Multifunctional antibacterial photodynamic therapy is a promising method to combat regular and multidrug‐resistant bacteria. In this work, eosin Y (EY)‐based antibacterial polycations (EY‐QEGEDR, R ...= CH3 or C6H13) with versatile types of functional components including quaternary ammonium, photosensitizer, primary amine, and hydroxyl species are readily synthesized based on simple ring‐opening reactions. In the presence of light irradiation, such antibacterial polymers exhibit high antibacterial efficiency against both Escherichia coli and Staphylococcus aureus. In particular, EY‐QEGEDR elicits a remarkable synergistic antibacterial activity owing to the combined photodynamic and quaternary ammonium antibacterial effects. Due to its rich primary amine groups, EY‐QEGEDR also can be readily coated on different substrates, such as glass slides and nonwoven fabrics via an adhesive layer of polydopamine. The resultant surface coating of EY‐QEGEDCH3 (s‐EY‐QEGEDCH3) produces excellent in vitro antibacterial efficacy. The plentiful hydroxyl groups impart s‐EY‐QEGEDCH3 with potential antifouling capability against dead bacteria. The antibacterial polymer coatings also demonstrate low cytotoxicity and good hemocompatibility. More importantly, s‐EY‐QEGEDCH3 significantly enhances in vivo therapeutic effects on an infected rat model. The present work provides an efficient strategy for the rational design of high‐performance antibacterial materials to fight biomedical device‐associated infections.
Polycationic synergistic antibacterial agents with versatile functional components including quaternary ammonium, photosensitizer, primary amine, and hydroxyl species are proposed for effective biomedical applications.
We report a facile green approach for in situ growth of silver nanoparticles (AgNPs) on the surface of graphene quantum dots (GQDs). GQDs serve as both reducing agent and stabilizer, and no ...additional reducing agent and stabilizer is necessary. The GQDs/AgNPs hybrid exhibits a superior absorbance fading response toward the reduction of H2O2. A simple colorimetric procedure is thus proposed for ultrasensitive detection of H2O2 without additional chromogenic agent. It provides a record detection limit of 33 nM for the detection of H2O2 by the AgNPs-based sensing system. This colorimetric sensing system is further extended to the detection of glucose in combination with the specific catalytic effect of glucose oxidase for the oxidation of glucose and formation of H2O2, giving rise to a detection limit of 170 nM. The favorable performances of the GQDs/AgNPs hybrid are due to the peroxidase-like activity of GQDs.
Objective
This review aims to summarize the latest application of optical coherence tomography (OCT) in oral mucosal diseases, promoting an accurate and earlier diagnosis of such disorders, which are ...difficult to be differentiated.
Subjective and Methods
References on the application of OCT in oral mucosal diseases were mainly obtained from PubMed, Embase, Web of Science and Scopus databases, using the keywords: “optical coherence tomography and ‘oral mucosa/oral cancers/oral potentially malignant diseases/oral lichen planus/oral leukoplakia/oral erythroplakia/discoid lupus erythematosus/oral autoimmune bullous diseases/oral ulcers/erythema multiforme/oral mucositis’”.
Results
It is found that OCT is showing a promising application potential in the early detection, diagnosis, differential diagnosis, monitoring of oral cancer and oral dysplastic lesions, as well as the delineation of tumor margins. OCT is also playing an increasingly important role in the diagnosis of oral potentially malignant disorders, oral mucosal bullous diseases, oral ulcerative diseases, erythema multiforme, and the early detection of oral mucositis.
Conclusion
Optical coherence tomography, as a novel optical technique featured by real‐time, noninvasive, dynamic and high‐resolution imaging, is of great use to serve as an adjunct tool for the diagnosis, differential diagnosis, monitoring and therapy evaluation of oral mucosal diseases.
In repetitive control (RC), the enhanced servo performance at the fundamental frequency and its higher order harmonics is usually followed by undesired error amplifications at other frequencies. In ...this paper, we discuss a new structural configuration of the internal model in RC, wherein designers have more flexibility in the repetitive loop-shaping design, and the amplification of nonrepetitive errors can be largely reduced. Compared to conventional RC, the proposed scheme is especially advantageous when the repetitive task is subject to large amounts of nonperiodic disturbances. An additional benefit is that the transient response of this plug-in RC can be easily controlled, leading to an accelerated transient with reduced overshoots. Verification of the algorithm is provided by simulation of a benchmark regulation problem in hard disk drives, and by tracking-control experiments on a laboratory testbed of an industrial wafer scanner.
Capacity of Gaussian Many-Access Channels Chen, Xu; Chen, Tsung-Yi; Guo, Dongning
IEEE transactions on information theory,
06/2017, Letnik:
63, Številka:
6
Journal Article
Recenzirano
Odprti dostop
Classical multiuser information theory studies the fundamental limits of models with a fixed (often small) number of users as the coding blocklength goes to infinity. This paper proposes a new ...paradigm, referred to as many-user information theory, where the number of users is allowed to grow with the blocklength. This paradigm is motivated by emerging systems with a massive number of users in an area, such as the Internet of Things. The focus of this paper is the many-access channel model, which consists of a single receiver and many transmitters, whose number increases unboundedly with the blocklength. Moreover, an unknown subset of transmitters may transmit in a given block and need to be identified as well as decoded by the receiver. A new notion of capacity is introduced and characterized for the Gaussian many-access channel with random user activities. The capacity can be achieved by first detecting the set of active users and then decoding their messages. The minimum cost of identifying the active users is also quantified.
The automated classification of heart sounds plays a significant role in the diagnosis of cardiovascular diseases (CVDs). With the recent introduction of medical big data and artificial intelligence ...technology, there has been an increased focus on the development of deep learning approaches for heart sound classification. However, despite significant achievements in this field, there are still limitations due to insufficient data, inefficient training, and the unavailability of effective models. With the aim of improving the accuracy of heart sounds classification, an in-depth systematic review and an analysis of existing deep learning methods were performed in the present study, with an emphasis on the convolutional neural network (CNN) and recurrent neural network (RNN) methods developed over the last five years. This paper also discusses the challenges and expected future trends in the application of deep learning to heart sounds classification with the objective of providing an essential reference for further study.
One great challenge in understanding the history of life is resolving the influence of environmental change on biodiversity. Simulated annealing and genetic algorithms were used to synthesize data ...from 11,000 marine fossil species, collected from more than 3000 stratigraphic sections, to generate a new Cambrian to Triassic biodiversity curve with an imputed temporal resolution of 26 ± 14.9 thousand years. This increased resolution clarifies the timing of known diversification and extinction events. Comparative analysis suggests that partial pressure of carbon dioxide (
co
) is the only environmental factor that seems to display a secular pattern similar to that of biodiversity, but this similarity was not confirmed when autocorrelation within that time series was analyzed by detrending. These results demonstrate that fossil data can provide the temporal and taxonomic resolutions necessary to test (paleo)biological hypotheses at a level of detail approaching those of long-term ecological analyses.
•This paper provides a comprehensive review of FMEA using MCDM methods.•The 169 articles were found and classified according to the used MCDM methods.•The risk factors, risk factor weighting methods ...and risk assessment methods are analyzed.•Directions for future research to adopt MCDM methods for FMEA are provided.
Failure mode and effect analysis (FMEA) is a proactive reliability management technique extensively utilized in a variety of fields. To enhance the effectiveness of FMEA, a great many multi-criteria decision making (MCDM) methods have been applied for properly evaluating the risk of failure modes over the past two decades. However, there is a lack of study concerning systematic literature review and classification of the researches on this topic. This article aims to provide a comprehensive review of the FMEA studies using MCDM approaches for evaluation and prioritization of failure modes. To do so, a total of 169 journal papers extracted from the online database over the period of 1998–2018 were selected and reviewed. These publications were classified into 10 categories according to the used MCDM methods, and analyzed in regard to the risk factors, risk factor weighting methods, and risk assessment methods in FMEA. Furthermore, a bibliometric analysis was performed based on the frequency of MCDM methods, number of citations, year of publication, appeared journals, country of origin and application areas. This research supports academics and practitioners in effectively adopting MCDM methods to overcome the deficiencies of the traditional FMEA and provides an insight into its state-of-the-art.
By analogy with Internet of things, Internet of vehicles (IoV) that enables ubiquitous information exchange and content sharing among vehicles with little or no human intervention is a key enabler ...for the intelligent transportation industry. In this paper, we study how to combine both the physical and social layer information for realizing rapid content dissemination in device-to-device vehicle-to-vehicle (D2D-V2V)-based IoV networks. In the physical layer, headway distance of vehicles is modeled as a Wiener process, and the connection probability of D2D-V2V links is estimated by employing the Kolmogorov equation. In the social layer, the social relationship tightness that represents content selection similarities is obtained by Bayesian nonparametric learning based on real-world social big data, which are collected from the largest Chinese microblogging service Sina Weibo and the largest Chinese video-sharing site Youku. Then, a price-rising-based iterative matching algorithm is proposed to solve the formulated joint peer discovery, power control, and channel selection problem under various quality-of-service requirements. Finally, numerical results demonstrate the effectiveness and superiority of the proposed algorithm from the perspectives of weighted sum rate and matching satisfaction gains.
As the penetration level of distributed photovoltaic (PV) systems keeps increasing in distribution networks, overvoltage due to reverse power flow is an urgent issue to be addressed. This paper ...proposes a voltage regulation method by utilizing the voltage control capability of PV inverters. A novel network partition approach based on a community detection algorithm is presented to realize zonal voltage control in a shorter control response time using the minimum amount of reactive power compensation and active power curtailment. An improved modularity index that considers local reactive power balance is introduced to partition a distribution network into several clusters/communities with PVs based on the node voltage sensitivity analysis. An optimal reactive and active power control strategy is proposed for voltage control in each cluster. The voltage management of the overall system can be achieved by controlling each cluster separately. The proposed approach is applied to the voltage control of a practical 10 kV, 37-node feeder. Case studies on the real distribution network and a modified IEEE 123-node system are carried out to verify the feasibility and effectiveness of the proposed method.
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