Acoustic diagnostics of femtosecond laser filamentation

The promising application of femtosecond laser filamentation in atmospheric remote sensing brings imperative demand for diagnosing the spatiotemporal dynamics of filamentation. Acoustic emission (AE) during filamentation opens a door to give the insight into the dynamic evolution of filaments in air. In particular, the frequency features of the acoustic emission provide relevant information on the conversion of laser energy to acoustic energy. Here, the acoustic emission of femtosecond laser filament manipulated by energy and the focal lengths was measured quantitatively by a broadband microphone, and the acoustic parameters were compared and analyzed. Our results showed that the acoustic power presents a squared dependence on the laser energy and the bandwidth of the acoustic spectrum showed a significant positive correlation with laser energy deposition. It was found that the spectrum of the acoustic pulse emitted from the middle of the filament has a larger bandwidth compared to those emitted from the ends of the filament and the spectrum of the acoustic pulse is also an indicator of the filament intensity distribution. These findings are helpful for studying the plasma filament properties and complex dynamic processes through acoustic parameters and allow the optimization of remote applications.Comment: 8 pages,5 figure

Femtosecond Laser Filamentation in Atmospheric Turbulence

The effects of turbulence intensity and turbulence region on the distribution of femtosecond laser filaments are experimentally elaborated. Through the ultrasonic signals emitted by the filaments, and it is observed that increasing turbulence intensity and expanding turbulence active region cause an increase in the start position of the filament, and a decrease in filament length, which can be well explained by the theoretical calculation. It is also observed that the random perturbation of the air refractive index caused by atmospheric turbulence expanded the spot size of the filament. Additionally, when turbulence intensity reaches , multiple filaments are formed. Furthermore, the standard deviation of the transverse displacement of filament is found to be proportional to the square root of turbulent structure constant under the experimental turbulence parameters in this paper. These results contribute to the study of femtosecond laser propagation mechanisms in complex atmospheric turbulence conditionsComment: 9 pages, 4 figure

Chemical probing of thiotetronate bio-assembly

Chemical ‘chain termination’ probes were utilised for the investigation of thiotetronate antibiotic biosynthesis in the filamentous bacteria Lentzea sp. and Streptomyces thiolactonus NRRL 15439. The use of these tools led to the capture of biosynthetic intermediates involved in the thiotetronate polyketide backbone assembly, providing first insights into substrate specificity and in vivo intermediate processing by unusual iterative synthases

Coupled air lasing gain and Mie scattering loss: aerosol effect in filament-induced plasma spectroscopy

Femtosecond laser filament-induced plasma spectroscopy (FIPS) demonstrates great potentials in the remote sensing for identifying atmospheric pollutant molecules. Due to the widespread aerosols in atmosphere, the remote detection based on FIPS would be affected from both the excitation and the propagation of fingerprint fluorescence, which still remain elusive. Here the physical model of filament-induced aerosol fluorescence is established to reveal the combined effect of Mie scattering and amplification spontaneous emission, which is then proved by the experimental results, the dependence of the backward fluorescence on the interaction length between filament and aerosols. These findings provide an insight into the complicated aerosol effect in the overall physical process of FIPS including propagation, excitation and emission, paving the way to its practical application in atmospheric remote sensing.Comment: 7 pages, 4 figure

Investigation of Focusing Properties on Astigmatic Gaussian Beams in Nonlinear Medium

Ultra-short laser filamentation has been intensively studied due to its unique optical properties for applications in the field of remote sensing and detection. Although significant progress has been made, the quality of the laser beam still suffers from various optical aberrations during long-range transmission. Astigmatism is a typical off-axis aberration that is often encountered in the off-axis optical systems. An effective method needs to be proposed to suppress the astigmatism of the beam during filamentation. Herein, we numerically investigated the impact of the nonlinear effects on the focusing properties of the astigmatic Gaussian beams in air and obtained similar results in the experiment. As the single pulse energy increases, the maximum on-axis intensity gradually shifted from the sagittal focus to the tangential focus and the foci moved forward simultaneously. Moreover, the astigmatism could be suppressed effectively with the enhancement of the nonlinear effects, that is, the astigmatic difference and the degree of beam distortion were both reduced. Through this approach, the acoustic intensity of the filament (located at the tangential focal point) increased by a factor of 22.8. Our work paves a solid step toward the practical applications of the astigmatism beam as the nonlinear lidar

Phishing page detection via learning classifiers from page layout feature

Abstract The web technology has become the cornerstone of a wide range of platforms, such as mobile services and smart Internet-of-things (IoT) systems. In such platforms, users’ data are aggregated to a cloud-based platform, where web applications are used as a key interface to access and configure user data. Securing the web interface requires solutions to deal with threats from both technical vulnerabilities and social factors. Phishing attacks are one of the most commonly exploited vectors in social engineering attacks. The attackers use web pages visually mimicking legitimate web sites, such as banking and government services, to collect users’ sensitive information. Existing phishing defense mechanisms based on URLs or page contents are often evaded by attackers. Recent research has demonstrated that visual layout similarity can be used as a robust basis to detect phishing attacks. In particular, features extracted from CSS layout files can be used to measure page similarity. However, it needs human expertise in specifying how to measure page similarity based on such features. In this paper, we aim to enable automated page-layout-based phishing detection techniques using machine learning techniques. We propose a learning-based aggregation analysis mechanism to decide page layout similarity, which is used to detect phishing pages. We prototype our solution and evaluate four popular machine learning classifiers on their accuracy and the factors affecting their results

Identifying Dike-Pond System Using an Improved Cascade R-CNN Model and High-Resolution Satellite Images

The dike-pond system (DPS) is the integration of a natural or man-made pond and crop cultivation on dikes, widely distributed in the Pearl River Delta and Jianghan plain in China. It plays a key role in preserving biodiversity, enhancing the nutrient cycle, and increasing crop production. However, DPS is rarely mapped at a large scale with satellite data, due to the limitations in the training dataset and traditional classification methods. This study improved the deep learning algorithm Cascade Region Convolutional Neural Network (Cascade R-CNN) algorithm to detect the DPS in Qianjiang City using high-resolution satellite data. In the proposed mCascade R-CNN, the regular convolution layer in the backbone was modified into the deformable convolutional layer, which was more suitable for learning the features of DPS with variable shapes and orientations. The mCascade R-CNN yielded the most accurate detection of DPS, with an average precision (AP) value that was 2.71% higher than Cascade R-CNN and 11.84% higher than You Look Only Once-v4 (YOLOv4). The area of oilseed rape growing on the dikes accounted for 3.42% of the total oilseed rape planting area. This study demonstrates the potential of the deep leaning methods combined with high-resolution satellite images in detecting integrated agriculture systems

High performance TadA-8e derived cytosine and dual base editors with undetectable off-target effects in plants

Abstract Cytosine base editors (CBEs) and adenine base editors (ABEs) enable precise C-to-T and A-to-G edits. Recently, ABE8e, derived from TadA-8e, enhances A-to-G edits in mammalian cells and plants. Interestingly, TadA-8e can also be evolved to confer C-to-T editing. This study compares engineered CBEs derived from TadA-8e in rice and tomato cells, identifying TadCBEa, TadCBEd, and TadCBEd_V106W as efficient CBEs with high purity and a narrow editing window. A dual base editor, TadDE, promotes simultaneous C-to-T and A-to-G editing. Multiplexed base editing with TadCBEa and TadDE is demonstrated in transgenic rice, with no off-target effects detected by whole genome and transcriptome sequencing, indicating high specificity. Finally, two crop engineering applications using TadDE are shown: introducing herbicide resistance alleles in OsALS and creating synonymous mutations in OsSPL14 to resist OsMIR156-mediated degradation. Together, this study presents TadA-8e derived CBEs and a dual base editor as valuable additions to the plant editing toolbox

Upgrading the school entry vaccination record check strategy to improve varicella vaccination coverage: results from a quasi-experiment study

Background The school entry vaccination record check strategy (SECS) is an appropriate opportunity to recommend vaccines for students to improve vaccination coverage (VC). However, it is only utilized for providing necessary catch-up vaccination for students who are missing the Expanded Program on Immunization (EPI) vaccines in China. We aimed to address that gap and quantify the relationship between the SECS policy and the increase of coverage in varicella vaccine (VarV). Methods We employed a pretest and posttest quasi-experimental design to examine the effect of the upgraded SECS policy on the change of VarV coverage in newly enrolled students in Lu’an, 2019–2020. Results Eight hundred participants were randomly divided into the control group (C group, 31.8%), the telephone-based intervention group (T group, 31.2%), and the written notification intervention group (W group, 37.0%). Totally, 84 students received VarV during the study period, with a VC of 10.5%. The possibility of vaccination in the T group (RR = 4.9, 95% CI:2.2–10.9) and W group (RR = 5.2, 95% CI:2.4–11.5) was significantly higher than that in the C group (p< .001). Conclusions Our study demonstrates that the upgraded SECS produce a positive effect on improving the VC of VarV. This nudge strategy may decrease varicella outbreaks in schools in China, especially in provinces where VarV is not introduced into EPI

Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage

Abstract Background Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrhage (ICH). Cerebral small vessel disease (CSVD) complicates clinical manifestations of stroke. In this study, we redefined the CSVD burden score and incorporated it into a novel radiological-clinical prediction model for SAP. Materials and methods A total of 1278 patients admitted to a tertiary hospital between 1 January 2010 and 31 December 2019 were included. The participants were divided into training and testing groups using fivefold cross-validation method. Four models, two traditional statistical models (logistic regression and ISAN) and two machine learning models (random forest and support vector machine), were established and evaluated. The outcomes and baseline characteristics were compared between the SAP and non-SAP groups. Results Among the of 1278 patients, 281(22.0%) developed SAP after their first ICH. Multivariate analysis revealed that the logistic regression (LR) model was superior in predicting SAP in both the training and testing groups. Independent predictors of SAP after ICH included total CSVD burden score (OR, 1.29; 95% CI, 1.03–1.54), haematoma extension into ventricle (OR, 2.28; 95% CI, 1.87–3.31), haematoma with multilobar involvement (OR, 2.14; 95% CI, 1.44–3.18), transpharyngeal intubation operation (OR, 3.89; 95% CI, 2.7–5.62), admission NIHSS score ≥ 10 (OR, 2.06; 95% CI, 1.42–3.01), male sex (OR, 1.69; 95% CI, 1.16–2.52), and age ≥ 67 (OR, 2.24; 95% CI, 1.56–3.22). The patients in the SAP group had worse outcomes than those in the non-SAP group. Conclusion This study established a clinically combined imaging model for predicting stroke-associated pneumonia and demonstrated superior performance compared with the existing ISAN model. Given the poor outcomes observed in patients with SAP, the use of individualised predictive nomograms is vital in clinical practice