Test Methods Research Articles

Multiprobe Amplification (MPA) with Melting Curve Analysis: A Highly Stable and Cost-Effective Platform for the Simultaneous Detection of Eight Potential Bacterial Bioterrorism Agents in Complex Samples.

We aimed to develop an efficient detection platform that can identify a larger number of suspicious samples in a single test, saving time, manpower, and material costs, and providing vital support to the public health system in coping with the current challenging and dynamic bioterrorism threat landscape, particularly in regions of turmoil and conflict. We have successfully developed a high-throughput, multitarget fluorescent array detection platform by effectively combining integrating multiprobe amplification (MPA) with melting curve analysis. Specifically, we have established reliable laboratory testing methods for eight highly pathogenic bacteria, including Bacillus anthracis, Yersinia pestis, Brucella spp., Burkholderia pseudomallei, Francisella tularensis, Vibrio cholerae, Salmonella typhi, and Staphylococcus aureus. Our method achieves sensitive and specific simultaneous detection of eight target bacteria in one well by optimizing the reaction conditions of MPA. In the assessment of 192 simulated environmental samples, both positive and negative coincidence rates were 100.00%. Among 48 simulated clinical samples, the positive coincidence rate reached 97.73%, while maintaining a perfect negative coincidence rate of 100.00%. Moreover, the detection platform holds immense potential for attaining a more comprehensive bioterrorism screening, and its high cost-effectiveness enables the provision of diverse and adaptable diagnostic methods for public health quarantine in underdeveloped countries and regions.

The impact of homocysteine on patients with diabetic nephropathy: a mendelian randomization study.

Homocysteine (Hcy) has been associated with an increased risk of diabetic nephropathy (DN) in patients, but there is still controversy. This study aims to investigate the causal relationship between plasma Hcy and DN. A Mendelian randomization (MR) study using data from 2 samples was employed to infer causal relationships. The aggregated genetic data associated with Hcy was derived from the largest genome-wide association study (GWAS) to date, involving 44,147 individuals of European ancestry.Data on SNP-diabetic nephropathy, creatinine, and urea nitrogen were obtained from the IEU GWAS database. The analysis method employed a fixed-effect or random-effect inverse variance-weighted approach to estimate effects.Additional analysis methods were used to assess stability and sensitivity. The potential for pleiotropy was evaluated using the MR-Egger intercept test. Using 12 SNPs as instrumental variables, two-sample MR analysis revealed no evidence of a causal relationship between genetically predicted plasma Hcy levels and diabetic nephropathy, as well as creatinine and blood urea nitrogen levels. This finding is consistent with the results obtained from other testing methods. Two-sample Mendelian Randomization analysis found no evidence of a causal relationship between plasma homocysteine levels and diabetic nephropathy, creatinine, or urea.

StrawSnake: A Real-Time Strawberry Instance Segmentation Network Based on the Contour Learning Approach

Automated harvesting systems rely heavily on precise and real-time fruit recognition, which is essential for improving efficiency and reducing labor costs. Strawberries, due to their delicate structure and complex growing environments, present unique challenges for automated recognition systems. Current methods predominantly utilize pixel-level and box-based approaches, which are insufficient for real-time applications due to their inability to accurately pinpoint strawberry locations. To address these limitations, this study proposes StrawSnake, a contour-based detection and segmentation network tailored for strawberries. By designing a strawberry-specific octagonal contour and employing deep snake convolution (DSConv) for boundary feature extraction, StrawSnake significantly enhances recognition accuracy and speed. The Multi-scale Feature Reinforcement Block (MFRB) further strengthens the model by focusing on crucial boundary features and aggregating multi-level contour information, which improves global context comprehension. The newly developed TongStraw_DB database and the public StrawDI_Db1 database, consisting of 1080 and 3100 high-resolution strawberry images with manually segmented ground truth contours, respectively, serves as a robust foundation for training and validation. The results indicate that StrawSnake achieves real-time recognition capabilities with high accuracy, outperforming existing methods in various comparative tests. Ablation studies confirm the effectiveness of the DSConv and MFRB modules in boosting performance. StrawSnake’s integration into automated harvesting systems marks a substantial step forward in the field, promising enhanced precision and efficiency in strawberry recognition tasks. This innovation underscores the method’s potential to transform automated harvesting technologies, making them more reliable and effective for practical applications.

Investigation of the Dewatering Process with Geotextile Tubes by Sedimentation, One- and Two-Dimensional Filtration Test Methods

AbstractDewatering applications are carried out with geotextile tubes for the disposal or reuse of industrial wastes with high water content. Class F Seyitomer thermal power plant fly ash, an industrial waste, was selected in this study. Turbidity, sedimentation and filtration experiments were carried out using anionic and cationic polymers and polypropylene synthetic fiber to investigate the effect of polymers and fibers on the dewatering of fly ash. The use of polymers was determined to significantly accelerate filtration and soil sedimentation speed while leading to a slight increase in the volume of the filter cake. When effective polymer and dosage are used, slurry filtration time can be reduced up to one-eighth of the time and dewatering can be achieved much faster. The addition of synthetic fiber accelerated the sedimentation of the slurry and increased the filtration in the vertical direction, while it did not show a significant effect on the total filtration in two-dimensional filtration. In geotextile tube applications, although one-dimensional filtration experiments might give misleading results in terms of estimating the effectiveness of the polymers used in solid–liquid separation and dewatering times, the jar test, sedimentation and two-dimensional filtration experiments were determined to give compatible and more realistic results. In two-dimensional filtration experiments, approximately 75% of the filtration occurred in the radial direction and the dewatering time was approximately 21–55% of the time estimated by one-dimensional filtration experiment. Geotextile tube dewatering design can be made more predictable and cost-effective in the field by performing small-scale laboratory experiments with the two-dimensional filtration test system designed for this study and various dewatering applications.

Reviewing the progress of corrosion fatigue research on marine structures

This paper reviews the state-of-the-art progress of research into corrosion fatigue on marine structures, both theoretical and experimental. This includes corrosion fatigue life prediction models/methods, load–environment interaction/coupling test methods, accelerated corrosion methods in corrosion fatigue testing, fatigue crack measurement, and corrosion fatigue life assessment in the whole life period. To date, some theoretical models and methods for predicting the corrosion fatigue life of metallic materials or structures have been proposed and applied. Meanwhile, load–environment interaction/coupling testing on metallic material specimens has been maturely developed and widely applied. Some newly developed corrosion fatigue theoretical and experimental methods, based on data-driven machine learning and at-sea monitoring, have received preliminary application. This review of accelerated corrosion methods, fatigue crack measurement methods, and corrosion fatigue life assessment for marine structures in the whole-life period has been undertaken by extensive reference to relevant studies conducted worldwide. Challenges and recommendations for further developing and improving corrosion fatigue assessment methods and test techniques are also reported and discussed.

Lubrication performance of graphene in the sliding electrical contact interface

AbstractElectrical contact materials are increasingly widely used, but the existing electric contact lubricants still have lots of room for improvement, such as anti-wear performance and lubrication life. Due to the excellent electrical and lubrication properties, graphene shows great potential in lubricating the sliding electrical contact interface, but there is a lack of relevant research. Some researchers have studied the lubrication performance of graphene between the gold-coated/TiN-coated friction pair at an ultra-low current. However, the lubrication performance of graphene on more widely used electrical contact materials such as copper and its alloys under larger and more commonly used current or voltage conditions has not been reported. In this paper, we study the lubrication performance of graphene in the copper and its alloys sliding electrical contact interface under usual parameters, which is explored through four aspects: different substrates—copper and brass, different test methods—constant voltage and constant current, different normal loads and durability test. The experiments demonstrate that graphene can significantly reduce the friction and wear on brass and copper under the above test methods and parameters, with low contact resistance at the same time. Our work is expected to provide a new lubricant for electrical contact materials and contribute to enriching the tribological theory of graphene.

Can isometric testing substitute for the one repetition maximum squat test?

When measuring maximum strength, a high accuracy and precision is required to monitor the training adaptations. Based on available reliability parameters, the literature suggests the replacement of the one repetition maximum (1RM) by isometric testing to save testing time. However, from a statistical point of view, correlation coefficients do not provide the required information when aiming to replace one test by another. Therefore, the literature suggests the inclusion of the mean absolute error (MAE), the mean absolute percentage error (MAPE) for agreement analysis. Consequently, to check the replaceability of 1RM testing methods, the current study examined the agreement of isometric and dynamic testing methods in the squat and the isometric mid-thigh pull. While in accordance with the literature, correlations were classified high r = 0.638-0.828 and ICC = 0.630-0.828, the agreement analysis provided MAEs of 175.75-444.17 N and MAPEs of 16.16-57.71% indicating an intolerable high measurement error between isometric and dynamic testing conditions in the squat and isometric mid-thigh pull. In contrast to previous studies, using MAE, MAPE supplemented by CCC and BA analysis highlights the poor agreement between the included strength tests. The recommendation to replace 1RM testing with isometric testing routines in the squat does not provide suitable concordance and is not recommended.

Estimation of mode I fracture toughness of rocks exposed to different environmental conditions using simple and linear multiple regression

AbstractMode I fracture toughness (Kıc) is a critical parameter in rock mechanics that is essential for understanding how rocks behave under tensile loading and crucial for applications ranging from safety assessments to structural design in geotechnical engineering. This study comprehensively investigates the influence of various environmental conditions (dry, saturated, frozen, thermal shock and thermal aging) on the physico-mechanical properties and Kıc of rocks. The primary novelty of this study lies in its comprehensive modeling approach under diverse environmental conditions, providing a nuanced understanding of factors influencing rock fracture toughness. By extending analysis to less-studied conditions such as freezing and thermal shock cycles, the study enhances the predictive capacity of fracture toughness models in practical geotechnical applications. Physico-mechanical properties, including uniaxial compressive strength, point load strength, Brazilian tensile strength (BT), Schmidt hardness, and ultrasonic wave velocity were evaluated across different environmental scenarios. Simple and linear multiple regression models were developed using these properties to predict Kıc. Notably, BT emerged as a significant predictor in the simple regression analyzes. Ten linear multiple regression models were formulated using SPSS 20, combining mechanical tests (UCS, BT, PL) with non-destructive testing methods (Vp, Vs, SH), demonstrating robust predictive capabilities with R2 values exceeding 0.95. Performance metrics (mean absolute error, mean absolute percentage error, root mean square error) were used to verify the accuracy of the model.

Evaluation of the Financial Reporting System of LKM Gapoktan Tani Manunggal Temanggung using Black Box Testing

This study employs Boundary Value Analysis (BVA), a kind of Black-Box Testing, to assess the financial information system of LKM Gapoktan Tani Manunggal Temanggung. Through testing the system's performance in a variety of edge situations pertaining to user registration, login, financial data entry, balance calculation, report creation, data storage, backup, alerts, and system accessibility, the research seeks to evaluate the functionality of the system. The outcomes demonstrate how well the system manages boundary circumstances, producing precise outputs and guaranteeing dependability across various functionality and devices. The study emphasizes the system's resilience and points out areas that may benefit more development, such as enhanced security, better user experience, integration testing, and sophisticated testing methods.

Au Nanoshell-Based Lateral Flow Immunoassay for Colorimetric and Photothermal Dual-Mode Detection of Interleukin-6

Interleukin-6 (IL-6) detection and monitoring are of great significance for evaluating the progression of many diseases and their therapeutic efficacy. Lateral flow immunoassay (LFIA) is one of the most promising point-of-care testing (POCT) methods, yet suffers from low sensitivity and poor quantitative ability, which greatly limits its application in IL-6 detection. Hence, in this work, we integrated Aushell nanoparticles (NPs) as new LFIA reporters and achieved the colorimetric and photothermal dual-mode detection of IL-6. Aushell NPs were conveniently prepared using a galvanic exchange process. By controlling the shell thickness, their localized surface plasmon resonance (LSPR) peak was easily tuned to near-infrared (NIR) range, which matched well with the NIR irradiation light. Thus, the Aushell NPs were endowed with good photothermal effect. Aushell NPs were then modified with IL-6 detection antibody to construct Aushell probes. In the LFIA detection, the Aushell probes were combined with IL-6, which were further captured by the capture IL-6 antibody on the test line of the strip, forming a colored band. By observation with naked eyes, the colorimetric qualitative detection of IL-6 was achieved with limit of 5 ng/mL. By measuring the temperature rise of the test line with a portable infrared thermal camera, the photothermal quantitative detection of IL-6 was performed from 1~1000 ng/mL. The photothermal detection limit reached 0.3 ng/mL, which was reduced by nearly 20 times compared with naked-eye detection. Therefore, this Aushell-based LFIA efficiently improved the sensitivity and quantitative ability of commercial colloidal gold LFIA. Furthermore, this method showed good specificity, and kept the advantages of convenience, speed, cost-effectiveness, and portability. Therefore, this Aushell-based LFIA exhibits practical application potential in IL-6 POCT detection.

Highly visible active 2D/2D BiOBr/CO32--Bi2O2CO3 Z-scheme heterojunction for photocatalytic removal of 2-hydroxy-1, 4-naphthoquinone

Photocatalysis technology is utilized for the elimination of water pollutants due to its gentle reaction conditions, affordability, cleanliness, and high efficiency. In this study, BiOBr/CO32--Bi2O2CO3 heterojunctions consisting of BiOBr and CO32- self-doped Bi2O2CO3 components were successfully synthesized by a one-pot hydrothermal method. The photocatalysts were subjected to various testing methods for characterization of their morphology, structure, and photoelectrochemical properties. The photocatalytic efficiency of 2-hydroxy-1,4- naphthoquinone (HNQ) was assessed based on its degradation under visible light irradiation. The findings demonstrated a significant enhancement in the photocatalytic activity of the 50 % BiOBr/CO32--Bi2O2CO3 system, resulting in an impressive degradation rate of 83 % for in 90 min. In addition, the material also has good recoverability and cycle stability, after four cycles, the degradation efficiency remains at 78 %. The free radical capture experiment indicated that•O2- is the active species in the photocatalytic degradation of HNQ. A potential reaction mechanism for the photocatalytic process of the BiOBr/CO32--Bi2O2CO3 Z-scheme heterojunction has been proposed based on experiments trapping free radicals and considering the energy band structure of the catalyst. The successful construction of a heterojunction utilizes photogenerated electrons (e-) and holes (h+) in a more rational manner, which accelerates carrier transfer at the interface and improves the photocatalytic performance of the material. This study can offer a novel idea and approach for the synthesis of Bi-based Z-scheme composite photocatalysts.

How do hotels test their strategies? An approach from the strategic planning process

ABSTRACT This study examines how managers test strategies, focusing on their understanding of the strategic planning process, and aims to develop a framework for integrating cutting-edge technologies in strategy testing. We used elite interviews with top hotel managers in Turkey and a hermeneutic approach to establish this framework. Results indicate that managers have limited knowledge of strategy testing, which is not yet recognized as a distinct phase in strategy development. Scenario planning and AI-driven methods are only minimally adopted in the industry. We introduced a “techno-human” model that integrates AI and human-oriented decision-making for strategy testing. Our paper contributes significantly by analysing top managers’ use of testing methods in strategic management and highlighting an overlooked area in the literature.

AI-Driven Prediction of Compressive Strength in Self-Compacting Concrete: Enhancing Sustainability through Ultrasonic Measurements

This study investigates the application of artificial intelligence (AI) to predict the compressive strength of self-compacting concrete (SCC) through ultrasonic measurements, thereby contributing to sustainable construction practices. By leveraging advancements in computational techniques, specifically artificial neural networks (ANNs), we developed highly accurate predictive models to forecast the compressive strength of SCC based on ultrasonic pulse velocity (UPV) measurements. Our findings demonstrate a clear correlation between higher UPV readings and improved concrete quality, despite the general trend of decreased compressive strength with increased air-entraining admixture (AEA) concentrations. The ANN models show exceptional effectiveness in predicting compressive strength, with a correlation coefficient (R2) of 0.99 between predicted and actual values, providing a robust tool for optimizing SCC mix designs and ensuring quality control. This AI-driven approach enhances sustainability by improving material efficiency and significantly reducing the need for traditional destructive testing methods, thus offering a rapid, reliable, and non-destructive alternative for assessing concrete properties.

A New Approach to Prevent Injuries Related to Manual Handling of Carts: Correcting Resistive Forces between Floors and Wheels to Evaluate the Maximal Load Capacity

Test methods that use pushing forces to evaluate the maximal load capacities of carts in design standards require a flat, smooth and horizontal steel plate and thus do not take into account the real conditions of work. Resistive forces of a single wheel of a cart in a uniform rectilinear motion were measured using a unique test bench with five loads. Forty-four wheels were tested (varying diameters, treads and bearings) with one steel plate and four resilient floor coverings. Based on a linear mixed model, all the following results were significant (p < 0.05). Resistive forces were increased linearly with the load and depended on the characteristics of both the wheel and floor. These forces decreased as the diameter increased. They were important for wheels with sleeve bearings but decreased for cone ball bearings and precision ball bearings. Resistive forces depended on the material of the tread and were higher for solid rubber treads. In contrast, the hardness of the tread had little effect. Resistive forces strongly depended on the hardness of the base foam of resilient floor coverings: the softer the base foam, the higher the resistive forces. Test methods in design standards should be reviewed, using corrective forces based on these present results, to prevent musculoskeletal disorders.

Evaluation of formation mobility inversion methods for formation testing while drilling

Formation mobility is a key parameter for characterizing reservoir permeability and predicting productivity. Formation mobility can be obtained in real-time by formation testing while drilling (FTWD), which is vital for improving the efficiency of oil and gas development and reducing production costs. In terms of FTWD, adopting an appropriate formation mobility inversion method is the key to accurately obtaining the mobility of the formation. The objective of this research is to evaluate the applicability and accuracy of formation mobility inversion methods in various coupled formations. Therefore, the mobility inversion methods for FTWD were reviewed in detail. Then, the process of finite element simulation of FTWD in various coupled formations, including uncoupled, hydro-mechanical coupled, thermal-hydro coupled, and thermal-hydro-mechanical coupled, was introduced. Based on the pressure response of FTWD generated by numerical simulation, four case studies of formation mobility inversion were performed using three different inversion methods, namely pressure drawdown (PDD), area integration (AI), and formation rate analysis (FRA). Finally, an evaluation was performed to assess the applicability of the inversion methods to different coupling formations, and the suggested method for each formation was provided. The results showed that the interpreted formation mobility based on the pressure response of FTWD is the apparent mobility near the wellbore, which can be influenced by the multi-physical coupling effect. The PDD method has a good applicability to high-mobility formations, a general applicability to low-mobility formations, and a poor applicability to tight formations. Both the AI and FRA methods can be used to invert formation mobility under different coupling conditions, and the accuracy of the FRA method is generally superior to that of the AI method. If the formation is in a coupled thermal-hydro-mechanical state, it is recommended to use the AI method, PDD method, and FRA method to invert the mobility for high-mobility, low-mobility, and tight formations, respectively. The results of this paper are beneficial for the accurate interpretation of formation mobility, which can promote the development of oil and gas resources.

Current limitations and future research needs for predicting soil precompression stress: A synthesis of available data

Precompression stress, compression index, and swelling index are used for characterizing the compressive behavior of soils, and are essential soil properties for establishing decision support tools to reduce the risk of soil compaction. Because measurements are time-consuming, soil compressive properties are often derived through pedotransfer functions. This study aimed to develop a comprehensive database of soil compressive properties with additional information on basic soil properties, site characteristics, and methodological aspects sourced from peer-reviewed literature, and to develop random forest models for predicting precompression stress using various subsets of the database. Our analysis illustrates that soil compressive properties data primarily originate from a limited number of countries. There is a predominance of precompression stress data, while little data on compression index or recompression index are available. Most precompression stress data were derived from the topsoils of conventionally tilled arable fields, which is not compatible with knowledge that subsoil compaction is a serious problem. The data compilation unveiled considerable variations in soil compression test procedures and methods for calculating precompression stress across different studies, and a concentration of data at soil moisture conditions at or above field capacity. The random forest models exhibited unsatisfactory predictive performance although they performed better than previously developed models. Models showed slight improvement in predictive power when the underlying data were restricted to a specific precompression stress calculation method. Although our database offers broader coverage of precompression stress data than previous studies, the lack of standardization in methodological procedures complicates the development of predictive models based on combined datasets. Methodological standardization and/or functions to translate results between methodologies are needed to ensure consistency and enable data comparison, to develop robust models for precompression stress predictions. Moreover, data across a wider range of soil moisture conditions are needed to characterize soil mechanical properties as a function of soil moisture, similar to soil hydraulic functions, and to develop models to predict the parameters of such soil mechanical functions.

Emphasis on the importance of comprehensive clinical and genetic analysis - spinal muscular atrophy combined with phenylketonuria: A case report.

Both spinal muscular atrophy (SMA) and Phenylketonuria (PKU) are caused by biallelic pathogenic mutations. However, there has been no report on case who suffering from both diseases simultaneously. SMA mainly affects the motor function while PKU may have an impact on both the intelligence and motor function. But if only 1 disease is treated while neglecting the other, the treatment effect will be compromised. Here, for the first time, we report a case from China diagnosed with both these diseases and treated properly. A boy was admitted to the Children's Hospital Affiliated to Shandong University (Jinan, China) due to "limb weakness for 19 months" when he was 22 months old. Considering that the child's motor function development is delayed, we made a comprehensive examinations including inherited metabolic diseases and found a significantly increase of phenylalanine concentration in the blood which indicating PKU. Combined with his typical clinical manifestations of SMA, target capture sequencing followed by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA) technologies were used for genetic confirmation. SMA and PKU was confirmed. The child was treated with risdiplam and low phenylalanine formula immediately when he was diagnosed with both SMA and PKU. The child showed remarkable improvement in motor function and significant decrease of blood phenylalanine concentration after treatment. To our knowledge, this is the first reported case of SMA combined with PKU. This case expands our understanding of diagnosis for synchronous SMA and PKU and highlights the importance of comprehensive examinations and the utilizing of various genetic testing methods to make an accurate diagnosis of genetic diseases, which may help avoiding the progressive damage caused by certain genetic disease with insidious clinical symptoms.

The dimer effect: A refinement approach towards skin sensitization assessment in-chemico using Amino acid Derivative Reactivity Assay.

Skin sensitization is a key endpoint for safety assessment, especially for cosmetics and personal care products. The adverse outcome pathway for skin sensitization and the chemical and biological events driving the induction of human skin sensitization are now well understood. Several non-animal test methods have been developed to predict sensitizer potential by measuring the impact of chemical sensitizers on these key events. In this work, we have focused on Key Event 1 (the molecular initiating step), which is based on formation of a covalent adduct between skin sensitizers and endogenous proteins and/or peptides in the skin. There exists three in-chemico assays approved by the Organization for Economic Co-operation and Development-(1) Direct Peptide Reactivity Assay (DPRA), (2) Amino Acid Derivative Reactivity Assay (ADRA), and (3) Kinetic Direct Peptide Reactivity Assay (kDPRA) to quantify peptide/amino acid derivative depletion after incubation with test chemicals. However, overestimated depletion of the cysteine-based peptide/amino acid derivatives is known in such assays because of the dimerization of the thiol group. In this present work, we report the synthesis and structural confirmation of the dimer of N-(2-[1-naphthyl]acetyl)-L-cysteine (NAC) from the ADRA assay to allow simultaneous determination of (a) peptide depletion by quantifying NAC monomer and (b) peptide dimerization by quantifying NAC dimer thereby eliminating the overestimation. We present a case study with three chemicals to demonstrate the importance of this approach. Thus, this simultaneous assay gives a more informed view of the peptide reactivity of chemicals to better identify skin sensitizers.

Printed circuit board and printed circuit board assembly methods for testing and visual inspection: a review

Testing and visual inspection of printed circuit boards (PCBs) and printed circuit board assemblies (PCBAs) are important procedures in the manufacturing process of electronic modules and devices related to locating and identifying possible defects and failures. Earlier defects detection leads to decreasing expenses, time and used resources to produce high quality electronics. In this paper an exploration and analysis about the current research regarding methods for PCB and PCBA testing, techniques for defects detection and vusial inspection is performed. The impact of machine and deep learning for testing and visual inspection procedures is also investigated. The used methodology comprises bibliometric approach and content analysis of papers, indexed in scientific database Scopus, considering the queries: “PCB and testing” and “PCB and testing”, “printed circuit board assembly and testing” and “PCBA and testing”, “PCB defect detection” and “PCBA defect detection”, “PCB and visual inspection”, and “PCBA and visual inspection”. The findings are presented in the form of a framework, which summarizes the contemporary landscape of methods for PCBs and PCBAs testing and visual inspection.

A practical clinical device for evaluating changes to the skin's sebum from ozone.

It is known that tropospheric ozone (O3) generated from pollutants reacting with UV forms lipid peroxidation products and induces oxidative stress to the skin. With the ever-increasing consumer awareness of the effects pollution has on skin, more testing methods will be needed to evaluate cosmetic ingredients. Recently, others have shown how antioxidants are able to reduce the effects from ozone on skin through in vitro, ex vivo and clinical studies where human subjects place their arms into large stationary chambers. To develop a small, easy to use ozone exposure module (OEM) that can be used on various sites of the body and to validate this device for use in testing the ability of topical products to mitigate the effects of ozone exposure on the skin. We have produced an OEM which can generate levels of ozone in excess of 1000 ppb and can be set to achieve the equivalent exposure to what is found in polluted environmental conditions. After exposure we used D-squame discs to remove the sebum and analytically quantitate squalene depletion. Squalene, which is very sensitive to ROS, easily oxidizes into early metabolite squalene monohydroperoxide (SQOOH) with ozone exposure. We were able to show decreases in squalene levels after exposure and protective effects from a topical formulation. This generator will be a useful tool for researchers to easily create a small and safe exposure from ozone for clinical testing.