Possibility Of Application Research Articles

그림책을 활용한 초등학교 1학년 한글 교육에 대한 교사의 경험

The purpose of this study is to investigate educational values and possibilities of application by analyzing teacher’s experiences in teaching Hangeul using picture books to first grade elementary school students. The participant is teacher A working at Seoul B Elementary School. This study conducted the procedures of curriculum analysis, picture book selection, and making Hangeul lesson plans using picture books from February 20th to March 31st, 2023, and implemented lessons for a total of 16 times from April 3rd to May 19th, June 12th to June 27th, 2023. Data were collected and analyzed qualitative data such as interviews, teacher journals, activity results, and photos. The results are as follows. The teacher experienced lessons that had students focused regardless of their individual differences, were playful rather than academic, facilitated voluntary reading and writing, had the teacher fun and excitement, had fellow teachers want to apply lessons and required sufficient number of class hours and assistants. In conclusion, this study is meaningful in that Hangeul education using picture books has educational significance to both teachers and students and it is a practical and effective teaching-learning method in school.

Optimization and Bioactive Evaluation of Bifurcaria bifurcata Antioxidant-Rich Extracts for Functional Food and Pharmaceutical Applications.

In recent years, consumers have been increasingly interested in natural, healthier, functional foods, with a focus on sea-based products such as algae. Bifurcaria bifurcata (BB) is a macroalga that belongs to the Phaeophyceae class. These brown algae are recognized as the source of bioactive molecules of great interest to the pharmaceutical and nutraceutical industries. The present work applied response surface methodology to optimize the microwave-assisted extraction of the poorly studied algae. The optimization variables were time, pressure, and solvent composition (ethanol/water) and the response parameters selected were yield, total phenolic and flavonoid content, and the antioxidant profile by evaluating DPPH•+, ABTS•+ scavenging activity, and β-carotene discoloration capacity. The results obtained reveal remarkable bioactivity of the crude extract of BB with positive results as an antioxidant and antimicrobial agent. Furthermore, the BB extract's capacity to inhibit enzymes related to neurodegenerative diseases and its anti-inflammatory and anti-proliferation activity open the possibility of future food or pharmaceutical applications.

수묵(⽔墨) 기법을 응용한 티타늄 구조색 발색 기법 연구

The purpose of this study is to present new color application possibilities using an anodizing device so that titanium, which is friendly to the human body and the environment, can be widely used in the art and design fields.In this study, it was found that controlling the appropriate viscosity of the glue that bonds titanium to paper is of utmost importance in order to develop the planned color. It was found that when the viscosity of the glue is low, the adhesion is weak, making it easy for the titanium to separate from the paper, and when the viscosity is high, the color development time is longer than normal. This study is a new structural color application method that has not been seen in the titanium anodization method until now. Through this study, we were able to confirm its usability in a variety of fields as well as art and design.

Flexible and Large‐Scale Liquid Metal Frequency‐Selective Surfaces: Enhanced Tuning through Mechanical Reconfiguration

The tuning capability is crucial for broadening the application possibilities of frequency‐selective surfaces (FSSs). Flexible and stretchable FSSs have attracted widespread research interest due to their ability for adhering to curved surfaces conformally and reconfiguring electromagnetic (EM) wave transmission performance mechanically. However, conventional metal FSSs lack sufficient flexibility and deformability due to material constraints, resulting in diminished durability and limited EM tuning range. In this article, a design approach for flexible liquid metal FSS (LMFSS), which can conform to curved structures and achieve a wide range of EM wave tuning via mechanical stretching without structural damage, is presented. The fabrication of LMFSS is simplified using silicone elastomer curing and liquid metal inkjet printing, avoiding the complexities of traditional microchannel techniques. In the experimental results, it is demonstrated that the designed LMFSS achieves a tuning range of up to 16% under biaxial stretch strains not more than 25%. The tuning mechanism is explored through mechanical–EM simulations and equivalent circuit analyses. Additionally, the tuning phenomenon observed in another flexible LMFSS in this study underscores the portability of the design approach and tuning mechanism. In this research, a promising direction for tunable flexible LMFSS applications is offered.

Fast and Efficient Fabrication of Functional Electronic Devices through Grayscale Digital Light Processing 3D Printing.

Fabricating polymeric composites with desirable characteristics for electronic applications is a complex and costly process. Digital light processing (DLP) 3D printing emerges as a promising technique for manufacturing intricate structures. In this study, polymeric samples are fabricated with a conductivity difference exceeding three orders of magnitude in various portions of a part by employing grayscale DLP (g-DLP) single-vat single-cure 3D printing deliberate resin design. This is realized through the manipulation of light intensity during the curing process. Specifically, the rational resin design with added lithium ions results in the polymer cured under the maximum UV-light intensity exhibiting higher electrical resistance. Conversely, sections that are only partially cured retains uncured monomers, serving as a medium that facilitates ion mobility, consequently leading to higher conductivity. The versatility of g-DLP allows precise control of light intensity in different regions during the printing process. This characteristic opens up possibilities for applications, notably the low-cost, facile, and rapid production of complex electrical circuits and sensors. The utilization of this technique makes it feasible to fabricate materials with tailored conductivity and functionality, providing an innovative pathway to advance the accelerated and facile creation of sophisticated electronic devices.

Encapsulating Azolates Within Cationic Metal-Organic Frameworks for High-Energy-Density Materials.

Despite the synthesis of numerous cationic metal-organic frameworks (CMOFs), their counter anions have been primarily limited to inorganic Cl-, NO3 -, ClO4 -, BF4 -, and Cr2O7 2-, which have weak coordination abilities. In this study, a series of new CMOFs is synthesized using azolates with strong coordination abilities as counter anions, which are exclusively employed as ligands for coordinating with metals. Owing to the unique nitrogen-rich composition of azolates, the CMOFs demonstrate significant potential as high-energy-density materials. Notably, CMOF(CuTNPO) has an exceptionally high heat of detonation of 7375kJ kg-1, surpassing even that of the state-of-art CL-20 (6536kJ kg-1). To further validate the advantages of employing azolates as counter anions, analogues with azolates serving as ligands are also synthesized. The comparison study indicates that encapsulating azolates within the cationic frameworks confers both high energy and safety properties. X-ray data and quantum calculations indicate that their enhanced performance stems from stronger H─bonds and π-π interactions. This study introduces new roles for azolates in MOFs and expands possibilities for structural diversity and potential applications of framework materials.

Biocompatibility and Enamel Remineralization Potential of Titanium-Doped Phosphate Glasses With/Without Diode Laser Irradiation

This study investigates the biocompatibility and enamel remineralization potential of titanium-doped phosphate glasses (TDPG), third-generation materials with promising applications in dentistry. The biocompatibility of TDPG paste and its components (TDPG powder and polyacrylic acid liquid) was assessed using human gingival fibroblast cells (hGF) and human dental pulp stem cells (hDPSC). Cell attachment and viability were examined at 1, 3, and 7 days, comparing results with Nupro® Prophy paste and Teethmate, commonly used desensitizers, and positive control cells in normal tissue culture medium. Furthermore, the remineralization potential of these glasses with or without the use of diode laser irradiation on white spot lesions in enamel was explored at 12- and 21-days using Raman Spectroscopy and Field Emission Scanning Electron Microscopy (FESEM). The remineralization potential of TDPG was compared with Nupro® Prophy paste and Teethmate. Furthermore, both sound and demineralized enamel were also used as other controls.Results indicated that cells exposed to TDPG extracts displayed similar morphology and viability to positive control cells. While all tested pastes did not show remineralizing action after 12 days, Nupro® Prophy and Teethmate exhibited such action after 21 days. However, laser application enhanced remineralization potential for all pastes at both time points, with TDPG showing comparable results to Nupro® Prophy paste and significantly higher potential than Teethmate when used with laser at 21 days.In summary, this study reveals the biocompatibility and enhanced remineralization potential of TDPG when combined with diode laser irradiation. These findings signify innovative strides in dental materials and treatment modalities, offering new possibilities for advanced dental applications.

The involvement of proinflammatory cytokines in the pathogenesis of audiogenic epilepsy

Epilepsy is a heterogeneous disease, which determines the relevance of investigating the mechanisms of pathogenesis of its various types, including reflex epilepsy. Pharmacotherapy is common for the treatment of patients with epilepsy, however, despite the significant recent achievements, 20-30% of patients remain resistant to the ongoing treatment. The urgency of creating new antiepileptic drugs, in particular, immune ones is due not only to a significant proportion of pharmacoresistant cases, but also to the struggle for the quality of life of patients. The neuroinflammation system in animals with different genetically determined audiogenic epilepsy proneness was investigated. These genetic groups were Krushinsky–Molodkina rats (tonic seizures of maximum intensity in response to the action of sound) and “0” strain (control group, non-convulsive phenotype). The main proinflammatory cytokines levels in the dorsal striatum and brain stem in rats of these genetic groups were measured by multiplex immunofluorescence assay. Background levels of IL-1â, IL-6 and TNFá in the dorsal striatum of KM rats were significantly lower than in the control “0” strain rats, whereas in the brain stem in the “background” levels of these metabolites did not differ. Four hours after the sound exposure, the TNFá level in the dorsal striatum of KM rats was significantly lower than in “0” rats. In KM rats, after the sound exposure and subsequent tonic seizures, the levels of IL-1â and IL-6 in the dorsal striatum were significantly higher than in the background. The IL-2 content was not detected in the background in KM rats, whereas after audiogenic seizures its level was 14.01 pg/ml. In the brain stem of KM rats, the levels of IL-1â and TNFá after audiogenic seizures were significantly lower than in the background. In rats of the “0” strain, cytokine levels in the dorsal striatum after the sound exposure did not differ from those in the background, while IL-1ß levels in their brain stem were significantly lower than the background state. Particular modulating role of the studied proinflammatory cytokines in the pathogenesis of audiogenic epilepsy is assumed, as well as certain possibility of anti-inflammatory and immune drugs application in anticonvulsant and antiepileptic therapy.

Synthesis, Fluorescence Properties, Molecular Docking Studies, and Analysis of the Crystalline Structure of the Novel 5‐Imino‐7‐Aryl‐5H‐Thiazolo[3.2‐a]Pyrimidine‐6‐Carbonitrile and Its Derivatives

ABSTRACTThis study describes a simple, inexpensive, and effective method for the synthesis of new 5‐imino‐7‐aryle‐5H‐thiazolo[3,2‐a]pyrimidine‐3‐carbonitrile derivatives 4a‐e using a green procedure that does not require the use of heat or a base, creating a strategy that meets both economic and environmental demands. Various synthesized products were characterized via diverse techniques such as 1H‐NMR, infrared (FT‐IR), Mass spectroscopy (MS), and single crystal X‐ray diffraction. Using a fluorescence spectrometer, the 5‐imino‐7‐phenyle‐5H‐thiazolo[3.2‐a]pyrimidine‐3‐carbonitrile 4a has been tested as a potent fluorescent agent in mixture of DMSO/Water at 10−4 M in one hand, and on the other hand the results of our fluorescence evaluation studies with metal ions (Pb(II), Ba(II), Cd(II), Ni(II), Mn(II), Hg(II), Zn(II), Fe(II), Co(II), Cu(II), La(II), Cr(III), and Fe(III)) have shown that this compound exhibits a turn‐on and turn‐off of the fluorescence to 4a compound with these metals, what forms poor to good interaction by these ions. This result represents the emergence of a new potential ligand for the two heavy cations Cd(II) and Pb(II), which are toxic and polluting, and whose detection is currently of high interest. As well, In the molecular docking evaluation study, it was determined that the 4e molecule has an exceptional ability to inhibit the binding energy of the tubulin protein by −9.13 kcal/mmol, compared to other compounds. The results demonstrate the possibilities for a novel oral medication application.

Possibilities of Application of Adaptive Knowledge Testing Using Artificial Neural Networks in Training Economics Students

Possibilities of Application of Adaptive Knowledge Testing Using Artificial Neural Networks in Training Economics Students

Identification of molecules from tomato plant residues using sustainable green chemicals

AbstractHigh quantities of biomass produced in greenhouses create environmental problems as this side stream, and its downgraded products are not further used in the production cycle. The aim of our research was the identification and semi-quantification of molecules extracted from vegetative tomato plant residues with sustainable green alternative solvents using vacuum-assisted soxhlet and solid–liquid extraction to evaluate the possibilities for high-value applications for the first time. To identify compounds, gas chromatography–mass spectrometry (GC–MS) analysis and the Folin–Ciocalteau method were used. In sum, 285 different compounds have been assigned to 383 detected peaks using GC–MS analysis. The solvents 2-methyltetrahydrofuran (2-MTHF) and ethyl acetate, compared with ethanol and hexane, provided better results with a maximum number of 99 ± 8.83 compounds, a maximum total concentration of 5894.82 ± 586.48 and 3363.02 ± 71.14 mg naphthalene equivalent (NEQ) kgdw−1, and a total phenolic content of 2143.25 ± 155.17 and 1605.92 ± 66.46 mg gallic acid equivalent (GAE) kgdw−1, respectively. With 781.2 ± 112.66 and 718.25 ± 54.89 mg NEQ kgdw−1, the compound neophytadiene was the most common terpene in ethyl acetate and 2-MTHF extracts, respectively. It can be concluded that vegetative tomato plant residues contain a large variety of bioactive molecules. Green solvents, such as 2-MTHF and ethyl acetate, enhance the extraction of these molecules from the solid matrix. Graphical abstract

Signal processing for miniature mass spectrometer based on LSTM-EEMD feature digging

Miniature mass spectrometers exhibit immense application potential in on-site detection due to their small size and low cost. However, their detection accuracy is severely affected by factors such as sample pre-processing and environmental conditions. In this study, we propose a data processing method based on long short-term memory-ensemble empirical mode decomposition (LSTM-EEMD) to improve the quality of on-site detection data from miniature mass spectrometers. The EEMD method can clearly decompose the different physical feature components in the small-scale spectrometer signals, while the LSTM method can adaptively learn the internal feature relationships of the signals. Thus, by combining the two, the parameters for the EEMD signal reconstruction can be optimized in an adaptive manner, obtaining the optimized coefficients. Compared to the previous EEMD feature enhancement approach, the LSTM-EEMD method not only significantly improves the coefficient of determination (R2) and relative standard deviation (RSD) of the data, enhancing the linear range, but also achieves fully adaptive processing throughout the workflow, greatly boosting the efficiency. By leveraging a miniature mass spectrometer, data for N-acetyl-l-aspartic acid (NAA), 2-Hydroxyglutarate (2-HG), and γ-Aminobutyric acid (GABA) in actual blood samples have been obtained. The experimental results demonstrate that the LSTM-EEMD method can markedly enhance the accuracy and usability of the biological sample data in practical testing, providing new perspectives and possibilities for research and applications in the relevant domain.

A bibliometric analysis for remote sensing applications in bush encroachment mapping of grassland and savanna ecosystems

AbstractGrasslands and savannas are experiencing transformation and degradation due to bush encroachment (BE). BE has been monitored using restrictive traditional techniques that include field surveys and manual long-term observations. Owing to the limitations of traditional techniques, remote sensing (RS) is an attractive alternative to assess BE because of its generally high precision and return interval, cost-effectiveness, and availability of historical data archives. Furthermore, RS has an added advantage in its ability of acquiring global coherent data in near-real time compared to the snapshot acquisition mode with traditional surveying techniques. Despite its extensive application and vast possibilities, a critical synthesis for RS successes, shortcomings, and best practices in mapping BE in savannas and grasslands is lacking. Thus, broadly, the direction, which this type of investigation has taken over the years is largely unknown. This study sought to connect and measure the progress RS has made in mapping BE in grassland and savanna ecosystems through bibliometric analysis. One hundred and twenty-three peer-reviewed English written documents from the Web of Science and Scopus databases were evaluated. The study revealed 13.05% average annual publication growth, indicating that RS and BE mapping research in grasslands and savannas has been increasing over the survey period. Most published studies came from the USA, while the rest came from South Africa, China, and Australia. The results indicate that BE has been extensively mapped in grasslands and savannas using coarse to medium resolution data. As a result, there is a weak relationship (r² = 0.324) between the dependent variable (aerial images) and the independent variable (percentage of woody cover). This connotes the need to improve BE assessments in grasslands and savannas by integrating recent high-resolution data, machine learning algorithms and artificial intelligence.

Using an interactive simulation tool of national energy and climate policy planning to explore environmental policy options from the perspectives of different interest groups

AbstractTo reach the Paris Agreement goals, European governments have defined national contributions to the EU binding climate goals and have developed national climate and energy plans for 2021–2030 (NECPs). NECPs are detailed strategies in which governments can flexibly emphasize specific sectors, technologies and national energy policy choices. Every country has built its own energy modelling capacity for forecasting purposes. In most countries, this national modelling relies on optimization tools such as Markal or TIMES. For Latvia's energy sector, a system dynamics (SD) model was built to complement the TIMES model. The SD model deals with an integrated energy system, including the primary energy supply and transformation sector; energy distribution and storage system; and energy demand sectors (residential, tertiary, public, industry and transportation). Sectoral policies are presented in the Stella Architect interface. This study demonstrates how the interactive simulation tool was used in the Environmental Engineering Master level course ‘Environmental Policy and Economics’ as an experiential learning approach. The student assignment involved applying this tool to develop and analyse the energy transition policy package for one of four ideological interest groups: deep greens, bright greens, light greens and greys. Students had to assume a role and adopt its perspective by applying their border‐crossing competence and reflecting on selected policy mixes for that ideology. Various transition pathways, based on different ideologies, illustrate the possibilities for application. Results show that students were successful in fulfilling the assignment.

The Role of Coronary Imaging in Chronic Total Occlusions: Applications and Future Possibilities.

Chronic total occlusions (CTOs) represent a challenging scenario in coronary artery disease (CAD). The prevalence of CTOS in patients undergoing coronary angiography underscores the need for effective diagnostic and therapeutic strategies. Coronary angiography, while essential, offers limited insights into lesion morphology, vessel course, and myocardial viability. In contrast, coronary imaging techniques-including optical coherence tomography (OCT), intravascular ultrasound (IVUS), and coronary computed tomography angiography (CCTA)-provide comprehensive insights for each stage of CTO percutaneous coronary intervention (PCI). OCT facilitates the assessment of plaque morphology and stent optimization, despite low evidence and several limitations in CTO-PCI. IVUS offers deeper penetration, allowing managing proximal cap scenarios and guiding subintimal navigation. CCTA provides a non-invasive, three-dimensional view of coronary anatomy, enabling the precise evaluation of myocardial mass at risk and detailed procedural planning. Despite their individual limitations, these imaging modalities have enhanced the success rates of CTO-PCI, thus reducing procedural and long-term complications and improving patient outcomes. The future of CTO management lies in further technological advancements, including hybrid imaging, artificial intelligence (AI) integration, and improved fusion imaging. These innovations promise to refine procedural precision and personalize interventions, ultimately improving the care of patients with complex coronary artery disease.

3D-Printed Transducers for Solid Contact Potentiometric Ion Sensors: Improving Reproducibility by Fabrication Automation.

3D printing technology has become attractive in the development of electrochemical sensors as it offers automation in fabrication, customization on-demand, and reproducibility, among other features. Nonetheless, to date, solid contact potentiometric ion sensors have remained overlooked using this technology. Thus, the novelty of this work relies on demonstrating for the first time the usefulness of the multimaterial 3D printing approach to manufacture potentiometric ion-selective electrodes. The significance is indeed twofold. First, we discovered that by using the polyethylene terephthalate glycol (PETg) and polylactic acid-carbon black (PLA-CB) filaments together with a rational electrode design containing a well to accommodate the ion-selective membrane, a tight seal among all of the sensing materials is obtained. Importantly, this has mainly impacted the electrode-to-electrode reproducibility (ERSD0 ± 3 mV). Second, 75 ready-to-use electrodes can be printed in less than 3.5 h in a completely automated manner at a cost of ∼0.32 €/sensor. This feature may positively impact the suitability of further scaled-up production as well as the possibility of application in low-resource contexts. Overall, the presented outcomes are expected to encourage certain research directions to adopt using multimaterial 3D-printing approaches for producing highly reproducible solid contact potentiometric ion-selective electrodes, but are not restricted to them.

Polyoxometalate-mediated film bearing near-infrared photothermal self-healing property for seawater desalination

The use of solar-powered seawater desalination films frequently results in damage, making repairable property a crucial concern. Here, a photothermal self-healing seawater desalination film is created using poly-thioctic aclhydrazine (P-TAH) as the bulk material and Keggin-type polyoxometalate (POM) doped with TAH as an additive. The film’s self-healing ability is supported by the dynamic covalent connections in TAH, while the addition of POM improves mechanical strength and adds photothermal properties. The Young’s modulus increases from 7 to 195 MPa when 1/100 M ratio of POM is added to bulk material. With an energy efficiency of 94.4 %, the produced film’s evaporation efficiency achieves a high value of 2.75 kg m−2h−1. Furthermore, the injured film can be repaired while maintaining nearly the same mechanical strength and evaporation efficiency. The outdoor experiments indicate that the prepared film has a high performance under the irradiation of natural sunlight, which makes its possibility for the further applications. This work demonstrates the unreported photothermal self-healing property of POM-containing materials, in addition to presenting a generic approach for building POM-based seawater desalination films.

PDMS/CNT electrodes with bioamplifier for practical in-the-ear and conventional biosignal recordings

Objective.Potential usage of dry electrodes in emerging applications such as wearable devices, flexible tattoo circuits, and stretchable displays requires that, to become practical solutions, issues such as easy fabrication, strong durability, and low-cost materials must be addressed. The objective of this study was to propose soft and dry electrodes developed from polydimethylsiloxane (PDMS) and carbon nanotube (CNT) composites.Approach.The electrodes were connected with both conventional and in-house NTAmp biosignal instruments for comparative studies. The performances of the proposed dry electrodes were evaluated through electromyogram, electrocardiogram, and electroencephalogram measurements.Main results.Results demonstrated that the capability of the PDMS/CNT electrodes to receive biosignals was on par with that of commercial electrodes (adhesive and gold-cup electrodes). Depending on the type of stimuli, a signal-to-noise ratio of 5-10 dB range was achieved.Significance.The results of the study show that the performance of the proposed dry electrode is comparable to that of commercial electrodes, offering possibilities for diverse applications. These applications may include the physical examination of vital medical signs, the control of intelligent devices and robots, and the transmission of signals through flexible materials.

Bio-inspired spreadable multi-signal self-sensing covering composite material for intelligent devices

The spreadable materials with multi-sensing capabilities offer a wide range of application possibilities. They can be applied directly to the surface of intelligent devices, facilitating the creation of self-sensing shells. Despite significant progress in the development of such materials, expanding their diverse sensing capabilities remains a critical focus in this field. Here, we present a spreadable material endowed with multiple signal self-sensing capabilities. The material, which can be easily applied to the surface of devices, offers real-time monitoring of temperature, humidity, and device damage. This material comprised carbon black nanoparticles, carbon nanotubes, and sodium carboxymethyl cellulose, exhibiting excellent electrical conductivity. It exhibited a temperature coefficient of resistivity (TCR) of approximately 0.35%per°C, a humidity sensing sensitivity ranging from 3.57 to 4.31 Ω/RH%, and a strain sensing sensitivity gauge factor value of approximately 2.3. We anticipate that the proposed strategy utilizing spreadable multi-signal sensing materials will be extensively applied to the surfaces of various intelligent equipment, thereby furnishing a diverse range of signal data crucial for both safeguarding intelligent systems and enhancing environmental monitoring capabilities.

Blind Quantum Machine Learning with Quantum Bipartite Correlator.

Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this Letter, we introduce novel blind quantum machine learning protocols based on the quantum bipartite correlator algorithm. Our protocols have reduced communication overhead while preserving the privacy of data from untrusted parties. We introduce robust algorithm-specific privacy-preserving mechanisms with low computational overhead that do not require complex cryptographic techniques. We then validate the effectiveness of the proposed protocols through complexity and privacy analysis. Our findings pave the way for advancements in distributed quantum computing, opening up new possibilities for privacy-aware machine learning applications in the era of quantum technologies.