Recently, dendritic mesoporous silica nanoparticles with widespread applications have attracted great interest. Despite many publications (>800), the terminology “dendritic” is ambiguous. ...Understanding what possible “dendritic structures” are, their formation mechanisms and the underlying structure–property relationship is fundamentally important. With the advance of characterization techniques such as electron tomography, two types of tree‐branch‐like and flower‐like structures can be distinguished, both described as “dendritic” in the literature. In this Review, we start with the definition of “dendritic”, then provide critical analysis of reported dendritic silica nanoparticles according to their structural classification. We update the understandings of the formation mechanisms of two types of “dendritic” nanoparticles, highlighting how to control their structural parameters. Applications of dendritic mesoporous nanoparticles are also reviewed with a focus on the biomedical field, providing new insights into the structure–property relationship in this family of nanomaterials.
A comprehensive review on dendritic mesoporous silica nanoparticles (DMSNs) with radial pores is provided. Perspectives into their formation mechanisms, synthesis–structure–property relationships and future research directions with a focus on biomedical applications are presented.
The effectiveness and longevity of IoT infrastructures heavily depend on the limitations posed by communication, multi-hop data transfers, and the inherent difficulties of wireless links. In dealing ...with these challenges, routing, and data transmission procedures are critical. Among the fundamental concerns are the attainment of energy efficiency and an ideal distribution of loads among sensing devices, given the restricted energy resources at the disposal of IoT devices. To meet these challenges, the present research suggests a novel hybrid energy-aware IoT routing approach that mixes the Particle Swarm Optimization (PSO) algorithm and fuzzy clustering. The approach begins with a fuzzy clustering algorithm to initially group sensor nodes by their geographical location and assign them to clusters determined by a certain probability. The proposed method includes a fitness function considering energy consumption and distance factors. This feature guides the optimization process and aims to balance energy efficiency and data transmission distance. The hierarchical topology uses the advanced PSO algorithm to identify the cluster head nodes. The MATLAB simulator shows that our method outperforms previous approaches. Various metrics have demonstrated significant improvements over DEEC and LEACH. The method reduces energy consumption by 52% and 16%, improves throughput by 112% and 10%, increases packet delivery rates by 83% and 15%, and extends the network lifespan by 48% and 27%, respectively, compared to DEEC and LEACH approaches.
Cloud computing has emerged as one of the most promising technologies for meeting rising computing needs. However, high-performance computing systems are more likely to fail due to the proliferation ...of components and servers. If a sub-system fails, the entire system may not be functional. In this regard, the occurrence of faults is tolerable using an efficient fault-tolerant method. Since cloud computing involves storing data on a remote network, system failures and congestion are the most common causes of faults. The paper presents a new approach to adopting a fault-tolerant mechanism that adaptively monitors health to detect faults, handles faults using a migration technique, and avoids network congestion. With the advantage of the Ant Colony Optimization (ACO) algorithm and active clustering, the load is distributed evenly in data centers. Simulation results indicate that our algorithm outperforms previous algorithms regarding total execution time and imbalance degree up to 10% and 17%, respectively.
This study aims to analyze whether information and communication technology (ICT) and renewable energy (RE) can assist in enhancing environmental quality. This study employs time series data from ...1990 to 2019 using econometric techniques. The results show that the use of ICTs in the US, UK, China, Russia, Canada, Australia, Sweden, Norway, Switzerland, and Italy has decreased environmental protection. The results reveal that RE use enhances the sustainability of the environment regardless of the sample size or surrogate utilized for ICT. Impulse response functions show that, on average, the influence of ICT and RE lasts between one and seven years. The error correction model segmentation study verified that ICT and RE contribute to the volatility of carbon dioxide emissions. There is strong evidence that carbon dioxide emissions, ICT, and RE use have a bidirectional causal relationship in most circumstances. Several ICTs and RE strategies have been established and explored to profit from the possible positive influence of ICT and RE usage on environmental quality.
•We analyze whether ICT and renewable energy helps enhance environmental quality.•This study employs time series data from 1990 to 2019 using econometric techniques.•Results show that the use of ICTs has led to decreased environmental protection.•CO2 emissions, ICT, and RE use have a bidirectional causal relationship.
It is vital to assess the lives of newly developed products by using failure data from various testing environments. In the current methods, two steps are generally included. The first step is ...transforming the failure data under one testing environment into the actual working environment, and the second step is integrating all failure data under the actual working environment into a unified result. However, most available methods cannot use information that includes part failure data and part expert knowledge simultaneously. To resolve the above issue, based on the belief rule base (BRB) and the evidential reasoning (ER) approach, a new BRB-ER-based model is proposed, where the BRB is used to transform the failure data from one testing environment into the actual working environment. The ER approach, which is adopted to aggregate the failure data from different testing environments, is used to assess the life of a product. To conclude, the BRB-ER-based model is applied to represent and integrate asynchronous multisource information. In the proposed model, the initial BRB system is constructed based on experts' knowledge, which results in uncertainty because of the ambiguous nature of human judgment and calls for training the parameters in the BRB-ER-based model. Therefore, an optimal algorithm that employs the differential evolutionary algorithm is proposed. The proposed model and the optimal algorithm operate in an integrated manner to improve the assessment precision by using both failure data and expert knowledge effectively. A case study in three scenarios and use of the conventional approach is examined to demonstrate the capability and potential applications of the new BRB-ER-based model.
Abstract
Objectives
To identify a novel plasmid-mediated colistin resistance gene in Klebsiella pneumoniae isolated from chickens in China.
Methods
WGS was used to identify a novel colistin ...resistance gene. The transferability of plasmids carrying mcr-7.1 was investigated by conjugation experiments. The expression of the mcr-7.1 gene was examined using an expression vector.
Results
A novel plasmid-mediated colistin resistance gene mcr-7.1, sharing 70% amino acid identity with the mcr-3 gene, was identified in three K. pneumoniae strains isolated from chickens in China. The mcr-7.1 gene was found in an IncI2-type plasmid (pSC20141012) that co-harboured the blaCTX-M-55 gene in one isolate. pSC20141012 can be transferred from K. pneumoniae SC20141012 to Escherichia coli J53Azr, exhibiting a ≥8-fold increase in colistin MIC compared with the recipient E. coli J53Azr.
Conclusions
We identified a novel plasmid-mediated colistin resistance gene named mcr-7.1 in K. pneumoniae in China. The prevalence of mcr-7.1 in various species of human and animal origin needs to be investigated immediately.
A human-induced rise in temperatures is exacerbating droughts and other adverse weather events. Fossil fuels as a primary energy source contribute to global warming. It is, therefore, necessary to ...boost the number of renewable energy initiatives. To better comprehend how to improve renewable energy initiatives, simultaneous evaluation of a range of influential factors is required. This study examined financial development, economic progress, and energy pricing to understand how they affect energy consumption. Using the nonlinear autoregression distributed lag model, we analyzed the effect of financial inclusion on renewable energy consumption in China's 30 provinces from 2000 to 2020. The data showed that financial development has a considerable impact on renewable energy use. The findings of this study revealed that every 1% increase in financial development leads to a 0.24% increase in renewable energy use. This study's primary goal is to offer China a framework for increasing renewable energy investments that are socially and economically viable. This study also paves the way for other nations that import energy. As a result, it will be easier to meet sustainability targets if more projects employ renewable energy after this pandemic.
•There is a dire need to measure the relationship between financial inclusion and renewable energy development.•Every 1% increase in financial development leads to a 0.24% increase in renewable energy use in case of China.•Every 1% increase in the urban population leads to an increase in renewable energy by 1.22%.•Financial development, renewable energy use is negatively associated with a rise in income disparity.•A 1% increase in economic disparity is associated with a 0.58% decrease in the use of renewable energy.
Within contemporary hadron physics there are two common methods for determining the momentum-dependence of the interaction between quarks: the top-down approach, which works toward an ab initio ...computation of the interaction via direct analysis of the gauge-sector gap equations; and the bottom-up scheme, which aims to infer the interaction by fitting data within a well-defined truncation of those equations in the matter sector that are relevant to bound-state properties. We unite these two approaches by demonstrating that the renormalisation-group-invariant running-interaction predicted by contemporary analyses of QCD's gauge sector coincides with that required in order to describe ground-state hadron observables using a nonperturbative truncation of QCD's Dyson–Schwinger equations in the matter sector. This bridges a gap that had lain between nonperturbative continuum-QCD and the ab initio prediction of bound-state properties.
Tumor erosion and metastasis can invade surrounding tissues, damage nerves, and sensitize the peripheral primary receptors, inducing pain, which can potentially worsen the suffering of patients with ...cancer. Reception and transmission of sensory signal receptors, abnormal activation of primary sensory neurons, and activation of glial cells are involved in cancer pain. Therefore, exploring promising therapeutic methods to suppress cancer pain is of great significance. Various studies have found that the use of functionally active cells is a potentially effective way to relieve pain. Schwann cells (SCs) act as small, biologically active pumps that secrete pain‐relieving neuroactive substances. Moreover, SCs can regulate the progression of tumor cells, including proliferation and metastasis, through neuro‐tumor crosstalk, which emphasizes the critical role of SCs in cancer and cancer pain. The mechanisms by which SCs repair injured nerves and exert analgesia include neuroprotection, neurotrophy, nerve regeneration, neuromodulation, immunomodulation, and enhancement of the nerve‐injury microenvironment. These factors may ultimately restore the damaged or stimulated nerves and contribute to pain relief. Strategies for pain treatment using cell transplantation mainly focus on analgesia and nerve repair. Although these cells are in the initial stages of nerve repair and pain, they open new avenues for the treatment of cancer pain. Therefore, this paper discusses, for the first time, the possible mechanism of SCs and cancer pain, and new strategies and potential problems in cancer pain treatment.
Main Points
Further outline the biological characteristics of SCs.
Further discussed and summarized the role of SCs in cancer.
Provided up‐to‐date data support for the possible mechanism of SCs and cancer pain.
For the first time, the therapeutic effect of SCs in cancer pain was explored.
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