Current Trends In Application Research Articles

Smart Hospitals: Integrating AI for Enhanced Patient Outcomes

The use of information technology and artificial intelligence in the healthcare sector has brought about smart hospitals. These hospitals incorporate AI, IoT, big data analytics, and robotics to increase productivity, optimize patient care, and decrease expenses. This paper aims at discussing the current trends in application of advanced IT in hospitals and the role of AI in enhancing the quality of patient care, clinical outcomes and financial performance. The study used a retrospective cohort design in two large hospitals in New York City and Los Angeles to evaluate the adoption of AI technologies from 2019 to 2023. The EHRs and interviews with the healthcare providers and patients were used to assess the mortality, complication, length of stay, and readmission rates before and after the implementation of AI. The findings show that there are statistically significant positive changes in patient outcomes after the integration of AI in smart hospital solutions. Issues related to data integration, privacy, and clinicians’ acceptance of AI-generated suggestions are also considered. This research contributes to the knowledge of the changes that AI brings to the healthcare system and the directions for the development of smart hospitals.

Gellan Gum as a Unique Microbial Polysaccharide: Its Characteristics, Synthesis, and Current Application Trends.

Gellan gum (GG) is a linear, negatively charged exopolysaccharide that is biodegradable and non-toxic. When metallic ions are present, a hard and transparent gel is produced, which remains stable at a low pH. It exhibits high water solubility, can be easily bio-fabricated, demonstrates excellent film/hydrogel formation, is biodegradable, and shows biocompatibility. These characteristics render GG a suitable option for use in food, biomedical, and cosmetic fields. Thus, this review paper offers a concise summary of microbial polysaccharides. Moreover, an in-depth investigation of trends in different facets of GG, such as biosynthesis, chemical composition, and physical and chemical properties, is emphasized. In addition, this paper highlights the process of extracting and purifying GG. Furthermore, an in-depth discussion of the advantages and disadvantages of GG concerning other polysaccharides is presented. Moreover, the utilization of GG across different industries, such as food, medicine, pharmaceuticals, cosmetics, etc., is thoroughly examined and will greatly benefit individuals involved in this field who are seeking fresh opportunities for innovative projects in the future.

An Overview of GIS-RS Applications for Archaeological and Cultural Heritage under the DBAR-Heritage Mission

In recent decades, the application of GIS and RS in archaeological and cultural heritage (ACH) has witnessed a notable surge both in terms of quantity and scope. During the initial implementation period (2016–2021) of the Digital Belt and Road Heritage (DBAR-Heritage) working group, several instances of GIS-RS-based applications in support of cultural heritage conservation have merged. In this paper, in order to discuss the great potential of GIS and RS on the Silk Road, an overview of GIS- and RS-based applications in ACH is first presented. In a substantial portion of the published scientific literature, the identification and comprehension of archaeological sites, the monitoring and risk assessment of cultural heritage, and the management and visualization of cultural heritage data are highlighted. Following this, five illustrative case studies from the DBAR-Heritage working group are presented to exemplify how the integration of GIS and RS serves as key approaches in recognizing and appreciating cultural heritage. These selected case studies showcase the utilization of multi-source data for the identification of linear sites; detailed, refined monitoring and assessment of the Angkor Wat heritage; and the reconstruction of the Silk Road routes. These instances serve as the cornerstone for highlighting current trends in GIS and RS applications in ACH along the Silk Road. These methodologies efficiently integrate multi-source geospatial data and employ multidisciplinary approaches, ultimately furnishing sophisticated and intelligent tools for the exploration and management of archaeological and cultural heritage in the era of Big Earth Data. Subsequently, a comprehensive discussion on the merits and challenges of GIS and RS applications in ACH is presented, followed by an exploration of the current application trends. Finally, the prospects for the widespread application of GIS and RS in ACH along the Silk Road are outlined in accordance with the operational plan of DBAR-Heritage during its second implementation phase.

40 Years Old and Still Solving Problems: Evolution of the ICP-MS Application Landscape

The year 2023 marks the 40th anniversary of the commercialization of inductively coupled plasma mass spectrometry (ICP-MS). Today, there are close to 2000 ICP-MS systems installed worldwide every year, representing around $400M in annual sales. These instruments are used for a wide variety of applications, from routine, high-throughput multielement analysis to more complex tasks, such as trace element speciation studies with high-performance liquid chromatography and monitoring of nanoparticles. My column this month will look at the evolving ICP-MS marketplace, highlighting current application trends (compared to other analytical spectroscopy techniques), and where the technique might be heading 5–10 years from now.

Graphitic carbon nitride (g-C3N4) based materials: current application trends in health and other multidisciplinary fields

Graphitic carbon nitride (g-C3N4) based materials: current application trends in health and other multidisciplinary fields

Advances in technology and utilization of natural resources for achieving carbon neutrality and a sustainable solution to neutral environment

The greatest environmental issue of the twenty-first century is climate change. Human-caused greenhouse gas emissions are increasing the frequency of extreme weather. Carbon dioxide (CO2) accounts for 80% of human greenhouse gas emissions. However, CO2 emissions and global temperature have risen steadily from pre-industrial times. Emissions data are crucial for most carbon emission policymaking and goal-setting. Sustainable and carbon-neutral sources must be used to create green energy and fossil-based alternatives to reduce our reliance on fossil fuels. Near-real-time monitoring of carbon emissions is a critical national concern and cutting-edge science. This review article provides an overview of the many carbon accounting systems that are now in use and are based on an annual time frame. The primary emphasis of the study is on the recently created carbon emission and eliminating sources and technology, as well as the current application trends for carbon neutrality. We also propose a framework for the most advanced naturally available carbon neutral accounting sources capable of being implemented on a large scale. Forming relevant data and procedures will help the “carbon neutrality” plan decision-making process. The formation of pertinent data and methodologies will give robust database support to the decision-making process for the “carbon neutrality” plan for the globe. In conclusion, this article offers some opinions, opportunities, challenges and future perspectives related to carbon neutrality and carbon emission monitoring and eliminating resources and technologies.

Research Trends and Applications of PMUs

This work is a survey of current trends in applications of PMUs. PMUs have the potential to solve major problems in the areas of power system estimation, protection, and stability. A variety of methods are being used for these purposes, including statistical techniques, mathematical transformations, probability, and AI. The results produced by the techniques reviewed in this work are promising, but there is work to be performed in the context of implementation and standardization. As the smart grid initiative continues to advance, the number of intelligent devices monitoring the power grid continues to increase. PMUs are at the center of this initiative, and as a result, each year more PMUs are deployed across the grid. Since their introduction, myriad solutions based on PMU-technology have been suggested. The high sampling rates and synchronized measurements provided by PMUs are expected to drive significant advancements across multiple fields, such as the protection, estimation, and control of the power grid. This work offers a review of contemporary research trends and applications of PMU technology. Most solutions presented in this work were published in the last five years, and techniques showing potential for significant impact are highlighted in greater detail. Being a relatively new technology, there are several issues that must be addressed before PMU-based solutions can be successfully implemented. This survey found that key areas where improvements are needed include the establishment of PMU-observability, data processing algorithms, the handling of heterogeneous sampling rates, and the minimization of the investment in infrastructure for PMU communication. Solutions based on Bayesian estimation, as well as those having a distributed architectures, show great promise. The material presented in this document is tailored to both new researchers entering this field and experienced researchers wishing to become acquainted with emerging trends.

Near-Real-Time Carbon Emission Accounting Technology Toward Carbon Neutrality

Climate change is the greatest environmental threat to humans and the planet in the 21st century. Global anthropogenic greenhouse gas emissions are one of the main causes of the increasing number of extreme climate events. Cumulative carbon dioxide (CO 2 ) emissions showed a linear relationship with cumulative temperature rise since the pre-industrial stage, and this accounts for approximately 80% of the total anthropogenic greenhouse gases. Therefore, accurate and reliable carbon emission data are the foundation and scientific basis for most emission reduction policymaking and target setting. Currently, China has made clear the ambitious goal of achieving the peak of carbon emissions by 2030 and achieving carbon neutrality by 2060. The development of a finer-grained spatiotemporal carbon emission database is urgently needed to achieve more accurate carbon emission monitoring for continuous implementation and the iterative improvement of emission reduction policies. Near-real-time carbon emission monitoring is not only a major national demand but also a scientific question at the frontier of this discipline. This article reviews existing annual-based carbon accounting methods, with a focus on the newly developed real-time carbon emission technology and its current application trends. We also present a framework for the latest near-real-time carbon emission accounting technology that can be widely used. The development of relevant data and methods will provide strong database support to the policymaking for China's “carbon neutrality” strategy. Finally, this article provides an outlook on the future of real-time carbon emission monitoring technology.

Current Application Trends of Virtual Communications in Libraries

Current Application Trends of Virtual Communications in Libraries

Industry 4.0 Technologies Applied to Inland Waterway Transport: Systematic Literature Review.

The focus of this article is inland waterway transport. Different problems in this domain have been studied due to the increase in waterway traffic globally. Industry 4.0 technologies have become an alternative for the possible solution of these problems. For this reason, this paper aims to answer the following research questions: (1) What are the main problems in transporting cargo by inland waterway? (2) What technological strategies are being studied to solve these problems? (3) What technologies from Industry 4.0 are used within the technological strategies to solve the exposed problems? This study adopts a Systematic Literature Review (SLR) approach. For this work, were recovered 645 articles, 88 of which were eligible, from which we could identify five domains corresponding to (1) traffic monitoring, (2) smart navigation, (3) emission reduction, (4) analytics with big data, and (5) cybersecurity. The strategies currently being considered combine navigation technologies, such as AIS (Automatic Identification System), which offers a large amount of data, with Industry 4.0 tools and mainly machine learning techniques, to take advantage of data collected over a long time. This study is, to our knowledge, one of the first to show how Industry 4.0 technologies are currently being used to tackle inland waterway transport problems and current application trends in the scientific community, which is a first step for the development of future studies and more advanced solutions.

Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review.

Background: Industry 4.0 technologies have been widely used in the railway industry, focusing mainly on maintenance and control tasks necessary in the railway infrastructure. Given the great potential that these technologies offer, the scientific community has come to use them in varied ways to solve a wide range of problems such as train failures, train station security, rail system control and communication in hard-to-reach areas, among others. For this reason, this paper aims to answer the following research questions: what are the main issues in the railway transport industry, what are the technologic strategies that are currently being used to solve these issues and what are the technologies from industry 4.0 that are used in the railway transport industry to solve the aforementioned issues? Methods: This study adopts a systematic literature review approach. We searched the Science Direct and Web of Science database inception from January 2017 to November 2021. Studies published in conferences or journals written in English or Spanish were included for initial process evaluation. The initial included papers were analyzed by authors and selected based on whether they helped answer the proposed research questions or not. Results: Of the recovered 515 articles, 109 were eligible, from which we could identify three main application domains in the railway industry: monitoring, decision and planification techniques, and communication and security. Regarding industry 4.0 technologies, we identified 9 different technologies applied in reviewed studies: Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing, Big Data, Cybersecurity, Modelling and Simulation, Smart Decision Support Systems (SDSS), Computer Vision and Virtual Reality (VR). This study is, to our knowledge, one of the first to show how industry 4.0 technologies are currently being used to tackle railway industry problems and current application trends in the scientific community, which is highly useful for the development of future studies and more advanced solutions. Funding: Colombian national organizations Minciencias and the Mining-Energy Planning Unit.

Current Trends in Application of Platelet Rich Fibrin

Current Trends in Application of Platelet Rich Fibrin

Development and Progress in Sensors and Technologies for Human Emotion Recognition.

With the advancement of human-computer interaction, robotics, and especially humanoid robots, there is an increasing trend for human-to-human communications over online platforms (e.g., zoom). This has become more significant in recent years due to the Covid-19 pandemic situation. The increased use of online platforms for communication signifies the need to build efficient and more interactive human emotion recognition systems. In a human emotion recognition system, the physiological signals of human beings are collected, analyzed, and processed with the help of dedicated learning techniques and algorithms. With the proliferation of emerging technologies, e.g., the Internet of Things (IoT), future Internet, and artificial intelligence, there is a high demand for building scalable, robust, efficient, and trustworthy human recognition systems. In this paper, we present the development and progress in sensors and technologies to detect human emotions. We review the state-of-the-art sensors used for human emotion recognition and different types of activity monitoring. We present the design challenges and provide practical references of such human emotion recognition systems in the real world. Finally, we discuss the current trends in applications and explore the future research directions to address issues, e.g., scalability, security, trust, privacy, transparency, and decentralization.

The potential of metal epoxy composite (MEC) as hybrid mold inserts in rapid tooling application: a review

Purpose Rapid tooling (RT) integrated with additive manufacturing technologies have been implemented in various sectors of the RT industry in recent years with various kinds of prototype applications, especially in the development of new products. The purpose of this study is to analyze the current application trends of RT techniques in producing hybrid mold inserts. Design/methodology/approach The direct and indirect RT techniques discussed in this paper are aimed at developing a hybrid mold insert using metal epoxy composite (MEC) in increasing the speed of tooling development and performance. An extensive review of the suitable development approach of hybrid mold inserts, material preparation and filler effect on physical and mechanical properties has been conducted. Findings Latest research studies indicate that it is possible to develop a hybrid material through the combination of different shapes/sizes of filler particles and it is expected to improve the compressive strength, thermal conductivity and consequently increasing the hybrid mold performance (cooling time and a number of molding cycles). Research limitations/implications The number of research studies on RT for hybrid mold inserts is still lacking as compared to research studies on conventional manufacturing technology. One of the significant limitations is on the ways to improve physical and mechanical properties due to the limited type, size and shape of materials that are currently available. Originality/value This review presents the related information and highlights the current gaps related to this field of study. In addition, it appraises the new formulation of MEC materials for the hybrid mold inserts in injection molding application and RT for non-metal products.

Nanomaterials in the production of refractory materials

On June 17, 2020 the International Scientific and Practical Online Conference “Current Trends in Application of Nano-Materials in Production of Refractories” was held. The conference was organized by “Magnezit” Group in cooperation with Wuhan University of Science and Technology, Fund of infrastructure and educational programs of ROSNANO group and National Research Technological University MISiS (Moscow). Leading specialists of practical work and experts from universities of Russia, China, Lithuania, the Netherlands and the USA delivered reports. Results of studies obtained in research laboratories and at industrial sites were presented by authors of 9 reports. The conference brought together about 300 participants, at that more than 60 participants had a chance to take part in the discussions and put questions to the speakers, and 200 listeners were observing the event by on-line transmission.

Nanostructured Materials for Artificial Tissue Replacements.

This paper review current trends in applications of nanomaterials in tissue engineering. Nanomaterials applicable in this area can be divided into two groups: organic and inorganic. Organic nanomaterials are especially used for the preparation of highly porous scaffolds for cell cultivation and are represented by polymeric nanofibers. Inorganic nanomaterials are implemented as they stand or dispersed in matrices promoting their functional properties while preserving high level of biocompatibility. They are used in various forms (e.g., nano- particles, -tubes and -fibers)—and when forming the composites with organic matrices—are able to enhance many resulting properties (biologic, mechanical, electrical and/or antibacterial). For this reason, this contribution points especially to such type of composite nanomaterials. Basic information on classification, properties and application potential of single nanostructures, as well as complex scaffolds suitable for 3D tissues reconstruction is provided. Examples of practical usage of these structures are demonstrated on cartilage, bone, neural, cardiac and skin tissue regeneration and replacements. Nanomaterials open up new ways of treatments in almost all areas of current tissue regeneration, especially in tissue support or cell proliferation and growth. They significantly promote tissue rebuilding by direct replacement of damaged tissues.

An insight into application of big data analytics in healthcare

The main aim of this paper is to comprehend, gain insight of the current trends in application of big data in healthcare, and to identify the various potential healthcare horizons. A brief analysis was done on 'big data analytics in healthcare' focusing on collection of data, the tools employed, the aspects of health that were addressed, the type of machine learning algorithms and which statistics commissioned to compare the performance of these algorithms. The focus was mainly on prediction of the diseases, emergency department visits or a disease outbreak, using 'HADOOP' and 'WEKA' tool, by obtaining data from University of California machine learning repository, hospitals and government agencies. Support vector machine, artificial neural networks, naive Bayes and decision tree were commonly used algorithms whose efficacy was compared statistically using 'accuracy'. In my perspective, apart from prediction of disease other domains of health are to be addressed.

An insight into application of big data analytics in healthcare

The main aim of this paper is to comprehend, gain insight of the current trends in application of big data in healthcare, and to identify the various potential healthcare horizons. A brief analysis was done on 'big data analytics in healthcare' focusing on collection of data, the tools employed, the aspects of health that were addressed, the type of machine learning algorithms and which statistics commissioned to compare the performance of these algorithms. The focus was mainly on prediction of the diseases, emergency department visits or a disease outbreak, using 'HADOOP' and 'WEKA' tool, by obtaining data from University of California machine learning repository, hospitals and government agencies. Support vector machine, artificial neural networks, naive Bayes and decision tree were commonly used algorithms whose efficacy was compared statistically using 'accuracy'. In my perspective, apart from prediction of disease other domains of health are to be addressed.

Review of photomixing continuous-wave terahertz systems and current application trends in terahertz domain

Within the last two decades, terahertz systems have become a well-established tool in scientific laboratories and industrial research and development departments. Unlike the methods of pulsed terahertz radiation that mainly rely on ultrafast optical technology, the technology behind continuous-wave terahertz sources and detectors has a long history involving many different types of technical schemes. The intent is to provide a brief review of the continuous-wave terahertz systems that are based on photomixing and current application trends in the field of terahertz technology.

Current Trends in Applications of Circulatory Microchimerism Detection in Transplantation.

Primarily due to recent advances of detection techniques, microchimerism (the proportion of minor variant population is below 1%) has recently gained increasing attention in the field of transplantation. Availability of polymorphic markers, such as deletion insertion or single nucleotide polymorphisms along with a vast array of high sensitivity detection techniques, allow the accurate detection of small quantities of donor- or recipient-related materials. This diagnostic information can improve monitoring of allograft injuries in solid organ transplantations (SOT) as well as facilitate early detection of relapse in allogeneic hematopoietic stem cell transplantation (allo-HSCT). In the present review, genetic marker and detection platform options applicable for microchimerism detection are discussed. Furthermore, current results of relevant clinical studies in the context of microchimerism and SOT or allo-HSCT respectively are also summarized.