Test Conditions Research Articles

Development of a dissolution method for analyzing the elemental composition of fuel debris using sodium peroxide fusion technique

ABSTRACT A dissolution method for analyzing the elemental composition of fuel debris using the sodium peroxide (Na2O2) fusion technique has been developed. Herein, two different types of simulated fuel debris (such as solid solution of (Zr,RE)O2 and molten core – concrete interaction products (MCCI)) were taken. At various temperatures, these debris samples were subsequently fused with Na2O2 in crucibles, which are made of different materials (Ni, Al2O3, Fe, and Zr). Then, the fused samples are dissolved in nitric acid. Effects of the experimental conditions on the elemental composition analysis were evaluated using inductively coupled plasma-atomic emission spectroscopy (ICP – AES), which suggested the use of a Ni crucible at 923 K as an optimum testing condition. The optimum testing condition was then applied to the demonstration tests with Three Mile Island unit-2 (TMI-2) debris in a shielded concrete cell, thereby achieving complete dissolution of the debris. The elemental composition of TMI-2 debris revealed by the proposed dissolution method has good reproducibility and has an insignificant contradiction in the mass balance of the sample. Therefore, this newly developed dissolution method can be effectively utilized in practical applications by dissolving fuel debris and analyzing its elemental composition.

Fertilizer application parameters for drip-irrigated peanut based on the fertilizer effect function established from a "3414" field trial.

Scientific fertilization is an important technical means of achieving high and stable peanut yields. Using soil testing and formula fertilization, the "3414" optimal regression design was used and included 14 nitrogen (N), phosphorus (P), and potassium (K) fertilization treatments. Ternary quadratic functions of the fertilizer effect were established according to three-season field experiments and the regression analysis of fertilizer-yield function was performed to explore the optimal fertilizer application mode and ratio for peanuts under mulched drip irrigation (MDI), and a suitable fertilizer application system was established. The ternary quadratic equation relating peanut yield (y) and the fertilizer application rates of N (N), P (P2O5), and K (K2O) was obtained after fitting, i.e., y = 2912.528 + 21.432N + 16.324P + 6.181K - 0.051N2 - 0.109P2 - 0.061K2 + 0.017NP + 0.023NK + 0.086PK, and significance analysis and typicality assessment were performed. The model R 2 was 0.9709, both values are extremely significant (p < 0.01), which indicates that the obtained ternary quadratic fertilizer effect function is typical and could be used for statistical purposes and fertilization recommendations. Three quadratic fertilizer effect functions were obtained. Among them, the equation for K is extremely significant, and the equations of N and P are significant. According to the assumption that the marginal yield is zero and the marginal profit is zero, the fertilizer application rate with the maximum yield, the fertilizer application rate with the best economic benefits, and the corresponding yields were obtained. The optimal fertilizer application rate predicted by the ternary quadratic fertilizer effect function was relatively high, so the three quadratic fertilizer effect functions were used for prediction. Under the test conditions, the recommended fertilizer application rates for peanuts under MDI are 256.6 kg N per ha, 164.2 kg P2O5 per ha, and 213.2 kg K2O per ha, the recommended fertilization ratio is 1:0.64:0.83, and the recommended ratio under formula fertilization is 23:15:19. The study has developed a data-based decision support system for Xinjiang drip-irrigated peanut, which assists farmers and agricultural managers in making more scientific and precise fertilization decisions based on the specific growth requirements of the crops and soil conditions. This evidence-based methodology enhances the precision of agricultural management, which is conducive to increasing crop yields while reducing resource wastage and environmental impact. However, multipoint and multiyear experiments are still needed to ensure that the findings are adaptable to the diverse soil conditions and fluctuating climate patterns that may be encountered in practice.

Usability Evaluation Ecological Validity: Is More Always Better?

Background: The ecological validity associated with usability testing of health information technologies (HITs) can affect test results and the predictability of real-world performance. It is, therefore, necessary to identify conditions with the greatest effect on validity. Method: We conducted a comparative analysis of two usability testing conditions. We tested a HIT designed for anesthesiologists to detect pain signals and compared two fidelity levels of ecological validity. We measured the difference in the number and type of use errors identified between high and low-fidelity experimental conditions. Results: We identified the same error types in both test conditions, although the number of errors varied as a function of the condition. The difference in total error counts was relatively modest and not consistent across levels of severity. Conclusions: Increasing ecological validity does not invariably increase the ability to detect use errors. Our findings suggest that low-fidelity tests are an efficient way to identify and mitigate usability issues affecting ease of use, effectiveness, and safety. We believe early low-fidelity testing is an efficient but underused way to maximize the value of usability testing.

Development of an experimental technique to determine the barrier performance of medical gloves when stretched.

Protective clothing standards, such as test methods published by ASTM International, play an integral role in ensuring the performance of personal protective equipment. The standard tests are not without limitations and are periodically reviewed and often updated. Some tests may not be reflective of in-use conditions. A new test cell was designed using sanitary fixtures to evaluate the effect of glove stretch on barrier performance using fluorescein solution as the challenge agent for enhanced visualization and fluorometer detection. Domed-shaped and flat screens were developed to permit and limit glove stretch within the test cell. The barrier performance of glove swatches was evaluated for both stretched and unstretched states. Latex, nitrile, and vinyl glove models of various thicknesses were evaluated. The tests were conducted following pressure and time parameters specified in ASTM F903, ASTM F1670, and ASTM F1671. Fluorescein solution movement, which may occur through penetration, was measured using a fluorometer. Glove stretch caused a reduction in glove thickness ranging from 16% to 40%. Overall, 21 sample failures were found (16.7%; n = 126) regardless of test condition. Nitrile gloves provided better barrier efficacy with the lowest failure rates (2.38%; 1 failure out of 42) compared to latex (19.4%; 7 failures out of 36) and vinyl gloves (27.1%; 13 failures out of 48). Differences in failure rates between stretched and unstretched gloves were insignificant; however, the latex material showed a 2.5 times increase in failures when stretched compared to unstretched. The new test apparatus was able to differentiate between the barrier performance of different glove materials. The use of a domed screen allowed the gloves to stretch, a condition that better represents the state of gloves when in use. Analysis of samples collected from the glove surface opposite to the exposure may provide a way to assess chemical permeation in addition to penetration.

Enhancing Internal and External Stability of Perovskite Solar Cells Through Polystyrene Modification of the Perovskite and Rapid Open‐Air Deposition of ZnO/AlOx Nanolaminate Encapsulation

In this study, the internal and external stabilities of a p–i–n methylammonium lead iodide perovskite solar cell (PSC) are improved. Polystyrene (PS) is introduced into the perovskite layer to form a cross‐linked polymer–perovskite network, which enhances the nucleation and growth of the perovskite grains. Moreover, for the first time, 60 nm thick ZnO/AlOx nanolaminate (NL) thin‐film encapsulation (TFE) is deposited directly on the PSC using an atmospheric‐pressure (AP) spatial atomic layer deposition system operated in AP spatial chemical vapor deposition (AP–SCVD) mode. The rapid nature of AP–SCVD enables encapsulation of the PSCs in open air at 130 °C without damaging the perovskite. The PS additive improves the performance and internal stability of the PSCs by reducing ion migration. Both the PS additive and the ZnO/AlOx NL TFEs improve the external stability under standard test conditions (dark, 65 °C, 85% relative humidity [RH]) by preventing water ingress. The number and thickness of the ZnO/AlOx NL layers are optimized, resulting in a water–vapor transmission rate as low as 5.1 × 10−5 g m−2 day−1 at 65 °C and 85% RH. A 14‐fold increase in PSC lifetime is demonstrated; notably, this is achieved using PS, a commodity‐scale polymer, and AP–SCVD, a scalable, open‐air encapsulation method.

Perbandingan Dataset Labelled Faces in the Wild (LFW) dan faces94 Menggunakan Algoritma Convolutional Neural Networks (CNN) untuk Pengenalan Wajah

This research compares the performance of two popular datasets, Labelled Faces in the Wild (LFW) and faces94, in the task of face recognition using Convolutional Neural Networks (CNN) algorithms. The LFW dataset is known for its high variation in pose, lighting, and expression, while faces94 is more structured with more uniform lighting and pose conditions. CNNs were chosen for their ability to extract important features from face images for classification. In this study, a CNN model was trained on both datasets and its performance was evaluated using accuracy, precision, and recall metrics. The experimental results showed that the model trained on the faces94 dataset achieved higher accuracy compared to the model trained on the LFW dataset. However, the model on the LFW dataset demonstrated better resilience to variations in lighting and pose conditions. These findings indicate that while a more structured dataset like faces94 can produce a model with high accuracy under testing conditions similar to the training data, a dataset with greater variation like LFW is more suitable for real-world applications involving diverse conditions. This study provides important insights into the selection of datasets for developing robust and accurate face recognition systems.

Habitual Caffeine Use is Associated with Heightened Cortisol Reactivity to Lab-Based Stress in Two Samples.

Habitual caffeine consumption protects against depression, but through unclear mechanisms. Although habitual caffeine use predicts cortisol release to other acute stressors (e.g., exercise), this is less examined with lab-based psychosocial stress in healthy adults. Further, caffeine-induced cortisol increases may mask theory-predicted cortisol blunting to robust stress in people with elevated depression risk. In two samples, we tested whether acute (same-day) and habitual caffeine use would predict greater cortisol reactivity to lab-based stress, and whether caffeine would "mask" the effect of a depression risk factor, trait rumination, on blunted cortisol reactivity. In Sample 1, N = 128 emerging adults completed one of three Trier Social Stress Test conditions: non-evaluative Control, ambiguously evaluative Intermediate, or explicit Negative Evaluative. In Sample 2, N = 148 emerging adults completed either a Control or Negative Evaluative condition. In both samples, multilevel growth curve modeling indicated habitual (t = -1.99, p = .048; t = -2.73, p = .007, Samples 1 and 2 respectively), but not acute caffeine use predicted heightened cortisol reactivity as a function of condition. In Sample 1, the relationship between condition, rumination, and blunted cortisol was evident only in caffeine non-users, which differed from users (t = 2.82, p = .005), but in Sample 2 the predicted blunting pattern was evident regardless of caffeine use. This provides evidence that habitual caffeine use is associated with greater cortisol release under psychosocial lab-based stress and may mask the influence of psychosocial variables; future research should examine whether habitual caffeine-induced cortisol release has behaviorally activating effects that protect against depression.

Modeling green recycled aggregate concrete using machine learning and variance-based sensitivity analysis

Recycled aggregate concrete (RAC) is commonly used to lessen the environmental effect of concrete building and demolition waste. The compressive strength of the RAC is one of the most critical factors influencing concrete quality. The compressive strength is assessed by a compression test, which takes a large number of materials and is expensive and time-consuming. With the development of novel concrete mixes and applications, academics are obliged to seek accurate models for forecasting mechanical strength. A significant source of difficulty in compressive strength modeling is that there are many mixture components and testing conditions whose variation significantly influences the predicted values. To this end, this study explores the mixture design of sustainable concrete in order to generate eco-friendly concrete mixes. Tests are conducted on 18 different mixtures comprising different proportions of waste tires, plastic, cement, and red brick to experiment with new green RAC mixtures. For the modeling part, the deep residual neural networks (DRNNs) method is first presented to the problem, aided by a database from the literature for a pretraining task. The proposed DRNNs structure uses shortcuts (i.e., residual connections) that bypass some layers in the deep network structure to alleviate the problem of training with high accuracy. The performance of the proposed DRNNs is evaluated using different goodness of fit measures and compared with well-known machine learning tools. The findings showed that the suggested model could provide credible predictions about the desired mechanical parameter, saving the required lab efforts by 40 %. Finally, a variance-based global sensitivity analysis is performed with the Latin hypercube simulation method to help rank/prioritize each mixture component's impact on determining the compressive strength in practice while mitigating the potential misrepresentation of results due to the correlations between the input parameters. The analysis showed that cement and waste contents are the most significant ones in their first and total order effects.

Preservatives for postmortem brain tissue in biomechanical testing: A pilot study.

Postmortem human subject (PMHS) studies are essential to brain injury research in motor vehicle safety. However, postmortem deterioration reduces the similarity between postmortem test results and invivo response in material testing of brain tissue and in biomechanical testing of the whole head. This pilot study explores the effect of potential preservatives on brain tissue breakdown to identify promising preservatives that warrant further investigation. To identify preservatives with potential to slow postmortem degradation, samples from an initial PMHS were refrigerated at 10°C to qualitatively compare tissue breakdown from 58 to 152 h postmortem after storage in candidate solutions. On brain tissue samples from a second PMHS, compressive stiffness was measured on six samples immediately after harvest for comparison to the stiffness of 23 samples that were stored at 10°C in candidate solutions for 24 h after harvest. The candidate solutions were artificial cerebrospinal fluid (ACSF) without preservatives; ACSF with a combination of antibiotics and antifungal agents; ACSF with added sodium bicarbonate; and ACSF with both the antibiotic/antifungal combination and sodium bicarbonate. Results were analyzed using multiple linear regression of specimen stiffness on harvest lobe and storage solution to investigate potential differences in tissue stiffness. Qualitative evaluation suggested that samples stored in a solution that contained both the antibiotic/antifungal combination and sodium bicarbonate exhibited less evidence of tissue breakdown than the samples stored without preservatives or with only one of those preservatives. In compression testing, samples tested immediately after harvest were significantly stiffer than samples tested after 24 h of storage at 10°C in ACSF (difference: -0.27 N/mm, 95% confidence interval (CI): -0.50, -0.05) or ACSF with antibiotics/antifungal agents (difference: -0.32 N/mm, 95% CI: -0.59, -0.04), controlling for harvest lobe. In contrast, the stiffness of samples tested after storage in either solution containing sodium bicarbonate was not significantly different from the stiffness of samples tested at harvest. There was no significant overall difference in the mean tissue stiffness between samples from the frontal and parietal lobes, controlling for storage solution. Given the importance of PMHS studies to brain injury research, any strategy that shows promise for helping to maintain invivo brain material properties has the potential to improve understanding of brain injury mechanisms and tolerance to head injury and warrants further investigation. These pilot study results suggest that sodium bicarbonate has the potential to reduce the deterioration of brain tissue in biomechanical testing. The results motivate further evaluation of sodium bicarbonate as a preservative for biomechanical testing using additional test subjects, more comprehensive material testing, and evaluation under a broader set of test conditions including in whole-head testing. The effect of antibiotics and antifungal agents on brain tissue stiffness was minimal but may have been limited by the cold storage conditions in this study. Further exploration of the potential for microbial agents to preserve tissue postmortem would benefit from evaluation of the effects of storage temperature.

Lean-and-Green Fractional Factorial Screening of 3D-Printed ABS Mechanical Properties Using a Gibbs Sampler and a Neutrosophic Profiler

The use of acrylonitrile butadiene styrene (ABS) in additive manufacturing applications constitutes an elucidating example of a promising match of a sustainable material to a sustainable production process. Lean-and-green datacentric-based techniques may enhance the sustainability of product-making and process-improvement efforts. The mechanical properties—the yield strength and the ultimate compression strength—of 3D-printed ABS product specimens are profiled by considering as many as eleven controlling factors at the process/product design stage. A fractional-factorial trial planner is used to sustainably suppress by three orders of magnitude the experimental needs for materials, machine time, and work hours. A Gibbs sampler and a neutrosophic profiler are employed to treat the complex production process by taking into account potential data uncertainty complications due to multiple distributions and indeterminacy issues due to inconsistencies owing to mechanical testing conditions. The small-data multifactorial screening outcomes appeared to steadily converge to three factors (the layer height, the infill pattern angle, and the outline overlap) with a couple of extra factors (the number of top/bottom layers and the infill density) to supplement the linear modeling effort and provide adequate predictions for maximizing the responses of the two examined mechanical properties. The performance of the optimal 3D-printed ABS specimens exhibited sustainably acceptable discrepancies, which were estimated at 3.5% for the confirmed mean yield strength of 51.70 MPa and at 5.5% for the confirmed mean ultimate compression strength of 53.58 MPa. The verified predictors that were optimally determined from this study were (1) the layer thickness—set at 0.1 mm; (2) the infill angle—set at 0°; (3) the outline overlap—set at 80%; (4) the number of top/bottom layers—set at 5; and (5) the infill density—set at 100%. The multifactorial datacentric approach composed of a fractional-factorial trial planner, a Gibbs sampler, and a neutrosophic profiler may be further tested on more intricate materials and composites while introducing additional product/process characteristics.

Discussion of EMA Draft Guideline on Quality and Equivalence of Topical Products Based on Comparison of Approved Mometasone Furoate Drugs.

Today, the approval for a generic topical product includes the presentation of therapeutic equivalence to the originator based on clinical trials. To facilitate this procedure, in 2018 the European Medicines Agency (EMA) published a draft guideline on quality and equivalence of topical products, which includes request parameters regarding the quality of the newly developed generic product and test protocols for the implementation of equivalence tests regarding efficacy. To date, no data are available on the quality and evidence of the proposed test conditions. In this study, we performed an in vitro penetration test (IVPT) following the terms of the EMA draft guideline on two authorized topical products for which therapeutic equivalence was already proven during the approval process. The complex biometric data processing revealed that in vitro equivalence could not be observed for all skin sections for either originator or generic product. Moreover, the necessity of the negative control proposed in the draft guideline is more than questionable. From the results presented, there were indications that a reduced number of skin donors would be sufficient to achieve statistically significant equivalence in the comparison of all applied formulations. Here, n = 7 donors was proposed instead of n 12 as the EMA draft guideline demands, decreasing the degree of biodiversity simultaneously. Moreover, a higher number of independent replicates (n > 2) was proposed for proper statistics. This bioequivalence study shows insufficient parameters, which should be discussed together with the EMA draft guideline.

Научно-методический подход к разработке проектов опытно-промышленных испытаний открытой разработки месторождений

Methodology of designing pilot tests in open-pit mining is a complex and insufficiently developed issue in the theory and practice of designing mining systems, which, as a rule, fails to take into account the mining and geological features of the deposits. The complex development of mineral deposits requires new methods of open-pit designing. Thus, the theoretical justification and development of the methods to determine the optimal parameters and indicators of open-pits during the design of pilot tests with the establishment of scales, deadlines, tasks and test conditions is an urgent research problem. The authors of the study have systematized the research trends in developing the basis for designing pilot tests in open-pit geotechnology. The level of geological inaccuracies in case of insufficiently reliable prospecting results leads to a decrease in the expected technical and economic indicators of the mining project ranging from 5-20% to several folds. When information on the deposit is insufficient, pilot test projects are prepared. This is done in order to obtain additional input data for preparation of the feasibility study of permanent conditions or at the stage of the field development to verify the created technologies and means of their mechanisation in order to avoid revision of the mining system parameters in the course of the field operations due to discrepancies between the geomechanical and hydrogeological representations given in the detailed exploration materials and the real conditions.

Научно-методический подход к разработке проектов опытно-промышленных испытаний открытой разработки месторождений

Methodology of designing pilot tests in open-pit mining is a complex and insufficiently developed issue in the theory and practice of designing mining systems, which, as a rule, fails to take into account the mining and geological features of the deposits. The complex development of mineral deposits requires new methods of open-pit designing. Thus, the theoretical justification and development of the methods to determine the optimal parameters and indicators of open-pits during the design of pilot tests with the establishment of scales, deadlines, tasks and test conditions is an urgent research problem. The authors of the study have systematized the research trends in developing the basis for designing pilot tests in open-pit geotechnology. The level of geological inaccuracies in case of insufficiently reliable prospecting results leads to a decrease in the expected technical and economic indicators of the mining project ranging from 5-20% to several folds. When information on the deposit is insufficient, pilot test projects are prepared. This is done in order to obtain additional input data for preparation of the feasibility study of permanent conditions or at the stage of the field development to verify the created technologies and means of their mechanisation in order to avoid revision of the mining system parameters in the course of the field operations due to discrepancies between the geomechanical and hydrogeological representations given in the detailed exploration materials and the real conditions.

Compression characteristics and fractography of in‐situ polymerisable thermoplastic and bio‐epoxy based non‐crimp carbon and glass fiber composites

AbstractThis experimental work involves characterization and fractography of a bio‐based epoxy and an in‐situ polymerisable thermoplastic polymer matrix based non‐crimp glass and carbon fiber composites under compressive loading. The laminates are characterized under compression loading using a combined loading compression (CLC) fixture. Laminates made using the thermoplastic matrix exhibit higher compressive strength (approx. 20% along fiber direction) compared to the bio‐epoxy based laminates. Further, both composites exhibit comparable compressive modulus characteristics. The tested composites are subjected to fractography analysis using Scanning Electron Microscopy (SEM) and Computed tomography (CT). SEM results indicate a difference in fiber‐matrix interface characteristics between the thermoplastic matrix and the bio‐epoxy matrix. Additionally, the CT scans reveal a difference in failure modes due to fiber orientations. A difference between failure mode of the exterior and interior plies of the specimens was also noticed. However, no specific influence of matrix type was observed on the overall macroscopic failure behavior.Highlights Bio‐epoxy and thermoplastic based laminates were characterized in compression. Post‐test fractography was performed using SEM and x‐ray CT scans. Use of thermoplastic matrix exhibits better fiber‐matrix adhesion compared to bio‐epoxy. Both laminates performed well in compression under laboratory test conditions.

Implementation of a toolbox for the generation of flight profiles for use in simulator studies

AbstractMotion sickness is a phenomenon which can produce various symptoms in affected individuals. During development of new aircraft types and cabin layouts, it is important to consider this phenomenon early on, to reduce resulting effects. For research on this topic, German Aerospace Center uses the simulator environment Air Vehicle Simulator together with the Advanced Future Cabin. The Air Vehicle Simulator is a full flight simulator with an interchangeable cockpit module. One of those modules is the Advanced Future Cabin, a realistic replica of an aircraft cabin. Good standardization of the test conditions is required to ensure objectivity and reliability of motion sickness studies in this simulator environment. A specialized software infrastructure is used to replay pre-recorded flight profiles, which are then reproduced by the simulator’s motion, visual and audio systems. Using this replay approach, complete flight profiles can be reproduced very well. However, when parts of the flight profile need exact reproduction within a flight profile or across multiple flight profiles, the approach to record pilot-in-the-loop simulation sessions becomes problematic, as flying the exact same twice is almost impossible. As an improved approach, a toolbox has been implemented, which automates the generation of flight profiles, enabling easier and more precise research on motion sickness in the simulator. The toolbox replaces the pilot-in-the-loop simulation with an automated control of the underlying aircraft simulation model. This leads to greatly improved accuracy of inputs to the simulation model and thus very good reproducibility even of flight profile segments. In this manuscript, details of the toolbox implementation and its validation are discussed.

Probabilistic Analysis of Strength in Retrofitted X-Joints under Tensile Loading and Fire Conditions

In the present study, a total of 360 FE analyses were carried out on tubular X-joints strengthened with collar plates under brace tension under laboratory testing conditions (20 °C) and various fire conditions. The generated FE models were validated based on 31 tests. The FE analyses produced a comprehensive dataset that encapsulated resistance metrics, with detailed simulations of welds, contacts, and the incorporation of non-linear geometrical and material attributes. Twelve theoretical probability density functions (PDFs) were matched to the constructed histograms, with the maximum likelihood (ML) technique utilized to assess the parameters of these fitted PDFs. The theoretical PDFs, rigorously evaluated against the Anderson–Darling, Kolmogorov–Smirnov, and Chi-squared tests, identified the Generalized Petrov distribution as the optimal model for capturing the resistance behaviors of X-joints under tensile load and varying fire conditions. The findings have led to the proposition of five detailed theoretical PDFs and cumulative distribution functions (CDFs), introducing a novel perspective for assessing and reinforcing the structural resilience of strengthened CHS X-joints in engineering practices.

Prediction of micro wear depth between engineering polymers

In the polymer industry, changes in the wear area that affect surface aesthetics have emerged as a significant issue in applications where surface appearance is crucial. Even minute changes in surface height can be visible to the naked eye, necessitating the need for micro-scale wear prediction of polymers. While the Archard model has been verified for decades for metal-metal or polymer-metal contact, predicting wear between polymer-polymer contacts remains challenging due to limitations in wear measurement and wear coefficient determination. In this study, we propose a method for determining the wear coefficient for polymer-polymer contact and validate the prediction model with a component wear test on polymer parts. Wear depth, an essential indicator of wear is measured after the sliding wear test of the polycarbonate (PC) pin and Acrylonitrile butadiene styrene (ABS) copolymer plate. The wear prediction model with the obtained wear coefficient exhibits 99.7 % accuracy in comparison to the test wear depth. A component wear test is performed on engineering polymer parts, and wear prediction under test conditions is made using the proposed model. The measured and predicted wear depth of the component demonstrates a difference smaller than 5 μm, which is within the range of no change in scratch visibility. This study ensures the accurate wear prediction of engineering polymer components with affordable computational efficiency. The ability to predict polymer-polymer wear, previously unattainable, will enable several applications in the polymer industry, such as component design, scratch visibility prediction, and quality assurance.

Robust U-HPLC Method Development of Desonide and its Application to In Vitro Release Testing (IVRT) of Topical Cream Products

Background: The study focuses on establishing In Vitro Release Testing (IVRT) parameters for Desonide cream, following the guidelines of the Topical Classification System (TCS), to assess the bioequivalence between the Reference Listed Drug (RLD) and test. Aim: This study aimed to develop a reliable IVRT method using Franz diffusion cells. An environmentally friendly U-HPLC method was created to analyze Desonide in the samples. objective: This includes assessing Linearity, robustness, precision, sensitivity, reproducibility, selectivity, specificity, and recovery. In the context of In-vitro Release Testing (IVRT), the concept of accuracy becomes irrelevant because there isn&amp;#039;t a definitive &amp;quot;actual&amp;quot; release rate. This is due to the variability in API release rates for a specific semisolid formulation under different test conditions Objective: To evaluate the drug release in Desonide products in accordance with SUPAC guidance, quantify the drug concentration using an analytical method, as per bioanalytical method validation guidelines, and ensure that the results meet the acceptance criteria. Linearity was established from 0.50μg/mL to 40μg/mL with acceptable regression values. Precision was confirmed three times, with an average % RSD of below 15% for 3 sets of 6QC level sample preparations. Stability tests demonstrated Desonide stability in receptor fluid (LLOQ and ULOQ) for 72 hours at 2-8°C and 25°C. Autosampler stability at LQC and HQC levels was proven at 25°C for 72 hours. Additionally, the stock solution remained stable at both 25°C and 2-8°C for 72 hours. Methods: The study involved evaluating the dosing regimen, release medium, and membrane while optimizing the U-HPLC method based on three variables including column temperature, mobile phase composition, and flow rate. After experimentation, it was determined that Nylon membrane and 0.9% NaCl: Methanol release media (70:30 v/v) with 1000 mg dose were used to maximize the release profile of desonide. Results: The created explanatory strategy is precise, delicate, and exact for measuring Desonide, with satisfactory Limits of Location LOD and Lower Limits of Measurement LLOQ measured at 0.15 and 0.50 ng /mL, respectively. The Regression coefficient r2 was identified to be 0.9996. The degree of Desonide measurement lessening was considered palatable, basically since the recuperation was underneath 30.00, additionally due to the favourable linear relationship watched within the Desonide discharge rates amid the IVRT study. Conclusion: All three generic products analyzed were found to be equivalent to the RLD, meeting for "sameness" outlined in the FDA's SUPAC-SS guidance. A novel U-HPLC method was developed for Desonide, covering the range from 0.5 to 40 μg/ml, with intra and inter-day variability below 2% RSD. Additional characterizations were established, and the stability of Desonide was successfully determined.

A rapid spectrophotometric test for assessing skin sensitization potential of chemicals by using N-acetyl-L-cysteine methyl ester in chemico

ABSTRACT During the key event 1 of skin sensitization defined as covalent binding or haptenization of sensitizer to either thiol or amino group of skin proteins, a sensitizer not only covalently binds with skin proteins but also interacts with nucleophilic small molecules such as glutathione (GSH). Although GSH would not be directly associated with skin sensitization, this interaction may be applied for developing an alternative test method simulating key event 1, haptenization. Thus, the aim of the present study was to examine whether N-acetyl-L-cysteine methyl ester (NACME), a thiol-containing compound, was selected as an electron donor to determine whether NACME reacted with sensitizers. Following a reaction of NACME with a sensitizer in a 96-well plate, the remaining NACME was measured spectrophotometrically using 5,5’-dithio-bis-(2-nitrobenzoic acid) (DTNB). Following the optimization of test conditions with two different vehicles, such as acetonitrile (ACN) and dimethyl sulfoxide (DMSO), 64 test chemicals were tested to determine the predictive capacity of current NACME test method. The results obtained showed, the predictive capacity of 94.6% sensitivity, 88.9% specificity, and 92.2% accuracy utilizing DMSO as a vehicle with a cutoff NACME depletion of 5.85%. The three parameters were also over 85% in case of ACN. These values were comparable to or better than other OECD-approved test methods. Data demonstrated that a simple thiol-containing compound NACME might constitute as a reliable candidate for identifying reactive skin sensitizers, and that this method be considered as practical method as a screening tool for assessing a chemical’s tendency to initiate skin sensitization.

Molten salt biomass torrefaction – A sensitivity analysis of process conditions

Biomass is an abundant renewable resource that can be upgraded via torrefaction. Molten salts catalyze the torrefaction reaction, creating enhanced products for fuel and soil amendment purposes at lower temperatures than inert gas torrefaction. The objective of this study is to elucidate the main effects of molten salt torrefaction process conditions on ponderosa pine (Pinus ponderosa) and cave in rock switchgrass (Panicum virgatum) in a binary salt blend of lithium nitrate and potassium nitrate using a Plackett-Burman screening analysis. The investigated process conditions include sweep gas, temperature, salt to biomass ratio (S-B ratio), residence time, and lithium content. The metrics used to evaluate torrefaction severity include mass yields, chemical composition (lignin, cellulose, hemicellulose, extractives), higher heating value (HHV), carbon and nitrogen content, pH, and water sorption. The results show that switchgrass is more severely torrefied through molten salt torrefaction than pine at the same process conditions. For example, switchgrass mass yields are on average 23.3 % lower than pine mass yields across the test conditions. For both feedstocks, the most impactful process conditions are temperature, time, and lithium content in that order with some exceptions. For instance, the effect of temperature, time and lithium content on HHV are, respectively, 3.4×, 2.3×, and 1.7× larger than the next largest process condition for pine, whereas for switchgrass, these values are 3.6×, 2.7×, and 1×. Particle size, sweep gas, and S-B ratio have minor effects depending on the metric, but are overall not significant compared to temperature. The data suggests that an inert gaseous environment need not be maintained to facilitate molten salt torrefaction. Additionally, molten salt torrefaction can produce torrefied biomass with slightly different characteristics than inert gas torrefaction.