This research presents the results of a fin heat transfer study of three different models of the motorcycle engine. The objective of this study is to minimize the external body temperature because the optimum design will be found when the heat transfer rate is maximized. The study obtains the procurement of a balance between the outer boundary temperature due to convective heat transfer and air-cooled fin design. Heat transfer coefficient varies according to wind velocity (Km/hr) and Nusselt Number. The analysis was performed on three different engine models, named A, B and C. The optimum design was design B through simulation which has lower temperature gain, lower deformation and lower normal stress. DOE (Design of Experiments) was performed on the optimum design of the engine among all with three parameters thickness of fin, size of fin, and shape of fin, and again analysis was performed according to DOE cases. The material used for manufacturing the models was aluminum alloy 6061 which has a thermal conductivity of 200 W/mK. The study was performed on the designed models by taking the outer boundary temperature of 750oC. The heat transfer coefficient was about 77.28 W/m2K at 40 Km/h velocity.

The rapid development of potency assays is critical in the development of life-saving vaccines. The traditional plaque assay or fifty percent tissue culture infectious dose (TCID50) assay used to measure the potency of live virus vaccines is time consuming, labor intensive, low throughput and with high variability. Described here is the development and qualification of a cell-based reporter potency assay for two vaccines for respiratory viral infection, one based on the recombinant vesicular stomatitis virus (rVSV) backbone, termed Vaccine 1 in this paper, and the other based on the measles virus vector, termed Vaccine 2. The reporter potency assay used a Vero E6 cell line engineered to constitutively express NanuLuc® luciferase, termed the VeroE6-NLuc or JM-1 cell line. Infection of JM-1 cells by a live virus, such as rVSV or measles virus, causes a cytopathic effect (CPE) and release of NanuLuc® from the cytoplasm into the supernatant, the amount of which reflects the intensity of the viral infection. The relative potency was calculated by comparison to a reference standard using parallel line analysis (PLA) in a log-log linear model. The reporter assay demonstrated good linearity, accuracy, and precision, and is therefore suitable for a vaccine potency assay. Further evaluation of the Vaccine 1 reporter assay demonstrated the robustness to a range of deliberate variation of the selected assay parameters and correlation with the plaque assay. In conclusion, we have demonstrated that the reporter assay using the JM-1 cell line could be used as a potency assay to support the manufacturing and release of multiple live virus vaccines.

Abrasion wear is a significant concern for cutting tools, particularly when milling asphalt concrete due to the presence of hard mineral aggregate particles. The pressure exerted on the cutting tool by the chipped material and the resulting cutting forces directly influence tool wear. To estimate the cutting forces in asphalt milling, the authors propose using either laboratory experiments or cost-effective Discrete Element Method (DEM) modeling-by simulating the real conditions-as direct measurement under real conditions is challenging. This article presents results from an original experimental program aimed at determining the cutting forces during asphalt pavement milling. A specialized stand equipped with a moving plate and recording devices was designed to vary milling depth, rotational speed, and advance speed. The experimental results for horizontal force values were compared with numerical results from DEM modeling. It was found that both increasing the milling depth and the advance speed lead to higher cutting forces. Generally, DEM modeling trends align with experimental results, although DEM values are generally higher. The statistical analysis allowed identification of the milling depth as the most significant parameter influencing cutting force and the optimal combination of milling parameters to achieve minimum horizontal force acting on cutting tooth, namely, 15 mm milling depth and 190 mm/min advanced speed.

The Heck reaction is widely employed to build a variety of biologically relevant scaffolds and has been successfully implemented in the production of active pharmaceutical ingredients (APIs). Typically, the reaction with terminal alkenes gives high yields and stereoselectivity toward the trans-substituted alkenes product, and many green variants of the original protocol have been developed for such substrates. However, these methodologies may not be applied with the same efficiency to reactions with challenging substrates, such as internal olefins, providing trisubstituted alkenes. In the present work, we have implemented a Heck reaction protocol under green conditions to access trisubstituted alkenes as final products or key intermediates of pharmaceutical interest. A set of preliminary experiments performed on a model reaction led to selecting a simple and green setup based on a design of experiments (DoE) study. In such a way, the best experimental conditions (catalyst loading, equivalents of alkene, base and tetraalkylammonium salt, composition, and amount of solvent) have been identified. Then, a second set of experiments were performed, bringing the reaction to completion and considering additional factors. The protocol thus defined involves using EtOH as the solvent, microwave (mw) irradiation to achieve short reaction times, and the supported catalyst Pd EnCat®40, which affords an easier recovery and reuse. These conditions were tested on different aryl bromides and internal olefines to evaluate the substrate scope. Furthermore, with the aim to limit as much as possible the production of waste, a simple isomerization procedure was developed to convert the isomeric byproducts into the desired conjugated E alkene, which is also the thermodynamically favoured product. The approach herein disclosed represents a green, efficient, and easy-to-use handle towards different trisubstituted alkenes via the Heck reaction.

Successful therapeutic delivery of siRNA with polymeric nanoparticles seems to be a promising but not vastly understood and complicated goal to achieve. Despite years of research, no polymer-based delivery system has been approved for clinical use. Polymers, as a delivery system, exhibit considerable complexity and variability, making their consistent production a challenging endeavor. However, a better understanding of the polymerization process of polymer excipients may improve the reproducibility and material quality for more efficient use in drug products. Here, we present a combination of Design of Experiment and Python-scripted data science to establish a prediction model, from which important parameters can be extracted that influence the synthesis results of polybeta-amino esters (PBAEs), a common type of polymer used preclinically for nucleic acid delivery. We synthesized a library of 27 polymers, each one at different temperatures with different reaction times and educt ratios using an orthogonal central composite (CCO-) design. This design allowed a detailed characterization of factor importance and interactions using a very limited number of experiments. We characterized the polymers by analyzing the resulting composition by 1H-NMR and the size distribution by GPC measurements. To further understand the complex mechanism of block polymerization in a one-pot synthesis, we developed a Python script that helps us to understand possible step-growth steps. We successfully developed and validated a predictive response surface and gathered a deeper understanding of the synthesis of polyspermine-based amphiphilic PBAEs.

BACKGROUND: Stem cell-derived therapies hold the potential for treatment of regenerative clinical indications. Static culture has a limited ability to scale up thus restricting its use. Suspension culturing can be used to produce target cells in large quantities, but also presents challenges related to stress and aggregation stability.
METHODS: Utilizing a design of experiments (DoE) approach in vertical wheel bioreactors, we evaluated media additives that have versatile properties. The additives evaluated are Heparin sodium salt (HS), polyethylene glycol (PEG), poly (vinyl alcohol) (PVA), Pluronic F68 and dextran sulfate (DS). Multiple response variables were chosen to assess cell growth, pluripotency maintenance and aggregate stability in response to the additive inputs, and mathematical models were generated and tuned for maximal predictive power.
RESULTS: Expansion of iPSCs using 100 ml vertical wheel bioreactor assay for 4 days on 19 different media combinations resulted in models that can optimize pluripotency, stability, and expansion. The expansion optimization resulted in the combination of PA, PVA and PEG with E8. This mixture resulted in an expansion doubling time that was 40% shorter than that of E8 alone. Pluripotency optimizer highlighted the importance of adding 1% PEG to the E8 medium. Aggregate stability optimization that minimizes aggregate fusion in 3D culture indicated that the interaction of both Heparin and PEG can limit aggregation as well as increase the maintenance capacity and expansion of hiPSCs, suggesting that controlling fusion is a critical parameter for expansion and maintenance. Validation of optimized solution on two cell lines in bioreactors with decreased speed of 40 RPM, showed consistency and prolonged control over aggregates that have high frequency of pluripotency markers of OCT4 and SOX2 (> 90%). A doubling time of around 1-1.4 days was maintained after passaging as clumps in the optimized medium. Controlling aggregate fusion allowed for a decrease in bioreactor speed and therefore shear stress exerted on the cells in a large-scale expansion.
CONCLUSIONS: This study resulted in a control of aggregate size within suspension cultures, while informing about concomitant state control of the iPSC state. Wider application of this approach can address media optimization complexity and bioreactor scale-up challenges.

Current research studies devoted to cutting forces in drilling are oriented toward predictive model development, however, in the case of mechanistic models, the material effect on the drilling process itself is mostly not considered. This research study aims to experimentally analyze how the machined material affects the feed force (Ff) during drilling, alongside developing predictive mathematical-statistical models to understand the main effects and interactions of the considered technological and tool factors on Ff. By conducting experiments involving six factors (feed, cutting speed, drill diameter, point angle, lip relief angle, and helix angle) at five levels, the drilling process of stainless steel AISI1045 and case-hardened steel 16MnCr5 is executed to validate the numerical accuracy of the established prediction models (AdjR = 99.600% for C45 and AdjR = 97.912% for 16MnCr5). The statistical evaluation (ANOVA, RSM, and Lack of Fit) of the data proves that the drilled material affects the Ff value at the level of 17.600% (p < 0.000). The effect of feed represents 44.867% in C45 and 34.087% in 16MnCr5; the cutting speed is significant when machining C45 steel only (9.109%). When machining 16MnCr5 compared to C45 steel, the influence of the point angle (lip relief angle) is lower by 49.198% (by 22.509%). The effect of the helix angle is 163.060% higher when machining 16MnCr5.

Fused Deposition Modelling (FDM) is one of the layer-based technologies that fall under the umbrella term \"Additive Manufacturing\", where the desired part is created through the successive layer-by-layer addition process with high accuracy using computer-aided design data. Additive manufacturing technology, or as it is commonly known, 3D (three-dimensional) printing, is a rapidly growing sector of manufacturing that is incorporated in automotive, aerospace, biomedical, and many other fields. This work explores the impact of the Additive Manufacturing process on the mechanical proprieties of the fabricated part. To conduct this study, the 3D printed tensile specimens are designed according to the ASTM D638 standards and printed from a digital template file using the FDM 3D printer Raise3D N2. The material chosen for this 3D printing parameter optimization is Polylactic acid (PLA). The FDM process parameters that were studied in this work are the infill pattern, the infill density, and the infill cell orientation. These factors\' effects on the tensile behavior of printed parts were analyzed by the design of experiments method, using the statistical software MINITAB2020.

This work is focused on performing a quantitative assessment of the environmental impacts associated with an organic synthesis reaction, optimized using an experimental design approach. A nucleophilic substitution reaction was selected, employing vanillin as the substrate, a phenolic compound widely used in the food industry and of pharmaceutical interest, considering its antioxidant and antitumoral potential. To carry out the reaction, three different solvents have been chosen, namely acetonitrile (ACN), acetone (Ace), and dimethylformamide (DMF). The syntheses were planned with the aid of a multivariate experimental design to estimate the best reaction conditions, which simultaneously allow a high product yield and a reduced environmental impact as computed by Life Cycle Assessment (LCA) methodology. The experimental results highlighted that the reactions carried out in DMF resulted in higher yields with respect to ACN and Ace; these reactions were also the ones with lower environmental impacts. The multilinear regression models allowed us to identify the optimal experimental conditions able to guarantee the highest reaction yields and lowest environmental impacts for the studied reaction. The identified optimal experimental conditions were also validated by experimentally conducting the reaction in those conditions, which indeed led to the highest yield (i.e., 93%) and the lowest environmental impacts among the performed experiments. This work proposes, for the first time, an integrated approach of DoE and LCA applied to an organic reaction with the aim of considering both conventional metrics, such as reaction yield, and unconventional ones, such as environmental impacts, during its lab-scale optimization.

The performance of a Pelton wheel is influenced by the jet created by the nozzle. Therefore, a Computational Fluid Dynamics (CFD) simulation was proposed. In this study, the significant output parameters (outlet velocity, outlet pressure, and tangential force component) and input parameters (different pressure and spear locations) were examined. In addition, the influencing parameters and their contributing percentages to the performance of the Pelton wheel were calculated using different optimisation techniques such as Taguchi Design of Experiments (DoE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA) and Criteria Importance Through Intercriteria Correlation (CRITIC). The effect of input factors on the output response was examined with DoE, and the results show that the inlet pressure had the most significant impact (97.38%, 99.18%, and 97.38%, respectively, for all different spear sites with a 99% confidence level). In terms of preference values, the TOPSIS and GRA results are comparable (best ranks for simulation runs #24 and #25 and least ranks for simulations #2 and #3, respectively). The CRITIC results for the pressure parameter are in good agreement with the Taguchi ANOVA analysis. The last spear location (5 mm after the nozzle outlet), with an inlet pressure of 413685 Pa generated the best result when employing the TOPSIS and GRA techniques. The outlet pressure of the nozzle was found to have a significant impact on the flow pattern of the Pelton Wheel based on the analysis of the CRITIC, Taguchi, and CFD results.