferences, meaning current understanding is based mainly on correlational evidence. In the current study, participants who regularly experience chills (N = 24) listened to an original and manipulated version of three pieces reported to elicit chills in a previous survey. Predefined chills sections were removed to create manipulated conditions. The effects of these manipulations on the chills response were assessed through continuous self-reports, and skin conductance measurements. Results show that chills were significantly less frequent following stimulus manipulation across all three pieces. Continuous measurements of chills intensity were significantly higher in the chills sections compared with control sections in the pieces; similar patterns were found for phasic skin conductance, although some differences emerged. Continuous measurements also correlated with psychoacoustic features such as loudness, brightness and roughness in two of the three pieces. Findings are discussed in terms of understanding structural and acoustic features and chills experiences within their local music contexts, the necessity of experimental approaches to musical chills, and the possibility of different features activating different underlying mechanisms.
Long-Range Temporal Correlations of Patients in Minimally Conscious State Modulated by Spinal Cord Stimulation

Spinal cord stimulation (SCS) has been shown to improve the consciousness levels of patients with disorder of consciousness (DOC). However, the underlying mechanisms of SCS remain poorly understood. This study recorded resting-state electroencephalograms (EEG) from 16 patients with minimally conscious state (MCS), before and after SCS, and investigated the mechanisms of SCS on the neuronal dynamics in MCS patients. Detrended fluctuation analysis (DFA), combined with surrogate data method, was employed to measure the long-range temporal correlations (LRTCs) of the EEG signals. A surrogate data method was utilized to acquire the genuine DFA exponents (GDFAE) reflecting the genuine LRTCs of brain activity. We analyzed the GDFAE in four brain regions (frontal, central, posterior, and occipital) at five EEG frequency bands [delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–45 Hz)]. The GDFAE values ranged from 0.5 to 1, and showed temporal and spatial variation between the pre-SCS and the post-SCS states. We found that the channels with GDFAE spread wider after SCS. This phenomenon may indicate that more cortical areas were engaged in the information integration after SCS. In addition, the GDFAE values increased significantly in the frontal area at delta, theta, and alpha bands after SCS. At the theta band, a significant increase in GDFAE was observed in the occipital area. No significant change was found at beta or gamma bands in any brain region. These findings show that the enhanced LRTCs after SCS occurred primarily at low-frequency bands in the frontal and occipital regions. As the LRTCs reflect the long-range temporal integration of EEG signals, our results indicate that information integration became more “complex” after SCS. We concluded that the brain activities at low-frequency oscillations, particularly in the frontal and occipital regions, were improved by SCS.
Analysis of Channel Tortuosity using 8 m Long Laboratory Sparks

The tortuosity of the channel is defined as “Mean absolute angle change of the angle change and it measures how strongly the tortuous path of the channel of lightning/laboratory spark is twisting. 8 m Long laboratory sparks and high speed (20000 frames per second) technology used for this experiment. Using these data it has been calculated the channel tortuosity of 8 m long sparks and vertical profile of channel tortuosity. In addition to that spectral analysis of the angel change of the twisting path of the channel has been done in this study.
Classifying Referential and Non-referential It Using Gaze

When processing a text, humans and machines must disambiguate between different uses of the pronoun it, including non-referential, nominal anaphoric or clause anaphoric ones. In this paper we use eye-tracking data to learn how humans perform this disambiguation and use this knowledge to improve the automatic classification of it. We show that by using gaze data and a POS-tagger we are able to significantly outperform a common baseline and classify between three categories of it with an accuracy comparable to that of linguistic-based approaches. In addition, the discriminatory power of specific gaze features informs the way humans process the pronoun, which, to the best of our knowledge, has not been explored using data from a natural reading task.
Dave the debater: a retrieval-based and generative argumentative dialogue agent

In this paper, we explore the problem of developing an argumentative dialogue agent that can be able to discuss with human users on controversial topics. We describe two systems that use retrieval-based and generative models to make argumentative responses to the users. The experiments show promising results although they have been trained on a small dataset.
Altered Ca2+ and Na+ Homeostasis in Human Hypertrophic Cardiomyopathy: Implications for Arrhythmogenesis

Hypertrophic cardiomyopathy (HCM) is the most common mendelian heart disease, with a prevalence of 1/500. HCM is a primary cause of sudden death, due to an heightened risk of ventricular tachyarrhythmias that often occur in young asymptomatic patients. HCM can slowly progress toward heart failure, either with preserved or reduced ejection fraction, due to worsening of diastolic function. Accumulation of intra-myocardial fibrosis and replacement scars underlies heart failure progression and represents a substrate for sustained arrhythmias in end-stage patients. However, arrhythmias and mechanical abnormalities may occur in hearts with little or no fibrosis, prompting toward functional pathomechanisms. By studying viable cardiomyocytes and trabeculae isolated from inter-ventricular septum samples of non-failing HCM patients with symptomatic obstruction who underwent myectomy operations, we identified that specific abnormalities of intracellular Ca2+ handling are associated with increased cellular arrhytmogenesis and diastolic dysfunction. In HCM cardiomyocytes, diastolic Ca2+ concentration is increased both in the cytosol and in the sarcoplasmic reticulum and the rate of Ca2+ transient decay is slower, while the amplitude of Ca2+-release is preserved. Ca2+ overload is the consequence of an increased Ca2+ entry via L-type Ca2+-current [due to prolongation the action potential (AP) plateau], combined with a reduced rate of Ca2+-extrusion through the Na+/Ca2+ exchanger [due to increased cytosolic (Na+)] and a lower expression of SERCA. Increased late Na+ current (INaL) plays a major role, as it causes both AP prolongation and Na+ overload. Intracellular Ca2+ overload determines an higher frequency of Ca2+ waves leading to delayed-afterdepolarizations (DADs) and premature contractions, but is also linked with the increased diastolic tension and slower relaxation of HCM myocardium. Sustained increase of intracellular [Ca2+] goes hand-in-hand with the increased activation of Ca2+/calmodulin-dependent protein-kinase-II (CaMKII) and augmented phosphorylation of its targets, including Ca2+ handling proteins. In transgenic HCM mouse models, we found that Ca2+ overload, CaMKII and increased INaL drive myocardial remodeling since the earliest stages of disease and underlie the development of hypertrophy, diastolic dysfunction and the arrhythmogenic substrate. In conclusion, diastolic dysfunction and arrhythmogenesis in human HCM myocardium are driven by functional alterations at cellular and molecular level that may be targets of innovative therapies.
Assessment of Characteristic Boundary Conditions Based on the Artificial Compressibility Method in Generalized Curvilinear Coordinates for Solution of the Euler Equations

Abstract The characteristic boundary conditions are applied and assessed for the solution of incompressible inviscid flows. The two-dimensional incompressible Euler equations based on the artificial compressibility method are considered and then the characteristic boundary conditions are formulated in the generalized curvilinear coordinates and implemented on both the far-field and wall boundaries. A fourth-order compact finite-difference scheme is used to discretize the resulting system of equations. The solution methodology adopted is more suitable for this assessment because the Euler equations and the high-accurate numerical scheme applied are quite sensitive to the treatment of boundary conditions. Two benchmark test cases are computed to investigate the accuracy and performance of the characteristic boundary conditions implemented compared to the simplified boundary conditions. The sensitivity of the solution obtained by applying the characteristic boundary conditions to the different numerical parameters is also studied. Indications are that the characteristic boundary conditions applied improve the accuracy and the convergence rate of the solution compared to the simplified boundary conditions.
Dynamic Formation Control Over Directed Networks Using Graphical Laplacian Approach

This paper investigates the dynamic formation control problem for multi-agent systems over directed networks, in which a desired spatial shape is time-varying instead of fixed one as usually assumed in the literature. Inspired by the fact that the existing approaches, including absolute positions based, relative positions based, inter-agent distances based, and inter-agent bearings based, for specifying a formation shape are not invariant under all three transformations: translations, rotations, and scalings, a novel specification for formation shapes is proposed that is invariant under translations, rotations, and scalings in two- and three-dimensional spaces, and thus more intrinsic. In doing so, a new notion, called matrix-valued Laplacian, for graphs is introduced in detail along with some useful properties. It is demonstrated that the matrix-valued Laplacian provides much flexibility. Subsequently, two controllers are designed for guaranteeing the achievement of a dynamic formation shape. It is proved that arbitrary dynamic geometric shape can be reached by the designed controllers. Finally, two numerical examples are provided for demonstrating the effectiveness of the theoretical results.
Constructing an Accurate and a High-Performance Power Profiler for Embedded Systems and Smartphones

The main objective of this paper is to present a new accurate power profiler for embedded systems and smartphones. The second objective is, for it, to be a tutorial explaining the main steps to build power profilers for embedded and mobile systems, in general. We start our work by firstly describing the general methodology of building a power profiler. Then, we showcase how each step is undertaken to build a profiler with two power models. The first one was an artificial neural network (called N2) that presented a lot of noise in its estimation. After debugging and improvement, the second model, a NARX neural network (we call N3) was built. It eliminated all the drawback of the first model and had a mean absolute percentage error of 2.8%.
The leader propagation velocity in long air gaps

Experimental measurements of long gap discharges and its interpretation are the base of engineering equations and complex models to design clearance distances, lightning protection systems, among others. Parameters like leader propagation velocity, average electric field of the leader channel, stability electric field of the streamer region, etc. are derived from experimental measurements for rod-plane arrangements. However, in high voltage engineering geometries are not only rod-plane arrangements but also rounded electrode geometries. Experimental measurements of sphere – plane arrangements are presented in this paper. Attention is given to the velocity of propagation of the leader. The velocity of propagation of the leader is compared for two different applied voltage conditions, such as overvoltage and non-overvoltage. Experimental observations indicate that the velocity of the leader does not have a linear relationship with the increment of the applied voltage, as described by other authors for rod-plane arrangements. By means of a model based on the physics of the discharge, it is observed that the velocity of propagation of the leader depends on the injected charge to the leader channel. The injected charge depends on the background electric field, the potential at the leader tip, the steepness of the applied voltage waveform, among other parameters.
Fast Switching Planar Power Module With SiC MOSFETs and Ultra-low Parasitic Inductance

Parasitic inductances caused by the package of semiconductor devices in power converters, are limiting the switching speed and giving rise to higher switching losses than necessary. In this study a half-bridge planar power module with Silicon Carbide (SiC) MOSFET bare dies was designed and manufactured for ultra-low parasitic inductance. The circuit structure was simulated and the parasitic inductances were extracted from ANSYS-Q3D. The values were then fed into LT-Spice to simulate the electrical behavior of the half-bridge. The experimental and simulation results were compared to each other and were used to adjust and easily extend the simulation model with additional MOSFETs for higher current capability. It was shown that the proposed planar module, with four parallel SiC MOSFETs at each position, is able to switch 600V and 400A during 40 and 17ns with EON and EOFF equal to 3.1 and 1.3mJ, respectively. Moreover, unlike the commercial modules, this design allows double-sided cooling to extract the generated heat from the device, resulting in lower operating temperature.
Lifetime Reliability-Aware Digital Synthesis

CMOS downscaling poses a growing concern for circuit lifetime reliability. Bias temperature instability (BTI) is a major source of transistor aging, causing a threshold voltage increase in CMOS devices, and affecting circuit timing. This paper presents an aging mitigation approach that can be incorporated into standard synthesis. We propose a technique to restructure the logic expressions for aging-critical gates and to reduce the BTI stress duty cycle. A new technology mapping strategy is demonstrated, including a forward pass to select the most suitable cells and implement the optimized logic, and a backward pass to validate remapped circuits by restricting the negative slacks. The negative slacks produced in the mapping stage are eliminated by gate-level optimization, which aims to optimize a circuit to improve lifetime reliability under timing and area constraints. It employs a sensitivity metric that can be adjusted according to the design specifications to pick the most favorable transformation in terms of timing, lifetime or both. Our results show a 59.1% lifetime improvement with 0.86% area overhead on average. Compared with conventional over-design, a 28.29% higher lifetime improvement is realized. In addition, our approach can optimize a circuit under each corner case, considering both process variations and input data.
Analyzing Correlated Evolution of Multiple Features Using Latent Representations

Statistical phylogenetic models have allowed the quantitative analysis of the evolution of a single categorical feature and a pair of binary features, but correlated evolution involving multiple discrete features is yet to be explored. Here we propose latent representation-based analysis in which (1) a sequence of discrete surface features is projected to a sequence of independent binary variables and (2) phylogenetic inference is performed on the latent space. In the experiments, we analyze the features of linguistic typology, with a special focus on the order of subject, object and verb. Our analysis suggests that languages sharing the same word order are not necessarily a coherent group but exhibit varying degrees of diachronic stability depending on other features.
Easy Lock-Free Indexing in Non-Volatile Memory

Large non-volatile memories (NVRAM) will change the durability and recovery mechanisms of main-memory database systems. Today, these systems make operations durable through logging and checkpointing to secondary storage, and recover by rebuilding the in-memory database (records and indexes) from on-disk state. A main-memory database stored in NVRAM, however, can potentially recover instantly after a power failure. Modern main-memory databases typically use lock-free index structures to enable a high degree of concurrency. Thus NVRAM-resident databases need indexes that are both lock-free, persistent, and able to recover (almost) instantly after a crash. In this paper, we show how to easily build such index structures. A key enabling component of our scheme is a multi-word compare-and-swap operation, PMwCAS, that is lock-free, persistent, and efficient. PMwCAS significantly reduces the complexity of building lock-free indexes, which we illustrate by implementing both doubly-linked skip lists and the Bw-tree lock-free B+-tree for NVRAM. Experimental results show that PMwCAS's runtime overhead is very low (~4–6% under realistic workloads). This overhead is sufficiently low that the same implementation can be used for both DRAM and NVRAM resident indexes.