Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability of Tungsten Crucible against Uranium, Rare Earth, Cadmium, and Chlorides for Cathode Process in Pyroprocessing

The stability of W against U, rare-earth (RE) elements, Cd, and various chlorides was evaluated by melting and distillation testing. Three runs were performed with a W crucible to examine its reactivity: (i) RE melting by induction heating, (ii) salt distillation test of U-dendrite and various chlorides, and (iii) Cd distillation test from U–Cd alloy. The W crucible remained stable after the RE melting test using induction melting, exhibiting its applicability for induction heating systems. The salt distillation test with the W crucible at 1050°C exhibited the stability of W against U and various chlorides, showing no interaction. The Cd distillation test with the W crucible at 500°C showed that the crucible was very stable against Cd, maintaining a shiny surface. These results reveal that the W crucible is stable under operation conditions for both salt and Cd distillation, suggesting the high potential utility of W as a crucible material for application in cathode processes in pyroprocessing.
Nanotechnology in food systems: Application and safety

Nanotechnology is a multidisciplinary technological and scientific field undergoing a rapid development. In this paper, current applications of nanotechnology in food systems include pesticide delivery systems through bioactive nanencapsulations, biosensors to detect and quantify pathogens, organic compounds, other chemicals and food composition alteration, high–performance sensors and edible thin films to preserve fruit and vegetable. The paper conclude that it is necessary to do a thorough risk assessment of nano foods before they are released to the market.
The LeaP Corpus

This article describes the compilation, annotation and some exemplary searches of the LeaP corpus, a multilingual 12-hour corpus of spoken learner German and learner English that contains extensive time-aligned phonological and phonetic transcriptions. After outlining the collection and type of primary data that forms the corpus and explaining the manual and automatic annotation procedure, the search options of this resource are described as well as its availability for use by other researchers. The exemplary corpus search is concerned with L2 fluency. Findings of some quantitative and qualitative corpus searches are presented, in particular, the phonetic correlates of fluency and the factors that influence the fluency of foreign language learners.
Real-Time Semantic Segmentation-Based Stereo Reconstruction

In this paper, we propose a novel semantic segmentation-based stereo reconstruction method that can keep up with the accuracy of the state-of-the art approaches while running in real time. The solution follows the classic stereo pipeline, each step in the stereo workflow being enhanced by additional information from semantic segmentation. Therefore, we introduce several improvements to computation, aggregation, and optimization by adapting existing techniques to integrate additional surface information given by each semantic class. For the cost computation and optimization steps, we propose new genetic algorithms that can incrementally adjust the parameters for better solutions. Furthermore, we propose a new post-processing edge-aware filtering technique relying on an improved convolutional neural network (CNN) architecture for disparity refinement. We obtain the competitive results at 30 frames/s, including segmentation.
CNN‐based CSI acquisition for FDD massive MIMO with noisy feedback

In frequency-division-duplex (FDD) massive multiple-input multiple-output (MIMO) systems, noisy feedback is a constant challenge for the base station (BS) to acquire accurate downlink channel state information (CSI). In this Letter, the authors propose a convolutional neural network (CNN)-based approach to overcome this problem, which they refer to it as an anti-noise CSI acquisition network (ANCAN). Results demonstrate that ANCAN can reconstruct CSI more accurately than other emerging CSI acquisition methods in the presence of noisy feedback links.
Government Public Service Advertising Design

Iklan layanan masyarakat merupakan salah satu strategi yang digunakan pemerintah untuk menyosialisasikan program pembangunan. Di tingkat nasional, pemerintah lebih memilih televisi sebagai media beriklan. Adapun di daerah, pemerintah biasanya cenderung memilih iklan yang berbiaya lebih murah. Di Banyumas, iklan layanan masyarakat banyak menggunakan media luar ruang seperti baliho, spanduk, ataupun poster. Kelebihan media luar ruang yang mengutamakan desain dalam menarik perhatian menjadi tantangan bagi pengiklan. Di sisi lain, pesan-pesan pembangunan juga membutuhkan ruang dalam iklan layanan masyarakat. Menarik untuk dikaji bagaimana eksekusi desain iklan luar ruang layanan masyarakat tersebut dalam usaha menggabungkan antara desain dengan pesan yang hendak disampaikan. Penelitian ini berusaha untuk mengkaji aspek desain dengan menggunakan metode interpretasi komposisi dan verbalisasi iklan luar ruang dengan metode analisis wacana. Hasil penelitian menyimpulkan bahwa desain iklan layanan masyarakat pemerintah masih perlu diperbaiki sesuai acuan dalam kaidah-kaidah desain komunikasi visual.
Multi-scale optical flow estimation of the video based on gradient optimization

A new algorithm based on gradient optimization is proposed for optical flow estimation of video images with different motion ranges.The original video images are transformed by using Loggabor filtering on phases and measures,and then the spatio-temporal gradient is calculated by using the obtained feature images.The optical flow is calculated with the spatio-temporal gradient.The video images are layered and processed with coarse-to-fine image pyramid method.The theoretical analysis and experimental results show that the algorithm is suitable for the video optical flow motion estimation of the significant range.It can not only obtain the video images following the human visual resolution characteristics,but also optimize the spatio-temporal gradient,while the optical flow calculation is more accurate.Besides,the time complexity of this algorithm is equivalent to that of the traditional optical flow method,and the accuracy of the algorithm is superior to the methods suggested by Horn-Schunck,Duan,et al.
NASA Selects 12 New Lunar Science, Technology Investigations

NASA has selected 12 new science and technology payloads that will help us study the Moon and explore more of its surface as part of the agency’s Artemis lunar program. These investigations and demonstrations will help the agency send astronauts to the Moon by 2024 as a way to prepare to send humans to Mars for the first time.
Pedestrian detection based on redundant wavelet transform

Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.
From Traditional to Automated Mobility on Demand: A Comprehensive Framework for Modeling On-Demand Services in SimMobility

Mobility on demand (MoD) systems have recently emerged as a promising paradigm for sustainable personal urban mobility in cities. In the context of multi-agent simulation technology, the state-of-the-art lacks a platform that captures the dynamics between decentralized driver decision-making and the centralized coordinated decision-making. This work aims to fill this gap by introducing a comprehensive framework that models various facets of MoD, namely heterogeneous MoD driver decision-making and coordinated fleet management within SimMobility, an agent- and activity-based demand model integrated with a dynamic multi-modal network assignment model. To facilitate such a study, we propose an event-based modeling framework. Behavioral models were estimated to characterize the decision-making of drivers using a GPS dataset from a major MoD fleet operator in Singapore. The proposed framework was designed to accommodate behaviors of multiple on-demand services such as traditional MoD, Lyft-like services, and automated MoD (AMoD) services which interact with traffic simulators and a multi-modal transportation network. We demonstrate the benefits of the proposed framework through a large-scale case study in Singapore comparing the fully decentralized traditional MoD with the future AMoD services in a realistic simulation setting. We found that AMoD results in a more efficient service even with increased demand. Parking strategies and fleet sizes will also have an effect on user satisfaction and network performance.
Hermitian Distance-Based Method to Discriminate Physical Targets and Active False Targets in A Distributed Multiple-Radar Architecture

In a distributed multiple-radar architecture, the spatial scattering properties of targets can be utilized to counter active deception jamming effectively. When the cooperative detection is performed, the difference in spatial scattering property makes the Hermitian distance of a false target considerably different from that of a physical target. The Hermitian distance of a false target increases with the raise of jamming-to-noise ratio, whereas the one of a physical target obeys an identical Beta distribution for all signal-to-noise ratios, which leads to the former much greater than the latter, especially in high jamming-to-noise ratio. Making full use of the difference, a novel method is proposed based on the Neyman–Pearson lemma to discriminate physical and active false targets in this paper. The proposed method overcomes the dependence of the available method on the prior information about the jamming environment. What’s more, the proposed method can keep a constant misjudgement probability for physical targets and discriminate targets effectively in one pulse repetition interval. The theoretical analysis and simulation verify the feasibility and validity of the proposed discrimination method.
Pulse width modulation technique with harmonic injection in the modulating wave and discontinuous frequency modulation for the carrier wave to reduce vibrations in asynchronous machines

A new carrier-based pulse-width modulation (PWM) technique to control power inverters is presented in this study. To generate the output waveform, this technique compares a harmonic-injection modulating wave and a frequency-modulated triangular carrier wave. The instantaneous frequency for the carrier wave is adjusted according to a periodic function synchronised with the fundamental term of the modulating wave. The main motivation for using this technique compared to a classic PWM sinusoidal technique revolves around the reduction of total harmonic distortion, the reduction of the distortion factor and the shift of temporal harmonics to higher frequencies for any modulation frequency order. Experimental results show that it is possible to optimise the time harmonics generated to minimise vibrations produced by an induction motor when it is fed with a DC/AC converter controlled by the proposed control strategy. This is made possible by using a control parameter that modifies the instantaneous frequency of the carrier wave without modifying the number of pulses per period of the modulating wave, i.e. the mean value of the carrier wave frequency. The proposed technique is applied to an open loop-controlled inverter that operates an induction motor, helping to reduce the vibration levels produced.
A vertex‐fed hexa‐band frequency reconfigurable antenna for wireless applications

Present article embodies the design and analysis of an octagonal shaped split ring resonator based multiband antenna fed at vertex for wireless applications with frequency‐band reconfigurable characteristics. The proposed antenna is printed on FR4 substrate with electrical dimension of 0.4884 λ × 0.4329 λ × 0.0178 λ (44 × 39 × 1.6 mm3), at lower frequency of 3.33 GHz. The antenna consists of SRR based vertex fed octagonal ring as the radiation element and switchable reclined L‐shaped slotted ground plane. Antenna achieves six bands for wireless standards viz: upper WLAN (5.0/5.8 GHz), lower WiMAX (3.3 GHz), super extended C‐band (6.6 GHz), middle X band (9.9 GHz—for space communication), and lower KU band (15.9 GHz—for satellite communication systems operating band). Stable radiation patterns are observed for the operating bands with low cross polarization. The proposed design achieves hexa band characteristics during switching ON state of PIN diode located at reclined L‐shaped slot in the ground plane. Experimental characteristic of antenna shows close agreement with those obtained by simulation of the proposed antenna.
Expansion Planning of Active Distribution Networks With Multiple Distributed Energy Resources and EV Sharing System

The ever-increasing energy demand and high penetration rate of distributed renewable generation brings new challenges to the planning of power distribution networks. This paper proposes an expansion planning model for distribution networks by considering multiple types of energy resources in distribution side, including shared electric vehicle (SEV) charging stations, solar-based distributed generation sources, and battery energy storage systems. The operational characteristics of SEV are considered and modeled. The proposed planning model aims to minimize the weighted sum of network investment cost, energy losses, and queue waiting time of SEVs. A stochastic scenario generation method is introduced to address the stochastic feature of SEVs’ driving behaviors. Numerical studies are tested on the systems with 54-node distribution network and 25-node traffic network.
Dyspnoea and its measurement

Key points Dyspnoea is the sensation of breathing discomfort that can be described with different terms according to different pathophysiological mechanisms that vary in intensity. The mechanisms of dyspnoea are complex. In COPD, whilst the intensity and quality of dyspnoea during activity correlates with the magnitude of lung hyperinflation and inspiratory events, it correlates poorly with FEV1. Valid, reliable and responsive instruments are available to measure the severity of dyspnoea in patients with respiratory disease. CME article: educational aims To introduce dyspnoea and explain its mechanisms. To present dyspnoea descriptors, which may help in the understanding of the language of dyspnoea, and to relate these to specific diseases. To describe some of the methods available for the measurement of dyspnoea. Summary Dyspnoea, a term used to characterise a subjective experience of breathing discomfort, is perhaps the most important symptom in cardiorespiratory disease. Receptors in the airways, lung parenchyma, respiratory muscles and chemoreceptors provide sensory feedback via vagal, phrenic and intercostal nerves to the spinal cord, medulla and higher centres. Knowledge of dyspnoea descriptors can help in understanding the language of dyspnoea and these are presented here. It is important to appreciate that differences in language, race, culture, sex and previous experience can all change the perception of and the manner in which the feeling of being dyspnoeic is expressed to others. Therefore, standard tools to measure dyspnoea are available. In addition, there are tools that can help to relate the severity of symptoms with observed levels of cardiac and pulmonary responses while performing supervised tasks. A range of methods are described here. Inventories that involve aspects of dyspnoea related to quality of life are not yet a routine part of the history and physical examination, although they have proved useful in the clinic. Measurement instruments may involve a cost for use, may be self-administered or require an interviewer, and can vary in the time required for completion and scoring.
Numerical Simulation of Crystalline Silicon Heterojunction Solar Cells with Different p-Type a-SiOx Window Layer

In this study, p-type amorphous silicon oxide (a-SiOx) films are deposited using a radio-frequency inductively-coupled plasma chemical vapor deposition system. Effects of the CO2 gas flow rate on film properties and crystalline silicon heterojunction (HJ) solar cell performance are investigated. The experimental results show that the band gap of the a-SiOx film can reach 2.1 eV at CO2 flow rate of 10 standard cubic centimeters per minute (sccm), but the conductivity of the film deteriorates. In the device simulation, the transparent conducting oxide and contact resistance are not taken into account. The electrodes are assumed to be perfectly conductive and transparent. The simulation result shows that there is a tradeoff between the increase in the band gap and the reduction in conductivity at increasing CO2 flow rate, and the balance occurs at the flow rate of six sccm, corresponding to a band gap of 1.95 eV, an oxygen content of 34%, and a conductivity of 3.3 S/cm. The best simulated conversion efficiency is 25.58%, with an open-circuit voltage of 741 mV, a short-circuit current density of 42.3 mA/cm2, and a fill factor of 0.816%.
Clustering of incomplete, high dimensional and dependent biological data with SpaCEM3

The SpaCEM3 software makes the most of variational estimates in Markov Random Field (MRF) models to cluster (i) high-dimensional (ii) dependent and (iii) incomplete data. This methodology has been applied to draw meaningful modules of genes from high-throughput data. To download the latest version, visit http://spacem3.gforge. inria.fr/
Secure SMS Method Based on Social Networks

Nowadays, Short Message Service (SMS) communications play important role in daily lives. Authentication, reports and personal communications are the common instances of SMS applications. The message signals are being transmitted in the air without any security measures. Hence, the message content could easily be intercepted without requiring complicated infrastructure. To protect confidentiality and integrity of the messages, various techniques are devised. Some early techniques rely on extra or upgraded hardware equipments and impose high implementation cost. However, the modern techniques mostly are applicable on smart phones and work in application layer. In this research, the proposed technique utilizes the profile information and users’ communications in social networks to generate two dynamic keys for SMS encryption and decryption. Cost of secure session establishment has dramatically reduced. The analysis results also show high level of user satisfaction and long secure lifetime for exchanged messages.
Co-creation for empathy and mutual learning: a framework for design in health and social care

ABSTRACT Co-creation is seen as imperative in healthcare however existing frameworks are in need for adapting to specific settings from a person-centred care perspective such as shared decision-making, characterised by asymmetrical power relations and restricted time resources. This article takes a workshop in shared decision-making with doctors, nurses, patients and relatives as a point of departure for process reflection. The aim of the workshop was to develop implementation strategies for a decision tool for future cancer care. By analysing its concept and methods, we propose a general framework for design in health and social care, based on meeting fellow stakeholders, switching over roles, voicing and developing ideas and finally evaluating proposals (MOVE). By evidence of our research, we propose that empathy can be created and strengthened through co-creation in health and social care.
PMU Signals Responses-Based RAS for Instability Mitigation Through On-The Fly Identification and Shedding of the Run-Away Generators

This paper presents a new method of instability detection and subsequent stabilization of the power system network using a proposed multi-shot remedial action scheme (RAS) that can extemporaneously detect critical generators based on the dynamic states of generator computed from the terminal phasor measurement units. The instability detector is a moving window classifier that predicts impending instability using rate of change of individual generator transient energy indices evaluated from the d–q axis voltage as well as conventional severity indices based on generator angle and frequency. A comparative performance analysis of a spectral feature based ensemble decision tree classifier with a multivariate long short-term memory network is also presented. The proposed RAS identifies critical generators through individual machine transient energy formulation and recursive coherency matrix, evaluated solely from system-wide generator dynamic states, and maintains stability by tripping adaptively the run-away generators. Performance evaluation of the proposed scheme has been made on IEEE 39-bus network and it has been demonstrated that the proposed RAS is robust with regards to instability prediction and it can effectively identify critical generators and stabilize the network by tripping the same.
Sign classification in sign language Corpora with deep neural networks

Automatic and unconstrained sign language recognition (SLR) in image sequences remains a challenging problem. The variety of signers, backgrounds, sign executions and signer positions makes the development of SLR systems very challenging. Current methods try to alleviate this complexity by extracting engineered features to detect hand shapes, hand trajectories and facial expressions as an intermediate step for SLR. Our goal is to approach SLR based on feature learning rather than feature engineering. We tackle SLR using the recent advances in the domain of deep learning with deep neural networks. The problem is approached by classifying isolated signs from the Corpus VGT (Flemish Sign Language Corpus) and the Corpus NGT (Dutch Sign Language Corpus). Furthermore, we investigate cross-domain feature learning to boost the performance to cope with the fewer Corpus VGT annotations.