Matoa leaf (Pometia pinnata J.R. Forst & G. Forst.) is one of Indonesia’s endemic plants originating from Papua. Matoa leaves can be utilized as a preventive measure against stunting. Increasing the absorption of active ingredients in a preparation can be achieved by creating nanoparticles. The purpose of this study was to test the potential of matoa leaf nano-powder as an additional ingredient to prevent stunting in children. The stages of this study include the preparation of nanoparticles using the Planetary Ball Mill (PBM) method, capsule preparation formulation, determination of total phenol and flavonoid content, antioxidant activity test, antibacterial test against Escherichia coli and Staphylococcus aureus bacteria, determination of protein content, determination of carbohydrate content, determination of fat content, and determination of caloric value. Based on the results of this study, the antioxidant activity of matoa leaf nano-powder is very strong, with an IC50 value of 38.2078 ± 0.26 µg/mL, corresponding to total phenol and flavonoid levels of 232.3319 ± 14.66 mg GAE/g sample and 4.5288 ± 0.99 mg QE/g sample, respectively. Matoa leaf nanoparticle capsules exhibit strong antibacterial activity against Escherichia coli bacteria at a dose of 150 mg (12.61 ± 2.07 mm), a dose of 200 mg (13.4 ± 2.00 mm), and a dose of 250 mg (13.4 ± 2.00 mm). For Staphylococcus aureus, the inhibition diameters obtained with doses of 150 mg, 200 mg, and 250 mg are 13.25 ± 0.78 mm, 13.81 ± 1.10 mm, and 14.13 ± 1.23 mm, respectively. The results of determining the total protein content of matoa leaf nano powder in the spectrophotometric method of 0.8571% and the Kjeldahl method of 11.2%, total carbohydrate content of 0.4617%, and crude fat content of 2.6916%, with a caloric value of 294.96 kcal / kg and 708.71 kcal / kg. It is concluded that matoa leaf nano powder has the potential to prevent stunting.
Brucellosis, primarily caused by Brucella abortus, is a significant zoonotic disease that adversely affects both public health and the livestock economy, particularly in regions reliant on animal husbandry. This study aimed to evaluate the spatial distribution and estimate the Relative Risk (RR) of B. abortus infections in Malaysia from 2018 to 2024, utilizing two statistical approaches: the Standardized Mortality Ratio (SMR) and the Bayesian Poisson-Gamma model. Disease incidence data were obtained from the World Organization for Animal Health (WOAH), and analyses were conducted using R Programming and ArcGIS software to generate risk estimates and produce spatial disease maps across 14 Malaysian states. The SMR provided initial risk estimates but exhibited limitations in regions with zero reported cases, often underrepresenting potential disease burden. In contrast, the Poisson-Gamma model yielded more nuanced and robust risk estimations, identifying additional high-risk areas such as Kuala Lumpur and Sarawak, where the SMR reported no observed risk. This discrepancy highlights the Bayesian model’s strength in addressing data sparsity and underreporting. Both models consistently identified Perlis, Perak, and Johor as very high-risk states. The study concludes that the Poisson-Gamma model offers superior performance in detecting spatial risk patterns of B. abortus, particularly in areas with incomplete surveillance data. However, its limitations include reduced flexibility in adjusting for covariates and spatial dependencies. Furthermore, these findings underscore the importance of adopting advanced spatial modeling techniques in disease surveillance to inform targeted interventions, optimize resource allocation, and support evidence-based policy development in managing brucellosis and similar zoonotic diseases.
Lung cancer is one the leading causes of cancer related deaths worldwide. Standard therapies such as cisplatin are commonly used however, their long-term use can lead toxic effects on normal cells. Consequently, the search for alternative herbal based therapies has gained increasing attention. One potential candidate is Benalu batu (Begonia medicinalis), an endemic plant from Sulawesi that has been traditionally used as remedy for various ailments, including tumors and cancer. This study aims to evaluate the anticancer potential of ethanolic extract and fraction of Benalu batu both in vitro A549 lung cancer cells and Vero cells, and in silico against EGFR-TK and Bcl-2 proteins, which are involved in the progression of Non-Small Cell Lung Cancer (NSCLC). Cytotoxicity was assessed using the MTT assay, while compound identification was performed using Thin Layer Chromatography (TLC) and Gas Chromatography-Mass Spectrometry (GC-MS). Druglikeness feasibility was evaluated through Lipinski’s Rule of Five using SwissADME, and molecular docking studies were conducted using PyRx and Visualized with Discovery Studio. The results demonstrated that the ethanolic extract of wild Benalu batu exhibited higher cytotoxic activity compared to the cultivated plant extract, with an IC50 value of 134.71 µg/mL, and was nontoxic to Vero cells (IC50 = 517.24 µg/mL). Thin Layer Chromatography profiling indicated that the compounds in the wild Benalu batu extract are predominantly non-polar. Cytotoxicity testing of the active fractions revealed that fraction A exhibited the most potent activity with an IC50 of 33.93 µg/mL and high selectivity index of 24.52, surpassing that of cisplatin. Gas Chromatography-Mass Spectrometry analysis identified eight bioactive compounds suspected to have anticancer potential, these compounds are stigmasterol (19.80%), campesterol (7.06%), neophytadiene (4.83%), sitosterol (3.29%), squalene (2.73%), phytol (2.39%), phytol acetate (1.22%), hexadecenoic acid ethyl ester (1.22%), and α-tocopheryl acetate (1.10%). Molecular docking against the EGFR-TK protein showed that campesterol (-9.2 kcal/mol), stigmasterol ((-9.1 kcal/mol), and sitosterol (-8.2 kcal/mol), had more favorable binding affinity values compared to the control drug gefitinib (-7.7 kcal/mol). Sitosterol exhibited the highest binding affinity(-8.7 kcal/mol) against Bcl-2 protein, followed by squalene and stigmasterol (-8.5 kcal/mol), and campesterol (-8.4 kcal/mol).
Bentong ginger (Zingiber officinale Roscoe var. Bentong) and Kelulut honey (Heterotrigona itama) are recognized natural antioxidants, yet their synergistic potential remains underexplored. This study evaluated the antioxidant activities of Bentong ginger, Kelulut honey, and their combinations (10% ginger with 15% or 20% honey) using DPPH and ABTS radical scavenging assays, alongside LCMS/MS QTOF profiling to identify key contributing phytochemicals. Both assays demonstrated concentration-dependent antioxidant activity, with the 10% ginger and 15% honey mixture exhibiting the strongest effect and a pronounced synergistic interaction (CI = 0.66). LCMS/MS QTOF analysis revealed diverse bioactive constituents across samples, including phenolic acids, oxygenated terpenoids, flavonoids, fatty acid derivatives, and flavin-related metabolites, supporting the enhanced radical-scavenging capacity observed in the mixtures. Overall, the findings demonstrate that combining Bentong ginger with Kelulut honey significantly augments antioxidant potency and provides a strong scientific basis for the development of natural health products or functional formulations utilizing their synergistic antioxidant properties.
Herein, 5,10,15,20-tetrakis(4-hydroxyphenyl)-21H,23H-porphine (TPP-(OH)4) was functionalised with methacrylate group to convert it to a crosslinker (TPP-M) which later was used in photo-polymerisation alongside acrylamide. TPP-M obtained was characterised using proton nuclear magnetic resonance (1H-NMR), Fourier-Transform infrared (FTIR), ultraviolet-visible (UV-Vis) and fluorescence spectroscopy. The ability of TPP-M to detect Pb(II) ions was tested, and the resulted spectrum showed the reduced fluorescence intensity upon addition of Pb(II) ions. Then, the TPP-M was made into a polymer film through photo-polymerisation using UV light as a light source and diphenyl(2,4,6-trimethylbenzoyl)phosphine oxide (TPO) as a photo-initiator. The film obtained was tested for Pb(II) ion detection using fluorescence spectroscopy and showed reduced fluorescence intensities.
Brucellosis, primarily caused by Brucella abortus, is a significant zoonotic disease that negatively impacts both public health and the livestock economy, especially in regions dependent on animal husbandry. This study evaluated the spatial distribution and estimated the relative risk (RR) of B. abortus infections in Malaysia from 2018 to 2024, using two statistical methods: the Standardized Mortality Ratio (SMR) method and the Bayesian Poisson-Gamma model. Disease incidence data were obtained from the World Organization for Animal Health (WOAH), and analyses were performed using R Programming and ArcGIS software to generate risk estimates and create spatial disease maps for 14 Malaysian states. The SMR method provided initial risk estimates but showed limitations in regions with zero reported cases, often underestimating potential disease burden. In contrast, the Poisson-Gamma model produced more nuanced and robust risk estimates, identifying additional high-risk areas such as Kuala Lumpur and Sarawak, where the SMR method indicated no observed risk. This discrepancy highlights the Bayesian model's strength in addressing data sparsity and underreporting. Both models consistently identified Perlis, Perak, and Johor as very high-risk states. The study concludes that the Poisson Gamma model offers superior performance in detecting spatial risk patterns of B. abortus, particularly in areas with incomplete surveillance data. However, its limitations include reduced flexibility in adjusting for covariates and spatial dependencies. These findings also highlight the importance of using advanced spatial modeling techniques in disease surveillance to inform targeted interventions, optimize resource allocation, and support evidence-based policy development for managing brucellosis and similar zoonotic diseases.
The advection-diffusion equation (ADE) is a fundamental mathematical model that is widely used to describe the transport of substances, such as the transport of pollutants in rivers, groundwater or soil. Incorporating a fractional derivative into the ADE allows for non-integer orders which have been demonstrated to capture more complex dynamics that cannot be described by classical ADE. This study investigates a two-dimensional ADE with time-fractional Caputo-Fabrizio derivative while considering a time-dependent velocity. The velocity function varies temporally, while the diffusion coefficient remains constant. By introducing appropriate transformations, the equation is reformulated and reduced to an equation with constant coefficients. Analytical solutions are obtained using the Laplace transform in time and the Fourier transform in spatial coordinates. The derived solutions encompass classical and fractional advection-diffusion processes, highlighting the impact of fractional-order derivatives. Numerical simulations illustrate the influence of time-dependent velocity on concentration profiles, providing a comparative analysis. The results show that lower fractional parameter values yield lower concentration profiles in both spatial domains, with a peak around the centerline and the source. As time increases, the fractional solutions maintain a localized concentration near the centerline and the source, while the classical solution becomes more flattened and moves further downstream. Additionally, a time-dependent velocity consistently yields higher concentration profiles than a constant velocity. These results offer valuable insights into the role of fractional calculus in modeling transport processes with evolving velocity fields, contributing to both theoretical advancements and practical applications in environmental and engineering sciences.
Ink analysis provides a crucial function in forensic document examination for authentication, forgery detection, and ink dating. Today, black gel inks are widely used in both legal and non-legal documents, however they are difficult to analyse due to their pigment formulations, which undergo subtle chemical changes during ageing. Destructive techniques such as Thin Layer Chromatography ( TLC) and High-Performance Liquid Chromatography ( HPLC) can discriminate ink but are unsuitable for evidentiary purposes. Non-destructive Attenuated Total Reflectance-Fourier Transform infrared (ATR-FTIR) spectroscopy offers an alternative, yet spectral similarities among black gel inks necessitate advanced computational models to facilitate discrimination, classification and age prediction. In this study, predictive ageing models for black gel inks was developed by integrating ATR-FTIR spectroscopy with machine learning (ML). Thirty black gel inks from 23 brands were analysed. Ink lines made using the black gel ink samples were aged for twelve months under three different environmental conditions, and their infrared (IR) spectral data were recorded monthly over the period of 12 months. For age prediction, four classifiers namely Discriminant Analysis ( DA), Support Vector Machine ( SVM), k-Nearest Neighbour (kNN), and Decision Tree(DT) were trained on full mid-IR, fingerprint region, and PCA (Principal Component Analysis)-derived datasets. Performances of the classifiers were evaluated using accuracy, precision, recall, F1-score, ROC (Receiver Operating Characteristics), and Area Under the Curve ( AUC). For age prediction, DA achieved the best accuracy (81.5%) with PCA features, outperforming SVM (76.1%), kNN (48.8%), and DT (40.2%). ROC-AUC values exceeded 90% across all classes. This study demonstrates that ATR-FTIR spectroscopy integrated with machine learning provides a reliable, non -destructive framework for black gel ink classification and age prediction, addressing limitations of destructive methods and strengthening forensic document analysis.
For more than six decades following the desiccation of the Aral Sea, soil formation processes on the exposed seabed have undergone continuous development, leading to pronounced changes in physicochemical and biological properties. This study evaluates the influence of soil salinity and physicochemical parameters on microbial communities in newly formed soils of the dried Aral Sea bed. The investigated soils exhibited moderate to high salinity (EC 6.2-8.2 mS cm(-1)) and slightly alkaline conditions (pH/H2O 7.7-8.9), with low organic carbon (0.20-0.39%) and humus contents (0.35-0.68%). Carbonate and sulfate-chloride salts predominated, while soil textures ranged from heavy to light. Microbiological analyses indicated the ubiquitous presence of ammonifying and humus-decomposing microorganisms, whereas phosphate-solubilizing and oligonitrophilic bacteria were mainly associated with moderately saline soils. Actinomycetes and micromycetes were detected only sporadically. Statistical analyses revealed a strong positive correlation between electrical conductivity and soil pH (r = 0.85, p < 0.01), while most microbial indicators showed negative relationships with salinity and alkalinity. These results demonstrate that soil salinity and pH are key environmental drivers constraining microbial diversity and activity during early soil development in arid, saline post-lacustrine ecosystems.
This study examines the biomechanical responses of the ankle, knee, and hip joints during walking on varying slopes to understand how different inclinations affect joint loading and movement mechanics. While previous research has explored slope walking, many studies lack detailed multi-plane analyses of joint moments and accelerations, limiting their applicability in rehabilitation and injury prevention. To address these gaps, we employed advanced motion capture and force plate measurements to quantify joint moments and accelerations at inclinations of 0 degrees, 5 degrees, 7.5 degrees, and 10 degrees. Our results indicate that steeper slopes significantly increase joint moments and accelerations, particularly in the knee and hip during incline walking and in the ankle during decline walking. These findings highlight the increased biomechanical demands on lower limb joints, emphasizing the need for tailored rehabilitation programs, training strategies, and ergonomic interventions. By providing a more comprehensive understanding of slope-related mechanical stresses, this study contributes valuable insights for injury prevention, rehabilitation, and performance optimization in both clinical and athletic settings. The findings suggest that to decrease the risk of falling and manage the demands of inclined walking, appropriate walking strategies and improved safety measures should be implemented, especially during decline and anterior-posterior orientations. This study also offers additional understanding of optimal incline walking techniques for secure and practical locomotion.
This paper aims to integrate the Laplace transformation method with the variational iteration method to deliver an analytical approximate solution for fractional-order integro-differential equations, where the fractional-order derivative and integration are defined in the conformable sense. The iterative solution sequence is obtained using the Laplace variational iteration method, and the convergence of this sequence of approximate solutions to the exact solution is established and demonstrated. First, we shall study the approximate solution of a linear fractional integrodifferential equation, and secondly, solve the nonlinear fractional integro-differential equations modeled using conformable differointegration. Some illustrative examples are considered to verify the validity and accuracy of the proposed technique, in which approximate solutions are compared with the exact solutions if they exist. Through the comparison, we conclude that the present hybrid approach is very effective for solving this type of problem.
Matoa leaf (Pometia pinnata J.R. Forst & G. Forst.) is one of Indonesia's endemic plants originating from Papua. Matoa leaves can be utilized as a preventive measure against stunting. Increasing the absorption of active ingredients in a preparation can be achieved by creating nanoparticles. The purpose of this study was to test the potential of matoa leaf nano-powder as an additional ingredient to prevent stunting in children. The stages of this study include the preparation of nanoparticles using the Planetary Ball Mill (PBM) method, capsule preparation formulation, determination of total phenol and flavonoid content, antioxidant activity test, antibacterial test against Escherichia coli and Staphylococcus aureus bacteria, determination of protein content, determination of carbohydrate content, determination of fat content, and determination of caloric value. Based on the results of this study, the antioxidant activity of matoa leaf nano-powder is very strong, with an IC50 value of 38.2078 +/- 0.26 & micro;g/mL, corresponding to total phenol and flavonoid levels of 232.3319 +/- 14.66 mg GAE/g sample and 4.5288 +/- 0.99 mg QE/g sample, respectively. Matoa leaf nanoparticle capsules exhibit strong antibacterial activity against Escherichia coli bacteria at a dose of 150 mg (12.61 +/- 2.07 mm), a dose of 200 mg (13.4 +/- 2.00 mm), and a dose of 250 mg (13.4 +/- 2.00 mm). For Staphylococcus aureus, the inhibition diameters obtained with doses of 150 mg, 200 mg, and 250 mg are 13.25 +/- 0.78 mm, 13.81 +/- 1.10 mm, and 14.13 +/- 1.23 mm, respectively. The results of determining the total protein content of matoa leaf nano powder in the spectrophotometric method of 0.8571% and the Kjeldahl method of 11.2%, total carbohydrate content of 0.4617%, and crude fat content of 2.6916%, with a caloric value of 294.96 kcal / kg and 708.71 kcal / kg. It is concluded that matoa leaf nano powder has the potential to prevent stunting.
The ash fouling inside the boiler has a detrimental effect on its performance, leading to suboptimal efficiency. Soot blower systems are commonly used during power plant operations to mitigate fouling. Most soot blower operations are scheduled and fixed without considering the actual degree of fouling inside the boiler, often resulting in either insufficient or excessive blowing. The former reduces heat transfer efficiency, while the latter leads to the wastage of high-pressure steam and shortens the lifespan of boiler pipes. This study aims to predict the fouling conditions of six individual heating surfaces within the boiler: primary, secondary, and final superheaters; primary and final reheaters; and the economizer, utilizing indirect and data-driven methods. Direct methods, such as sensor installation, are impractical due to the extreme conditions within the boiler. The study initially establishes the relative cleanliness level as an indicator of fouling degree by comparing current heat absorption values with reference values derived from statistical analysis during periods of stable boiler conditions. Data cleaning methods are then applied before employing regression techniques for ash fouling prediction. Gaussian Process Regression (GPR), a nonparametric kernel-based probabilistic model, and Support Vector Machine (SVM) with different kernels are experimented with for comparison. Experimental analysis demonstrates high accuracy, ranging from 91.4% to 98.2% for GPR and 89.1% to 98.1% for SVM on the case study data. The implementation of the prediction model in this study is expected to enhance soot blowing operations, ultimately optimizing boiler performance. This improvement will lead to higher energy efficiency and a reduction in detrimental emissions.
Diarrhea is a common digestive disorder characterized by frequent bowel movements and a shift in stool consistency toward a more liquid form. Amaranthus spinosus L., a plant known to contain tannins and flavonoids, is believed to have antidiarrheal potential due to its astringent properties, which may help reduce intestinal secretions. This study explored the antidiarrheal effect of the ethanolic extract of A.spinosus leaves in male mice. A total of 25 mice were divided into five groups: a negative control group receiving 0.5% CMC-Na suspension, a positive control group treated with Loperamide HCl (0.52 mg/kg BW), and three test groups receiving the A.spinosus extract at doses of 25, 50, and 100 mg/kg BW. Diarrhea was induced using castor oil (oleum ricini), and observations were made every 30 minutes over six hours, focusing on the onset of diarrhea, stool consistency, frequency of defecation, and overall duration of symptoms. The results showed that all doses of the extract had a measurable antidiarrheal effect, with higher doses producing stronger responses. Mice treated with the highest dose (100 mg/kg BW) experienced a delayed onset of diarrhea, fewer episodes, faster normalization of stool consistency, and shorter symptom duration. Statistically, the 100 mg/kg BW dose showed a significant improvement (p < 0.05) compared to the Loperamide HCl treated group in delaying diarrhea onset and reducing defecation frequency. These findings support the potential use of A.spinosus leaf extract as a natural antidiarrheal agent, which may be associated with the presence of tannins and flavonoids identified through phytochemical screening. In conclusion, the ethanolic extract of A.spinosus leaves demonstrated promising antidiarrheal activity in mice, especially at higher doses.
Present paper studies the characteristics of an upgraded fluid called Williamson ternary hybrid ferrofluid. This fluid comprises three types of nanoparticles which are magnetite, gold and aluminium oxide in a Williamson based fluid in hopes to improve the fluidity and heat transfer of based fluid. Thus, the objective of this research is to understand the capabilities of this upgraded fluid and to determine whether it performs better than the less nanoparticles hybrid fluid. The blood is taken as a based fluid to integrate the pseudoplastic behaviour of Williamson fluid. The physical model developed is interpreted into non-linear partial differential equations then transformed into ordinary differential equations using similarity transformations. Using Runge-Kutta-Fehlberg (RKF45) method, the transformed equations then coded in Maple software. Parameter used to study the behaviour of the fluid are the nanoparticles volume fraction, the magnetic parameter, the moving plate parameter and buoyancy parameter. Comparison with different types of ferroparticle volume fractions are also included in this research. In summary, the Williamson ternary hybrid ferrofluid demonstrates a 2.81% enhancement in fluidity relative to the Williamson hybrid ferrofluid, with both showing comparable heat transfer characteristics when evaluated using the same value moving plate parameter. Magnetic parameter as predicted do reduced the thermal and velocity boundary layer. Buoyancy parameter also showed similar result with magnetic parameter.
Accurate segmentation of retinal vessels is critical for the early detection of vision-threatening diseases. Although U-Net-based methods have shown strong performance, they often fail to capture thin vessels and preserve boundary details due to repeated downsampling. To overcome these limitations, we propose an enhanced U-shaped network that incorporates a multi-scale attention guided filtering module, allowing the model to retain edge details and suppress noise more effectively. Experiments conducted on the DRIVE, STARE, CHASE_DB1, and HRF datasets demonstrate that the proposed method consistently achieves the best results across multiple metrics. The improvements in F1 score and sensitivity confirm its capability to recover fine vascular structures and its potential for clinical application.
Laccase is a versatile oxidative enzyme widely applied in the degradation of various environmental pollutants. However, its practical application is often limited by poor operational stability and reusability in free form. Immobilization onto suitable support materials has therefore emerged as an effective strategy to enhance enzyme stability and performance. Among carbon-based supports, graphene and its derivatives have attracted considerable attention due to their high surface area, abundant functional groups, and excellent physicochemical properties. This study investigates the intermolecular interactions between laccase and graphene-based supports to elucidate the structural stability, flexibility, and compactness of enzyme-support complexes at the molecular level. Molecular docking and molecular dynamics (MD) simulations were employed to evaluate graphene oxide (GO) and reduced graphene oxide (rGO) as immobilization supports. Docking results revealed that the laccase-GO (Lac-GO) complex exhibited the strongest binding affinity (-14.4 kcal/mol), forming three hydrogen bonds with bond lengths of 2.03 & Aring;, 2.52 & Aring;, and 3.13 & Aring;, whereas weaker interactions were observed for laccase-rGO. MD simulations further demonstrated that free laccase exhibited the lowest root mean square deviation (RMSD), reflecting inherent structural stability, while the Lac-GO complex maintained lower RMSD values than Lac-rGO, indicating improved structural stability among immobilized systems. Root mean square fluctuation (RMSF) analysis showed moderate residue-level flexibility for Lac-GO compared to higher fluctuations in Lac-rGO, suggesting better conformational preservation upon GO binding. Additionally, the radius of gyration (Rg) analysis revealed that Lac-GO retained greater compactness than Lac-rGO while allowing slight structural expansion relative to free laccase, which may facilitate enhanced enzyme loading and reduced mass transfer limitations. Overall, the computational findings indicate that graphene oxide provides a superior immobilization platform for laccase compared to reduced graphene oxide, offering favourable interaction stability and structural characteristics.
Pomegranate peel extract (PPE) offers a rich source of natural polyphenols for cosmetic applications, yet its incorporation into stable topical formulations remains challenging due to poor bioactive stability and skin permeability. This study aimed to develop a stable water-in-oil-in-water (W/O/W) double emulsion co-loaded with PPE and hyaluronic acid (HA) using a high-energy two-step emulsification method, and to evaluate its physicochemical properties and consumer acceptability. The optimal formulation, identified through systematic screening of oil and xanthan gum concentrations, consisted of 15% grapeseed oil and 1.0% xanthan gum. Physicochemical characterization revealed that the emulsion possessed a mean droplet size of approximately 155 nm with a narrow size distribution (polydispersity index < 0.3), indicating a homogeneous system conducive to topical delivery. The formulation exhibited pseudoplastic (shear-thinning) rheological behavior, favorable for skin application, and maintained a skin-compatible pH (approximately 5.0) over 7 weeks of storage at 25 degrees C. Stability studies demonstrated that the double emulsion resisted coalescence and Ostwald ripening throughout the storage period, with conductivity measurements confirming the structural integrity of the multiple emulsion system. Sensory evaluation by untrained panelists (n = 40) using a 9-point hedonic scale showed that the formulation achieved overall acceptance comparable to that of a commercial reference product, with particular preference noted for its fragrance and spreadability. These findings establish a foundational formulation strategy for incorporating PPE and HA into a physically stable W/O/W double emulsion with acceptable sensory properties. The systematic optimization approach and demonstration of resistance to key destabilization mechanisms distinguish this work from prior studies, though further biological and efficacy testing are required to substantiate any dermatological applications.
The aim of this study is to fabricate a micro-lens for enhanced light coupling efficiency based on plasmonic effect by modifying the structure of fiber end into the micro-peanut shape using a low-cost heat-and-pull technique, coated with gold nanoparticles and platinum thin film. The fabrication process involves the usage of a Z2C core alignment fusion splicer by varying few important parameters including arc power, arc time, fiber pulling and fiber pulling length. During tapering, the fiber optics experienced structural modification from bi-tapered structure to the formation of micro-peanut fiber probe. Platinum thin film and gold nanoparticles in a form of nanospheres and nanorods are deposited onto the fiber probe to transport electromagnetic energy in micro and nanoscale with high efficiency. The transition process for forming the micro-peanut structure begins with the fabrication of a bi-tapered microfiber. This bi-tapered structure consists of two tapered regions, with tapered lengths ranging from 0.109 to 0.127 mm and taper angles between 53.68 degrees and 65.10 degrees. Subsequently, the micro-peanut probe develops a distinct peanut-like geometry, characterized by ellipsoidal sections with tip radii ranging from 0.051 to 0.080 mm. Greater nano-focusing assisted by surface plasmon polariton with maximum coupling efficiency up to 95.40% is successfully achieved by utilizing gold nanorods with a platinum-coated micro-peanut probe. The LSPR effect clearly enhances light-matter interactions, maximizing nano-focusing for light coupling and enabling optical trapping applications. This study presents a highly efficient light-coupling approach with broad potential applications, ranging from biosensing to biomedical fields.
Ground Penetrating Radar (GPR) is a geophysical method that uses electromagnetic waves to map utilities and subsurface layers. It transmits electromagnetic waves, reflects them when they contact the medium, and then records them. Peatlands have unique properties, characterized by low density due to their composition of partially decomposed organic matter and a very high water storage capacity of up to 90% of the total volume. This research aims to interpret the reflection patterns in the subsurface layer of peatland areas. This research used a Plug-in Cobra GPR SE70 system operating at 80 MHz. The research location was in Rasau Jaya Sub-district, Kubu Raya Regency, Indonesia. Data acquisition in the field applied ten tracks with lengths varying from 162 m to 287 m. The data processing consisted of several stages, namely static correction, subtract-mean (dewow), Butterworth bandpass, background removal, average subtraction, and manual gain. The results showed that the reflection patterns on the peat layer showed random/irregular diffraction and undulated (hummocky) with high amplitude. In contrast, the reflection patterns on the clay layer showed parallel to wavy patterns with low amplitude. The results also showed that the peat layer thickness at the research location ranged from 1.07 m to 2.78 m. These findings serve as an essential reference for GPR surveys using the same approach in other areas to improve carbon reserve estimates and assess hydrological risks in peatlands of Kubu Raya Regency.
