Probing Transverse Momentum Broadening via Dihadron and Hadron-jet Angular Correlations in Relativistic Heavy-ion Collisions

Dijet, dihadron, hadron-jet angular correlations have been reckoned as important probes of the transverse momentum broadening effects in relativistic nuclear collisions. When a pair of high-energy jets created in hard collisions traverse the quark-gluon plasma produced in heavy-ion collisions, they become de-correlated due to the vacuum soft gluon radiation associated with the Sudakov logarithms and the medium-induced transverse momentum broadening. For the first time, we employ the systematical resummation formalism and establish a baseline calculation to describe the dihadron and hadron-jet angular correlation data in $pp$ and peripheral $AA$ collisions where the medium effect is negligible. We demonstrate that the medium-induced broadening $\langle p_\perp^2\rangle$ and the so-called jet quenching parameter $\hat q$ can be extracted from the angular de-correlations observed in $AA$ collisions. A global $\chi^2$ analysis of dihadron and hadron-jet angular correlation data renders the best fit $\langle p_\perp^2 \rangle \sim 13~\textrm{GeV}^2$ for a quark jet at RHIC top energy. Further experimental and theoretical efforts along the direction of this work shall significantly advance the quantitative understanding of transverse momentum broadening and help us acquire unprecedented knowledge of jet quenching parameter in relativistic heavy-ion collisions.Comment: 6 pages, 3 figure

3D Trajectory Design for UAV-Assisted Oblique Image Acquisition

In this correspondence, we consider a new unmanned aerial vehicle (UAV)-assisted oblique image acquisition system where a UAV is dispatched to take images of multiple ground targets (GTs). To study the three-dimensional (3D) UAV trajectory design for image acquisition, we first propose a novel UAV-assisted oblique photography model, which characterizes the image resolution with respect to the UAV's 3D image-taking location. Then, we formulate a 3D UAV trajectory optimization problem to minimize the UAV's traveling distance subject to the image resolution constraints. The formulated problem is shown to be equivalent to a modified 3D traveling salesman problem with neighbourhoods, which is NP-hard in general. To tackle this difficult problem, we propose an iterative algorithm to obtain a high-quality suboptimal solution efficiently, by alternately optimizing the UAV's 3D image-taking waypoints and its visiting order for the GTs. Numerical results show that the proposed algorithm significantly reduces the UAV's traveling distance as compared to various benchmark schemes, while meeting the image resolution requirement

Polymorphism and Balancing Selection of MHC Class II DAB Gene in 7 Selective Flounder (Paralichthys olivaceus) Families

In order to determine the genetic variation of the MHC class IIB exon2 allele in the offspring, 700 fry from seven families of Japanese flounder challenged with V. anguillarum were studied, and different mortality rates were found in those families. Five to ten surviving and dead fry from each of the seven families were selected to study the MHC class II B exon2 gene with PCR and a direct sequencing method. One hundred and sixteen different exon2 sequences were found and 116 different alleles were identified, while a minimum of four loci were revealed in the MHC class II B exon2 gene. The ratio (dN/dS) of nonsynonymous substitution (dN) to synonymous substitutions (dS) in the peptide-binding region (PBR) of the MHC class IIB gene was 6.234, which indicated that balancing selection is acting on the MHC class IIB genes. The MHC IIB alleles were thus being passed on to their progeny. Some alleles were significantly more frequent in surviving than dead individuals. All together our data suggested that the alleles Paol-DAB*4301, Paol-DAB*4601, Paol-DAB*4302, Paol-DAB*3803, and Paol-DAB*4101 were associated with resistance to V. anguillarum in flounder

WC@meso-Pt core–shell nanostructures for fuel cells

We developed a facile method to synthesize core–shell WC@meso-Pt nanocatalysts by carburizing ammonium tungstate and copper nitrate via gas–solid reactions, followed by a Pt replacement reaction. The mesoporous nanocomposite displays higher activity and stability towards methanol electrooxidation than commercial Pt/C catalysts

Bacterial etiology in early re-admission patients with acute exacerbation of chronic obstructive pulmonary disease

Background: Repeatedly hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) are often exposed to more antibiotics, but the distribution of pathogenic bacteria in these patients is poorly understood. The objectives of this study were to analyze the distribution of pathogenic bacteria and the risk factors associated with multidrug-resistant (MDR) bacteria infection in early re-admission patients with AECOPD.Methods: We retrospectively reviewed charts for patients with AECOPD admitted to our hospital between January 2011 and november 2012. The early re-admission group and non-early readmission group were determined by whether patients were readmitted within 31 days after discharge. Detection of potentially pathogenic microorganisms (PPMs) and MDR bacteria were analyzed. Logistic regression analysis was performed to identify independent risk factors for MDR bacteria infection.Results: PPMs were isolated from 230 (32.0%) cases of respiratory tract specimens; MDR bacteria accounted for 24.7% (57/230). Pseudomonas aeruginosa (43.7%), Klebsiella pneumoniae (15.6%), and Acinetobacter baumannii (12.5%) were the top three PPMs in the early readmission group, while the top three PPMs in the non-early readmission group were K. pneumoniae (23.7%), P. aeruginosa (21.2%), and Streptococcus pneumoniae (17.1%). Multivariate analysis showed that use of antibiotics within 2 weeks (odds ratio [OR] 8.259, 95% confidence interval [CI] 3.056-22.322, p = 0.000) was the independent risk factor for MDR bacteria infection.Conclusion: Non-fermentative Gram-negative bacilli (NFGNB) and enterobacteria were the predominant bacteria in early readmission patients with AECOPD. The detection rate of MDR bacteria was high which was related to the use of antibiotics within 2 weeks before admission in these patients.Keywords: AECOPD, re-admission, bacteria, multidrug-resistant (MDR), risk factors

(3S,NR)-3-Hydroxy­methyl-2-methyl-2-(3-methyl­but-2-en-1-yl)-1,2,3,4-tetra­hydro­isoquinolinium bromide–1,1′-bi-2-naphthol (1/1)

In the title compound, C16H24NO+·Br−·C20H14O2, the N-hetero­cyclic six-membered ring assumes a half-chair conformation. The two naphthalene ring systems are nearly perpendicular to one another, making a dihedral angle of 89.5 (2)°. Inter­molecular O—H⋯Br hydrogen bonding helps to stabilize the crystal structure

PP-MobileSeg: Explore the Fast and Accurate Semantic Segmentation Model on Mobile Devices

The success of transformers in computer vision has led to several attempts to adapt them for mobile devices, but their performance remains unsatisfactory in some real-world applications. To address this issue, we propose PP-MobileSeg, a semantic segmentation model that achieves state-of-the-art performance on mobile devices. PP-MobileSeg comprises three novel parts: the StrideFormer backbone, the Aggregated Attention Module (AAM), and the Valid Interpolate Module (VIM). The four-stage StrideFormer backbone is built with MV3 blocks and strided SEA attention, and it is able to extract rich semantic and detailed features with minimal parameter overhead. The AAM first filters the detailed features through semantic feature ensemble voting and then combines them with semantic features to enhance the semantic information. Furthermore, we proposed VIM to upsample the downsampled feature to the resolution of the input image. It significantly reduces model latency by only interpolating classes present in the final prediction, which is the most significant contributor to overall model latency. Extensive experiments show that PP-MobileSeg achieves a superior tradeoff between accuracy, model size, and latency compared to other methods. On the ADE20K dataset, PP-MobileSeg achieves 1.57% higher accuracy in mIoU than SeaFormer-Base with 32.9% fewer parameters and 42.3% faster acceleration on Qualcomm Snapdragon 855. Source codes are available at https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.8.Comment: 8 pages, 3 figure