The newly developed bioaerosol single particle mass spectrometer (Bio-SPAMS) has been innovatively designed for its optical sizing system. The first laser beam in the previous single particle mass spectrometer was spl...
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The newly developed bioaerosol single particle mass spectrometer (Bio-SPAMS) has been innovatively designed for its optical sizing system. The first laser beam in the previous single particle mass spectrometer was split into near distance double beams, similar to the design of APS (Aerodynamic Particle Sizer) and SBS-LIBS (Single Beam Splitting-Laser Induced Breakdown Spectroscopy). All the particles focused by the aerodynamic lens can be sized and got number concentration statistic. However, due to the imperfect beam quality and the large scattering intensity of the large-sized particles, there may be some noise in the scattered signals, particle diameter measured by this sizing system was often larger than actual value if the same trigger threshold was set. In this study, when measuring PSL microspheres with diameters of 1.9, 3.1, and 4.9 mu m, the identification rates of the fixed threshold algorithm were only 75.25%, 55.26%, and 0.27%, respectively. To address such issue, we developed a dynamic threshold waveform recognition algorithm based on field programmable gate array (FPGA), which could process the photoelectric signals collected by a photomultiplier tube (PMT) in real time. The algorithm can dynamically adjust the trigger threshold of the collected scattered signals and accurately calculate the interval time between the near distance double beam. For PSL microspheres with diameters of 1.9, 3.1, and 4.9 mu m, the accuracy of the dynamic threshold algorithm increased by 19.09%, 25.72%, and 88.20%, respectively. This algorithm effectively solves the problem of particle sizing deviation, and improves the particle size measurement accuracy of the bioaerosol mass spectrometer in a wide particle size range from 0.3-6 mu m.
In the paper, the chemical ingredient of potash glasswork and baryta glasswork is known from the archaic Chinese glassworks. The class, ornamentation and pigment of glasswork are known both without and with rotting. T...
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In the paper, the chemical ingredient of potash glasswork and baryta glasswork is known from the archaic Chinese glassworks. The class, ornamentation and pigment of glasswork are known both without and with rotting. The chemical ingredient percentage before rotting is predicted. Thus, the chemical ingredient is subclassified. The relativity of the chemical ingredient between the different classes of glasswork is found.
BackgroundDifferences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. algorithm-assisted tools must be able to contend with this variability in order ...
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BackgroundDifferences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. algorithm-assisted tools must be able to contend with this variability in order to be applicable in clinical practice. In a previous study, a decision support algorithm was developed to assist in the diagnosis of Hirschsprung's disease. In the current study, we tested the robustness of this algorithm while assessing for pre-analytic factors which may affect its *** decision support algorithm was used on digital pathology slides obtained from four different medical centers (A-D) and scanned by three different scanner models (by Philips, Hamamatsu and 3DHISTECH). A total of 192 cases and 1782 slides were used in this study. RGB histograms were constructed to compare images from the various medical centers and scanner models and highlight the differences in color and *** algorithm was able to correctly identify ganglion cells in 99.2% of cases, from all medical centers (All scanned by the Philips slide scanner) as well as 95.5% and 100% of the slides scanned by the 3DHISTECH and Hamamatsu brand slide scanners, respectively. The total error rate for center D was lower than the other medical centers (3.9% vs 7.1%, 10.8% and 6% for centers A-C, respectively), the vast majority of errors being false positives (3.45% vs 0.45% false negatives). The other medical centers showed a higher rate of false negatives in relation to false positives (6.81% vs 0.29%, 9.8% vs 1.2% and 5.37% vs 0.63% for centers A-C, respectively). The total error rates for the Philips, Hamamatsu and 3DHISTECH brand scanners were 3.9%, 3.2% and 9.8%, respectively. RGB histograms demonstrated significant differences in pixel value distribution between the four medical centers, as well as between the 3DHISTECH brand scanner when compared to the Philips and Hamamatsu brand *** results reported in this paper suggest tha
Purpose: We developed an open-source, rule-based algorithm to automate cause of death coding for analyzing mortality in understudied populations, such as people experiencing homelessness, and dynamic public health cri...
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Purpose: We developed an open-source, rule-based algorithm to automate cause of death coding for analyzing mortality in understudied populations, such as people experiencing homelessness, and dynamic public health crises including overdoses and climate-related deaths. Methods: Death categories of immediate public health concern were selected and keyword lists representing each category were developed in consultation with a domain expert. A rule-based keyword matching algorithm was built to assign death records into the selected death categories. The algorithm was trained on death certificate data from five counties across the United States. A case study applying the algorithm to deaths among people experiencing homelessness in Clark County, NV from 2015 to 2018 (N = 646) tested the accuracy of the program against a manual coder. Results: There was strong agreement between the algorithm and the manual coder in the all-cause identification (kappa 0.905) and mutually exclusive sorting (kappa 0.853) methods. Our findings illustrate the algorithm's ability to accurately classify death certificates into useful categories. Conclusion: This open-source, customizable algorithm may be utilized by researchers, journalists, and others to conduct mortality analyses with publicly available death certificate data, bridging gaps in existing mortality tracking efforts.
Efficient and accurate insulator defect detection is essential for maintaining the safe and stable operation of transmission ***,the detection effectiveness is adversely impacted by complex and changeable environmenta...
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Efficient and accurate insulator defect detection is essential for maintaining the safe and stable operation of transmission ***,the detection effectiveness is adversely impacted by complex and changeable environmental backgrounds,particularly under extreme weather that elevates accident ***,this research proposes a high-precision intelligent strategy based on the synthetic weather algorithm and improved YOLOv7 for detecting insulator defects under extreme *** proposed meth-odology involves augmenting the dataset with synthetic rain,snow,and fog algorithm ***,the original dataset undergoes augmentation through affine and colour transformations to improve model's generalisation performance under complex power inspection *** achieve higher recognition accuracy in severe weather,an improved YOLOv7 algorithm for insulator defect detection is proposed,integrating focal loss with SIoU loss function and incorporating an optimised decoupled head *** results indicate that the synthetic weather algorithm processing significantly improves the insulator defect detection accuracy under extreme weather,increasing the mean average precision by 2.4%.Furthermore,the authors’improved YOLOv7 model achieves 91.8%for the mean average precision,outperforming the benchmark model by 2.3%.With a detection speed of 46.5 frames per second,the model meets the requirement of real-time detection of insulators and their defects during power inspection.
The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves(SLGWs).This effect presents both challenges and opport...
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The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves(SLGWs).This effect presents both challenges and opportunities for the detection and appli-cation of ***,investigating this wave effect requires computing a complete diffraction integral over each microlens in the *** is extremely time-consuming due to the large number of microlenses(10^(3)-10^(6)).Therefore,simply adding all the microlenses is ***,the complexity of the time delay surface makes the lens plane resolution a crucial factor in controlling numerical *** this paper,we propose a trapezoid approximation-based adaptive hierarchical tree algo-rithm to meet the challenges of calculation speed and *** find that this algorithm accelerates the calculation by four orders of magnitude compared to the simple adding method and is one order of magnitude faster than the fixed hierarchical tree algorithm proposed for electromagnetic *** importantly,our algorithm ensures controllable numerical errors,increasing confidence in the *** with our previous work(***.66,239511,2023),this paper addresses all numerical issues,including integral convergence,precision,and computational time1).Finally,we conducted a population study on the microlensing wave effect of SLGWs using this algorithm and found that the microlensing wave effect cannot be ignored,especially for Type II SLGWs(from saddle position of the time delay surface)due to their intrinsic geometric structures and their typical intersection with a denser microlensing ***,more than 33%(11%)of SLGWs have a mismatch larger than 1%(3%)compared to the unlensed ***,we found that the mismatch between signal pairs in a doubly imaged GW is generally larger than 10^(−3),and 61%(25%)of signal pairs have a mismatch larger than 1%(3%).Theref
Alveolar-pleural fistulas (APF) are a clinical entity that represents a diagnostic and therapeutic challenge. Objective: The objective of this work is to design a diagnostic algorithm for the anatomical detection of A...
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Alveolar-pleural fistulas (APF) are a clinical entity that represents a diagnostic and therapeutic challenge. Objective: The objective of this work is to design a diagnostic algorithm for the anatomical detection of APF in patients who are not candidates for surgical treatment. Method: Prospective non-randomized study of 47 patients. Diagnostic procedures were performed: (a) prior to bronchoscopy: computed axial tomography (CT) and implantation of electronic pleural drainage system (EPD) and (b) endoscopic: endobronchial occlusion (EO) by balloon, selective endobronchial oxygen insufflation (OI) (2 l) and selective bronchography (BS) (instillation of iodinated radiological contrast using continuous fluoroscopy). Results: The sample was predominantly male (81%). The diagnostic methods revealed: (a) Determination of the anatomical location of APF by CT in 15/46 patients (31.9% of sample), and variations in the pattern (intermittent or continuous air leak) and quantification after drug administration sedatives using EPD, (b) endoscopic: anatomical determination of APF was achieved in 57.1, 81 and 63.4% respectively using EO, OI and BS. The combination of the diagnostic tests allowed us to determine the anatomical location of the APF in 91.5% of the sample. No complications were recorded in 85.1% of cases. Conclusions: The diagnosis of APF by flexible bronchoscopy is a useful method, with an adequate safety and efficacy profile. The proposed diagnostic algorithm includes the use of EPD and performing a CT scan. Regarding endoscopic diagnosis: in case of continuous air leak, the first option is OE;and if the leak is intermittent, we recommend endobronchial OI, with BS as a secondary option (respective sensitivity 81% vs 63.4% and complications 8.1% vs 7.3%). (c) 2024 SEPAR. Published by Elsevier Espana, S.L.U. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)***,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complexity,resultin...
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Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)***,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complexity,resulting in slow convergence or high *** address this issue,a low-complexity Approximate Message Passing(AMP)detection algorithm with Deep Neural Network(DNN)(denoted as AMP-DNN)is investigated in this ***,an efficient AMP detection algorithm is derived by scalarizing the simplification of Belief Propagation(BP)***,by unfolding the obtained AMP detection algorithm,a DNN is specifically designed for the optimal performance *** the proposed AMP-DNN,the number of trainable parameters is only related to that of layers,regardless of modulation scheme,antenna number and matrix calculation,thus facilitating fast and stable training of the *** addition,the AMP-DNN can detect different channels under the same distribution with only one *** superior performance of the AMP-DNN is also verified by theoretical analysis and *** is found that the proposed algorithm enables the reduction of BER without signal prior information,especially in the spatially correlated channel,and has a lower computational complexity compared with existing state-of-the-art methods.
This letter presents a Rubik metamaterial with sextuple orbital angular momentum (OAM) capabilities. The design is based on a comprehensive algorithm that draws inspiration from the Rubik's cube. This metamaterial...
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This letter presents a Rubik metamaterial with sextuple orbital angular momentum (OAM) capabilities. The design is based on a comprehensive algorithm that draws inspiration from the Rubik's cube. This metamaterial can generate multiple phased vortex waves using only one model and is easily constructed from metallic blocks with varying heights. The performance of the metamaterial is verified at 18 GHz with a gain of over 30 dB. A faster verification process is achieved using an automated program based on macroscript for height-adjusted Rubik metamaterials, which is more efficient than manual operations. By calculating the purity of the sextuple OAMs, it can be determined that the Rubik model is capable of generating multiple phased vortex wave beams as effectively as possible. This Rubik metamaterial has potential applications in experimental and educational settings, particularly with the growing trend in three-dimensional printing.
The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as backg...
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The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as background and *** this study,an integrated cascade framework that synergizes detectors and trackers was introduced for the simultaneous identification of tomato leaf diseases and fruit *** applied an autonomous robot with smartphone camera to collect images for leaf disease and fruits in greenhouses.
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