Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal preventive 'maintenance-first or -last' policies with generalized imperfect maintenance models

This paper presents modified preventive maintenance policies for an operating system that works at random processing times and is imperfectly maintained. The system may suffer from one of the two types of failures based on a time-dependent imperfect maintenance mechanism: type-Ⅰ (minor) failure, which can be rectified by minimal repair, and type-Ⅱ (catastrophic) failure, which can be removed by corrective maintenance. When the system needs to be maintained, two policies "preventive maintenance-first (PMF) and preventive maintenance-last (PML)" may be applied. In each maintenance interval, before any type-Ⅱ failure occurs, the system is maintained at a planned time \begin{document}$ T $\end{document} or at the completion of a working time, whichever occurs first and last, which are called PMF and PML, respectively. After any maintenance activity, the system improves but its failure characteristic is also altered. At the \begin{document}$ N $\end{document} -th maintenance, the system is replaced rather than maintained. For each policy, the optimal preventive maintenance schedule ( \begin{document}$ T $\end{document} , \begin{document}$ N $\end{document} ) \begin{document}$ ^{*} $\end{document} that minimizes the mean cost rate function is derived analytically and determined numerically in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.
Phenolic antioxidants based on calixarene: Synthesis, structural characterization, and antioxidative properties in natural rubber

C-methylcalix[4]resorcinarene (CMCR) was first synthesized by condensation reaction between resorcinol and acetaldehyde, and then used as functional monomer to prepare two CMCR derivatives including C-methylcalix[4]resorcinarene-1 (CMCR-1) and C-methylcalix[4]resorcinarene-2 (CMCR-2) with four ethoxymethyl chains and four hexylthiolmethyl chains, respectively. The structures of CMCR and its derivatives were confirmed by Fourier transform infrared (FT-IR) spectroscopy and high-resolution mass spectrometry (HRMS). Thermogravimetric analysis (TGA) revealed CMCR, CMCR-1, and CMCR-2 had superior thermal stability than commercial antioxidant 2,6-Di-tert-butyl-4-methylphenol (BHT). Oxidation induction time and accelerated thermal aging tests indicated that CMCR-2 exhibited excellent antioxidative property in natural rubber (NR), which was due to multiphenol groups, big steric hindrance, and synergistic effect between thiother and hindered phenol. Importantly, CMCR-2 also possessed outstanding extraction resistance. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45144.
Postfledging dispersal of red‐fronted parakeets (Cyanoramphus novaezelandiae) from a fenced mainland sanctuary

Translocations are an important tool for conserving species at risk of extinction from a range of threats. However, an understanding of the life history of many threatened species prior to translocation is often lacking despite being critical for translocation success. For example, dispersal away from the release site in the years following a translocation—particularly when a protected release site is surrounded by unmanaged habitat—can result in failure to establish a self‐sustaining population; successful translocation practice must therefore include an understanding of a species' dispersal patterns. We examined the postfledging dispersal of 22 juveniles reared from a population of red‐fronted parakeets (Cyanoramphus novaezelandiae), or kākāriki, translocated to a mainland sanctuary in Wellington, New Zealand, 6 years prior. The translocation was one of the first of this species to mainland New Zealand and presented several unknowns, in particular whether a population would establish in a sanctuary bordered both by contiguous forest as well as suburban areas. Juvenile kākāriki were radio‐tracked and their location recorded once a day, 5 days per week, for 6 months or until the transmitter battery was exhausted. Approximately one‐third of radio‐tracked juveniles that dispersed outside the sanctuary were killed by predators. Kākāriki postfledging dispersal beyond the sanctuary was male‐biased, possibly driven by inbreeding avoidance, and distance dispersed decreased with increasing body condition. As species are increasingly being translocated back to mainland New Zealand, information gained in this study helps to fill a fundamental knowledge gap regarding dispersal behavior in a mainland context.
What Is Important for the Growth of Latecomers in the Medical Device Industry?

In the medical device industry, which is highly value-added and requires multidisciplinary knowledge, major global firms dominate the market, so it is necessary to establish a growth strategy suitable for latecomers. Through a Korean case, it was confirmed that import, diversification, and R&D activity are distinguishing strategies. The existing literature covers these strategies, but these findings are fragmented and differ from those of latecomers. This study examined the impact of the above factors on corporate growth, based on data of 440 Korean medical device manufacturers from 2011 to 2016. According to the results of panel data regression, diversification and R&D activity have a positive effect on the financial performance of a firm, while the import business model shows a negative effect. These results are expected to provide implications with respect to strategies for the growth of latecomers in the medical device industry. In future research, it is necessary to investigate how detailed strategies in accordance with the growth stages of a firm can be established.
Matching Demodulation Synchrosqueezing S Transform and its Application in Seismic Time–Frequency Analysis

Time–frequency (TF) analysis is a powerful tool to describe the frequency response of subsurface rocks and hydrocarbon reservoirs. In this letter, the matching demodulation synchrosqueezing S transform (MDSST) that achieves a highly concentrated TF representation was introduced to seismic TF analysis. The MDSST includes two steps: the matching demodulation technique is preprocessing that provides a rough estimation of instantaneous frequency (IF) of the analyzed signal, and the synchrosqueezing transform (SST) is postprocessing that produces an accurate IF. Numerical experiments on synthetic and real signals demonstrate the superiority of the MDSST in seismic TF analysis.
Traffic Signal Control With Reinforcement Learning Based on Region-Aware Cooperative Strategy

With the increase of private cars, traditional traffic signal control methods cannot alleviate the traffic congestion problem. Reinforcement learning (RL) is increasingly used in adaptive traffic light control. As urban traffic becomes more complex, reinforcement learning algorithms solely based on value or policy are not suitable for such scenarios. Moreover, the centralized method does not show a good effect on the multi-intersection, in particular, when the traffic flow is in the high-dimensional continuous state space. In this article, we propose a decentralized framework based on the advantage actor-critic (A2C) algorithm by assigning global control to each local RL agent or intersection. A2C algorithm involved in this article is a product of combining policy function and value function, which has good convergence ability and can be applied to continuous state space. The decentralized methods may put a new challenge: from the perspective of each local agent, the environment becomes partially observable. We overcome this problem by putting forward a region-aware cooperative strategy (RACS) based on graph attention network (GAT), which can incorporate the spatial information of the surrounding agents. We carry out experiments on synthetic traffic grid and real-world traffic network of Monaco city to compare with the existing A2C and Q-learning algorithms. Experimental results confirm that our RACS method has a shorter queue length and less waiting time than the two existing algorithms, and can reduce the total vehicle travel time.
The Data-Driven Deep Learning to Localization Product in Convenience Store

The penetration of Industry 4.0 in the convenience store is increasingly visible. The combination of Artificial Intelligence (AI), the Internet of Things (IoT), and robotic were always under evaluation, including applied AI in the whole system that is demanded robust when integrated with online shop. Meanwhile, the problem of speed detection and precision is still a challenge in AI. In this study data-driven deep learning was developed to improve the speed and maximize localization of consumer products. After the selected data-driven received from the online shop platform then triggers deep learning and activates a modified YOLOv2 in parallel. Thus, each detector per product is needed. Our system performance is proven by experiments to meet expectations in evaluating speed, precision, and performance in recognition and localization.
Revista de Administração Contemporânea Journal of Contemporary Administration

Editor-in-chief: Wesley Mendes-da-Silva (Fundação Getulio Vargas, EAESP, Brazil) Associate Editor: Paula C. P. de S. Chimenti (Universidade Federal do Rio de Janeiro, COPPEAD, Brazil) Guest Editor: Leonardo Marques (Universidade Federal do Rio de Janeiro, COPPEAD, Brazil) Reviewers: Flavia D'Albergaria Freitas (Universidade Federal do Rio de Janeiro, COPPEAD, Brazil) Ana Paula Passos (Universidade do Vale do Itajaí, Brazil)
Implementation of surface crack detection method for nuclear fuel pellets guided by convolution neural network

ABSTRACT Crack detection is one of the important contents of the nuclear fuel pellet quality inspection. Aiming at the problem of high crack false detection rate caused by low image contrast of nuclear fuel pellets, complex image background and fine cracks on the pellet surface, a Weighted Object Variance (WOV) threshold crack detection method guided by SE-CrackNet convolutional neural network is proposed. The method first uses the sliding window scanning technology and SE-CrackNet network to locate the crack regions in the pellet image, and then uses the WOV threshold method to extract the cracks to achieve accurate identification of the cracks on the surface of the nuclear fuel pellet. The pixel-level F1-measure of the method is about 92%, which can accurately identify cracks on the surface of nuclear fuel pellets, greatly reduce the crack false detection rate, meet the real-time quality inspection requirements of nuclear fuel pellet production lines, and vastly improve the performance of traditional machine vision inspection systems. At the same time, the method can be extended to the quality inspection of other industrial products.
Study on night transportation organization of high-speed rail express products

Along with the rapid development of high-speed railway, high-speed railway express products gradually mature, the electronic commerce industry of high-speed rise in demand for goods, the implementation of the high-speed rail freight trains is imperative, but freight trains operation organization faces new challenges at night. In this paper, we study the freight trains, different types of high-speed rail transportation express product process, the purpose is to effectively reduce skylight influence on train operation organization and freight trains for passenger train interference, and improve transportation efficiency, increase freight trains, operation specification, create a good environment for the emu operation. Based on the characteristics of different types of high-speed rail express products, this paper puts forward suggestions on rationalizing the transport process of freight emu, so as to give full play to the transport capacity advantages of freight emu, which is conducive to the high-quality development of freight emu.
Two-dimensional thin-layer chromatography fingerprint profiles of ten Cirsium species by chemometric processing

Ten methanolic extracts of selected Cirsium species were analyzed using two-dimensional thin-layer chromatography (2D-TLC) system with octadecyl reversed-phase (RP-18) chromatographic plate as the stationary phase and two eluents: nonaqueous, consisting of 2-butanone-toluene-acetic acid (4.5:5:0.5, v/v) used in the first direction of developing, and aqueous, consisting of methanol—water—formic acid (4:5:1, v/v) used in the second direction. The Naturstoff reagent was used for the derivatization of some phenolic compounds. Five selected standards were analyzed under the same chromatographic conditions, and their retention factor values were used for the confirmation of their presence on selected Cirsium chromatograms. Photographs of ten chromatograms were treated using the ImageJ program. 2D-TLC analysis was also performed to obtain the fingerprint chromatographic profiles of the studied methanolic extracts. The experimental data were objected to principal component analysis (PCA), and the PC2 vs. PC3 graphs were created. Based on the PCA results, the similarity between the selected Cirsium species was confirmed.
Improving the process performance of magnetic abrasive finishing of SS304 material using multi-objective artificial bee colony algorithm

Magnetic abrasive finishing is a super finishing process in which the magnetic field is applied in the finishing area and the material is removed from the workpiece by magnetic abrasive particles in the form of microchips. The performance of this process is decided by its two important quality characteristics, material removal rate and surface roughness. Significant process variables affecting these two characteristics are rotational speed of tool, working gap, weight of abrasive, and feed rate. However, material removal rate and surface roughness being conflicting in nature, a compromise has to be made between these two objective to improve the overall performance of the process. Hence, a multi-objective optimization using an artificial bee colony algorithm coupled with response surface methodology for mathematical modeling is attempted in this work. The set of Pareto-optimal solutions obtained by multi-objective optimization offers a ready reference to process planners to decide appropriate process parameters for a particular scenario.
Phytochemical Evaluation and Free Radical Scavenging Properties of Rhizome of Bergenia ciliata (Haw.) Sternb. Forma ligulata Yeo

Objective : To carry out phytochemical analysis of Bergenia ciliata forma ligulata rhizome and to evaluate its free radical scavenging properties. Materials and methods : Preliminary phytochemical analysis, estimation of total phenolic content, development of fingerprint profiles and estimation of gallic acid by HPTLC method were carried out as a part of phytochemical evaluation of Bergenia ciliata forma ligulata rhizome. Further, the free radical scavenging activity was evaluated using three in vitro models. Results : Preliminary phytochemical screening showed the presence of phenols, tannins, flavonoids and sterols. Total phenolic content was found to be 5.78% (w/w). The solvent system developed for fingerprint profile and gallic acid estimation gave good separation of gallic acid from the other components of the extract. The HPTLC method for gallic acid estimation was validated in terms of instrumental precision, accuracy and repeatability. The amount of gallic acid in the rhizome of B. ciliata forma ligulata was found to be 1.54% (w/w, dwb). The methanolic extract was found to be a good scavenger of DPPH radical with an EC 50 of 36.24 μg/ml. The extract scavenged superoxide radical in a dose dependent manner with EC 50 of 106.48 μg/ml. Conclusion : Phytochemical evaluation was carried out for Bergenia ciliata forma ligulata , and a sensitive HPTLC method was developed for the estimation of gallic acid as a marker compound. This developed method can be adopted for the estimation of gallic acid from various herbal drugs and formulations. Further, the methanolic extract of B. ciliata forma ligulata rhizome was found to scavenge DPPH and superoxide radicals in the models tested.
Computational Methods and Techniques Across Acoustics

Sound in the World Throughout human history, people and cultures have created sound for more than simple communication. For example, early humans likely made music using primitive flutes (Atema, 2014) and considered sound integral in the design of cities (e.g., Kolar, 2018). Furthermore, the Mayans designed structures at the ruins at Chichen Itza in Mexico that used sound for worship (Declercq et. al., 2004). Specifically, clapping in front of the stairs of the El Castillo pyramid creates a sound resembling a highly revered bird by way of a series of reflections up the stairs (available at bit.ly/3jPfOTk).
Comparative higher education research in times of globalisation of higher education: Theoretical and methodological insights

In times of globalisation of higher education, alternative theoretical and methodological approaches were introduced in the field of comparative higher education research. To stimulate the debate on this issue, this paper firstly addresses them theoretically by combining the concept of institutional isomorphism and the ‘glonacal’ analytical heuristic. On this basis, it discusses arguments in favour of convergence and diversity from the perspective of the internationalisation of higher education and also points to the limits of institutional isomorphism resulting from ‘glonacal’ influences of agencies and agency on the development of (internationalisation of) higher education. Secondly, the paper also draws attention to the influence of globalisation on the selection of methodology in comparative higher education research by exposing the limits of methodological nationalism. Along these lines, it portrays the reversed pyramid model of different horizontal and vertical levels of comparisons with which it establishes the (missing) link between the selected theoretical and methodological framework of comparative (higher education) research. In conclusion, it acknowledges the need to integrate the contextual element into the comparative framework which allows thorough analysis of complex relationships between globalisation and higher education both theoretically and methodologically.
Study on the Adsorption of Methylene Blue from Dye Wastewater by Humulus Japonicus Leaves

This paper took the objective of preparing high-performance, low-cost biological adsorbent for printing and dyeing wastewater, and the adsorption experiment of dyestuff wastewater with high chromaticity and high biodegradability was studied. The Methylene Blue was adsorbed by the prepared Humulus Japonicus Leaves (HJ), the effects of adsorption time, pH, dosage of adsorbent, initial Methylene Blue concentration and temperature on the adsorption process were investigated, and the adsorption mechanism was described by adsorption isotherm, adsorption thermodynamics and adsorption kinetics, and the results showed that: when HJ was added 0.15g and ph was 7, the temperature was 30°C (303K), adsorption was carried out for 20min, simulated dye wastewater, adsorption efficiency of Methylene Blue of 100mg/l were excellent, adsorption rate reached up to 92%, the equilibrium adsorption rate was positively correlated with the initial concentration of CV dye. Humulus leaves adsorption CV Gibbs free energy of ΔG<0, ΔH>0, ΔS>0 showed spontaneous adsorption process, the adsorption process Methylene Blu was more suitable for the Freundlich isothermal adsorption equation, the adsorption kinetics accorded with the quasi two level kinetic model, the adsorption of the Methylene Blue dye molecule by the HJ was chemically adsorbed as the rate control step, the Methylene Blue molecule was mainly adsorbed on the surface of the Humulus leaves; the model of internal diffusion kinetics showed that there was membrane diffusion and internal diffusion of the HJ in the process of Methylene Blue adsorption. The experimental results showed that HJ as adsorbent can effectively remove Methylene Blue from dye wastewater, and the research results provide a new method and idea for biological treatment of dye wastewater.
A new thermoresponsive polymer of poly(N-acryloylsarcosine methyl ester) with a tunable LCST

Poly(N-acryloylsarcosine methyl ester) (PNASME), a thermoresponsive N-ester substituted polyacrylamide that has a well-defined molecular weight and a low Đ, was synthesized by solution RAFT polymerization. The synthesized PNASME exhibited a cloud point temperature (Tcp) or lower critical solution temperature (LCST) of 44.0 °C. It was found that various factors could affect the Tcp of PNASME, e.g., the polymer molecular weight, the polymer concentration, the salt effect on Tcp following the order of the Hofmeister series, urea induced increasing Tcp, and phenol induced decreasing Tcp. The mechanism of urea and phenol inducing the phase transition of PNASME was revealed by 2D NOESY spectroscopy, and how the hydrogen bonding between PNASME and the solutes of urea and phenol affected the phase transition of PNASME was clarified. The contrary effect on the Tcp of PNASME induced by urea and phenol makes it easy to adjust the thermoresponse of PNASME, and the tunable thermoresponse of the diblock copolymer of poly(N-acryloylsarcosine methyl ester)-block-poly(N-isopropylacrylamide) was demonstrated. The present study is believed to offer a new route to tune the solution behavior of thermoresponsive polymers.
Robust Design for Integrated Satellite–Terrestrial Internet of Things

In this article, we investigate an integrated satellite–terrestrial (IST) Internet-of-Things (IoT) network, where satellite networks provide wireless services to the IoT devices uncovered by terrestrial cellular networks, so as to realize seamless coverage across the world. In order to support massive access of a large number of IoT devices, the low Earth orbit (LEO) satellites and the terrestrial base station (BS) both adopt power-domain nonorthogonal multiple access (NOMA) techniques designed according to channel state information (CSI). Due to the limited capacity of feedback links, there exists channel uncertainty at the LEO satellites and BSs, resulting in internetwork interference inevitably. In order to guarantee the performance of the IST-IoT network, we formulate a optimization problem to minimize the total transmit power of the IST-IoT network subject to outage probability constraints on the rates for the IoT devices associated to both satellite and terrestrial networks. Since the original problem is mathematically intractable, we utilize a series of transformations to obtain an approximate equivalent convex problem. Then, we propose an iterative penalty function (IPF)-based algorithm to jointly design robust beamforming for the satellite and BSs. Finally, we provide extensive simulation results to reveal the impacts of important system parameters and confirm the effectiveness of the proposed robust design algorithm for IST-IoT networks.
An MMTES algorithm for dynamic photovoltaic array reconfiguration to enhance power output under partial shading conditions

Funding information Science and Engineering Research Board, Grant/Award Number: CRG/2018/003908 Abstract Partial shading is a severe impediment to the effective use of photovoltaic systems. It will lead to performance degradation in the photovoltaic system. This work proposes a maximum–minimum tier equalisation swapping reconfiguration algorithm for total-crosstied connection under shading conditions. The proposed reconfiguration algorithm uses a switch matrix to alter the interconnection of modules in a photovoltaic array. The switch matrix dynamically modifies the connections based on the equalisation of tier irradiance. This algorithm applies to the symmetrical and asymmetrical photovoltaic array. Further, simulation studies show the efficacy of the proposed algorithm by minimising the multiple peaks and enhancing the output power compared with the traditional total-cross-tied configuration. The performance of experimental tests ascertains the feasibility of the proposed method.