Rotatable Design Research Articles

An implementation evaluation of a sports-based health intervention for underrepresented middle school youth in Philadelphia.

Multicomponent, community-based programs aiming to improve health behaviors in youth are needed but can be challenging to implement. Research is needed to better understand the factors that facilitate and inhibit effective implementation of these programs especially for youth at increased risk of health disparities. This study aimed to identify and explore the implementation determinants and outcomes of a multicomponent health intervention conducted from 2021 to 2022 for middle school students living in underserved communities in Philadelphia, PA, USA. Mixed methods approaches, including self-report surveys and semi-structured qualitative interviews, were administered to 18 members of the implementation staff at the end of the program, including coaches (n = 7), assistant coaches (n = 2), school champions (n = 6), administrative leaders (n = 2), and a school district administrator (n = 1). Survey and interview questions were guided by the Consolidated Framework for Implementation Research (CFIR), and interviews were thematically coded following transcription based on 26 CFIR constructs. Innovation source, evidence strength and quality, cosmopolitanism, and the personal attributes of individuals were key constructs associated with implementation effectiveness. Data revealed three multidimensional themes that highlighted broader challenges influencing implementation: (i) broad consensus, different interpretations, (ii) staffing challenges, and (iii) continuity is key. The need for the program was clearly recognized and overall belief in the purpose of the intervention was strong among key program staff and administration. However, issues including limited engagement with training, staffing turnover, and the rotational programming design hindered implementation. Future projects aiming to implement multicomponent after-school time interventions must ensure a consistent vision among partners and continuity in program delivery.

An investigation on wire-EDM of a biodegradable ZE41A magnesium alloy

ABSTRACT The ZE41A magnesium alloy is a propitious material for biomedical applications since it offers a concoction of good biocompatible and biodegradable properties. The wire cut electrical discharge machining (WEDM) is used for machining magnesium alloys primarily because it can produce products with good dimensional accurateness when compared one-on-one with the traditional machining methods. The kerf width and surface roughness are pivotal response factors heavily impacted by WEDM machining parameters. The current research uses WEDM to machine the biodegradable magnesium alloy ZE41A. The preliminary studies were conducted to identify the range of machining parameters by carefully considering kerf width and surface roughness as the responses. The central composite rotatable design determines the optimal experiments to evaluate the response parameters. Based on a comparative analysis, it is clinched that the flushing pressure is a dominant parameter on both kerf width and surface roughness. The experimental data is further processed to develop an empirical or experimental model for both responses as a function of machining parameters. The corroboration experiments were conducted to test the predictability of the experimental model. The accurateness of the empirical model was examined with the experimental results, and the outcomes were found to be satisfactory.

Optimization investigation of parameters for spot-welding of AA2014 and AISI316 dissimilar alloys

The objective of the research was to determine the exact process parameters required for spot-welding AA2014 and AISI316 alloys. The main focus was on achieving particular welding results, including nugget diameter, hardness, and tensile shear fracture load (TSFL). The central composite rotatable design model within the framework of a Response Surface Methodology (RSM) optimization approach, the study sought to intensify key spot weld process factors. The mechanical characteristics and nugget diameter of the welded joints were analyzed by carefully examining these factors to determine their significant effects. The investigation yielded crucial insights, revealing that the highest strength of welded joints, characterized by a nugget diameter of 5.982 mm, hardness of 149.6 VHN, and TSFL of 2.355 KN, was achieved at 3.4 kgf, when accompanied by 60 W power and a 2.5s duration. Notably, power emerged as the predominant factor driving the spot-welding process. Furthermore, microhardness and TSFL displayed direct correlations with power, while nugget diameter exhibited an inverse relationship. Moreover, rigorous statistical analyses, including F-tests and ANOVA, provided robust validation, indicating that the observed values fell comfortably within a 99.5% confidence interval for hardness, nugget diameter, and TSFL. These meticulously derived conclusions represent a significant stride towards establishing more standardized and efficient spot-welding protocols, particularly beneficial for the manufacturing sectors dealing with mild steel and aluminium materials.

Study of machine learning on the photocatalytic activity of a novel nanozeolite for the application in the Rhodamine B dye degradation

Contamination of wastewater with organic dyes has caused a serious threat to humans and aquatic life due to the hazardous effect of these contaminants. In this context, the present work aims to carry out a Machine Learning (ML) study to evaluate the photocatalytic activity of a nanozeolite (nANA) in the degradation of Rhodamine B (RhB) dye. Three machine learning algorithms (Random Forest, Artificial Neural Network and Xtreme Gradient Boosting) were used in the regression model development. The dataset used in the machine learning and data correlation was generated by Central Composite Rotational Design (CCRD 2²). Regarding the machine learning study, the ANN with structure 3:6:1 showed the best performance as a predictive model (R² = 0.98 and 0.9 for training and testing, RMSE < 5.0), resulting in the 50.37 ± 1.01 % RhB removal at pH 5.7, [RhB] = 200 mg L−1 and [nANA] = 2.75 g L−1 after 180 min under visible light. Feature importance revealed that all parameters (pH, [RhB], [nANA]) were relevant to the response. Therefore, this work confirms the potentiality of machine learning algorithms to develop predictive models as well as a good starting point for the scale-up of advanced oxidation processes.

Optimized phenol degradation and lipid production by Rhodosporidium toruloides using response surface methodology and genetic algorithm-optimized artificial neural network

Oleaginous yeast can produce lipids while degrading phenol in wastewater treatment. In this study, a Plackett-Burman Design (PBD) was adopted to identify key factors of phenol degradation and lipid production using R toruloides 9564T. While temperature, inoculum size, and agitation were significant for both the processes (p < 0.05), pH and incubation were significant for lipid production, and phenol removal, respectively. Results from four factors (pH, temperature, inoculum size, and incubation period) central composite design (CCD) experiment were used to formulate quadratic and genetic algorithm-optimized ANN models. The reduced quadratic model for phenol degradation (R2: 0.993) and lipid production (R2: 0.958) were marginally inferior to ANN models (R2: 0.999, 0.982, respectively) on training sets. Multi-objective optimization with equal importance suggests phenol degradation between 106.4 and 108.76%, and lipid production of 0.864–0.903 g/L, by polynomial and ANN models. Complete phenol degradation (100%) and 3.35-fold increment (0.918 g/L) in lipid production were obtained at pH 6.07, inoculum size 14.68% v/v, at 29.5 °C in 92.17 h experimentally.

Potency of Cocoa Honey, Byproduct of Cocoa Bean Processing as Probiotic Media: Optimization of Saccharomyces boulardii Growth and Its Antimicrobial Activity

Cocoa honey, a byproduct of cocoa bean processing, contains high sugars and minerals; thus, it has potential as a fermentation medium. This research investigated the potency of cocoa honey as probiotic media for promising yeast probiotic Saccharomyces boulardii. The growth of S. boulardii in the cocoa honey medium was optimized through response surface methodology employing a central composite rotatable design to obtain maximum cell production and antimicrobial activity. The effects of inoculum size (2–5%), sucrose addition (2.0–3.0%), and fermentation time (5–20 h) were evaluated. The agar diffusion technique assessed the cocoa honey medium's antibacterial activity. Results showed that these independent variables significantly affected the production of S. boulardii cells and their microbial activity against Escherichia coli. The optimal values generated by the model with a desirability value of 0.908 were 20 h of fermentation time, 2% of sucrose addition, and 2% of inoculum size. The maximum yeast count (log10 8.07 cells/mL) and antibacterial activity (4.88 mm) were reached under these optimized conditions, which agreed with the predicted value of the RSM model. This study provided valuable information on the potency of cocoa honey as a fermentative medium for applying S boulardii to develop a probiotic drink.

Unlocking DOE potential by selecting the most appropriate design for rAAV optimization

Producing recombinant adeno-associated virus (rAAV) for gene therapy via triple transfection is an intricate process involving many cellular interactions. Each of the different elements encoded in the three required plasmids-pHelper, pRepCap, and pGOI-plays a distinct role, affecting different cellular pathways when producing rAAVs. The required expression balance emphasizes the critical need to fine-tune the concentration of all these different elements. The use of design of experiments (DOE) to find optimal ratios is a powerful method to streamline the process. However, the choice of the DOE method and design construction is crucial to avoid misleading results. In this work, we examined and compared four distinct DOE approaches: rotatable central composite design (RCCD), Box-Behnken design (BBD), face-centered central composite design (FCCD), and mixture design (MD). We compared the abilities of the different models to predict optimal ratios and interactions among the plasmids and the transfection reagent. Our findings revealed that blocking is essential to reduce the variability caused by uncontrolled random effects and that MD coupled with FCCD outperformed all other approaches, improving volumetric productivity 109-fold. These outcomes underscore the importance of selecting a model that can effectively account for the biological context, ultimately yielding superior results in optimizing rAAV production.

Optimisation of dry heat treatment conditions for modification of faba bean (Vicia faba L.) starch

Faba bean is a protein-rich starchy grain that is underutilised in the UK. The starch of faba bean can be modified using environmentally friendly methods like dry heat treatment (DHT) to enhance functional and its physicochemical properties. This study investigated the impact of dry heat temperature and time on the structure, functional and physicochemical properties of faba bean starch (FBS) using a two-factor central composite rotatable design. Factors (DHT temperature:100–150 °C and DHT time:0.5–5 h) with their respective α mid-point values led to 13 experimental runs. Selected pasting and functional properties were measured as response variables. Corn starch was included as a reference and compared with the FBS modified using the optimized conditions. DHT increased peak (approx. 2205–2267 cP), final (approx. 3525–3642 cP) and setback (approx. 1887–1993 cP) viscosities but decreased the amylose content of FBS. Colour, as measured by lightness value, morphology and crystalline type were not altered but the starches showed a loss of order and an increase in crystallinity after DHT. FBS appeared resilient to DHT but showed higher swelling power and pasting properties compared to the corn starch control. The optimum DHT conditions to produce starch with desirable properties are a temperature of 100 °C for 0.1716 h, with a desirability factor of 66 %.

Modified Slope Rotatability for Balanced Ternary Designs of Second Order Response Surfaces

Objective: To evaluate the best optimal solutions of modified Second Order Slope Rotatable Designs (SOSRD) using Balanced Ternary Designs (BTD) and to compare with different methods of Modified SOSRD for 3≤v≤8. Methods: To estimate the parameters of the response surface design of second order the principle of least squares was applied for design of experiments, we also evaluated modified slope rotatable value and variance of estimated responses. Findings: The outcome of this research reveals the influence of various design parameters on key aspects such as the variance of the estimated response, slope rotatable value, axial points, central points and also total number of design points of modified SOSRD framework. Novelty: The variance of the estimated responses in the new method of Modified SOSRD using BTD provides the best optimal solutions with minimum variances while compared to different methods of Modified SOSRD. Keywords: Response ­ Surface Experimental Designs, Second Order Rotatable Designs, Second ­ Order Slope ­ Rotatability, Second ­ Order Modified Slope ­ Rotatability, Balanced Ternary Designs

Optimization of activation by peroxidation and photo-assisted peroxidation of biochar produced from sewage sludge

Biochar from biomass, a cost-effective and sustainable alternative to pulverized activated carbon (PAC), often faces limitations in pore size and surface functionality. Hydrogen peroxide (H₂O₂) activation can enhance biochar's surface properties but requires large quantities and high concentrations, increasing production costs. Advanced oxidation methods, such as H₂O₂/UV radiation, can reduce H₂O₂ usage by generating highly reactive hydroxyl radicals (*OH). This study investigates biochar production from activated sewage biosolids using H2O2 activation and H2O2/UV radiation. Optimization was conducted via a central composite rotational design, varying activation parameters activation pH (1.5, 4.0, 7.0, 9.0, and 11.5) and H2O2 concentration (0, 10, 20, 30, and 40 vol), with methylene blue (MB) adsorption capacity as the metric. Characterization was performed using FTIR, SEM, EDS, XRD, and N2 adsorption/desorption techniques. Results indicated optimal biochar activation at pH 11.5 with 20 vol% H2O2. Activation pH was more significant than H2O2 concentration. Desirability curve analysis suggested that optimized parameters did not significantly enhance adsorption capacity, with desirability values at 93.053 %. Overall, H2O2 efficiently increased surface area by degrading the adsorbent, while H2O2/UV effectively removed impurities.

Extrusion pretreatment of green Arabica coffee beans for lipid enhance extraction

Brazil is the world's largest producer and exporter of green coffee. Coffee beans have intrinsic and extrinsic defects that affect their chemical composition and the consumer perception of the beverage. The aim of this work is to evaluate the impact of extrusion process in green Arabica healthy and defective coffee beans in order to increase oil yield. The chromatographic analyses of the non-processed beans showed that caffeine, diterpenes and serotonin amides did not vary between the samples (p<0.05), while moisture and ash content varied significantly. The extrusion process followed by Soxhlet was optimized using central composite rotation design (CCRD) 22. Extrusion at the point selected as optimal (68ºC and 60 rpm) proved to be efficient when applied in combination with Soxhlet extraction, causing an increase of 61–81 % of oil yield (15.29 ± 0.42 % from defective beans and 16.42 ± 0.63 % from healthy beans), while its use combined with pressing (6.99 ± 0.08 %) was not significant compared to Soxhlet extraction alone (9.05 ± 0.24 %). Caffeine, diterpenes, serotonin amides and fatty acids methyl esters (FAMES) were analyzed in the oils where most of the fatty acids showed similar percentage values (p ≤ 0.05). The total diterpene content was higher in the extruded beans, while serotonin amides varied according to healthy and defective beans and pre-treatment (for defective grains), with defective grains showing consistently higher content compared to healthy grains (p ≥ 0.05). Caffeine content was similar between the healthy extruded, defective and defective extruded grains, with the lowest content in the healthy grain. It can be concluded that extrusion is a pre-treatment with a high impact in coffee oil yield. Green coffee oil is commercially explored by cosmetics and pharmaceutical industries due to its emollient and moisturizer properties. Besides, this oil protects skin against UV radiation. These properties are related to bioactive compounds present in the lipid fraction of coffee bean as diterpene esters, fatty acids and serotonin amides, which together justify this study.

Second type second order slope rotatable designs utilizing symmetrical unequal block arrangements with two unequal block sizes

Kim and Ko developed second order slope rotatable designs (SOSRD) of second type utilizing central composite designs (CCD), in which two numbers are used to represent the positions of star points. In this paper, we suggest second type SOSRD utilizing symmetrical unequal block arrangements (SUBA) with two unequal block sizes. In some cases, the suggested method may develop designs containing fewer design points than second type SOSRD obtained utilizing CCD, pairwise balanced designs (PBD) and balanced incomplete block designs (BIBD). The first order partial derivative's for estimated second order response variance for factors 6≤v≤15 is also obtained.

Operational parameters optimization of convection air-drying with ultrasound pretreatment of Cyperus rotundus L. tubers by RSM

Drying is an important step in the postharvest processing of agricultural products, as it allows the product to be preserved by reducing water activity to safe values, which stops microorganism growth and enzymatic reactions. In this context, the objective of this study was to assess how various drying temperatures, combined with ultrasonic pretreatment, affect drying rates and essential oil production. Assays were conducted according to a Central Composite Rotational Design, considering two factors with the following intervals: duration of the ultrasonic bath from 0 to 40 min, drying air temperature from 40 to 70 °C. The optimization was carried out using Response Surface Methodology (RSM). The essential oil was extracted by hydrodistillation and its constituents were identified by gas chromatography coupled to mass spectrometry. Histochemical analyses of fresh tubers were performed. The Midilli model was the one that best described the drying kinetics of Cyperus rotundus in all treatments. The drying time of C. rotundus tubers was dependent only on temperature (decreasing linear effect), it was possible to describe the variation in drying time as a function of temperature. It was not possible to adjust a model for ultrasonic bath time or drying temperature that would optimize both essential oil yield and the drying time of C. rotundus tubers. However, in this study, shorter drying times were observed compared to previous studies on C. rotundus tubers drying in the shade at room temperature. A total of 29 chemical constituents have been identified in the essential oil extracted from C. rotundus tubers, of which the majority are: 3,4-dimethyl-3-cyclohexen-1-carboxaldehyde (19.23%); caryophyllene oxide (17.63%); and α-cyperone (9.54%). Histochemical analyses of C. rotundus tubers showed the presence of starch, phenolic compounds, and lipids.

Optimized Ultrasonic Extraction of Essential Oil from the Biomass of Lippia graveolens Kunth Using Deep Eutectic Solvents and Their Effect on Colletotrichum asianum

Essential oils are emerging as alternatives to conventional pest control chemicals. Lippia graveolens Kunth (Mexican oregano) is a source of essential oils and during conventional extraction, the biomass generated is discarded as waste; however, reports show that this biomass is still a rich source of essential oils. Conventional essential oil extraction causes contamination and utilizes toxic solvents. Deep eutectic solvents (DESs) offer low toxicity, biodegradability, high selectivity, and yields comparable to organic solvents. This study obtained essential oil from Lippia graveolens biomass via hydrodistillation with ultrasound-assisted DES pretreatment. This research aimed to optimize the extraction of essential oil from Lippia graveolens biomass using ultrasound-assisted DESs and assess its in vitro and in vivo inhibitory effect on C. asianum. The response variables were extraction yield and total reducing capacity. Optimal conditions were determined using a central composite rotatable design, considering solid-to-liquid ratio (0.38 g/mL), ultrasonic amplitude (45.05%), and time (7.47 min). The optimized oil, with thymol (48%) as the predominant component, exhibited more volatile compounds than conventional hydrodistillation. Fungicidal assays highlighted its potential in controlling anthracnose in papaya fruits caused by C. asianum, making ultrasound-assisted DES pretreatment a promising alternative for obtaining essential oil from botanical byproducts.

Ecological pre-treatment of cell wall degrading enzymes from Pleurotus djamor for optimized essential oil extraction from Melissa officinalis L.

Melissa officinalis L. is a plant with different medicinal and culinary uses, which is considered one of the essential oils with the highest market value, mainly because of its low yield. The use of technologies that improve the extraction of this essential oil is justified. The study evaluated the use of cell wall degrading enzymes (CWDE) obtained from Pleorotus djamor to extract essential oil of Melissa officinalis L.. For the optimization of the enzymatic pre-treatment, the independent variables time and CWDE/H2O ratio were evaluated through central composite rotational design (CCRD). The essential oil extraction was carried out by hydrodistillation after pre-treatment. The results showed that the pre-treatment was able to increase the essential oil yield by 71 % and reduced energy consumption and CO2 emissions by 42 %, when applied for 60 minutes and CWDE/H2O ratio (25/450 mL.mL−1). Gas chromatography-mass spectrometry (GC/MS) was used to evaluate the essential oil composition. The majority of compounds were citral (Neral +Geranial). In addition, the increase of this compound was observed at about 24 %. The lemon balm plant cell wall was degraded. Considering the production and energy costs and increase yield as well as the quality of lemon balm essential oil, the application of CWDE was efficient.

Exploring the impact of mycogenic selenium nanoparticles on production of exopolysaccharides from arid zone bacteria

Modulating bacterial exopolysaccharides (EPS) with nanoparticles is an emerging application of nanotechnology due to the enhancement of soil fertility, encouragement of nutrient uptake, and plant growth in agriculture. This study highlights the seamless integration of nanotechnology with EPS, the fungus, Serendipita indica strain is used here to reduce selenium ions and forms selenium nanoparticles (Se NPs). Se NPs has been characterized by visual observation, UV–vis spectroscopy, FTIR, TEM, SEM-EDX, XRD, DLS and Zeta potential. Production of EPS was monitored in the presence of Se NPs. Extracted EPS was characterized by FTIR, SEM-EDX, HPLC, and NMR. Results exhibit the successful formation of spherical, crystalline Se NPs with size ranging between 20-80 nm with 92.24% selenium. Response surface methodology (RSM) was used to identify and optimise the production of exopolysaccharides (EPS) from Bacillus subtilis that was isolated from arid zone agricultural soil. The central composite rotatable design (CCRD) exhibited the highest yield of EPS 11.332 g/l. EPS was then characterized by FTIR, HPLC, NMR, and SEM which revealed the presence of carboxyl and hydroxyl groups and flakes-like structure of EPS. Hence, the present work will pave the way for the application of nanotechnology for increasing EPS production and will also offer new dimensions for further research.

Multiplexed All‐Optical Permutation Operations Using a Reconfigurable Diffractive Optical Network

AbstractLarge‐scale and high‐dimensional permutation operations are important for various applications in, for example, telecommunications and encryption. Here, all‐optical diffractive computing is used to execute a set of high‐dimensional permutation operations between an input and output field‐of‐view through layer rotations in a diffractive optical network. In this reconfigurable multiplexed design , every diffractive layer has four orientations: , , , and . Each unique combination of these layers represents a distinct rotation state, tailored for a specific permutation operation. Therefore, a K‐layer rotatable diffractive design can all‐optically perform up to independent permutation operations. The original input information can be decrypted by applying the specific inverse permutation matrix to output patterns. The feasibility of this reconfigurable multiplexed diffractive design is demonstrated by approximating 256 randomly selected permutation matrices using = 4 rotatable diffractive layers. To further enhance its multiplexing capability, input polarization diversity is also utilized. Additionally, this reconfigurable diffractive design is experimentally validated using terahertz radiation and 3D‐printed diffractive layers, providing a decent match to numerical results. The presented rotation‐multiplexed diffractive processor is particularly useful due to its mechanical reconfigurability, offering multifunctional representation through a single fabrication process.

Effect of heating and pH on hydroxymethylfurfural content, diastase and invertase activity of Dalbergia honey using response surface methodology

The current study explored the botanical origin of Dalbergia (Dalbergia sissoo) honey source using melissopalynology. The 20 runs in triplicate were evaluated using the composite central rotatable design (CCRD) for the analysis of effect of heating (45–55 ºC), pH (4.8–5.8) and time (5–15 min) on attributes features like hydroxymethylfurfural (HMF) content, diastase & invertase activity of Dalbergia honey with Response Surface Method (RSM). A significant effect of process variables on three responses has btabeen observed from the statistical data. The amount of HMF content increased at higher temperature and pH. However, the diastase activity can be well monitored in the increased temperature. The invertase activity of honey was significantly (P < 0.0001) reduced for every pH value from 4.8 to 5.8. The results attained when heating beyond 49 ºC as well as a higher pH with prolonged time could alter HMF content, diastase and invertase activity, which may deteriorate the grade of honey.

Multiscale topology optimization for the design of spatially-varying three-dimensional lattice structure

This paper introduces three dimensional (3D) topology optimization specifically tailored for designing spatially-varying primitive-cubic (CP) type lattice structures. The developed design process consists of three steps: pre-processing, main processing, and post-processing. In the pre-processing step, a surrogate model between lattice geometry variables and effective elasticity tensor is constructed using an artificial neural network. This surrogate model is essential because it enables the quick calculation of the effective elasticity tensor of lattice microstructure. In the subsequent main processing step, multiscale topology optimization is performed. During this step, lattice microstructure size and rotation design variables are optimized together with the macrostructure density design variables. Macrostructures are designed using a well-established three-field density scheme with a SIMP formulation. Formulations for spatially-varying 3D lattice microstructure are newly developed based on a unit quaternion rotation representation scheme. In the final post-processing step, a spatially-varying microstructure is restored using a de-homogenization scheme, newly developed particularly for the primitive-cubic (CP) type 3D lattice structures. The effectiveness and robustness of the proposed formulations are validated through three design examples for the compliance minimization problem. Moreover, a designed lattice structure is fabricated using an additive manufacturing machine.

Enhancing Bovine Embryo Development In Vitro Using Oil-in-Water Nanoemulsions as Specific Carriers for Essential Lipids.

Worldwide meat consumption and production have nearly quintupled in the last 60 years. In this context, research and the application of new technologies related to animal reproduction have evolved in an accelerated way. The objective of the present study was to apply nanoemulsions (NEs) as carriers of lipids to feed bovine embryos in culture media and verify their impact on the development of embryos produced in vitro. The NEs were characterized by particle size, polydispersity, size distribution, physical stability, morphology using atomic force microscopy (AFM), surface tension, density, pH, and rheological behavior. The NEs were prepared by the emulsification/evaporation technique. A central composite rotatable design (CCRD) was used to optimize the NE fabrication parameters. The three optimized formulations used in the embryo application showed an emulsion stability index (ESI) between 0.046 and 0.086, which reflects high stability. The mean droplet diameter analyzed by laser diffraction was approximately 70-80 nm, suggesting a possible transit across the embryonic zona pellucida with pores of an average 90 nm in diameter. AFM images clearly confirm the morphology of spherical droplets with a mean droplet diameter of less than 100 nm. The optimized formulations added during the higher embryonic genome activation phase in bovine embryos enhanced early embryonic development.