Science and Technology Indonesia

Physicochemical Characterization of Spray-Dried Morinda citrifolia Extract Microcapsules Using an Alginate-Chitosan-STPP System

2026-04-17T07:57:26+00:00

Scopoletin, the primary bioactive marker of Morinda citrifolia L. with antihyperlipidemic activity, is susceptible to thermal and oxidative degradation during processing and storage. Despite the established role of microencapsulation in protecting herbal bioactives, studies on spray-dried polyelectrolyte wall systems for Morinda citrifolia extract remain limited, particularly regarding the influence of chitosan concentration on microcapsule formation and encapsulation performance. This study investigated the effect of chitosan concentration on the physicochemical properties and scopoletin encapsulation efficiency of spray-dried alginate-chitosan-sodium tripolyphosphate (STPP) microcapsules. Morinda citrifolia fruit extract was prepared by maceration in 70% ethanol and characterized prior to microencapsulation. Two formulations differing in chitosan concentration were spray-dried: F1 (1% w/v) and F2 (2% w/v), with sodium alginate (1% w/v), STPP (0.1% w/v), and extract concentration held constant. Microcapsules were characterized by FTIR spectroscopy, particle size analysis (PSA), differential scanning calorimetry (DSC), moisture content determination, scanning electron microscopy (SEM), and scopoletin quantification via validated TLC–densitometry. FTIR confirmed extract integration into the polymer matrix through hydrogen bonding, electrostatic interactions, and ionic crosslinking, with more pronounced polyelectrolyte interactions in F1. F1 also exhibited a narrower particle size distribution, greater thermal stability, lower moisture content (3.38 ± 0.20%), and higher encapsulation efficiency (88.37%) than F2 (moisture: 4.89 ± 0.16%; EE: 72.09%; p = 0.043). SEM revealed greater particle discreteness in F1, whereas F2 exhibited denser aggregation. These results demonstrate that chitosan concentration critically governs polyelectrolyte complex formation and encapsulation performance, with F1 showing optimal physicochemical characteristics as a stable, standardized Morinda citrifolia-based oral herbal formulation.

Integrated Cellular and Molecular Interaction Analysis of Turmeric and Black Rice Bran Extract in HeLa Cells as a Potential Anticancer

2026-04-02T06:51:36+00:00

Cervical cancer continues to be a leading cause of female mortality due to multidrug resistance therapy associated with EGFR overexpression and evasion of apoptosis. Turmeric and black rice bran are recognized for their potential anticancer properties; however, the combined effects of these extracts and their predicted molecular interactions remain to be elucidated. This study investigated the potential enhanced effect of combined turmeric and black rice bran extracts using an integrated phenotypic and molecular docking approach. The antiproliferative effect of the combination of the ethanolic extract of turmeric and black rice bran was assessed in HeLa cells using the MTT assay, whereas cell cycle arrest and apoptosis were analyzed using flow cytometry. Several compounds in turmeric and black rice bran extract were docked against the growth signaling protein (EGFR) and death receptors (BCL-2, DR-4). The optimal formulation (Combination 1) demonstrated a progressive reduction in HeLa cell viability from 61.02% at 24 hours to 47.88% at 48 hours, inducing a distinct G2/M phase arrest. This growth inhibition was accompanied by cell clearance through early apoptosis (38.57%) and secondary necrosis (28.03%). Molecular docking supported these findings by suggesting that bisdemethoxycurcumin may interact with EGFR, with a binding affinity of -7.6 kcal/mol. Compounds derived from black rice bran were also predicted to complementarily target BCL-2 and DR-4, suggesting a potential multi-target mechanism. In summary, the combination extract demonstrates both growth signaling inhibition and apoptotic induction, offering a promising baseline for further validation in in vivo models.

Colorimetric Intelligent Film Based on Carboxymethyl Cellulose/Sodium Alginate Incorporated Black Rice Bran Anthocyanins Co-Pigments for Shrimp Spoilage Monitoring

2026-04-29T20:55:02+00:00

Colorimetric intelligent film for monitoring shrimp spoilage based on carboxymethyl cellulose (CMC)/sodium alginate (SA) and co-anthocyanin extract derived from natural source was fabricated. Juedanor (JD) rice, a black-purple variety cultivated and consumed in Pattani province, Southern Thailand, served as the primary source of anthocyanin in this study. Consequently, utilizing anthocyanin pigments from JD and other plants in indicator films for the detection of food deterioration is an effective approach. Mulberry (M) showed the highest anthocyanin content at 341.275 mg/L, followed by 170.730 mg/L in purple cabbage (PC) and 136.955 mg/L in JD rice. The intelligent films were then fabricated using CMC/SA loading with co-anthocyanin pigment (PC: JD) at a 1:4 ratio. The film incorporating JD extract and purple cabbage established the widespread colour change during pH sensitive test. Further tests were conducted on the film using an ammonia solution to assess shrimp spoilage. Film color (%S, ΔE) and pH showed a high association, suggesting that the films can be used as sensitive markers of shrimp freshness during storage time. The predicted ΔE values closely match the experimental values over the ammonia exposure duration, with a high R² coefficient of 0.985, which signifies a robust association. This study demonstrates the potential of utilizing anthocyanins from the indigenous JD rice variety for intelligent packaging and future food production. The value assigned to this native rice will aid in its utilization, conservation, and additional benefit to the community.

On the Minimum Coprime Number of Some Graphs

2026-05-02T13:15:14+00:00

Let G be a finite simple graph. A coprime labeling of G is an injective assignment of positive integers to the vertices such that adjacent vertices receive relatively prime labels. The minimum coprime number of G, denoted by pr(G), is the smallest integer k for which G admits a coprime labeling using labels from {1, 2, ..., k}. In this paper, we determine the exact minimum coprime number of several graph families, namely the disjoint union of cycle graphs, the disjoint union of complete graphs, and dumbbell graphs. For the graph mCn with n odd, explicit coprime labeling constructions are provided and exact values of pr(mCn) are obtained for several infinite families. We also establish exact minimum coprime numbers for mKn and characterize prime and coprime labelings of dumbbell graphs according to the parity of their parameters. Furthermore, constructive labeling functions are presented for all considered graph classes. These results extend previous studies on minimum coprime labeling for graph operations and disconnected graph families.

The Power of Interpolation Effects on SARIMA and LSTM: An Indonesia Domestic Forecasting Case Study

2026-05-11T15:59:02+00:00

In regional economic planning, the accurate prediction of domestic tourism demand presents a critical challenge because limited access to historical time series data often causes advanced forecasting models to perform poorly. This study aims to demonstrate how linear interpolation can effectively serve as a data augmentation technique to overcome data scarcity when developing Long Short Term Memory (LSTM) networks to forecast domestic tourism arrivals. The methodology involves evaluating four distinct forecasting models using 80 months of Indonesian domestic tourism visitation data spanning from January 2019 to August 2025. These models include a statistical benchmark SARIMA (2,0,1)(0,1,1)[3] model selected via grid search out of 216 combinations and three LSTM variants run with identical random seeds. Performance evaluation is rigorously completed using MAE, RMSE, MAPE, sMAPE, and Theil’s U statistics. Key findings reveal that while unaugmented LSTM models perform poorly relative to a simple average baseline (Theil’s U = 1.38, MAPE = 24.6%), LSTMs enhanced with triple linear interpolation achieve superior predictive accuracy (MAPE = 2.6%, sMAPE = 2.6%, Theil’s U = 0.14). This approach significantly outperforms the benchmark SARIMA model (MAPE = 8.0%, Theil’s U = 0.63), which otherwise demonstrated adequate statistical validity through satisfactory residual diagnostics, including Ljung Box and Shapiro Wilk tests. In conclusion, the study demonstrates that utilizing linear interpolation as an augmentation technique is highly appropriate and effective, enabling deep learning models like LSTMs to accurately capture underlying temporal patterns from limited tourist arrival.

Facile Synthesis of Magnetic ZIF-67@Fe3O4 Composite with Synergistic Properties for Monolayer Adsorption of Pb(II) Pollutants

2026-04-27T08:57:05+00:00

The development of efficient and easily recoverable adsorbents for heavy metal removal remains a significant challenge in wastewater treatment. In this study, a magnetic ZIF-67@Fe3O4 (ZIFO) composite was successfully synthesized via a simple methanol-assisted in situ method at ambient temperature for the removal of Pb(II) from aqueous solution. The physicochemical properties of the synthesized material were comprehensively characterized using XRD, FTIR, FESEM-EDS, HR-TEM, Raman spectroscopy, BET surface area analysis, XPS, and zeta potential, confirming the successful integration of Fe3O4 into the ZIF-67 framework. Batch adsorption experiments were conducted to evaluate the effects of pH, contact time, and initial Pb(II) concentration on adsorption performance. The results showed that Pb(II) uptake was strongly dependent on solution pH, with optimal removal achieved at pH 6. Under the optimized conditions, ZIFO exhibited an experimental adsorption capacity of 212.69 mg g⁻¹ and achieved up to 99.86% Pb(II) removal. Kinetic analysis revealed that the adsorption process was best described by the pseudo-second-order model (R² = 0.99535), indicating that chemisorption dominated the adsorption mechanism. The equilibrium data were well-fitted by the Langmuir isotherm model (R² = 0.9887), with a maximum monolayer adsorption capacity of 158.73 mg g⁻¹. These findings demonstrate that ZIFO is a fast, efficient, and magnetically separable adsorbent with strong potential for the practical treatment of Pb(II)-contaminated wastewater.

Rapid and Sensitive Gold Nanoparticles Based Colorimetric Sensor for Mn(II) Ions Detection: A Potential Approach for Urinary Health Monitoring

2026-06-13T03:52:02+00:00

Manganese (Mn) is an essential trace element, but excessive accumulation in the human body can cause severe neurotoxic effects, making sensitive monitoring in biological fluids such as urine important for public health. This study reports a rapid colorimetric sensor based on ethylenediaminetetraacetic acid (AuNPs-EDTA) for selective Mn(II) detection. AuNPs were synthesized by chemical reduction of HAuCl4 using NaBH4, producing spherical nanoparticles with a surface plasmon resonance (SPR) peak at 525 nm and a size of 20-40 nm. EDTA functionalization was confirmed by an SPR red shift to 535 nm, a zeta potential change from -32.34 to -45.68 mV, FTIR spectral shifts of carboxylate and hydroxyl groups, and retention of spherical morphology with a size of 25-40 nm. Upon addition of Mn(II), the AuNPs-EDTA suspension exhibited a concentration-dependent color change from wine red to blue accompanied by an LSPR shift from 535 to 670 nm. This sensor showed good linearity over 0.5-7.0 μg/L Mn(II) (R² = 0.9905), with a limit of detection (LOD) of 0.392 μg/L and a limit of quantification (LOQ) of 1.189 μg/L. High selectivity was obtained against common urinary ions and interferents, including Na+, K+, Ca²+, Mg²+, Zn²+, Cu²+, Pb²+, Cd²+, Co²+, Ni²+, Fe²+, Cl−, urea, uric acid, and creatinine. Recovery values of 94.46-98.01% (RSD < 2%) were achieved in spiked urine samples. These results demonstrate that AuNPs-EDTA provides a rapid, cost-effective, and promising platform for urinary Mn(II) monitoring.

Effect of Capacity Characterization with C-Rate Variations on ECM Parameter Identification Accuracy in Li-Ion Batteries using the HPPC Method

2026-05-13T04:17:30+00:00

Accurate battery models are essential for battery management systems to ensure reliable state estimation and performance prediction. However, the influence of capacity characterization conditions on equivalent circuit model (ECM) parameter identification remains insufficiently investigated. This study evaluates the effect of characterization C-rates on the parameter identification accuracy of a second-order Thevenin ECM using the Hybrid Pulse Power Characterization (HPPC) method. Three characterization conditions, namely C/20, C/5, and C/3, were applied to Panasonic NCR18650B lithium-ion cells to investigate the relationship between effective capacity variation, ECM parameters, and model accuracy. The results show that the effective capacity varied by less than ±2% across
the investigated C-rates. Model validation demonstrated that the C/20 and C/3 characterization conditions produced comparable prediction accuracies, with RMSE values of 0.0213 V and 0.0214 V, respectively, whereas the C/5 condition resulted in larger prediction errors. Residual analysis further confirmed that the C/3-based model exhibited uncertainty characteristics similar to those obtained under the conventional C/20 condition. These findings indicate that increasing the characterization rate from C/20 to C/3 does not significantly degrade ECM parameter identification accuracy while substantially reducing the experimental duration. Therefore, the C/3 characterization condition provides a favorable trade-off between model accuracy and testing efficiency, making it a promising
approach for rapid battery characterization and battery management applications, particularly for lithium-ion battery systems used in LEO satellites.

Formulation and In Vivo Study of A Liquid Crystal Containing Propolis Extract For Wound Healing Treatment

2026-06-02T06:10:04+00:00

Impaired wound healing remains a major clinical challenge, necessitating the development of effective and biocompatible topical therapies. This study aimed to develop and evaluate a lipid-based liquid crystalline propolis extract (LCPE) cream for wound-healing applications. Propolis was extracted with 70% ethanol using ultrasound-assisted extraction (UAE), yielding 21.21% extract with a total phenolic content of 249.6 ± 20.8 mg GAE/g and antioxidant activity (IC₅₀) of 504 ± 12 ppm. LC–MS/MS analysis the identified major bioactive compounds was mangostin. Liquid crystalline cream bases were optimized using a one-factor-at-a-time (OFAT) approach with varying concentrations of cetostearyl alcohol. The formula demonstrated suitable pH (5.4–5.8), viscosity (10,402–40,742 cps), spreadability, adhesiveness, and physical stability. Polarized light microscopy (PLM) confirmed the formation of anisotropic liquid crystalline structures, while DSC analysis indicated successful incorporation and thermal compatibility of the extract within the system. In vivo wound-healing evaluation using a rabbit excisional wound model demonstrated that LCPE significantly accelerated wound closure and reduced inflammation compared to untreated control group. Among the tested concentrations (1%, 2.5%, and 5%), LCPE 2.5% exhibited the most effective healing performance, as evidenced by faster wound closure and lower REEDA scores. In conclusion, LCPE represents a stable, skin-compatible, and promising topical delivery system for wound healing.

Magnetically Recoverable BiVO4/Fe3O4/g-C3N4 Photocatalyst via One-Pot Hydrothermal Synthesis for Visible-Light Methylene Blue Degradation

2026-05-04T06:59:59+00:00

The development of efficient and recyclable photocatalysts offers promising alternatives for wastewater treatment. However, significant challenges remain, including inefficient light utilization for photodegradation and rapid charge-carrier recombination. This study aims to synthesize a distinctive reusable BiVO4/Fe3O4/g-C3N4 (BNFC) photocatalyst with magnetic recovery via a one-pot hydrothermal method for visible-light methylene blue (MB) degradation. The optimal composite, BNFC-0.5, exhibited superior photocatalytic performance, achieving a degradation efficiency of 93.04% under optimal conditions of catalyst composition, pH 9, and 160 minutes of irradiation, with a TOC mineralization efficiency of 42.48%. The high degradation efficiency of the BNFC-0.5 composite is ascribed to its enhanced ability to harvest visible light, facilitate electron excitation with lower energy input, and promote effective electron–hole migration via the proposed Z-scheme configuration. Evaluation of the reactive oxygen species revealed that hydroxyl radicals (•OH) made the greatest contribution to the oxidation of MB. Kinetic assessment of the photocatalytic process revealed that the experimental behavior was adequately described by the Langmuir–Hinshelwood model, indicating a pseudo-first-order degradation pathway. In addition, the photocatalyst maintained a degradation efficiency of 79.32% over four cycles, demonstrating good stability and reusability, which is supported by the composite’s good structural stability. Overall, the findings demonstrate that constructing a ternary heterojunction is an effective strategy for enhancing the composite’s photocatalytic capability. Owing to its high degradation efficiency and reusability, the composite represents a promising candidate for wastewater purification under visible-light conditions.

Rapid Prediction of Total Gingerol Content and Harvest Age Classification of Fresh Indonesian Red Ginger Using UV-Vis Spectroscopy

2026-04-18T06:42:53+00:00

Red ginger (Zingiber officinale var. rubrum) is a potential spice commodity widely used in the food and pharmaceutical industries due to its high gingerol content, which has antioxidant, anti-inflammatory, and anticancer properties. This study aims to develop a predictive model for gingerol content and a classification model for harvest age in Indonesian fresh red ginger using chemometrics and machine learning based on Ultraviolet-Visible (UV-Vis) spectroscopy. Samples from three harvest ages (7, 8, and 9 months after planting) were analyzed using a UV-Vis spectrometer. UV-Vis spectral data were acquired and processed using several spectral preprocessing techniques, namely baseline correction, Savitzky-Golay (SGs), Multiplicative Scatter Correction (MSC), and first derivative (D1). The analysis was performed using Partial Least Squares (PLS) and Artificial Neural Network (ANN) for prediction, as well as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), k-NN, Random Forest, and Support Vector Machine (SVM) for harvest age classification. The ANN paired with SGs+D1 with 2 hidden nodes achieved the best predictive performance (R² = 0.66, r = 0.74), with RMSEC and RMSEP of 0.7062 and 0.8317, respectively. Meanwhile, the SVM model with a combination of Baseline+D1 preprocessing achieved a harvest age classification accuracy of 0.91 and precision, recall, and F1-score of 0.93 each. The findings of this research yield significant practical implications for both advanced post-harvest technology and the phytopharmaceutical industry. By delivering a highly precise classification model, this work lays a solid technical foundation required to design high-throughput, automated, and cost-effective sorting systems tailored for fresh Indonesian red ginger matrices.

Development of Cassava Starch-Based Bioplastic Films Reinforced with Jerbung Shrimp Waste Powder (Fenneropenaeus merguiensis de Man)

2026-03-13T11:18:24+00:00

Plastic waste is a major environmental concern because of its long-term persistence and slow degradation under environmental conditions. Bioplastics derived from renewable resources offer a potential alternative to conventional petroleum-based plastics. This study evaluated cassava starch-based bioplastic films prepared using five paired formulations in which increasing Jerbung shrimp waste powder (JSWP) content was accompanied by a proportional reduction in glycerol content. A completely randomized design was used to evaluate formulations containing 0, 0.33, 0.67, 1.00, and 1.33% JSWP, paired with 2.00, 1.67, 1.33, 1.00, and 0.67% glycerol, respectively, based on the total mass of the film-forming formulation. Film morphology, functional groups, and crystalline structure were characterized using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD), respectively. SEM revealed relatively rough and heterogeneous film surfaces, while FTIR spectra showed bands associated with starch and amide-containing components derived from JSWP. XRD analysis indicated the disappearance of native cassava starch crystallinity after film formation and the appearance of diffraction peaks associated with JSWP components, confirming successful incorporation of the filler into the bioplastic matrix. Thermogravimetric analysis showed that formulations containing more JSWP and less glycerol exhibited lower maximum mass-loss rates and greater residual mass at 600°C, with JSWP1.33 producing the highest residual mass among the composite films. Across the paired formulations, tensile strength and water resistance increased, whereas elongation at break and transparency decreased numerically. WVTR also showed a decreasing numerical trend, although differences in WVTR and elongation were not statistically significant. Among the evaluated formulations, JSWP1.33 exhibited the highest mean tensile strength, water resistance, thickness, and residual mass, together with the lowest mean elongation, transparency, and WVTR. These findings demonstrate the potential of paired JSWP–glycerol formulation as a strategy for increasing the strength and water resistance of cassava starch-based films (CSBF), although the independent contributions of JSWP and glycerol require further investigation.

Effect of Sputtering Voltage on the Microstructure, Hardness, and Corrosion Resistance of Ni-Cr Coatings on Zirconium for Accident-Tolerant Fuel Applications

2026-06-09T11:30:00+00:00

Zirconium alloys are commonly employed as fuel cladding materials in pressurized water reactors; nevertheless, their low corrosion and oxidation resistance under harsh operating circumstances remain a significant barrier for accident-tolerant fuel applications. This work investigates how sputtering voltage affects the microstructural evolution, as well as the mechanical and corrosion performance, of DC-sputtered Ni-20Cr coatings deposited on Zr-4 substrates. The coatings were formed at sputtering voltages of 4, 5, and 6 kV and evaluated by X-ray diffraction, scanning electron microscopy-energy dispersive spectroscopy, microhardness and nanoindentation tests, and potentiodynamic polarization in a simulated PWR primary coolant. The findings show that sputtering voltage has a significant impact on crystallite refinement, coating compactness, and the integrity of the coating-substrate interface, all of which influence the functional performance of coatings. Among the investigated deposition conditions, the coating deposited at 5 kV had the best combination of microstructural, mechanical, and corrosion properties, whereas increasing the sputtering voltage to 6 kV resulted in microstructural degradation, which reduced protective performance despite increasing thickness. These results show a clear relationship between sputtering voltage, microstructural evolution, and the mechanical and corrosion performance of Ni-Cr coatings. The study offers important guidance for optimizing sputtering parameters and illustrates the efficacy of DC-sputtered Ni-Cr coatings for accident-tolerant nuclear fuel cladding.

Equatorial Electrodynamic Disturbances During the May and October 2024 Extreme Geomagnetic Storms: Implications for HF Communication and Geomagnetically Induced Current Risks in Indonesia

2026-07-13T06:04:44+00:00

The effects of the two biggest storms of Solar Cycle 25, the intense geomagnetic storms of May 10–11 and October 10–11, 2024, on the Indonesian equatorial region are examined in this study. For the 500-kV Jawa-Madura-Bali (JAMALI) transmission network, geomagnetically induced current (GIC) modeling was integrated with magnetometer and ionosonde observations from Pontianak (PTN), close to the geomagnetic equator, and Kupang (KPG), close to the southern crest of the Equatorial Ionization Anomaly (EIA). During both storms, significant equatorial amplification was noted. While the October storm caused lower local perturbations, the horizontal magnetic disturbance at PTN during the May event reached -471 nT, around 16% bigger than the minimum global Dst index (-406 nT). In the JAMALI network, rapid changes in the geomagnetic field produced geoelectric fields that caused quasi-DC currents of 0.6–1.6 A. Such currents may contribute to long-term transformer stress even when they are below essential operational criteria. Significant ionospheric disruptions were caused by both storms, with foF2 reductions of more than 50% and matching drops in maximum usable frequency (MUF) of about 4 MHz, suggesting increased dangers to HF communication equipment. Ionospheric variability over Indonesia is regulated by geomagnetic latitude, local time, storm-time electrodynamic forcing, and thermospheric dynamics, as demonstrated by the differences between PTN and KPG responses.

Synthesis and Characterization of Superabsorbent Bio-Based Hydrogels from Pandanus tectorius Leaf Cellulose through Ester-Based Crosslinking for Water-Holding Applications

2026-07-09T08:37:04+00:00

The development of sustainable hydrogels from renewable biomass has attracted increasing interest for environmental and agricultural applications. In this study, cellulose isolated from Pandanus tectorius leaves was utilized as a precursor for the synthesis of carboxymethyl cellulose (CMC), which was subsequently used to prepare hydrogels through ester-based crosslinking. A dual-network hydrogel structure was formed by blending CMC with hydroxyethyl cellulose (HEC), followed by esterification with citric (CA), fumaric (FA), and malic (MA) acids. Structural characterization using FTIR confirmed successful carboxymethylation and ester crosslinking within the polymer network, while SEM revealed a porous morphology favorable for water diffusion. The synthesized hydrogels exhibited gel fractions of 67–89%, swelling ratios of 578–4163%, and maximum degradation temperatures of 311–428°C. The CMC/HEC-MA hydrogel at a 15% crosslinker concentration demonstrated the most balanced combination of swelling capacity, gel fraction, and thermal stability. Owing to their high water-retention capability, porous structure, and biodegradability, these hydrogels show strong potential as superabsorbent materials for soil moisture conservation, controlled water release in agriculture, drought mitigation, and sustainable water management. These findings highlight the potential of biomass-derived hydrogels to support SDG 2 (Zero Hunger) by improving agricultural water retention, SDG 6 (Clean Water and Sanitation) by promoting efficient water management and treatment, and SDG 12 (Responsible Consumption and Production) by transforming renewable biomass resources into sustainable value-added materials.

Structural Characterization and Immunogenic Evaluation of a 50 kDa Thyroid Peroxidase Fraction Isolated from Hypothyroid Patient Serum

2026-05-12T17:15:29+00:00

Thyroid peroxidase (TPO) is a key enzyme involved in thyroid hormone biosynthesis and one of the major autoantigens in autoimmune thyroid disease. However, studies investigating immunoreactive serum-derived TPO-related protein fractions remain limited. This study aimed to isolate an approximately 50 kDa immunoreactive protein fraction from the serum of hypothyroid patients, characterize its biochemical properties, and evaluate its immunogenicity for rabbit polyclonal antibody production. Serum samples were initially characterized based on anti-TPO antibody levels and total protein concentration. Rabbits were immunized with the isolated protein, and the resulting immune response was evaluated by indirect ELISA, SDS-PAGE, Western blotting, histopathology, and immunohistochemistry. SDS-PAGE consistently revealed a distinct protein band at approximately 50 kDa. ATR-FTIR analysis demonstrated characteristic protein-associated functional groups, while LC-MS/MS confirmed the proteinaceous nature of the isolated fraction through amino acid composition analysis. Immunization induced a progressive increase in anti-TPO IgG levels, and the purified rabbit IgG exhibited the expected electrophoretic profile under reducing and non-reducing conditions. Western blot analysis demonstrated that the generated polyclonal antibodies recognized the isolated approximately 50 kDa protein fraction, whereas no signal was detected in the secondary antibody-only control. Histopathological and immunohistochemical analyses further supported activation of the immune response following immunization. These findings demonstrate that the isolated approximately 50 kDa immunoreactive protein fraction possesses biochemical and immunogenic properties and has potential as an experimental immunogen for polyclonal antibody production.

Semi-Analytical and Numerical Solutions of the KdV-BBM Equation Using Differential Transformation Method and iRK-5 Based Method of Lines

2026-07-13T09:17:08+00:00

The Korteweg-de Vries-Benjamin-Bona-Mahony (KdV-BBM) equation is a fundamental mathematical model describing nonlinear long-wave propagation in dispersive media. This study presents a comprehensive computational investigation employing two distinct and complementary approaches: a tailored semi-analytical Differential Transformation Method (DTM) and a numerical Method of Lines (MOL) coupled with an improved fifth-order Runge-Kutta (iRK-5) scheme to solve both homogeneous and inhomogeneous KdV-BBM equations. The scientific novelty of this work lies in optimizing these two independent frameworks to achieve high accuracy without requiring restrictive linearization or excessively small time steps. Semi-analytically, DTM is optimized using prescribed Cauchy boundary conditions for the homogeneous model to supply essential derivative data that guarantees coefficient uniqueness and accelerates series convergence, while Nayar’s Theorem is incorporated to efficiently circumvent complex recurrence relations in the inhomogeneous case via variable separability. Numerically, the continuous PDE is discretized spatially via centered differences and integrated in time using the high-order iRK-5 scheme. Both approaches demonstrate exceptional performance in resolving the KdV-BBM model. Comparative evaluations demonstrate that the MOL(iRK-5) scheme superiorly preserves physical wave integrity, soliton peak height, and phase characteristics over extended simulation periods (T = 30), significantly outperforming standard explicit Fourth-Order Runge-Kutta (RK-4) and implicit Crank-Nicolson (C-N) methods. Unlike lower-order implicit schemes like C-N, which exhibit limited temporal accuracy (O(Δt2)) and high matrix inversion costs, or RK-4 which faces severe CFL constraints, iRK-5 achieves higher temporal precision (O(Δt5)) and an expanded stability domain, allowing larger time steps (Δt =0.5) with minimal error (E ≈6.58 ×10−4). Von Neumann stability analysis applied to the spatial discretization of the MOL framework confirms neutral stability, with iRK-5 providing a larger stability margin along the imaginary axis compared to RK-4. Grid refinement tests for the inhomogeneous model further confirm that spatial resolution (Δx) dominates total accuracy; reducing Δx from 0.01 to 0.0003 successfully decreases the Mean Square Error from 10−3 to 10−7. Overall, both the semi-analytical DTM and numerical MOL(iRK-5) frameworks prove to be highly accurate, robust, and effective standalone tools for investigating complex nonlinear dispersive wave dynamics.

On the Spectral Characterization of Prime Coprime Graphs Associated with Dihedral Groups

2026-07-11T05:05:23+00:00

Spectral graph theory and group theory help reveal how the structure of graphs shapes their mathematical properties. This research aims to analyze the spectral descriptors of the prime coprime graph of a dihedral group associated with the Laplacian, normalized Laplacian, and Seidel matrices. We also establish a method for determining the eigenvalues of these matrices. The results show that the Laplacian, signless Laplacian, and normalized Laplacian energies of the obtained graph are always even integers, whereas the adjacency and Seidel energies are never odd integers. These findings are consistent with previous studies and further strengthen the role of spectral descriptors in understanding algebraicgraph structures.

Aminated Porous Methacrylate-Based Polymer Monolith as an Anion Exchanger Microreactor for Sustainable Continuous Flow Transesterification of Palm Oil

2026-06-29T14:13:01+00:00

The development of regenerable heterogeneous catalysts for sustainable biodiesel production remains a major challenge, particularly for continuous-flow systems. This study aimed to develop a functionalized methacrylate-based monolithic polymer as a catalytic microreactor for the continuous transesterification of palm oil. The novelty of this work lies in (i) the use of diethylamine (DEA) as an amination agent for poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) (PGMEGD) monoliths, (ii) the systematic optimization of the alkalization process to produce an anion-exchange resin, and (iii) the demonstration of catalyst regeneration through an effective sequential washing procedure. PGMEGD monoliths were synthesized in situ using a ternary porogenic system consisting of 1-propanol, 1,4-butanediol, and water, followed by functionalization with DEA at concentrations ranging from 5 to 25% and subsequent alkalization with NaOH. FTIR and SEM analyses confirmed successful chemical modification while preserving the interconnected three-dimensional porous structure of the monolith. The highest amine density of 3.43 mmol g⁻¹ was obtained at a DEA concentration of 20%, whereas an optimum OH⁻ exchange capacity of 3.28 mmol g⁻¹, corresponding to 96% of the amine density, was achieved after alkalization with 1.0 M NaOH. In the continuous transesterification of palm oil with methanol, the catalyst achieved an optimum biodiesel yield of 86.28% at a methanol-to-oil molar ratio of 9:1 and a flow rate of 0.05 mL min⁻¹. The catalyst maintained a biodiesel yield above 80% for four consecutive cycles, while regeneration using sequential citric acid-NaOH-ethanol washing restored more than 99% of its catalytic activity and exhibited a consistent recovery pattern over two regeneration cycles. These findings demonstrate that the PGMEGD-NH₂-OH monolithic resin is a promising catalytic microreactor for sustainable biodiesel production under continuous-flow conditions.

Durability Controlled Hydration Mechanisms of High-Volume FABA-Based Binders with Nano Silica and Silica Fume Modification

2026-04-26T03:59:37+00:00

High-volume supplementary cementitious materials (SCMs) offer significant potential for reducing clinker consumption and CO₂ emissions, but maintaining hydration efficiency and long-term durability remains a major challenge. This study investigated the hydration behavior, microstructural evolution, and transport-related durability of high-volume fly ash–bottom ash (FABA) binders incorporating mechanically activated bottom ash, nano-silica, and silica fume. The binder systems were evaluated using mechanical, transport, and integrated microstructural characterization. The 60% FABA (M1) binder exhibited the optimum performance, achieving a compressive strength of 44.5 MPa at 56 days together with the lowest sorptivity and water absorption. Integrated SEM, XRD, TGA/DTG, and BET/BJH analyses confirmed enhanced secondary hydration, progressive matrix densification, and mesopore refinement, with the highest specific surface area (11.9 m2/g) and the smallest average pore diameter (12.6 nm). These findings demonstrate that the durability of high-volume FABA binders is governed primarily by hydration-induced pore refinement and reduced pore connectivity, providing a scientific basis for the design of durable low-carbon cementitious binders with high clinker replacement.

Isolation on Unsaturated Fatty Acids from Terminalia catappa L. Seed Oil Using Urea Crystallization Method as A Basic Material for Dihydroxy Octadecanoic Acid

2026-05-04T02:44:24+00:00

Dihydroxyoctadecanoic acid (DHOA) is a fatty acid-based compound with industrial and cosmetic applications. This compound can be synthesized through the chemical transformation of unsaturated fatty acids in vegetable oils, including Terminalia catappa L. (TC) seed oil. In this study, DHOA was synthesized and characterized using the unsaturated fatty acid (UFA) fraction of TC seed oil as the precursor. The UFA fraction was enriched by urea crystallization and subsequently subjected to epoxidation and hydroxylation reactions to convert the double bonds into dihydroxy groups through an epoxide intermediate. The UFA fraction was obtained as a viscous yellow liquid, with a maximum yield of 27.14% at a urea-to-fatty acid ratio of 8.57:1 (w/w). The fraction exhibited an iodine value of 74.23 mg I₂ g⁻¹ and a hydroxyl value of 33.66 mg KOH g⁻¹, indicating the presence of unsaturation and hydroxyl groups (−OH). GC-MS analysis showed that the urea crystallization product contained 73.28% unsaturated fatty acids. The resulting DHOA was obtained as a pale yellow semi-solid with an oxirane oxygen content (OOC) of 0.051% and a hydroxyl value of 186.96 mg KOH g⁻¹, indicating a low residual epoxide content and a high concentration of hydroxyl groups. Spectroscopic characterization revealed an O–H absorption band at 3432.84 cm⁻¹ in the FT-IR spectrum, accompanied by the disappearance of the epoxide C–O–C band. The ¹³C NMR spectrum exhibited a resonance at approximately δ 74 ppm, indicating hydroxylated carbon, while the ¹H NMR spectrum showed a resonance at approximately δ 3.3 ppm, corresponding to a methine proton in a –CH–O environment. Overall, these spectroscopic results provide structural evidence for the successful formation of DHOA.

A Comparative Study of Confidence Intervals for the Parameter of the XShanker Distribution with Applications

2026-07-10T02:12:12+00:00

Statistical modeling of lifetime and reliability data has gained significant interest in the last few decades because of its potential use in various disciplines, including engineering, biomedical sciences, agriculture, and medicine. For portraying complex data behaviors, especially when the hazard rate demonstrates non-constant patterns, traditional distributions such as the exponential and gamma distributions are frequently insufficient. The X-Shanker distribution offers a simple mixture distribution that retains a single parameter while providing greater flexibility in modeling positively skewed and heterogeneous data than some conventional lifetime distributions. Despite the increased interest in the X-Shanker distribution, no thorough comparative evaluation of confidence interval (CI) estimation approaches for its parameter has been conducted. Consequently, this work aimed to recommend four CIs for the X-Shanker distribution parameter. Using simulation studies and applications to two actual datasets, the likelihood, Wald, bootstrap-t, and bias-corrected and accelerated (BCa) bootstrap CIs were assessed. Monte Carlo simulations were used to evaluate their performance, with parameter values ranging from 0.2 to 2.5, sample sizes from 10 to 500, 2,000 simulation replications, and 2,000 bootstrap resamples. The empirical coverage rate (ECR) and average width were used as evaluation criteria. Likelihood and Wald intervals typically maintained coverage rates close to the nominal level of 0.95 across various parameter settings, including small sample sizes. Conversely, the bootstrap-t and BCa bootstrap CIs showed significant undercoverage, with empirical coverage rates decreasing to approximately 0.87–0.92 in some scenarios, although typically yielding narrower intervals. For the ECRs of all four methods, the values increasingly became similar and approached 0.95. The proposed methods were applied to two real datasets on bank customer waiting times and vinyl chloride concentrations in groundwater. The maximum likelihood estimate for the waiting-time data was 0.1945, and the four interval methods produced broadly similar 95% confidence intervals, with the bootstrap-based intervals being slightly narrower. For the vinyl chloride data, the likelihood and Wald CIs were narrower than the bootstrap-t and BCa bootstrap CIs. The results of model comparison based on information criteria and graphical analysis confirmed that the X-Shanker distribution provided a satisfactory fit for the two datasets. These empirical findings were consistent with the simulation results. In conclusion, the likelihood and Wald CIs are recommended when reliable coverage is the primary concern, particularly for small samples, whereas the bootstrap-based CIs may be preferred for larger samples when shorter interval widths are desired.

Synthesis of Nuclear Fuel Based on U–6Zr–xNb Alloy (x = 0, 1, 4, and 7 wt.%): Corrosion Product Analysis and γ-Phase Stability in Acidic and Alkaline Environment

2026-07-14T05:23:15+00:00

The U-6Zr alloys, considered as nuclear fuel, must endure mechanical, thermal, and corrosive loads. Corrosion resistance is crucial during reactor operation and storage, as environmental conditions can trigger material degradation. Niobium (Nb) addition is expected to suppress corrosion. The U-6Zr-xNb alloys (x = 0, 1, 4, and 7 wt.%) were fabricated using arc melting and tested in acidic and alkaline environments. XRD analyses before corrosion revealed that the x = 0 and 1 wt.% alloys consisted of a single α-U phase, while the x = 4 wt.% alloy showed both α-U and γ-U phases. At x = 7 wt.%, only the α-U phase was present. After corrosion, XRD showed the formation of α-U and UO₂ phases for x = 0 and 1 wt.%, α-U, γ-U, and UO₂ phases for x = 4 wt.%, and only the α-U phase for x = 7 wt.%. Electrochemical tests demonstrated that E_corr increased and the corrosion rate (CR) decreased with increasing Nb content. Thus, Nb effectively enhanced the corrosion resistance of the U-6Zr alloys. Among all compositions, the U-6Zr-7Nb alloy showed the lowest corrosion rate and highest corrosion resistance in both environments, suggesting its strong potential as a nuclear fuel candidate.

A Remark on the Energy Bounds and Degree-Based Topological Indices of the Zero-Divisor Graph ℤₚ[x]/⟨x⁴⟩

2026-07-19T03:49:05+00:00

The zero-divisor graph of a commutative ring, Γ(R), is a prominent subject in graph theory. Previous research has investigated the energy and topological indices of Γ(ℤₚ[x]/⟨x⁴⟩) for any prime p; however, errors were identified in the characteristic polynomial and the associated energy bounds. Recent work by Rather addressed these discrepancies using a vertex partitioning and quotient matrix approach. In contrast, this study presents a distinct matrix-theoretic approach based on the Schur complement to systematically derive the characteristic polynomial and its corresponding eigenvalues, thereby independently confirming and reinforcing the corrected energy bounds. Furthermore, this study significantly extends the existing literature by investigating a broader range of previously unexplored degree-based topological indices, including the second modified Zagreb, general and inverse general Randić, third and fifth symmetric division, harmonic, inverse sum, and forgotten indices.

Sustainable Fabrication of Banana Pseudo-stem (Musa paradisiaca L.)-derived ZnO/Carbon Composite as a Photo-antibacterial Agent

2026-04-13T03:28:32+00:00

Bacterial infections and antimicrobial resistance (AMR) represent critical global health challenges, necessitating sustainable antibacterial alternatives. This study presents the hydrothermal synthesis of ZnO nanoparticles integrated with banana pseudo-stem-derived carbon (BPS-C) nanocomposite as a photo-antibacterial agent. Structural characterization confirmed crystalline hexagonal wurtzite ZnO formation (XRD), with ZnO nanoparticles distributed within the amorphous BPS-C matrix (broad halo 2θ ≈ 20–30°), verified by FTIR, SEM-EDS (C, O, and Zn peaks), and DLS analysis. These composites exhibited a significantly reduced hydrodynamic diameter (377 nm) compared to pure ZnO (826 nm) and BPS-C (19,602 nm), suggesting that the incorporation of BPS-C influenced the dispersion behavior of the composite particles. Furthermore, the incorporation of BPS-C influenced the optical properties and charge-carrier behavior of the composite material. More importantly, antibacterial activity was assessed using Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative) as representative bacterial strains. The ZnO/BPS-C composite demonstrated antibacterial effects against the Gram-positive Staphylococcus aureus, whereas its impact on the Gram-negative Escherichia coli was lower compared to pure ZnO. The observed photo-antibacterial activity may be associated with reactive oxygen species (ROS) generation from the ZnO phase under light irradiation. The lower sensitivity of E. coli (maximum inhibition zone of 7.23 mm) may be associated with its protective lipopolysaccharide-rich outer membrane, while pristine BPS-C showed no antibacterial activity (6.00 mm). These findings demonstrate the feasibility of utilizing banana pseudo-stem as a sustainable biomass precursor for ZnO/carbon composite fabrication. Moreover, the ZnO/BPS-C nanocomposite emerges as a promising sustainable candidate for photo-antibacterial applications.

Bioactivity and Secondary Metabolites Profiling of Kitasatospora sp. TC-ARCL7 Isolated from Curcuma longa L. Rhizosphere

2026-07-11T05:11:04+00:00

Actinomycetes are important sources of bioactive compounds with pharmaceutical potential. Kitasatospora sp. TC-ARCL7, isolated from the rhizosphere of Curcuma longa L., has previously shown anticancer activity against the T47D cell line, but its broader biological activities remain unexplored. This study evaluated the anticancer, antimicrobial, and antioxidant activities of its ethyl acetate extract. Cytotoxic activity was assessed against T47D, HepG2, HeLa, and Vero cell lines, while antimicrobial activity was determined against selected bacterial and fungal pathogens using minimum inhibitory concentration (MIC) analysis. Antioxidant activity was evaluated using the DPPH and FRAP assays. The extract exhibited potent cytotoxic activity, with IC50 values of 0.20 ± 0.04 (SI: 3883.03 ± 476.79), 2.64 ± 0.46 (SI: 301.28 ± 67.38), and 2.33 ± 0.39 (SI: 328.86 ± 23.37) μg/mL against T47D, HepG2, and HeLa cells, respectively. The Kitasatospora sp. TC-ARCL7 isolate inhibited the growth of Bacillus subtilis, Escherichia coli, Staphylococcus aureus, and Candida albicans. In contrast, the ethyl acetate extract showed no inhibitory zone against Pseudomonas aeruginosa and C. albicans. The extract exhibited antioxidant activity predominantly through electron-transfer mechanisms, as indicated by its strong FRAP response (118.70 ± 18.8 mM Fe(II)/g) despite weak DPPH scavenging activity (IC50 = 513.35 μg/mL). GC-MS analysis identified several compounds previously reported to possess anticancer, antimicrobial, and antioxidant activities. The high selectivity indices and potent cytotoxic activity against T47D cells suggest that the ethyl acetate extract of Kitasatospora sp. TC-ARCL7 is a promising source of bioactive compounds for further research into anticancer drug discovery.

Antibacterial Efficacy of Chitosan Nanoparticles from Musa paradisiaca L. Peel Ethanol Extract against Propionibacterium acnes: Characterization and Identification of the Compounds

2026-04-26T14:32:33+00:00

Hijau lumut banana peel (Musa × paradisiaca L.) contains bioactive compounds with antibacterial properties and has potential as a natural anti-acne agent. This study aimed to prepare and characterize chitosan-based nanoparticles incorporating hijau lumut banana peel (HLBP) ethanol extract, evaluate their antibacterial activity against Propionibacterium acnes, and identify their chemical constituents. HLBP extract was obtained by ethanol maceration and subsequently incorporated with chitosan and sodium tripolyphosphate (NaTPP) through an ionic gelation process to produce nanoparticles. The broth microdilution technique was used to determine the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC), while the agar diffusion assay was used to evaluate antibacterial activity. The nanoparticles were characterized using particle size analysis (PSA), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), and liquid chromatography–tandem mass spectrometry (LC–MS/MS). The nanoparticles exhibited strong antibacterial activity against P. acnes, with inhibition zones of 31.47 ± 0.03 mm and 28.15 ± 0.10 mm for formulations containing 0.5% and 1% chitosan, respectively. The MIC and MBC values were 1.25% and 2.50%, respectively. The optimal formulation containing 0.5% chitosan had a particle size of 721.9 ± 25.57 nm, a polydispersity index of 0.509 ± 0.018, and a zeta potential of −36.2 ± 0.60 mV. Morphological analysis revealed irregular, flattened particles. These findings suggest that chitosan nanoparticles loaded with HLBP exhibit promising antibacterial activity against P. acnes and have potential for use as a natural anti-acne formulation.

Enhanced Growth Control of Silver Nanowires Through Silver Nitrate Concentration for the Optical, Thermal, Crystal Structure, and Morphology Properties

2026-06-08T07:59:10+00:00

Silver nanowires were successfully synthesized using the polyol method with silver nitrate concentrations of 0.3 M and 0.5 M. The synthesized silver nanowires were characterized using UV-Vis, FTIR, DTA/TGA, XRD, TEM, SEM–EDX, and SAED to investigate their optical, chemical, thermal, structural, and morphological properties. UV-Vis spectra exhibited characteristic surface plasmon resonance absorption bands at 350-390 nm, with peak positions influenced by changes in nanowire dimensions and aspect ratio as a function of silver nitrate concentration. FTIR analysis confirmed the interaction of polyvinylpyrrolidone and ethylene glycol with the silver surface, indicating effective surface stabilization during synthesis. Thermal analysis showed that silver nanowires synthesized at 0.5 M possessed higher thermal stability, as evidenced by higher decomposition temperatures and greater residual mass. XRD patterns revealed the characteristic face-centered cubic crystal structure of silver with dominant diffraction planes of (111), (200), (220), (311), and (222). TEM and SAED analyses confirmed the formation of one-dimensional polycrystalline silver nanowires, while SEM observations showed that increasing silver nitrate concentration produced nanowires with smaller diameters (185.79 ± 3 nm) and longer lengths (16.98 ± 2 µm). EDX analysis further verified the high purity of silver in the synthesized samples. These results demonstrate that silver nitrate concentration plays a crucial role in controlling the optical, thermal, structural, and morphological characteristics of silver nanowires synthesized via the polyol method. The improved properties obtained at higher precursor concentration highlight the potential of these silver nanowires as conductive nanomaterials for transparent conductive films, flexible electronics, optoelectronic devices, and sensor applications.

Characterization and Immunogenicity of Thyroid Stimulating Hormone (TSH) Isolated from Neonatal Umbilical Cord Serum

2026-06-18T05:49:51+00:00

Congenital hypothyroidism (CH) is among the most prevalent and preventable causes of intellectual disability in neonates worldwide, with thyroid-stimulating hormone (TSH) serving as the primary biochemical screening biomarker. In Indonesia, limited availability of locally produced anti-TSH antibodies restricts the scalability of neonatal CH screening programs. This study aimed to isolate TSH from neonatal umbilical cord serum and to evaluate its capacity to induce polyclonal antibodies suitable for immunoassay-based CH screening. Umbilical cord serum was processed using PBST-PMSF buffer and ethanol precipitation, followed by SDS-PAGE separation. A 28 kDa protein fraction was confirmed as a TSH-enriched antigen by Western blot analysis using a monoclonal anti-TSHβ antibody, then isolated via electroelution for immunogenic assessment. Structural characterization was performed by ATR-FTIR spectroscopy and LC-HRMS amino acid profiling. The electroeluted fraction was subsequently used as an immunogen in New Zealand White rabbits, and antibody performance was evaluated by indirect ELISA, dot blot analysis, splenic histopathology, and immunohistochemistry (IHC). Western blot confirmed a single immunoreactive band at 28 kDa. ATR-FTIR revealed a characteristic absorption at 1046 cm⁻¹, consistent with carbohydrate-associated structures of glycoproteins, while LC-HRMS detected amino acids compatible with TSH subunit composition, including arginine, leucine, lysine, and cystine. Immunization successfully induced polyclonal antibody production, with peak reactivity at a 1:200 serum dilution by indirect ELISA. Dot blot analysis demonstrated optimal antigen-antibody binding at a 1:10 dilution. Splenic histopathology confirmed systemic immune activation, evidenced by significant white pulp enlargement (110.25 ± 11.67 µm vs. 88.47 ± 6.67 µm; P < 0.05). IHC demonstrated specific antibody reactivity localized to thyrotroph cells of the rat anterior pituitary. These findings provide preliminary evidence supporting the utility of neonatal cord serum-derived TSH as an antigenic source for local polyclonal antibody production. Further analytical and clinical validation, including cross-reactivity assessment and diagnostic performance evaluation, is required prior to application in routine CH screening.

A Generalized Uncertainty Principle Involving Fractional Fourier Transform

2026-07-19T04:11:42+00:00

It is well known that the fractional Fourier transform (FrFT) is a non-trivial generalization of the classical Fourier transform. This transform has been extensively utilized in signal analysis and image processing. The uncertainty principle is one of the fundamental results related to the FrFT. In the present paper, we first propose the different method in proving a variant of Heisenberg uncertainty principles associated with the FrFT. This method combines the Heisenberg-type uncertainty principle pertaining to the FrFT and the additive property of the FrFT. We then provide an alternative proof of the logarithmic inequality for the FRFT and find that this result differs slightly that in the literature. Finally, we explicitly expand the variant of Heisenberg uncertainty principle to a more general case.

A Residual-Based Hybrid SVR–Ordinary Kriging–IDW with Residual Correction for Spatial Interpolation of Seismicity Parameters in Sumatra

2026-08-11T03:39:27+00:00

Accurate spatial prediction of seismicity parameters is important for characterizing seismotectonic behavior in tectonically complex regions. This study developed a hybrid spatial interpolation framework integrating Support Vector Regression–Ordinary Kriging (SVR–OK) with Inverse Distance Weighting (IDW) residual correction for estimating seismic activity (a-value) and rock fragility (b-value) across Sumatra. A total of 238 seismicity data points derived from ISC and BMKG earthquake catalogs (Mw > 5.0) for 2000–2023 were analyzed. SVR–OK was used to capture global spatial variation through flexible empirical semivariogram modeling, while IDW-based residual correction captured local variation remaining unexplained by the primary model. Performance was evaluated using LOOCV, independent testing, RMSE, MAE, RMSEP, residual diagnostics, and Moran’s I. The Hybrid SVR–OK–IDW Residual model achieved the lowest test RMSEP, reducing errors from 0.961 to 0.837 for the a-value and from 0.166 to 0.149 for the b-value, while reducing remaining positive spatial autocorrelation. Spatial contour maps identified distinct seismotectonic zonation, particularly in the Nias–Simeulue and Mentawai–Pagai segments. Simulation experiments showed that its advantage was most pronounced for clustered spatial patterns at small to moderate sample sizes (n = 64 and 225), whereas Gaussian–OK and SVR–OK performed better for unclustered patterns. These findings demonstrate the advantage of combining SVR–OK for global spatial variation with IDW residual correction for localized variation, particularly under clustered and spatially heterogeneous conditions.

Space Weather-Induced Charging in The Garuda-1 Satellite Power Failure

2026-05-05T14:46:16+00:00

This study investigates the relationship between the geostationary space environment and the Garuda-1 satellite power anomaly that occurred on April 5, 2005. To assess potential anomaly mechanisms, GOES-12 electron and proton flux data, geomagnetic indices, solar wind parameters, and SPENVIS-based charging simulations were examined. While proton fluxes and solar X-ray activity remained relatively low during the event period, relativistic electron fluxes increased significantly under disturbed geomagnetic conditions, as indicated by enhanced AE activity, increased solar wind speed, and prolonged southward IMF Bz. Under these conditions, SPENVIS simulations indicate increased spacecraft surface and internal charging susceptibility. The findings suggest that storm-time energetic electron enhancement and associated charging processes in the geostationary environment may have been associated with the reported Garuda-1 anomaly. This work emphasizes the importance of magnetic local time dependence and geomagnetic activity in influencing spacecraft charging risk for geostationary satellites.

Jacobson-Type Graphs Over Rings: Induced Subgraphs and Isomorphisms

2026-06-18T15:10:10+00:00

Jacobson-type graphs provide a combinatorial framework for studying structural properties of finite commutative rings. We address two foundational questions: the behavior of these graphs under subring inclusions, and conditions under which distinct Jacobson-type constructions are isomorphic. This paper proves that whenever $S$ is a subring of a finite commutative ring $R$ , the Jacobson-type graphs of $S$ arise naturally as induced subgraphs of the corresponding graphs of $R$ , with finiteness playing an essential role in sustaining this embedding. We further characterize precisely when the Jacobson graph, the $nn$ -array Jacobson graph, and the matrix Jacobson graph over a ring are isomorphic. These results establish a correspondence between algebraic relations of rings and combinatorial relations of their associated graphs.

Independence and Matchings on Cayley Digraphs of Transformation Semigroups with Fixed Sets

2026-07-09T07:14:26+00:00

Let $Y$ be a nonempty set of $X$ and denote by $Fix(X,Y)$ a semigroup of full transformations $\alpha$ on $X$ provided that $a\alpha = a$ for all $a\in Y$. Further, let $A$ be a nonempty subset of $Fix(X,Y)$. The Cayley digraph $\text{Cay}(Fix(X,Y),A)$ is defined to be a digraph whose vertex set is $Fix(X,Y)$ and arc set is the set of all ordered pairs $(\alpha,\beta)$; where $\alpha, \beta\in Fix(X,Y)$, such that $\beta = \alpha\gamma$ for some $\gamma\in A$. A nonempty subset $I$ of $Fix(X,Y)$ is said to be independent if every two vertices in $I$ are independent, that is, there is no arc joining them. The maximum cardinality of an independent set is called the independence number. Moreover, an edge independent set is called a matching and the maximum cardinality of an edge independent set is called the matching number. In this paper, we determine several independence and matching parameters of Cayley digraphs of $Fix(X,Y)$ whose connection sets are relative to minimal idempotents and permutations.

An Investigation on the Edge-gracefulness of Bubble Sort, Bubble Sort Star, and Kulli-Cycle Windmill Graphs

2026-05-11T16:14:21+00:00

A fundamental area of graph theory, graph labeling concerns the assignment of integers to the vertices, edges, or both of a graph under specified constraints. One of the many types of graph labeling is edge-graceful labeling. Edge-graceful labeling requires assigning distinct integers from 1 to q to the edges of a graph G with p vertices and q edges so that the induced vertex labels, obtained by summing the labels of all incident edges modulo p, are pairwise distinct. Now, determining which graph families admit such labeling remains challenging, and this study focuses on the edge-gracefulness of bubble sort graphs, bubble sort star graphs, and Kulli-cycle windmill graphs, whose orders and sizes depend on multiple variables or factorial terms, unlike simpler graphs determined by a single parameter. Using the contrapositive of Lo’s Theorem and number-theoretic techniques, we establish that the bubble sort graph B_n is not edge-graceful whenever the parameter n is not an even integer that is greater than or equal to 4, that the only bubble sort star graphs that have the potential to be edge-graceful are BS_n with n ≥ 4, and that W₃ is the only edge-graceful Kulli-cycle windmill graph.