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Bearings are critical in today’s mechanisms, and their reliability is continuously improving. Yet, working under high loads for long periods, bearings will degrade and eventually fail. An unpredicted bearing failure can lead to total and catastrophic failures of machines and may even lead to human injuries that result in substantial economic losses and reductions in production. Determining a bearing’s remaining useful life (RUL) has become an important topic in many industrial fields. Vibration signals are the most used representation for understanding a bearing’s health status. Using different algorithms, time-domain vibration signals can be transformed into time-frequency domain signals that help indicate a bearing’s status. For instance, this thesis investigates spectrograms and scalograms to visually represent a bearing’s health condition using a short-time Fourier transform (STFT) and a continuous wavelet transform (CWT). Both representations are plotted as a function of time and frequency and can detect the bearing’s working condition. However, spectrograms are advantageous in revealing frequency changes along the time axis, while scalograms facilitate the detection of abrupt changes. Combined with a convolutional neural network (CNN), these plots can be used to interpret bearing RUL. The strength of CNNs lie in their ability to identify and detect features in images, including such tasks as image classification, using share-weight architectures, convolutional layers, and kernels. This thesis explores CNNs combined with spectrograms and scalograms using the PRONOSTIA dataset to perform bearing RUL predictions and explore relationships between prognosis and diagnosis for bearing faults analysis.

Optical box traps for cold atoms offer new possibilities for quantum-gas experiments. Building on their exquisite spatial and temporal control, we propose to engineer system-reservoir configurations using box traps, in view of preparing and manipulating topological atomic states in optical lattices. First, we consider the injection of particles from the reservoir to the system: this scenario is shown to be particularly well suited to activate energy-selective chiral edge currents, but also, to prepare fractional Chern insulating ground states. Then, we devise a practical evaporative-cooling scheme to effectively cool down atomic gases into topological ground states. Our open-system approach to optical-lattice settings provides a new path for the investigation of ultracold quantum matter, including strongly-correlated and topological phases., Comment: 15 pages, 11 figures including Supplementary material

A novel vacuum cooling system, which mainly consists of a 49-stage thermal transpiration based vacuum pump and a 100 L vacuum vessel, is proposed. The novel system can directly be driven by heat, w...

The recent progress in engineering topological band structures in optical-lattice systems makes it promising to study fractional Chern insulator states in these systems. Here we consider a realistic finite system of a few repulsively interacting bosons on a square lattice with magnetic flux and sharp edges, as it can be realized in quantum-gas microscopes. We investigate under which conditions a fractional Chern insulator state corresponding to the Laughlin-like state at filling $\nu=1/2$ can be stabilized and its fractional excitations probed. Using numerical simulations, we find an incompressible bulk density at the expected filling for systems, whose linear extent is as small as 6-8 sites. This is a promising result, since such small systems are favorable with respect to the required adiabatic state preparation. Moreover, we also see very clear signatures of excitations with fractional charge in response both to static pinning potentials and dynamical flux insertion. Since the compressible edges, which are found to feature chiral currents, can serve as a reservoir, these observations are robust against changes in the total particle number. Our results suggest that signatures of both a fractional Chern insulator state and its fractional excitations can be found under realistic experimental conditions., Comment: 23 pages, 8 figures; minor revision; resubmit to SciPost Physics

An optical fiber immunosensor with a low detection limit based on plasmon coupling enhancement is proposed for detecting human immunoglobulin G (IgG). Graphene oxide (GO)-gold nanorod composites are synthesized and modified onto a photonic crystal fiber (PCF) surface coated with a Au film. GO, as a biosensitive layer, is used to decorate the gold nanorods and concentrate target molecules. The experimental result indicates that the refractive index sensitivity is drastically enhanced to 22248 nm/RIU because of plasmon coupling. Correspondingly, the human IgG detection limit decreases to 6 ng/mL. Moreover, the PCF is insensitive to temperature fluctuation, which can further reduce the measurement error.

A sapphire fiber high temperature sensor based on Fabry-Perot interference was studied in the paper. A sapphire wafer served as the Fabry-Perot cavity was fixed to the end face of the sapphire fiber. The sensor was encapsulated in an alumina ceramic tube-ceramic sleeve structure to improve structural stability. Experiment results showed the sensor had a wide temperature measurement range of 25 °C–1550 °C. The temperature sensitivity reached 32.5 pm/°C at 1550 °C. Furthermore, the temperature was demodulated from the interference spectrum through fast Fourier transform algorithm. It was concluded that the sapphire fiber sensor with advantages of small size, good stability and a wide range of temperature measurement is very promising for measuring high temperature.

Mars surface composition detector (MarSCoDe) is a scientific instrument suite onboard the Mars rover of the “Tianwen-1” mission, which uses laser-induced breakdown spectroscopy and shortwave infrared spectroscopy to detect the composition of soils and rocks at the surface of Mars. The optical head unit (OHU) is the core hardware of MarSCoDe, containing a Cassegrain telescope and other optical modules for lasers generation and signals transmission. The unit lacks thermal control resources and is located outside the rover’s cabin, which will directly face the Martian surface drastic temperature changes. We introduce the optomechanical designs that realize the lightweight and high thermal stability of the OHU optical system, especially the designs and implementations of the semiopen primary mirror based on silicon carbide and the fully closed optical bench based on carbon fiber-reinforced polymer. Meanwhile, the advantages and difficulties of silicon carbide, long carbon fiber-reinforced silicon carbide composites, and carbon fiber-reinforced polymer materials used for small and compact optomechanical systems are discussed. Subsequently, the environmental adaptability of the telescope system of OHU was studied through analytical and experimental methods, which show that it can achieve the required optical performance over a temperature range of approximately 100°C.

Mars Surface Composition Detector (MarSCoDe) is a scientific payload onboard the Mars rover of China’s Tianwen-1 mission. With the capability of 1.6∼7 m remote detection and analysis, MarSCoDe instrument suite consists of a two dimensional pointing mirror and an optical head outside the rover cabin, a Laser Induced Breakdown Spectroscopy (LIBS) spectrometer and a Short Wave Infrared (SWIR) spectrometer collectively covering 240∼2400 nm and a master controller unit inside the rover body, calibration target sets, optical fibers and power cables connecting the internal and external units. Combining the techniques of active LIBS, passive SWIR and micro-imaging, MarSCoDe provides functions including elemental composition discrimination and quantitative determination, classification of rock and soil characteristics, sample texture imaging and characterization of plasma-excited area. This paper introduces MarSCoDe mainly in terms of scientific objectives, design requirements, assembly and implementation, spectral and radiation calibration, and performance verification. The LIBS laser irradiance on the target can soundly exceed 10 MW/mm2, and the performance of the LIBS module operated at different temperatures has been tested. The field of view of the SWIR spectrometer is 36.5 mrad. The micro-imager can extract the central pixel area of 320 × 320 and 1024 × 1024, and the former is binned into 64 × 64. The 2D pointing mirror has a wide forward detection range and a narrow backward calibration range, with the pointing pitch accuracy better than 0.133°.

BPTF associated protein of 18 kDa (BAP18) has been reported as a component of MLL1-WDR5 complex. However, BAP18 is an uncharacterized protein. The detailed biological functions of BAP18 and underlying mechanisms have not been defined. Androgen receptor (AR), a member of transcription factor, plays an essential role in prostate cancer (PCa) and castration-resistant prostate cancer (CRPC) progression. Here, we demonstrate that BAP18 is identified as a coactivator of AR in Drosophilar experimental system and mammalian cells. BAP18 facilitates the recruitment of MLL1 subcomplex and AR to androgen-response element (ARE) of AR target genes, subsequently increasing histone H3K4 trimethylation and H4K16 acetylation. Knockdown of BAP18 attenuates cell growth and proliferation of PCa cells. Moreover, BAP18 depletion results in inhibition of xenograft tumor growth in mice even under androgen-depletion conditions. In addition, our data show that BAP18 expression in clinical PCa samples is higher than that in benign prostatic hyperplasia (BPH). Our data suggest that BAP18 as an epigenetic modifier regulates AR-induced transactivation and the function of BAP18 might be targeted in human PCa to promote tumor growth and progression to castration-resistance.

Recent 2D-to-3D human pose estimation works tend to utilize the graph structure formed by the topology of the human skeleton. However, we argue that this skeletal topology is too sparse to reflect the body structure and suffer from serious 2D-to-3D ambiguity problem. To overcome these weaknesses, we propose a novel graph convolution network architecture, Hierarchical Graph Networks (HGN). It is based on denser graph topology generated by our multi-scale graph structure building strategy, thus providing more delicate geometric information. The proposed architecture contains three sparse-to-fine representation subnetworks organized in parallel, in which multi-scale graph-structured features are processed and exchange information through a novel feature fusion strategy, leading to rich hierarchical representations. We also introduce a 3D coarse mesh constraint to further boost detail-related feature learning. Extensive experiments demonstrate that our HGN achieves the state-of-the art performance with reduced network parameters. Code is released at https://github.com/qingshi9974/BMVC2021-Hierarchical-Graph-Networks-for-3D-Human-Pose-Estimation., Comment: accepted by BMVC 2021

Imperial Users only Distinction

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A review is presented on high temperature measurement technology based on sapphire optical fiber. This review paper focuses on the sensing theory, sensor structures and sensing performances of different sapphire fiber sensors. Firstly, there is discussion on pyrometer made from sapphire fiber and description on its corresponding sensing properties. Secondly, there are summary on sapphire fiber Bragg grating (SFBG) inscribed by different methods for high temperature measurement. Thirdly, there are analysis on sapphire fiber sensors based on Fabry Perot (FP) interference with different structures. All above, subsequently, lead to the discussion on microwave interferometry and Raman scattering-based sapphire fiber sensors. Then a sensing performance comparison of sapphire pyrometers based on different detection principles are discussed. On the premise of all above, a future prospect and development trend of high-temperature sapphire fiber sensor are addressed as well.

The wing parameters of a subsoiler, such as the location and angle of the wings, have an important impact on the operating performance of the winged subsoilers. To study the comprehensive effect of wing parameters and to determine the optimal parameters of a winged subsoiler, a field experiment was conducted. The experimental factors were the mounting height (50, 100, 150, 200, and 250 mm), sweep angle(5°, 15°, 25°, 35°, and 45°) and mounting angle(5°, 15°, 25°, 35°, and 45°). The draft force of the subsoiler and the disturbed soil area were measured; these two variables defined the Specific Draft Force (SDF). The SDF was used as the response index to evaluate the performance of the winged subsoiler. The mathematical model of regression between experimental factors and SDF was established. The results showed that the normal probability distribution of the predicted and measured values of SDF tended to be linear, indicating that the credibility of the results of the analysis was higher. The mounting height, mounting angle, and sweep angle had interactive effects on SDF. The order of significance was mounting height, mounting angle, and sweep angle. The experimental parameters were optimized by Design-Expert 8.0 software: 124 mm for the mounting height, 45° for the mounting angle, and 45° for the sweep angle. This optimal combination of parameters resulted in a SDF of 69.9 kN/m2. The winged subsoiler designed using the optimization results showed that the average value of SDF was 78.73 kN/m2: significantly lower than SDF (79.34-95.33 kN/m2) before optimization. Keywords: Mounting angle, Mounting height, Optimization, Parameter, Specific Draft Force (SDF), Subsoiler, Sweep angle, Wing.

Background: We aimed to conduct a meta-analysis to evaluate the efficacy and safety between once daily (OD) and twice daily (BD) regime dosing of mesalazine for mild-to-moderate ulcerative colitis (UC). Methods: PubMed, Embase, the Cochrane library, and Web of Science from 1990 to November 2018 were investigated. We searched randomized controlled trials (RCTs) comparing OD with BD regime dosing of mesalazine for mild-to-moderate UC. The software Review Manager 5.3 was used to pool the risk ratio (RR) with a 95% confidence interval (CI). Results: Eight RCTs containing 3495 patients were identified. Regardless of induction of remission or maintenance of remission of UC, OD regime dosing of mesalazine was as effective as BD regime dosing in clinical and endoscopic remission and clinical remission. Also, no obvious difference was found between OD and BD regime dosing of mesalazine regardless of total adverse events, treatment-related adverse events or serious adverse events. Conclusion: OD is as effective and safe as BD regime dosing of mesalazine for active UC.

The performance of Deep Neural Networks (DNNs) keeps elevating in recent years with increasing network depth and width. To enable DNNs on edge devices like mobile phones, researchers proposed several network compression methods including pruning, quantization and factorization. Among the factorization-based approaches, low-rank approximation has been widely adopted because of its solid theoretical rationale and efficient implementations. Several previous works attempted to directly approximate a pre-trained model by low-rank decomposition; however, small approximation errors in parameters can ripple a large prediction loss. As a result, performance usually drops significantly and a sophisticated fine-tuning is required to recover accuracy. We argue that it is not optimal to separate low-rank approximation from training. Unlike previous works, this paper integrates low rank approximation and regularization into the training. We propose Trained Rank Pruning (TRP), which iterates low rank approximation and training. TRP maintains the capacity of original network while imposes low-rank constraints during training. A stochastic sub-gradient descent optimized nuclear regularization is utilized to further encourage low rank in TRP. The TRP trained network has low-rank structure in nature, and can be approximated with negligible performance loss, eliminating fine-tuning after low rank approximation. The methods are comprehensively evaluated on CIFAR-10 and ImageNet, outperforming previous compression methods using low rank approximation. Code is available: https://github.com/yuhuixu1993/Trained-Rank-Pruning, Accepted by NIPS2019 EMC2 workshop, the same version as the withdrawn arXiv:1910.04576

Activated carbon modified with Cu2+ and Co2+ was used to remove PH3 and H2S from yellow phosphorus off-gas. An orthogonal experiment was carried out to identify the superiority order of influencing factors and the optimal experimental parameters. For PH3, the superiority order was temperature > oxygen content > parch temperature > impregnant concentration (Cu2+) > flow rate > diameter, whereas, for H2S, it was reaction temperature > oxygen content > impregnant concentration > parch temperature > diameter > flow rate. Following were the optimal experimental parameters for both PH3 and H2S: reaction temperature, 95°C; impregnant concentration (Cu2+), 0.25 mol/L; diameter of metallic modified activated carbon (MMAC), 3.5 mm; oxygen content, 1%; parch temperature, 300°C; and flow rate, 0.4 L/min. Regeneration of MMAC was effective for PH3 but not compelling for H2S. The activation energy and reaction orders were calculated, and the transmission process was evaluated to assess the characteristics of the dynamics of the adsorb-catalytic reaction. The reaction orders were -0.8 and -0.76 for PH3 and H2S and the average activation energies were 1247.6 and 134.4 J/mol for PH3 and H2S, respectively. The adsorb-catalytic reaction was fast, and decreasing transmission resistance can play a key role in improving the performance of MMAC.

We study the phase transition from Mott insulator (MI) to Bose glass (BG) of a disordered Bose-Hubbard model within the framework of Ginzburg-Landau effective action approach. By treating MI as unperturbed ground state and performing a systematic expansion with respect to tunneling matrix element, we extend such a field-theoretic method into the disordered lattice Bose systems. To the lowest order, a second order phase transition is confirmed to happen here and the corresponding phase boundary equation coincides with the previous mean-field approximation result. Keeping all the terms second order in hopping parameter, we obtain the beyond mean-field results of MI-BG phase boundary of 2D and 3D disordered Bose-Hubbard models. Our analytic predictions are in agreement with recent semianalytic results., 16 pages, 4 figures

The number of cycle matchings increases exponentially with the number of subscriptions and the maximum length of cycle matchings, which needs a large amount of space to store intermediate results. Approximate cycle matching aims to store only a small part of intermediate results and find cycle matchings as many as possible. The existing solution prunes the intermediate results by a threshold of probability of a subscription to be matched, where the discrete degree of probabilities is neglected. In this paper, we propose an approximate dynamic cycle matching algorithm based on intermediate results classification using extreme learning machine. We first introduce a method of incorporating probability information into feature vector, and then propose the approximate cycle algorithm. Further, we propose a dynamic classification strategy considering that the data distribution of subscriptions may change as time goes on. The proposed approximate cycle matching algorithm and the dynamic classification strategy are evaluated in a simulated environment. The results show that compared with the approximate cycle matching based on probability threshold, the approximate cycle matching based on ELM classification is faster, and the dynamic classification strategy is more efficient and convenient. ELM is more suitable for approximate dynamic cycle matching than SVM with regards to response time.

Mobile object index should support efficient update operations besides efficient query operations. In this paper, we consider the issue of the efficient updating of mobile object index. Based on a model for the mobile data, we introduce a method of incorporating statistical information of the regions covered by the mobile objects into feature vectors. We then propose a novel architecture of mobile object index, where R-tree is used to index the occupied regions instead of the mobile objects themselves and extreme learning machine (ELM) is used to classify the regions. Further, we describe several related algorithms and the update strategy based on the classification of the regions. The proposed strategy and algorithms are evaluated in a simulated environment. The experiments demonstrate that the proposed update strategy based on region classification using ELM can achieve higher performance with respect to I/O operations. Compared to the strategy without region classification, the proposed method can reduce the number of I/O operations more than 80%.

The integration of intelligent spore image sequence capture device is designed for capturing spores and then generates a series of images. Powdery mildew spore is an extremely harmful bacteria spore in agricultural crops. This paper mainly introduced a new method which could realize the automatic detection of the powdery mildew spores. The new method mainly included pre-processing, image segmentation, feature extraction and identification. Pre-processing included illumination compensation, graying, image enhancement. Image segmentation included binary, image smoothing. Finally identification used BP neural network method. Training pictures used 155 pictures and the correct rate was 95.5%. Testing took 89 pictures, and the correct rate was 63.6%. The result proved the validity and correctness of this method.

The V.29 fax demodulation principle is studied, the algorithms of carrier synchronization, inverse signal space mapping and the cancellation of redundant data are improved. The improved algorithm is also implemented. Test show that an ideal optimization effect is achieved.

Performance is a major issue in the acceptance of database, especially for the database holding massive data. It's natural to apply parallel technology to handle these large data sets. ShusseUo is an Object Database Management Systems (ODBMSs) and it provides persistent global object management on persistent Distributed Shared Virtual Memory (DSVM) distributed on Network Of Workstations (NOWs). This paper introduces the performance evaluation of ShusseUo using extended Sequoia 2000 benchmark. The goal is to test the scalability and speedup of ShusseUo while dealing with mass size of extended spatial benchmark data in parallel. Experiments show that good scalability and speedup can be gotten by ShusseUo.

This paper examines the effectiveness of a computer-based corpus approach to college English writing. The empirical study in this paper illustrates that the use of corpus does benefit college English writing but there are some problems in its application. Pedagogical implications are then provided to enhance the effective integration of corpus and college English Writing: 1) teachers and learners need to negotiate frequently during the whole process of corpus-based DDL; 2) corpus use in writing must adapt to the students’ needs and teaching environments; 3) the alternative use of corpus and dictionaries will enhance the efficiency of corpus-based learning of the students; 4) Integrating cooperative learning and DDL will promote college students’ writing greatly.

Funder: Royal Society under the Newton International Fellowship, The implementation of static artificial magnetic fields in ultracold atomic systems has become a powerful tool, e.g. for simulating quantum-Hall physics with charge-neutral atoms. Taking an interacting bosonic flux ladder as a minimal model, we investigate protocols for adiabatic state preparation via magnetic flux ramps. Considering the fact that it is actually the artificial vector potential (in the form of Peierls phases) that can be experimentally engineered in optical lattices, rather than the magnetic field, we find that the time required for adiabatic state preparation dramatically depends on which pattern of Peierls phases is used. This can be understood intuitively by noting that different patterns of time-dependent Peierls phases that all give rise to the same magnetic field ramp, generally lead to different artificial electric fields during the ramp. As an intriguing result, we find that an optimal choice allows for preparing the ground state almost instantaneously in the non-interacting system, which can be related to the concept of counterdiabatic driving. Remarkably, we find extremely short preparation times also in the strongly-interacting regime. Our findings open new possibilities for robust state preparation in atomic quantum simulators.