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.

A Study on Optimizing the Maximal Product in Cubic Fuzzy Graphs for Multifaceted Applications

Graphs in the field of science and technology make considerable use of theoretical concepts. When dealing with numerous links and circumstances in which there are varying degrees of ambiguity or robustness in the connections between aspects, rather than purely binary interactions, cubic fuzzy graphs (CFGs) are more adaptable and compatible than fuzzy graphs. To better represent the complexity of interactions or linkages in the real world, an emerging CFG can be very helpful in achieving better problem-solving abilities that specialize in domains like network analysis, the social sciences, information retrieval, and decision support systems. This idea can be used for a variety of uncertainty-related issues and assist decision-makers in selecting the best course of action through the use of a CFG. Enhancing the maximized network of three cubic fuzzy graphs’ decision-making efficiency was the ultimate objective of this study. We introduced the maximal product of three cubic fuzzy graphs to investigate how interval-valued fuzzy membership, fuzzy membership, and the miscellany of relations are all simultaneously supported through the aspect of degree and total degree of a vertex. Furthermore, the domination on the maximal product of three CFGs was illustrated to analyze the minimum domination number of the weighted CFG, and the proposed approach is illustrated with applications.

Spatially Resolved Single-Cell Omics: Methods, Challenges, and Future Perspectives.

Overlaying omics data onto spatial biological dimensions has been a promising technology to provide high-resolution insights into the interactome and cellular heterogeneity relative to the organization of the molecular microenvironment of tissue samples in normal and disease states. Spatial omics can be categorized into three major modalities: (a) next-generation sequencing-based assays, (b) imaging-based spatially resolved transcriptomics RNA approaches including in situ hybridization/in situ sequencing, and (c) imaging-based proteomics. These modalities allow assessment of transcripts and proteins at a cellular level, generating large and computationally challenging datasets. The lack of standardized computational pipelines to analyze and integrate these nonuniform structured data has made it necessary to apply artificial intelligence and machine learning strategies to best visualize and translate their complexity. In this review, we summarize the currently available techniques and computational strategies, highlight their advantages and limitations, and discuss their future prospects in the scientific field.

Synthesis of special feature —Tailored Restoration Response: Predictions And Guidelines For Wetland Renewal

Growing understanding of decision‐making and environmental science is essential to carry out a successful wetland renewal. To foster this understanding and integrate knowledge on wetland renewal, we convened a diverse group of researchers, policymakers, and practitioners at an online symposium held on 23 November 2021. Following the symposium, we curated 22 papers from a global community of wetland experts for the special feature on “Wetland Renewal” in Restoration Ecology. This special feature encompasses findings from 15 field‐based experiments and 7 data‐based papers (P). The research spans various scientific fields such as: Biodiversity Conservation (P15), Coastal Engineering (P4, P8, and P9), Plant Ecology (P1, P2, P10, P12, and P13), Invasion Ecology (P7), Social Science (P3), Peat Soil Science (P6), Wildlife Ecology (P5, P11, and P22), Ecological Modeling (P16, P17, P18, P19, and P20), Microbiology (P22), and Policy and Law (P21).

Perception of Violence in Multimodal Text: Cross-Disciplinary Approach

The article deals with the linguistic and psychological concepts explaining the perception of multimodal texts that imply information about violence. The importance of the subject is verified by the task of countering the spread of ideologies of violence, extremism, and terrorism in Internet communication. The multimodal text is considered a popular means of propagating radical ideas relating to incitement to social discord. The absence of complex models explaining the transmission of violence through multimodal texts is observed. It is shown that linguistic and psychological concepts can be relevant resources for building such a model. The purpose of the article is to generalize concepts in the form of intra- and extralinguistic factors that determine the perception of information about violence in a multimodal text. The generalization of cognitive linguistic theories into the group of intralinguistic factors is complemented by the conclusion that the semantic structure of a multimodal text is formed by visual, sign, and verbal coding systems; the perception of information about violence is determined by the typicality of linguistic means and the presence of logical and semantic links between the elements of a multimodal text. The conclusion is made about the influence of aggressiveness, personal attitude toward violence, and the experience of using violence on the perception of multimodal information about violence by the reader. The article may be interesting to linguists, psychologists, and a wide range of researchers in the field of humanities and humanities-related social sciences.

On heritage pharmacology: Rethinking ‘heritage pathologies’ as tropes of care

This article develops the concept of heritage pharmacology as an encompassing critical framework in order to radically recast the interactions and efficacies of heritage as a particularly potent pharmacology of care. I critically engage with Stiegler's philosophic reflections On Pharmacology, which builds on Derrida's work and recasts pharmacology – a term usually reserved for that branch of the biomedical sciences dealing with drugs and their interactions and efficacies – in order to draw out the ‘curative-toxic’ dimensions at play in wider care tropes. By placing core concepts and practices of heritage and pharmacology in critical dialogue, my aim as heritage critic is to gain mutual insights into ‘care’, as that which links together the two domains of heritage and health, as otherwise distinct discourses, concepts, technics, and practices. My specific intervention rethinks the crucial role of ‘heritage pathologies’ and the underpinning memory-work at play within these tropes while grounding these in a case study of Jerusalem Syndrome (JS). I argue that it is the dynamic of heritage pathologies, best crystallized in JS debates, that invests us in the wider Stieglerian quest/ion of ‘pharmacology’, as a concern with ‘what makes life worth living’. Such quests ultimately take this article into the realpolitik of Palestine.

Single-exposure femtosecond laser direct writing of Salvinia-inspired micropatterned functional surface

Bioinspired functional surfaces have attracted considerable attention within multiple scientific and industrial fields. In particular, the hollow hierarchical structure and chemical heterogeneity endow Salvinia leaves with superhydrophobicity and underwater air retention capability. However, replicating complex three-dimensional Salvinia-like patterns at the microscale currently relies on time-consuming additive manufacturing methods, preventing their wide adoption in industrial applications. Here, we report a high-throughput femtosecond laser direct writing strategy based on the quadrifurcate abruptly autofocusing beam for the single-exposure fabrication of Salvinia-like microstructures. Combined with chemical functionalization, both the hollow morphology and heterogeneous chemical properties of the natural counterpart were mimicked. The obtained bioinspired surfaces can repel and manipulate water droplets, and maintain superhydrophobicity even immersed underwater. The proposed single-exposure fabrication strategy is expected to contribute to the mass production of Salvinia-inspired surfaces, whose unique wetting properties promise great potential in chemical engineering, micro bioanalysis, and microfluidic devices.

Developing a circular design framework: Co‐creation and validation of a circular product and service design tool

AbstractSustainable products are at the core of the circular economy, which is gaining momentum in scientific, economic, and policy fields. However, existing research in the field of circular product design remains fragmented. The literature has generally tended to focus on material or resource efficiency, while other complex issues related to product ecosystem also exist, such as the needs of the ecosystem (non‐human) and human user, circular challenge, and circular business model. By using a co‐creation approach, this study aims to create and validate a circular product design framework (CD‐Framework) and a self‐assessment tool for circular product design (CD‐Tool) that facilitates an understanding of how product circularity can be improved from the product ideation. The proposed CD‐Framework consists of 10 interconnected categories: circular challenge; circular business model; production; digital fabrication technologies; materials; branding and communication for circularity; packaging, distribution and logistics; user; usage; and after usage. The CD‐Tool was designed as a tool to aid product developers from various industry sectors in the self‐assessment of the circularity of product design. We contribute to developing tools that accelerate integration of circularity into product design through product‐level and ecosystem‐level considerations.

Artificial Receptor in Synthetic Cells Performs Transmembrane Activation of Proteolysis.

The designof artificial, synthetic cells is a fundamentally important and fast-developing field of science. Of the diverse attributes of cellular life, artificial transmembrane signaling across the biomolecular barriers remains a high challenge with only a few documented successes. Herein, the study achieves signaling across lipid bilayers and connects an exofacial enzymatic receptor activation to an intracellular biochemical catalytic response using an artificial receptor. The mechanism of signal transduction for the artificial receptor relies on the triggered decomposition of a self-immolative linker. Receptor activation ensues its head-to-tail decomposition and the release of a secondary messenger molecule into the internal volume of the synthetic cell. Transmembrane signaling is demonstrated in synthetic cells based on liposomes and mammalian cell-sized giant unilamellar vesicles and illustrates receptor performance in cell mimics with a diverse size and composition of the lipid bilayer. In giant unilamellar vesicles, transmembrane signaling connects exofacial receptor activation with intracellular activation of proteolysis. Taken together, the results of this study take a step toward engineering receptor-mediated, responsive behavior in synthetic cells.

Revolutionizing Cybersecurity with Machine Learning: A Comprehensive Review and Future Directions

In the realm of computing, data science has revolutionized cybersecurity operations and technologies. The key to creating automated and intelligent security systems lies in extracting patterns or insights from cybersecurity data and building data-driven models. Data science, encompassing various scientific approaches, machine learning techniques, processes, and systems, studies real-world occurrences through data analysis. Machine learning techniques, known for their flexibility, scalability, and adaptability to new and unknown challenges, have been applied across many scientific fields. Cybersecurity is rapidly expanding due to significant advancements in social networks, cloud and web technologies, online banking, mobile environments, smart grids, and more. Various machine learning techniques have effectively addressed a wide range of computer security issues. This article reviews several machine learning applications in cybersecurity, including phishing detection, network intrusion detection, keystroke dynamics authentication, cryptography, human interaction proofs, spam detection in social networks, smart meter energy consumption profiling, and security concerns associated with machine learning techniques themselves. The methodology involves collecting a large dataset of phishing and legitimate instances, extracting relevant features such as email headers, content, and URLs, and training a machine learning model using supervised learning algorithms. These models can effectively identify phishing emails and websites with high accuracy and low false positive rates. To enhance phishing detection, it is recommended to continuously update the training dataset to include new phishing techniques and employ ensemble methods that combine multiple machine learning models for improved performance

EDITORIAL

Greetings to the Readers of Jurnal Teknosains!We are proud to present the latest edition of Jurnal Teknosains in Volume 13, Number 2, June 2024. In a world that is constantly evolving, innovation and sustainable development are crucial foundations for progress in the fields of technology and science. This edition takes us through a series of research articles that highlight various important aspects in this regard, ranging from the development of renewable energy technologies to efforts in addressing global pandemics. In broad strokes, we endeavor to provide an overview of the eight research articles in the field of technology and science published in this June 2024 edition.

Reply to "Various issues around the $L_1$-norm distance"

A distance function between two random variables or vectors was proposed in 2003 in a Ph.D. dissertation. Initially called a probability metric, it is now known as "Łukaszyk-Karmowski metric" or LK-metric and has been successfully applied in various fields of science and technology. It does not satisfy the identity of indiscernible (Leibniz's law) axiom of the metric, the ontological axiom also invalidated by the ugly duckling theorem. This note addresses two false claims made in a preprint that LK-metric is the same as the mean absolute difference and that it is ill-defined. The fallacy of the first claim is straightforward: the mean absolute difference is defined solely for independent and identically distributed random variables, contrary to LK-metric. Thus, if one considers E|X-X|, then the random variable X must be independent of itself, which implies its degenerate probability distribution and E|X-X|=0. If X has a degenerate probability distribution, then Y, which is identically distributed as X, also has a degenerate probability distribution and E|X-X|=0=E|X-Y|, invalidating the second claim.

Mechanochemistry in Organic Synthesis: An Italian Journey through Innovations

Mechanochemistry, as an enabling technology, harnesses mechanical force to drive chemical reactions, presenting compelling advantages in organic synthesis within the principles of green chemistry. This review explores how its unique advantages and alignment with sustainable practices have been widely developed in different scientific fields in Italy. As a transformative strategy for organic synthesis, mechanochemistry has been portrayed in this review as a valuable synthetic alternative due to the various advantages, such as solvent reduction and new reaction pathways, that its use brings. Nonetheless, the improvements brought about by its use have also been crucial in other fields of chemistry described by Italian scientists. In this whole context, Italian researchers have analysed both already optimised processes and new feasible pathways, paving the way for new avenues previously hampered by all the limitations that belong to in‐solution chemistry.