The Lattices of Group Fuzzy Congruences and Normal Fuzzy Subsemigroups on E

The aim of this paper is to investigate the lattices of group fuzzy congruences and normal fuzzy subsemigroups on E-inversive semigroups. We prove that group fuzzy congruences and normal fuzzy subsemigroups determined each other in E-inversive semigroups. Moreover, we show that the set of group t-fuzzy congruences and the set of normal subsemigroups with tip t in a given E-inversive semigroup form two mutually isomorphic modular lattices for every t∈0,1

Thiopeptide Antibiotics Exhibit a Dual Mode of Action against Intracellular Pathogens by Affecting Both Host and Microbe

SummaryThiostrepton (TSR) is an archetypal thiopeptide antibiotic possessing a quinaldic acid (QA) moiety in the side ring system. According to the mechanism of TSR previously known to target bacterial ribosome, we recently designed and biosynthesized several TSR derivatives that varied in QA substitution. Utilizing these thiopeptide antibiotics to treat the intracellular pathogen Mycobacterium marinum, we herein report a novel mode of action of TSRs, which induce ER stress-mediated autophagy to enhance host cell defense. This intracellular response, which is sensitive to the modification of the QA group, serves as an indirect but unignorable mechanism for eliminating intracellular pathogens. TSRs are thus the only type of antibiotics, to our knowledge, with the dual action on both the parasitic bacteria and the infected host cells. The newly observed mechanism of TSRs may inspire the future change in the treatment of intracellular pathogens, by taking host response into account

Who buys new energy vehicles in china? Assessing social-psychological predictors of purchasing awareness, intention, and policy

This paper investigates the salience of social-psychological factors in explaining why drivers purchase (or fail to purchase) New Energy Vehicles (NEVs)—including hybrid electric vehicles, battery electric vehicles, and fuel cell electric vehicles—in China. A questionnaire measuring six dimensions (including attitudes, subjective norms, perceived behavioral control, personal norms, low-carbon awareness and policy) was distributed in Tianjin, where aggressive policy incentives for NEVs exist yet adoption rates remain low. Correlation analysis and hierarchical multiple regression analyses are applied data collected through 811 valid questionnaires. We present three main findings. First, there is an “awareness-behavior gap” whereby low-carbon awareness has a moderating effect on purchasing behavior via psychological factors. Second, subjective norms has a stronger influence on intention to purchase New Energy Vehicles than other social-psychological factors. Third, acceptability of government policies has positive significant impact on adoption of New Energy Vehicles, which can provide reference potential template for other countries whose market for New Energy Vehicles is also in an early stage

The prognostic role of the change in albumin-derived neutrophil-to-lymphocyte ratio during neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

The prognosis of patients with locally advanced rectal cancer (LARC) has improved with the adoption of a multidisciplinary treatment approach combining neoadjuvant chemoradiotherapy (nCRT) and total mesorectal excision (TME). Developing real-time, sensitive biomarkers to monitor systemic changes during nCRT is of paramount importance. Although the association between albumin-derived neutrophil-to-lymphocyte ratio (Alb-dNLR) and prognosis in various cancers is established, its prognostic value in LARC patients undergoing nCRT is not well-studied. This study enrolled a cohort of 618 LARC patients, stratifying them into two groups according to their change in Alb-dNLR (∆Alb-dNLR) values, using an optimal cut-off point: a low ∆Alb-dNLR group (≤ 0.90) and a high ∆Alb-dNLR group (> 0.90). The prognostic significance of ∆Alb-dNLR was evaluated using a Cox proportional hazards model. The 5-year overall survival (OS) rates were 75.2% in the low ∆Alb-dNLR group (≤ 0.90) and 85.9% in the high ∆Alb-dNLR group (>0.90) (P < 0.001). The 5-year disease-free survival (DFS) rates were 71.2% and 80.6%, respectively (P = 0.016). Multivariate analyses demonstrated that both ∆Alb-dNLR and pre-Alb-dNLR were independent prognostic factors for OS (P ≤ 0.001), while ∆Alb-dNLR was demonstrated as an independent prognostic factor for DFS (P = 0.016). A predictive nomogram, incorporating the ∆Alb-dNLR subgroup, demonstrated enhanced performance (concordance index [C-index] of 0.720 for OS and 0.690 for DFS) compared to the pre-treatment Alb-dNLR subgroup (C-index of 0.700 for OS and of 0.680 for DFS). Therefore, ∆Alb-dNLR shows significant potential as a usable and prognostic biomarker for predicting OS and DFS in LARC patients undergoing nCRT

Guidance Compliance Behavior on VMS Based on SOAR Cognitive Architecture

SOAR is a cognitive architecture named from state, operator and result, which is adopted to portray the drivers' guidance compliance behavior on variable message sign (VMS) in this paper. VMS represents traffic conditions to drivers by three colors: red, yellow, and green. Based on the multiagent platform, SOAR is introduced to design the agent with the detailed description of the working memory, long-term memory, decision cycle, and learning mechanism. With the fixed decision cycle, agent transforms state through four kinds of operators, including choosing route directly, changing the driving goal, changing the temper of driver, and changing the road condition of prediction. The agent learns from the process of state transformation by chunking and reinforcement learning. Finally, computerized simulation program is used to study the guidance compliance behavior. Experiments are simulated many times under given simulation network and conditions. The result, including the comparison between guidance and no guidance, the state transition times, and average chunking times are analyzed to further study the laws of guidance compliance and learning mechanism

Surface Roughness Models and Their Experimental Validation in Micro Milling of 6061-T6 Al Alloy by Response Surface Methodology

Due to the widespread use of high-accuracy miniature and micro features or components, it is required to predict the machined surface performance of the micro milling processes. In this paper, a new predictive model of the surface roughness is established by response surface method (RSM) according to the micro milling experiment of 6061-T6 aluminum alloy which is carried out based on the central composite circumscribed (CCC) design. Then the model is used to analyze the effects of parameters on the surface roughness, and it can be concluded that the surface roughness increases with the increasing of the feed rate and the decreasing of the spindle speed. At last, based on the model the contour map of the surface roughness and material removal rate is established for optimizing the process parameters to improve the cutting efficiency with good surface roughness. The prediction results from the model have good agreement with the experimental results

Optimal Analysis of Tunnel Construction Methods through Cross Passage from Subway Shaft

The conversion section of the cross passage and shaft is a priority concern in the stress transformation of a tunnel structure during subway underground excavation. In the construction of Subway Line 5 in Xi'an, China, the main line in the loess layer was constructed through the cross passage from the subway shaft of the Yue Deng Pavilion–San Dian Village Station tunnel section. Numerical simulation and field measurement were adopted to study the construction stability of the cross passage and shaft under two possible construction methods: the “shaft followed by cross passage construction” method and the “cross passage parallel shaft construction” method. The results showed that the surface deformation and plastic zone of the surrounding rock are similar under the two construction methods. However, of the two, the “cross passage parallel shaft construction” method was more advantageous in controlling the structural deformation of the original shaft and the stress distribution of the horsehead structure. The field monitoring data showed that the surface settlements and the deformation of the original shaft structures meet the requirement of control standards under the “cross passage parallel shaft construction” method

6G Network Operation Support System

6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional perception, global coverage, green and low-carbon, native network security, etc. 6G will realize the transition from serving people and people-things communication to supporting the efficient connection of intelligent agents, and comprehensively leading the digital, intelligent and green transformation of the economy and the society. As the core support system for mobile communication network, 6G OSS needs to achieve high-level network automation, intelligence and digital twinning capabilities to achieve end-to-end autonomous network operation and maintenance, support the operation of typical 6G business scenarios and play a greater social responsibility in the fields of environment, society, and governance (ESG).This paper provides a detailed introduction to the overall vision, potential key technologies, and functional architecture of 6G OSS . It also presents an evolutionary roadmap and technological prospects for the OSS from 5G to 6G.Comment: 103 pages, 20 figures, 52 references (chinese version