The iron and steel industry (ISI) is energy-intensive and is responsible for approximately 25% of the global direct greenhouse gas (GHG) emissions from industrial sectors. As the largest steel ...producer and consumer, China bears the primary responsibility for saving energy and reducing GHG emissions; accordingly, they have developed many strategies for GHG abatement. However, owing to the high investment costs and long equipment service lives, the ISI must carefully weigh the cost and emission reduction potential of these approaches. This review discusses research findings aimed at technological improvements and ultra-low carbon technologies relevant to the ISI, emphasizing their cost-effectiveness and development prospects. Based on the life cycle analysis method, this review establishes a comprehensive analytical framework to integrate the results from different studies to consider more factors in the design of GHG emission reduction strategies. The results indicate that the full application of mainstream technological improvements can reduce CO2 emissions by approximately 43%. Furthermore, combining these strategies with ultra-low carbon technologies can achieve a reduction of 80%–95%. The marginal cost reduction associated with implementing such technological improvements is in the range of −5 to 0.5 USD/kgCO2. Applying carbon capture, utilization, and storage strategies or hydrogen-based technologies in China's ISI for deep decarbonization scenarios is expected to lead to cost reductions between 12 and 35 billion USD by 2050. We propose that China's ISI requires technological improvements in the short term and should prioritize ultra-low carbon technology development for the long term.
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•Discussion of researches and pilot projects aimed at technological improvements of the iron and steel industry.•Review and potential of ultra-low carbon emission technologies in the iron and steel industry.•Overview of energy consumption and GHG emissions of the iron and steel industry.•Development strategies designed based on analysis of cost and GHG mitigation potential.
To support the development of miniaturized photoacoustic gas sensors, a fully coupled finite element model for a frequency response simulation of cantilever-based photoacoustic gas sensors is ...introduced in this paper. The model covers the whole photoacoustic process from radiation absorption to pressure transducer vibration, and considers viscous damping loss. After validation with experimental data, the model was further applied to evaluate the possibility of further optimization and miniaturization of a previously reported sensor design.
Merging mobile edge computing (MEC) functionality with the dense deployment of base stations (BSs) provides enormous benefits such as a real proximity, low latency access to computing resources. ...However, the envisioned integration creates many new challenges, among which mobility management (MM) is a critical one. Simply applying existing radio access-oriented MM schemes leads to poor performance mainly due to the co-provisioning of radio access and computing services of the MEC-enabled BSs. In this paper, we develop a novel user-centric energy-aware mobility management (EMM) scheme, in order to optimize the delay due to both radio access and computation, under the long-term energy consumption constraint of the user. Based on Lyapunov optimization and multi-armed bandit theories, EMM works in an online fashion without future system state information, and effectively handles the imperfect system state information. Theoretical analysis explicitly takes radio handover and computation migration cost into consideration and proves a bounded deviation on both the delay performance and energy consumption compared with the oracle solution with exact and complete future system information. The proposed algorithm also effectively handles the scenario in which candidate BSs randomly switch ON/OFF during the offloading process of a task. Simulations show that the proposed algorithms can achieve close-to-optimal delay performance while satisfying the user energy consumption constraint.
The (ultra-)dense deployment of small-cell base stations (SBSs) endowed with cloud-like computing functionalities paves the way for pervasive mobile edge computing, enabling ultra-low latency and ...location-awareness for a variety of emerging mobile applications and the Internet of Things. To handle spatially uneven computation workloads in the network, cooperation among SBSs via workload peer offloading is essential to avoid large computation latency at overloaded SBSs and provide high quality of service to end users. However, performing effective peer offloading faces many unique challenges due to limited energy resources committed by self-interested SBS owners, uncertainties in the system dynamics, and co-provisioning of radio access and computing services. This paper develops a novel online SBS peer offloading framework, called online peer offloading (OPEN), by leveraging the Lyapunov technique, in order to maximize the long-term system performance while keeping the energy consumption of SBSs below individual long-term constraints. OPEN works online without requiring information about future system dynamics, yet provides provably near-optimal performance compared with the oracle solution that has the complete future information. In addition, this paper formulates a peer offloading game among SBSs and analyzes its equilibrium and efficiency loss in terms of the price of anarchy to thoroughly understand SBSs' strategic behaviors, thereby enabling decentralized and autonomous peer offloading decision making. Extensive simulations are carried out and show that peer offloading among SBSs dramatically improves the edge computing performance.
Hyperoside is a natural flavonol glycoside in various plants, such as Crataegus pinnatifida Bge, Forsythia suspensa, and Cuscuta chinensis Lam. Medical research has found that hyperoside possesses a ...broad spectrum of biological activities, including anticancer, anti‐inflammatory, antibacterial, antiviral, antidepressant, and organ protective effects. These pharmacological properties lay the foundation for its use in treating multiple diseases, such as sepsis, arthritis, colitis, diabetic nephropathy, myocardial ischemia–reperfusion, pulmonary fibrosis, and cancers. Hyperoside is obtained from the plants and chemical synthesis. This study aims to provide a comprehensive overview of hyperoside on its sources and biological activities to provide insights into its therapeutic potential, and to provide a basis for high‐quality studies to determine the clinical efficacy of this compound.
Cholesterol and its metabolites (precursors and derivatives) play an important role in cancer. In recent years, numerous studies have reported the functions of cholesterol metabolism in the ...regulation of tumor biological processes, especially oncogenic signaling pathways, ferroptosis, and tumor microenvironment. Preclinical studies have over the years indicated the inhibitory effects of blocking cholesterol synthesis and uptake on tumor formation and growth. Besides, some new cholesterol metabolic molecules such as SOAT1, SQLE, and NPC1 have recently emerged as promising drug targets for cancer treatment. Here, we systematically review the roles of cholesterol and its metabolites, and the latest advances in cancer therapy targeting cholesterol metabolism.
The arrival of the big data era makes the amount of data explosive growth, which puts forward new challenges and demands for computer network technology, and the integration of big data and network ...technology has become an important trend. This paper uses the optimization strategy and the elimination mechanism of the genetic algorithm to optimize the inertia weight and particle position speed updating mechanism of the particle swarm algorithm and combines the searching method of the Tennessee whisker algorithm with the sharing mechanism of the particle swarm algorithm to achieve the optimal data searching ability. Finally, the improved artificial intelligence algorithm and MapReduce are combined to improve the performance of the computer neural network algorithm in big data processing. The average data redundancy rate of this paper’s algorithm for big data processing is only 1.18%, and the resource integration checking rate always exceeds 85%, according to simulation experiments. In addition, the algorithm also shows good performance in practical applications, and it can achieve accurate classification of big data labels in big data label classification tasks while maintaining a low energy overhead. Meanwhile, it can accurately recognize electronic medical record data in large medical databases. Big data processing can benefit greatly from the proposed neural network algorithm in this paper.
This study on the fusion of deep convolutional neural network (CNN) and extended short-term memory network (LSTM) aims to improve the efficiency and accuracy of broken information recovery. The ...challenges faced by traditional information recovery techniques are addressed through improved algorithms. The research methodology includes constructing CNN models to automatically extract features and combining LSTM networks to process complex time-series data. We conducted a detailed experimental evaluation of the CNN-LSTM fusion algorithm, including recovery of different types of corrupted data, and compared it with other algorithms. The results show that the CNN-LSTM fusion algorithm has the highest structural similarity (0.9545) and the most minor normalized mean square error (0.0016) for recovering broken video information, outperforming the methods using CNN or LSTM alone. The fusion algorithm dramatically reduces computation time and resource consumption for processing complex datasets. The combination of CNN and LSTM significantly improves the performance of broken information recovery, especially in processing video and audio data, and provides new ideas for future information processing techniques.
This study was aimed at investigating the effects of lncRNA AK139328 on myocardial ischaemia/reperfusion injury (MIRI) in diabetic mice. Ischaemia/reperfusion (I/R) model was constructed in normal ...mice (NM) and diabetic mice (DM). Microarray analysis was utilized to identify lncRNA AK139328 overexpressed in DM after myocardial ischaemia/reperfusion (MI/R). RT‐qPCR assay was utilized to investigate the expressions of lncRNA AK139328 and miR‐204‐3p in cardiomyocyte and tissues. Left ventricular end diastolic diameter (LVEDD), left ventricular end systolic diameter (LVESD), left ventricular ejection fraction (LVEF) and fractioning shortening (FS) were obtained by transthoracic echocardiography. Haematoxylin‐eosin (HE) staining and Masson staining were utilized to detect the damage of myocardial tissues degradation of myocardial fibres and integrity of myocardial collagen fibres. Evans Blue/TTC staining was used to determine the myocardial infarct size. TUNEL staining was utilized to investigate cardiomyocyte apoptosis. The targeted relationship between lncRNA AK139328 and miR‐204‐3p was confirmed by dual‐luciferase reporter gene assay. MTT assay was used for analysis of cardiomyocyte proliferation. Western blot was utilized to investigate the expression of alpha smooth muscle actin (α‐SMA), Atg7, Atg5, LC3‐II/LC3‐I and p62 marking autophagy. Knockdown of lncRNA AK139328 relieved myocardial ischaemia/reperfusion injury in DM and inhibited cardiomyocyte autophagy as well as apoptosis of DM. LncRNA AK139328 modulated miR‐204‐3p directly. MiR‐204‐3p and knockdown of lncRNA AK139328 relieved hypoxia/reoxygenation injury via inhibiting cardiomyocyte autophagy. Silencing lncRNA AK139328 significantly increased miR‐204‐3p expression and inhibited cardiomyocyte autophagy, thereby attenuating MIRI in DM.
Tapetum development and pollen production are regulated by a complex transcriptional network that consists of a group of tapetum-specific Arabidopsis transcription factors (TFs). Among these TFs, ...DEFECTIVE IN TAPETAL DEVELOPMENT AND FUNCTION 1 (TDF1) encodes an R2R3 MYB factor, and ABORTED MICROSPORE (AMS) encodes a basic helix-loop-helix (bHLH) factor. However, knowledge regarding the regulatory role of TDF1 in anther development remains limited.
Here, we discovered that TDF1 directly regulates AMS via an AACCT cis-element. We found the precocious AMS transcript and absence of AMS protein in ams
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gpTDF1:AMS-FLAG lines, suggesting the timing of the TDF1-regulated AMS expression is a prerequisite for AMS functioning.
We found that TDF1 interacts with AMS. Additionally, the TDF1–AMS complex additively promotes the expression of AMS-regulated genes, suggesting that TDF1 and AMS regulate the downstream genes through a feed-forward loop.
EPXB5, encoding a beta-expansin family protein, is another direct target of TDF1, and it is highly expressed in the tapetum and pollen grains. The TDF1–AMS complex acts in concert to activate EXPB5 expression through a feed-forward loop. The identification of the regulatory pathway between TDF1 and AMS provides an interlocked feed-forward loop circuit that precisely regulates the transcriptional cascades that support anther development.
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