Automatic Filtering Research Articles

Rapid Detection of Clenbuterol Residues in Pork Using Enhanced Raman Spectroscopy.

Clenbuterol (CB) is a synthetic β-receptor agonist which can be used to improve carcass leanness in swine, but its residues in pork also pose health risks. In this report, surface-enhanced Raman scattering (SERS) technology was used to achieve rapid detection and identification of clenbuterol hydrochloride (CB) residues. First, the effects of several different organic solvents on the extraction efficiency were compared, and it was found that clenbuterol in pork had a better enhancement effect using ethyl acetate as an extraction agent. Then, SERS signals of clenbuterol in different solvents were compared, and it was found that clenbuterol had a better enhancement effect in an aqueous solution. Therefore, water was chosen as the solvent for clenbuterol detection. Next, enhancement effect was compared using different concentration of sodium chloride solution as the aggregating compound. Finally, pork samples with different clenbuterol content (1, 3, 5, 7, 9, and 10 µg/g) were prepared for quantitative analysis. The SERS spectra of samples were collected with 0.5 mol/L of NaCl solution as aggregating compound and gold colloid as an enhanced substrate. Multiple scattering correction (MSC) and automatic Whittaker filter (AWF) were used for preprocessing, and the fluorescence background contained in the original Raman spectra was removed. A unary linear regression model was established between SERS intensity at 1472 cm-1 and clenbuterol content in pork samples. The model had a better linear relationship with a correlation coefficient R2 of 0.99 and a root mean square error of 0.263 µg/g. This method can be used for rapid screening of pork containing clenbuterol in the market.

Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram.

The electrohysterogram (EHG) is the uterine muscle electromyogram recorded at the abdominal surface of pregnant or non-pregnant woman. The maternal respiration electromyographic signal (MR-EMG) is one of the most relevant interferences present in an EHG. Alvarez (Alv) waves are components of the EHG that have been indicated as having the potential for preterm and term birth prediction. The MR-EMG component in the EHG represents an issue, regarding Alv wave application for pregnancy monitoring, for instance, in preterm birth prediction, a subject of great research interest. Therefore, the Alv waves denoising method should be designed to include the interference MR-EMG attenuation, without compromising the original waves. Adaptive filter properties make them suitable for this task. However, selecting the optimal adaptive filter and its parameters is an important task for the success of the filtering operation. In this work, an algorithm is presented for the automatic adaptive filter and parameter selection using synthetic data. The filter selection pool comprised sixteen candidates, from which, the Wiener, recursive least squares (RLS), householder recursive least squares (HRLS), and QR-decomposition recursive least squares (QRD-RLS) were the best performers. The optimized parameters were L = 2 (filter length) for all of them and λ = 1 (forgetting factor) for the last three. The developed optimization algorithm may be of interest to other applications. The optimized filters were applied to real data. The result was the attenuation of the MR-EMG in Alv waves power. For the Wiener filter, power reductions for quartile 1, median, and quartile 3 were found to be −16.74%, −20.32%, and −15.78%, respectively (p-value = 1.31 × 10−12).

High Efficiency Compound Vacuum Oil Gas Separation Technology Based on Integrated Oil Filter of Ultra-High Voltage Transformer

In order to improve the filtering effect of vacuum oil purifier, the author proposes the research and application of high-efficiency compound vacuum oil-gas separation technology based on electric ultra-high voltage transformer integrated oil purifier. The author studies under the condition of constant oil temperature and flow rate, the effect of vacuum degree on the filtering effect of transformer oil vacuum oil filter. Using the research results, a frequency conversion automatic vacuum oil filter is designed, which makes the processing process have the characteristics of simple operation, high degree of automation, and high work efficiency. The test results show that if the transformer oil processed by the variable frequency automatic vacuum oil purifier is new oil, its water content is less than 45 mg/kg and the gas content is less than 12%; when the breakdown voltage is greater than 25 kV, the transformer oil index can meet the following requirements after the equipment is filtered for one cycle: breakdown voltage ≥75 kV; water content ≤5 mg/kg; and gas content ≤0.1% (volume ratio). After one cycle (after 100 min), the variable frequency automatic (three-stage) vacuum oil filter can greatly shorten the time of transformer oil circulating and filtering. Conclusion. The designed frequency conversion automatic vacuum oil purifier is obviously better than other transformer oil vacuum oil purifiers.

Derivation of maximum permissive switching time for automatic welding filter based on retinal thermal and blue light exposure limits

Automatic welding filters are intended to protect the eyes of the welder from optical radiation generated by the welding process. Safety standards for automatic welding filters (AWFs) have been developed worldwide. However, switching time requirements have not been studied considering the exposure limits established by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) or the American Conference of Governmental Industrial Hygienists (ACGIH). The aim of this study is to derive the maximum permissive switching time based on ICNIRP guidelines for exposure to intense optical radiation. The single and cumulative exposures associated with retinal thermal and blue light hazards were assessed in the welding environment. The results show that the maximum switching time is inversely proportional to the exponential function of the shade number difference. The proposed maximum switching time, 1/2 to 1/10 smaller than the current ISO, is derived from the effective blue light radiance limits. In addition, an evaluation of the periodic short circuit welding indicates that AWFs do not transmit hazardous levels of radiation in the dark state.

Performance of disc, conventional and automatic screen filters under rainbow trout fish farm effluent for drip irrigation system.

This study aims to investigate the performance of disc, conventional screen, and automatic screen filters when rainbow trout fish effluent is used for irrigation. The experiments were performed in a fish farm, located in the north-west of Iran. The disc and conventional screen filters were tested at pressures of 150 and 300kPa, and the automatic screen filter at 200 and 300kPa. The filtration experiments continued until the backwashing was reached. The results showed that (1) the initial head loss of disc and conventional screen filters was 40kPa, while for the automatic screen filter was 5kPa. (2) In the disc filter, with increasing working pressure, the filtered volume significantly (P < 0.05) increased from 9.7 to 14.5 m3m-2 (10kPa)-1, but for conventional and automatic screen filters, it was constant at 5.5 and 7.0 m3m-2 (10kPa)-1, respectively, and all of them had significant (P < 0.05) differences. (3) In the disc filter, with increasing the working pressure, the filtered volume to reach backwashing significantly (P < 0.01) increased from 80.9 to 104.4 m3m-2, while in the conventional screen filter increased from 14.1 to 16.4 m3m-2. This volume at two working pressures was 29.5 m3m-2 for the automatic screen filter. These volumes were significantly different (P < 0.01) between filters. (4) The mass retention for the disc, conventional, and automatic screen filters were 28.88, 9.11, and 7.72gmin-1m-2, respectively, and tended to increase at lower working pressures. Based on this index, the difference in the performance of the filters was significant (P < 0.01). (5) Overall, the best performance was for the disc filter, and after that was the automatic screen filters, but the period of time to operate for the filters until backwashing time was less than half an hour, which is not applicable under farm conditions.

Short-time prediction of DNS queries using deep learning and pre-trained word embedding

Word embeddings are used in natural language processing to group semantically similarwords. In this paper, we create word embeddings for Internet Domain Names (DNS)from corpora of anonymized DNS queries from an Internet Service Provider. We use eachembedding as a layer of a recurrent neural network (RNN) that works as a LanguageModel for the DNS queries generated by the users. We use these RNNs to predict thenext DNS query in two different cases. A first case tries to predict the next domain queryfrom the DNS server’s point of view so the corpus is close to the original log data. Asecond case tries to predict the next domain queried by a user from the user’s point ofview. Here the corpus has larger preprocessing.We show that this procedure has good accuracy for the DNS server-side problem, butlow accuracy for the user-side problem. Moreover, we show that training the same RNNwithout using the pre-trained embedding takes more time and is substantially less accu-rate. These results have practical applications for the service’s latency reduction, cacheoptimization in recursive DNS servers, automatic filtering of inappropriate domains, anddetecting anomalies.

Washed preparation of faecal microbiota changes the transplantation related safety, quantitative method and delivery.

SummaryThe safety, quantitative method and delivery of faecal microbiota transplantation (FMT) vary a lot from different countries in practice. Recently, the improved methodology of FMT based on the automatic filtration, washing process and the related delivery was named as washed microbiota transplantation (WMT). First, this study aimed to describe the methodology development of FMT from manual to washing preparation from 2012 to 2021 in China Microbiota Transplantation System (CMTS), a centralized stool bank for providing a national non‐profit service. The secondary aim is to describe donor screenings, the correlation between faecal weight and treatment doses, incidence of adverse events and delivery decision. The retrospective analysis on the prospectively recorded data was performed. Results showed that the success rate of donor screening was 3.1% (32/1036). The incidence rate of fever decreased significantly from 19.4% (6/31) in manual FMT to 2.7% (24/902) in WMT in patients with ulcerative colitis (UC), which made UC a considerable disease model to reflect the quality control of faecal microbiota preparation. We defined one treatment unit as 10 cm3 microbiota precipitation (1.0 × 1013 bacteria) based on enriched microbiota instead of rough faecal weight. For delivering microbiota, colonic transendoscopic enteral tube is a promising way especially for multiple WMTs or frequent colonic administration of drugs combined with WMT. This study should help improve the better practice of FMT for helping more patients in the future.

Trainable segmentation for transmission electron microscope images of inorganic nanoparticles.

We present a trainable segmentation method implemented within the python package ParticleSpy. The method takes user labelled pixels, which are used to train a classifier and segment images of inorganic nanoparticles from transmission electron microscope images. This implementation is based on the trainable Waikato Environment for Knowledge Analysis (WEKA) segmentation, but is written in python, allowing a large degree of flexibility and meaning it can be easily expanded using other python packages. We find that trainable segmentation offers better accuracy than global or local thresholding methods and requires as few as 100 user-labelled pixels to produce an accurate segmentation. Trainable segmentation presents a balance of accuracy and training time between global/local thresholding and neural networks, when used on transmission electron microscope images of nanoparticles. We also quantitatively investigate the effectiveness of the components of trainable segmentation, its filter kernels and classifiers, in order to demonstrate the use cases for the different filter kernels in ParticleSpy and the most accurate classifiers for different data types. A set of filter kernels is identified that are effective in distinguishing particles from background but that retain dissimilar features. In terms of classifiers, we find that different classifiers perform optimally for different image contrast; specifically, a random forest classifier performs best for high-contrast ADF images, but that QDA and Gaussian Naïve Bayes classifiers perform better for low-contrast TEM images.

Topographic Surveying using Low-Cost Amateur Drones &amp; 4K Ultra-High-Definition Videos

These days, the science of photogrammetry is frequently used in a wide range of applications, including engineering geology, medication, security, navigation, and topographic surveying works. Drones have gradually become an effectual and frequent technique for obtaining a number of photogrammetric products, such as ortho-mosaics, Digital Elevation Model (DEM), and land detailed topographic maps. This paper investigates the possibility of employing low-cost amateur drones with 4K Ultra-High-Definition (UHD) video for topographic surveying works and creating DEM's. DJI Mavic 2 PRO drone with Hasselblad L1D-20C 20 MP camera has been used for covering an expected gas &amp; oil pipeline route in the South of Libya with length of nearly 15 km and width of 200 m. 60 well-distributed high-quality 3D ground points, divided as 30 Ground Control Points (GCP's) and 30 check points, have been used for more stable and robust photogrammetric processing and for reliable evaluation, respectively. The camera has been calibrated twice, before and after executing the flight mission for trustworthy Interior Orientation Elements (IOE's). The recorded video has been split into smaller videos based on the capturing time of the required frames, and the small videos have been extracted to individual UHD photos using Matlab image tools. Leica Photogrammetric Suite (LPS) software has been used for all processing steps, except the automatic filtration of the generated tie points, which has been carried out using self-developed Matlab algorithm for epipolar geometry and 2D transformation based filters. Results show that DEM's with quality of nearly 1.2 to 2 decimeter in plane and elevation, respectively can be obtained using DJI Mavic 2 PRO drone, 4K UHD video taken by Hasselblad L1D-20C 20 MP camera, pixel ground footprint of 8 cm, and flight height of 350 m. This level of accuracy is appropriate for many engineering applications, such as initial-planning projects stretched on huge areas, urban development plans, GIS data collection, inventory of earth works materials, and 3D modeling. The obtained quality of the generated DEM depends on the flight height and the camera quality, IOE's, and resolution. Tests show that using 4K UHD video for photogrammetric applications can provide UHD extracted frames, similar to that captured singly, especially with fit flight speed and camera settings, namely: ISO sensitivity, shatter speed, and aperture size. Also, using video facilitates the aerial photography process, overcoming the difficulties of determining the suitable capturing time and location of individual photos in site. The other advantage is the ability of taking alternative frames if the selected images are not suitable for photogrammetric works in terms of tilting and blurring. The opportunity of changing the overlapping rates across the route is another important advantage of using video, especially for curvy routes. Moreover, using different groups of overlapped images for the same route helps for creating different DEM's for the same area, resulting more precise and dense topographic surveying works.

Monovalent Antigen-Induced Aggregation (MAA) Biosensors Using Immunomagnetic Beads in Both Sample Separation and Signal Generation for Label-Free Detection of Enrofloxacin.

Exploring new functions of nanomaterials can help facilitate the development of biosensors for the detection of antibiotics. Herein, a new detection modality based on monovalent antigen-induced aggregation (MAA) of immunomagnetic beads (IMBs) was proposed for rapid and label-free detection of enrofloxacin (ENR), which endowed IMBs with the abilities of both sample separation and signal generation. In the presence of ENR, the initially well-dispersed IMBs were aggregated and the degree of aggregation was in a concentration-dependent manner. After exploring the mechanism underlying IMB aggregation and investigating the key parameters affecting it, a label-free biosensing platform was developed for rapid and sensitive detection of ENR. Based on the significant differences in the magnetic separation speed and size between the aggregated and well-dispersed IMBs, two methods were proposed for quantitatively determining ENR, i.e., measuring the turbidity of the IMB supernatant after magnetic separation for a given time and visualizing and calculating the grayscale value of the aggregated IMBs trapped on the surface of a nitrocellulose membrane. A three-dimensional (3D)-printed syringe was designed and fabricated for automatic filtration of IMBs. This immunosensor allowed for sensitive detection of ENR in less than 15 min without any labels. It exhibited a satisfactory limit of detection of 0.79 ng mL-1 and showed the feasibility for ENR detection of spiked chicken meat with recovery rates ranging from 74.8 to 98.3%. The MAA immunosensor can act as a promising tool to detect trace levels of ENR and has the potential to be applied to complex food samples.

Kajian Perbandingan Akurasi DTM Pengolahan Data Foto Udara Menggunakan Metode Otomatis Dan Semi-Otomatis Filtering

Advances in UAV technology produce various superior products that can be utilized for the development and analysis of natural dynamics. One of them is DTM which is a visual representation of the shape of the ground surface that is displayed in 3 dimensions. DTM is obtained from the results of DSM filtering, where all features above the ground are digitally removed using a certain method. To produce a good DTM, a good quality DSM is needed, therefore a Horizontal and Vertical accuracy analysis was carried out based on ASPRS 2015. In this study, two software with different data processing methods were used, namely automatic filtering and semi-automatic filtering from DSM to DTM. To determine the quality of DTM, spot-height data is used as a comparison which is considered to be the actual form in the field. From the series of data processing processes, DTM results were obtained which were then tested for accuracy utilizing statistical validation tests using the calculation of RMSEZ values and non-statistical validation tests (Visual) using the transverse profile method. The test results show that the DTM produced by the PCI Geomatica software with the semi-automatic filtering method has more accurate and precise quality than the DTM from the SAGA GIS software with the automatic filtering method with an elevation value of 1,249 m and RMSEz 3,542 m to the spot-height. Then the visualization of the DTM transverse profile produced by the PCI Geomatica software semi-automatic filtering method to the spot height also does not appear to experience a significant difference where the elevation at Point 1 is 0.5 m and Point 2 is 0.5 m.

Automatic weighting filter tuning for robust flight control law design

This article presents a practical framework for the co-design of weighting filter parameters and controller gains in the context of multi-objective/multi-model tuning of flight control laws. A non-smooth optimization-based procedure is proposed aiming to reduce the complexity of the control design process, evolving from a rather classical manual filter selection all the way to a fully automatic one. A normal acceleration Control Augmentation System (CAS), designed by making use of non-smooth optimization software, for the linearized dynamics of an agile autonomous aerospace vehicle is used as an illustrative example. Several performance indexes are compared in the context of the developed framework as well as against more classical tuning methods such as pole placement, demonstrating that the proposed approach may lead to improved results and potentially benefit the flight control engineer via an easier handling of conflicting design requirements, model uncertainty and application-tailored control structures.

МОДЕРНІЗАЦІЯ АСТРОНОМІЧНОГО КОМПЛЕКСУ СПОСТЕРЕЖНОЇ СТАНЦІЇ ЛІСНИКИ

The Lisnyky observation station (international code 585) is actively used for observations of small bodies and for educational purpose. The station operates two telescopes AZT-8 (D=700 mm, F=2830 mm, D/F=1:4) and AZT-14 (D=480 mm, F=7715 mm, D/F=1:16). They have an outdated design and need to be modernized to meet the modern requirements of observational astronomy. The world practice of modernizing optical telescopes is reduced, as a rule, to installing new modern light receivers, changing the optical system, improving optical characteristics by aluminizing mirrors. Light receivers are now CCD image sensors, the use of which allows you to significantly increase the penetrating power (to observe fainter objects) and the temporal and spatial resolution of telescopes. Modern light receivers are equipped with automatic filter units with various sets of astronomical filters. Different sets of light receivers are used for different tasks of observational astronomy. The concept of modernization of the observation complex based on the AZT-14 and AZT-8 telescopes was developed according to these modern requirements. A new Moravian C4-16000ES CMOS camera (4096 × 4096 pixels, 9 × 9 μm) with a UBVRI light filter unit of the Johnson-Cousins photometric system was installed at the main focus of the AZT-8 telescope in 2021. In this version, the telescope is used to monitor small bodies and search for new comets and asteroids, photometric and positional observations of comets, observations of active galactic nuclei. An optical reducer (4.5 times reduction focal length) with a block of broadband light filters BVRI light filters was developed and manufactured for the AZT-14 telescope in order to increase the field of view on the CCD array, reduce the size of star images and increase the light power of the telescope. A new block of 8 comet narrowband filters, which is used with the Apogee Alta U47 CCD camera, was designed and manufactured for observations of comets. An electronic control system, which includes the following main electronic components: a light filter position sensor board, an electronic board, a stable frequency generator, a stepper motor driver, a controller for controlling all electronic components and for communication with a personal computer, was developed and manufactured for control the unit.

Dose reduction potential in diagnostic single energy CT through patient-specific prefilters and a wider range of tube voltages.

Various studies have demonstrated that additional prefilters and/or reduced tube voltages have the potential to significantly increase the contrast-to-noise ratios at unit dose (CNRDs) and thereby to significantly reduce patient dose in clinical CT. An exhaustive analysis, accounting for a wide range of filter thicknesses and a wide range of tube voltages extending beyond the 70 to 150kV range of today's CT systems, including their specific choice depending on the patient size, is, however, missing. Therefore, this work analyzes the dose reduction potential for patient-specific selectable prefilters combined with a wider range of tube voltages. We do so for soft tissue and iodine contrast in single energy CT. The findings may be helpful to guide further developments of x-ray tubes and automatic filter changers. CT acquisitions were simulated for different patient sizes (semianthropomorphic phantoms for child, adult, and obese patients), tube voltages (35-150kV), prefilter materials (tin and copper), and prefilter thicknesses (up to 5mm). For each acquisition soft tissue and iodine CNRDs were determined. Dose was calculated using Monte Carlo simulations of a computed tomography dose index (CTDI) phantom. CNRD values of acquisitions with different parameters were used to evaluate dosereduction. Dose reduction through patient-specific prefilters depends on patient size and available tube current among others. With an available tube current time product of 1000mAs dose reductions of 17% for the child, 32% for the adult and 29% for the obese phantom were achieved for soft tissue contrast. For iodine contrast dose reductions were 57%, 49%, and 39% for child, adult, and obese phantoms, respectively. Here, a tube voltage range extended to lower kV isimportant. Substantial dose reduction can be achieved by utilizing patient-specific prefilters. Tube voltages lower than 70kV are beneficial for dose reduction with iodine contrast, especially for small patients. The optimal implementation of patient-specific prefilters benefits from higher tube power. Tin prefilters should be available in 0.1mm steps or lower, copper prefilter in 0.3mm steps or lower. At least 10 different prefilter thicknesses should be used to cover the dose optima of all investigated patient sizes and contrast mechanisms. In many cases it would be advantageous to adapt the prefilter thickness rather than the tube current to the patient size, that is, to always use the maximum available tube current and to control the exposure by adjusting the thickness of the prefilter.

Comparing automatic baseflow separation filters on three watersheds in the urbanised area of East Java, Indonesia

Comparing automatic baseflow separation filters on three watersheds in the urbanised area of East Java, Indonesia

UAV based accurate displacement monitoring through automatic filtering out its camera's translations and rotations

In this paper, three translations and three rotations of the unmanned aerial vehicle (UAV) were derived through the suggested Normalized Cross Correlation (NCC) based template matching computer vision method and their effect on the monitored structural displacement is analyzed. The NCC-based template matching is used to obtain the vibration of UAVs by tracing far-field background points at the recorded images. The images captured at any general orientations are rotated back to their original positions which could detect errors in the monitored displacement induced by the rotation angles. A fast NCC-based template matching method was also proposed in this paper, which could accelerate the original NCC-based template matching method significantly and reaches the same level accuracy as that of the original NCC-based template matching method. In order to verify the concept, a series of experiments were performed on a Multipurpose Testing System (MTS) machine with amplitudes of 10 mm, 5 mm, and 2.5 mm and frequencies of 2 Hz, 1 Hz and 0.5 Hz, respectively, at the same time a UAV and a fixed camera were used to record the motions of the MTS piston. The derived displacements through the UAV and the fixed camera are compared with the true motions of the MTS machine. Excellent precision and consistence were obtained for the UAV monitored displacement, the MTS piston motion, and the fixed camera derived displacement. Comparing to the case of the fixed camera, scales and rotation angles of the UAV are critical and largely affect the accuracy of monitored displacements. A field experiment was conducted to test the proposed method in a windy environment. Excellent agreement was found between the monitored displacement obtained by the UAV and that derived from the fixed camera.

Plasmon-enabled spectrally narrow ultraviolet luminescence device using Pt nanoparticles covered one microwire-based heterojunction.

Owing to great luminescent monochromaticity, high stability, and independent of automatic color filter, low dimensional ultraviolet light-emitting diodes (LEDs) via the hyperpure narrow band have attracted considerable interest for fabricating miniatured display equipments, solid state lighting sources, and other ultraviolet photoelectrical devices. In this study, a near-ultraviolet LED composed of one Ga-doped ZnO microwire (ZnO:Ga MW) and p-GaN layer was fabricated. The diode can exhibit bright electroluminescence (EL) peaking at 400.0 nm, with a line width of approximately 35 nm. Interestingly, by introducing platinum nanoparticles (PtNPs), we achieved an ultraviolet plasmonic response; an improved EL, including significantly enhanced light output; an observed blueshift of main EL peaks of 377.0 nm; and a reduction of line width narrowing to 10 nm. Working as a powerful scalpel, the decoration of PtNPs can be employed to tailor the spectral line profiles of the ultraviolet EL performances. Also, a rational physical model was built up, which could help us study the carrier transportation, recombination of electrons and holes, and dynamic procedure of luminescence. This method offers a simple and feasible way, without complicated fabricating technology such as an added insulating layer or core shell structure, to realize hyperpure ultraviolet LED. Therefore, the proposed engineering of energy band alignment by introducing PtNPs can be employed to build up high performance, high spectral purity luminescent devices in the short wavelengths.

Combining direct urinary injection with automated filtration and nanoflow LC-MS for the confirmatory analysis of doping-relevant small peptide hormones

Nano-liquid chromatography (nanoLC) has proven itself as a powerful tool and its scope entails various applications in (bio)analytical fields. Operation at low (nL/min) flow rates in combination with reduced inner dimensions (ID < 100 µm), leads to significantly enhanced sensitivity when coupled with electrospray ionization-mass spectrometry (ESI-MS). Challenges that remain for the routine implementation of such miniaturized setups are related to clogging of the system and robustness in general, and thus the application of tedious sample preparation steps. To improve ruggedness, a filter placed upstream in the LC prevents particles from entering and clogging the system. This so-called online automatic filtration and filter back-flush (AFFL) system was combined with nanoLC and the direct injection principle for the sensitive confirmatory analysis of fifty different doping-relevant peptides in urine.The presented assay was fully validated for routine purposes according to selectivity and matrix interference, limit of identification (LOI), carryover, matrix effect, sample extract stability, analysis of educational external quality assessment (EQAS) samples, robustness of the online AFFL-setup and retention time stability. It was also fully compliant with the most recent minimum required performance levels (MRPL) and chromatographic/mass spectrometric identification criteria (IDCR), as imposed by the World Anti-Doping Agency (WADA).In the absence of labor-intensive sample preparation, the application of AFFL allowed for the injection of diluted urine samples without any noticeable pressure buildup in the nanoLC system. Contrary to earlier observations by our group and others, the addition of dimethylsulfoxide (DMSO) to the mobile phase did not enhance sensitivity in the presented nanoflow setup, yet was beneficial to reduce carry over. Although the robustness of the presented setup was evaluated only for the analysis of diluted urine samples, it is entirely conceivable that routine applications employing other matrices and currently running on analytical scale LC instruments could be transferred to micro/nanoLC scale systems to reach lower detection limits.

Data synthesis using deep feature enhanced generative adversarial networks for rolling bearing imbalanced fault diagnosis

Rolling bearing fault diagnosis is of great significance to the stable operation of rotating machinery systems. However, the fault data collected in practical engineering is seriously imbalanced, which degrades the diagnosis performance. In this paper, a novel data synthesis method called deep feature enhanced generative adversarial network is proposed to improve the performance of imbalanced fault diagnosis. Firstly, to avoid the mode collapse phenomenon and improve the stability of the generative adversarial networks, a pull-away function is integrated to design a new objective function of the generator. Secondly, a self-attention module is utilized in the networks to enhance the deep features of real signals, thereby the quality of synthesized data is improved. Finally, an automatic data filter is established to timely ensure the accuracy and diversity of synthesized samples. Experiments are implemented on two rolling bearing datasets. The results indicate that the proposed method outperforms other intelligent methods and shows great potential in imbalanced fault diagnosis.

A Novel Feature Extraction Method for the Condition Monitoring of Bearings

This paper presents an innovative approach to the extraction of an indicator for the monitoring of bearing degradation. This approach is based on the principles of the empirical mode decomposition (EMD) and the Hilbert transform (HT). The proposed approach extracts the temporal components of oscillating vibration signals called intrinsic mode functions (IMFs). These components are classified locally from the highest frequencies to the lowest frequencies. By selecting the appropriate components, it is possible to construct a bank of self-adaptive and automatic filters. Combined with the HT, the EMD allows an estimate of the instantaneous frequency of each IMF. A health indicator called the Hilbert marginal spectrum density is then extracted in order to detect and diagnose the degradation of bearings. This approach was validated on two test benches with variable speeds and loads. The obtained results demonstrated the effectiveness of this approach for the monitoring of ball and roller bearings.