Multiwavelength Transmission Research Articles

Rapid identification of bacteria in water by multi-wavelength transmittance spectroscopy and the artificial neural network

Background: Multi-wavelength transmittance spectroscopy, in combination with the artificial neural network, has been a novel tool used to identify and classify microorganisms in recent years.Methods: In our work, the transmittance spectra in the region from 200 to 900 nm for four bacterial species of interest, Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), Klebsiella pneumoniae (K.pneumoniae), and Salmonella typhimurium (S. typhi), were recorded using an ultraviolet–visible spectrophotometer. Considering too much redundant data on the full-wave band spectra, the characteristic wavelength variables were selected using the competitive adaptive reweighting sampling (CARS) algorithm. Spectra of the initial training set of these targeted microorganisms were used to create identification models representing the spectral variability of each species using four kinds of neural networks, namely, backpropagation (BP), radial basis function network (RBF), generalized regression neural network (GRNN), and probabilistic neural network (PNN).Results: The blinded isolate spectra of targeted species were identified using the four identification models given above. Compared to fullband modeling, after using CARS to screen the wavelength variables, four identification models are established for the 35 preferred characteristic wavelengths, and the prediction performance of the four models is notably improved. Among them, the CARS–PNN model is the best, and the identification rates of all targeted bacteria were achieved with 100% accuracy; the calculation time is just approximately 0.04 s.Discussion: The use of CARS can effectively remove useless information from the spectra, reduce model complexity, and enhance model prediction performance. Multi-wavelength transmission spectroscopy, combined with the CARS–PNN method, can provide a new method for the rapid detection of bacteria in water and could be readily extended for bacterial microbiological detection in blood and food.

Rapid Determination of Escherichia coli Concentration in Water Using Multiwavelength Transmission Spectroscopy

Bacterial concentration is an important indicator to measure the degree of water pollution. Realizing rapid and accurate quantification of bacterial concentration in water is of great significance for ensuring water safety and maintaining human health. This paper proposes a method for rapid determination of bacterial concentration by multiwavelength transmission spectroscopy combined with partial least squares regression. Escherichia coli (E. coli) is selected because it is a common indicator microorganism for assessing water pollution status, and it is easy to handle. First, we measure the transmission spectra for E. coli suspensions in the region from 200 to 900 nm and analyze the differences in the spectral characteristics at different concentrations; subsequently, considering that the concentration is affected by the instrument linearity and other factors, the sensitivity, correlation, and detection ability of the spectra at different wavelengths with the change of concentration are analyzed, and the optimal characteristic band is selected according to its wavelength variation characteristics; finally, the determination of E. coli concentrations are completed by using the optimal characteristic band spectra combined with partial least squares regression. We calculate the bacterial concentration, compared with the plate counting, the maximum relative error is 4.500%, the average relative error is 0.677%, respectively, which is less than 5%, and their accuracy and stability are all better than those calculated by the single-wavelength method. This study provides a reference for the rapid and accurate detection of bacterial concentration in water.

Scanning of the Near-field Focused Beam by Changing Frequency

A new antenna array system is introduced which enables the movement of a near-field focused beam by change of frequency. The shift in the beam is achieved by using multi-wavelength transmission lines between successive elements of the array. At the designed frequency the beam is focused at the focal point. Due to the differences in the transmission line lengths feeding the antenna elements, a progressive phase change occurs between these elements. These phase differences between the elements cause a shift in the beam position. An 8×8 patch antenna array system was designed at 2.4 GHz on a microstrip to implement the proposed system. Two substrates were used: one for the patch antenna array and the other one for the feed network and transmission lines. A full-wave simulation model was used to analyze this design and demonstrate the movement of the beam. For this design, the focused beam is moved 310 mm by changing the frequency from 2.2025 GHz to 2.5750 GHz.

Color Recognition of Transparent Plastic Based on Multi-Wavelength Transmission Spectrum

Plastic recycling is the most effective way to solve plastic pollution. Color recognition of plastic is a key step in the plastic recycling process, which is very important for improving the utilization rate of waste plastic. At present, the manual recognition method is inefficient and cannot meet the requirements of large-scale production, while the existing color recognition based on machine vision has problems such as low recognition accuracy of similar colors, complicated algorithm and high system cost. According to the above problems, a color recognition method based on multi-wavelength transmission spectrum was proposed in this paper for the color recognition of colorless, light blue, light green and apple green transparent plastic. For each transparent plastic, the transmission spectra at 381 nm, 439 nm, 620 nm and white transmission light source were obtained, and the ratios of R, G and B wavebands of the transmission spectra were used to set up a color feature, which was then used for color recognition. A color recognition model was established based on the color features and naive Bayes model. The 10-fold cross-validation results showed that the recognition accuracy of the four colors of transparent plastic reached 100%.

A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology

Previously, we successfully realized the identification of a single species of bacteria based on the multi-wavelength transmission spectrum of bacteria. The current research is focused on realizing the spectral analysis of mixed bacteria. Principal component analysis-Monte Carlo (PCA-MC) model was developed for the implementation of spectral separation of mixed bacteria by obtaining the ratio of components. And, the separated spectrum was regarded as the model input of the neural network concentration inversion model to obtain the concentration of each bacteria in the mix. Mean relative errors in component analysis of mixing S.aureus with K.pneumoniae, mixing S.aureus with S.typhimurium twice, mixing K.pneumoniae with S.typhimurium are 3%, 2%, 3.9% and 6.1%, respectively. The coefficient of determination (R2) of validation set and test set are 0.9947 and 0.9954 in concentration inversion model. The results show that this method can quickly and accurately determine the component ratio and concentration information in the mixed bacteria. A new method was proposed to separate the spectrum of mixed bacteria effectively and measure its concentration quickly, which makes a big step forward in the detection and online monitoring of waterborne microbial contamination based on multi-wavelength transmission spectroscopy.

Simulation and experimental investigation of nonlinear effects in 5G fronthaul transmission system based on WDM-PON architecture

Wavelength-division multiplexing passive optical network (WDM-PON) is considered as a mainstream solution for 5G fronthaul transmission system to cope with the rapidly increasing bandwidth demand. In such a multi-wavelength system, nonlinear effects limit the achievable transmission distance and channel capacity. Therefore, in this paper, the impact of nonlinear effects on a multi-wavelength transmission system with 25 Gb/s/λ non-return-to-zero (NRZ) and a 200-GHz channel spacing over 25 km standard single-mode fiber (SSMF) is investigated through experiment and simulation. The effects of four-wavelength mixing (FWM) in O-band as well as cross-phase modulation (XPM) in C-band are both studied and discussed. Experiments are performed for 3- and 4-channel transmission cases, while 12-channel transmission is performed by simulation. The results show that in the O-band scenario, the FWM effect severely affects the performance of the channels near the zero-dispersion wavelength. Besides, the XPM products overlap the signal in the C-band, which also degrades the sensitivity. Based on these analyses, the nonlinear effects should be fully considered when planning wavelengths for 5G fronthaul transmission, including wavelength distribution and channel spacing selection.

Artificial neural networks combined multi-wavelength transmission spectrum feature extraction for sensitive identification of waterborne bacteria

Present research is focused on the rapid and accurate identification of bacterial species based on artificial neural networks combined with spectral data processing technology. The spectra of different bacterial species in the logarithmic growth phase were obtained. Model input features were extracted from the raw spectra using signal processing techniques, including normalization, principal component analysis (PCA) and area-based feature value extraction. The identification models based on artificial neural network of back propagation neural networks (BPNN), generalized regression neural networks (GRNN) and probabilistic neural networks (PNN) were developed using the extracted features in order to ascertain whether the different species of bacteria could be differentiated. The performance of developed models and its corresponding signal processing techniques is tested by the recognition accuracy of validation set and test set, and model error. The maximum recognition accuracy of normalized spectrum combined with BPNN was 95.5% (error: 10%, test accuracy: 100%). The total recognition accuracy of PCA-reduced features (200–400 nm) combined with GRNN resulted in 96.3%~96.8% (error: 3.3%~6.7%, test accuracy: 97.5%~100%). While the overall recognition accuracy of area-based features combined with GRNN reached 97.3% with test accuracy of 100% (model error: 5.0%). Choosing of model and signal processing techniques has a positive influence on improving classification accuracy, so as to make it possible to realize the rapid detection and online monitoring of waterborne microbial contamination.

HD 191939: Three Sub-Neptunes Transiting a Sun-like Star Only 54 pc Away

Abstract We present the discovery of three sub-Neptune-sized planets transiting the nearby and bright Sun-like star HD 191939 (TIC 269701147, TOI 1339), a K s = 7.18 mag G8 V dwarf at a distance of only 54 pc. We validate the planetary nature of the transit signals by combining 5 months of data from the Transiting Exoplanet Survey Satellite with follow-up ground-based photometry, archival optical images, radial velocities, and high angular resolution observations. The three sub-Neptunes have similar radii ( , , and ), and their orbits are consistent with a stable, circular, and coplanar architecture near mean-motion resonances of 1:3 and 3:4 (P b = 8.88, P c = 28.58, and P d = 38.35 days). The HD 191939 system is an excellent candidate for precise mass determinations of the planets with high-resolution spectroscopy due to the host star’s brightness and low chromospheric activity. Moreover, the system’s compact and near-resonant nature can provide an independent way to measure planetary masses via transit timing variations while also enabling dynamical and evolutionary studies. Finally, as a promising target for multiwavelength transmission spectroscopy of all three planets’ atmospheres, HD 191939 can offer valuable insight into multiple sub-Neptunes born from a protoplanetary disk that may have resembled that of the early Sun.

Recognition of Heterogeneous Edges in Multiwavelength Transmission Images Based on the Weighted Constraint Decision Method.

Multiwavelength light transmission imaging provides a possibility for early detection of breast cancer. However, due to strong scattering during the transmission process of breast tissue analysis, the transmitted image signal is weak and the image is blurred and this makes heterogeneous edge detection difficult. This paper proposes a method based on the weighted constraint decision (WCD) method to eliminate the erosion and checkerboard effects in image histogram equalization (HE) enhancement and to improve the recognition of heterogeneous edge. Multiwavelength transmission images of phantom are acquired on the designed experimental system and the mask image with high signal-to-noise ratio (SNR) is obtained by frame accumulation and an Otsu thresholding model. Then, during image enhancement the image is divided into low-gray-level (LGL) and high-gray-level (HGL) regions according to the distribution of light intensity in image. And the probability density distribution of gray level in the LGL and HGL regions are redefined respectively according to the WCD method. Finally, the reconstructed image is obtained based on the modified HE. The experimental results show that compared with traditional image enhancement methods, the WCD method proposed in this paper can greatly improve the contrast between heterogeneous region and normal region. Moreover, the correlation between the original image data is maintained to the greatest extent, so that the edge of the heterogeneity can be detected more accurately. In conclusion, the WCD method not only accurately identifies the edge of heterogeneity in multiwavelength transmission images, but it also could improve the clinical application of multiwavelength transmission images in the early detection of breast cancer.

Detection of heterogeneity on multi-spectral transmission image based on multiple types of pseudo-color maps

In transmission imaging, there are many difficulties in identifying heterogeneity on multi-spectral transmission images due to the strong absorption and scattering of biological tissues. This paper combines the multi-wavelength fusion information with the Faster-RCNN model to achieve the heterogeneous detection on the multi-spectral fusion pseudo-color map. Firstly, the original multi-spectral transmission images of phantom are collected on the self-built experimental platform. Then, the gray-scale level of image is improved by modulation and frame accumulation technique. Thereby, fusion pseudo-color maps (fusion pseudo-color maps of original RGB and gradient image) with high quality are obtained. And by comparing the running time, mean average precision (mAP) and root mean square error (RMSE) of Faster-RCNN model, the optimal iteration times and learning rate of model are determined. Finally, the fusion pseudo-color maps used for testing are input into the best Faster-RCNN model to realize the heterogeneous detection. The results show that the Faster-RCNN model established in this paper can effectively identify 2, 4 and 7 different types of heterogeneity on multi-spectral images, respectively. And the best mAP detection results for 2, 4 and 7 heterogeneities are 97.65%, 96.78% and 97.04%, respectively. In conclusion, this paper achieves the detection of heterogeneity on multi-spectral transmission images by fusing high-quality multi-wavelength transmission images and the Faster-RCNN network model, which will promote the clinical application of transmission imaging in early screening of breast cancer.

Simulation Platform for Analyzing Environmental Effects in Multi-Wavelength Transmission Systems in Matlab Simulink

Simulation Platform for Analyzing Environmental Effects in Multi-Wavelength Transmission Systems in Matlab Simulink

Expandable high-capacity wavelength division multiplex-over-optical code division multiple access millimeter wave radio-over-fiber system

The design and performance evaluation of a W-band wavelength division multiplexed-over-optical code division multiple access radio-over-fiber system are presented. The system’s performance introduces expansion in the number of channels and bit rate per channel for millimeter wave signals by optically encoding signals in a multiwavelength transmission system. The performance of the system is verified based on software simulation of three channels that carry six users’ encoded data. The achieved results are measured in bit-error-rate and eye-diagram figures. The obtained results are analyzed for each wavelength channels and each code families used. Bit error rates of 10 − 2 to 10 − 6 are obtained for channels operating at 10 Gb / s.

A Fusion Method in Frequency Domain for Multi-Wavelength Transmission Image

Multi-wavelength transmission imaging provides a possibility for early breast cancer detection. However, due to the strong scattering effect of light source in the transmission process of biological tissue, there exist many difficulties in the heterogeneous identification of multi-wavelength images. In this paper, a multi-wavelength images frequency fusion method based on regional variance significance and regional space energy weighting is proposed to improve the accuracy of heterogeneous detection. Firstly, the acquisition experiment of phantom multi-wavelength transmission images is designed. And R\G\B three-channel wavelength images are extracted from multi-wavelength images as an example to realize subsequent image fusion. Secondly, frame accumulation technique and second-order Butterworth filter are used to improve the signal-to-noise ratio of images and suppress the noise of images. Then, after homomorphic filtering, it is found that the same frequency domain of images is connected, which is not conducive to the recognition of heterogeneity in image. In order to break the connectivity of images in the same frequency domain and improve the accuracy of heterogeneous detection, the regional variance significance and the regional space energy weighting fusion strategies are used to reconstruct the low-frequency and high-frequency fusion images respectively. Finally, the heterogeneous detection results of the proposed image fusion method and the state-of-the-art methods in the multi-wavelength image are compared. The experimental results show that compared with the state-of-the-art image fusion methods, the fusion method proposed in this paper can identify the location of heterogeneous region more accurately and significantly improve the contrast between heterogeneous region and normal region in the fusion image. In conclusion, the fusion algorithm not only effectively realizes the recognition of heterogeneity in multi-wavelength images, but also promotes the potential application of multi-wavelength transmission image in early breast cancer detection.

水体细菌微生物多波长透射光谱定量分析归一化方法研究

水体细菌微生物多波长透射光谱定量分析归一化方法研究

基于多波长透射光谱的水体细菌生长阶段特征参数反演研究

基于多波长透射光谱的水体细菌生长阶段特征参数反演研究

(LBA-and-WRM)-based DBA scheme for multi-wavelength upstream transmission supporting 10 Gbps and 1 Gbps in MAN

Abstract DBA scheme based on Load balance algorithm (LBA) and wavelength recycle mechanism (WRM) for multi-wavelength upstream transmission is proposed in this paper. According to 1 Gbps and 10 Gbps line rates, ONUs are grouped into different VPONs. To facilitate wavelength management, resource pool is proposed to record wavelength state. To realize quantitative analysis, a mathematical model describing metro-access network (MAN) environment is presented. To 10G-EPON upstream, load balance algorithm is designed to ensure load distribution fairness for 10G-OLTs. To 1G-EPON upstream, wavelength recycle mechanism is designed to share remained wavelengths. Finally, the effectiveness of the proposed scheme is demonstrated by simulation and analysis.

Analytic Method on Characteristic Parameters of Bacteria in Water by Multiwavelength Transmission Spectroscopy

An analytic method together with the Mie scattering theory and Beer-Lambert law is proposed for the characteristic parameter determination of bacterial cells (Escherichia coli10389) from multiwavelength transmission spectroscopy measurements. We calculate the structural parameters ofE. colicells, and compared with the microscopy, the relative error of cell volume is 7.90%, the cell number is compared with those obtained by plate counting, the relative error is l.02%, and the nucleic content and protein content of singleE. colicells are consistent with the data reported elsewhere. The proposed method can obtain characteristic parameters of bacteria as an excellent candidate for the rapid detection and identification of bacteria in the water.

Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

Abstract Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.

Zeroth- and First-Order-Convertible Fiber Interleaving Filter

In this paper, we propose a zeroth- and first-order-convertible fiber interleaving filter that has a frequency-interleaving capability in the zeroth- or first-order multiwavelength transmission spectrum. The proposed interleaving filter is a kind of polarization-diversity-loop-based comb filter composed of a polarization beam splitter, three half-wave plates (HWPs), and two polarization-maintaining fiber (PMF) segments, each of which is located between two adjacent HWPs. The HWP inserted between two PMF segments enables the interleaving filter to operate in the zeroth- or first-order transmission mode by adjusting the relative angular difference between the principal axes of two PMF segments. With the orientation angles of the three HWPs set as specific angles, first-order flat-top and narrow-band transmission spectra with a channel spacing of ∼0.792 nm could be obtained and be interleaved by controlling only the HWP between the two PMF segments. In particular, at other specific angle sets of the three HWPs, the zeroth-order transmission spectrum with the same channel spacing could be obtained, and their multiwavelength channels could be interleaved by adjusting only the orientation angle of the intermediary HWP. That is, a first-order comb spectrum could be converted into a zeroth-order one with the same fringe period, and each one could be interleaved through the proper control of the three HWP angles.

Reagentless Bacterial Identification Using a Combination of Multiwavelength Transmission and Angular Scattering Spectroscopy

Optics based technologies are being advanced by many diagnostic companies around the globe. This resurgence is being driven by several factors including novel materials, enhanced computer power, nonlinear optics, and advances in algorithmic and statistical analysis. This study expands on a previous paper that evaluated the capability of a reagent-free optical profiling platform technology that used multiwavelength transmission spectroscopy to identify bacterial pathogens from pure culture. This study combines multiwavelength angular scattering with transmission based analysis into a single algorithm that will identify bacterial pathogens. Six predominant organisms,S. aureus, E. coli,K. pneumoniaeandP. aeruginosa,E. faecalis,and coagulase negativeStaphylococcus, were analyzed from a total of 753 clinical isolates received from three large community hospital systems. The bacterial identification method used for comparison in this study was the Vitek-2 (bioMerieux) which utilizes a biochemically based identification system. All of the clinical isolates received were blinded as to their identification until completion of the optical analysis. Sensitivities ranged from 87.7 to 94.6% with specificities ranging from 97.2 to 99.9% indicating that optical profiling is a powerful and exciting new technology that could be developed for the rapid identification of pathogens without the use of chemical reagents.