Optimal Proportion Research Articles

PENGARUH UKURAN BUTIR AGREGAT KASAR TERHADAP KAPASITAS KUAT TEKAN DAN NILAI SLUMP BETON POROUS

Porous concrete is an innovation and development solution for parking areas, yards and pedestrian areas, as a way to avoid standing water or even flooding. The purpose of this study was to determine the proportion of the optimum coarse aggregate mixture for porous concrete in terms of compressive strength and slump value. The research method used was experimental research conducted at the Laboratory of Structures and Materials, Muhammadiyah Parepare University. The results of this study can indicate that the optimum mixture proportions were obtained at aggregate variations of 0.5-1 cm. The compressive strength with an aggregate size of 0.5-1 cm is 6.13 MPa, an aggregate size of 1-2 cm is 5.47 MPa, while an aggregate size of 2-3 cm is 5.00 MPa. The slump value with an aggregate size of 0.5-1 cm is 196 mm, an aggregate size of 1-2 cm is 192 mm, while an aggregate size of 2-3 cm is 178 mm.

A REVIEW ON EXPLORING THE SIGNIFICANCE OF MICRONUTRIENTS IN CROP PRODUCTION

The essential plant nutrients for growth and development include Zinc, Iron, Boron, Molybdenum, Manganese, Copper, and Chlorine. For an agricultural product to be successfully developed proper crop nutrition is crucial. One of the most significant variables that promote crop production and development is the linked supply of micronutrients with macronutrients in sufficient levels and optimum proportions. Even though they are frequently needed in very low amounts, micronutrients are necessary for plant development. To produce a maximum number of high-quality products, vegetable production must employ micronutrients effectively. The current study has given a significant of micronutrients in crops. Zinc, Boron, Copper, Chloride, Iron, Manganese, and Molybdenum are significant micronutrients. Although Mo is particularly specific to nitrate reductase, other micronutrients are engaged in a variety of photosynthetic processes. Other micronutrients like Zn, Cu, Fe, and Mn are also connected to a variety of enzymatic activities.

Experimental and numerical study of road-bridge link slabs in fully jointless bridges using rubberized engineered cementitious composites (R-ECC)

This paper presents a different way using crumb rubber and fine sand totally replaced for silica sand within ECC mixtures to make rubberized engineered cementitious composites (R-ECC) to solve the issues of high construction cost of the road-bridge link slab for fully jointless bridges (FJBs). The crumb rubber with a size of 80 CR was replaced with fine sand from a volume rate of 5–20% in multiples of 5% to prepare the R-ECC material. Five different R-ECC mixtures (CR0-CR20) with different mix designs were prepared and tested, then an optimum mix proportion for the R-ECC mixtures was found. An R-ECC road-bridge link slab made of the optimum mix proportion which replace with fine sand in a volume rate of 15% was constructed, and its absorptive deformation capacity, tensile performance, and crack distribution under the most unfavourable load (temperature drop load) were studied. It is found that the R-ECC slab has good absorptive deformation capacity, crack control capacity and better internal force distribution. Therefore, R-ECC mixtures can be utilized for road-bridge link slab construction. Then, a sensitivity finite element comparative analysis was carried out considering the content of crumb rubbers, the friction coefficient and the slab length. It is found that the design length has a greater influence on the tensile performance of the R-ECC slab than other factors. Finally, a preliminary design theory of road-bridge link slab for FJBs has been established.

Research on a Multi-Objective Optimization Design for the Durability of High-Performance Fiber-Reinforced Concrete Based on a Hybrid Algorithm

To achieve durable high-performance fiber-reinforced concrete that meets economic requirements, this paper introduces a hybrid intelligent framework based on the Latin hypercube experimental design, response surface methodology (RSM), and the NSGA-III algorithm for optimizing the mix design of high-performance fiber-reinforced concrete. The developed framework allows for the prediction of concrete performance and obtains a series of Pareto optimal solutions through multi-objective optimization, ultimately identifying the best mix proportion. The decision variables in this optimization are the proportions of various materials in the concrete mix, with concrete’s frost resistance, chloride ion permeability resistance, and cost as the objectives. The feasibility of this framework was subsequently validated. The results indicate the following: (1) The RSM model exhibits a high level of predictive accuracy, with coefficient of determination (R-squared) values of 0.9657 for concrete frost resistance and 0.9803 for chloride ion permeability resistance. The RSM model can be employed to construct the fitness function for the optimization algorithm, enhancing the efficiency of multi-objective optimization. (2) The NSGA-III algorithm effectively balances durability and cost considerations to determine the optimal mix proportion for the concrete. After multi-objective optimization, the chloride ion permeability resistance and frost resistance of the high-performance fiber-reinforced concrete improved by 38.1% and 6.45%, respectively, compared to the experimental averages, while the cost decreased by 2.53%. The multi-objective optimization method proposed in this paper can be applied to mix design for practical engineering projects, improving the efficiency of concrete mix design.

Grey correlation analysis and molecular simulation study on modification mechanism of red mud mixed manganese slag

In order to promote the virtuous cycle of economic society, minimize the harm of red mud and manganese slag and maximize the efficiency of processing and utilization of red mud and manganese slag; in order to analyze the influence of red mud and manganese slag on the performance of matrix asphalt, this paper conducts multiple groups of compound proportion tests after fully mixing red mud and manganese slag, and finally determines the optimal compound proportion of 1：1.5. The red mud manganese slag compound modified asphalt binder was prepared by adding the powder-oil ratio of 0, 3%, 6%, 9%, 12%, 15%, 18%, 21% and 24% to the matrix asphalt by the external mixing method. Through the determination of three indexes of modified asphalt binder, the modification effect of different dosage on matrix asphalt is analyzed. From a large number of experimental data, it is concluded that when the mixing ratio is 15%, the three indexes of modified asphalt binder are the best. In this paper, the grey correlation theory is used to analyze the correlation between the dosage of the compound modifier and the penetration, ductility and softening point of the matrix asphalt. It is concluded that the addition of the compound modifier has the most obvious influence on the penetration at 10 ℃, followed by the penetration at 20 ℃, the softening point, the penetration at 25 ℃, the penetration at 30 ℃, the penetration at 15 ℃, the delay at 5 ℃ and the delay at 15 ℃. The adsorption process of red mud compound manganese slag and asphalt was qualitatively simulated by molecular dynamics theory, and the interaction energy between red mud compound manganese slag modified asphalt binder and matrix asphalt was quantitatively calculated, and the modification mechanism of modified asphalt was analyzed.

Effect of multi-walled carbon nanotubes on the visible light photocatalytic activity of AgInS2 for Rhodamine B degradation

Visible-light responsive AgInS2 (AIS) nanoparticles modified with either pristine multi-walled carbon nanotubes (p-MWCNTs) or mixed-acid (H2SO4 and HNO3) oxidized multi-walled carbon nanotubes (o-MWCNTs) were synthesized using a low-temperature liquid phase method. The resulting nanocomposites are denoted as p-MWCNTs/AIS or o-MWCNTs/AIS. The structure, morphology, and optical properties of the samples were characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), high-resolution transmission electron microscopy (HRTEM), photoluminescence spectroscopy (PL), and ultraviolet-visible diffuse reflectance spectroscopy (UV–Vis DRS). The photocatalytic activity of p/o-MWCNTs/AIS towards the degradation of Rhodamine B (RhB) was investigated, and the optimal proportion of p/o-MWCNTs introduced on AIS was determined. A possible degradation mechanism of RhB over p/o-MWCNTs/AIS was proposed. The results demonstrated that p/o-MWCNTs were successfully incorporated into AIS, and the addition of an appropriate amount of p/o-MWCNTs improved the visible-light photocatalytic activity of AIS. Among the samples, 2 % o-MWCNTs/AIS exhibited the highest visible-light catalytic activity, achieving a degradation efficiency of 95 % within 40 min. The·⋅O2− species were identified as the main active species during the photocatalytic degradation process. The introduction of o-MWCNTs not only facilitated the separation of photogenerated electron-hole pairs (e−/h+) in AIS but also enhanced the visible-light absorption of AIS, leading to a significant improvement in its photocatalytic performance. Furthermore, the incorporation of o-MWCNTs greatly enhanced the cycling stability of AIS for reuse.

Bina Betonunun Karışım Oranı için Kaba-AHP ve MOORA Tabanlı Taguchi Optimizasyonu

In the construction industry, materials that are used for producing construction concrete and their mixture proportions are an important decision-making and optimization problem for concrete manufacturers. Amounts (mixture proportions) of the materials, which are used in order to obtain a mixture of high strength and functional concrete, can positively or negatively affect performance criteria which are individually determined for each customer. Furthermore, the effect and significance of each performance criterion on the concrete may differ from each other. This paper proposes the Rough-AHP approach to determine the significance levels and weights of the performance criteria decided according to the customer demands and the MOORA-based Taguchi approach to calculate the optimal mixture proportion of the concrete for the customer demand. It is aimed to determine the best design of the experiment to minimize the experiment duration and cost rather than to perform all experimental designs.

Predictive modeling for compressive strength of 3D printed fiber-reinforced concrete using machine learning algorithms

Three-dimensional (3D) printing in the construction industry is growing rapidly due to its inherent advantages, including intricate geometries, reduced waste, accelerated construction, cost-effectiveness, eco-friendliness, and improved safety. However, optimizing the mixture composition for 3D-printed concrete remains a formidable task, encompassing multiple variables and requiring a comprehensive trial-and-error experimentation process. Accordingly, this study used seven machine learning (ML) algorithms, including support vector regression (SVR), decision tree (DT), SVR-Bagging, SVR-Boosting, random forest (RF), gradient boosting (GB), and gene expression programming (GEP) for forecasting the compressive strength (CS) of 3D printed fiber-reinforced concrete (3DP-FRC). For model development, 299 data points were collected from experimental studies and split into two portions: 70% for model training and 30% for model validation. Various statistical metrics were employed to examine the accuracy and generalizability of the established models. The DT, RF, GB, and GEP models demonstrated higher accuracy in the validation set, achieving correlation (R) values of 0.987, 0.986, 0.986, and 0.98, respectively. The DT, RF, GB, and GEP models exhibited mean absolute error (MAE) scores of 4.644, 3.989, 3.90, and 5.691, respectively. Furthermore, the combination of SVR with boosting and bagging techniques slightly improved the accuracy compared to the individual SVR model. Additionally, the SHapley Additive exPlanations (SHAP) approach unveils the proportional significance of parameters in influencing the CS of 3DP-FRC. The SHAP technique revealed that water, silica fume, superplasticizer, sand content, and loading directions are the dominant parameters in estimating the CS of 3DP-FRC. The SHAP local interpretability unveils the intrinsic relationship between diverse input variables and their impacts on the strength of 3DP-FRC. The SHAP interpretability offers significant insights into the optimum mix proportion of 3DP-FRC.

Ecological desalination of anchovy residues and their mixture with soybean meal for the production of poultry feed: Optimization of waste through response surface methodology (RSM)

Salted anchovy bones are a non-recyclable waste product containing high salt levels. However, they also contain valuable minerals such as calcium, phosphorus, potassium, magnesium, and nitrogen. This study aimed to find a cost-effective method to desalinate anchovy bones while preserving their nutritional value and repurposing them as a raw material for poultry feed. Through various tests, we were able to reduce the salt content of the anchovy bones from 15.4% to 4.7% using a 50/50 percent mixture of tap water and from 15.4% to 3.7% using a mixture of tap water and soybean meal in a 30/70 percent ratio. Combining soybean meal with desalted anchovy bones resulted in a nutritional composition comparable to that found in poultry feed, reducing salt content. The response surface method (RSM) was employed to determine the optimal proportions of desalted anchovy bones (70-90%) and soybean meal (10-30%) and to study the variables affecting the concentrations of NaCl, Ca, P, Ash, and TNM. The study revealed the influence of desalted anchovy bone and soybean meal percentages on these concentrations. This study demonstrates that the method used provides an ideal approach for understanding the interactions between input parameters (% DAR, % SM) and output parameters (NaCl, Ca, P, Ash, and TNM) and shows promising results for the desalination of anchovy bones using a soybean meal cake as well as the feasibility of creating poultry feed.

Impact of reinforcement proportions on mechanical properties and micro-structure of modified Al2O3-LM6 cast composites synthesize at self-pouring temperature: optimization through mixture design of experiment (DoE)

Purpose The purpose of this study is to investigate and evaluate the impact of varying proportions of reinforcement on the mechanical properties of a modified Al2O3-LM6 cast composite under self-pouring temperature conditions. This study aims to determine the optimal mixture proportion of fine powders of Al, Si and xAl2O3 (with x values of 2%, 3% and 4%) through the application of design of experiment (DoE) and statistical analysis using the Minitab software. This study also involved evaluating the microstructural estimation and other physical properties of the cast composite to understand the combined effect of the reinforcement proportion on the material’s properties. Design/methodology/approach The researchers initially mixed the powders through ball milling and then compacted the moisture-free powder mix in a closed steel die. The resulting preforms were heated at the self-pouring temperature in an inert environment to fabricate the final cast composite. By applying DoE and performing an analysis of variance (ANOVA), the researchers sought to optimize the mixture proportion that would yield the best mechanical properties. Findings The experimental results indicated that a mixture combination of 83.5% Al blended with 12.5% Si and 4% Al2O3 led to the greatest improvement in mechanical properties, specifically in terms of increased density, hardness and impact strength. The ANOVA further supported the interaction effect of each processing parameter on the observed results. The results of this study offer valuable insights for the fabrication of modified Al2O3-LM6 cast composites under self-pouring temperature conditions. The identified optimal mixture proportion provides guidance for manufacturing processes and material selection to achieve improved mechanical properties in similar applications. Originality/value This study focuses on a specific composite material consisting of modified Al2O3 and LM6. Although Al2O3 and LM6 have been studied individually in various contexts, the combination of these materials and their impact on mechanical properties under self-pouring temperature conditions is a novel aspect of this research. The researchers use DoE methodology, along with statistical analysis using Minitab software, to optimize the mixture proportion and analyze the data. This systematic approach allows for a comprehensive exploration of the parameter space and the identification of significant factors that influence the mechanical properties of the composite.

Coarse–Fine Registration of Point Cloud Based on New Improved Whale Optimization Algorithm and Iterative Closest Point Algorithm

In this paper, a point cloud coarse–fine registration method based on a new improved version of the whale optimization algorithm (NIWOA) and iterative closest point (ICP) algorithm is proposed; we use three strategies to improve the whale optimization algorithm (WOA). Firstly, circle chaotic mapping is used to initialize the whale population to increase the diversity of the population and make the search space more comprehensively explored. In addition, a Newton inertia weight is proposed to flexibly adjust the proportion of global exploration and local optimization in order to achieve the balance between the exploitation performance and exploration ability of the algorithm. At the same time, we introduce the nonlinear convergence factor that can adjust the size adaptively so that the algorithm can find the global optimal solution faster and more accurately, allowing it to avoid falling into the local optimal solution to a certain extent. The NIWOA algorithm is used to optimize the objective function of point cloud coarse registration to obtain the optimal coordinate transformation, and the rotation and translation operation is carried out on the registered point cloud. The obtained position is used as the initial pose of the ICP fine registration, and the final registration is achieved through ICP iteration. We conduct coarse registration experiments on multiple model point clouds and scene point clouds using the Stanford 3D Scanning Repository dataset and Princeton 3Dmatch dataset, respectively. The experimental results confirm that the NIWOA algorithm can not only find the initial position that is closer to the target point cloud, but also provide reliable initial values for the ICP algorithm. Meanwhile, the NIWOA algorithm combined with ICP experiment results show that the method has a higher registration accuracy and operation efficiency.

Investigation of Mechanical Properties of Ultra-High-Performance Polyethylene-Fiber-Reinforced Recycled-Brick-Aggregate Concrete.

The utilization of ultra-high-molecular-weight polyethylene fibers (UHMWPEFs) to enhance recycled-brick-aggregate concrete represents an efficacious approach for ameliorating the concrete's performance. This investigation addresses the influences of recycled-brick aggregates (RAs) and UHMWPEFs on the concrete's slump, shrinkage, flexural strength, resistance to chloride-ion ingress, and freeze-thaw durability. The mechanisms through which UHMWPEFs ameliorate the performance of the recycled-brick-aggregate concrete were elucidated at both the micro and macroscopic levels. The findings underscore that the three-dimensional network structure established by the UHMWPEFs, while resulting in a reduction in the concrete slump, substantially enhances the concrete's mechanical properties and durability. A regression model for the multifaceted performance of the UHMWPEF-reinforced recycled-brick-aggregate concrete (F-RAC) was formulated by employing response-surface methodology, and the model's reliability was confirmed through variance analysis. The interactive effects of the RA and UHMWPEFs on the concrete were analyzed through a combined approach involving response-surface analysis and contour plots. Subsequently, a multiobjective optimization was conducted for the F-RAC performance, yielding the optimal proportions of RA and UHMWPEFs. It was determined that the optimal performance across the dimensions of the shrinkage resistance, flexural strength, chloride-ion resistance, and freeze-thaw durability of the F-RAC could be simultaneously achieved when the substitution rate of the RA was 14.02% and the admixture of the UHMWPEFs was 1.13%.

Reducing NOx emissions in biodiesel-powered LHR engines using an antioxidant additive: a methodological approach

This study examined the effects of various biodiesel blends with an antioxidant additive on the performance and emissions of a 5.2 kW diesel engine, coated with lanthanum oxide to enhance its performance. The aim was to identify the optimal blend and proportion of biodiesel and antioxidant that could reduce NOx emissions while maintaining or improving engine performance. Experiments were conducted on low heat rejection and conventional engines, using different blends of AME, WCOME, and JME with different proportions of L-ascorbic acid and LA. Results showed that a 20% biodiesel blend with 200 mg of LA additive performed best in a low heat rejection engine, with a 15.8%, 10.4%, and 9.3% reduction in HC, CO, and smoke emissions, respectively, compared to diesel. The NOx emissions increased by 13.7% with biodiesel blends, but AME20 exhibited the lowest increase of only 2.1%. Additionally, AME20 showed the highest brake thermal efficiency (BTE) of 30.3% and the lowest HC, CO, and smoke emissions among all the blends. Further experiments revealed that adding LA200 mg to a 20% blend of biodiesel in a low heat rejection engine resulted in even more significant improvements.

Effect on properties of geopolymer concrete by inclusion of recycled aggregate and methods to enhance the packing density of aggregate

Purpose This study aims to practically determine the optimum proportion of aggregates to attain the desired strength of geopolymer concrete (GPC) and then compare the results using established analytical particle packing methods. The investigation further aims to assess the influence of various amounts of recycled aggregate (RA) on properties of low-calcium fly ash-based GPC of grade M25. Design/methodology/approach Fine and coarse aggregates were blended in various proportions and the proportion yielding maximum packing density was selected as the optimum proportion and they were compared with analytical models, such as Modified Toufar Model (MTM) and J. D. Dewar Model. RAs for this study were produced in laboratory and they were used in various amounts, namely, 0%, 50% and 100%. 12M NaOH solution was mixed with Na2SiO3 in the ratio of 1:2. The curing of concrete was done at the temperatures of 60° and 90 °C for 24, 48 and 72h. Findings The experimentally obtained optimum proportion of coarse to fine aggregate was 60:40 for all amounts of RA. Meanwhile, MTM and Dewar Model resulted in coarse aggregate to fine aggregates as 40:60, 45:55, 55:45 and 55:45, 35:65, 60:40, respectively, for 0% 100% and 50% RAs. The compressive strength of GPC elevated with the increase in curing regime. In addition, the ultrasonic pulse velocity also displayed a similar trend as that of strength. Originality/value The GPC with 50% RAs may be considered for use, as it exhibited superior properties compared to GPC with 100% RAs and was comparable to GPC with natural aggregates. Furthermore, compressive strength is correlated with split tensile strength and ultrasonic pulse velocity.

Amoxicillin degradation in persulfate activation system induced by concrete-based hydrotalcites: Efficiency, mechanism, and degradation pathway

Concrete-based hydrotalcites (CLDHs) was synthesized from concrete to activate peroxysulphate (PDS) for amoxicillin (AMX) degradation. The proportion of Fe2+ in CLDHs was optimized, the effects of initial pH, CLDHs/PDS ratio and PDS dosage on AMX degradation were investigated. To clarify the removal mechanism and degradation pathway of AMX, a quenching test was conducted to identify the active species in the system, the reactive sites of AMX were predicted by density functional theory (DFT) calculation, and the degradation intermediates of AMX were analyzed by liquid chromatography-mass spectrometry (LC-MS). Furthermore, the toxicity of AMX and its degradation intermediates were evaluated based on quantitative structure–activity relationship (QSAR). The results showed that when the molar ratio of M2+/M3+ in CLDHs was 2:1, the optimal mole proportion of Fe2+ in M2+ was 33 %. The activation system obtained better AMX removal as pH value ranged in 4–6, and the optimum CLDHs/PDS mass ratio was 2.6. The removal of AMX by CLDHs-PDS system was the coordination of SO4·- and HO·, and the contribution of SO4·- was slightly higher than that of HO·. Based on DFT calculations and intermediates identification, the degradation pathway of AMX in CLDHs-PDS system was proposed, including quaternary ring opening reaction and hydroxylation reaction. The ecotoxicological assessment showed a slight increase in toxicity of intermediates during AMX degradation. Therefore, appropriate time extension is required to ensure the full mineralization of AMX.

Potential Use of Biomass Waste as a Sustainable Energy Source in the Future: A Case Study

Mangroves have been degraded and converted for decades due to a multitude of factors, ranging from human activity to natural perturbations such as disasters and global warming. Experiments were conducted to determine the impact of fly ash (FA) on the growth of Rhizophora apiculata Blume's (R. apiculate). A completely randomised design (CRD) was employed with D as the control, and nine treatment soil amendments were created from abandoned shrimp pond sediment with rubberwood fly ash (RWFA). These amendments were made by mixing three separate FA samples (A, B, and C) in the ratios of 75:25, 50:50, and 25:75, respectively (A1-A3, B1-B3, and C1-C3), using a total of 200 R. apiculata specimens. The experiment revealed that the addition of FA and its combination had a significant effect on promoting the growth of R. apiculate and improved nutrient availability and retention in the soil. The results of the experiment demonstrate that the effect of Fly Ash (FA) and its combination significantly influence the growth of R. apiculate, impacting the total heights and number of leaves. The most beneficial effect the results of the experiment demonstrate that the effect of fly ash (FA) and its combination significantly influence the growth of R. apiculate, affecting the total height and number of leaves. The most beneficial effects were observed when the optimal proportion of each type of soil amendment was used. The study holds substantial benefits: it introduces a method for improving the soil of shrimp farms through the utilisation of rubberwood fly ash (RWFA) and serves essential nutrients to mangroves. Moreover, implementing this plantation technique can aid in protecting against coastal erosion.

An Analysis of the Performance and Comfort Properties of Fire-Protective Material by Using Inherently Fire-Retardant Fibers and Knitting Structures

This paper investigates the development of fabric materials using several blends of inherently fire-resistant (FR) fibers and various knitted structures. The samples are evaluated with respect to their performance and comfort-related properties. Inherently fire-resistant fibers, e.g., Nomex, Protex, carbon and FR viscose, were used to develop different structures of knitted fabrics. Cross-miss, cross-relief, and vertical tubular structures were knitted by using optimum fiber blend proportions and combinations of stitches. Several important aspects of the fabric samples were investigated, e.g., their physical, mechanical and serviceability performance. Thermo-physiological and tactile/touch-related comfort properties were evaluated in addition to flame resistance performance. An analysis of mechanical performance indicated that the knitted structure has a significant influence on the tensile strength, bursting strength and pilling resistance. The cross-relief structure proved to be the strongest followed by the cross-miss and vertical tubular structures. The FR station suits made from 70:30 Protex/Nomex exhibited the best combination of tensile and bursting strength; therefore, this material is recommended for making a stable and durable station suit. Interestingly, it was also concluded from the experimental study that knitted samples with a cross-relief structure exhibit the best fire-resistance performance. Fiber blends of 70:30 Protex/Nomex and 70:30 Nomex/carbon were found to be optimum in terms of overall performance. The best flame resistance was achieved with Nomex:carbon fiber blends. These results were confirmed with vertical flammability tests, TGA, DTGA and cone calorimetry analysis. The optimization of blend composition as well as knitting structure/architecture is a crucial finding toward designing the best FR station suit in terms of mechanical, dimensional, thermal, thermo-physiological and flame resistance performance.

An effective class of estimators for population mean estimation in successive sampling using simulation approach

In surveys, successive sampling is generally considered to study the same characteristic from one occasion to another so that the change in characteristics over time can be further studied. This paper presents a class of estimators using a novel approach to estimate population mean on two occasions under successive sampling. We have carried out numerical study and simulation study to validate the significance of the proposed class and its members. We have used an optimum unmatched proportion of each class or estimator to compute their respective mean square error during simulation, while other studies considered some fixed value for unmatched units. For large population, the suggested estimation technique is always better for survey practitioners than others.

Association of Depression and Adherence to Oral Anticoagulation in Patients With Atrial Fibrillation.

Adherence to oral anticoagulation is essential for stroke prevention in atrial fibrillation (AF). Depression has been associated with decreased adherence to medications in multiple disease states and in AF is further associated with increased risk of stroke. We hypothesized that individuals with depression and AF have decreased adherence to anticoagulation than those without depression. We used administrative claims data to identify individuals with AF initiating anticoagulation with direct-acting oral anticoagulants (DOACs) or warfarin between 2013 and 2019. We quantified adherence using proportion of days covered, categorized as limited (proportion of days covered, <80%), adequate (proportion of days covered, ≥80% to <90%), or optimal (proportion of days covered, ≥90%). We related depression to 12-month adherence to anticoagulation in logistic regression models, adjusting for demographics, medical and psychiatric comorbidities, household income, educational attainment, and insurance type. As a secondary analysis, we determined the association of depression to adherence for each DOAC agent. We identified 101 041 individuals (aged 74.5±8.9 years; 50.6% women; 29.5% race or ethnicity other than White, including Asian or Black race and Hispanic ethnicity) who initiated either DOACs or warfarin. The odds of adequate adherence to DOACs was 11% (95% CI, 0.85-0.93), and the odds of optimal adherence was 12% (95% CI, 0.83-0.91) less in individuals with depression than those without. Depression was not associated with adherence to warfarin. We identified an association between depression and decreased adherence to DOACs but not warfarin in individuals with AF. Recognizing depression in AF may guide interventions to improve anticoagulation adherence and reduce stroke risk.

SIMULATION OF OPTIMAL MIX OF SIO2-TIO2-AL2O3 NANO ADDITIVES FOR THE MINIMAL WEAR AND COEFFICIENT OF FRICTION OF LUBRICANT USING FUZZY LOGIC

Nano-particles of oxides of various metals are typically added with the base lubricants for enhancing the tribological properties, especially the wear and coefficient of friction of the lubricants. However, it is required to determine the optimum proportion of mix of the nano-additives in order to obtain the desirable characteristics gained through the addition of various oxides of metals mixed with the lubricants. This paper deals with the application of fuzzy logic to simulate the various proportions of a mix of three nano-additives of SiO2, Al2O3 and TiO2 with the corresponding predicted values of tribological characteristics of wear and coefficient of friction. The limited number of outcomes obtained from a full factorial design of experiments carried out with these three nano-additives at three different levels of mixing, are used as inputs to the fuzzy logic simulation. This approach facilitates simulating as many combinations of nano-additives as possible with the base lubricant oil along with the predicted output of characteristics of interest, which otherwise will be cumbersome to carry out the experiments for all the combinations of mix of additives.