双碳目标下废旧聚酯纺织品的回收再利用研究进展

随着人们生活和消费水平的提高以及对服装时尚化的进一步追求,纺织品的更新换代愈加频繁,服用周期也越来越短,这就导致了废旧纺织品,尤其是聚酯类纺织品的大量累积。由于我国废旧纺织品回收体系总体回收率低,于是造成了严重的资源浪费,也给环境和人类健康带来了巨大的压力和隐患。《关于加快推进废旧纺织品循环利用的实施意见》的出台进一步要求加快构建废旧物资循环利用体系,提升资源安全保障能力。为促进废旧聚酯纺织品的高效循环回收利用,文中首先综述了当前废旧聚酯纺织品的回收途径和新方法,并对其进行了比较和分析,总结其特点,指出废旧聚酯纺织品循环回收再利用所面临的困境及技术壁垒,展望了废旧聚酯纺织品未来的发展趋势,即可降解聚酯材料的创制及废旧聚酯纺织品的循环回收再利用新途径的探索,以期推动纺织行业的可持续发展。

人在回路的深度强化学习算法及其在自动驾驶智能决策中的应用

由于机器学习智力和能力有限,它目前仍无法处理各种情况,因此不能在现实应用中完全取代人类。因为人类在复杂场景中表现出稳健性和适应性,所以将人类引入人工智能(AI)的训练循环并利用人类智慧进一步提升机器学习算法变得至关重要。本研究开发了一种基于实时人工指导(Hug)的深度强化学习(DRL)方法,用于端到端自动驾驶案例中的策略训练。通过新设计的人类与自动化之间的控制转移机制,人类能够在模型训练过程中实时干预和纠正智能体的不合理行为。基于这种人机回环的指导机制,本研究开发一种基于修正策略和价值网络的改良的动作-评价架构(actor-critic architecture)。所提出的Hug-DRL的快速收敛允许实时的人工指导行为融合到智能体的训练循环中,进一步提高了DRL的效率和性能。本研究通过40名受试者的人机回环实验对开发的方法进行了验证,并与其他最先进的学习方法进行了比较。结果表明,该方法可以在人工指导下有效地提高DRL算法的训练效率和性能,且对参与者的专业知识或经验没有硬性要求。

High-efficiency and pollution-controlling in-situ gasification chemical looping combustion system by using CO_2 instead of steam as gasification agent

Using CO_2 as gasification agent instead of steam in in-situ coal gasification chemical looping combustion(i G-CLC)power plant can eliminate energy consumption for steam generation, thus obtaining higher system efficiency. In this work, a comparative study of iG-CLC power plant using steam and CO_2 as gasification agent is concentrated on. The effects of steam to carbon ratio(S/C) and CO_2 to carbon ratio(CO_2/C) on the fuel reactor temperature,char conversion, syngas composition and CO_2 capture efficiency are separately investigated. An equilibrium carbon conversion of 88.9% is achieved in steam-based case as S/C ratio increases from 0.7 to 1.1, whereas a maximum conversion of 84.2% is obtained in CO_2-based case with CO_2/C ranging from 0.7 to 1.1. Furthermore the effects of oxygen carrier to fuel ratio(φ) on system performances are investigated. Increasing φ from 1.0 to1.4 helps to achieve char conversion from 75.9% to 88.9% in steam-based case, by contrast the char conversion can achieve 66.3%–84.2% in CO_2-based case within the same φ range. In terms of iG-CLC power plant, recycling partial CO_2 to the fuel reactor improves the overall performance. Approximately 3.9% of net power efficiency are increased in CO_2-based plant, from steam-based plant. Higher CO_2 capture efficiency and lower CO_2 emission rate are observed in CO_2-gasified iG-CLC power plant, expecting to be 90.63% and 85.18 kg·MW-1·h-1,respectively.

A CO_(2)-controllable phase change absorbent solvent used to waste recycling of dining lampblack

Dining lampblack as a source of atmospheric pollution,urban residents had to spend a lot of economic costs all year round to solve its impact.However,traditional treatment methods often carry the risk of secondary pollution.The use of phase change absorption solvent(PCAS)controlled by CO_(2)can effectively absorb the oily components in dining lampblack,and smoothly avoid the generation of secondary pollutants and squandering of resources.The reversibility of PCASs under CO_(2)control was explained by pH changes and macroscopic visualizations.The absorption effects of favorable absorbents and PCASs on dining lampblack were compared and analyzed.The fatty acid(FA)in the oil absorption mixture was desorbed by interacting with D230.The results of GC/MS analysis on the oil components separated by desorption showed that the desorption of PCASs was effective for these refractory oil components.FAs can be enriched and applied to the subsequent dining lampblack treatment link to realize the waste recycling.In addition,the absorption and desorption of oily components by PCASs were combined with the CO_(2)-controlled phase transformation of PCASs itself to achieve the absorption circulation of treating dining lampblack by using PCASs.

Optimization for UAV-assisted simultaneous transmission and reception communications in the existence of malicious jammers

In this paper,we study an unmanned aerial vehicle(UAV)-assisted communication system,where the UAV is dispatched to implement simultaneous transmission and reception(STR)in the existence of multiple malicious jammers.Two schemes are investigated,namely frequency band-division-duplex(FDD)and time-fraction(TF).Based on the FDD scheme,the UAV can transmit information by using the portion of the bandwidth and receive information within the remaining portion of the bandwidth simultaneously.To perform the STR within the whole bandwidth,the TF-based scheme is considered by using a fraction of a time slot for the downlink,while the remaining fraction of the time slot is allocated for the uplink.We aim to maximize the worst-case throughput by optimizing the UAV three-dimensional(3D)trajectory and resource allocation for each scheme.The optimization problem is non-convex and thus computationally intractable.To handle the nonlinear problem,we use the block coordinate decomposition method to disaggregate the optimization problem into four subproblems and adopt the successive convex approximation technique to tackle non-convex problems.The simulation results demonstrate the performance of the TF-based scheme over the benchmark schemes.

MGCPN:An Efficient Deep Learning Model for Tibetan Plateau Precipitation Nowcasting Based on the IMERG Data

The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP) impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address such a challenge,we introduce a model called Multisource Generative Adversarial Network-Convolutional Long Short-Term Memory(GAN-ConvLSTM) for Precipitation Nowcasting(MGCPN),which utilizes data products from the Integrated Multi-satellite Retrievals for global precipitation measurement(IMERG) data,offering high spatiotemporal resolution precipitation forecasts for upcoming periods ranging from 30 to 300 min.The results of our study confirm that the implementation of the MGCPN model successfully addresses the problem of underestimating and blurring precipitation results that often arise with increasing forecast time.This issue is a common challenge in precipitation forecasting models.Furthermore,we have used multisource spatiotemporal datasets with integrated geographic elements for training and prediction to improve model accuracy.The model demonstrates its competence in generating precise precipitation nowcasting with IMERG data,offering valuable support for precipitation research and forecasting in the TP region.The metrics results obtained from our study further emphasize the notable advantages of the MGCPN model;it outperforms the other considered models in the probability of detection(POD),critical success index,Heidke Skill Score,and mean absolute error,especially showing improvements in POD by approximately 33%,19%,and 8% compared to Convolutional Gated Recurrent Unit(ConvGRU),ConvLSTM,and small Attention-UNet(SmaAt-UNet) models.

Complete response of a locally advanced pulmonary hepatoid adenocarcinoma patient to perioperative XELOX-containing chemoimmunotherapy

With morphological features resembling hepatocellular carcinoma,hepatoid adenocarcinoma of the lung(HAL)is a rare and aggressive subtype of lung cancer with a 5-year survival of only 8%.1 Most HAL patients present increased serum alpha-fetoprotein(AFP)levels that are commonly related to poor prognosis.Most insights into HAL have come from case series or reports,and TP53 is frequently mutated in HAL.The heterogeneity of HAL complicates the diagnosis.With no established standard,the management of HAL is modeled on that of classical lung adenocarcinoma,although with dismal outcomes.2 Herein,we reported the effective management of a stage IIIb HAL patient with perioperative chemoimmunotherapy and curative-intent surgery.The patient remained disease-free and minimal residual disease(MRD)-negative for more than one year after surgery.

废旧纺织品的资源化循环再生利用研究进展

随着社会的快速发展和人民生活水平的显著提高,人们对穿着时尚化的需求使纺织品的更新换代愈加频繁、新型纺织品生命周期也越来越短,这产生了大量的废旧纺织品.同时,由于技术与经济瓶颈,我国废旧纺织品再生行业产业链亟待完善,使大量的废旧纺织品无法进行资源化利用,给环境带来了巨大的压力,也给人类健康带来了巨大隐患.基于此,本文回顾了废旧纤维制品的最新研究进展,总结其特点,指出废旧纺织品回收行业所面临的技术壁垒,并从废旧纺织品回收的安全性、高效性、可持续性和规范性方面进行展望,为进一步践行绿色发展理念,推进废旧纺织品的循环再生而努力,以期推动纺织品的转型升级.

Full‑Color Tunable and Highly Fire‑Retardant Colored Carbon Fibers

Carbon fibers(CFs)are widely used in various cutting-edge fields,such as aerospace,military,automobiles,and sports,owing to their unique combination of excellent mechanical properties,good thermal stability,and lightweight.However,their inherent super-black appearance makes it difficult to satisfy the aesthetic/fashion requirements of the colorful world,and the flammability of CFs severely limits their practical utilization in high-temperature and other extreme environments.Herein,we fabricated full-color tunable colored CFs on a large-scale via atomic layer deposition,based on the monolayer film interference strategy.CFs exhibited brilliant colors and excellent environmental durability in extreme environments,such as intense ultraviolet(UV)irradiation,accelerated laundering,friction,high-temperature,and low-temperature treatments.Colored CFs also exhibited excellent fire-retardant performance that could withstand alcohol-lamp flame burning for 60 min.Our work provides insights into an innovative material/structural design that can help achieve rapid development of the CF industry and global carbon neutrality/sustainability.

Coverability of Wireless Sensor Networks

The coverability of Wireless Sensor Networks （WSNs） is essentially a Quality of Service （QoS） problem that measures how well the monitored area is covered by one or more sensor nodes. The coverability of WSNs was examined by combining existing computational geometry techniques such as the Voronoi diagram and Delaunay triangulation with graph theoretical algorithmic techniques. Three new evaluation algorithms, known as CRM （Comprehensive Risk Minimization）, TWS （Threshold Weight Shortest path） and CSM （Comprehensive Support Maximization）, were introduced to better measure the coverability. The experimental results show that the CRM and CSM algorithms perform better than the MAM （MAximize Minimum weight） and MIM （Minimize Maximum weight） algorithms, respectively. In addition, the TWS algorithm can provide a lower bound detection possibility that accurately reflects the coverability of the wireless sensor nodes. Both theoretical and experimental analyses show that the proposed CRM, TWS, and CSM algorithms have O（n2） complexity.

Etiological Analysis of a Food Poisoning Caused by Staphylococcus Aureus

Objective To analyze the etiology of food poisoning,provide data support for food poisoning treatment,and protect people’s health.Methods RT-PCR was used to screen suspicious food and vomit.An enzyme-linked immunofluorescence assay(ELFA)was used to detect Staphylococcus aureus enterotoxin.RT-PCR was used to detect enterotoxin genotypes.An automatic drug sensitivity reading system was used for drug resistance analysis and mass spectrometry identification.Results Staphylococcus aureus were isolated from 5 leftovers and 2 vomitus samples.The enterotoxin types of 7 strains were sed and seen;the drug sensitivity test showed that 7 strains were resistant to penicillin,and 6 strains were inducible clindamycin resistant.Conclusion This is a food poisoning event caused by Staphylococcus aureus,which produces sed and sees enterotoxins.The isolated strains have different degrees of drug resistance.

Advanced Aramid Fibrous Materials:Fundamentals,Advances,and Beyond

Aramid fibers(AFs)are widely applied in many cutting-edge fields,due to their excellent comprehensive performance.Ongoing research efforts are therefore underway to expand the applicability by designing more environmentally friendly and low-cost synthesis methods,incorporating new chemical components in the skeletons or internal structures of polyamide to enhance their processability and functionality.Despite being at the forefront of scientific research,there are fewer reviews that comprehensively summarize the latest progress of AFs.This review focuses on the fundamental research of AFs since their inception and summarizes the advanced progress and applications of AFs.Firstly,the synthesis mechanism and methods of AFs and their structure-property relationship are comprehensively discussed.Subsequently,we review the recent progress in surface functionalization of AFs by using advanced micro-nanoscale modification strategies to enhance the interface properties and ultraviolet(UV)-resistance properties,and summarize the advantages and disadvantages of various modified methods.Then,applications of AF and aramid nanofiber(ANF)in various fields are discussed.Finally,the possible challenges and outlooks toward the future development of AFs are highlighted,which is expected to provide new insights for the next-generation advanced functional AF materials and facilitate the industrialization development level for high-performance AFs and their composites.

Advances in colored carbon-based fiber materials and their emerging applications

Carbon-based fiber materials are widely used in aerospace,military,and electronics owing to their outstanding comprehensive properties.However,the high degree of crystallization and chemical inertness of their surfaces impede the coloring of such materials by traditional dyeing methods,thereby limiting their application in a broader field.Exploring advanced micro/nano-processing technology for colored carbon-based fiber materials has become a growing interdisciplinary research area in recent years.Therefore,this review comprehensively discusses the structure‒color‒function relationships of carbon-based fiber materials.The structure of carbon-based fiber materials and their properties responsible for challenges in coloring by traditional dyeing methods are discussed.Moreover,the color-generating mechanisms underlying the display of structural colors by living organisms due to fundamental optical phenomena,including thin/multilayer-film interference,diffraction grating,scattering,and photonic crystals,are described.Furthermore,recent progress in bio-inspirated colored carbon-based fiber materials prepared via advanced micro/nanoscale manufacturing strategies is reviewed.In addition,emerging applications of colored carbon-based fiber materials in various fields are presented.Finally,the possible challenges and future directions for the design,large-scale production,and application of colored carbon-based fibermaterials and their composites are discussed,aiming to promote the material design of innovative next-generation systems and research in the advanced material and related engineering fields.