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The necrotrophic pathogen Sclerotinia sclerotiorum is one of the most damaging and economically important plant pathogens. Pydiflumetofen, which was developed by Syngenta Crop Protection, has already been registered in China for the management of Sclerotinia stem rot, which was caused by S. sclerotiorum in oilseed rape. In an attempt to preempt and forestall the development of resistance to this useful fungicide, the current study was initiated to investigate the potential mechanism of resistance in laboratory mutants. Five pydiflumetofen-resistant S. sclerotiorum mutants were successfully generated by repeated exposure to the fungicide under laboratory conditions. Although the mutants had greatly reduced sensitivity to pydiflumetofen, they were also found to have significantly (P < 0.05) reduced fitness, exhibiting reduced mycelial growth and sclerotia formation on potato dextrose agar medium. However, three of the four mutants had significantly (P < 0.05) increased pathogenicity on detached soybean leaves compared with their respective parental isolates, indicating a moderate to high level of fungicide resistance risk according to the criteria of the Fungicide Resistance Action Committee. Sequence analysis of four succinate dehydrogenase (Sdh) target genes identified several nucleotide changes in the sequences of the pydiflumetofen-resistant mutants, most of which were synonymous and caused no changes to the predicted amino acid sequences. However, all of the pydiflumetofen-resistant mutants had two amino acid point mutations (A11V and V162A) in their predicted SsSdhB sequence. No similar changes were found in the SsSdhA, SsSdhC, and SsSdhD genes of any of the mutants tested. In addition, there was a positive cross-resistance between pydiflumetofen and boscalid, and no cross-resistance between pydiflumetofen and other commonly used fungicides, including tebuconazole, fludioxonil, cyprodinil, dimethachlone, prochloraz, pyraclostrobin, fluazinam, procymidone, and carbendazim. These results indicate that pydiflumetofen has great potential as an alternative fungicide for the control of S. sclerotiorum, especially where resistance to other fungicides has already emerged. Mixing or alternate application with fludioxonil, prochloraz, and fluazinam could be used to limit the risk of resistance to pydiflumetofen.

Background: Recent years, PET/CT equipment has played an increasingly important role in the medical field, and its quality control and evaluation requirements have become more stringent. Correspondingly, the performance testing phantom used for PET/CT quality control needs to be upgraded and optimized to meet the requirement of equipment imaging quality testing. The commonly used NEMA IEC Body performance testing phantom has the defects that it cannot detect micro-lesion and cannot measure CT performance parameters. This article proposes a NIM PET/CT phantom capable of simultaneously testing the performance of PET and CT equipment, and evaluates its imaging quality.Methods: Compared with the NEMA IEC Body phantom, the PET performance testing module in the phantom has new balls with inner diameters of 4mm and 7mm. Combined with the CT performance testing module, it can be used for both PET and CT performance testing. The 28mm and 37mm balls are filled with pure water as a cold stove, and the remaining balls are filled with F-FDG solution as a hot stove. The activity concentration ratio of the hot ball to the background is 4:1. This study compares the imaging results of the NIM PET/CT phantom and the NEMA IEC Body phantom to verify its effectiveness; compares the imaging results of 3 different brands of PET/CT on the NIM phantom to verify that it is on different equipment The generalization ability of the system; apply PSF and TOF technology to the reconstruction algorithm and compare the improvement of the image quality; finally, the accuracy of the CT low-contrast module and the uniformity of the background are verified.Results: The imaging quality of the NIM PET/CT phantom and the NEMA IEC Body phantom is relatively consistent. The NIM phantom under different types of PET/CT scans can detect 7mm balls without affecting the imaging quality of other areas, which is better The device can detect 4mm small balls, which can clearly classify the ability of different devices to present images of small lesions; the integration of PSF technology into the reconstruction algorithm significantly improves the image resolution and hot bulb contrast, but the edges of the lesions are still blurred , TOF technology improves the detection limit of the equipment and improves the overall quality of the image. PSF&TOF technology combines the advantages of the two, significantly reducing image noise and strengthening image details, so that the image quality has been comprehensively improved; the measurement in the CT module The result is consistent with the true value, and the relative error is within ±5%. The CT value transition between the background and pure water area is smooth, and the background uniformity is good.Conclusion: NIM PET/CT Phantom and NEMA IEC Body phantom are comparability, and the former includes all the functions of the latter. In addition, the phantom can meet the testing requirement of different grades of PET/CT.

This study aimed to optimize the evaluation procedure of contrast to noise ratio (CNR) on low-contrast resolution (LCR) phantom images of computed tomography (CT). Axial CT images of phantom Catphan 600 which contained the low-contrast module CTP515 and the uniformity module CTP486 were acquired from five 64-slices spiral CT scanners with the same scanning parameters. Through conjoint analysis of images of CTP515 and CTP486, two steps of optimization were added to the evaluation procedure to get the optimized CNR results. Meanwhile, four experts were invited to perform the subjective evaluation of the same low-contrast images. With the method of normalization, results gained by optimized CNR and the experts' subjective evaluation were compared to investigate the consistency of the two evaluation methods. According to the comparison of the normalized values, the optimized CNR gained by the method of two-stage average could be used as basis to assist tester achieve similar result compared to that from experts' subjective evaluation.

Speckle is an especially relevant issue as far as self-mixing interferometry works onto diffusive targets and for large displacements sensing. This article proposed a new signal processing technique, based on three envelope extraction transition detection algorithm, to correctly extract and processes self-mixing signals corrupted by speckle. The algorithm also discriminates the direction of the target movement for different self-mixing regimes. The validity of the proposed method was demonstrated by means of simulated signals and confirmed by several experimental measurements with envelope variation of a decade in amplitude. The use of this technique effectively removes the need for optical/electro-mechanical component and strict sampling number determination.

With the vigorous development of renewable energy, large-scale wind power is connected to the power grid. Compared with conventional energy sources, wind power generation has the stochastic and intermittent characteristics, which brings great challenges to the safe and stable operation of power grids. Forecasting is essential for the rational, safe and effective use of wind power. Thus, the ability to predict wind power in a timely and accurate manner is particularly significant.The short-term prediction error of wind power is mainly caused by inherent stochastic factors and extrinsic stochastic factors. The inherent stochastic factor refers to the defect or imperfection of the prediction system itself. The external stochastic factor refers to the imperfect data input by the system or the error of the input data. Artificial neural network (ANN) algorithms are supposed to be with better performance to solve such problems. This paper reviews the development of wind power generation and the research status of wind power prediction technology. On this basis, a wind power prediction model of convolutional neural network (CNN) and genetic algorithm (GA) is constructed to predict the short-term wind power. The learning accuracy, the number of hidden nodes, and the training function are discussed. The selection of the optimal neural network and GA prediction model are presented. The simulation results show that the prediction accuracy and stability of the proposed prediction system are improved, compared with the BP neural network and CNN.

The accurate estimation of patient’s exposure to the radiofrequency (RF) electromagnetic field of magnetic resonance imaging (MRI) significantly depends on a precise individual anatomical model. In the study, we investigated the applicability of an efficient whole-body individual modelling method for the assessment of MRI RF exposure. The individual modelling method included a deformable human model and tissue simplification techniques. Besides its remarkable efficiency, this approach utilized only a low specific absorption rate (SAR) sequence or even no MRI scan to generate the whole-body individual model. Therefore, it substantially reduced the risk of RF exposure. The dosimetric difference of the individual modelling method was evaluated using the manually segmented human models. In addition, stochastic dosimetry using a surrogate model by polynomial chaos presented SAR variability due to body misalignment and tilt in the coil, which were frequently occurred in the practical scan. In conclusion, the dosimetric equivalence of the individual models was validated by both deterministic and stochastic dosimetry. The proposed individual modelling method allowed the physicians to quantify the patient-specific SAR while the statistical results enabled them to comprehensively weigh over the exposure risk and get the benefit of imaging enhancement by using the high-intensity scanners or the high-SAR sequences.

Supplemental Digital Content is available in the text, Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Diabetes mellitus is one of major of ill health in the world. One of the popular topics in biomedical optics applications is using the near infrared spectra for non-invasive blood glucose measurement. Nonetheless, the most researches of blood glucose concentration measurement focus on the diffuse reflection either in domestic or overseas, the research of transmission is rare. In this paper, by the transmission experiment setup of non-invasive blood glucose measurement in our lab, the experiments of glucose concentration in glucose aqueous solutions based on Lambert-Beer theory are discussed. First, the optimal waveband (1310nm) is chosen for the non-invasive blood glucose concentration measurement set-up. And then, the hardware system which including laser diode, photoelectric detector and data processing module of this experiment set-up has been designed and some relevant experiments about glucose measurement are carried out. Finally, the optimal finger position of hand for human blood glucose concentration measurement is chosen. In a word, after some transmission experiments on glucose sensing??we could conclude that near infrared 1310nm light is proper for glucose concentration sensing in glucose aqueous solution, the index finger of hand is proper as the non-invasive blood glucose measurement and the transmission experiment set-up could be used for human blood glucose concentration sensing experiment later.

Non-contact measurement has the characteristics of high speed and high efficiency, which fit the requirements of the measurement of engine blade. According to high-speed and efficient measurement in the condition of high precision, we design a point laser beam direction calibration method based on a standard ball by analysing the mathematical model. By experiment, it proves that the stability and accuracy can meet the requirements of blade measurement.

The different positions and angles of the optical sensor are calibrated before using the optical coordinate measuring system. In this paper, we analyze and optimize the common calibration process, reduce the unnecessary links, shorten the calibration time, and improve the efficiency of the optical coordinate measuring system by 50 percent.

In traditional acupuncture, reinforcement and reduction are conducted to stimulate the channel Qi by puncturing or heating the points with specific manners so as to regulate the functional activities of the internal organs. Reinforcement and reduction manners played an important role in clinical practice of traditional Chinese medicine, especially in disease curing. And the non-invasive nature of laser acupuncture has made lasers an attractive alternative in Medical Acupuncture at the last 25 years. The objective of this paper was to introduce the methods to implement reinforcement and reduction in laser acupuncture. According to reinforcement and reduction of traditional acupuncture and the theory of laser optics, lifting and thrusting of acupuncture, twisting and twirling of acupuncture and sparrow-pecking moxibustion are implemented.

The non-invasive nature of laser biostimulation has made lasers an attractive alternative in medical acupuncture at the last 25 years. To get much better effect of laser acupuncture, the objective of this work was to design and build a low cost portable laser acupuncture instrument which can implement reinforcement and reduction of traditional acupuncture. According to reinforcement and reduction of traditional acupuncture and the theory of laser optics, lifting and thrusting of acupuncture, and twisting and twirling of acupuncture are implemented. The laser source is 30 mW AlGalnP laser diode with an emission wavelength of 650 nm. The MSP430 microcontroller system is used as the control center of the device.

Cardiac Diseases are very harmful to the human health. The application of electrocardiogram (ECG) is essential for the clinical diagnosis of cardiac diseases. The use of computers for accurately and quickly cardiac disease diagnosis has been a subject fervently pursued by both internal and external researchers. Therefore, it is great significant to explore even more accurate and higher-speed automatic ECG analysis method. Support Vector Machine (SVM) is a novel powerful machine learning method based on statistical learning theory, which is powerful for the characterization of small sample (nonlinearity, high dimension and local minima). In this paper, Clinical diagnosis of cardiac disease based on SVM is proposed. There are two input patterns of samples: 8-lead ECG in series and in parallel. All experiments are implemented on Pentium 350 MHz with 512 MB RAM. Matlab 6.5 is employ to solve the quadratic programming. Comparison in two input patterns based on SVM, the result shows that SVM method in parallel is highly reliable and accurate. It will have great potential application in clinical diagnosis.

With the increasing performance of computer, the virtual instrument technology has greatly advanced over the years, and then virtual medical instrument technology becomes available. This paper presents the virtual medical instrument, and then as an example, an application of a signal acquisition, processing and analysis system using LabVIEW is also given.

Laser acupuncture is defined as the stimulation of traditional acupuncture points with low-intensity, non-thermal laser irradiation. It has been well applied in clinic since the 1970s; however, some traditional acupuncture manipulating methods still cannot be implemented in the design of this kind of instruments, such as lifting and thrusting manipulating method, and twisting and twirling manipulating method, which are the essential acupuncture method in traditional acupuncture. The objective of this work was to design and build a low cost portable laser acupuncture therapeutic instrument, which can implement the two essential acupuncture manipulating methods. Digital PID control theory is used to control the power of laser diode (LD), and to implement the lifting and thrusting manipulating method. Special optical system is designed to implement twisting and twirling manipulating method. M5P430 microcontroller system is used as the control centre of the instrument. The realization of lifting and thrusting manipulating method and twisting and twirling manipulating method are technological innovations in traditional acupuncture coming true in engineering.

To cure brain paralysis this paper has briefly summarized the rudimentary knowledge of the ultrasonic therapy, and briefly introduced the methods of dolphin ultrasonic therapy, through the research of the dolphin ultrasonic therapy, the ultrasonic frequency chart wave band which is more efficient to the therapy of brain paralysis is measured, and one method of simulated dolphin therapy mechanism is found. Finally, one of the ultrasonic therapy instruments against brain paralysis is developed.