Optimization Criteria Research Articles

Wood Polymer Composite Based on Poly-3-hydroxybutyrate-3-hydroxyvalerate (PHBV) and Wood Flour-The Process Optimization of the Products.

This study involved the optimization of the molded pieces manufacturing process from a poly-3-hydroxybutyrate-co-3-hydroxyvalerate biocomposite containing 30% wood flour by mass. The amount of wood flour and preliminary processing parameters were determined on the basis of preliminary tests. The aim of the optimization was to find the configuration of important parameters of the injection process to obtain molded pieces of good quality, in terms of aesthetics, dimensions, and mechanical properties. The products tested for quality were dog bone specimens. The biocomposite was produced using a single-screw extruder, whereas molded pieces were made using an injection molding process. The Taguchi method was applied to optimize the injection molding parameters, which determine the products quality. Control factors were selected at three levels. The L27 orthogonal plan was used. For each set of input parameters from this plan, four processing tests were performed. The sample weight, shrinkage, elongation at break, tensile strength, and Young's modulus were selected to assess the quality of the molded parts. As a result of the research, the processing parameters of the tested biocomposite were determined, enabling the production of good-quality molded pieces. No common parameter configuration was found for different optimization criteria. Further research should focus on finding a different range of technological parameters. At the same time, it was found that the range of processing parameters of the produced biocomposite, especially processing temperature, made it possible to use it in the Wood Polymer Composites segment.

Horizon 2020 Project Analysis by Using Topic Modelling Techniques in the Field of Transport

Abstract Understanding the main research directions in transport is crucial to provide useful and relevant insights. The analysis of Horizon 2020, the largest research and innovation framework, has been already realized in a few publications but rarely for the field of transport. Thus, this article is devoted to fill this gap by introducing a novel application of topic modelling techniques, specifically the Latent Dirichlet Allocation (LDA), in the Horizon 2020 framework for transport projects. The method is using the Mallet software with pre-examined code optimizations. As the first step, a corpus is created by collecting 310 project abstracts; afterward, the texts of abstracts are prepared for the LDA analysis by introducing stop words, optimization criteria, the number of words per topics, and the number of topics. The study successfully uncovers the following five main underlying topics: road and traffic safety, aviation and aircraft, mobility and urban transport, maritime industry and shipping, open and real-time data in transport. Besides that, the main trends in transport are identified based on the frequency of words and their occurrence in the corpus. The applied approach maximizes the added value of the Horizon 2020 initiatives by revealing insights that may be overlooked using traditional analysis methods.

Optimizing the Location of Supports under a Monolithic Floor Slab

Monolithic reinforced concrete floor slabs are one of the most common types of building structures, and their optimization is an urgent task. The article presents the methodology for finding the optimal position of point supports under a reinforced concrete floor slab of arbitrary configuration at arbitrary load. The slab is considered thin, elastic and isotropic, with constant over-the-area stiffness, that is, the reinforcement is not taken into account or is constant. The solution is performed using the finite element method in combination with the nonlinear optimization methods. Finite element analysis is implemented by authors in MATLAB (R2024a) environment in such a way that the location of the columns may not coincide with the nodes of the finite element mesh of the slab. This allows to significantly increase the efficiency of solving the optimization problem compared to previously used algorithms, including the Monte Carlo method. Boundary conditions are taken into account using the Lagrange multiplier method. As an optimization criterion, the maximum deflection value is used, as well as the value of the potential strain energy. The effectiveness of six nonlinear optimization methods is compared in the example of a square slab under the action of a uniformly distributed load. For solutions obtained using the pattern search, simulated annealing and internal point methods, the maximum deflections are at least 1.2 times higher than for solutions obtained using the particle swarm method and genetic algorithm. An example of real object optimization is also presented. By changing the position of seven columns, it was possible to reduce the maximum deflection of the floor slab by 1.6 times.

First-principles study on the effect of torsional deformation on WSe2 as an anode material for calcium ion batteries.

In this paper, the effects of torsional deformation on the electronic properties of intrinsic WSe2 system and Ca-adsorbed WSe2 system were systematically studied by first-principles method. The results show that Ca can be stably adsorbed on the vacancy (H site) of WSe2 surface in all deformation systems, and the adsorption energy of the system without deformation is the highest. Intrinsic WSe2 is a semiconductor with a direct band gap of 1.53 eV. The torsional deformation makes WSe2 change from a direct band gap semiconductor to an indirect band gap semiconductor and finally to a metal property. The adsorption of Ca makes the conduction band of WSe2 move down and increases the number of peaks in the conduction band region. The new density of state peaks are mainly derived from the contribution of W-d, Se-p, and d orbitals of adsorbed atoms in each adsorption system. Mulliken charge analysis shows that Ca transfers most of the valence electrons to the substrate, and the torsional deformation changes the amount of transferred charge. The twist deformation reduces the diffusion barrier of Ca on WSe2 surface from 0.20 to 0.14 eV. The above results provide a basis for the improved application of WSe2 in ion batteries. In this study, all the first-principles calculations are based on Materials Studio 8.0 software package. The generalized gradient approximation (GGA) functional Perdew-Burke-Ernzerhof (PBE) is used for the electron exchange correlation interactions in all systems. The optimization algorithm uses Broyden-Fletcher-Goldfarb-Shanno (BFGS) to optimize the model structure and calculate the energy. The measured cutoff energy is optimized to 450 eV, and the radius of the vacuum layer in the Z-axis direction is 20 Å. The K-point of 7 × 7 × 1 is selected by Monkhorst-Pack method. The structural optimization criterion is selected, the convergence radius of the force is 0.01 eV/Å, and the displacement radius between atoms is within 0.001 Å distance. The energy convergence radius of each atom is less than 1.0 × 10-6 eV/atom.

Effects of Failure Criteria on Quantitatively Determining the Machining Mechanics for CFRP with Different Tool Rake Angles

Abstract The machining mechanics of carbon fiber reinforced polymer (CFRP) materials is influenced by the coupled effects of the workpiece anisotropy, tool edge geometry, and cutting parameters. Predicting the chip formation mechanism is crucial for optimizing cutting parameters, reducing tool wear, and improving efficiency and surface quality. This study quantitatively evaluates the effect of main CFRP failure criteria on the chip formation mechanism in modeling the machining mechanics of CFRP. The results show that the Hashin-Puck and Davila criteria excel at capturing chip formation across all fiber orientations because of the incorporation of ‘internal friction’ concept, while others only achieve accurate predictions in specific fiber orientation ranges due to improper shear strength consideration. The sources of the prediction similarities, differences, and limitations of failure criteria are experimentally validated. Sensitivity analyses quantitatively determine the effect of the tool rake angle on the machining energy consumption and cutting forces across the fiber orientation range. This research can be used to select the optimal failure criteria, design proper cutting tool geometry, and inform the cutting parameter choices for CFRP machining operations.

Ultrasound criteria for assessing the correction of metabolic-associated fatty liver disease and liver blood flow disorders using arginine in patients with coronary artery disease in combination with COVID-19

Background. Coronavirus disease 2019 (COVID-19) remains one of the most urgent global health problems today. In the conditions of its spread around the world, the global scientific community is trying to study not only respiratory, but also extrapulmonary manifestations of this infection. It is known that with COVID-19, the endothelium, the hemostasis system, and the liver are affected with the occurrence of such a complication as metabolic dysfunction-associated steatotic liver disease (MASLD). The most vulnerable group of patients in terms of coronavirus disease and its complications (including MASLD) are those with coronary heart disease (CAD), therefore the search for effective drugs and optimal ultrasound criteria to evaluate liver steatosis in the dynamics of treatment is the main task of modern medicine. Goal: to determine the ultrasound criteria for assessing the correction of MASLD and liver blood flow disorders using arginine in patients with CAD associated with COVID-19. Materials and methods. A prospective study was conducted in 52 patients with CAD combined with PCR-positive COVID-19. The study was carried out upon admission to the hospital and 6 months after discharge. Group I (n = 27) consisted of CAD + COVID-19 patients who, in addition to standard therapy for MASLD, received arginine for 6 months after discharge from the hospital; group II (comparison group, n = 25) included participants who received standard therapy wi­thout arginine. Results. Splanchnic artery duplex scanning at baseline showed that 21 (78.0 %) patients in group I and 19 (76.0 %) in group II had a decrease in peak systolic velocity (PSV) in the proper hepatic artery (PHA), an increase in portal vein blood flow at the beginning of treatment, as well as increased liver size in 20 (74.0 %) patients in group I and 17 (68.0 %) in group II. An increase in the attenuation coefficient was detected in all patients of groups I and II. There were no differences between the groups at the time of inclusion in the study in terms of splanchnic blood flow and atte­nuation coefficient. After 6 months of arginine treatment, an improvement in the portal vein blood flow and a decrease in blood flow velocity in the PHA, a decrease in the diameter of the portal vein, a decrease in the size of the right and left liver lobes were found in group I, with no improvement in group II. A repeated study revealed a decrease in the attenuation coefficient in group I and no changes in group II. At the beginning of the study, a direct correlation was found between fibrinogen and the attenuation coefficient in group I (r = 0.54; p < 0.05), as well as in group II (r = 0.51; p < 0.05). After 6 months, C-reactive protein decreased in both groups. Conclusions. In patients with CAD combined with COVID-19 in the presence of MASLD, a decrease in the portal vein blood flow and an increase in PSV in the PHA were found. When arginine was used for 6 months in combination with standard therapy, according to the European Society of Cardiology protocols, there was a significant decrease in the attenuation coefficient, PSV in the PHA, and an increase in the portal vein blood flow. This indicates the possibility of using the attenuation coefficient as the main marker, and PSV in the PHA and the portal vein blood flow as additional criteria for ultrasound assessment of MASLD correction with arginine in patients with CAD combined with COVID-19.

Regional ionospheric correction generation for GNSS PPP-RTK: theoretical analyses and a new interpolation method

The regional ionospheric corrections have become one of the critical parts of Precise Point Positioning (PPP)-based Real-Time-Kinematic (RTK) services to achieve fast positioning convergence. Several methods for regional ionospheric corrections supporting PPP-RTK have been developed and implemented over recent years, but little attention is given to the theoretical foundation of existing ionospheric correction methods and their performance comparison to find an optimal method in some sense. The optimality criterion of such methods should not only be based on the precision of the ionospheric correction itself, but also on its broadcasting strategies, and implementation aspects. This contribution studies ionospheric correction generation methods within the best linear unbiased predictor (BLUP) framework. Comparing the accuracy performances of the methods, we demonstrate that the Kriging method with trend, as a special case of BLUP, is the most appropriate method for large-scale networks (above 500 km). A strategy for the evaluation of the uncertainty of the grid-interpolated ionospheric corrections is also developed. In contrast to other empirical methods, this new method is rigorous in the sense that it avoids the underestimation of the uncertainty of predicted ionospheric corrections, especially when reference stations are close to a grid point.

Short-, mid- and long-term efficacy of dupilumab in moderate-to-severe atopic dermatitis: a real-world multicentre Italian study of 2576 patients

Abstract Background The efficacy and safety of dupilumab in atopic dermatitis (AD) have been defined in clinical trials but limited real-world evidence on long-term treatment outcomes is currently available to inform clinical decisions. Objectives To describe the long-term effectiveness and safety of dupilumab up to 48 months in patients with moderate-to-severe AD. Methods A multicentre, retrospective, dynamic cohort study was conducted to assess long-term effectiveness and safety of dupilumab in patients with moderate-to-severe AD in a real-world setting. Predictors of minimal disease activity (MDA) optimal treatment target criteria [defined as the simultaneous achievement of a 90% reduction in Eczema Area and Severity Index score, itch-numeric rating scale (NRS) score ≤ 1, sleep-NRS score ≤ 1 and Dermatology Life Quality Index ≤ 1] were investigated. Results In total, 2576 patients were enrolled from June 2018 to July 2022. MDA optimal treatment target criteria were achieved by 506/2309 (21.9%), 769/1959 (39.3%), 628/1247 (50.4%), 330/596 (55.4%) and 58/106 (54.7%) of those that reached 4, 12, 24, 36 and 48 months of follow-up, respectively. Logistic regression revealed a negative effect on MDA achievement for conjunctivitis and food allergy at all timepoints. Adverse events (AEs) were mild and were observed in 373/2364 (15.8%), 166/2066 (8.0%), 83/1291 (6.4%), 27/601 (4.5%) and 5/110 (4.5%) of those that reached 4, 12, 24, 36 and 48 months of follow-up. Conjunctivitis was the most frequently reported AE during the available follow-up. AEs led to treatment discontinuation in < 1% of patients during the evaluated time periods. Conclusions The high long-term effectiveness and safety of dupilumab were confirmed in this dynamic cohort of patients with moderate-to-severe AD, regardless of clinical phenotype and course (persisting or relapsing) at baseline. Further research will be needed to investigate the effect of T helper cell 2 comorbidities and disease duration on the response to dupilumab and other newer therapeutics for AD.

Method in Selecting Vehicles for Interventions and Surveillance of Navigation Safety at Sea

Selecting a vehicle to monitor navigational safety is an important goal, especially in search and rescue operations. It depends on the criteria set and the type of equipment in use. The study aimed to select the optimal vehicle according to the optimal criterion. In the decision-making, the AHP method was used to analyze and rank the selection criteria and vehicle types. As the most important criterion, the results point to reliability in different weather conditions and the SAR vessel as the first choice for interventions and monitoring navigational safety in Croatia. In the selection process, the AHP methodology pointed directly to the significant inconsistency of the expert group and indirectly to the need for more careful selection of members, additional training, and a broader selection of criteria and equipment.

A Decision Support System is Developed to Determine the Optimal Criteria for Selecting Exceptional Lecturers Based on Their Lecturer Performance Index

Decision Support Systems (DSS) are computer systems that analyze data and convert it into actionable information for decision-making. The prior application mainly emphasized design analysis in web development, neglecting the use of decision-making knowledge as a responsibility within the Tri Dharma of Higher Education. Analyzing data to transform it into information is a complex task involving decision-making. The process of decision-making has a significant impact on the information generated for recommendation purposes. Suggestions in a decision-making process only sometimes serve as a standard for leaders to implement immediately. However, it is essential to acknowledge that multiple suggestions are required to make a final decision since they provide a basis for comparison with earlier recommendations. The Decision Support System (DSS) utilized in this research focuses on selecting the optimal criteria from several criteria. The research employed the Analytical Hierarchy Process (AHP) technique, which consists of six stages : Criteria Alternative Determination, Pairwise Matrix Comparison, Criteria And Making Matrix, Square of Pairwise Matrix, Normalisation, and Alternative Ranking. All six steps must be sequentially executed without skipping any stage, ensuring each stage complements the others and generates accountable information. The research concludes by proposing a Decision Support System for Determining the Best Criteria for Lecturer Selection. This system utilizes the Lecturer Performance Index to provide recommendations to parties seeking information on selecting criteria for assessing lecturer performance. The system aims to enhance accountability in the performance of the Tri Dharma of Higher Education.

Multi-Objective Optimization of Morphology in High-Rise Residential Areas for Outdoor Thermal Comfort in Yulin City, Northwest China

Urban residential areas significantly influence outdoor thermal comfort through architectural morphology. This study concentrates on the multi-objective optimization of the thermal comfort environment in residential areas, with a focus on Yulin—a city in the cold, inland region of Northwestern China. Yulin is characterized by its distinctly defined seasons, particularly harsh and windy conditions in the spring, which significantly impact thermal comfort. Utilizing field surveys, characteristics of scale and layout from high-rise residential areas in Yulin were extracted to formulate design strategies adapted to local climates. The Universal Thermal Climate Index (UTCI) served as the optimization criterion, and genetic algorithms, integrated with parametric modeling software, generated multiple layout schemes. These were refined through the Pareto evolutionary algorithm II to optimize thermal comfort across seasons. Furthermore, the Sobol’ sensitivity analysis method was employed to assess the impact of key parameters on outdoor thermal comfort, identifying crucial layout design elements. The optimization improved UTCI values for different seasons, ensuring year-round comfort. Specifically, summer UTCI improved to 25.51, while winter and spring values reached optimal values of −14.02 and −6.41, demonstrating enhanced thermal retention and reduced wind exposure. Sobol’ sensitivity analysis identified building length, orientation, and density as key parameters, highlighting their critical impact on thermal comfort. This study offers practical guidelines for urban residential area design in similar climatic zones, aligning architectural planning with environmental sustainability and enhancing thermal comfort effectively. This study provides practical guidelines for the design of residential areas in cold inland—seasonal windy—regions and other similar climatic zones, aligning building morphology design with environmental sustainability and enhancing thermal comfort effectively.

IMMUNOTAR - Integrative prioritization of cell surface targets for cancer immunotherapy.

Cancer remains a leading cause of mortality globally. Recent improvements in survival have been facilitated by the development of less toxic immunotherapies; however, identifying targets for immunotherapies remains a challenge in the field. To address this challenge, we developed IMMUNOTAR, a computational tool that systematically prioritizes and identifies candidate immunotherapeutic targets. IMMUNOTAR integrates user-provided RNA-sequencing or proteomics data with quantitative features extracted from publicly available databases based on predefined optimal immunotherapeutic target criteria and quantitatively prioritizes potential surface protein targets. We demonstrate the utility and flexibility of IMMUNOTAR using three distinct datasets, validating its effectiveness in identifying both known and new potential immunotherapeutic targets within the analyzed cancer phenotypes. Overall, IMMUNOTAR enables the compilation of data from multiple sources into a unified platform, allowing users to simultaneously evaluate surface proteins across diverse criteria. By streamlining target identification, IMMUNOTAR empowers researchers to efficiently allocate resources and accelerate immunotherapy development.

Nonlinear compartmental modeling to monitor ovarian follicle population dynamics on the whole lifespan.

In this work, we introduce a compartmental model of ovarian follicle development all along lifespan, based on ordinary differential equations. The model predicts the changes in the follicle numbers in different maturation stages with aging. Ovarian follicles may either move forward to the next compartment (unidirectional migration) or degenerate and disappear (death). The migration from the first follicle compartment corresponds to the activation of quiescent follicles, which is responsible for the progressive exhaustion of the follicle reserve (ovarian aging) until cessation of reproductive activity. The model consists of a data-driven layer embedded into a more comprehensive, knowledge-driven layer encompassing the earliest events in follicle development. The data-driven layer is designed according to the most densely sampled experimental dataset available on follicle numbers in the mouse. Its salient feature is the nonlinear formulation of the activation rate, whose formulation includes a feedback term from growing follicles. The knowledge-based, coating layer accounts for cutting-edge studies on the initiation of follicle development around birth. Its salient feature is the co-existence of two follicle subpopulations of different embryonic origins. We then setup a complete estimation strategy, including the study of structural identifiability, the elaboration of a relevant optimization criterion combining different sources of data (the initial dataset on follicle numbers, together with data in conditions of perturbed activation, and data discriminating the subpopulations) with appropriate error models, and a model selection step. We finally illustrate the model potential for experimental design (suggestion of targeted new data acquisition) and in silico experiments.

Mixed-integer linear programming for computing optimal experimental designs

The problem of computing an exact experimental design that is optimal for the least-squares estimation of the parameters of a regression model is considered. We show that this problem can be solved via mixed-integer linear programming (MILP) for a wide class of optimality criteria, including the criteria of A-, I-, G- and MV-optimality. This approach improves upon the current state-of-the-art mathematical programming formulation, which uses mixed-integer second-order cone programming. The key idea underlying the MILP formulation is McCormick relaxation, which critically depends on finite interval bounds for the elements of the covariance matrix of the least-squares estimator corresponding to an optimal exact design. We provide both analytic and algorithmic methods for constructing these bounds. We also demonstrate the unique advantages of the MILP approach, such as the possibility of incorporating multiple design constraints into the optimization problem, including constraints on the variances and covariances of the least-squares estimator.

Extraction of phenolic compounds from lucuma (Pouteria lucuma) seeds with natural deep eutectic solvents: modelling using response surface methodology and artificial neural networks

The present study aimed to extract polyphenolic compounds from lucuma (Pouteria lucuma) seeds using natural deep eutectic solvents (NADES) as a green, efficient, and environmentally friendly extraction. This was optimized by using the Response Surface Method (RSM) and comparing its predictive capacity with Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN). Four NADES were prepared by mixing lactic acid (LA) with each of the following reagents: sodium acetate (SA), urea (U), glucose (G), and ammonium acetate (AA), separately. The yield of total phenolic compounds (TPC) obtained from lucuma seeds with each NADES was measured as an optimization criterion with the Box-Benhken design. The following factors were evaluated: time, temperature, and the lucuma seed flour (LSF): NADES ratio. The response variables were TPC and antioxidant activity. The LA-AA extract was selected because it exhibited the highest TPC value and was analyzed by UHPLC–MS (Ultra-performance Liquid Chromatography-Mass Spectrometry). From the RSM, the optimal extraction parameters were 80 min, 52°C, and LSF: NADES ratio of 8:100 (w/v), obtaining a TPC value of 3601.51 ± 0.51 mg GAE/100 g LFS. UHPLC–MS analysis evidenced the formation of epigallocatechin isomers from epigallocatechin gallate. The predictive ability of ANNs compared to RSM was demonstrated.

Numerical energy and entropy analyses of a tube with wavy tape insert including CoFe2O4/water nanofluid under laminar regime

The primary objective of this investigation is to assess the impact of vortex generator geometry and nanofluid on thermohydraulic and irreversibility characteristics within a laminar flow regime. The study introduces an original CoFe2O4/H2O (1 % vol.) nanofluid and employs a wave tape insert to induce forced convection in a tube, accompanied by first and second-law thermodynamic analysis. The novelty of this research lies in the numerical exploration of heat transfer and flow profiles for a nanofluid in a tube, varying the wave rate (y = 4-5-6). The investigation considers the laminar model and single-phase approach in all analyses under constant heat flux (q” = 2000 W/m2). The study observed that the nanofluid flowing in the tube with a wave ratio of 4, 5, and 6 resulted in an average enhancement in the Nusselt number of 93.25 %, 86.26 %, and 80.06 %, respectively. The optimal performance evaluation criterion (PEC) for water flowing in the tube with a wave ratio of 6 at Re = 500 exhibited an increase of 11.0 %, whereas the CoFe2O4/H2O flow showed a 9.14 % increment in the average PEC along the Reynolds number. Moreover, the total entropy generation values for water flowing in tubes with wave ratios of 5, 6, and 4 exhibited increases of 101.88 %, 94.66 %, and 51.34 %, respectively, in comparison to the smooth tube.

Optimization of cross-sectional dimensions of castellated beams with hexagonal openings

The object of this study is a castellated beam, in which the web openings have the shape of a regular hexagon. The beam is examined to find optimal cross-sectional dimensions. The optimization task is stated as the task of finding the optimal profile numbers for top and bottom Tees of the beam and the optimal width of the web opening while ensuring the required load-carrying capacity of the beam. Minimization of the volume of the beam material was considered as an optimality criterion. The stated optimization problem was solved using the exhaustive search method. For an assortment of normal I-beams with parallel flanges, castellated beams were obtained with optimal cross-sectional dimensions depending on the steel grade, the beam span, and the magnitude of transverse uniformly distributed load. The optimization calculations proved that it was possible to increase the elastic section modulus of the beam to 35.48...50 % through the use of a castellated web. Castellated beams with optimal cross-sectional dimensions at the same load-carrying capacity are characterized by lower steel consumption (up to 23.19 %) compared to I-beams with a solid web. Analysis of the results has made it possible to devise recommendations for the optimal distribution of material in the cross-sections of such beams. The results are valid only for the assortment of normal I-beam profiles and only for the case of uniformly distributed load acting on the beam when the compressed beam flange is laterally restrained from the bending plane and the beam web has openings in the form of regular hexagons. It is under such conditions that the reported results can be implemented in practice both at the stage of selecting cross-sections of the studied class of structures, and at the development of effective assortments of castellated beams

NON-ANALYTICAL DESIGN OF THE PI CONTROLLER OPTIMAL PARAMETERS FOR A CONTINUOUS LINE

The multiple motor drives are complex and coupled MIMO nonlinear systems. Due to the complexity of their mathematical models the development of effective control systems is quite complicated task. This paper presents the design of optimal control based on the quadratic optimality criterion for the central section of the continuous production line using soft computer methods when fuzzy model of the controlled system has been used. In this case, the proposed method demonstrates non-analytical design of the optimal parameters of PI controller with emphasis on minimal knowledge on the controlled system. The realized experimental measurements on a continuous line laboratory model confirmed the effectiveness and the good dynamic properties of the optimal continuous line controller and also its applicability to others MIMO nonlinear dynamic systems.

Optimization of rotor blind hole parameters for inner-hole rotary cavitator

Abstract In order to study the cavitation characteristics of rotary cavitator and the optimization of blind hole parameters, this paper first deduces the blind hole geometric parameters (aperture, hole depth, and number of holes) that affect the cavitation effect, then uses a numerical simulation method to optimize the blind hole parameters that affect the cavitation effect based on the control variable method and gas phase contour. Using single factor analysis as the optimization criterion and gas phase volume as the optimization basis, the response surface method was applied to the multi-parameter optimization problem with interaction. The results indicate that the intensity of cavitation can be effectively increased by increasing the geometric dimensions of the blind holes’ diameter, depth, and number appropriately. On the other hand, the response surface method can be utilised to study the multi-parameter optimization problem in the multivariable system comprised of the geometric parameters of the blind hole of the cavitator rotor. This paper’s optimization research on the rotor parameters of inner-hole rotary cavitator provides a foundation and reference for future cavitator structure optimization research.

Data-driven strategies for enhancing diversity in oncology clinical trials: Optimization of eligibility criteria.

11020 Background: Advancing inclusive clinical research is essential to benefit all patients (pts) and is an expectation, and in some cases a requirement, by regulators. Enabling the inclusion of representative populations should begin at protocol design. However, it is not always clear which changes in eligibility criteria (EC) will have the most impact on representativeness and whether the impact will have similar effect across historically underrepresented populations (HUPs; i.e., pts ≥75 yrs, females, non-Latinx[NL] Black, or Latinx pts). We have defined a novel application of scoring to assess implications of EC on inclusion of HUPs in trials. Methods: Using real-world data from the US nationwide Flatiron Health electronic health record-derived de-identified database for aNSCLC as a benchmark (N=50,263), we selected pts who met trial EC and therapy indication criteria for 9 Phase III aNSCLC trials (2012–2018). We quantified representativeness of the eligible cohort via log disparity [LD], a machine learning fairness metric for the odds of selecting a subgroup vs. the rest of the population; 100% represents parity and 80% is sometimes considered a lower bound for representativeness, but higher benchmarks (e.g., 95%) may be more appropriate. We then identified EC drivers of representativeness by removing or modifying EC. Results: Across HUP groups, the majority of trials (≥55%) were below parity. Removing creatinine clearance (CrCl) had a consistently positive impact for older pts (median % Δ [range]: +2 [1, 32]) and NL Black pts (+2 [1, 5]), but the direction of impact differed across trials for female and Latinx pts (increase in representativeness for some trials, decrease for others). The impact of removing ECOG Performance Status (PS) varied across HUPs (positive for older pts, neutral or positive for female pts, trial-dependent for Latinx and NL Black pts); e.g., in Keynote010, removing ECOG PS increased LD for older pts (93% to 99%), but decreased LD for Latinx pts (97% to 93%). Across trials, removing hemoglobin, HIV, and Hepatitis B/C had a consistently positive or neutral impact on LD for NH Black pts (e.g., hemoglobin median % Δ [range]: +3 [2, 5]), however, the impact was negative or trial-dependent for Latinx and older pts. LD scores can also guide modification of cutpoints to optimize representativeness; e.g., for Keynote189, lowering the CrCL cutpoint from 50 to to 37 mL/min could be expected to improve representativeness for older patients (LD: 66% to 80%, the lower bound for representativeness). Conclusions: It is important to consider the complex nature of diversity when designing trials to ensure that optimizing inclusion of one group of pts does not inadvertently reduce representativeness for another group. These findings support a data-driven approach to modifying EC during protocol design to maximize inclusion of HUPs in concert with a robust operational plan.