The optical absorption of an isolated Λ-type three-level semiconductor quantum dot under continuous-wave excitation was investigated theoretically using a semiclassical density-matrix approach. The equations of motion were derived from the master equation within the rotating-wave approximation and solved in the steady-state regime to obtain the optical susceptibility and absorption spectrum. The roles of the transition dipole moment and relaxation rate were examined systematically in both weak- and strong-field regimes. In the weak-field regime, the spectrum was dominated by the ∣1⟩↔∣3⟩ transition, while a weaker secondary feature associated with the ∣2⟩↔∣3⟩ transition emerged through relaxation-assisted population redistribution. Increasing the relaxation rate broadened and suppressed the dominant peak, whereas increasing the transition dipole moment mainly broadened the weaker secondary feature. In the strong-field regime, the two absorption channels merged into a broadened composite profile due to the combined effects of stronger coherent driving, power broadening, and relaxation. These results clarify how transition strength and dissipation govern the absorption line shape of an elementary multilevel semiconductor quantum-dot system.
A laser processing strategy is presented for the high-concentration synthesis of ligand-free Au, Ag, and Au–Ag alloy nanoparticles. Monometallic Au and Ag nanoparticles were first synthesized independently by nanosecond pulsed laser ablation in liquid (PLAL), producing stable ligand-free colloids. The Au and Ag colloids were then mixed in an equimolar ratio and irradiated with femtosecond laser pulses to induce alloy formation without chemical stabilizers or reducing agents. Ultraviolet–visible (UV–vis) spectroscopy shows a single localized surface plasmon resonance peak that shifts from 400 nm (Ag) to 509 nm (Au), with the Au–Ag alloy peak located between the two, confirming alloy formation. Transmission electron microscopy (TEM) reveals spherical Au, Au–Ag alloy, and Ag nanoparticles with average diameters of 11.8 ± 8.1 nm, 18.8 ± 5.9 nm, and 20.3 ± 9.4 nm, respectively, with the alloy nanoparticles exhibiting a narrower size distribution. Zeta potential measurements of −36.4, −41.2, and −48.1 mV for Ag, Au, and Au–Ag nanoparticles indicate good colloidal stability, with the alloy nanoparticles showing the highest stability. This laser-based approach provides a chemical-free route for producing high-concentration noble metal and alloy nanoparticles with tunable plasmonic and colloidal properties.
Silver nanoparticles (AgNPs) have strong potential as antibacterial agents, with effectiveness highly influenced by particle-size stability. This study synthesized AgNPs via a green sol-gel method using noni (Morinda citrifolia) leaf extract as a natural reducing agent and polyvinylpyrrolidone (PVP) as a capping agent. PVP concentrations of 0.5, 1.0, and 1.5 g were mixed with 25 mL noni extract and 25 mL double-distilled water. Characterization using UV–vis, XRD, FE-SEM/EDX, and FTIR showed decreasing UV–vis absorption peaks of 433, 412, 368 nm with increasing PVP content. XRD confirmed a face-centered cubic (FCC) crystal structure with >80% similarity to standard Ag patterns. FE-SEM/EDX indicated the presence of Ag, C, and O elements, and particle sizes remained stable at 16.8, 18.8, and 18.4 nm. The 0.5 g PVP sample produced the smallest particles and showed dominant O–H and C–H functional groups. It exhibited the strongest antibacterial activity, with inhibition zones of 12.5 mm (E. coli) and 12.0 mm (S. aureus). These results demonstrate that eco-friendly sol-gel-synthesized AgNPs using noni leaf extract and PVP exhibit promising antibacterial activity, positioning them as potential candidates for further development as antibacterial materials.
Quantum refrigerators (QRs) are pivotal in exploring thermodynamic behavior at microscopic scales. This study investigates a quantum Otto refrigerator using a bosonic gas confined in a cubic potential, operating under finite-time thermalization. We derive key thermodynamic quantities analytically, including the coefficient of performance (COP), cooling power, entropy, and cooling rate. Additionally, we investigate how partial thermalization during the isochoric heating and cooling stages influences overall system performance. The findings reveal a trade-off between COP and cooling power, emphasizing the importance of thermalization duration. Notably, by extending the cooling time relative to heating, the COP can be significantly improved, offering a practical approach to optimizing QR performance under realistic conditions.
The climatological pattern of rainfall and the occurrence of extreme drought and extreme wet in Indonesia are influenced by monsoon dynamics, topography, and Sea Surface Temperature Anomalies (SSTA) in the Pacific and Indian Oceans. Although studies on extreme droughts in Indonesia exist, none have quantified the spatial frequency of extreme drought and rainfall events. This study aims to determine the frequency and trend of extreme drought and extreme rain in Indonesia during 1995–2024. Gridded precipitation data from the Global Precipitation Climatology Center (GPCC) with 0.5° resolution were used. Frequencies of extreme drought and extreme wet were calculated using the Standardized Precipitation Index (SPI), while trends were estimated from the Poisson Regression slope. Frequency and trend were computed for the grid to represent spatial distributions. SPI results at 3, 6, and 12-month scales show Sumatra, Kalimantan, and Papua experienced extreme droughts 8–12 times, with varying frequencies. Extreme droughts were widespread in eastern Indonesia during the dry season (JJA and SON), with longer persistence in SPI-6 and SPI-12. In contrast, extreme wet events occurred more frequently in western and central Indonesia, during the rainy season (DJF), when the western monsoon transported moisture from the Indian Ocean.
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by multiscale structural brain degeneration. Many MRI-based machine learning approaches rely on coarse volumetric measures or black-box models with limited anatomical interpretability. This study aims to localize anatomically meaningful brain regions that discriminate AD from cognitively normal (CN) subjects using a hierarchical tissue-based (HTB) MRI framework. The method models gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) volumetric changes at lobar, gyral, and 246 fine-grained subregions defined by the Brainnetome atlas. T1-weighted MRI scans from 454 participants (227 AD, 227 CN) obtained from ADNI and MIRIAD were preprocessed using AC-PC alignment, N4 bias correction, skull stripping, and nonlinear registration to MNI space. A total of 561 HTB features were extracted to train Random Forest and XGBoost classifiers using five-fold stratified cross-validation with Bayesian hyperparameter optimization. The XGBoost model achieved the best performance (Accuracy: 79.74%, ROC-AUC: 85.07%), comparable to recent atlas-based MRI classification studies, while providing improved multiscale anatomical interpretability. SHAP analysis revealed consistent hierarchical atrophy patterns in hippocampal subregions, medial amygdala, and areas 35/36 and 28/34, demonstrating that hierarchical anatomical modeling with explainable machine learning enables transparent localization of clinically meaningful AD biomarkers without reliance on black-box architectures.
Existing crude oil percentage prediction methods often rely on direct measurements and historical data, neglecting the coupled multiphase characteristics of oil–water–sediment systems, which limits predictive accuracy. This study develops a computational physics–based machine learning model integrating key multiphase production parameters, including water cut, basic sediment, and BS&W, using samples from PT. Pertamina Puspa Field Jambi. Data were split into two sets: one for model development and one for validation to prevent overfitting. Linear Regression, Support Vector Machine (SVM), and Random Forest algorithms were applied, with Linear Regression achieving the best performance. For the test dataset, the model yielded a Mean Absolute Error of 0.022168, a Mean Squared Error of 0.001227, and an accuracy of 0.99877, demonstrating precise capture of multiphase interactions. The proposed computational physics–based modelling framework provided improved predictive reliability and consistency. Correlation analyses indicated a coefficient of determination (R²) of 0.99 and a perfect negative correlation (r = −1) between BS&W and oil content, showing that higher BS&W corresponds to lower oil percentage. This framework offers improved predictive reliability and consistency for crude oil quality assessment.
This study examines long-term GNSS-derived velocities along southern Java during 2011–2020 to characterize regional crustal deformation. Data from six InaCORS stations operated by BIG were processed using GAMIT/GLOBK to produce time series and estimate horizontal and vertical velocities. Horizontal velocities range from 21.35 mm/yr to 27.54 mm/yr toward the southeast, reflecting strong Eurasian Plate influence. The time series indicates gradual, continuous displacement without significant co-seismic offsets, despite several Mw ~6 earthquakes in the region. Vertical velocities show both uplift and subsidence, ranging from −13.84 mm/yr to 12.61 mm/yr, likely resulting from combined tectonic and non-tectonic processes. Because vertical GNSS measurements generally have higher uncertainty, these results must be interpreted cautiously. Although station motions appear stable, this does not indicate low seismic hazard. Instead, it may suggest ongoing strain accumulation within a seismic gap that could generate a future major earthquake. Overall, these findings enhance understanding of southern Java’s subduction dynamics and support improved earthquake hazard assessment and disaster preparedness.
Analysis of breast cancer radiation dose distribution using bolus density in radiotherapy planning of the Three-Dimensional Conformal Radiotherapy (3DCRT) technique has been conducted. This research aims to analyze radiation dose distribution in breast cancer patients using bolus density in radiotherapy planning of the 3DCRT technique. Five images of breast cancer patients were processed using TPS Eclipse software. The bolus density values used were a mixture of beeswax and petroleum jelly, playdough, silicone rubber, and 3D Polylactic Acid. CI and HI values were calculated based on the International Commission on Radiation Units and Measures (ICRU) Reports 62 and 83. Radiation dose in OAR was verified based on the Quantitative Analysis of Normal Tissue Effect in the Clinic (QUANTEC) standard. The results showed that all four bolus densities can be used in breast cancer patients, with CI values the CI value ranges from 0.93 to 0.98 by ICRU Report 62 standards and HI values close to ICRU Report 83 standards. In cardiac OAR, one patient exceeded the QUANTEC standard, while for lung OAR, all patients were below the QUANTEC standard. Using bolus density provides optimal radiation dose distribution on breast cancer targets.
This study aims to identify the profile of shear wave velocity (Vs30) and to analyze the classification of soil types of the Rammang-Rammang Maros Karst Area based on Vs30 value. This research was carried out at Rammang-Rammang Maros Karst Area, Salenrang and Bontolempangan Village, Bontoa District, Maros Regency, South Sulawesi. The method used in this research was the Horizontal to Vertical Spectral Ratio (HVSR) method to produce the HVSR curve and then analysed in the inversion method using Dinver to produce a ground profile. The Vs30 values were obtained in the range from 249 to 1384 m/s. The characteristics of the rock response could indicate the specifications of a rock type. Based on the Vs30 values, it was found that the classification of rock (SB) located around the karst hilly areas, soft rock (SC) located around the residential areas and the river, and stiff soil (SD) located near ricefield. The overall seismic risk in the research area is low based on Vs30 values below 200 m/s. These findings provide essential baseline data to support sustainable land use and tourism development planning in the region.
Asteroids have various shapes (mostly irregular) and physical characteristics. Space missions to asteroids are becoming frequent, and a global mapping scheme is applied to collect the asteroids’ physical properties. Depending on the mission purposes, the mapping scheme can encircle the whole asteroid’s body or utilize the asteroid’s equilibrium points for the least energy consumption. Furthermore, it is essential to construct optimal trajectories to maximize the coverage and science results. Thus, an efficient mission can be achieved by devoting periodic orbits of artificial satellites around the equilibria. This study aims to construct periodic orbits related to the equilibria of an oblate shape and rotating asteroid, under the influences of gravitational and rotational potentials. Equations of motion of the satellite affected by the potentials are formulated in the Cartesian coordinate system. By acquiring mutual zero accelerations (first derivative of the potentials with respect to all directions), the equilibria are then obtained. Adjacent to the asteroid, four equilibria were revealed, and analysis of their stability showed that all of them are unstable. Despite this, some periodic orbits centered at the respective equilibria were successfully constructed using some arbitrary parameters (harmonics) that affect the coverage area for mapping the asteroid.
Magnetite (Fe₃O₄) and RTV 48 silicone rubber-based magnetic composites have potential for outdoor applications due to their flexible and tunable magnetic properties. This study investigates the effect of immersion for 14 days in fresh water and seawater on its mechanical, magnetic, and thermal properties. Specimens were made by mixing 70 wt% Fe₃O₄ powder into RTV 48 matrix, then tested for hardness using Shore A durometer, magnetic properties using Vibrating Sample Magnetometer (VSM), and thermal stability using Thermogravimetric Analysis (TGA). Results showed a decrease in surface hardness due to matrix degradation by water penetration. The magnetic properties continued to exhibit soft magnetic characteristics with low coercivity and remanence. TGA analysis revealed changes in thermal degradation patterns, signaling chemical interactions between the material and the wet environment. These findings suggest that exposure to water can affect the long-term performance of Fe₃O₄-RTV 48 composites, making moisture resistance an important aspect for their outdoor applications.
Accurately determining stellar orbits within astrophysical systems is paramount for understanding celestial mechanics. This study proposes a novel approach to enhance orbit accuracy by incorporating a radius power law time step function model. The methodology involves the numerical integration of the system's dynamics using a forward fourth-order symplectic integrator, combined with a time step function dependent on the distance of the test particle from the system's center. We conduct simulations on various astrophysical scenarios represented by conservative potentials, including point mass, Plummer, and Hernquist models. Our results demonstrate that employing a power-law time step function with an exponent of 1.5 significantly reduces phase-space error (measured by the ratio of radial to orbital periods) and improves orbit accuracy (measured by the gradient of the relative total energy drift). The method is easy to implement, computationally efficient, and adaptable to N-body and more general dynamical systems. Its solid theoretical basis and numerical reliability make it a practical tool for improving orbit accuracy in diverse astrophysical applications.
Monte Carlo (MC) simulations provide a powerful approach to investigate electrolyte–electrode interactions and to optimize battery design. This study aims to determine the entropy and average energy of a lithium salt–ethylene carbonate (EC) system, as these parameters are essential for evaluating the Boltzmann factor. The Boltzmann factor was derived from entropy concepts and the principle of maximum entropy, which involves the Boltzmann constant (k) and the number of accessible states (Ω). Simulations were performed using Lennard–Jones parameters within a canonical ensemble framework to compute entropy and energy for systems with varying atom numbers. Results show that the system entropy for two atom types (200 atoms) was 6.67 × 107 kJ·mol–1·K–1. For three atom types (300 atoms), the equilibrium entropy reached 1.1 × 1010 kJ·mol–1·K–1, and for four atom types (400 atoms), 1.3 × 1013 kJ·mol–1·K–1. When reduced to five atom types with only 300 atoms (to minimize computational cost), the entropy was 2.4 × 108 kJ·mol–1·K–1. The simulations, employing the Metropolis criterion, successfully identified globally stable configurations, providing new insights into entropy-driven behavior in lithium battery electrolytes.
This research was conducted in Pondok Kelapa Subdistrict, Central Bengkulu Regency, to analyze subsurface characteristics using microtremor data and the Horizontal-to-Vertical Spectral Ratio (HVSR) method. The research compared DFA (Diffuse Field Assumption) and Geopsy approach. In this study, 40 points were measured with a distance between points ranging from 200 to 300 meters. The data were processed using Terraware-HV and Geopsy software with a Monte Carlo approach to model the 3D subsurface structure. Results show that the dominant frequencies range from 0.64 to 8.19 Hz, with high amplification zones between 1.92 and 7.72 concentrated in areas of loose soil, indicating their high seismic susceptibility. Vs30 values range from 55 to 465 m/s, reflecting the dominance of soft to medium materials, such as clay, gravel, sand, and soft rock at specific depths. 3D modeling revealed a heterogeneous distribution of subsurface materials, with high amplification zones requiring special mitigation. This study provides important insights for seismic risk zoning, disaster mitigation, and earthquake-resistant structure design, and supports sustainable development planning in earthquake-prone areas. The results are expected to serve as a reference in spatial management based on earthquake risk mitigation.
Thunderstorms are a significant challenge for aviation operations, especially in tropical regions such as West Sumatra. This study aims to determine threshold values for six atmospheric stability indices—Convective Available Potential Energy (CAPE), K-Index (KI), Lifted Index (LI), Showalter Index (SI), Severe Weather Threat Index (SWEAT), and Total-totals Index (TTI)—to predict thunderstorm events at Minangkabau International Airport (MIA). Radiosonde and daily synoptic reports from 2018–2022 were analyzed using Rawinsonde Observation Programs (RAOB) and Statistical Package for the Social Sciences (SPSS) with a dummy regression approach. The model was validated using a confusion matrix, measuring accuracy, precision, and recall. Results show that the use of locally calibrated thresholds leads to higher and more consistent accuracy, precision, and recall values compared to global benchmarks, due to better adaptation to local weather parameters such as vertical humidity, mid-layer temperature, and wind structure. KI, SI, and TTI showed high sensitivity (recall >88%), while LI and CAPE performed moderately. Monthly variation in index performance was observed, with KI, SI, and TTI dominant in the wet and transition seasons, and SWEAT effective in the dry season when shear-driven convection increases. Thus, locally calibrated indices are recommended for thunderstorm early warning systems in aviation.
Electricity is essential for everyday needs, including food preservation through refrigeration. However, access to electricity remains uneven in remote regions due to geographical constraints. Solar energy offers a promising alternative, especially in areas with abundant sunlight, highlighting the need for compact, portable, and eco-friendly cooling system. This study aims to design an eco-friendly cooling system using the Seebeck Effect in Peltier TEC 12706 modules powered by solar energy. The system consists of two Peltier TEC 12706 modules, a 50 Wp solar panel, and a 33 Ah accumulator, with a cooling chamber measuring 26 × 17 × 10 cm. Temperature and humidity were remotely monitored via the Blynk application. Experimental results showed the lowest temperature achieved was 15°C between 08:00 AM and 10:00 AM. In comparison, the most significant temperature drop of 11.7°C occurred between 12:00 PM and 02:00 PM, with an average light intensity of 176,846.15 Lux. Although the system demonstrated cooling performance, the minimum temperature of 15°C does not meet the standard refrigeration temperature of around 0°C. Therefore, the current system is not yet suitable for replacing conventional refrigerators, but it shows potential as an environmentally friendly alternative cooling solution with further development.
Ultrasonics in the medical field require a safe treatment for patients. The uncontrolled intensities of the ultrasonic waves cause ineffective treatment. So far, the hydrophone probe provides a standard for ultrasonic visualization. However, this method has constraints such as being time-consuming, intrusive, and requiring off-axis measurements. In this paper, an optical method called background-oriented schlieren imaging (BOSI) has been developed as an alternative. The BOSI uses a background of fringe patterns captured by a digital camera. The ultrasonic waves in water displace the patterns relative to the reference. A Hilbert Transform (HT) has been used to estimate the displacement of patterns proportional to the phase difference. The developed BOSI reconstructs these phase differences as an ultrasonic visualization. This paper reports that the developed BOSI is capable of visualizing the ultrasonic waves produced by a 1-MHz frequency medical transducer operated in continuous-wave (CW) mode. The visualization shows an undulation of phase difference that corresponds to the change in water density due to ultrasonic exposure. Meanwhile, the amplitude mode is proportional to the ultrasonic intensity profile. Thus, the developed BOSI is promising to be used as a calibration device to ensure safe ultrasonics in the medical field.
This study investigates the synthesis via solid state reaction and characterization of Li₇La₃Zr₂O₁₂ (LLZO) as a solid electrolyte doped with Al₂O₃ using a one-step heat treatment (sintering at 900°C for 4 hours). Samples were prepared with doping variations; pure LLZO (0Al-LLZO), 0.25Al-LLZO, and 0.5Al-LLZO, based on the formula with x = 0, 0.25, and 0.5, and were mixed using ball milling for 4 hours at 25 Hz. XRD and Rietveld refinement confirmed the formation of a dominant tetragonal Li₇La₃Zr₂O₁₂ phase alongside minor secondary phases. Grain sizes ranged from 1.2 to 1.3 µm, and densification improved with increasing Al content. The 0.25Al-LLZO sample exhibited the highest ionic conductivity of 2.83 × 10⁻⁹ S/cm at room temperature, representing a 2.96-fold increase over undoped LLZO. These results indicate that Al doping significantly enhances structural stability and Li-ion transport in LLZO electrolytes processed at moderate temperatures.
The fabrication of MAPbI3 perovskite solar cell (PSC) devices with the modification of adding cesium iodide (CsI) into the PbI2 layer to enhance performance has been successfully carried out. The used synthesis method was a two-step spin coating with CsI concentration variations: without CsI (control), 2 mg/mL, 3 mg/mL, and 5 mg/mL. Characterization using UV-vis, FESEM, and XRD showed improved in optical properties, morphology, and crystal stability. The UV-Vis spectrum indicated an increase in absorption from 2.29 to 3.17 a.u after CsI addition. FESEM results revealed that a 3 mg/mL CsI concentration produced a uniform morphology, a more compact film layer, and clear grain boundaries compared to other concentrations. XRD analysis showed a 2θ peak shift of 0.04°, indicating changes in crystal lattice parameters and increased lattice density without altering MAPbI₃ crystallinity. The device with 3 mg/mL CsI achieved an open-circuit voltage (Voc) of 1.2 V, a short-circuit current density (Jsc) of 11.34 mA/cm², a fill factor (FF) of 0.65, a power conversion efficiency (PCE) of 2.8%. In conclusion, 3 mg/mL CsI successfully enhanced PSC performance, but performance declined to 5 mg/mL.
