Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining moisture content in concrete under simulated precipitation using ultrasonic propagation time measurements

The use of ultrasound is recognised as a means to obtain information about concrete with non-destructive testing. Various aspects of the material can be characterised. However, the scientific literature in this area is quite sparse. The present paper therefore addresses the issue of moisture content, and related compressive strength, in a systematic experimental manner. The moisture content profiles of 24 concrete cubes under constant simulated precipitation over 24 h were investigated using ultrasonic methods. Different values of water/cement ratio, duration of pre-curing vibration and curing regime were used. The propagation time of ultrasonic compression wave pulses gave a good correlation with gravimetric moisture content and it was found that the type of curing and the amount of vibration had the greatest impact on the propagation time of the ultrasonic wave. The moisture diffusion coefficient was estimated using a simple finite difference model and good agreement was achieved with experimental measurements.
Adaptive Q-Structure for Agent Formations

In this paper, we further extend the Queue-formation structure (or Q-structure) in 3D spaces with additional features including: (i) specifying orientation information, (ii) a mechanism for forming sub-formations before the convergence into the final formation, and (iii) adapting the communication structure when communications is limited. Bobber-agents are used to guide each vehicle toward the appropriate queue, by acting as intermediate targets. The proposed scheme relies mainly on simple behaviors between embodied and virtual agents and is computationally inexpensive method. Extensive simulations show the effectiveness of the proposed method.
Learning Class-to-Image Distance with Object Matchings

We conduct image classification by learning a class-to-image distance function that matches objects. The set of objects in training images for an image class are treated as a collage. When presented with a test image, the best matching between this collage of training image objects and those in the test image is found. We validate the efficacy of the proposed model on the PASCAL 07 and SUN 09 datasets, showing that our model is effective for object classification and scene classification tasks. State-of-the-art image classification results are obtained, and qualitative results demonstrate that objects can be accurately matched.
60GHz transmitter front-end in 40nm LP-CMOS with improved back-off efficiency

A three-stage, transformer-coupled class-AB power amplifier (PA) and a super source-follower-based I-Q upconversion mixer are implemented in 40nm LP-CMOS technology. The transmitter (Tx) front-end is designed for multi-Gbps QPSK/QAM-16 signal transmission at 60GHz with improved back-off efficiency. It achieves 5.7% power-added efficiency (PAE) at 5dB back-off with a total power consumption of only 90mW. Power gain and output 1dB compression point (P-1dB) are 22dB and 10.2dBm respectively. A second Tx front-end, based on a class-A PA and Gilbert-cell upconversion mixer, is designed as a benchmark for comparison. With a similar value of P-1dB, PAE of the class-AB prototype at 5dB back-off is three times higher and the total power consumption is 100mW lower than the benchmark Tx.
Plane labeling trinocular stereo matching with baseline recovery

In this paper we present an algorithm which recovers the rigid transformation that describes the displacement of a binocular stereo rig in a scene, and uses this to include a third image to perform dense trinocular stereo matching and reduce some of the ambiguities inherent to binocular stereo. The core idea of the proposed algorithm is the assumption that the binocular baseline is projected to the third view, and thus can be used to constrain the transformation estimation of the stereo rig. Our approach shows improved performance over binocular stereo, and the accuracy of the recovered motion allows to compute optical flow from a single disparity map. These claims are validated with the KITTI 2012 data set.
A varactor tuned microstrip patch antenna

Microstrip patch antennas offer many practical advantages, such as being lightweight, having low profile, able to conform to the body of a host object, and relatively simple and inexpensive to fabricate compared with other types of antennas. One of the principal disadvantages of the microstrip patch antenna is its very narrow bandwidth, and many techniques have been suggested in recent years to improve the bandwidth of the antenna. The use of varactor diodes is one of these techniques implemented in practice. The varactor diode has a nonlinear capacitance characteristic which depends on the applied reverse bias voltage. Such a varactor diode can be mounted near the patch radiator's edge to maximize its tuning effect since the electric field is a maximum at that point. The paper investigates the effect of introducing a varactor diode on the performance of a microstrip patch antenna.
An Effective Method of Automatic Image Mosaic for Remote Video Monitoring System

Current remote video monitoring system in substation can not fully play the role it is supposed to have in real-time active supervision. In order to improve the effect of remote video monitoring system, image mosaic technology is introduced firstly. Then an automatic image mosaic SIFTbased method for remote video monitoring system is proposed. The steps of this method are described in detail, and the implementation process of image mosaic is demonstrated by an example. The experimental results show that the proposed method can perform well, and meet the requirement of real project, which is beneficial to improve the safety and reliability of substation operation.
Discovery of Natural Products Possessing Selective Eukaryotic Readthrough Activity: 3‐epi‐Deoxynegamycin and Its Leucine Adduct

Herein we report the first discovery of natural readthrough products that do not display antimicrobial activity. Two natural negamycins, 3‐epi‐deoxynegamycin and its leucine adduct, isolated 37 years ago, were found to be potent readthrough agents against nonsense mutations of eukaryotes, but not prokaryotes, without displaying antimicrobial activity. These results suggest that the compounds are valuable leads for the development of readthrough drugs against nonsense‐mediated genetic diseases without the potential for contributing to the emergence of drug‐resistant bacteria.
Physical and bonding characteristics of N-doped hydrogenated amorphous silicon carbide films grown by PECVD and annealed by pulsed electron beam

Nitrogen-doped amorphous silicon carbide films were grown by a plasma enhanced chemical vapour deposition (PE CVD) technique. The actual amount of nitrogen in the SiC films is determined by Rutherford backscattering spectrometry (RBS). For irradiation experiments we use electron beams with a kinetic energy 200 keV, a pulse duration of 300 ns, and a beam current of 150 A/cm2. It is found that with increased nitrogen doping and following activation of dopants the resistivity of the amorphous SiC films is substantially reduced.
Acquisition of direct sequence spread spectrum signals with correlated fading

Antenna diversity is an effective way of improving the performance of a communication system, especially for initial acquisition in a narrowband code division multiple access (CDMA) system that operates in a flat fading environment. Earlier attempts to analyze such systems assume independent fading at various antenna elements. However, the diversity gain predicted by these analyses is often unrealizable, since the assumption about the independence of the fades is unrealistic in a spatially constrained system. We relax the assumption about the spatial independence of the fades by employing a realistic model for spatial correlation. Also, we obtain an optimum receiver for initial acquisition that takes into account the particulars of the spatial correlation and present a technique for the analysis of this receiver. We also study the diversity gain available for various parameters of the spatial correlation model and conclude that there exists an optimum number of the antenna elements for an initial acquisition system, based on the spatial correlation of the fades. Further, we consider a wideband multicarrier CDMA system with correlated fades among its subcarriers, which also employs antenna diversity, and apply the techniques used in the narrowband case to obtain an optimum receiver and analyze its performance. Finally, we study the tradeoff between the diversity gain available and the noncoherent loss incurred as the numbers of subcarriers and antenna elements are changed.
Action respecting embedding

Dimensionality reduction is the problem of finding a low-dimensional representation of high-dimensional input data. This paper examines the case where additional information is known about the data. In particular, we assume the data are given in a sequence with action labels associated with adjacent data points, such as might come from a mobile robot. The goal is a variation on dimensionality reduction, where the output should be a representation of the input data that is both low-dimensional and respects the actions (i.e., actions correspond to simple transformations in the output representation). We show how this variation can be solved with a semidefinite program. We evaluate the technique in a synthetic, robot-inspired domain, demonstrating qualitatively superior representations and quantitative improvements on a data prediction task.
A Greener, Quick and Comprehensive Extraction Approach for LC-MS of Multiple Mycotoxins

In food/feed control, mycotoxin analysis is often still performed “one analyte at a time”. Here a method is presented which aims at making mycotoxin analysis environmentally friendlier through replacing acetonitrile by ethyl acetate and reducing chemical waste production by analyzing four mycotoxins together, forgoing sample extract clean-up, and minimizing solvent consumption. For this, 2 g of test material were suspended in 8 mL water and 16 mL ethyl acetate were added. Extraction was accelerated through sonication for 30 min and subsequent addition of 8 g sodium sulfate. After centrifugation, 500 µL supernatant were spiked with isotopologues, dried down, reconstituted in mobile phase, and measured with LC-MS. The method was validated in-house and through a collaborative study and the performance was fit-for-purpose. Repeatability relative standard deviation (RSDs) between 16% at low and 4% at higher contaminations were obtained. The reproducibility RSDs were mostly between 12% and 32%. The trueness of results for T-2 toxin and Zearalenone were not different from 100%, for Deoxynivalenol and HT-2 toxin they were larger than 89%. The extraction was also adapted to a quick screening of Aflatoxin B1 in maize by flow-injection–mass spectrometry. Semi-quantitative results were obtained through standard addition and scan-based ion ratio calculations. The method proved to be a viable greener and quicker alternative to existing methods.
Microstructural Investigations of Ultra-High Performance Concrete Obtained by Pressure Application within the First 24 Hours of Hardening

Abstract In this study, the effect of pressure application (0-50 MPa) to fresh concrete right after casting and during the first 24 hours of hardening has been examined. Supplementary cementitious materials in a form of silica fume, nanosilica and ground quartz sand were used. The aim of pressure application was to reduce porosity, thus improving concrete mechanical properties. Considerable reduction in porosity and a subsequent increase in compressive strength reaching the level of Ultra-High Performance Concrete (UHPC) were achieved. Mechanical and physical properties were tested and gas sorption porosimetry, mercury intrusion porosimetry (MIP), X-ray diffraction (XRD), as well as scanning electron microscopy (SEM) were used for material characterization.
Generating Paraphrases from DBPedia using Deep Learning

Recent deep learning approaches to Natural Language Generation mostly rely on sequence-to-sequence models. In these approaches, the input is treated as a sequence whereas in most cases, input to generation usually is either a tree or a graph. In this paper, we describe an exper-iment showing how enriching a sequential input with structural information improves results and help support the generation of paraphrases.
Characterization of the Substituted N-Triazole Oxindole TROX-1, a Small-Molecule, State-Dependent Inhibitor of Cav2 Calcium Channels

Biological, genetic, and clinical evidence provide validation for N-type calcium channels (CaV2.2) as therapeutic targets for chronic pain. A state-dependent CaV2.2 inhibitor may provide an improved therapeutic window over ziconotide, the peptidyl CaV2.2 inhibitor used clinically. Supporting this notion, we recently reported that in preclinical models, the state-dependent CaV2 inhibitor (3R)-5-(3-chloro-4-fluorophenyl)-3-methyl-3-(pyrimidin-5-ylmethyl)-1-(1H-1,2,4-triazol-3-yl)-1,3-dihydro-2H-indol-2-one (TROX-1) has an improved therapeutic window compared with ziconotide. Here we characterize TROX-1 inhibition of Cav2.2 channels in more detail. When channels are biased toward open/inactivated states by depolarizing the membrane potential under voltage-clamp electrophysiology, TROX-1 inhibits CaV2.2 channels with an IC50 of 0.11 μM. The voltage dependence of CaV2.2 inhibition was examined using automated electrophysiology. TROX-1 IC50 values were 4.2, 0.90, and 0.36 μM at −110, −90, and −70 mV, respectively. TROX-1 displayed use-dependent inhibition of CaV2.2 with a 10-fold IC50 separation between first (27 μM) and last (2.7 μM) pulses in a train. In a fluorescence-based calcium influx assay, TROX-1 inhibited CaV2.2 channels with an IC50 of 9.5 μM under hyperpolarized conditions and 0.69 μM under depolarized conditions. Finally, TROX-1 potency was examined across the CaV2 subfamily. Depolarized IC50 values were 0.29, 0.19, and 0.28 μM by manual electrophysiology using matched conditions and 1.8, 0.69, and 1.1 μM by calcium influx for CaV2.1, CaV2.2, and CaV2.3, respectively. Together, these in vitro data support the idea that a state-dependent, non–subtype-selective CaV2 channel inhibitor can achieve an improved therapeutic window over the relatively state-independent CaV2.2-selective inhibitor ziconotide in preclinical models of chronic pain.
Effects of deferoxamine on intracerebral hemorrhage-induced brain injury in aged rats.

BACKGROUND AND PURPOSE Deferoxamine (DFX) reduces brain edema, neuronal death, and neurological deficits after intracerebral hemorrhage (ICH) in young rats. In the present study, we investigated whether DFX is effective on brain injury after ICH in aged rats and examined dose dependency. METHODS Male Fischer 344 rats (18 months old) had an intracaudate injection of 100 microL autologous whole blood and were treated with different doses of DFX (10, 50, and 100 mg/kg) or vehicle 2 and 6 hours post-ICH and then every 12 hours up to 7 days. Rats were euthanized at Day 3 for brain edema determination and Day 56 for brain atrophy measurement. Behavioral tests were performed during the experiments. RESULTS All 3 doses of DFX attenuated perihematomal brain edema at 3 days (eg, at dose 50 mg/kg, 80.4+/-0.5 versus 81.6+/-0.9% in the vehicle-treated group, P<0.01). Fifty and 100 mg/kg DFX also reduced ICH-induced ventricle enlargement, caudate atrophy, and ICH-induced neurological deficits in aged rats. However, although 10 mg/kg DFX reduced ventricle enlargement and forelimb-placing deficits, it did not reduce caudate atrophy and corner turn deficits. CONCLUSIONS These results indicate that DFX can reduce ICH-induced brain injury in aged as well as young rats and that a dose >10 mg/kg is the optimal dose of DFX in this model.
An improvement of Bandler-Kohout fuzzy information retrieval model using reduced set

BK-FIRM (Bandler-Kohout fuzzy information retrieval model) suggested by Kohout et al. (1984) has been expanded from Boolean information retrieval model. It uses the concept of fuzzy relation which represents relative containments between documents and terms, and it is able to retrieve documents in the way based not on morphology but on semantics, dissimilar to traditional information retrieval theories. It also has merits such that it builds thesaurus automatically and it provides the system with fuzzy ranked documents. BK-FIRM, however, is not able to accept so many domains because its operations have very high time complexity. A-FIRM (advanced Bandler-Kohout fuzzy information retrieval model) improves time complexity of BK-FIRM by using reduced set which is the subset of the term set. In this paper, we suggest A-FIRM which improves time complexity of BK-FIRM's operations.
Histogram-Based Global Load Balancing in Structured Peer-to-Peer Systems

Over the past few years, peer-to-peer (P2P) systems have rapidly grown in popularity and have become a dominant means for sharing resources. In these systems, load balancing is a key challenge because nodes are often heterogeneous. While several load-balancing schemes have been proposed in the literature, these solutions are typically ad hoc, heuristic based, and localized. In this paper, we present a general framework, HiGLOB, for global load balancing in structured P2P systems. Each node in HiGLOB has two key components: 1) a histogram manager maintains a histogram that reflects a global view of the distribution of the load in the system, and 2) a load-balancing manager that redistributes the load whenever the node becomes overloaded or underloaded. We exploit the routing metadata to partition the P2P network into nonoverlapping regions corresponding to the histogram buckets. We propose mechanisms to keep the cost of constructing and maintaining the histograms low. We further show that our scheme can control and bound the amount of load imbalance across the system. Finally, we demonstrate the effectiveness of HiGLOB by instantiating it over three existing structured P2P systems: Skip Graph, BATON, and Chord. Our experimental results indicate that our approach works well in practice.
Heart Rate and Respiratory Rate Influence on Heart Rate Variability Repeatability: Effects of the Correction for the Prevailing Heart Rate

Background: Since heart rate variability (HRV) is associated with average heart rate (HR) and respiratory rate (RespRate), alterations in these parameters may impose changes in HRV. Hence the repeatability of HRV measurements may be affected by differences in HR and RespRate. The study aimed to evaluate HRV repeatability and its association with changes in HR and RespRate. Methods: Forty healthy volunteers underwent two ECG examinations 7 days apart. Standard HRV indices were calculated from 5-min ECG recordings. The ECG-derived respiration signal was estimated to assess RespRate. To investigate HR impact on HRV, HRV parameters were corrected for prevailing HR. Results: Differences in HRV parameters between the measurements were associated with the changes in HR and RespRate. However, in multiple regression analysis only HR alteration proved to be independent determinant of the HRV differences—every change in HR by 1 bpm changed HRV values by 16.5% on average. After overall removal of HR impact on HRV, coefficients of variation of the HRV parameters significantly dropped on average by 26.8% (p < 0.001), i.e., by the same extent HRV reproducibility improved. Additionally, the HRV correction for HR decreased association between RespRate and HRV. Conclusions: In stable conditions, HR but not RespRate is the most powerful factor determining HRV reproducibility and even a minimal change of HR may considerably alter HRV. However, the removal of HR impact may significantly improve HRV repeatability. The association between HRV and RespRate seems to be, at least in part, HR dependent.
Decision-related pupil dilation reflects upcoming choice and individual bias

Significance A number of studies reported that the pupil dilates (under constant illumination) during decision-making. Pupil dilation is also associated with the brain-wide release of modulatory neurotransmitters. It has remained unknown which specific elements of decision processes drive pupil dilation. Using a visual detection task, we here show that pupil dilation is primarily driven during, and not at the end of, a protracted decision. Further, pupil dilation differentiates between “yes” and “no” choices for conservative subjects deciding yes against their bias. Thus, pupil dilation reveals the content of the evolving decision and the decision maker’s attitude. These findings have important implications for interpreting decision-related brain activity. They also point to a possible role of neuromodulation in interacting with decision biases. A number of studies have shown that pupil size increases transiently during effortful decisions. These decision-related changes in pupil size are mediated by central neuromodulatory systems, which also influence the internal state of brain regions engaged in decision making. It has been proposed that pupil-linked neuromodulatory systems are activated by the termination of decision processes, and, consequently, that these systems primarily affect the postdecisional brain state. Here, we present pupil results that run contrary to this proposal, suggesting an important intradecisional role. We measured pupil size while subjects formed protracted decisions about the presence or absence (“yes” vs. “no”) of a visual contrast signal embedded in dynamic noise. Linear systems analysis revealed that the pupil was significantly driven by a sustained input throughout the course of the decision formation. This sustained component was larger than the transient component during the final choice (indicated by button press). The overall amplitude of pupil dilation during decision formation was bigger before yes than no choices, irrespective of the physical presence of the target signal. Remarkably, the magnitude of this pupil choice effect (yes > no) reflected the individual criterion: it was strongest in conservative subjects choosing yes against their bias. We conclude that the central neuromodulatory systems controlling pupil size are continuously engaged during decision formation in a way that reveals how the upcoming choice relates to the decision maker’s attitude. Changes in brain state seem to interact with biased decision making in the face of uncertainty.
Anomaly Detection of Solar Power Generation Systems Based on the Normalization of the Amount of Generated Electricity

Solar power generation has attracted significant attention recently as a safe and environmentally friendly renewable energy source. However, generally speaking, since the service lives of solar power systems are relatively long, and since it is difficult to detect anomalies in individual solar panels, such plants tend to operate without much consideration for individual panel anomalies. In order to more comprehensively monitor solar power generation systems, the National Institute of Advanced Industrial Science and Technology (AIST) of Japan has developed a direct current (DC) power line communication system that enables monitoring of each panel in a system. Monitored data are then integrated and uploaded to the cloud. Using this monitored data, we found that the integrated power ratio trends of single panel power output are in accordance with a normal distribution. Therefore, herein, we propose an anomaly detection method that uses a normal distribution. We then describe an experiment using 24 solar panels into which pseudo-faults were induced and show that our proposal makes it possible to detect errors with high accuracy.