Ekaterina N. Muratova, Andrey A. Ryabko, Vyacheslav A. Moshnikov
et al.
TiO<sub>2</sub> films with a thickness of 20 nm were obtained by anodizing a titanium film with an aluminum sublayer on a glass substrate. The I–V characteristics were studied in a temperature range of 100–300 K. Three linear sections can be distinguished on the I–V curves in logarithmic coordinates with a bias voltage of up to 2.5 V. The first section is an ohmic section with a bias voltage sweep from 0 V. The second section is associated with the space-charge-limited currents. The third section is characterized by the flow of Poole–Frenkel currents. In the third section, the slope of the approximating line is greater than in the second one due to the flow of higher currents. This is explained by the transition of electrons from donor centers to trap levels, which leads to a decrease in the number of free traps available for capturing electrons injected from the contacts into the conduction band. The obtained values of the Fermi energy of 0.032 and 0.028 eV for temperatures from 100 to 300 K, respectively, indicate that the electron traps in the forbidden zone of TiO<sub>2</sub> are shallow. The value of the donor level energy E = 0.082 eV is close to the values of the activation energy of thermal conductivity. This indicates the formation of donor centers in anodic TiO<sub>2</sub> by the mechanism of donor vacancies. In anodic TiO<sub>2</sub> films, the concentration of electron traps is 10<sup>15</sup> cm<sup>−3</sup>, which is approximately three orders of magnitude less than their concentration in anodic TiO<sub>2</sub> films obtained by vacuum deposition.
Accurate electricity demand forecasting is essential for Thailand’s energy system planning, particularly for the small business sector, whose consumption exhibits high variability (coefficient of variation: 26.34%). This study develops a Long Short-Term Memory (LSTM) model to forecast monthly electricity consumption of Thailand’s small business sector over a 12-month horizon from September 2025 to August 2026. The analysis is based on 284 months of historical consumption data (January 2002–August 2025) obtained from official national statistics. The forecasting framework employs Min–Max normalization and a supervised learning formulation with a 12-month lookback window. The dataset is chronologically divided into training (80%) and testing (20%) subsets, and model performance is evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The optimized LSTM model achieves strong forecasting accuracy, with a training RMSE of 93.93 and MAPE of 5.45%, and a testing RMSE of 143.68 and MAPE of 6.25%. These results meet the criterion for highly accurate forecasting (MAPE < 10%), demonstrating the model’s ability to capture long-term trends and seasonal patterns while generalizing well to unseen data. The findings highlight the suitability of LSTM-based models for long-term electricity demand forecasting in high-volatility small-business sectors and underscore their practical relevance for energy planning and policy development in Thailand.
The motivation for this work is to study the cause and present mitigation for some challenges faced in preparing porous silicon. This enables benefiting from the appealing benefits of porous silicon that offers a wide range, simple technique for varying the refractive index. Such challenges include the refractive index values, sensitivity to oxidation, some fabrication parameters, and other factors. Additionally, highly doped p-type silicon is preferred to form porous silicon, but it causes high losses, which necessitates its detachment. We investigate some possible causes of refractive index change, especially after detaching the fabricated layers from the silicon substrate. Thereby, we could recommend simple but essential precautions during fabrication to avoid such a change. For example, the native oxide formed in the pores has a role in changing the porosity upon following some fabrication sequence. Oppositely, intrinsic stress doesn’t have a significant role. On another aspect, the effect of differing etching/break times on the filter’s responses has been studied, along with other subtle details that may affect the lateral and depth homogeneity, and thereby the process success. Solving such homogeneity issues allowed reaching thick layers not suffering from the gradient index. It is worth highlighting that several approaches have been reported; unlike these, our method doesn’t require sophisticated equipment that might not be available in every lab. To well characterize the thin films, it has been found essential that freestanding monolayers are used for this purpose. From which, the wavelength-dependent refractive index and absorption coefficient have been determined in the near infrared region (1000–2500 nm) for different fabricated conditions. Excellent fitting with the measured interference pattern has been achieved, indicating the accurate parameter extraction, even without any ellipsometry measurements. This also demonstrates the refractive index homogeneity of the fabricated layer, even with a large thickness of over 16 µm. Subsequently, multilayer structures have been fabricated and tested, showing the successful nano-manufacturing methodology.
This study investigates the influence of carbon electrode properties on plasma behavior and morphology of nanocarbon in submerged arc discharge (SAD) synthesis. Two commercially available graphite rods with contrasting physical and electrical properties-fine-grained, low-resistivity Rod 1 and coarse-grained, high-resistivity Rod 2-were employed as anodes in a dc arc configuration submerged in deionized water. Time-synchronized currentvoltage ( $I$ – $V$ ) and optical emission spectroscopy (OES) diagnostics were used to derive plasma ionization energy distributions, which were further correlated with the morphology of synthesized nanocarbons via high-resolution transmission electron microscopy (HRTEM). Rod 1 consistently produced a lower voltage arc with greater stability and a narrower ionization energy spectrum, concentrated below 4 eV, leading to the formation of spherical carbon nano-onions (CNOs) due to rapid quenching and shell closure dynamics. In contrast, Rod 2 exhibited a broader energy distribution extending beyond 10 eV, associated with a hotter, less stable arc and increased production of multiwalled carbon nanotubes (MWCNTs) and few-layer graphene sheets. The findings reveal that microstructural parameters, such as grain size, porosity, and resistivity, critically influence arc ignition, plasma energetics, and product selectivity. These insights demonstrate the utility of integrated electrical and spectroscopic diagnostics in tailoring SAD conditions for tunable nanomaterial synthesis and highlight electrode engineering as a key parameter for directing carbon nanostructure growth in plasma-based processes.
This study presents and evaluates Phi Method, a novel data-driven algorithm designed to discover discretized differential equations governing dynamical systems from data. Phi Method employs a constrained regression on a library of candidate terms to develop reduced-order models (ROMs) capable of accurate predictions of systems' state. To validate the approach, we first benchmark Phi Method against canonical dynamical systems governed by ordinary differential equations, highlighting the strengths and limitations of our approach. The method is then applied to a 2D fluid flow problem to verify its performance in learning governing partial differential equations (PDEs). The fluid flow test case also underlines the method's ability to generalize from transient training data and examines the characteristics of the learned local operator in both basic and parametric Phi Method implementations. The approach is finally applied to a 1D azimuthal plasma discharge problem, where data are now generated from a kinetic particle-in-cell simulation that does not explicitly solve the governing fluid-like equations. This application aims to demonstrate Phi Method's ability to uncover underlying dynamics from kinetic data in terms of optimally discretized PDEs, as well as the parametric dependencies in the discharge behavior. Comparisons with another ROM technique—the optimized dynamic mode decomposition—for the plasma test case emphasize Phi Method's advantages, mainly rooting in its ability to capture local dynamics with interpretable coefficients in the learned operator. The results establish Phi Method as a versatile tool for developing data-driven ROMs across a wide range of scenarios.
Laser-driven tin droplets represent the primary technique for generating extreme ultraviolet (EUV) radiation in lithography light sources. The implementation of a vertical external magnetic field is a critical strategy for reducing the ion debris produced by the tin plasma. Nonetheless, the detailed mechanisms through which the external magnetic field affects ion debris dynamics have not yet been fully elucidated. In our study, numerical simulations were conducted using the radiation hydrodynamics code FLASH to investigate the magnetohydrodynamic properties of tin plasma under an external magnetic field with a strength of 1 T. Our results reveal, for the first time, the intermediate-timescale (tens to hundreds of nanoseconds) evolution of tin plasma under an external magnetic field, providing new insights into the mechanisms of ion debris mitigation in EUV lithography systems. The magnetic field guides the plasma from the front and rear surfaces of the target to flow to both sides, forming a vortex street phenomenon, accompanied by backflow opposing the vortex street flow. Beyond the vortex region, the plasma transitions to laminar flow, where hydrodynamic instabilities between layers of varying velocities are significantly suppressed. These phenomena are recognized as significant factors to the effective trapping of tin plasma by an externally applied magnetic field in a vertical configuration.
The synergy between voltage waveform tailoring and structured electrodes is investigated in a radio -frequency atmospheric-pressure microplasma jet operated in helium with a 0.1% oxygen admixture. The device incorporates rectangular trenches in both electrodes and is driven by ‘Peaks’ and ‘Valleys’ waveforms synthesized from four harmonics (base frequency fb=13.56 MHz, Vpp=500 V, and P=1.2 W). Two-dimensional plasma fluid simulations, together with spatially and temporally resolved optical diagnostics (phase-resolved optical emission spectroscopy and tunable diode laser absorption spectroscopy), are used to demonstrate that the combination of asymmetric voltage waveforms with electrode structuring results in the strong spatial localization of electron power absorption and radical generation. This synergy leads to a single pronounced maximum inside a trench at either the powered or grounded electrode, depending on the applied waveform, unlike a symmetric excitation, which produces a spatially symmetric enhancement at both electrodes. This effect is attributed to the interplay between waveform-induced sheath dynamics and geometric focusing provided by the trenches, enabling electrically reversible and selective enhancement of electron power absorption at a chosen location.
Challenges persist in developing a suitable method to distinguish high-quality cultivated rice seeds, which can be estimated based on their characteristics. To prevent rice grain varieties from being incorrectly labeled, the quality and type of rice grains must be accurately identified. In this paper, the classification of rice grains is analyzed, and a study is conducted on various algorithms used at each stage. Generally, visual observations are made by specialists using specialized devices that measure various properties. The resultant data are processed through different stages using multiple algorithms, which are discussed in detail. This study reviews machine learning techniques for differentiating rice seeds based on various algorithms. Each stage is analyzed with distinct objectives, and necessary conclusions are drawn to inform the next stage of research.
Cerium oxide nanoparticles (CeO<sub>2</sub> NPs) have gained significant attention in various fields, including biomedicine, semiconductors, cosmetics, and fuel cells, due to their unique physico-chemical properties. Notably, green-synthesized CeO<sub>2</sub> NPs have demonstrated enhanced potential as drug carriers, particularly in biomedical applications such as anti-inflammatory, anticancer, antimicrobial, and anti-oxidant therapies. This study aimed to investigate the anticancer effects of cerium oxide nanoparticles synthesized using turmeric rhizomes on human lung cancer cells. The cytotoxicity and proliferation inhibition of these nanoparticles were assessed using MTT and Live/Dead assays, revealing a dose-dependent reduction in cell viability. Additionally, reactive oxygen species (ROS) generation was quantified through ROS assays, confirming oxidative stress induction as a key mechanism of cytotoxicity. Cell proliferation analysis further demonstrated that increasing concentrations of CeO<sub>2</sub> NPs significantly reduced the multiplication of healthy lung cancer cells. These findings highlight the potential of turmeric-derived CeO<sub>2</sub> NPs as a promising therapeutic agent for lung cancer treatment, warranting further exploration of their mechanism of action and in vivo efficacy.
Steel Fibre Concrete-Filled Steel Square Tubes (SFCFSST) represent a modern and highly efficient structural system that combines steel’s strength and enhanced fibre-reinforced concrete performance. These columns exhibit improved compressive strength, ductility, and overall structural integrity by integrating steel fibres and expansive agents into the concrete mix. Although using such composite columns remains a relatively new concept, their potential to enhance seismic resistance, load-bearing capacity, and fire resilience positions them as a promising solution for future construction practices. In this study, axial compression tests were completed. According to the test results, the axial compression behaviour of columns increases with the proportion of steel fibres replaced. It has higher ductility than regular Concrete Filled Steel Tubes (CFST) columns. In this article, the strength attributes of CFST structures were investigated utilising Steel Fibre in various proportions, i.e., 0%, 0.5%, 1%, 2%, and 3% as partial replacements for Coarse Aggregate.
Justin C. Bonner, Bishal Bhandari, Garrett J. Vander Stouw
et al.
This study addresses the challenges of efficient, large-scale production of flexible transparent conducting electrodes (TCEs). We fabricate TCEs on polyethylene terephthalate (PET) substrates using a high-speed roll-to-roll (R2R) compatible method that combines gravure printing and photonic curing. The hybrid TCEs consist of Ag metal bus lines (Ag MBLs) coated with silver nanowires (AgNWs) and indium zinc oxide (IZO) layers. All materials are solutions deposited at speeds exceeding 10 m/min using gravure printing. We conduct a systematic study to optimize coating parameters and tune solvent composition to achieve a uniform AgNW network. The entire stack undergoes photonic curing, a low-energy annealing method that can be completed at high speeds and will not damage the plastic substrates. The resulting hybrid TCEs exhibit a transmittance of 92% averaged from 400 nm to 1100 nm and a sheet resistance of 11 Ω/sq. Mechanical durability is tested by bending the hybrid TCEs to a strain of 1% for 2000 cycles. The results show a minimal increase (<5%) in resistance. The high-throughput potential is established by showing that each hybrid TCE fabrication step can be completed at 30 m/min. We further fabricate methylammonium lead iodide solar cells to demonstrate the practical use of these TCEs, achieving an average power conversion efficiency (PCE) of 13%. The high-performance hybrid TCEs produced using R2R-compatible processes show potential as a viable choice for replacing vacuum-deposited indium tin oxide films on PET.
Muhammad Fauzan Hanif, Ahmad Rofik Harahap, Ade Fakhrudin
et al.
The accelerated evolution of information technology (IT) has compelled organizations to adopt structured governance frameworks to enhance audit efficacy and ensure robust information security. This study presents a systematic literature review examining the integration of COBIT and ISO/IEC 27001 within IT audit practices. Employing a qualitative descriptive methodology, the review synthesizes insights from seven primary scholarly sources, including case studies from both public and private sectors. The analysis delineates integration patterns, identifies best practices, and explores the synergistic potential of aligning COBIT’s strategic governance capabilities with the technical control rigour of ISO/IEC 27001. Findings demonstrate that such integration enhances audit capability maturity, facilitates structured risk mitigation, and fosters alignment between IT functions and organizational objectives. Nonetheless, notable research gaps persist, particularly the scarcity of quantitative assessments, limited cross-sector generalizability, and the absence of longitudinal evaluations of implementation outcomes. Additionally, practical challenges—including integration complexity, inadequate human resource competencies, and the lack of standardized implementation guidelines—impede broader adoption. The study concludes that integrating COBIT and ISO/IEC 27001 constitutes a viable foundation for advancing IT governance and audit maturity. However, further empirical investigation and development of pragmatic toolkits are essential. These insights aim to inform auditors, IT governance professionals, and policy makers in devising adaptive, standard-aligned audit strategies.
This study assessed the competence of junior secondary school Computer Science teachers in Benue State, Nigeria, in constructing essay test items based on Bloom’s Taxonomy, comparing the LOTS and HOTS. Adopting a descriptive survey design, the study was guided by two research questions and a hypothesis. The scope targeted junior secondary school Computer Science teachers in the state, and stratified disproportionate random sampling was used to select 105 teachers. Data was collected using the Computer Science Teachers’ Essay Test Item Construction Competency Test (CSTETICCT), a validated 30-item instrument covering all six cognitive levels of Bloom’s Taxonomy. Instrument reliability was confirmed through a pilot test involving 20 respondents, yielding a KR-20 coefficient of 0.85. Descriptive statistics (frequencies, percentages, means, and standard deviations) and visual aids (charts and graphs via Microsoft Excel) were used for data presentation. Inferential statistics, including t-test, ANOVA, and post hoc analysis, were conducted using SPSS Version 20. Findings, among others, revealed that teachers demonstrated high competence in constructing items for lower-order thinking skills (knowledge and comprehension), moderate ability at the application level, and low competence in higher-order thinking skills (analysis, synthesis, and evaluation), these different competency levels in constructing items that assess LOTS and HOTS were found to be significant. The study concludes that while teachers are proficient in evaluating lower-order cognitive skills, there is a notable gap in their ability to develop higher-order assessment items. It recommends continuous professional development, curriculum revision to include specialised Computer Science training, optional certification in assessment design, and mentorship programs to enhance teachers’ assessment competencies across all cognitive levels.
Md. Shahidur Rahaman, Mohammad Safi Ullah, Mohammad Nazrul Islam
The nonlinear fractional soliton neuron model is an important part of many complex fields, such as fluid mechanics, applied science, neuroscience, nonlinear dynamics, mathematical physics, engineering, biosciences, plasma physics, and geochemistry. It shows how nonlinear waves propagate. This paper uses a thermodynamic theory of neural signal transmission to show how the suggested model works, what it can do, and how it might work as it moves along axons. To solve this model, we first convert the partial differential equation form to the ordinary differential equation form. We then use the φ6-model expansion scheme to determine the wave profiles for the above-stated equation. We manufactured 2D and 3D density plots and different types of soliton solutions with the help of computational software. Additionally, we illustrated a sensitivity analysis of the mentioned nonlinear problem using planner dynamics. The results of different solitons show that the suggested method works very well and is perfect for dealing with the soliton solutions of nonlinear equations. This makes it especially useful for studying complicated wave phenomena in many scientific areas.
The purpose of this paper was to investigate how librarians in the Federal College of Education Library, Odugbo, Benue State, have disseminated health information on anti-malarial drug resistance, and how post-natal mothers have utilised that information. The study adopted a survey research design. The study had a sample size of 192, comprising 187 post-natal mothers and five librarians. Due to the manageable population size, a total enumeration (census) method was employed. Separate questionnaires and an observation checklist were used as data collection instruments. A total of 187 copies of the questionnaire were administered to post-natal mothers, and 5 to librarians. Out of these, 184 (99.4%) and all 5 (100%) were correctly completed and returned, respectively. The data was analysed using descriptive statistics. The study findings indicated that the effects of librarians’ information dissemination on anti-malarial drug resistance among post-natal mothers are moderate. It further revealed that, according to the post-natal mothers, the actual use of the disseminated information had a relatively lower impact on addressing anti-malarial drug resistance. The perceptions of a subset of mothers (12 respondents) indicated that access to information helped them understand child delivery, gain general health and medical knowledge, recognise the consequences of drug misuse, and adhere strictly to malaria prescriptions and medications. Among other recommendations, the study suggests that the management of the Federal College of Education should collaborate with healthcare providers to offer timely and relevant information on the prevention and treatment of malaria.
Abstract The nonlinear Schrödinger equation, held in high regard in the realms of plasma physics, fluid mechanics, and nonlinear optics, reverberates deeply within the field of ocean engineering, imparting profound insights across a plethora of phenomena. This article endeavours to establish a connection between the equation’s theoretical framework and its practical applications in ocean engineering, presenting a range of solutions tailored to grasp the intricacies of water wave propagation. By employing three methodologies, namely, the simplest equation method, the ratio technique, and the modified extended tanh-function method, we delineate various wave typologies, encompassing solitons and periodic manifestations. Enhanced by visual representations, our findings have the potential to deepen the comprehension of wave dynamics, with promising implications for the advancement of ocean engineering technologies and the refinement of marine architectural design.
Adil Jhangeer, Beenish, Abdallah M. Talafha
et al.
Abstract The Riemann wave equation presents appealing nonlinear equations applicable in sea-water and tsunami wave propagation, ion and magneto-sound waves in plasmas, electromagnetic waves in transmission lines, and homogeneous stationary media. This study focuses on deriving soliton solutions in optics and exploring their physical properties. A wave transformation is used to convert a partial differential equation into an ordinary differential equation, from which soliton solutions are obtained using the generalized Riccati equation mapping approach. The solutions encompass various types of solitons, including bright, dark, periodic, and kink solitons. A comparison of solutions from this analytical method enhances the understanding of the nonlinear model’s behavior, with implications in plasma physics, fluid dynamics, optics, and communication technology. Additionally, 2D and 3D graphs illustrate the physical phenomena of the solutions using appropriate constant parameters. The qualitative analysis of the undisturbed planar system involves examining phase portraits in bifurcation theory, followed by introducing an outward force to induce disruption and reveal chaotic phenomena. Chaotic trajectories in the perturbed system are detected through various plots, including 3D, 2D, power spectrum, and chaotic attractor, alongside Lyapunov exponents. Stability analysis under different initial conditions is conducted, and sensitivity assessments are performed using the Runge–Kutta method. The findings are innovative and have not been previously explored for this system, highlighting the reliability, simplicity, and effectiveness of these techniques in analyzing nonlinear models in mathematical physics and engineering.