Application of nanotechnology to dentistry:Impact of graphene nanocomposites on clinical air quality

Concerns about air quality in dental clinics where aerosol generation during procedures poses significant health risks,have prompted investigations on advanced disinfection technologies.This editorial describes the strengths and limitations of ventilation and aerosol control measures in dental offices,especially with respect to the use of graphene nanocomposites.The potential of graphene nanocomposites as an innovative solution to aerosol-associated health risks is examined in this review due to the unique properties of graphene(e.g.,high con-ductivity,mechanical strength,and antimicrobial activity).These properties have produced promising results in various fields,but the application of graphene in dentistry remains unexplored.The recent study by Ju et al which was published in World Journal of Clinical Cases evaluated the effectiveness of graphene-based air disinfection systems in dental clinics.The study demonstrated that graphene-based disinfection techniques produced significant reductions in suspended particulate matter and bacterial colony counts,when co-mpared with traditional methods.Despite these positive results,challenges such as material saturation,frequency of filter replacement,and associated costs must be addressed before widespread adoption of graphene-based disinfection techniques in clinical practice.Therefore,there is need for further research on material structure optimization,long-term safety evaluations,and broader clinical applications,in order to maximize their positive impact on public health.

Exploring Deep Learning Methods for Computer Vision Applications across Multiple Sectors:Challenges and Future Trends

Computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other media.Deep learning(DL)methods are more successful than other traditional machine learning(ML)methods inCV.DL techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face recognition.In this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is presented.The sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and CV.This review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer Discrimination from CT Images

This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold clinical significance. Therefore, it may be premature to consider replacing CNNs with ViTs in this specific application.

Clinical Application of Preliminary Breast Cancer Screening for Dense Breasts Using Real-Time AI-Powered Ultrasound with Deep-Learning Computer Vision

Objective:We propose a solution that is backed by cloud computing,combines a series of AI neural networks of computer vision;is capable of detecting,highlighting,and locating breast lesions from a live ultrasound video feed,provides BI-RADS categorizations;and has reliable sensitivity and specificity.Multiple deep-learning models were trained on more than 300,000 breast ultrasound images to achieve object detection and regions of interest classification.The main objective of this study was to determine whether the performance of our Al-powered solution was comparable to that of ultrasound radiologists.Methods:The noninferiority evaluation was conducted by comparing the examination results of the same screening women between our AI-powered solution and ultrasound radiologists with over 10 years of experience.The study lasted for one and a half years and was carried out in the Duanzhou District Women and Children's Hospital,Zhaoqing,China.1,133 females between 20 and 70 years old were selected through convenience sampling.Results:The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value were 93.03%,94.90%,90.71%,92.68%,and 93.48%,respectively.The area under the curve(AUC)for all positives was 0.91569 and the AUC for all negatives was 0.90461.The comparison indicated that the overall performance of the AI system was comparable to that of ultrasound radiologists.Conclusion:This innovative AI-powered ultrasound solution is cost-effective and user-friendly,and could be applied to massive breast cancer screening.

Night Vision Characteristics and Application of MTV 2821CB CCD Camera

Aim To describe accumulating frames characteristics of CCD camera as a night vision detector. Methods Utilizing CCD external trigger, computer video capture card and image processing software, the image accumulation was made. Results The detection of the static object image whose illuminance on the CCD FPA(focal plane array) was less than 3 7×10 -5 lx was realized and the image's resolution of 300?TV lines was achieved. Conclusion This experimental system can provide a kind of night vision device capable of detecting the static object at low light level and with low cost compared to an image intensifier.

Application of Computer Vision Technique to Maize Variety Identification

Variety identification is important for maize breeding, processing and trade. The computer vision technique has been widely applied to maize variety identification. In this paper, computer vision technique has been summarized from the following technical aspects including image acquisition, image processing, characteristic parameter extraction, pattern recognition and programming softwares. In addition, the existing problems during the application of this technique to maize variety identification have also been analyzed and its development tendency is forecasted.

The evolution of robotics:research and application progress of dental implant robotic systems

The use of robots to augment human capabilities and assist in work has long been an aspiration.Robotics has been developing since the 1960s when the first industrial robot was introduced.As technology has advanced,robotic-assisted surgery has shown numerous advantages,including more precision,efficiency,minimal invasiveness,and safety than is possible with conventional techniques,which are research hotspots and cutting-edge trends.This article reviewed the history of medical robot development and seminal research papers about current research progress.Taking the autonomous dental implant robotic system as an example,the advantages and prospects of medical robotic systems would be discussed which would provide a reference for future research.

A Review of Multifunctional Nanocomposite Fibers:Design,Preparation and Applications

Nanocomposite fibers are fibrous materials with specific properties and functionalities,which are prepared by introducing nanomaterials or nanostructures in the fibers.Polymeric nanocomposite fibers exhibit multiple functionalities,showing great application potential in healthcare,aerospace,mechanical engineering,and energy storage.Here,six functionalities of polymer nanocomposite fibers are reviewed:mechanical reinforcement,resistance to electromagnetic interference and flame,thermal and electrical conduction,generation of far-infrared ray,negative ion and electricity,energy storage,and sensing.For each functionality,the fiber component selection and preparation methods are summarized.The commonly used polymers comprise natural and synthetic polymers,and typical nanomaterials include carbon-based,polymer-based,metal-based,and metal oxide-based ones.Various compounding strategies and spinning approaches,such as wet-spinning,melt-spinning,and electrospinning,are introduced.Moreover,the functional properties of fibers fabricated from different constituents and by different strategies are compared,providing a reference for performance optimization.Finally,the prospective directions of research and application are discussed,and possible approaches are suggested to facilitate the development of advanced nanocomposite fibers.

Potential industrial applications of photo/electrocatalysis: Recent progress and future challenges

Nowadays,the rapid development of the social economy inevitably leads to global energy and environmental crisis.For this reason,more and more scholars focus on the development of photocatalysis and/or electrocatalysis technology for the advantage in the sustainable production of high-value-added products,and the high efficiency in pollutants remediation.Although there is plenty of outstanding research has been put forward continuously,most of them focuses on catalysis performance and reaction mechanisms in laboratory conditions.Realizing industrial application of photo/electrocatalytic processes is still a challenge that needs to be overcome by social demand.In this regard,this review comprehensively summarized several explorations in thefield of photo/electrocatalytic reduction towards potential industrial applications in recent years.Special attention is paid to the successful attempts and the current status of photo/electrocatalytic water splitting,carbon dioxide conversion,resource utilization from waste,etc.,by using advanced reactors.The key problems and challenges of photo/electrocatalysis in future industrial practice are also discussed,and the possible development directions are also pointed out from the industry view.

Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

Application of Computer Vision Technology in Agriculture

With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-research progress on diagnosis of agricultural products, water diagnosis, weed identification,product quality testing and grading, agricultural picking and sorting and other as- pects, and finally put forward its existing problems and prospects for the future.

MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

A Review of Contact Electrification at Diversified Interfaces and Related Applications on Triboelectric Nanogenerator

The triboelectric nanogenerator(TENG)can effectively collect energy based on contact electrification(CE)at diverse interfaces,including solid–solid,liquid–solid,liquid–liquid,gas–solid,and gas–liquid.This enables energy harvesting from sources such as water,wind,and sound.In this review,we provide an overview of the coexistence of electron and ion transfer in the CE process.We elucidate the diverse dominant mechanisms observed at different interfaces and emphasize the interconnectedness and complementary nature of interface studies.The review also offers a comprehensive summary of the factors influencing charge transfer and the advancements in interfacial modification techniques.Additionally,we highlight the wide range of applications stemming from the distinctive characteristics of charge transfer at various interfaces.Finally,this review elucidates the future opportunities and challenges that interface CE may encounter.We anticipate that this review can offer valuable insights for future research on interface CE and facilitate the continued development and industrialization of TENG.

The Application of Bilayer Artificial Dermis Combined with VSD Technology in Chronic Wounds

Background: Bilayer artificial dermis promotes wound healing and offers a treatment option for chronic wounds. Aim: Examine the clinical efficacy of bilayer artificial dermis combined with Vacuum Sealing Drainage (VSD) technology in the treatment of chronic wounds. Method: From June 2021 to December 2023, our hospital treated 24 patients with chronic skin tissue wounds on their limbs using a novel tissue engineering product, the bilayer artificial dermis, in combination with VSD technology to repair the wounds. The bilayer artificial dermis protects subcutaneous tissue, blood vessels, nerves, muscles, and tendons, and also promotes the growth of granulation tissue and blood vessels to aid in wound healing when used in conjunction with VSD technology for wound dressing changes in chronic wounds. Results: In this study, 24 cases of chronic wounds with exposed bone or tendon larger than 1.0 cm2 were treated with a bilayer artificial skin combined with VSD dressing after wound debridement. The wounds were not suitable for immediate skin grafting. At 2 - 3 weeks post-treatment, good granulation tissue growth was observed. Subsequent procedures included thick skin grafting or wound dressing changes until complete wound healing. Patients were followed up on average for 3 months (range: 1 - 12 months) post-surgery. Comparative analysis of the appearance, function, skin color, elasticity, and sensation of the healed chronic wounds revealed superior outcomes compared to traditional skin fl repairs, resulting in significantly higher satisfaction levels among patients and their families. Conclusion: The application of bilayer artificial dermis combined with VSD technology for the repair of chronic wounds proves to be a viable method, yielding satisfactory therapeutic effects compared to traditional skin flap procedures.

Comprehensive Evaluation of Flower Border Application Value of New and Superior Plants in Hefei Area

An analytic hierarchy process(AHP)was employed to assess the applicability of 18 new and superior varieties of flowers in Hefei City flower border applications.A total of 12 indicators were selected from three distinct aspects of adaptability,ornamental characteristics and use traits,in order to establish a comprehensive evaluation model.The results demonstrate that grade I(J≥2.685)exhibits excellent application value,encompassing six species of plants,such asHydrangeamacrophylla‘Endless Summer’;grade II(2.684≤J≤2.420)is also of notable application value,encompassing five species of plants,such asCallistemonrigidus;grade III(2.419≤J≤2.615)is of average application value,including five species of plants,such asCrocosmiacrocosmiflora;grade IV(J≤2.16)is of relatively poor application value.The evaluation results may be utilized as a theoretical reference for the promotion of new and superior varieties in the flower border of Hefei.

A review of the research and application of deep learning-based computer vision in structural damage detection

Damage detection is a key procedure in maintenance throughout structures′life cycles and post-disaster loss assessment.Due to the complex types of structural damages and the low efficiency and safety of manual detection,detecting damages with high efficiency and accuracy is the most popular research direction in civil engineering.Computer vision(CV)technology and deep learning(DL)algorithms are considered as promising tools to address the aforementioned challenges.The paper aims to systematically summarized the research and applications of DL-based CV technology in the field of damage detection in recent years.The basic concepts of DL-based CV technology are introduced first.The implementation steps of creating a damage detection dataset and some typical datasets are reviewed.CV-based structural damage detection algorithms are divided into three categories,namely,image classification-based(IC-based)algorithms,object detection-based(OD-based)algorithms,and semantic segmentation-based(SS-based)algorithms.Finally,the problems to be solved and future research directions are discussed.The foundation for promoting the deep integration of DL-based CV technology in structural damage detection and structural seismic damage identification has been laid.

Synthesis and modification strategies of g-C_(3)N_(4) nanosheets for photocatalytic applications

Graphitic carbon nitride nanosheets(CNNs)become the most promising member in the carbon nitride family benefitted from their two-dimensional structural features.Recently,great endeavors have been made in the synthesis and modification of CNNs to improve their photocatalytic properties,and many exciting progresses have been gained.In order to elucidate the fundamentals of CNNs based catalysts and provide the insights into rational design of photocatalysis system,we describe recent progress made in CNNs preparation strategies and their applications in this review.Firstly,the physicochemical properties of CNNs are briefly introduced.Secondly,the synthesis approaches of CNNs are reviewed,including top-down stripping strategies(thermal,gas,liquid,and composite stripping)and bottom-up precursor molecules design strategies(solvothermal,template,and supramolecular self-assembly method).Subsequently,the modification strategies based on CNNs in recent years are discussed,including crystal structure design,doping,surface functionalization,constructing 2D heterojunction,and anchoring single-atom.Then the multifunctional applications of g-C_(3)N_(4) nanosheet based materials in photocatalysis including H_(2) evolution,O_(2) evolution,overall water splitting,H_(2)O_(2) production,CO_(2) reduction,N_(2) fixation,pollutant removal,organic synthesis,and sensing are highlighted.Finally,the opportunities and challenges for the development of high-performance CNNs photocatalytic systems are also prospected.

A review of the application of computer vision technology in aquaculture

In recent years, aquaculture industry in China is developing rapidly, and especially, China has the largest aquaculture area and the most output in the world. In the past, traditional aquaculture mainly depended on manual labour to breed and gain aquatic organisms. However, with the increasing scale of production and the continuous improvement of science and technology, the traditional aquaculture approach has become more and more unsuitable for the development of the times. With the rapid development of computer technology, computer vision technology infiltrates through the traditional aquaculture industry quickly and improves the aquaculture production efficiency .This paper mainly introduces the basic situation of computer vision technology and summarizes the application of computer vision technology in aquaculture industry at home and abroad. The paper concludes with the expectation of application of computer vision in the aquaculture.

Application of Machine Vision to Vehicle Automatic Collision Warning Algorithm

Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system（CWS） can acquire road condition, adjacent vehicle march condition as well as its dynamics performance continuously, then it can forecast the oncoming potential collision and give a warning. Based on the analysis of driver＇s driving behavior, algorithm＇s warning norms are determined. Based on warning norms adopting machine vision method, the cooperation collision warning algorithm（CWA） model with multi-input and multi-output is established which is used in supporting vehicle CWS. The CWA is tested using the actual data and the result shows that this algorithm can identify and carry out warning for vehicle collision efficiently, which has important meaning for improving the vehicle travel safety.

Heating of nanoparticles and their environment by laser radiation and applications

This review considers the fundamental dynamic processes involved in the laser heating of metal nanoparticles and their subsequent cooling.Of particular interest are the absorption of laser energy by nanoparticles,the heating of a single nanoparticle or an ensemble thereof,and the dissipation of the energy of nanoparticles due to heat exchange with the environment.The goal is to consider the dependences and values of the temperatures of the nanoparticles and the environment,their time scales,and other parameters that describe these processes.Experimental results and analytical studies on the heating of single metal nanoparticles by laser pulses are discussed,including the laser thresholds for initiating subsequent photothermal processes,how temperature influences the optical properties,and the heating of gold nanoparticles by laser pulses.Experimental studies of the heating of an ensemble of nanoparticles and the results of an analytical study of the heating of an ensemble of nanoparticles and the environment by laser radiation are considered.Nanothermometry methods for nanoparticles under laser heating are considered,including changes in the refractive indices of metals and spectral thermometry of optical scattering of nanoparticles,Raman spectroscopy,the thermal distortion of the refractive index of an environment heated by a nanoparticle,and thermochemical phase transitions in lipid bilayers surrounding a heated nanoparticle.Understanding the sequence of events after radiation absorption and their time scales underlies many applications of nanoparticles.The applicationfields for the laser heating of nanoparticles are reviewed,including thermochemical reactions and selective nanophotothermolysis initiated in the environment by laser-heated nanoparticles,thermal radiation emission by nanoparticles and laser-induced incandescence,electron and ion emission of heated nanoparticles,and optothermal chemical catalysis.Applications of the laser heating of nanoparticles in laser nanomedicine are of particular interest.Significant emphasis is given to the proposed analytical approaches to modeling and calculating the heating processes under the action of a laser pulse on metal nanoparticles,taking into account the temperature dependences of the parameters.The proposed models can be used to estimate the parameters of lasers and nanoparticles in the various applicationfields for the laser heating of nanoparticles.