Rapid Development Research Articles

Transforming Adolescent Smiles: Correcting Skeletal Mandibular Retrusion and Bimaxillary Protrusion with Clear Aligners.

Maxillary protrusion combined with mandibular retraction is a highly prevalent but extremely complex maxillofacial deformity that can have a serious negative impact on patients' facial aesthetics and mental health. The traditional orthodontic treatment strategy often involves extracting 4 first premolars and conventional fixed techniques, combined with mini-implant screws, to retract the anterior teeth and improve facial protrusion. In recent years, an invisible orthodontic technique, without brackets, has become increasingly popular. However, while an invisible aligner has been used in some cases with reasonable results, there remain significant challenges in achieving a perfect outcome. This case report presents an adolescent patient with bimaxillary protrusion and mandibular retrognathia. Based on the characteristics of the invisible aligners and the growth characteristics of the adolescent's teeth and jawbone, we designed precise three-dimensional tooth movement and corresponding resistance/over-correction for each tooth, while utilizing the patient's jawbone growth potential to promote rapid development of the mandible, accurately and efficiently correcting bimaxillary protrusion and skeletal mandibular retrognathia. The patient's facial aesthetics, especially the lateral morphology, have been greatly improved, and various aesthetic indicators have also shown significant changes, and to the patient's great benefit, invasive mini-implant screws were not used during the treatment. This case highlights the advantages of using invisible aligners in adolescent maxillary protrusion combined with mandibular retraction patients. Furthermore, comprehensive and accurate design combined with good application of growth potential can also enable invisible orthodontic technology to achieve perfect treatment effects in tooth extractions, providing clinical guidance for orthodontists.

Visualizing Electrochemical CO2 Conversion via the Emerging Scanning Electrochemical Microscope: Fundamentals, Applications and Perspectives.

With the rapid development and maturity of electrochemical CO2 conversion involving cathodic CO2 reduction reaction (CO2RR) and anodic oxygen evolution reaction (OER), conventional ex situ characterizations gradually fall behind in detecting real-time products distribution, tracking intermediates, and monitoring structural evolution, etc. Nevertheless, advanced in situ techniques, with intriguing merits like good reproducibility, facile operability, high sensitivity, and short response time, can realize in situ detection and recording of dynamic data, and observe materials structural evolution in real time. As an emerging visual technique, scanning electrochemical microscope (SECM) presents local electrochemical signals on various materials surface through capturing micro-current caused by reactants oxidation and reduction. Importantly, SECM holds particular potentials in visualizing reactive intermediates at active sites and obtaining instantaneous morphology evolution images to reveal the intrinsic reactivity of active sites. Therefore, this review focuses on SECM fundamentals and its specific applications toward CO2RR and OER, mainly including electrochemical behavior observation on local regions of various materials, target products and onset potentials identification in real-time, reaction pathways clarification, reaction kinetics exploration under steady-state conditions, electroactive materials screening and multi-techniques coupling for a joint utilization. This review undoubtedly provides a leading guidance to extend various SECM applications to other energy-related fields.

Metal Organic Frameworks as Polysulfide Reaction Modulators for Lithium Sulfur Batteries: Advances and Perspectives.

Currently, lithium sulfur (Li-S) battery with high theoretical energy density has attracted great research interest. However, the diffusion and loss process of intermediate lithium polysulfide during charge-discharge hindered the application of the Li-S battery in modern life. To overcome this issue, metal organic frameworks (MOFs) and their composites have been regarded as effective additions to restrain the LiPS diffusion process for Li-S battery. Benefiting from the unique structure with rich active sites to adsorb LiPS and accelerate the LiPS redox, the Li-S batteries with MOFs modified exhibit superior electrochemical performance. Considering the rapid development of MOFs in Li-S battery, this review summarizes the recent studies of MOFs and their composites as the sulfur host materials, functional interlayer, separator coating layer, and separator/solid electrolyte for Li-S batteries in detail. In addition, the promising design strategies of functional MOF materials are proposed to improve the electrochemical performance of Li-S battery.

A lipid nanoparticle platform incorporating trehalose glycolipid for exceptional mRNA vaccine safety

The rapid development of messenger RNA (mRNA) vaccines formulated with lipid nanoparticles (LNPs) has contributed to control of the COVID-19 pandemic. However, mRNA vaccines have raised concerns about their potential toxicity and clinical safety, including side effects, such as myocarditis, anaphylaxis, and pericarditis. In this study, we investigated the potential of trehalose glycolipids-containing LNP (LNP S050L) to reduce the risks associated with ionizable lipids. Trehalose glycolipids can form hydrogen bonds with polar biomolecules, allowing the formation of a stable LNP structure by replacing half of the ionizable lipids. The efficacy and safety of LNP S050L were evaluated by encapsulating the mRNA encoding the luciferase reporter gene and measuring gene expression and organ toxicity, respectively. Furthermore, mice immunized with an LNP S050L-formulated mRNA vaccine expressing influenza hemagglutinin exhibited a significant reduction in organ toxicity, including in the heart, spleen, and liver, while sustaining gene expression and immune efficiency, compared to conventional LNPs (Con-LNPs). Our findings suggest that LNP S050L, a trehalose glycolipid-based LNP, could facilitate the development of safe mRNA vaccines with improved clinical safety.

Fluorescent small molecule donors.

Small molecule donors (SMDs) play subtle roles in the signaling mechanism and disease treatments. While many excellent SMDs have been developed, dosage control, targeted delivery, spatiotemporal feedback, as well as the efficiency evaluation of small molecules are still key challenges. Accordingly, fluorescent small molecule donors (FSMDs) have emerged to meet these challenges. FSMDs enable controllable release and non-invasive real-time monitoring, providing significant advantages for drug development and clinical diagnosis. Integration of FSMDs with chemotherapeutic, photodynamic or photothermal properties can take full advantage of each mode to enhance therapeutic efficacy. Given the remarkable properties and the thriving development of FSMDs, we believe a review is needed to summarize the design, triggering strategies and tracking mechanisms of FSMDs. With this review, we compiled FSMDs for most small molecules (nitric oxide, carbon monoxide, hydrogen sulfide, sulfur dioxide, reactive oxygen species and formaldehyde), and discuss recent progress concerning their molecular design, structural classification, mechanisms of generation, triggered release, structure-activity relationships, and the fluorescence response mechanism. Firstly, from the large number of fluorescent small molecular donors available, we have organized the common structures for producing different types of small molecules, providing a general strategy for the development of FSMDs. Secondly, we have classified FSMDs in terms of the respective donor types and fluorophore structures. Thirdly, we discuss the mechanisms and factors associated with the controlled release of small molecules and the regulation of the fluorescence responses, from which universal guidelines for optical properties and structure rearrangement were established, mainly involving light-controlled, enzyme-activated, reactive oxygen species-triggered, biothiol-triggered, single-electron reduction, click chemistry, and other triggering mechanisms. Fourthly, representative applications of FSMDs for trackable release, and evaluation monitoring, as well as for visible in vivo treatment are outlined, to illustrate the potential of FSMDs in drug screening and precision medicine. Finally, we discuss the opportunities and remaining challenges for the development of FSMDs for practical and clinical applications, which we anticipate will stimulate the attention of researchers in the diverse fields of chemistry, pharmacology, chemical biology and clinical chemistry. With this review, we hope to impart new understanding thereby enabling the rapid development of the next generation of FSMDs.

Efficient Classification on Remote Sensing Image Using Transfer Learning

With a rapid development in aerial technology, applications of Remote Sensing Images (RSI) have become more diverse. Remote sensing image classification plays a crucial role in analyzing and interpreting Earth observation data for various applications, such as land cover mapping, environmental monitoring, and urban planning. However, accurately classifying remote sensing images poses significant challenges due to their complex spatial and spectral characteristics. In recent years, transfer learning has emerged as a promising technique to improve the classification accuracy by leveraging the knowledge learned from pre-trained models on large-scale datasets. The proposed model explores different transfer learning strategies employed in remote sensing image classification, including fine-tuning, feature extraction, and domain adaptation. It discusses popular pre-trained models, such as VGG16, VGG19, and Inceptionv3, and their applicability to remote sensing datasets. The advantages and limitations of each strategy are analyzed, providing insights into their suitability for various remote sensing applications. A comparative study is done on all these techniques to evaluate the performance measures like Accuracy and Loss.

Research on the Development and Application of ChatGPT

With the rapid development of AI technology, AI is increasingly capable of performing complex computational and creative tasks. The combination of automation, machine learning, and natural language processing technologies provides powerful capabilities for AI systems. This project uses ChatGPT as an example to explore in depth the dynamic cross-cutting features of AI and its impact on human behavior. This paper utilizes a multifaceted research methodology, including case studies, and focuses on ChatGPT as a relevant case study. The findings of this project not only deepen the understanding of ChatGPT's functions, but also have implications for the interaction between AI and human intelligence. This research emphasizes the need for consultative and ethical architectures and the importance of using them in a balanced way in this ever-changing field of technology. This thesis offers valuable thoughts on the coexistence of AI and human endeavors.

Critical Sensing Modalities for Hydrogen: Technical Needs and Status of the Field to Support a Changing Energy Landscape.

Decarbonization of the energy system is a key aspect of the energy transition. Energy storage in the form of chemical bonds has long been viewed as an optimal scheme for energy conversion. With advances in systems engineering, hydrogen has the potential to become a low cost, low emission, energy carrier. However, hydrogen is difficult to contain, it exhibits a low flammability limit (>40000 ppm or 4%), low ignition energy (0.02 mJ), and it is a short-lived climate forcer. Beyond commercially available sensors to ensure safety through spot checks in enclosed environments, new sensors are necessary to support the development of low emission infrastructure for production, transmission, storage, and end use. Efficient scalable broad area hydrogen monitoring motivates lowering the detection limit below that (10 ppm) of best in class commercial technologies. In this perspective, we evaluate recent advances in hydrogen gas sensing to highlight technologies that may find broad utility in the hydrogen sector. It is clear in the near term that a sensor technology suite is required to meet the variable constraints (e.g., power, size/weight, connectivity, cost) that characterize the breadth of the application space, ranging from industrial complexes to remote pipelines. This perspective is not intended to be another standard hydrogen sensor review, but rather provide a critical evaluation of technologies with detection limits preferably below 1 ppm and low power requirements. Given projections for rapid market growth, promising techniques will also be amenable to rapid development in technical readiness for commercial deployment. As such, methods that do not meet these requirements will not be considered in depth.

Effect of Dietary Supplementation on the Growth and Immunity of Fish and Shellfish

With the rapid development of aquaculture, the shortage of high-quality dietary ingredients has become a critical problem limiting the sustainable development of aquaculture [...]

Analysis of interventional treatment options of the common femoral artery - a retrospective single center experience.

Background: Due to the rapid development of treatment techniques of peripheral arterial disease (PAD) treatment is nowadays predominantly interventional. An exception are lesions of the common femoral artery (CFA), which should be treated surgically according to vascular guidelines. However, recent evidence has shown that endovascular techniques, e.g. stenting, have comparable clinical outcomes while causing fewer complications. The aim of the present analysis was to evaluate the therapeutic success of endovascular therapy of CFA lesions in a single center, all - comers registry. Patients and methods: All patients who were treated for a CFA lesion at the Department of Internal Medicine I of the University Hospital Jena in the period from 01/2017 to 12/2020 were included. Treatment success was determined by evaluating the ankle-brachial-index (ABI) pre- and post-interventional as well as after follow-up (FU), measuring walking distance (WD) and by target revascularization rate (TLR) and primary patency rate (PPR). Results: The analysis included 109 patients with a mean age of 73.4 years, with 67% (73) of those being men. 72 patients received interventional treatment, whereas 33 were treated surgically and 4 conservatively. Resting ABI in the overall cohort showed an increase from 0.5 to 0.7 post intervention (p=<0.05; mean FU-time: 6.5 months). In the interventional cohort ABI increases from 0.6 to 0.8 (p=<0.05; mean FU-time: 5,8 months) at FU and from 0.3 to 0.6 (p=<0.05; mean FU-time: 8,8 month) in the surgically treated group. The WD improved in the whole collective from 116.5 meter (m) to 152.5 m (p=<0.05). The TLR showed no significant difference with 8.1% after interventional treatment and 6.1% after vascular surgery in the present analysis (p=0.72) as well as PPR with 89.8% after EVT and 90.9% after surgical approach (p=0.87). The intra-/postinterventional complication rate was 5.5% in the intervention group, compared to postoperative complication rate of 15.2% in the surgically treated group. Conclusions: The present analysis demonstrates that even in a real-world, all-comers collective, interventional therapy for CFA lesions was safe and equally effective as the surgically treated patient cohort. Continuing to generate registry data is important to eventually initiate a paradigm shift.

Building and Developing Smart Cities in Ho Chi Minh City, Vietnam - Current Situation and Solutions

Building and developing smart cities is an inevitable trend globally, including in Vietnam. Ho Chi Minh City is one of Vietnam's largest cities, experiencing rapid development and urbanization. Establishing and developing smart cities in Ho Chi Minh City is a necessity in the context of the fourth industrial revolution and the ongoing digital transformation in all sectors, aiming at the ultimate goal of serving and improving the quality of life for the city's residents. This article focuses on clarifying several issues: (1) Analyzing the concept and criteria of the smart city model; (2) Investigating the current situation of building and developing smart cities in Ho Chi Minh City, including both the achievements and existing limitations; (3) Proposing solutions to enhance the effectiveness of building and developing smart cities in Ho Chi Minh City in the current context.

Research on Network Novel Infringement

The rapid development of the Internet has brought great changes to our lives and has had a far-reaching impact on the law. In the context of the Internet, the network culture represented by network novels has gradually entered the historical stage and has become an important part of China's cultural system. However, with the continuous increase in the total number of online novels, copyright infringement cases of online fiction are also increasing. Especially in the present, China's legal system for the protection of copyright in network novels is still not perfect, and the infringement of copyright in network fictions continues to emerge. Clarifying the relevant legal relations of network novels is also an important premise to solve their dilemma. On the basis of explaining its concept, this paper analyzes the case, points out the existing problems based on practice, and finally puts forward constructive suggestions.

Exosomes: the next-generation therapeutic platform for ischemic stroke

Abstract Current therapeutic strategies for ischemic stroke fall short of the desired objective of neurological functional recovery. Therefore, there is an urgent need to develop new methods for the treatment of this condition. Exosomes are natural cell-derived vesicles that mediate signal transduction between cells under physiological and pathological conditions. They have low immunogenicity, good stability, high delivery efficiency, and the ability to cross the blood-brain barrier. These physiological properties of exosomes have the potential to lead to new breakthroughs in the treatment of ischemic stroke. The rapid development of nanotechnology has advanced the application of engineered exosomes, which can effectively improve targeting ability, enhance therapeutic efficacy, and minimize the dosages needed. Advances in technology have also driven clinical translational research on exosomes. In this review, we describe the therapeutic effects of exosomes anc their positive roles in current treatment strategies for ischemic stroke, including their anti-inflammation, anti-apoptosis, autophagy-regulation, angiogenesis, neurogenesis, and glial scar formation reduction effects. However, it is worth noting that, despite their significant therapeutic potential, there remains a dearth of standardized characterization methods and efficient isolation techniques capable of producing highly purified exosomes. Future optimization strategies should prioritize the exploration of suitable isolation techniques and the establishment of unified workflows to effectively harness exosomes for diagnostic or therapeutic applications in ischemic stroke. Ultimately, our review aims to summarize our understanding of exosome-based treatment prospects in ischemic stroke and foster innovative ideas for the development of exosome-based therapies.

Photocatalytic application of nickel oxide/zinc oxide nanoparticles decorated kaolinite nanocomposite for the degradation of crystal violet

The photocatalysis process, which is effective, economical, and environmentally friendly can overcome rapidly increasing environmental problems, has shown rapid development in recent years. Nontoxic, low-cost natural minerals are often used in photocatalysis processes that remove organic pollution from wastewater. In this study, a selective method for the removal of crystal violet (CV) from aqueous solutions using nanocomposite of nickel oxide/zinc oxide nanoparticles (NiO/ZnO) supported on kaolinite photocatalyst was investigated. The raw kaolinite, bare NiO, bare ZnO and nanocomposite samples were characterized by the XRD, TEM, SEM-EDX, XPS and FTIR techniques. The photocatalytic performances of kaolinite-NiOZnO (K-NiO/ZnO) nanocomposite and bare samples were also investigated and comparatively evaluated by the photodegradation of CV (cationic dye) dye under visible light irradiation. The effects of various parameters such as the dosage of photocatalysis, contact time, and initial dye concentration on the rate of removal of dye were investigated and optimized. The kinetics of decolorization by samples can be well described by the pseudo-first-order model. Finally, it can be used in advanced oxidative processes for the degradation of organic pollutants.

Developing virtual collaborative health team educational environments

In this short paper we introduce a conceptual framework that is under development to create virtual educational environments to simulate collaborative health team experiences. Building on our work of developing virtual environments for authentic Paramedicine education scenarios, we are extending the concept across the seven health disciplines at the university, beginning initially with a prototype involving three health discipline teams: Paramedicine, Nursing, and Physiotherapy. Using a design based research methodology we are developing prototypes of immersive simulated environments to simulate the real - world interaction between these three health teams for our students. We leverage a low cost mobile BYOD approach enabling rapid prototyping and development of these scenarios.

Short-Term Air Traffic Flow Prediction Based on CEEMD-LSTM of Bayesian Optimization and Differential Processing

With the rapid development of China’s civil aviation, the flow of air traffic in terminal areas is also increasing. Short-term air traffic flow prediction is of great significance for the accurate implementation of air traffic flow management. To enhance the accuracy of short-term air traffic flow prediction, this paper proposes a short-term air traffic flow prediction model based on complementary ensemble empirical mode decomposition (CEEMD) and long short-term memory (LSTM) of the Bayesian optimization algorithm and data differential processing. Initially, the model performs CEEMD on the short-term air traffic flow series. Subsequently, to improve prediction accuracy, the data differencing is employed to stabilize the time series. Finally, the smoothed sequences are, respectively, input into the LSTM network model optimized by the Bayesian optimization algorithm for prediction. After data reconstruction, the final short-term flow prediction result is obtained. The model proposed in this paper is verified by using the data from Shanghai Pudong International Airport. The results show that the evaluation indexes of the prediction accuracy and fitting degree of the model, RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and R2 (Coefficient of Determination), are 0.336, 0.239, and 97.535%, respectively. Compared to other classical time-series prediction models, the prediction accuracy is greatly improved, which can provide a useful reference for short-term air traffic flow prediction.

G2D-Net: Efficient Dehazing with Second-Order Gated Units

Image dehazing aims to reconstruct potentially clear images from corresponding images corrupted by haze. With the rapid development of deep learning-related technologies, dehazing methods based on deep convolutional neural networks have gradually become mainstream. We note that existing dehazing methods often accompany an increase in computational overhead while improving the performance of dehazing. We propose a novel lightweight dehazing neural network to balance performance and efficiency: the g2D-Net. The g2D-Net borrows the design ideas of input-adaptive and long-range information interaction from Vision Transformers and introduces two kinds of convolutional blocks, i.e., the g2D Block and the FFT-g2D Block. Specifically, the g2D Block is a residual block with second-order gated units, which inherit the input-adaptive property of a gated unit and can realize the second-order interaction of spatial information. The FFT-g2D Block is a variant of the g2D Block, which efficiently extracts the global features of the feature maps through fast Fourier convolution and fuses them with local features. In addition, we employ the SK Fusion layer to improve the cascade fusion layer in a traditional U-Net, thus introducing the channel attention mechanism and dynamically fusing information from different paths. We conducted comparative experiments on five benchmark datasets, and the results demonstrate that the g2D-Net achieves impressive dehazing performance with relatively low complexity.

Manajemen Perpustakaan Berbasis Information and Communication Tecnology (ICT) di Universitas Muslim Nusantara Al –Washliyah

This study aims to determine ICT-based library management because the rapid development of technology makes significant changes, especially in information technology. Related to the development of information technology, libraries have also changed from conventional libraries to digital libraries. Library as an information center in the face of technological developments, namely by managing libraries using library management based on Information and Communication Technology (ICT) as library management. This development can be felt now with many libraries using Infomation and Communication Technology (ICT) as management in libraries. This type of research is descriptive with qualitative methods. The techniques used for data collection are interviews, observation, and documentation. Data analysis using three stages, namely: data reduction, presentation, and conclusions. The results of this study show that ICT-based library management is able to improve services and use in libraries, as well as make it easier for students to obtain books and information needed because in its services it does not have a difficult process but is faced with a lack of human resources (Human Resources) in ICT management.

Engineering strategies for high‐voltage LiCoO2 based high‐energy Li‐ion batteries

AbstractTo drive electronic devices for a long range, the energy density of Li‐ion batteries must be further enhanced, and high‐energy cathode materials are required. Among the cathode materials, LiCoO2 (LCO) is one of the most promising candidates when charged to higher voltages over 4.3 V. However, high‐voltage LCO materials are confronted with severe surface and bulk issues inducing poor cyclic stability. To completely unleash the potential of LCO cathodes, a more comprehensive theoretical understanding of the underlying issues is necessary, along with active exploration of previous modifications. This paper mainly presents the degradation mechanisms of LCO under high voltage, the formation and evolution mechanisms of the cathode electrolyte interface, and the surface engineering strategies employed to enhance the cell performance. By organizing and summarizing these modifications, this work aims to establish associations among common research issues and to suggest future research priorities, thus facilitating the rapid development of high‐voltage LCO.

In Situ Laser-Induced 3D Porous Graphene within Transparent Polymers for Encapsulation-Free and Tunable Ultrabroadband Terahertz Absorption.

Three-dimensional (3D) porous carbon materials have great potential for fabricating flexible tunable broadband absorbers owing to their high electrical conductivity, strong dielectric loss, and unique microstructure. Herein, we introduce an innovative method for synthesizing 3D porous graphene that incorporates advanced tuning and encapsulation processes to augment its functional efficacy. Through the modulation of both thermal and nonthermal interactions between a femtosecond (fs) laser and a polydimethylsiloxane (PDMS) film, we have synergistically fine-tuned the surface morphology and lattice properties of 3D porous graphene. This approach enabled us to create a flexible terahertz (THz) absorber with customizable characteristics, boasting an impressive absorbance range of 80%-99% in the 0.4-1.0 THz spectrum, alongside a peak reflection loss (RL) of up to 35.6 dB. Furthermore, we have successfully demonstrated the production of photoinduced 3D porous graphene within a PDMS film, which serves as both a carbon precursor and protective layer. This simplifies the conventional packaging process. These devices exhibit a RL of up to 41.6 dB and an absorption bandwidth of 2.5 THz (0.6-3.1 THz). Our study presents a production methodology for high-performance, flexible THz absorbers, offering a straightforward and innovative solution for the rapid development of sophisticated, flexible THz absorbing materials.