Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental Study on the Decomposition Products of CF3I/N2Gas Mixtures

Sulfur hexafluoride (SF6) has been limited to use because its high global warming potential (GWP). Iodotrifluoromethane (CF3I) is a potential alternative to SF6, which has advantages on environmental performance. But due to its instability, it may decompose during discharge process. The decomposition products may affect the insulating characteristics of Cf<inf>3</inf>I/N<inf>2</inf>. In this paper the decomposition products are detected include C<inf>2</inf>F<inf>6</inf>, C<inf>2</inf>F<inf>4</inf>, C<inf>3</inf>F<inf>8</inf> and their quantities after 50, 100, 150 and 200 times of discharge in non-uniform electric field and analyzed the breakdown voltages after different times discharge. The decompositions of Cf<inf>3</inf>I/N<inf>2</inf> can change the components of insulating gas and have the solid decomposition iodine. But the amount of decomposition will not be very large and it will not have a significant impact on the insulation properties after limited and transient discharges.
Intuitionistic Fuzzy Analytic Network Process

Since the analytic network process (ANP) is much more flexible than the analytic hierarchy process in handling the multiple criteria decision making (MCDM) problems in which the criteria or subcriteria are interdependent, it has attracted many scholars’ attention and has been applied into many different areas. Given the powerfulness of intuitionistic fuzzy set in representing positive, negative, and indeterminate information, this paper investigates the ANP framework for the MCDM problems in which all the pairwise comparison judgment information over the objects are represented by intuitionistic fuzzy numbers. We first justify the way to decompose the MCDM problem into a holarchy and network structure, based on which, the intuitionistic fuzzy preference relations (IFPRs) can be constructed through pairwise comparisons over the goals, criteria, clusters as well as the elements. Considering that not all the IFPRs are consistent, we then propose a new method to derive the priorities from the IFPRs no matter the IFPRs are consistent or not. After that, we address the way to construct the supermatrix for those interdependent elements. The complete algorithm of intuitionistic fuzzy ANP (IFANP) is given and illustrated by a flow chart. To show the applicability and efficiency of the IFANP, we implement the method to a case study concerning the brand management of the six golden flowers of Sichuan liquor. Some comparative analyses are given to clarify the advantages and invalidation of the IFANP.
System Design and Measurements of a 115-kV/3.5-ms Solid-State Long-Pulse Modulator for the European Spallation Source

In this paper, the results of a 2.88-MW solid-state long-pulse modulator, which has been designed for the new linear collider at the european spallation source in Lund, are summarized. The presented modulator generates an output voltage pulse of 115 kV with a pulselength of 3.5 ms. The main components of the modular system, which include a series–parallel resonance converter, a high-voltage high-frequency transformer, and an output rectifier, are discussed. The modulator design is verified by measurements performed with a full-scale prototype, which is operated under nominal load conditions. A detailed output voltage ripple evaluation is given, and in addition, the system design has been proven by a 7- and 2/3-h heat run test. All specifications are well within the given limits, and the maximum occurring temperatures in the transformer stay below 110 °C even under worst case assumptions. The system achieves a pulse efficiency (determined by the pulse shape) of 96.78%, an overall electrical system efficiency of 91.9%, and a combined pulse system efficiency of 89%.
Generating EEG Graphs Based on PLA for Brain Wave Pattern Recognition

Brain Computer Interface (BCI) has been an emerging topic in recent years. Specially, Artificial Intelligence (AI) is becoming a hot research area in recent years. However, many BCI techniques utilize invasive interfaces to brains (animal or human), which could cause potential risks for experimental subjects. EEG (Electroencephalography) technique has been used extensively as a non-invasive BCI solution for brain activity study. Many psychological work has suggested that human brains can generate some recognizable EEG signals associated with some specific activities. This paper suggests a novel EEG recognition method, i.e. Segmented EEG Graph using PLA (SEGPA), that incorporates improved Piecewise Linear Approximation (PLA) algorithm and EEG-based weighted network for EEG pattern recognition, which can be used for machinery control. The improved PLA algorithm and EEG-based weighted network technique incorporates the data sampling and segmentation method. This research proposes a potentially efficient method for recognizing human's brain activities that can be used for machinery or robot control.
Double Auction-Based Resource Allocation for Mobile Edge Computing in Industrial Internet of Things

Mobile edge computing (MEC) yields significant paradigm shift in industrial Internet of things (IIoT), by bringing resource-rich data center near to the lightweight IIoT mobile devices (MDs). In MEC, resource allocation and network economics need to be jointly addressed to maximize system efficiency and incentivize price-driven agents, whereas this joint problem is under the locality constraints, i.e., an edge server can only serve multiple IIoT MDs in the vicinity constrained by its limited computing resource. In this paper, we investigate the joint problem of network economics and resource allocation in MEC where IIoT MDs request offloading with claimed bids and edge servers provide their limited computing service with ask prices. Particularly, we propose two double auction schemes with dynamic pricing in MEC, namely a breakeven-based double auction (BDA) and a more efficient dynamic pricing based double auction (DPDA), to determine the matched pairs between IIoT MDs and edge servers, as well as the pricing mechanisms for high system efficiency, under the locality constraints. Through theoretical analysis, both algorithms are proved to be budget-balanced, individual profit, system efficient, and truthful. Extensive simulations have been conducted to evaluate the performance of the proposed algorithms and the simulation results indicate that the proposed DPDA and BDA can significantly improve the system efficiency of MEC in IIoT.
A Joint Multi-Criteria Utility-Based Network Selection Approach for Vehicle-to-Infrastructure Networking

The emerging technologies for connected vehicles have become hot topics. In addition, connected vehicle applications are generally found in heterogeneous wireless networks. In such a context, user terminals face the challenge of access network selection. The method of selecting the appropriate access network is quite important for connected vehicle applications. This paper jointly considers multiple decision factors to facilitate vehicle-to-infrastructure networking, where the energy efficiency of the networks is adopted as an important factor in the network selection process. To effectively characterize users’ preference and network performance, we exploit energy efficiency, signal intensity, network cost, delay, and bandwidth to establish utility functions. Then, these utility functions and multi-criteria utility theory are used to construct an energy-efficient network selection approach. We propose design strategies to establish a joint multi-criteria utility function for network selection. Then, we model network selection in connected vehicle applications as a multi-constraint optimization problem. Finally, a multi-criteria access selection algorithm is presented to solve the built model. Simulation results show that the proposed access network selection approach is feasible and effective.
Multiple Scattering Modeling for Dual-Polarized MIMO Land Mobile Satellite Channels

This communication investigates the validity of application of a multiple-scattering model to a dual-polarized multiple-input-multiple-output land mobile satellite (LMS) channel based on a measurement campaign. Two LMS link scenarios in an urban pedestrian environment are examined. In the first one, the transmitter was located at the top of a tall building and in the second one, on an airship. The third-order scattering model is utilized to statistically characterize the measured channels, and the results reveal that the model provides an excellent fit to the LMS composite fading amplitude in the line-of-sight (LOS) and non-LOS scenarios. For this generic radio channel, asymptotic expressions for the theoretical probability density function and the cumulative distribution function are derived. The comparison of the third-order scattering model with existing LMS ones showed that it provides better overall accuracy together with a physical interpretation of the propagation mechanisms involved.
Genetic Algorithm Based Dynamics Modeling and Control of a Parallel Rehabilitation Robot

This paper is devoted to modeling and controlling a new upper-limb rehabilitation robot which has a parallel structure. Genetic algorithm (GA) is successfully applied in parameter identification based on dynamic analysis of the parallel robot. For accurate identification, joint velocities and accelerations are computed by the Kalman filter. By taking the non-linear characteristics of frictions into account, the unknown friction parameters differ depending on directions of motion. Compared with the traditional least square estimation (LSE) based method, the proposed identification method improves performance. Further, a model-based PD computed-torque controller is designed, and the feasibility of the estimated dynamic model and controller is validated by passive training task along a circular trajectory.
ACCURATE METHOD OF TEMPORAL-SHIFT ESTIMATION FOR 3D VIDEO

Video synchronization is a fundamental computer-vision task that is necessary for a wide range of applications. A 3D video involves two streams, which show the scene from different angles concurrently, but many cases exhibit desynchronization between them. This paper investigates the problem of synchronizing the left and right stereoscopic views. We assume the temporal shift (time difference) and geometric distortion between the two streams are constant throughout each scene. We propose a temporal-shift estimation method with subframe accuracy based on a block-matching algorithm.
Occupational radiation exposure to nursing staff during cardiovascular fluoroscopic procedures: A review of the literature

Abstract Fluoroscopy is a method used to provide real time x‐ray imaging of the body during medical procedures to assist with medical diagnosis and treatment. Recent technological advances have seen an increase in the number of fluoroscopic examinations being performed. Nurses are an integral part of the team conducting fluoroscopic investigations and are often located close to the patient resulting in an occupational exposure to radiation. The purpose of this review was to examine recent literature which investigates occupational exposure received by nursing staff during cardiovascular fluoroscopic procedures. Articles published between 2011 and 2017 have been searched and comprehensively reviewed on the referenced medical search engines. Twenty‐four relevant studies were identified among which seventeen investigated nursing dose comparative to operator dose. Seven researched the effectiveness of interventions in reducing occupational exposure to nursing staff. While doctors remain at the highest risk of exposure during procedures, evidence suggests that nursing staff may be at risk of exceeding recommended dose limits in some circumstances. There is also evidence of inconsistent use of personal protection such as lead glasses and skull caps by nursing staff to minimize radiation exposure. Conclusions: The review has highlighted a lack of published literature focussing on dose to nurses. There is a need for future research in this area to inform nursing staff of factors which may contribute to high occupational doses and of methods for minimizing the risk of exposure, particularly regarding the importance of utilizing radiation protective equipment.
A Group-Oriented DTLS Handshake for Secure IoT Applications

The datagram transport layer security (DTLS) is a de facto standard for the end-to-end security of the constrained application protocol (CoAP) that defines the following three security modes: preshared key (PSK), raw public key, and certificate. The pros and cons of each security mode are obvious. Even though the PSK mode is the most preferable in terms of the performance of the DTLS handshake, the in-advance distribution of a unique symmetric key for each pair of endpoints is difficult as the number of pairs increases. Alternatively, the certificate mode provides a convenient key-management functionality but its performance is very poor. The focus of most of the previous works is the reduction of the computational load for a single DTLS handshake that is induced by the certificate mode. In this paper, a group-oriented end-to-end security is considered, together with the introduction of a new security mode. Namely, a security association is established between a CoAP client and a group of CoAP servers (sensor devices); however, a fine-grained access control can be enforced so that each CoAP client can access a limited number of CoAP servers in the group. Furthermore, when each CoAP client performs several DTLS handshakes with the CoAP servers in the group, the first DTLS handshake involves a single public-key operation. A public-key operation, however, is not required for the subsequent DTLS handshakes, so the overall computational burden can be reduced. Also, a testbed was established along with the implementation of the proposed security mechanism for the conduction of a performance comparison with the other security mechanisms. Note to Practitioners—Datagram transport layer security (DTLS) is a standards-based security protocol to secure communications in an IoT environment, including home, factory, or building automation systems. However, to develop a practical security solution based on DTLS, several assumptions inherent to DTLS need to address the practical requirements of various IoT scenarios. Furthermore, some barriers associated with implementing DTLS in an IoT environment should be overcome. This paper presents an interface to extend the basic security functionalities provided by DTLS. Through the interface, a general security platform can be constructed and combined with DTLS. Hence, fine-grained access control and group security can be merged with DTLS, together with standards compliance.
A standardised database of Chinese emotional film clips

ABSTRACT Film clips are widely used in emotion research due to their relatively high ecological validity. Although researchers have established various film clip sets for different cultures, the few that exist related to Chinese culture do not adequately address positive emotions. The main purposes of the present study were to establish a standardised database of Chinese emotional film clips that could elicit more categories of reported positive emotions compared to the existing databases and to expand the available film clips that can be used as neutral materials. Two experiments were conducted to construct the database. In experiment 1, 111 film clips were selected from more than one thousand Chinese movies for preliminary screening. After 315 participants viewed and evaluated these film clips, 39 excerpts were selected for further validation. In experiment 2, 147 participants watched and rated these 39 film clips, as well as another 8 excerpts chosen from the existing databases, to compare their validity. Eventually, 22 film excerpts that successfully evoked three positive emotions (joy, amusement, and tenderness), four negative emotions (moral disgust, anger, fear, and sadness), and neutrality formed the standardised database of Chinese emotional film clips.
Attacker-Centric View of a Detection Game against Advanced Persistent Threats

Advanced persistent threats (APTs) are a major threat to cyber-security, causing significant financial and privacy losses each year. In this paper, cumulative prospect theory (CPT) is applied to study the interactions between a cyber system and an APT attacker when each of them makes subjective decisions to choose their scan interval and attack interval, respectively. Both the probability distortion effect and the framing effect are applied to model the deviation of subjective decisions of end-users from the objective decisions governed by expected utility theory, under uncertain attack durations in a pure-strategy game and scan interval in a mixed-strategy game. The CPT-based APT detection game incorporates both the probability weighting distortion and the framing effect of the subjective attacker and security agent of the cyber system, rather than discrete decision weights, as in earlier prospect theoretic study of APT detection. The Nash equilibria of the APT detection game are derived, showing that a subjective attacker becomes risk-seeking if the frame of reference for evaluating the utility is large, and becomes risk-averse if the frame of reference for evaluating the utility is small. A policy hill-climbing (PHC) based detection scheme is proposed to increase the policy uncertainty to fool the attacker in the dynamic game, and a “hotbooting” technique that exploits experiences in similar scenarios to initialize the quality values is developed to accelerate the learning speed of PHC-based detection. A practical example of a mobile network is presented to evaluate the performance of the proposed detection strategy. Simulation results show that the proposed strategy can improve detection performance with a higher data protection level and utilities of the cloud in the presence of an attacker compared with a standard Q-learning strategy.
Event Structures Drive Semantic Structural Priming, Not Thematic Roles: Evidence From Idioms and Light Verbs

What are the semantic representations that underlie language production? We use structural priming to distinguish between two competing theories. Thematic roles define semantic structure in terms of atomic units that specify event participants and are ordered with respect to each other through a hierarchy of roles. Event structures instead instantiate semantic structure as embedded sub-predicates that impose an order on verbal arguments based on their relative positioning in these embeddings. Across two experiments, we found that priming for datives depended on the degree of overlap in event structures. Specifically, while all dative structures showed priming, due to common syntax, there was a boost for compositional datives priming other compositional datives. Here, the two syntactic forms have distinct event structures. In contrast, there was no boost in priming for dative light verbs, where the two forms map onto a single event representation. On the thematic roles hypothesis, we would have expected a similar degree of priming for the two cases. Thus, our results support event structural approaches to semantic representation and not thematic roles.
Diacritization of a Highly Cited Text: A Classical Arabic Book as a Case

We present a robust and accurate diacritization method of highly cited texts by automatically "borrowing" diacritization from similar contexts. This method of diacritization has been tested on diacritizing one book: "Riyad As-Salheen", for the purpose of morphological annotation of the Sunnah Arabic Corpus. The original source of Riyad is about 48.66% diacritized, and after borrowing diacritization, the percentage jumps to 76.41% with low diacritic error rate (0.004), compared to 61.73% (DER=0.214) using MADAMIRA toolkit, and 67.68% (DER=0.006) using Farasa toolkit. More importantly, this method has reduced the word ambiguity from 4.83 diacritized form/word to 1.91.
Executive Control Deficits Potentiate the Effect of Maladaptive Metacognitive Beliefs on Posttraumatic Stress Symptoms

The metacognitive model and recent preliminary research suggests that metacognitive beliefs (i.e., beliefs about thinking) may be particularly important for understanding the pathogenesis of posttraumatic stress (PTS). The metacognitive model also suggests that deficits in executive control (i.e., metacognitive control) may increase the impact of metacognitive beliefs on PTS symptoms. Trauma-exposed adult participants (N = 469), recruited through an online crowdsourcing website, completed a battery of measures assessing the constructs of interest. As predicted, deficits in executive control strengthened the positive association between metacognitive beliefs and PTS symptoms. This effect was found in relation to positive (e.g., “Worrying will keep me safe”), but not negative (e.g., “My thoughts are uncontrollable”), metacognitive beliefs. Supplemental analyses, indicated that the interaction between positive metacognitive beliefs and executive control significantly predicted all PTS cluster scores (i.e., Intrusion, Cognition, Arousal, Avoidance). Taken together, results support the proposal that executive control deficits potentiate the effect of metacognitive beliefs on PTS symptoms. Intervention strategies designed to strengthen executive control (e.g., the attention training technique) may be useful in treating individuals with PTS.
CREG1 promotes uncoupling protein 1 expression and brown adipogenesis in vitro

Brown adipocytes play a critical role for adaptive thermogenesis to regulate body temperature in cold or to circumvent diet-induced obesity. In this study, we investigated the role of cellular repressor of E1A-stimulated genes 1 (CREG1) on brown adipogenesis and uncoupling protein 1 (UCP1) expression by using in vitro culture models. In murine mesenchymal stem cell line C3H10T1/2, Creg1 mRNA expression significantly increased in a time-dependent manner along with Ucp1 mRNA induction in brown adipogenesis. Creg1 gene overexpression upregulated the expression of brown fat-related genes including Ucp1 but its suppression downregulated these gene expression in C3H10T1/2 cells. Unlike the brown adipogenesis, Creg1 mRNA expression decreased significantly after differentiation stimulation in white adipogenesis of 3T3-L1 cells. Either Creg1 gene overexpression or suppression hardly affected white adipogenesis. In addition, CREG1 protein stimulated brown adipogenesis and rescued the adipogenesis in the absence of thyroid hormone in C3H10T1/2 cells. In reporter assay, CREG1 induction stimulated Ucp1 promoter activity, which was enhanced by co-expression with thyroid hormone receptors. The effect of CREG1 on Ucp1 promoter activity was also stimulated by retinoic acid. These results strongly suggest that CREG1 plays an important role on the regulation of UCP1 expression and brown adipogenesis.