Analysis Techniques Research Articles

The effect of interdisciplinary teaching approach on the creative and critical thinking skills of gifted pupils

The aim of this study is to develop "Teaching Practices to Improve Thinking Skills Based on an Interdisciplinary Approach (PTSIA)" and to examine its effect on creative thinking and critical thinking skills of gifted fifth-grade students. This study used explanatory sequential design, which is a mixed research method that combines quantitative and qualitative research techniques. The study group of the research consisted of 62 gifted fifth grade students. For the students in the experimental group, the activities in accordance with the results prepared for the PTSIA for the students in the experimental group were carried out for a total of 45 h, 3 h per week during the extracurricular hours. The study used both quantitative and qualitative data analysis techniques. Quantitative data were analysed using the independent samples t-test, which is one of the relational statistics based on the comparison of two variables, experimental and control groups, and Cohen d values were calculated to determine the effect size. Qualitative data were analysed using descriptive and content analysis. It was concluded that the PTSIA prepared with the research were effective in developing creative and critical thinking skills, which are among the high-level thinking skills of gifted students. The applications were found to be beautiful, interesting, intriguing, and exciting by the students. It was concluded that teachers had positive opinions about the practices. Based on the results obtained from this study, the use of an interdisciplinary approach in teaching practices aimed at developing students' thinking skills will facilitate the acquisition of cognitive thinking abilities and their application to daily life. This approach will enable students to more clearly perceive the relationships between events, facts, and ideas, and learn to establish deeper connections between them by integrating various disciplines and perspectives.

Public opinion and Chinese exports: evidence from Twitter sentiment analysis

This paper employs web-crawling and sentiment analysis techniques to quantify public opinion and then investigates its effects on Chinese exports to trading partners during 2007–2019. The empirical results show that, after the control of possible reverse causality, negative China-related public opinion is associated with decreased exports. This relationship could be nurtured through three channels namely consumer preference, economic policy uncertainty and political conflicts. Further analysis reveals that the observed relationship is especially prevalent in developed markets and non-participatory countries of the Belt and Road Initiative as well as for industrial and capital-intensive products. In addition, it is found that political relation is positively associated with exports and plays a mitigating role in the negative relationship between public opinion and exports. Our findings have important policy implications. Policy makers are encouraged to think outside the box and exploit soft power of country image to promote exports.

Texture graph transformer for prostate cancer classification

Prostate cancer classification plays a pivotal role in the diagnosis and treatment of this disease. In this paper, we present a novel approach called the texture graph transformer, which combines texture analysis techniques, graph-based representations, and multi-head attention to enhance the accuracy of prostate cancer classification. Our texture graph transformer adeptly captures intricate texture details and patterns within prostate cancer lesion regions, efficiently improving the model’s ability to discern between different cancer types. By leveraging graph-based representations, our model constructs texture graphs that effectively capture the spatial and textural relationships among various regions in MRI images, enabling comprehensive feature extraction. The incorporation of a texture graph multi-head attention further enhances the model’s capacity to capture long-range dependencies and global context, with a specific focus on informative regions. Through extensive experiments conducted on a dataset comprising 226 MRI images, we demonstrate the efficacy of our proposed approach in significantly improving the performance of prostate cancer classification.

Pengaruh Kompetensi Sumber Daya Manusia, Gaya Kepemimpinan dan Pemanfaatan Teknologi Informasi terhadap Kualitas Laporan Keuangan Gereja Paroki Wilayah Kota Maumere

The aim of this research is to determine the influence of human resource competence, leadership style and use of information technology on the quality of financial reports of Parish Churches in the Maumere City area. This research uses an associative quantitative approach. The population in this study was the Financial Council taken from 5 Parish Churches in Maumere City, namely 32 respondents. The sampling method used in this research was saturated sampling so that the number of samples obtained was 32 respondents. The data collection process was carried out by distributing questionnaires to respondents, where the research instrument used a Likert scale. The data analysis technique used in this research uses a multiple linear regression analysis model with the help of the IBM SPSS Statistics 26 program. The results of this research show that the variables of human resource competency, leadership style and the use of information technology partially and simultaneously have a significant effect on the quality of the Church's financial reports. Maumere City Parish.

Classification of kimchi using laser-induced breakdown spectroscopy and k-nearest neighbors modeling

This study introduces a novel application of Laser-Induced Breakdown Spectroscopy (LIBS) combined with k-nearest neighbors (KNN) modeling to classify the origin of kimchi. Using the spectral intensities of Mg II at 279 nm and K I at 766 nm, we achieved a classification accuracy of 92.8 %. This method effectively leverages regional differences in salt supply chains impacting kimchi's elemental composition. The innovation lies in applying the interclass distance method for variable selection in LIBS analysis, enhancing the interpretability and accuracy of food classification. Compared to traditional elemental analysis techniques, LIBS offers a practical, cost-effective solution for rapid field analysis with minimal sample preparation. This study not only demonstrates the potential of LIBS for food authenticity but also provides insights for developing accurate methods for detecting Mg and K in various food products, contributing to advancements in food quality control.

Assessing the size transformation of nanoplastics in natural water matrices

Understanding the stability of NPs in different aqueous environments, related with their size is crucial for assessing their potential risks. This is influenced by several factors, including pH, ionic strength, and the presence of biomolecules, or dissolved organic matter (DOM). In this study, dispersions of NPs derived from common plastic waste materials, including polystyrene (PS), polyethylene terephthalate (PET), polyvinyl chloride (PVC), polymethyl methacrylate (PMMA), and polycarbonate (PC), were synthesized by a nanoprecipitation method with sizes: 189 ± 7, 58 ± 3, 123 ± 4, 151 ± 7 and 182 ± 6 nm, respectively. Stability for a period of 14 days of these NPs was assessed in various natural water matrices. Different analytical techniques were used, including Asymmetric Flow Field-Flow Fractionation (AF4) coupled with UV–Vis and Dynamic Light Scattering (DLS) in series, batch DLS, Fourier-Transform Infrared Spectroscopy-Attenuated Total Reflection (FTIR-ATR), and Transmission Electron Microscopy (TEM). None of the studied NPs was stable in seawater and NPs were transformed in microplastics (MPs) by aggregation. PET was more prone to aggregation in all waters and PS was the most stable followed for PC, PVC and PMMA. However, bottle and tap waters maintained better the original size of NPs. For the most stable dispersion PS, the influence of heteroaggregation in tap and lagoon waters and aging from exposure to UV light in sea water were tested. In both cases, the stability over time was worse for PS. The results can contribute to a more comprehensive understanding of the fate and behaviour of NPs in natural aquatic environments, emphasizing the importance of studying a wide range of polymers.

Green and Reflux method synthesis of CeO2/rGO for their characterization and Photodegradation of dye

In this study, cerium oxide (CeO2) was synthesized using a green and eco-friendly solution combustion method with lemongrass as the fuel source. The synthesis process was simple and environmentally friendly, leveraging a straightforward reflux technique to prepare the CeO2/rGO composite. The resulting CeO2 and CeO2/rGO composite was characterized using various analytical techniques, including XRD, FE-SEM, FTIR, EDX, UV-Vis, XPS, and BET analysis. The photocatalytic performance of the CeO2/rGO composite was evaluated through the degradation of Methyl Violet (MV) dye, demonstrating a remarkable photocatalytic efficiency with approximately 99 % degradation following a first-order reaction kinetics. The half-life period (t₁/₂) of the degradation process was determined to be 19.01 minutes, and the rate constant (k) was calculated to be 0.03971 min⁻¹. The study also explored various factors affecting the photocatalytic activity, including pH levels, dye concentration, light source, and the amount of catalyst used. Additionally, scavenger studies were performed to identify the reactive species involved, and the total organic carbon (TOC) removal efficiency was evaluated. The reusability of the CeO2/rGO catalyst was also investigated, demonstrating its potential for sustainable and effective application in environmental remediation processes.

High near-infrared reflectance Zn1-xMnxO yellow pigment prepared and properties by co-precipitation method

A successful synthesis of yellow pigments, namely Zn1-xMnxO (x = 0.001–0.009), was achieved using the co-precipitation method. To characterize the prepared pigments, various analytical techniques were employed, including powder X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared spectroscopy (FT-IR), and thermogravimetric-differential scanning calorimetry (TG-DSC). The results showed that the Zn1-xMnxO series pigments prepared by co-precipitation method retained the ZnO fibrous zincite structure and all had a good yellow color (b*=30.14–40.56) and high NIR solar reflectance (80.66 %-87.80 %). The results of the simulated heat shielding experiments confirmed that the Zn0.997Mn0.003O (abbreviated as ZM3) pigment synthesized in the study was 5°C cooler than the commercial iron yellow pigment, and the thermal imaging experiments showed that the surface temperature of the sample coatings was reduced by 8°C, which further confirmed that the ZM3 pigment had good heat shielding properties. Furthermore, the pigment demonstrates excellent chemical and thermal stability. and can be used as a cold pigment in architectural coatings to obtain energy-saving effects, which has great potential for development.

Spectroscopic analysis of La2(WO4)3:Tb3+ phosphor and the delayed concentration quenching of 5D4 →7FJ emission

Trivalent terbium ion doped lanthanum tungstate (La2-xTbx(WO4)3; x = 0.6,1.0,1.4) and terbium tungstate (Tb2(WO4)3) phosphors were successfully synthesized via optimized microwave-assisted co-precipitation technique. The phase purity and crystallinity of the prepared samples were confirmed using the powder XRD technique. The photoluminescence studies revealed a quenching-free emission up to 70 % of Tb3+ doping concentration, even though the emission intensity slightly decreases under host excitation since it becomes less relevant at higher doping concentrations. The experimental and calculated oscillator strengths were evaluated using absorption data and further used to quantify the Judd - Ofelt (JO) intensity parameters, which appeared in a trend of Ω2>Ω4>Ω6 for all samples. As a theoretical approach to assure the excellency of the tungstate host, the radiative parameters were calculated from the emission data using the JO analysis technique. The dominance in the values of stimulated emission cross section and gain bandwidth corresponding to 5D4→7F5 transition of Tb3+ ion of lanthanum tungstate proclaims it as an excellent green phosphor. Hence, the less susceptibility of the tungstate host towards concentration quenching is confirmed in the present work.

Isogeometric topology optimization for maximizing band gap of two-dimensional phononic crystal structures

A smooth and efficient isogeometric topology optimization (ITO) method for maximizing band gaps in two-dimensional phononic crystals is developed in the paper. The band gaps of phononic crystals are computed by the NURBS-based isogeometric analysis, and the material distributions of two-dimensional phononic crystals are represented by the smooth, high-order continuity of the NURBS surface. The densities defined at each control point of the NURBS surface are employed as optimized design variables. The isogeometric analysis optimization using the same spline technique for both geometry and numerical analysis can benefit the optimization procedure and obtain smooth optimized structures, which can be easily used in 3D printing. The maximizing band gaps of phononic crystals for both out-of-plane and in-plane wave modes are obtained here using the present ITO approach. Numerical examples validated the effectiveness and reliability of the ITO method in broadening the band gaps and finding the optimal phononic crystals. And the numerical results show that the smooth optimized structures are obtained with fewer iterations.

PopMLvis: a tool for analysis and visualization of population structure using genotype data from genome-wide association studies

One of the aims of population genetics is to identify genetic differences/similarities among individuals of multiple ancestries. Many approaches including principal component analysis, clustering, and maximum likelihood techniques can be used to assign individuals to a given ancestry based on their genetic makeup. Although there are several tools that implement such algorithms, there is a lack of interactive visual platforms to run a variety of algorithms in one place. Therefore, we developed PopMLvis, a platform that offers an interactive environment to visualize genetic similarity data using several algorithms, and generate figures that can be easily integrated into scientific articles.

Enhancing stock market Forecasting: A hybrid model for accurate prediction of S&P 500 and CSI 300 future prices

This paper investigates the challenging domain of stock market prediction, a significant aspect of financial markets. It focuses on developing predictive models to forecast stock prices accurately, vital for mitigating losses and maximizing gains amidst the inherent unpredictability and volatility of the market. The study comprehensively analyzes various predictive models, including time series analysis and advanced machine learning techniques. It highlights the superiority of ensemble or hybrid models in enhancing prediction reliability. Central to this research is the development of a model incorporating detailed data collection, thorough analysis, and state-of-the-art machine learning methods, achieving notable predictive accuracy. This approach underscores the benefits of data-centric strategies in today’s rapidly evolving business environment and the widespread applicability of predictive analytics. The model outperforms conventional methods by decomposing time series into simpler components and optimizing hyperparameters, thereby enhancing prediction accuracy, as demonstrated by performance testing on the S&P 500 and CSI 300 indices. The RMSE, MAE, and R2 values of the MEME-AO-LSTM model are 27.12, 19.43, and 0.992, respectively, which serve as evidence of this. The model’s generalizability and high performance are demonstrated by its efficacy in a variety of major markets, including the NASDAQ 100, Nikkei 225, FTSE, DAX, SSE, and KOSPI. Additionally, the model’s adaptability under diverse market conditions is demonstrated through its evaluation of its robustness in response to significant events, such as the economic stimulus responses to the COVID-19 pandemic and the geopolitical tensions resulting from the tension and conflict between Russia and Ukraine. Consequently, the proposed methodology has the potential to help investors achieve substantial and advantageous returns.

Disintegration of lignocellulosic material through visible light SiO2/g-C3N4 photocatalyst for biogas generation

This study presents the synthesis of g-C3N4 and the fabrication of SiO2/g-C3N4 via the hydrothermal polycondensation method, serving as a highly efficient visible light activated photocatalyst for enhancing anaerobic digestion and biogas production from rice straw through pretreatment at various time intervals. The efficacy of the pretreatment was evaluated using a range of analytical techniques, including XRD, FTIR, FESEM, EDX, and UV–vis analysis. The results showcased a remarkable 81 % reduction in silica content compared to untreated rice straw, along with a significant 121 % increase in biogas production. The study demonstrate that the 7-h treatment duration facilitates the highest silica reduction and biogas yield. These findings underscore the immense potential of SiO2/g-C3N4 as a promising catalyst for rice straw pretreatment, thereby leading to enhanced biogas production during anaerobic digestion.

CuCo2S4 nanoparticles synthesized via a thermal decomposition approach: evaluation of their potential as peroxidase mimics.

The current study demonstrates the synthesis of CuCo2S4 nanoparticles using a novel thermal decomposition approach. The CuCo2S4 nanoparticles were synthesized under various conditions by changing the source of sulfur and the solvent. The CuCo2S4 nanoparticles were characterized using an array of analytical techniques. Powder XRD results indicate the successful formation of CuCo2S4 nanoparticles. TEM results show agglomerated nanoparticles with close to spherical morphology and XPS measurements indicate the presence of Cu2+, Cu+, Co3+, Co2+, and S2- in the samples. The CuCo2S4 nanoparticles exhibit weak ferromagnetic and paramagnetic behaviour at 5 K and 300 K, respectively. The CuCo2S4 nanoparticles were explored for their enzyme mimetic activity using 3,3',5,5' tetramethylbenzidine (TMB) as a substrate. They exhibit better catalytic activity compared to that of a natural enzyme (horseradish peroxidase) and other metal sulfide nanoparticles reported in the literature.

Innovative Nanomaterial-Based Analytical Techniques for Early Detection of Diseases: A Comprehensive Review

Innovative Nanomaterial-Based Analytical Techniques for Early Detection of Diseases: A Comprehensive Review

From cornfield to catalyst support: Eco-friendly synthesis of Cu/CuO nanoparticles, immobilization on the waste corn husk fibers, photocatalytic exploration and bioactivity evaluation

This study presents an innovative approach to eco-friendly synthesis and utilization of copper nanoparticles (CuNPs) for photocatalytic applications, employing waste corn husk fibers as sustainable catalyst support. The synthesis of CuNPs was achieved through a green synthesis method utilizing myrtle extract. Subsequently, the remarkable photocatalytic activity of the CuNPs explored (76% removal efficiency of Crystal Violet), showcased their potential in environmental remediation applications. Furthermore, the immobilization of CuNPs onto waste corn husk fibers was investigated, aiming to develop a novel composite material with enhanced catalytic performance. A distinctive approach was introduced by immobilizing CuNPs onto fibers derived from corn husks, and waste biomass material, leading to a significant enhancement in photocatalytic efficiency, surpassing 95.1%. Furthermore, bioactivity evaluation studies revealed the significant antioxidant, antidiabetic, DNA fragmentation, cell viability, antibiofilm and antimicrobial properties of CuNPs. The antioxidant ability was determined at 100 mg/L as 87.12%. The most powerful antimicrobial activity of CuNP was found as a MIC value of 8 mg/L against E. faecalis. The cell viability inhibition of CuNP was 90.05% at 20 mg/L. CuNP exhibited biofilm inhibition activity at different concentrations. The antibiofilm ability was investigated against Staphylococcus aureus compared to Pseudomonas aureginosa. While the DNA cleavage activity of CuNP observed double-strand breaks at 50 and 100 mg, complete fragmentation occurred at 200 mg concentrations. The bioactivity of the synthesized CuNPs shed light on their potential biomedical applications. The synthesized CuNPs are characterized using various analytical techniques to elucidate their structural and morphological properties. Fourier-transform infrared (FTIR) analysis provided insights into the chemical composition and surface properties of the synthesized materials. EDS analysis confirmed their successful integration into waste corn husk fibers. Overall, this interdisciplinary study highlights the potential of CuNPs immobilized on waste corn husk fibers for addressing environmental pollution, advancing sustainable technologies and paving the way for the development of efficient catalysts with diverse functionalities.

NiCr2−xGdxO4 ceramics’ magnetic, structural and electrical conductivity as well as their activation energy properties

The goal of this work is to synthesize and characterize nanoscale nickel chromites nanoparticles doped with Gd using the economical solution combustion method. Numerous analytical techniques, including energy formation, electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction, are used for in-depth characterization. The results show that at low values of coercivity, high values of saturation magnetization, and low values of remnant magnetization, the chromites correspond. The crystalline size of Gd-doped nickel chromites decreases. For the normal spinel structure’s tetrahedral and octahedral coordinated forms, respectively. The present research shows that agglomerated forms and irregular, spherical structures formed by SEM (Scanning Electron Microscope) form regular structures. The present investigation uses a transmission electron microscope (TEM) to illustrate the formation of regular-shaped particles. As demonstrated by Gd-doped NiCr2O4 and pure NiCr2O4, stable interstitial positions are among the typical interstitial positions of the metal oxides. Investigations of magnetic properties from the paramagnetic to the ferromagnetic phase formation. Electrical conductivity and activation energy dropped with Gd doping of nickel chromites and showed an inverse relationship with particle/crystallite sizes. Lastly, applications for NiCr2−x GdxO4 particles were examined and future research directions were also suggested.

Electrochemical sensing of vitamin B6 using platinum nanoparticles decorated poly(2-aminothiazole)

Vitamin B6 (Vit B6), also known as pyridoxine, is pivotal in fundamental physiological and metabolic processes within the body. Insufficient levels of this essential nutrient may contribute to various health complications. We introduce an electrochemical sensor designed to determine Vit B6 levels precisely. This sensor is constructed through a two-step process: first, by modifying a bare carbon fiber paper electrode (CFP) with poly(2-aminothiazole) (PAT), and second, by electrodepositing platinum nanoparticles onto the modified electrode surface, giving the final working electrode- Pt/PAT/CFP. Electrochemical impedance spectroscopy (EIS) and Cyclic voltammetry (CV) were utilized to examine the electrochemical characteristics of the developed sensor. The characterization of the sensor was done through a range of analytical techniques, including X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and optical profilometric studies. Furthermore, we optimized the sensor’s performance by assessing the impact of pH, scan rates, and analyte concentrations. The sensor showed a wide linear dynamic range of 5.0 nM–80 µM and a low detection limit of 0.054 µM. We have successfully quantified Vit B6 levels in tablet formulations and dried palm date fruits. The outcomes of this study hold the promise of substantial progress in Vit B6 quantification, with far-reaching implications across pharmaceuticals, healthcare, and nutritional science.

The Nature of Community Empowerment in Local Governance: The Case of Selected Amhara Regional State Zones

Abstract The study sought to explore the nature of community empowerment in holding local councils accountable. The study adopted both quantitative and qualitative data collection methods. Three Zones, namely Central Gondar, Wag Hemra, and South Wollo, were selected as study areas. From these three Zones, five woredas were selected. Two kebeles were selected purposively from each sample Woreda. Accordingly, 10 study kebeles were selected. A total of 269 samples from the community have been incorporated into the survey. Primary data were collected through survey, key informant interview, fgd, and in-depth interview techniques. The study used thematic analysis technique for the qualitative data and descriptive analysis for the quantitative data. The results show that the level of community empowerment in holding council members accountable for their needs and priorities is low. Local people have little say in their local affairs. Currently, the council members are serving their second term without local elections. Hence, Some Kebeles and Woredas do not have representatives in the local councils.

Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks

Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablets are a very popular pharmaceutical technology. In this study, it was investigated whether a rapid, nondestructive method can be used to characterize the floating properties of a tablet.To accomplish our objective, the same composition was compressed, and varied compression forces were applied to achieve the desired tablet. In addition to physical examinations, digital microscopic images of the tablets were captured and analyzed using image analysis techniques, allowing the investigation of the floatability of the dosage form. Image processing algorithms and artificial neural networks (ANNs) were utilized to classify the samples based on their strength and floatability. The input dataset consisted solely of the acquired images.It has been shown by our research that visible imaging coupled with pattern recognition neural networks is an efficient way to categorize these samples based on their floatability. Rapid and non-destructive digital imaging of tablet surfaces is facilitated by this method, offering insights into both crushing strength and floating properties.