Prominent Parameter Research Articles

Accounting for the mechanical response of the cell membrane during the uptake of random nanoparticles

In order to improve the efficiency of the delivery of cancer treatments to cancer cells, the cellular uptake of nanoparticles (NPs), used as drug delivery systems, is numerically investigated through a mechanical approach. The objective is to optimize the NP's mechanical and geometrical properties to enhance their entry into cancer cells while avoiding benign ones. In previous studies, these properties are modeled as constant during the process of cellular uptake. However, recent observations of the displacement of the membrane's constituents towards the region in the cell membrane where the uptake of the NPs takes place show that the mechanical properties of the membrane vary during this process. Reason for writing The important contribution of adhesion to the wrapping process is already well documented in literature. It is therefore crucial to model this parameter properly as the conclusions made with a constant adhesion model may not be accurate compared to reality. Methodology Based on the existing knowledge on the reaction of membrane constituents to interaction with NPs, a 3-parameter sigmoidal function, accounting for the delay, amplitude, and speed of the reaction, has been used to model the evolution of adhesion. A variance-based sensitivity analysis has then been performed in order to quantify the influence of these parameters on the outputs of the model. Results It was found that the introduction of a variable adhesion tends to alter the predictions of endocytosis of NPs. The contribution of the amplitude and delay is respectively 0.32 and 0.43 times as important as that of the NP's aspect ratio, which is the prominent parameter. The influence of the slope of the transition is the least important parameter and does not appear to contribute to endocytosis. Implications Hence, models of the cellular uptake of NPs should use a variable, instead of constant, adhesion in order a representative as possible of the behavior of the cell membrane. The predictions are different from those obtained using a model with constant adhesion.

New metabolites of 2-ethylhexyl salicylate in human urine after simulated real-life dermal sunscreen application

2-Ethylhexyl salicylate (EHS) is an organic UV filter which is used in sunscreen and other personal care products. The dermal uptake of EHS was studied in several dermal-exposure experiments. This paper aims to coherently assess urine samples after dermal exposure for the biomarkers EHS, 5OH-EHS, 5oxo-EHS, and 5cx-EPS as well as further biomarkers of interest, specifically 4OH-EHS, 4oxo-EHS, 2OH-EHS, and 6OH-EHS, for the first time. Samples from 18 participants of a pre-existing dermal exposure study under real-life conditions were reassessed using a comprehensive LC-MS/MS method. EHS accounts for 34 % of the cumulative excretion of all analytes within 24 h after exposure, followed by 5OH-EHS (19 %), 5cx-EPS (18 %), 4OH-EHS (15 %) and 5oxo-EHS (11 %). Further metabolites were only quantified in minor amounts. EHS as the most prominent excretion parameter in this study demonstrates the missing first-pass effect after dermal absorption. Furthermore, the applied novel comprehensive analytical procedure revealed oxidation at the ω (5cx-EPS, 6OH-EHS), ω-1 (5OH-EHS, 5oxo-EHS), and ω-2 positions (4OH-EHS, 4oxo-EHS) in the main chain of the ethylhexyl group as well as oxidation in the side chain (2OH-EHS). The presented data are of high relevance for a reliable toxicological risk assessment of dermal exposure to EHS.

Effect of seawater salinity, pH, and temperature on external corrosion behavior and microhardness of offshore oil and gas pipeline: RSM modelling and optimization

This research aims to investigate the effects of seawater parameters like salinity, pH, and temperature on the external corrosion behaviour and microhardness of offshore oil and gas carbon steel pipes. The immersion tests were performed for 28 days following ASTM G-1 standards, simulating controlled artificial marine environments with varying pH levels, salinities, and temperatures. Besides, Field emission scanning electron microscopy (FESEM) analysis is performed to study the corrosion morphology. Additionally, a Vickers microhardness tester was used for microhardness analysis. The results revealed that an increase in salinity from 33.18 to 61.10 ppt can reduce the corrosion rate by 28%. In contrast, variations in seawater pH have a significant effect on corrosion rate, with a pH decrease from 8.50 to 7 causing a 42.54% increase in corrosion rate. However, the temperature of seawater was found to be the most prominent parameter, resulting in a 76.13% increase in corrosion rate and a 10.99% reduction in the microhardness of offshore pipelines. Moreover, the response surface methodology (RSM) modelling is used to determine the optimal seawater parameters for carbon steel pipes. Furthermore, the desirability factor for these parameters was 0.999, and the experimental validation displays a good agreement with predicted model values, with around 4.65% error for corrosion rate and 1.36% error for microhardness.

Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks.

Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pressure, heart rate, and heart rate variability. Various physiological signals, such as photoplethysmogram (PPG) signals, are used to extract respiratory information. RR is also estimated by detecting peak patterns and cycles in the signals through signal processing and deep-learning approaches. In this study, we propose an end-to-end RR estimation approach based on a third-generation artificial neural network model-spiking neural network. The proposed model employs PPG segments as inputs, and directly converts them into sequential spike events. This design aims to reduce information loss during the conversion of the input data into spike events. In addition, we use feedback-based integrate-and-fire neurons as the activation functions, which effectively transmit temporal information. The network is evaluated using the BIDMC respiratory dataset with three different window sizes (16, 32, and 64 s). The proposed model achieves mean absolute errors of 1.37 ± 0.04, 1.23 ± 0.03, and 1.15 ± 0.07 for the 16, 32, and 64 s window sizes, respectively. Furthermore, it demonstrates superior energy efficiency compared with other deep learning models. This study demonstrates the potential of the spiking neural networks for RR monitoring, offering a novel approach for RR estimation from the PPG signal.

Advances in medical data modeling: A new logarithmic beta generated family of distributions with theory and inference

This paper introduces a novel logarithmic beta generated family of distributions, designed specifically for the nuanced analysis of medical data. Through meticulous development, we have establish a comprehensive suite of distributional properties, including quantiles, moments, and hazard rate functions. Central to our contributions is the exploration of the power function distribution, a pivotal sub-model within this innovative family, demonstrating unparalleled flexibility across a broad spectrum of data types. Our investigation delves into seven prominent parameter estimation techniques, rigorously assessing their efficacy through both simulation studies and real-life medical datasets. This comparative analysis highlights the superior performance of the proposed model against existing standards, particularly through improved goodness-of-fit measures across four distinct medical science lifetime datasets. The findings highlight the new model's dominance in capturing complex data patterns, attributable to its adaptable density and hazard rate functions. These attributes significantly enhance modeling capabilities, paving the way for more precise and reliable medical research outcomes. The study concludes by emphasizing the model's potential in advancing statistical methodologies for medical science, backed by theoretical and empirical validations of its superior performance and versatility.

Parametric investigation of thermal additive centrifugal abrasive flow machining process for enhancing productivity

Thermal additive centrifugal abrasive flow machining hybrid of abrasive flow machining caters to low material removal issues which enhances the acceptability of the process. The present investigation investigates the different centrifugal force-generating electrode geometry performances in the thermal additive centrifugal abrasive flow machining process. The L27 orthogonal array is used for optimizing the process parameters (electrode type, current supply, and the duty cycle) and their effect on material removal and percentage improvement in surface finish (%Δ Ra) are analyzed. Based on the percentage contribution obtained from Taguchi analysis, electrode type is the prominent parameter for material removal (88.27%) and %Δ Ra (78.54%) followed by current (7.43% for material removal and 13.92% for %Δ Ra) and duty cycle (3.95% for material removal and 6.42% for %Δ Ra). The spline electrode with a curved blade is found optimum with 10 A current and 0.76 duty cycle. The average experimental value based on the design of the experiment and the predicted value for material removal is 10.373 and 10.881 mg, respectively. The average experimental value and the predicted value for percentage improvement in the surface are 42.24% and 43.71%, respectively. The percentage error between the predicted and experimental values for material removal and %Δ Ra is 4.66% and 3.15%, respectively.

Investigation of leaching of nickel sulfide flotation tailings to recover valuable metals

The global transition towards renewable energy, driven by low-carbon theories and technologies, has resulted in an increasing surge in the demand for critical and unique elements, of which nickel (Ni) and copper (Cu) are encompassed. In this investigation, using acid leaching, the recovery of such elements from polymetallic tailings to supplement conventional extraction processes was studied. The effective leaching parameters were investigated and optimized to enhance the simultaneous recovery of Ni, Cu, cobalt (Co), chromium (Cr), and manganese (Mn) from the tailings sample. To this end, the response surface methodology (RSM) was employed, with sulfuric acid (H2SO4) concentration (0–20 g/L), ethylenediaminetetraacetic acid (EDTA) concentration (0–20 g/L), ferric chloride (FeCl3) concentration (0–20 g/L), leaching temperature (20–80 °C), and leaching time (4–12 h) as independent variables. The analysis of variance depicted that ferric chloride concentration was the most prominent process parameter for the recovery of Ni, Cu, Co, and Mn. The recovery of Cr was contingent to leaching temperature and sulfuric acid addition. Ensuing tests under the optimal conditions resulted in the recovery of 100.0 % Cu, 89.8 % Co, 42.1 % Cr, and 100.0 % Mn in addition to 93.7 % Ni. The kinetics was also studied using the shrinking-core model. Kinetic data indicates that the dissolution of Ni, Cu, Co, and Cr is governed by the chemically controlled model, while that of Mn by the diffusion control model. The activation energies as per the Arrhenius equation are estimated as 32.43, 36.78, 34.88, 24.02, and 29.18 kJ/mol for Ni, Cu, Co, Cr and Mn.

Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e., PM2.5, PM10, SO2, NO2, and O3 over four different sampling stations of Delhi-NCR region (Dwarka, Knowledge park III, Sector 125, and Vivek Vihar), India, by using satellite remote sensing data (MERRA-2, OMI, and Aura Satellite) and different ground-based instruments. The ground-based observation revealed the mean concentration of PM2.5 in Dwarka, Knowledge park III, Sector 125, and Vivek Vihar as 279 µg m-3, 274 µg m-3, 294 µg m-3, and 365 µg m-3, respectively. The ground-based instrumental concentration of PM2.5 was greater than that of satellite observations, while as for SO2 and NO2, the mean concentration of satellite-based monitoring was higher as compared to other contaminants. Negative and positive correlations were observed among particulate matter, trace gases, and various meteorological parameters. The wind direction proved to be one of the prominent parameter to alter the variation of these pollutants. The current study provides a perception into an observable behavior of particulate matter, trace gases, their variation with meteorological parameters, their health hazards, and the gap between the measurements of satellite remote sensing and ground-based measurements.

Optimization and modelling of WCEDM process parameters for GZR-AA7475 HMMC using GRA and Taguchi approach

Purpose This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite. Design/methodology/approach To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (Ip), pulse-on-time (TON) and flushing pressure (PF) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses. Findings Results from the current study concluded that the optimal condition for grey relational grade is obtained at TON = 105 µs, Ip = 100 A and PF = 90 kg/cm2. Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure. Originality/value Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

Assessing the key parameters for efficient sensitized infrared emission from erbium-doped SnO2 films

Erbium-doped SnO2 films (Er:SnO2) combine the properties of Er3+ and SnO2, providing an avenue for developing unique luminophores with sensitized infrared emission. In such a system, Er3+ luminescence evolves over doping-concentration and thermal-treatment shifts, where low-temperature-annealed or highly-doped Er:SnO2 exhibits degraded emission. To fully exploit the potential of Er:SnO2, a deep understanding of the underlying physical process is required. This paper discusses the parameters determining the intensity of sensitized Er3+ emission and their evolution with doping concentration and thermal treatment. The observation of temperature-independent decay of Er3+ luminescence excludes the nonradiative interaction of the Er3+4I13/2 → 4I15/2 transition with defects in SnO2. Moreover, despite the loss of Er3+ optical activity observed in highly-doped or low-temperature-annealed samples, the sensitized emission intensity doesn't scale linearly with it. Instead, the most prominent parameter determining the sensitized emission intensity is found to be the energy transfer efficiency from SnO2 to Er3+, which highly depends on the crystallinity of SnO2. The presence of defects in low-crystallinity SnO2, that is, highly-doped or low-temperature-annealed ones, would deteriorate the energy transfer efficiency, which could be healed by high-temperature annealing. This work negates the traditional consensus of concentration quenching in Er:SnO2 and provides an important insight into developing efficient Er:SnO2 based infrared luminophores.

Performance evaluation of proactive, reactive, and hybrid routing protocols for small, medium, and large mobile ad hoc networks

The popularity of wireless ad hoc networks is increasing daily. Examples of such networks are MANETs, VANETs, and Sensor networks. These types of wireless networks are dynamic and have different working features in common, and it is not always obvious to know which network type should be used given the needs of users. Determining the best protocols for a particular sort of wireless network’s problems is frequently another challenge. We evaluate the above-mentioned networks to fill this gap and ultimately demonstrate that MANET is the best option since it can be easily deployed anywhere, at any time, to meet the needs of the majority of users. For evaluation purposes, we used prominent network evaluation parameter metrics, i.e., End-to-end Delay, Network Throughput, and Packet delivery ratio. We compare three different MANET routing protocol types—PROACTIVE, REACTIVE, and HYBRID—one from each type; DSDV [Proactive], TORA [Hybrid], and AODV [Reactive]. The simulations and their results for both small and large systems were done on the OPNET simulator. According to MANET, DSDV outperforms other protocols in networks with high node densities in terms of the same metrics, while TORA performs better in networks with low node densities in terms of packet delivery ratio, end-to-end delay, and throughput.

Two Difficult Pandemics: Tuberculosis and COVID-19.

The coinfection of Mycobacterium tuberculosis and SARS-CoV-2 is called tuberculosis and COVID-19 coinfection (TB-COVID-19). We aimed to share the clinical, radiological, and laboratory findings and treatment processes of our patients with TB-COVID-19 coinfection in our tertiary reference hospital. Patients aged 18 years and over and hospitalized in the tuberculosis service between March 2020 and September 2022 were included. All coinfected patients whose COVID-19 polymerase chain reaction results were positive while receiving tuberculosis treatment or who were diagnosed with tuberculosis while receiving treatment for COVID-19 were included. The number of patients was 39; 61.6% of males; the mean age was 52 ± 17.1 years; 20% were foreign nationals; 92.5% were Asian; 69.5% had a bacteriological diagnosis; 84.6% had pulmonary tuberculosis; 10% had received antituberculosis treatment before; and 87.5% were sensitive to the first-line antituberculosis drugs. The most common comorbidities were diabetes and hypertension. 87.5% of the patients were diagnosed with tuberculosis and were superinfected with COVID-19 while receiving tuberculosis treatment. 49.5% of patients had received at least one dose of COVID-19 vaccine. The most common presenting symptom was cough and sputum; the prominent laboratory parameter was C-reactive protein increase, and thorax computed tomography finding was consolidation, tree-in-bud, and cavitation. While 45.9% of the patients were still under treatment, 1 (2.5%) patient also resulted in mortality. In this study, attention was drawn to two infectious diseases seen with respiratory tract symptoms. The mortality rate was found to be low. Neither disease was found to be a factor aggravating the course of each other.

The influence of musical parameters and subjective musical ratings on perceptions of culture

Recent research suggests that music can affect evaluations of other groups and cultures. However, little is known about the objective and subjective musical parameters that influence these evaluations. We aimed to fill this gap through two studies. Study 1 collected responses from 52 American participants who listened to 30 folk-song melodies from different parts of the world. Linear mixed-effects models tested the influence of objective and subjective musical parameters of these melodies on evaluations of the cultures from which they originated. Musical parameters consistently predicted cultural evaluations. The most prominent musical parameter was musical velocity, a measure of number of pitch onsets, predicting more cultural warmth, competence and evolvedness and less cultural threat. Next, with a sample of 212 American participants, Study 2 used a within-subjects experiment to alter the tempo and dissonance for a subset of six melody excerpts from Study 1, testing for causal effects. Linear mixed-effects models revealed that both dissonance and slow tempo predicted more negative cultural evaluations. Together, both studies demonstrate how musical parameters can influence cultural perceptions. Avenues for future research are discussed.

Brain blood flow pulse analysis may help to recognize individuals who suffer from hydrocephalus

BackgroundNormal pressure hydrocephalus (NPH) is often associated with altered cerebral blood flow. Recent research with the use of the ultrasonic method suggests specific changes in the shape of cardiac-related cerebral arterial blood volume (CaBV) pulses in NPH patients. Our study aims to provide a quantitative analysis of the shape of CaBV pulses, estimated based on transcranial Doppler ultrasonography (TCD) in NPH patients and healthy individuals.MethodsThe CaBV pulses were estimated using TCD cerebral blood flow velocity signals recorded from probable NPH adults and age-matched healthy individuals at rest. The shape of the CaBV pulses was compared to a triangular shape with 27 similarity parameters calculated for every reliable CaBV pulse and compared between patients and volunteers. The diagnostic accuracy of the most prominent parameter for NPH classification was evaluated using the area under the receiver operating characteristic curve (AUC).ResultsThe similarity parameters were calculated for 31 probable NPH patients (age: 59 years (IQR: 47, 67 years), 14 females) and 23 healthy volunteers (age: 54 years (IQR: 43, 61 years), 18 females). Eighteen of 27 parameters were different between healthy individuals and NPH patients (p < 0.05). The most prominent differences were found for the ascending slope of the CaBV pulse with the AUC equal to 0.87 (95% confidence interval: 0.77, 0.97, p < 0.001).ConclusionsThe findings suggest that in NPH, the ascending slope of the CaBV pulse had a slower rise, was more like a straight line, and generally was less convex than in volunteers. Prospective research is required to verify the clinical utility of these findings.

Impact of Nonthermal Plasma on Lipid Oxidation from the Perspective of Plasma Treatment Parameters and Plasma Species: Identification of Key Reactive Species.

Nonthermal plasma is a mild processing technology for food preservation. Its impact on lipid oxidation was investigated in this study. Stripped methylesters were considered as a basic lipid model system and were treated by a multihollow surface dielectric barrier discharge. In dry air plasma, O3, ·NO2, ·NO3, and 1O2 were identified as the main reactive species reaching the sample surface. Treatment time was the most prominent parameter affecting lipid oxidation, followed by the (specific) power input and the plasma-sample distance. In humid air plasma, less O3 was detected, but ONOOH and O2NOOH were generated and presumed to play a role in lipid oxidation. Ozone mainly resulted in the formation of carbonyl substances via the trioxolane pathway, while reactive nitrogen species (i.e., ·NO2, ·NO3, ONOOH, and O2NOOH) led to the formation of hydroperoxides. The impact of short-living radicals (e.g., ·O, ·N, ·OH, and ·OOH) was restricted in general, since they dissipated too fast to reach the sample.·NO, HNO3, H2O2, and UV radiation did not induce lipid oxidation. All the reactive species identified in this study were associated with the presence of O2 in the input gas.

A novel sintering method of Al2O3/SiCw ceramic composites with improved wear resistance: Oscillatory pressure‐assisted sinter forging

As a typical ceramic tool, the wear resistance of Al2O3/SiCw composites is a prominent parameter in engineering applications. Therefore, how to improve its wear resistance has becomes a research emphasis of ceramic tools. In this work, the Al2O3/SiCw composites with improved wear resistance were prepared by a novel oscillatory pressure-assisted sinter forging (OPSF) process. The composites prepared by OPSF process not only exhibit higher density and significantly improved mechanical properties, but also own lower coefficient of friction than conventional sinter forging and hot oscillatory pressing processes. EBSD results indicated that the OPSF process could improve the texture of (0001) crystal face, low-angle grain boundaries, high-angle grain boundaries with special angles in the Al2O3 matrix and enhance shear deformation at micro-scales, which are multiple contributed to enhanced wear resistance. Therefore, OPSF process is a promising technique to prepare ceramic-based cutting tools with excellent mechanical properties and wear resistance.

Use of chip seal treatments to mitigate pavement roughness progression in cold regions

ABSTRACT Chip Seals are a type of pavement preservation treatment characterised by its ability to reduce pavement deterioration and restore surface condition. Chip seal performance, like other pavement preservation treatments, depends on several factors such as environmental conditions, traffic level and the condition of the existing pavement structure prior to treatment application. In cold regions, the presence of freeze and thaw cycles promotes the generation of thermal cracks and possible tenting distresses, consequently, pavement roughness has been a prominent parameter to assess treatment performance. The objective of this study was to evaluate the roughness progression on several chip seal configurations in a cold climate region, utilising a set of field performance data from the Pavement Preservation Group Study, a broader research study conducted by the National Center for Asphalt Technology and the Minnesota Department of Transportation’s Road Research Facility. The main findings indicate that chip seals provide a negligible effect on immediate roughness improvement; however, on a long-term basis, they provide a reduction in IRI progression over time. The magnitude of the IRI benefit is dependent on the type of chip seal implemented and the traffic level experienced.

A Structural Complexity Analysis of Synchronous Dynamical Systems

Synchronous dynamical systems are well-established models that have been used to capture a range of phenomena in networks, including opinion diffusion, spread of disease and product adoption. We study the three most notable problems in synchronous dynamical systems: whether the system will transition to a target configuration from a starting configuration, whether the system will reach convergence from a starting configuration, and whether the system is guaranteed to converge from every possible starting configuration. While all three problems were known to be intractable in the classical sense, we initiate the study of their exact boundaries of tractability from the perspective of structural parameters of the network by making use of the more fine-grained parameterized complexity paradigm. As our first result, we consider treewidth - as the most prominent and ubiquitous structural parameter - and show that all three problems remain intractable even on instances of constant treewidth. We complement this negative finding with fixed-parameter algorithms for the former two problems parameterized by treedepth, a well-studied restriction of treewidth. While it is possible to rule out a similar algorithm for convergence guarantee under treedepth, we conclude with a fixed-parameter algorithm for this last problem when parameterized by treedepth and the maximum in-degree.

Additive manufacturing of metal-polymer hybrid parts: the influence of as-printed LPBF surface roughness on the joint strength

As-printed Laser-Powder Bed Fusion (LPBF) surfaces can provide anchoring spots for the infiltration of polymer printed by Fused Filament Fabrication (FFF), enhancing metal-polymer joint strength. This work evaluates the influence of the as-printed LPBF surface roughness and FFF parameters on the strength of Ti-6Al-4V/PA-CF joints produced by this process combination. A three-point bending testing method based on ISO 14679:1997 was deployed, whereby the energy dissipated by the joint interface was measured. Roughness was varied by 3D-printing the substrate with different inclination angles; Height and printing speed of the coating layer (the polymer layer in direct contact with the metal) were also varied. Data was interpreted using a combination between Decision Tree and Gradient Boosting Regression, ultimately suggesting that printing speed is the prominent parameter followed by inclination angle for joint strength. Additionally, the combined effect of low printing speed and inclination angle resulted in the highest energy absorption at the interface (&amp;gt;200 J).

Makine Öğrenimi Yoluyla Bölgesel Arı Sütü Farklarının Arkasındaki Kimyasal Faktörleri Keşfetmek

This study aims to discover the characteristic chemical factors for determining the region of royal jelly using machine learning. 84 samples from 13 different regions of Turkey were used for the study, and the chemical parameters of moisture, pH, acidity, and 10-hydroxy-2-decanoic acid (10-HDA) were investigated. ANOVA test was conducted to determine whether there are differences between royal jelly from 13 locations concerning the four chemical values. In addition to the statistical tests, a machine learning model was used to find out what makes royal jelly different from each other. The descriptive statistics of the chemical analysis results of royal jelly showed the following values: moisture 63.05%±2.99, pH 3.67±0.08, acidity 45.32±3.55, and 10-HDA 2.40±0.24. Surprisingly, the machine learning model suggests that 10-HDA may be the most prominent parameter for determining the region of royal jelly. This information will help us identify royal jelly’s authenticity more easily.