Field Of Science Research Articles

Sago-shaped embedded nanolayers of WO3/NiO/gC3N4 nanohybrids for natural degradation of environmental pollutants: A photocatalytic sunlight mediated approach

In recent years the applicability of semiconductor nanomaterials is almost in every field of science and technology. In the current study, hybrid nanomaterials containing tungsten trioxide (WO3) and nickel oxide (NiO) supported on graphitic carbon nitride (gC3N4) were prepared by a simple hydrothermal technique. Synthesis was sequential requiring the individual preparation of gC3N4 and WO3 as preliminary. The desired composition of gC3N4, WO3, nickel nitrate, and a base was transferred to an autoclave and maintained at 180°C for 18h. The resulting inorganic/organic hybrid was filtered, washed, dried, and named as inorganic/organic hybrid nanocomposite (HNC). Various compositions of HNC were prepared and characterized by Fourier transform infrared spectrometer (FT-IR), Ultra Violet-Visible Diffuse reflectance spectrometer (UV-Vis-DRS), X-ray diffractometer (XRD), and Field emission scanning electron microscope (FE-SEM). The FE-SEM images showed a sago-shaped embedded particle in gC3N4 layers with a 40-60 nm particle size. The band gap energy was found to be 2.69 eV from UV-Vis-DRS analysis. This proves the promising activity of sago-shaped HNC under sunlight radiation. Various preliminary and kinetic studies were conducted, and HNC possessed excellent photocatalytic activity for the degradation of an organic dye under sunlight. The photocatalytic activity for the degradation of dye by the prepared HNC was found to be two-fold when compared to the activity of pristine gC3N4 under sunlight irradiation.

Neobots: an open-source platform for a low-cost neonatal incubator with internet of things approach

<div align="center">A baby incubator implements the internet of things (IoT) with an architectural design combining several scientific fields, such as networks, software, and hardware. Furthermore, this research develops an open-source platform called Neobots, including open-source program code to create a baby incubator. Then an overview of the system includes sending sensor data to the IoT Broker with the message queuing telemetry transport (MQTT) protocol and automatically storing data in the database. The results of the comparison value on each temperature sensor with a temperature sensor at the midpoint with an error of less than 0.7°C. Then testing the fuzzy between the Neobots program and the simulation in MATLAB got an error rate of 0-28.27%. In addition, in less than 10 minutes, the system response can adjust the temperature conditions to a setpoint value of 34°C from 29°C, and the average error value is 0.35°C during 1 hour of the Fuzzy implementation on the incubator. Then transfer data from the incubator to the database in a room without noise and full noise to get results for lost data less than 16.41% and 42.14%, delay rates between 0-6 seconds and 0-7 seconds with testing for 1 hour at every 1 second.</div>

The 21st-century skills scales: many facet Rasch measurements

This study aims to develop a 21st century skills scale for prospective school counselor. The method used is the research and development. The data were analyzed using content analysis/expert judgment with many-facet Rasch model (MFRM). Three facets were employed: scale, item, and measurement criteria. The initial version of the scale comprises 129 items measuring four aspects: way of thinking, way of working, tools for working, and living in the world. However, 78 items were deemed valid following the expert judgment analysis result. The inter-rater agreement opportunity shows raters’ similarity score of 10,836, implying that experts in this study tend to give similar assessments. This research results in a 21st century skills scale for prospective school counselors with a total of 78 valid items. The purpose of this study was to develop a 21st century skills scale for prospective school counselors that had been fulfilled, the instrument had been tested for validity and reliability based on expert judgment. The current research recommends that further research be carried out to develop a 21st century skills scale instrument for prospective educators in other scientific fields.

Enhancing EEG-based brain-computer interface systems through efficient machine learning classification techniques

Advances in the fields of neuroscience and computer science have greatly enhanced the human brain’s ability to communicate and interact with the surrounding environment. In addition, recent steps in machine learning (ML) have increased the use of electroencephalography (EEG)-based BCIs for artificial intelligence (AI) applications. The prevailing challenge in recording EEG sensor data is that the captured signals are mixed with noise, which makes their effective use difficult. Therefore, strengthening the classification stage becomes extremely important and plays a major role in addressing this problem. In this study, we chose five most widely used classification models that obtained the best results in this field and tested them on two open-source databases. We also focused on improving the hyperparameters of each algorithm to obtain best results. Our results indicate excellent results on the first dataset and acceptable for most models on the second, while RF showed superior performance on both with an accuracy of 100% on the first dataset and 86.47% on the second. This was achieved with the lowest training costs, and better performance compared to previous works we evaluated that used the same databases. These results provide valuable insights and advance the development of brain-computer interface (BCI) technology and design.

The scientific legacy of professor Y.V. Krykavskyi: development of logistics theory in Ukraine and future perspectives

The article presents the first attempt at scientometric analysis of the scientific legacy of the prominent Ukrainian scholar, Doctor of Economic Sciences, Professor Yevhen Vasylovych Krykavskyi. The main stages of his scientific work and its impact on the development of the general theory and practice of logistic science in Ukraine are identified. It is demonstrated that Y.V. Krykavskyi himself formulated the theoretical foundations of logistics as a separate direction of scientific research in the field of economic sciences, established the basic conceptual framework, founded a scientific school of marketing and logistics, and trained a large number of candidates and doctors of sciences who continue and deepen the theoretical developments of the great scientist, as well as expand the spheres of practical application of logistic concepts, tools, and methods, and supply chain management in new economic conditions.

Đặc điểm lâm sàng và hiệu quả điều trị của liệu pháp oxy cao áp ở bệnh nhân chóng mặt ngoại biên

This paper presents “Clinical characteristics and therapeutic efficacy of hyperbaric oxygen therapy in patients with peripheral vertigo” to determine the clinical features of peripheral vertigo and its therapeutic efficacy. The study was carried out at Hyperbaric Oxygen Center (Southern Branch of Joint Vietnam-Russia Tropical Science and Technology Research Center) from October 2021 to December 2022, with 60 patients, divided into 2 groups. Group 1 consisted of 30 patients was treated with hyperbaric oxygen therapy (HBOT) and group 2 consisted of 30 patients was treated with HBOT and drugs (vestibular inhibitors, antiemetics and brain tonics). The results showed that: vertigo often occured when changing head position, vertigo accompanied by nausea, loss of balance. After the treatment, the group treated with HBOT and drugs, the patient's condition improved better, the level gradually increased with HBOT. In the group treated with HBOT and drugs, the mean score before treatment was 12.5 points, after 10 days of treatment was 4.37 points, after 20 days of treatment decreased to 0.63 points and after 30 days of treatment to 0.27 points. Particularly, in the group treated with HBOT, this rate was 12.33 points, respectively; 6.37 points; 2.1 points and 0.97 points (p < 0.05).

Approach to automating the construction and completion of ontologies in a scientific subject field

Domain ontologies facilitate the organization, sharing, and reuse of subject areas. Building a software ontology is labor-intensive and time-consuming. In the process of obtaining a software ontology, it is required to analyze a huge number of scientific publications relevant to the software being modeled. The process of ontology replenishing with information from a huge number of scientific publications can be facilitated and accelerated through the use of lexical-syntactic patterns of ontological design. In this paper, we consider the possibility of automated construction of scientific subject area ontologies based on a heterogeneous patterns system of ontological design. This system includes ontological design patterns and is intended for ontology developers. System also includes automatically built lexical and syntactic patterns, which help to automatic replenishment of the ontology with information extracted from natural language texts.

Кластеризация научных публикаций по морскому автономному надводному судовождению для выявления кластеров ключевых слов

An approach to structuring scientific publications is proposed using the example of scientific works on marine autonomous surface navigation, which allows for data mining with clustering and visualization of the main keywords and phrases related to the designated topic. The resource of the Russian scientific electronic library was used as a source for obtaining data eLIBRARY.RU. Information has been collected on 534 relevant scientific publications for the period from 2013 to the beginning of 2024, containing the title of the work, the year of publication, the list of authors and their affiliation, keywords and phrases, etc. A database for intellectual analysis has been formed, containing 1304 keywords or phrases indicated by the authors of scientific publications related to the selected topic. Data mining was performed using an open source software package for visualization and analysis of related data Gephi. The processing results are presented in the form of undirected graphs. The undirected graphs obtained are presented, and the characteristics of certain graphs for various kernel parameters are indicated. Clusters of keywords or phrases and connections between them have been identified, demonstrating current trends in the development of the chosen scientific field. With the advent of new scientific publications on marine autonomous surface navigation, the graphs will change, fixing new connections between the authors of scientific publications, key words and phrases. Such an approach to data processing may be useful for students, graduate students and researchers to identify a pool of keywords and phrases that need to be paid attention to when studying this topic.

Environmental Blindspots: Identification and Mitigation using Technologies, Education, and Policies

Objectives:“Environmental Blindspots” are newly defined as a type of social problem within the realm of various environmental pollution and climate issues, wherein they are pushed down in priority due to factors such as corporate profit, consumer preferences, and government regulations, consequently remaining unresolved. This ultimately leads citizens to experience a sense of guilt. Despite the significant influence they wield on the welfare of current and future generations, various environmental social issues characterized by environmental blindspots (such as micro-hazardous substances like microplastics and environmental hormones) fail to become major considerations in societal decision-making. Consequently, they are not actively discussed within the social community. This absence of social consensus on these issues reflects the current situation. As a result, citizens repeatedly make choices that do not prioritize environmental values due to a perception of powerlessness stemming from the absence of environmentally friendly options, the belief that the issue is too immense to tackle individually, and lack of knowledge about specific actions to take for environmental problem-solving, among other factors. In this process, they experience involuntary and deliberate emotions of guilt. Since environmental blindspots are issues collectively experienced by the societal community comprising citizens, businesses, and government, solutions must also be derived collectively through collective thinking. This review has endeavored to incorporate such efforts.Methods:In this review, to develop a more effective interdisciplinary research methodology for addressing the previously mentioned environmental social issues, ten interdisciplinary researchers from the Environmental Engineering and Social Sciences fields at the center for convergence research (SEBIS) collaborated, leveraging their respective expertise to document literature survey results. Firstly, they reported on the environmental behavior, toxicity, distribution, and regulatory status of micro-hazardous substances, namely (micro)plastics and volatile organic compounds, which are the research subjects of the Environmental Blindspot Research Center. Secondly, they compiled relevant treatment technologies. Subsequently, they described the socio-structural causes of environmental blindspots and various solutions to environmental social issues through social science methodologies.Results and Discussion:To address the environmental blindspots, a key environmental social issue, it is necessary to advance various environmental technologies alongside responsible production by businesses and the enhancement of citizen environmental awareness. It is crucial for the government to institutionalize policies in the public domain to achieve this. Understanding the structural roles of citizens, businesses, and government is essential. It requires ethical consumer awareness and active participation, public campaigns and education, as well as effective government environmental policies to incentivize environmental friendly technological innovations by companies.Conclusion:In this review, the issue of environmental blindspots as an environmental social issue is being addressed comprehensively for the first time. Through this, we aim to establish an effective communication and cooperation system among social entities to explore solutions to environmental blindspots, and to propagate this ability to address social issues to future academic generations.

Research on the aerodynamic causes of airplane wings

As the fastest means of transportation in the globe for people, airplanes are receiving more and more attention in the fields of science and engineering. Experts around the world try to figure out methods of increasing safety for airplanes, while it may elicit an ongoing debate on how to explain wing aerodynamics. This essay delves into the intricate world of wing aerodynamics, first presenting an analysis of forces acting on the airplane which could help provide basic knowledge and serve as background information. Three main theories, Bernoullis equation, Newtons third law, and the Coanda effect are analyzed and compared here to get a relatively accurate explanation. By figuring out how wings work to make a plane uplift in the air, the results help improve the design of traditional airliners and increase their stability.

Seamless integration of Internet of Things, miniaturization, and environmental chemical surveillance.

IoT is a game-changer across all fields, including chemistry. Embracing sustainable practices and green chemistry, the miniaturization and automation of systems, and their integration into IoT is key to achieving these principles, as a rising trend with momentum. Particularly, IoT and analytical chemistry are linked in the rapid exchange of analytical data for environmental, industrial, healthcare, and educational applications. Meanwhile, cooperation with other fields of science is evident, and there is a prompt and subjective analysis of information related to analytical systems and methodologies. This paper will review the concepts, requirements, and architecture of IoT and its role in the miniaturization and automation of analytical tools using electronic modules and sensors. The aim is to explore the standards and perspectives of IoT and its interaction with different aspects of analytical chemistry. Additionally, it aimed to explain the basics and applications of IoT for chemists, and its relevance to different subfields of analytical chemistry, particularly in the field of environmental chemical surveillance. The article also covers updating IoT devices and creating DIY-based degradation devices to enhance the educational aspect of chemistry and reduce barriers to lab facilities and equipment. Lastly, it will explore how IoT is really important and how it's going to significantly impact analytical chemistry.

The view of synthetic biology in the field of ethics: a thematic systematic review

Synthetic biology is designing and creating biological tools and systems for useful purposes. It uses knowledge from biology, such as biotechnology, molecular biology, biophysics, biochemistry, bioinformatics, and other disciplines, such as engineering, mathematics, computer science, and electrical engineering. It is recognized as both a branch of science and technology. The scope of synthetic biology ranges from modifying existing organisms to gain new properties to creating a living organism from non-living components. Synthetic biology has many applications in important fields such as energy, chemistry, medicine, environment, agriculture, national security, and nanotechnology. The development of synthetic biology also raises ethical and social debates. This article aims to identify the place of ethics in synthetic biology. In this context, the theoretical ethical debates on synthetic biology from the 2000s to 2020, when the development of synthetic biology was relatively faster, were analyzed using the systematic review method. Based on the results of the analysis, the main ethical problems related to the field, problems that are likely to arise, and suggestions for solutions to these problems are included. The data collection phase of the study included a literature review conducted according to protocols, including planning, screening, selection and evaluation. The analysis and synthesis process was carried out in the next stage, and the main themes related to synthetic biology and ethics were identified. Searches were conducted in Web of Science, Scopus, PhilPapers and MEDLINE databases. Theoretical research articles and reviews published in peer-reviewed journals until the end of 2020 were included in the study. The language of publications was English. According to preliminary data, 1,453 publications were retrieved from the four databases. Considering the inclusion and exclusion criteria, 58 publications were analyzed in the study. Ethical debates on synthetic biology have been conducted on various issues. In this context, the ethical debates in this article were examined under five themes: the moral status of synthetic biology products, synthetic biology and the meaning of life, synthetic biology and metaphors, synthetic biology and knowledge, and expectations, concerns, and problem solving: risk versus caution.

Recent Advances in Biochar: Synthesis Techniques, Properties, Applications, and Hydrogen Production

The field of material sciences has evolved vastly in the last two decades, largely due to the discovery of carbon nanomaterials such as graphene and its derivatives. Although they offer positive characteristics, the cost of production and material processing of these carbon nanomaterials has limited their application. However, scientists have started searching for cheaper and more environmentally friendly alternatives. Biochar, a carbonaceous material derived from biowaste, is the most viable alternative, as it offers characteristics on par with traditional carbon nanomaterials. This review will discuss the production of biochar from biomass, methods of production, the effects various conditions have on the production of biochar, biomass selection, current biochar applications, and the potential biochar has to produce hydrogen as an energy carrier.

NSGAN: a non-dominant sorting optimisation-based generative adversarial design framework for alloy discovery

The design and discovery of new materials is fundamental to advancing scientific and technological innovation. The recent emergence of the materials genome concept holds great promise in revolutionising materials science by enabling the systematic utilisation of data for efficient prediction and optimisation of ‘superior’ materials. However, the materials genome approach can be stymied by the vast complexity of design spaces, which often demand substantial computational resources and sophisticated data processing capabilities. To address these challenges, this work introduces a generative design framework called the non-dominant sorting optimisation-based generative adversarial networks (NSGAN). Capitalising on the synergies of genetic algorithms (GA) and generative adversarial networks (GANs), NSGAN provides a robust and efficient approach for tackling high-dimensional multi-objective optimisation design problems. To validate the efficacy of the proposed framework, we applied the model to a comprehensive dataset of aluminium alloys. Additionally, an online tool was created as a supplementary resource, offering a brief introduction to this innovative method for the wider scientific community. This study explores the potential of a predictive and data-driven approach in material design, indicating a promising pathway for widespread applications in the field of materials science.

Methods for studying structural oppression in quantitative family research

AbstractResearchers have long documented the impact of social inequalities on family life. Most family research has focused on inequalities at the individual and family levels, and extant studies on macro‐level conditions have primarily examined economic conditions and specific family‐focused social policies. Yet, an emerging body of largely conceptual research suggests that structural inequities also have enormous power to shape families. Structural racism, structural sexism, and structural sexual and gender minority oppression, and other forms of structural injustice operate across various levels (macro, meso, and micro) and systems (e.g., educational, economic, political, criminal‐legal, etc.), to influence individuals' social environments and everyday lives in ways that may impact how, when, and where people form families. Structural oppression, moreover, may influence relationship quality, caregiving patterns, child outcomes, and various other aspects of family life. Yet, the consequences of these structural forces for families have not yet been thoroughly examined. In this article, we (1) develop a conceptual framework linking structural oppression to family characteristics and outcomes, (2) outline innovative approaches for conceptualizing and measuring structural oppression and describe how incorporating these approaches can move the field of family science forward, and (3) make several recommendations regarding best practices and fruitful avenues for future research.

Structural Impediments Impacting Early-Career Women of Color STEM Faculty Careers

Women of Color faculty continue to experience many challenges in their careers, especially in the science, technology, engineering, and mathematics (STEM) fields. As such, more research is needed that considers structural issues inhibiting their success. Using structuration theory and critical race feminism as a conceptual framework, we conducted semi-structured interviews with 19 faculty and administrators in STEM departments at higher education institutions to investigate their perceptions of structural impediments impacting early-career Women of Color STEM faculty careers. Our findings revealed the need to establish policies that are clear, documented, and transparent. Additionally, incremental approaches to tenure and promotion evaluations should be reconsidered, especially when this approach may position Women of Color faculty to appear as if they are underperforming, when the opposite may be true. Furthermore, as higher education institutions endeavor to diversify the professoriate, this study is significant in enabling institutions and STEM departments to be aware of systemic issues confronting them to make significant inroads in retaining and advancing Women of Color faculty in these disciplines.

Application of artificial intelligence to hepatobiliary cancer clinical outcomes research

The rapid evolution of modern technology has made artificial intelligence (AI) an important emerging tool in healthcare. AI, which is a broad field of computer science, can be used to develop systems or machines equipped with the ability to tackle tasks that traditionally necessitate human intelligence. AI can be used to perform multifaceted tasks that involve the synthesis of large amounts of data with the generation of solutions, algorithms, and decision support tools. Various AI approaches, including machine learning (ML) and natural language processing (NLP), are increasingly being used to analyze vast healthcare datasets. In addition, visual AI has the potential to revolutionize surgery and the intraoperative experience for surgeons through augmented reality enhancing surgical navigation in real-time. Specific applications of AI in hepatobiliary tumors such as hepatocellular carcinoma and biliary tract cancer can improve patient diagnosis, prognostic risk stratification, as well as treatment allocation based on ML-based models. The integration of radiomics data and AI models can also improve clinical decision making. We herein review how AI may be of particular interest in the care of patients with complex cancers, such as hepatobiliary tumors, as these patients often require a multimodal treatment approach.

STEM Pathway and College Progression: The Link Between Engineering CTE and Postsecondary Outcomes for Students With Learning Disabilities

Despite growing calls to increase diversity in science, technology, engineering, and mathematics (STEM) fields, students with learning disabilities (SWLDs) remain underrepresented in STEM at the postsecondary level. Considering this call for increased diversity as a means to expand and strengthen STEM success, we used the High School Longitudinal Study of 2009 to explore how participation in engineering career and technical education (E-CTE) links to postsecondary educational outcomes for SWLDs. Particularly, we examined how E-CTE participation relates to postsecondary remedial course taking, enrollment in a 4-year postsecondary institution, and declaration of a STEM major. Results from school fixed-effects estimations suggest that each credit of E-CTE earned is associated with fewer remedial college courses, a higher likelihood of enrolling in a 4-year as opposed to sub-baccalaureate institution, and increased odds of declaring a STEM major. To conclude, we discuss the implications of our findings for both policymakers and practitioners.

Bibliometric Analysis of the Development of International Scientific Collaboration of Nguyen Tat Thanh University (Vietnam) over the last Decade

This study explores the key features of scientific articles resulting from international collaborations between Nguyen Tat Thanh University (NTTU), a private higher educational body in Vietnam, and scholars from other countries during the 2011-2023 period. Metadata of 1505 articles indexed in the Scopus database has been downloaded to conduct a bibliometric analysis using VOSviewer and Biblioshiny software. Findings reveal that NTTU’s international collaboration publication record can be divided into two main sub-periods: before 2018, accounting for only 9% of the total publication, and after 2019, comprising over 91%. The major contributors to NTTU’s international collaboration come from scholars in Korea, the USA, and Singapore, while contributions from scholars in other countries are relatively less significant. Only three strong research groups are identified, led by some permanent scientists of NTTU, and some from other institutions in Vietnam, Singapore and the USA. Consequently, the diversity of strong research directions of NTTU is somewhat restricted, primarily focusing on a few specific topics with medical science, wastewater treatment, adsorption, and photocatalysis. Excluding most cited articles in the field of medical science, main authors of nine over ten the top cited articles in other research fields are not permanent scientists of NTTU, suggesting that contributions of NTTU in these important studies were not significant.

Role Of Artificial Intelligence in Big Database Management

This exploration article digs into the significant effect of (artificial intelligence) AI, on big Data base management in the field of computer science by utilizing the broad abilities of artificial intelligence AI technologies, this study investigates different strategies to improve the oversight and administration of huge information bases. Through an exhaustive assessment of existing academic works, itemized contextual investigations, and master experiences, the article disentangles the mind-boggling combination of Ai’s integration and its important impacts on database management rehearses. Covering an extensive variety of artificial intelligence aspects, for example, AI, regular language handling, and profound realizing, this academic request plans to explain the complex job of computer-based intelligence in the domain of big database management. As a critical commitment to scholarly talk, this research article fills in as an original work, planning the groundbreaking excursion of Ai transformative into the center of data base management system, introducing another time of development and productivity in the computerized scene.