Granular computing and optimization model-based method for large-scale group decision-making and its application

In large-scale group decision-making process, some decision makers hesitate among several linguistic terms and cannot compare some alternatives, so they often express evaluation information with incomplete hesitant fuzzy linguistic preference relations. How to obtain suitable large-scale group decision-making results from incomplete preference information is an important and interesting issue to concern about. After analyzing the existing researches, we find that: i) the premise that complete preference relation is perfectly consistent is too strict, ii) deleting all incomplete linguistic preference relations that cannot be fully completed will lose valid assessment information, iii) semantics given by decision makers are greatly possible to be changed during the consistency improving process. In order to solve these issues, this work proposes a novel method based on Granular computing and optimization model for large-scale group decision-making, considering the original consistency of incomplete hesitant fuzzy linguistic preference relation and improving its consistency without changing semantics during the completion process. An illustrative example and simulation experiments demonstrate the rationality and advantages of the proposed method: i) semantics are not changed during the consistency improving process, ii) completion process does not significantly alter the inherent quality of information, iii) complete preference relations are globally consistent, iv) final large-scale group decision-making result is acquired by fusing complete preference relations with different weights

MHITNet: a minimize network with a hierarchical context-attentional filter for segmenting medical ct images

In the field of medical CT image processing, convolutional neural networks (CNNs) have been the dominant technique.Encoder-decoder CNNs utilise locality for efficiency, but they cannot simulate distant pixel interactions properly.Recent research indicates that self-attention or transformer layers can be stacked to efficiently learn long-range dependencies.By constructing and processing picture patches as embeddings, transformers have been applied to computer vision applications. However, transformer-based architectures lack global semantic information interaction and require a large-scale training dataset, making it challenging to train with small data samples. In order to solve these challenges, we present a hierarchical contextattention transformer network (MHITNet) that combines the multi-scale, transformer, and hierarchical context extraction modules in skip-connections. The multi-scale module captures deeper CT semantic information, enabling transformers to encode feature maps of tokenized picture patches from various CNN stages as input attention sequences more effectively. The hierarchical context attention module augments global data and reweights pixels to capture semantic context.Extensive trials on three datasets show that the proposed MHITNet beats current best practise

An H{\alpha} Impression of Ly{\alpha} Galaxies at z≃6z\simeq6 with Deep JWST/NIRCam Imaging

We present a study of seven spectroscopically confirmed Ly{\alpha} emitting galaxies at redshift $z\simeq6$ using the James Webb Space Telescope (JWST) NIRCam images. These galaxies, with a wide range of Ly{\alpha} luminosities, were recently observed in a series of NIRCam broad- and medium-bands. We measure the continuum and H{\alpha} line properties of the galaxies using the combination of the NIRCam photometry and archival Hubble Space Telescope imaging data. We find that galaxies with bluer UV continuum slopes likely have higher escape fractions of Ly{\alpha} photons. We also find that galaxies with higher Ly{\alpha} line emission tend to produce ionizing photons more efficiently. The most Ly{\alpha}-luminous galaxy in the sample has a high ionizing photon production efficiency of log$_{10} \xi_{\rm ion, 0}$ (Hz erg$^{-1}$) > 26. Our results support that Ly{\alpha} galaxies may have served as an important contributor to the cosmic reionization. Blue and bright Ly{\alpha} galaxies are also excellent targets for JWST follow-up spectroscopic observations.Comment: 10 pages, 4 figures, 2 tables, submitted to ApJ

Seasonal trends in PM2.5 source contributions in Beijing, China

The 24-h PM2.5 samples (particles with an aerodynamic diameter of 2.5 μm or less) were taken at 6-day intervals at five urban and rural sites simultaneously in Beijing, China for 1 month in each quarter of calendar year 2000. Samples at each site were combined into a monthly composite for the organic tracer analysis by GC/MS (gas chromatography/mass spectrometry). Compared to the data obtained from other metropolitan cities in the US, the PM2.5 mass and fine organic carbon (OC) concentrations in Beijing were much higher with an annual average of 101 and 20.9 μg m^(−3), respectively. Over one hundred organic compounds including unique tracers for important sources were quantified in PM2.5 in Beijing. Source apportionment of fine OC was conducted using chemical mass balance receptor model (CMB) in combination with particle-phase organic compounds as fitting tracers. Carbonaceous aerosols and major ions (sulfate, nitrate and ammonium) constituted 69% of PM2.5 mass on average. The major sources of PM2.5 mass in Beijing averaged over five sites on an annual basis were determined as dust (20%), secondary sulfate (17%), secondary nitrate (10%), coal combustion (7%), diesel and gasoline exhaust (7%), secondary ammonium (6%), biomass aerosol (6%), cigarette smoke (1%), and vegetative detritus (1%). The lowest PM2.5 mass concentration was found in January (60.9 μg m^(−3)), but the contribution of carbonaceous aerosol to PM2.5 mass was maximal during this season, accounting for 57% of the mass. During cold heating season, the contributions from coal combustion and biomass aerosol to PM2.5 mass increased, accounting for 20.9% of fine particle mass in October and 24.5% in January. The contribution of the biomass aerosols peaked in the fall. In April 2000, the impact of dust storms was so significant that dust alone constituted 36% of PM2.5 mass. On average, the model resolved 88% of the sources of the PM2.5 mass concentrations in Beijing

The Magellan M2FS Spectroscopic Survey of High-Redshift Galaxies: A Sample of 260 Lyα\alpha Emitters at Redshift z≈5.7z\approx5.7

We present a spectroscopic survey of Ly$\alpha$ emitters (LAEs) at $z\approx5.7$ using the multi-object spectrograph M2FS on the Magellan Clay telescope. This is part of a high-redshift galaxy survey carried out in several well-studied deep fields. These fields have deep images in multiple UV/optical bands, including a narrow NB816 band that has allowed an efficient selection of LAE candidates at $z\approx5.7$. Our sample consists of 260 LAEs and covers a total effective area of more than two square degrees on the sky. This is so far the largest (spectroscopically confirmed) sample of LAEs at this redshift. We use the secure redshifts and narrowband photometry to measure Ly$\alpha$ luminosities. We find that these LAEs span a Ly$\alpha$ luminosity range of $\sim 2\times10^{42} - 5\times10^{43}$ erg s$^{-1}$, and include some of the most luminous galaxies known at $z \ge 5.7$ in terms of Ly$\alpha$ luminosity. Most of them have rest-frame equivalent widths between 20 and 300 \r{A}, and more luminous Ly$\alpha$ emission lines tend to have broader line widths. We detect a clear offset of $\sim20$ \r{A} between the observed Ly$\alpha$ wavelength distribution and the NB816 filter transmission curve, which can be explained by the intergalactic medium absorption of continua blueward of Ly$\alpha$ in the high-redshift spectra. This sample is being used to study the Ly$\alpha$ luminosity function and galaxy properties at $z\approx5.7$.Comment: 16 pages, 12 figures, 3 tables; Accepted for publication in Ap

Heterogeneous N2O5 reactions on atmospheric aerosols at four Chinese sites : improving model representation of uptake parameters

Heterogeneous reactivity of N2O5 on aerosols is a critical parameter in assessing NOx fate, nitrate production, and particulate chloride activation. Accurate measurement of its uptake coefficient (gamma N2O5) and representation in air quality models are challenging, especially in the polluted environment. With an in situ aerosol flow-tube system, the gamma N2O5 was directly measured on ambient aerosols at two rural sites in northern and southern China. The results were analyzed together with the gamma N2O5 derived from previous field studies in China to obtain a holistic picture of gamma N2O5 uptake and the influencing factors under various climatic and chemical conditions. The field-derived or measured gamma N2O5 was generally promoted by the aerosol water content and suppressed by particle nitrate. Significant discrepancies were found between the measured gamma N2O5 and that estimated from laboratory-determined parameterizations. An observation-based empirical parameterization was derived in the present work, which better reproduced the mean value and variability of the observed gamma N2O5. Incorporating this new parameterization into a regional air quality model (WRF-CMAQ) has improved the simulation of N2O5, nitrogen oxides, and secondary nitrate in the polluted regions of China.Peer reviewe