Miracle-dz/UniFAR-FTUs huggingface dataset:
Realisation of a Novel Functionally Redundant Actuation System for a Railway Track-Switch

This paper focuses on modelling, control, realisation and performance analysis of a full-scale demonstrator for a novel railway track switch. For over a century, railway track switches (or points) have been allowing trains to safely change between routes. As they are safety-critical elements of the rail network, when they fail, the signalling system will prevent trains from using that route. This means poor reliability (or lack of availability) leads to significant delays and costs; hence there is huge interest from researchers and engineers in improving the overall reliability of track switches. This paper presents new results, which represent a meaningful first step toward a revolution in the way track switches are actuated. A “REPOINT-Light” railway track switch demonstrator is introduced which uses a new concept of locking to allow redundant actuation with three actuator bearers operating under closed-loop feedback control. The new concept, its control system and its mechanical viability are tested in experiments at the Great Central Railway in the UK. To support the design of the actuators and the control system, a dynamic simulation model is developed by co-simulation involving Simulink and Simpack. The experimental results presented are used to validate the models and the paper discusses how the models themselves are used as the vehicle for the design of feedback controllers. Virtual testing of the controllers in simulation is a vital step prior to the implementation and deployment of the controllers in the demonstrator switch. The major contribution of this work is demonstrating, for the first time at full scale on a real-world track switch, that it is possible to use one-out-of-three actuator redundancy to provide fault-tolerant operation of railway track switch.
Generating Long Time Series of High Spatiotemporal Resolution FPAR Images in the Remote Sensing Trend Surface Framework

To improve our capacity to map long-term vegetation dynamics in heterogeneous landscapes, this study proposed a new prior knowledge-based spatiotemporal enhancement method, namely, PK-STEM, to fuse MODIS and Landsat FPAR products following the remote sensing trend surface framework. PK-STEM uses historical Landsat FPAR images as prior knowledge and fuses them with new satellite-derived FPAR data. PK-STEM can work in three modes: 1) using only MODIS data; 2) using only Landsat data; and 3) using both MODIS and Landsat data. This study retrieved FPAR from Landsat images using a scaling-based method and tested the performance of PK-STEM in a regional application. For the entire year of 2012, we compared the performance of PK-STEM in different modes and with that of two typical spatiotemporal fusion methods, the enhanced spatial and temporal adaptive reflectance model (ESTARFM) and unmixing-based linear mixing growth model (LMGM). Then, a long time series FPAR data set at 30-m resolution and eight-day intervals was generated for 13 years (2000–2012). Our results show that PK-STEM in mode III is the most robust and accurate (root mean squared error (RMSE) = 0.062; mean <inline-formula> <tex-math notation="LaTeX">$R = 0.851$ </tex-math></inline-formula>) among the three modes and more accurate than ESTARFM (mean RMSE = 0.065; mean <inline-formula> <tex-math notation="LaTeX">$R = 0.776$ </tex-math></inline-formula>) and LMGM (mean RMSE = 0.074; mean <inline-formula> <tex-math notation="LaTeX">$R = 0.734$ </tex-math></inline-formula>). For the 12 years (2000–2011), PK-STEM also achieves high accuracies with mean RMSE = 0.066 and <inline-formula> <tex-math notation="LaTeX">$R = 0.938$ </tex-math></inline-formula>. PK-STEM is very flexible with a continual update mechanism and is efficient for long time series applications.
ResNet + LSTM method for age-related macular degeneration and diabetic retinopathy diagnosis on OCT images

With the fast development of medical image devices and technologies, the amount of medical image data has increased signiﬁcantly at a unprecedented rate. In many clinical specialities, there can be a shortage of doctors and radiologist experts to give timely diagnosis and referral to patients when facing the large amount of medical images and data. Especially for the ophthalmology, the widespread availability of optical coherence tomography (OCT), which is a novel medical imaging technology that allow acquisition of cross-sectional images of the retina with semihistologic resolution[1], has not been matched by the availability of human experts to interpret scans and provide appropriate treatments[2]. According to the National Reporting and Learning System (NRLS), there are about 250 cases of sight harm due to the diagnosis delay per year in UK[3]. Hence, how can we improve the eﬃciency of clinical diagnosis is a urgent problem need to be solved. In this dissertation, we are going to present a method for classifying normal, diabetic retinopathy (DR) and age-related macular degeneration (AMD) on OCT scan
Magnetic Properties Identification by Using a Bi-Objective Optimal Multi-Fidelity Neural Network

In order to identify the magnetic properties of magnetic steel, the synergy between the data arising from the experimental activity, an FE model, and the use of a multi-fidelity surrogate could relieve the burden of the total cost. A neural network, with as many outputs as fidelity levels, is adopted in quality of metamodel to describe the forward problem [forward neural network (FNN)]. FNN is trained using multiple losses aiming at getting a robust surrogate that is poorly sensitive to the chosen norm. This makes it bi-objective optimal since several error metrics are simultaneously minimized. In addition, a conjugate, inverse net (INNCJ) is built, which is a ready-to-use tool for inverse properties identification, since no optimization runs are required. Its performances are compared to those obtained with a transfer learning-based approach (INNTR) and a single-fidelity inverse neural network (INNSF). Finally, a real $B - H$ curve identification task has been solved, thereby validating the conjugate inverse net.
Enantioselective Diels–Alder reaction in the confined space of homochiral metal–organic frameworks

A novel homochiral porous metal–organic framework (MOF) has been synthesized using (R)-2,2′-dihydroxy-1,1′-binaphthyl-4,4′-dibenzoic acid as the chiral ligand. This MOF acts as an effective heterogeneous catalyst for the enantioselective Diels–Alder reaction between isoprene and N-ethyl maleimide.
A K-means++ Based User Classification Method for Social E-commerce

At present, the research on the classification of e-commerce users is relatively mature, but with the rise of mobile social networks, the combination of social networks and e-commerce networks has become a trend and is developing rapidly. Traditional e-commerce user classification methods are not suitable for social e-commerce users. Therefore, based on the research on traditional e-commerce user classification methods, according to the characteristics of social e-commerce users, we improved data preprocessing and parameter tuning methods, and proposed a clustering method of social e-commerce users based on the K-means++ algorithm. The test on the actual data of social e-commerce users showed that the retention rates of users of various classes are significantly different, which express that the proposed method can classify social e-commerce users accurately.
Usage of the multivariate adaptive regression splines (MARS) in studies of the sorption process of three-dyed mixture on dolomitic limestone

Abstract The aim of the study is to check the possibility of usage of statistical calculations in determining of actual concentration of single dye in the mixture of three dyes by single full spectrum UV–Vis analysis. The paper presents the usage of the multivariate adaptive regression splines method in the study over kinetic model and equilibrium parameters of the multicomponent sorption process of three-dyed mixture on dolomitic limestone. The MARSplines method allowed for quick and simple determination of the accurate concentration of each dye in the mixture simultaneously. The best parameters of the sorption process were 100 mg/dm3 concentration of each dye and 50 mg of the bed. The equilibrium is best described by the Extended Langmuir model. The calculated values of maximum sorption capacity (q max) for the Extended Langmuir model were: 398.23 mg/g for quinoline yellow, 101.03 mg/g for crystal violet and 269.56 mg/g for methylene blue. The kinetics of the process was best described by pseudo-second-order model, which together with Extended Langmuir model indicates the chemical type of this process.
Probing the local, electronic and magnetic structure of matter under extreme conditions of temperature and pressure

ABSTRACT In this paper we present recent achievements in the field of investigation of the local, electronic and magnetic structure of the matter under extreme conditions of pressure and temperature. These results were obtained thanks to the coupling of a compact laser heating system to the energy-dispersive XAS technique available on the ID24 beamline at the ESRF synchrotron. The examples chosen concern the melting and the liquid structure of 3d metals and alloys under high pressures (HPs) and the observation of temperature-induced spin crossover in FeCO3 at HP.
Synthesis of Some Novel Fused Heterocyclic Compounds Derivatives from Bis-chalcones

A chalcone was prepared by the reaction of 1,4-diacetylbenzene with benzaldehyde. Reaction of this chalcone with cynanothioacetamide/guanidine hydrochloride and malnonitrile in presence of piperdene afforded the corresponding pyridine, pyrimidine, and pyrans derivatives in good yields respectively. Further, bis-chalcone 1 was cyclized to pyrazole analogs by using thiosemicarbazide, semicarbazide and tertiarybutylcarbazate. The newly heterocyclic compounds have been characterized by IR, 1H-NMR and elemental analyses.
A Multifunctional Full-Polarization Reconfigurable 28 GHz Staggered Butterfly 1-D-Beam Steering Antenna

A novel multifunctional staggered <inline-formula> <tex-math notation="LaTeX">$8\,\,\times12$ </tex-math></inline-formula> Butterfly phased array antenna is proposed at <italic>Ka</italic>-band (28 GHz) for 5G communications with key features of full-polarization reconfigurability, flexible radiation pattern, and wide-angle 1-D-beam steering performance. The unit cell of the proposed array is a two Butterfly radiating antennas separated by <inline-formula> <tex-math notation="LaTeX">$2\lambda \text{g}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\lambda \text{g}\,\,=$ </tex-math></inline-formula> effective wavelength) with two ports, where each Butterfly is a sequentially rotated series-fed microstrip patch antennas. Full-polarization reconfiguration (right-hand circular polarization (RHCP), left-hand circular polarization (LHCP), Linear-X, and Linear-Y polarization) is achieved by suitable excitation of the ports to realize increased system capacity. Flexible radiation pattern with dynamic 3 dB gain-beamwidth from 16° to 90° is achieved to realize a variable cellular range, angle, and gain requirements. The proposed staggered planar array configuration reduces the spacing between the adjacent series-fed linear array to <inline-formula> <tex-math notation="LaTeX">$0.45\lambda _{0}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the free-space wavelength at 28 GHz. The proposed array size of <inline-formula> <tex-math notation="LaTeX">$8\,\,\times12$ </tex-math></inline-formula> Butterfly provides beam steering up to ±63° without any grating lobes. Analytical study using a periodic leaky-wave antenna (LWA) theory is included to provide insights into the radiation characteristics of the Butterfly series-fed linear array antenna. The beam steering characteristics were verified by using measured patterns of the individual branches and by applying the computed array factor. The full-polarization reconfiguration and flexible radiation patterns with sidelobe reduction are implemented and experimentally verified with a 16-channel Analog Devices ADMV4821 RFIC <italic>Ka</italic>-band beamformer.
Planar Ultra-Wideband and Wide-Scanning Dual-Polarized Phased Array With Integrated Coupled-Marchand Balun for High Polarization Isolation and Low Cross-Polarization

In this article, a dual-polarized planar phased array with high polarization isolation and low cross-polarization is presented operating from 4 to 18 GHz, i.e., 4.5:1. The proposed array is comprised of tightly coupled dipoles with integrated coupled-Marchand baluns. To improve the uniformity of fields distributed on the array, the center-feeding dipole is used in this design instead of the conventional edge-feeding one at first. Then, the outer conductors of the feed are composed of a group of shorted vias with the proper number and position. Based on these methods, the output balance of the balun is significantly improved, resulting in high isolation between ports with different polarization modes. Furthermore, this feed has a natural ability to suppress the D-plane common mode resonance. The capacitive metallic annular plate over adjacent radiating elements and the thick aluminum plate with an air cavity placed under the array are employed together to suppress the in-band coupled-loop modes. The infinite array simulation indicates that the array can achieve transmit (Tx)/receive (Rx) isolation more than 48 dB at broadside. Isolation better than 32 and 30 dB can be achieved when scanning to 45° in E-/H-planes and 60° in E-plane, respectively. The cross-polarization level is below −54 dB at broadside and remains below −29 dB when scanning to 60° in E-plane as well as 45° in H-plane. A $12\times12$ dual-polarized antenna array is fabricated and measured to validate the correctness of this design. This type of antenna can be applied in wideband simultaneous transmit and receive (STAR) monostatic systems.
Interpretable Hyperspectral Artificial Intelligence: When nonconvex modeling meets hyperspectral remote sensing

Hyperspectral (HS) imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to process and analyze these HS products, mainly by seasoned experts. However, with an ever-growing volume of data, the bulk of costs in manpower and material resources poses new challenges for reducing the burden of manual labor and improving efficiency. For this reason, it is urgent that more intelligent and automatic approaches for various HS RS applications be developed. Machine learning (ML) tools with convex optimization have successfully undertaken the tasks of numerous artificial intelligence (AI)-related applications; however, their ability to handle complex practical problems remains limited, particularly for HS data, due to the effects of various spectral variabilities in the process of HS imaging and the complexity and redundancy of higher-dimensional HS signals. Compared to convex models, nonconvex modeling, which is capable of characterizing more complex real scenes and providing model interpretability technically and theoretically, has proven to be a feasible solution that reduces the gap between challenging HS vision tasks and currently advanced intelligent data processing models.
Institutional environment, competencies and firm export performance: A study of the emerging country

How to cite this paper: Siddiqui, A. A. , & Singh, P. (2021). Institutional environment, competencies and firm export performance: A study of the emerging country. Corporate Ownership & Control, 18(2), 169-179. https://doi.org/10.22495/cocv18i2art14 Copyright © 2021 The Authors This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/
A bias-corrected Nelson-Aalen estimator

The starting point to model an incomplete dataset of a non-negative random variable is usually to estimate its reliability function using a non-parametric reliability estimator. Two such estimators are Kaplan-Meier estimator and Nelson-Aalen estimator. Their performances have been compared and some drawbacks (e.g., biasness) have been identified in the literature. However, improvements on them are scarce. This paper aims to fill this gap by proposing a simple and almost unbiased estimator. This estimator is a weighted average of the Nelson-Aalen reliability estimates at two successive time points. An application of the proposed estimator in model selection is discussed and a real-world dataset is analyzed to illustrate the appropriateness and usefulness of the proposed estimator.
Energy-Efficient Hybrid Symbol-Level Precoding for Large-Scale mmWave Multiuser MIMO Systems

We address the symbol-level precoding design problem for the downlink of a multiuser millimeter wave (mmWave) multiple-input multiple-output (MIMO) wireless system where the transmitter is equipped with a large-scale antenna array. The high cost and power consumption associated with the massive use of radio frequency (RF) chains prohibit fully-digital implementation of the precoder, and therefore, we consider a hybrid analog-digital architecture where a small-sized baseband precoder is followed by two successive networks of analog on-off switches and variable phase shifters according to a fully-connected structure. We jointly optimize the digital baseband precoder and the states of the switching network on a symbol-level basis, i.e., by exploiting both the channel state information (CSI) and the instantaneous data symbols, whereas the phase-shifting network is designed only based on the CSI due to practical considerations. Our approach to this joint optimization is to minimize the Euclidean distance between the optimal fully-digital and the hybrid symbol-level precoders. Remarkably, the use of a switching network allows for power-savings in the analog precoder by switching some of the phase shifters off according to the instantaneously optimized states of the switches. Our numerical results indicate that, on average, up to 50 percent of the phase shifters can be switched off. We provide an analysis of energy efficiency by adopting appropriate power dissipation models for the analog precoder, where it is shown that the energy efficiency of precoding can substantially be improved thanks to the phase shifter selection approach, compared to the fully-digital and the state-of-the-art hybrid symbol-level schemes.
Modeling the Dynamics of Tamponade Multicomponent Gases During Retina Reattachment Surgery

Vitrectomy and pneumatic retinopexy are common surgical procedures used to treat retinal detachment. To reattach the retina, gases are used to inflate the vitreous space allowing the retina to attach by surface tension and buoyancy forces that are superior to the location of the bubble. These procedures require the injection of either a pure tamponade gas, such as C3F8 or SF6, or mixtures of these gases with air. The location of the retinal detachment, the anatomical spread of the retinal defect, and the length of time the defect has persisted, will determine the suggested volume and duration of the gas bubble to allow reattachment. After inflation, the gases are slowly absorbed by the blood allowing the vitreous to be refilled by aqueous. We have developed a model of the mass transfer dynamics of tamponade gases during pneumatic retinopexy or pars plana vitrectomy procedures. The model predicts the expansion and persistence of intraocular gases (C3F8, SF6), oxygen, nitrogen, and carbon dioxide, as well as the intraocular pressure. The model was validated using published literature in rabbits and humans. In addition to correlating the mass transfer dynamics by surface area, permeability, and partial pressure driving forces, the mass transfer dynamics are affected by the percentage of the tamponade gases. Rates were also correlated with the physical properties of the tamponade and blood gases. The model gave accurate predictions in humans.
Formononetin - An isoflavone metabolite found in the liver of rats fed with soy protein isolate

Soy protein isolate, containing genistein, daidzein and glycitein, was used to study the profiles of soy isoflavone metabolites in Sprague-Dawley rats. After 50 days, rat liver tissues, serum and urine were analyzed by HPLC-MS and HPLC-ECD. HPLC-APCI-MS results showed that daidzein, equol, genistein and O-DMA were detected. Interestingly, the aglycone and the conjugated forms of formononetin, which is a methylated derivative of daidzein found in many plants, were also observed in rat liver and serum, but no t in urine. The respective concentrations of these two forms of formononetin were 0.056 ± 0.022 and 0.621 ± 0.116 nmoL/g (mean ± SD) in liver tissue, and were 0.005 ± 0.001 and 0.035 ± 0.002 nmoL/mL in rat serum. Formononetin in conjugated forms were 90.8% in liver tissue and 85.7% in serum by calculation. Incubation of daidzein with liver homogenate, microsomes, and catechol 4’- O-methyl transferase (COMT) resulted in a 7~10% conversion of daidzein to the aglycone form of formononetin. Formononetin is proposed t o be a metabolite of O-methylation of daidzein in rat liver and exists mainly in conjugated forms.
Paper-based thioglycolic acid (TGA)-capped CdTe QD device for rapid screening of organophosphorus and carbamate insecticides

A paper-based device, based on the fluorescence switching of water-soluble thioglycolic acid (TGA)-capped CdTe QDs, was developed for the simple, rapid and sensitive detection of organophosphorus (OP) and carbamate (CM) insecticides. A new design platform for the developed device was created, comprising a foldable sheet with a detection zone and a buffer solution loading channel, to simplify the multi-step reaction of a bi-enzyme assay with a signal enhancement system. This device was very useful for fast screening and on-site detection, without requiring many reagents. The bi-enzyme includes acetylcholinesterase (AChE), choline oxidase (ChOx) and TGA-capped CdTe QDs, which were coated on the paper-based device at the detection zone in a separated sheet, starting with an acetylcholine (ACh) substrate coating. After incubation of the sample at the detection zone, the device was closed to initiate enzyme catalyzed hydrolysis of the pre-spotted ACh. Subsequently, the buffer solution was applied to the device, allowing for the pre-spotted chemicals to mix well and importantly, result in signal enhancement. The hydrolysis of ACh was catalyzed by AChE followed by ChOx to yield H2O2, which can quench the fluorescence of the TGA-capped CdTe QDs. In the presence of OP and CM insecticides, the AChE activity was inhibited, resulting in decreased quenching of the TGA-capped CdTe QDs. The change in the fluorescence intensity of the TGA-capped CdTe QDs can be observed using the naked eye under UV-black light. Under optimized conditions, the limit of detection for pirimicarb, dichlorvos and carbaryl were found to be 0.05, 0.01 and 0.01 ppm, respectively, using visual measurements. This developed device was successfully applied to the detection of OP and CM insecticide residues in agricultural products. The data correlated well with the data obtained using gas chromatography-tandem mass spectrometry (GC-MS/MS). This developed device shows good selectivity and sensitivity for the rapid screening of insecticides and could be useful for on-site applications.