Controlling the polarization of nitrogen ion lasing

Air lasing provides a promising technique to remotely produce coherent radiation in the atmosphere and attracts continuous attention. However, the polarization properties of N2+ lasing with seeding has not been understood since it was discovered ten years ago, in which the behaviors appear disordered and confusing. Here, we performed an experimental and theoretical investigation on the polarization properties of N2+ lasing and successfully revealed its underlying physical mechanism. We found that the optical gain is anisotropic owing to the permanent alignment of N2+ induced by the preferential ionization of the pump light. As a result, the polarization of N2+ lasing tends to align with that of the pump light after amplification, which becomes more pronounced with increasing amplification factor. Based on the permanent alignment of N2+, we built a theoretical model that analytically interpreted and numerically reproduced the experimental observations, which points out the key factors for controlling the polarization of N2+ lasing.Comment: 12 pages, 4 figure

Succinylation modification provides new insights for the treatment of immunocompromised individuals with drug-resistant Aspergillus fumigatus infection

Invasive Aspergillus fumigatus infection poses a serious threat to global human health, especially to immunocompromised individuals. Currently, triazole drugs are the most commonly used antifungals for aspergillosis. However, owing to the emergence of drug-resistant strains, the effect of triazole drugs is greatly restricted, resulting in a mortality rate as high as 80%. Succinylation, a novel post-translational modification, is attracting increasing interest, although its biological function in triazole resistance remains unclear. In this study, we initiated the screening of lysine succinylation in A. fumigatus. We discovered that some of the succinylation sites differed significantly among strains with unequal itraconazole (ITR) resistance. Bioinformatics analysis showed that the succinylated proteins are involved in a broad range of cellular functions with diverse subcellular localizations, the most notable of which is cell metabolism. Further antifungal sensitivity tests confirmed the synergistic fungicidal effects of dessuccinylase inhibitor nicotinamide (NAM) on ITR-resistant A. fumigatus. In vivo experiments revealed that treatment with NAM alone or in combination with ITR significantly increased the survival of neutropenic mice infected with A. fumigatus. In vitro experiments showed that NAM enhanced the killing effect of THP-1 macrophages on A. fumigatus conidia. Our results suggest that lysine succinylation plays an indispensable role in ITR resistance of A. fumigatus. Dessuccinylase inhibitor NAM alone or in combination with ITR exerted good effects against A. fumigatus infection in terms of synergistic fungicidal effect and enhancing macrophage killing effect. These results provide mechanistic insights that will aid in the treatment of ITR-resistant fungal infections

A flexible dual-mode pressure sensor with ultra-high sensitivity based on BTO@MWCNTs core-shell nanofibers

Wearable flexible sensors have developed rapidly in recent years because of their improved capacity to detect human motion in wide-ranging situations. In order to meet the requirements of flexibility and low detection limits, a new pressure sensor was fabricated based on electrospun barium titanate/multi-wall carbon nanotubes (BTO@MWCNTs) core-shell nanofibers coated with styrene-ethylene-butene-styrene block copolymer (SEBS). The sensor material (BTO@MWCNTs/SEBS) had a SEBS to BTO/MWCNTs mass ratio of 20:1 and exhibited an excellent piezoelectricity over a wide range of workable pressures from 1 to 50 kPa, higher output current of 56.37 nA and a superior piezoresistivity over a broad working range of 20 to 110 kPa in compression. The sensor also exhibited good durability and repeatability under different pressures and under long-term cyclic loading. These properties make the composite ideal for applications requiring monitoring subtle pressure changes (exhalation, pulse rate) and finger movements. The pressure sensor developed based on BTO@MWCNTs core-shell nanofibers has demonstrated great potential to be assembled into intelligent wearable devices

Association of Metabolic Dysfunction-Associated Fatty Liver Disease With Left Ventricular Diastolic Function and Cardiac Morphology

Background and AimNon-alcoholic fatty liver disease (NAFLD) is closely related to cardiovascular diseases (CVD). A newly proposed definition is metabolic dysfunction-associated fatty liver disease (MAFLD), which was changed from NAFLD. The clinical effect of this change on abnormalities of cardiac structure and function is yet unknown. We aimed to examine whether MAFLD is associated with left ventricular (LV) diastolic dysfunction (LVDD) and cardiac remolding and further identify the impact of different subgroups and severity of MAFLD.MethodWe evaluated 228 participants without known CVDs. Participants were categorized by the presence of MAFLD and the normal group. Then, patients with MAFLD were subclassified into three subgroups: MAFLD patients with diabetes (diabetes subgroup), overweight/obesity patients (overweight/obesity subgroup), and lean/normal-weight patients who had two metabolic risk abnormalities (lean metabolic dysfunction subgroup). Furthermore, the severity of hepatic steatosis was assessed by transient elastography (FibroScan®) with a controlled attenuation parameter (CAP), and patients with MAFLD were divided into normal, mild, moderate, and severe hepatic steatosis groups based on CAP value. Cardiac structure and function were examined by echocardiography.ResultsLVDD was significantly more prevalent in the MAFLD group (24.6% vs. 60.8%, p < 0.001) compared to the normal group. The overweight subgroup and diabetes subgroup were significantly associated with signs of cardiac remolding, including interventricular septum thickness, LV posterior wall thickness, left atrial diameter (all p < 0.05), relative wall thickness, and LV mass index (all p < 0.05). Additionally, moderate-to-to severe steatosis patients had higher risks for LVDD and cardiac remolding (all p-values < 0.05).ConclusionMAFLD was associated with LVDD and cardiac remolding, especially in patients with diabetes, overweight patients, and moderate-to-to severe steatosis patients. This study provides theoretical support for the precise prevention of cardiovascular dysfunction in patients with MAFLD

End-to-End Network for Pedestrian Detection, Tracking and Re-Identification in Real-Time Surveillance System

Surveillance video has been widely used in business, security, search, and other fields. Identifying and locating specific pedestrians in surveillance video has an important application value in criminal investigation, search and rescue, etc. However, the requirements for real-time capturing and accuracy are high for these applications. It is essential to build a complete and smooth system to combine pedestrian detection, tracking and re-identification to achieve the goal of maximizing efficiency by balancing real-time capture and accuracy. This paper combined the detector and Re-ID models into a single end-to-end network by introducing a new track branch to YOLOv5 architecture for tracking. For pedestrian detection, we employed the weighted bi-directional feature pyramid network (BiFPN) to enhance the network structure based on the YOLOv5-Lite, which is able to further improve the ability of feature extraction. For tracking, based on Deepsort, this paper enhanced the tracker, which uses the Noise Scale Adaptive (NSA) Kalman filter to track, and adds adaptive noise to strengthen the anti-interference of the tracking model. In addition, the matching strategy is further updated. For pedestrian re-identification, the network structure of Fastreid was modified, which can increase the feature extraction speed of the improved algorithm by leaps and bounds. Using the proposed unified network, the parameters of the entire model can be trained in an end-to-end method with the multi-loss function, which has been demonstrated to be quite valuable in some other recent works. Experimental results demonstrate that pedestrians detection can obtain a 97% mean Average Precision (mAP) and that it can track the pedestrians well with a 98.3% MOTA and a 99.8% MOTP on the MOT16 dataset; furthermore, high pedestrian re-identification performance can be achieved on the VERI-Wild dataset with a 77.3% mAP. The overall framework proposed in this paper has remarkable performance in terms of the precise localization and real-time detection of specific pedestrians across time, regions, and cameras

Examination of Time-Variant Asset Correlations Using High- Frequency Data

Drawing motivation from the 2007-2009 global financial crises, this paper looks to further examine the potential time-variant nature of asset correlations. Specifically, high frequency price data and its accompanying tools are utilized to examine the relationship between asset correlations and market volatility. Through further analyses of this relationship using linear regressions, this paper presents some significant results that provide striking evidence for the time-variability of asset correlations. These findings have crucial implications for portfolio managers as well as risk management professionals alike, especially in the contest of diversification.George Tauchen, Timothy Bollersle

Clustering Cloud-Like Model-Based Targets Underwater Tracking for AUVs

Autonomous underwater vehicles (AUVs) rely on a mechanically scanned imaging sonar that is fixedly mounted on AUVs for underwater target barrier-avoiding and tracking. When underwater targets cross or approach each other, AUVs sometimes fail to track, or follow the wrong target because of the incorrect association of the multi-target. Therefore, a tracking method adopting the cloud-like model data association algorithm is presented in order to track underwater multiple targets. The clustering cloud-like model (CCM) not only combines the fuzziness and randomness of the qualitative concept, but also achieves the conversion of the quantitative values. Additionally, the nearest neighbor algorithm is also involved in finding the cluster center paired to each target trajectory, and the hardware architecture of AUVs is proposed. A sea trial adopting a mechanically scanned imaging sonar fixedly mounted on an AUV is carried out in order to verify the effectiveness of the proposed algorithm. Experiment results demonstrate that compared with the joint probabilistic data association (JPDA) and near neighbor data association (NNDA) algorithms, the new algorithm has the characteristic of more accurate clustering

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy

Underwater Images Enhancement using Multi-Wavelet Transform and Median Filter

Autonomous underwater vehicles (AUV) are usually equipped with vision sensors. However, the underwater images captured by AUV often suffer from effects such as diffusion, scatter and caustics. So image enhancement methods are necessary to increase visual quality. A Median filter de-noising approach based on multi-wavelet transform was proposed to remove the impulse noise viewed as random noise from the blurred underwater image. Biorthogonal muti-wavelet has two scaling functions that may generate different multiresolution analysis, so it was chosen as the basic wavelet for underwater image two-layer decomposition and reconstruction. On this basis, the blurred underwater image was decomposed and reconstructed adopting Biorthogonal and the Median filter was applied for removing the impulse noise form the decomposition images of each layer. Four indexes were involved to evaluate the performance of de-noising. The results show that the proposed approach provides superior results compared to other de-noising method. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.450