Optimal Test Research Articles

Establish a noninvasive model to screen metabolic dysfunction-associated steatotic liver disease in children aged 6–14 years in China and its applications in high-obesity-risk countries and regions

The prevalence of metabolic-associated steatotic liver disease (MASLD) is rising precipitously among children, particularly in regions or countries burdened with high prevalence of obesity. However, identifying those at high risk remains a significant challenge, as the majority do not exhibit distinct symptoms of MASLD. There is an urgent need for a widely accepted non-invasive predictor to facilitate early disease diagnosis and management of the disease. Our study aims to 1) evaluate and compare existing predictors of MASLD, and 2) develop a practical screening strategy for children, tailored to local prevalence of obesity. We utilized a school-based cross-sectional survey in Beijing as the training dataset to establish predictive models for screening MASLD in children. An independent school-based study in Ningbo was used to validate the models. We selected the optimal non-invasive MASLD predictor by comparing logistic regression model, random forest model, decision tree model, and support vector machine model using both the Beijing and Ningbo datasets. This was followed by serial testing using the best performance index we identified and indices from previous studies. Finally, we calculated the potential MASLD screening recommendation categories and corresponding profits based on national and subnational obesity prevalence, and applied those three categories to 200 countries according to their obesity prevalence from 1990 to2022. A total of 1018 children were included (NBeijing=596, NNingbo=422). The logistic regression model demonstrated the best performance, identifying the waist-to-height ratio (WHtR, cutoff value≥0.48) as the optimal noninvasive index for predicting MASLD, with strong performance in both training and validation set. Additionally, the combination of WHtR and lipid accumulation product (LAP) was selected as an optimal serial test to improve the positive predictive value, with a LAP cutoff value of ≥668.22cm×mg/dL. Based on the obesity prevalence among 30provinces, three MASLD screening recommendations were proposed: 1) "Population-screening-recommended": For regions with an obesity prevalence ≥12.0%, where MASLD prevalence ranged from 5.0% to 21.5%; 2) "Resources-permitted": For regions with an obesity prevalence between 8.4% and 12.0%, where MASLD prevalence ranged from 2.3% to 4.4%; 3) "Population-screening-not-recommended": For regions with an obesity prevalence <8.4%, where MASLD prevalence is difficult to detect using our tool. Using our proposed cutoff for screening MASLD, the number of countries classified into the "Population-screening-recommended" and "Resources-permitted" categories increased from one and 11 in 1990 to 95 and 28 in 2022, respectively. WHtR might serve as a practical and accessible index for predicting pediatric MASLD. A WHtR value≥0.48 could facilitate early identification and management of MASLD in areas with obesity prevalence ≥12.0%. Furthermore, combining WHtR ≥0.48 with LAP ≥668.22cm×mg/dL is recommended for individual MASLD screening. Moreover, linking these measures with population obesity prevalence not only helps estimate MASLD prevalence but also indicates potential screening profits in regions at varying levels of obesity risk. This study was supported by grants from Capital's Funds for Health Improvement and Research (Grant No. 2022-1G-4251), National Natural Science Foundation of China (Grant No. 82273654), Major Science and Technology Projects for Health of Zhejiang Province (Grant No. WKJ-ZJ-2216), Cyrus Tang Foundation for Young Scholar 2022 (2022-B126) and Sino-German Mobility Programme (M-0015).

Small-scale fluidised bed flotation device for ore amenability testing

Fluidised bed flotation, such as with Eriez’s HydroFloat®, has demonstrated the ability to recover coarse particles up to 600 µm in size during sulphide flotation. The ability to perform flotation at coarse particle sizes provides significant benefits to the minerals processing industry, including energy savings in comminution and increased plant throughput.However, the smallest available fluidised bed flotation units require between 15 and 20 kg of sample for a single test and upwards of 100 kg of sample to conduct initial scoping studies for new ore feed material. This high sample requirement often prohibits the execution of small-scale flotation optimisation tests using this technology.The development of a small-scale fluidised bed flotation device is therefore vital to enable rapid and efficient testing for essential operations such as ore amenability and geometallurgical evaluation, circuit modelling and design, and routine metallurgical assessment.This work presents the design and development of a small-scale fluidised bed flotation device that uses 1–2 kg of sample per test. The work further outlines the testing methodology to achieve both reasonable and reproducible flotation results. Both the device and test methodology were demonstrated using two copper ore samples, and the flotation results generated were similar in form to laboratory batch testing using conventional flotation cells.

Multimodal assessment of high-risk human papillomavirus in sinonasal squamous cell carcinoma

High-risk human papillomavirus (hrHPV) is an emerging risk factor for sinonasal squamous cell carcinoma (SNSCC). The goal of this study was to assess the prevalence of hrHPV and subtype distribution in SNSCC and correlation with patient and clinical characteristics. This retrospective cohort study included 43 cases diagnosed with incident primary SNSCC at the University of Cincinnati Medical Center from 2010 to 2015. The prevalence of hrHPV was interrogated using a multi-assay approach that included p16 immunohistochemistry (IHC), RNA in-situ hybridization (ISH), and hrHPV DNA sequencing. The association of hrHPV with 5-year overall survival (OS) and 2-year disease-free survival (DFS) was assessed. Fourteen cases (32.6 %) were classified as hrHPV positive, based on the a priori definition of having either a positive RNAScope™ ISH test or hrHPV DNA and p16-positive IHC; 9 cases (20.9 %) were positive for all three tests. All cases that arose from an inverted sinonasal papilloma (ex-ISP) were negative for hrHPV. HPV16 was the most common subtype among hrHPV positive cases (58.8 %), followed by HPV18 (17.6 %). No significant association was observed between hrHPV and OS or DFS after adjusting for potential confounding. hrHPV is prevalent in a sizable fraction of SNSCC. Additional studies are needed to better elucidate the relationship with patient survival outcomes and determine the optimal testing modality for prognostication.

Green and efficient extraction process of flavonoids from sea buckthorn fruits by natural deep eutectic solvents aided with ultrasound

In recent years, with the advantages of environment friendly, natural deep eutectic solvents (NADES) have been gradually applied for the extracting bioactive compounds from natural products. In this study, NADES-12 (betaine-lactic acid, n/n, 1:2) was selected for the first time to extract flavonoids from sea buckthorn fruit after screening of 23 NADES. The optimal technical conditions of NADES combined with ultrasonic assisted extraction (UAE) were determined by single factor test and response surface optimization test. The results showed that the optimal process for the extraction of antioxidant components by NADES-12 was 37 min extraction time, 40 °C extraction temperature, 17 % (v/v) water content, 40 mL mg−1 liquid–solid ratio, 160 W ultrasonic power, and a maximum extraction rate of 5.248 mg g−1, and the extraction yield is 2.4 and 3.1 times that of 60 % ethanol and water. The sea buckthorn extract by NADES has antioxidant activity. The study proposes a green and efficient method for the extraction of bioactive components from sea buckthorn fruit and provides a valuable basis for the exploitation of other natural plants.

Self-flocculating Chlorella vulgaris: A high-efficiency purification mechanism of radioactive Th4+ in an aquatic environment

This study aimed to investigate the purification of radioactive thorium (Th4+) by Chlorella vulgaris in aquatic environments. Single-factor experiments and response surface optimization tests identified optimal purification conditions. The purification and metabolic response mechanisms of Chlorella to Th4+ were elucidated using physiological and biochemical analyses, three-dimensional excitation-emission matrix (3D-EEM) analysis, and metabolomic profiling. Increases in the Th4+ concentration caused Chlorella to self-flocculate, significantly improving the Th4+ purification efficiency. Under optimal conditions, the Th4+ purification efficiency for Th4+ in wastewater by Chlorella stabilized between 94.3 % and 98.2 %. Morphological analysis revealed that the purified Th4+ existed mainly in a stable residual state. Chlorella efficiently purified wastewater during treatment by regulating environmental pH, performing redox reactions, and utilizing extracellular polymeric substances (EPS) to interact with Th4+. Metabolomic analysis indicated that Chlorella adapted to the Th4+-contaminated environment and enhanced its purification function by adjusting the synthesis of metabolites, such as carbohydrates, nucleotides, and amino acids. Chlorella demonstrated a remarkable self-flocculation phenomenon and a high-efficiency purification capability for Th4+, offering new possibilities for environmental remediation. Its purification mechanism involves environmental regulation, redox reactions, and complex metabolic adjustments. The results presented here provide theoretical support for environmental remediation using Chlorella.

Paired comparison of the analytical performance between the Oncomine™ Comprehensive Assay v3 and whole-exome sequencing of ovarian cancer tissue

BackgroundNext-generation sequencing (NGS) has been implemented in clinical oncology as a personalized medicine tool to identify targetable genetic alterations and to guide treatment decisions. However, the optimal NGS test strategy and target genes for clinical use are still being discussed. The aim was to compare the performance of the Oncomine™ Comprehensive Assay v3 (OCAv3) (targeted gene panel) and whole-exome sequencing (WES) to investigate somatic single and multiple nucleotide variants and small indels in ovarian cancer patients.Methods and resultsGenomic DNA was isolated from fresh frozen samples of five high-grade serous (HGSC) and three clear cell ovarian (oCCC) cancer patients. Exome sequencing libraries were prepared by using the Ion AmpliSeq Exome RDY kit, whereas libraries for OCAv3 were prepared using by Ion AmpliSeq™ Library Kit Plus. Sequencing was performed using the Ion S5XL System (Thermo Fisher Scientific). When including only variants classified as pathogenic, likely pathogenic or unknown significance based on ClinVar database verdicts and comparing overlapping regions covered both by the OCAv3 assay and WES, 23 variants were detected by both assays. However, OCAv3 detected additionally two variants: ARID1A: p.Gln563Ter and TP53: p.Ser261ValfsTer84 that have not passed WES filtering criteria due to low coverage.ConclusionsWith the present treatment possibilities, OCAv3 panel testing provided higher diagnostic yield due to better coverage. Our study emphasizes that WES, although offering the potential to identify novel findings in genes not covered by OCAv3, might overlook variants in genes relevant for OC.

Real-world data on ALK rearrangement test in Chinese advanced non-small cell lung cancer (RATICAL): a nationwide multicenter retrospective study.

Anaplastic lymphoma kinase (ALK) test in advanced non-small cell lung cancer (NSCLC) can help physicians provide target therapies for patients harboring ALK gene rearrangement. This study aimed to investigate the real-world test patterns and positive rates of ALK gene rearrangements in advanced NSCLC. In this real-world study (ChiCTR2000030266), patients with advanced NSCLC who underwent an ALK rearrangement test in 30 medical centers in China between October 1, 2018 and December 31, 2019 were retrospectively analyzed. Interpretation training was conducted before the study was initiated. Quality controls were performed at participating centers using immunohistochemistry (IHC)-VENTANA-D5F3. The positive ALK gene rearrangement rate and consistency rate were calculated. The associated clinicopathological characteristics of ALK gene rearrangement were investigated as well. The overall ALK gene rearrangement rate was 6.7% in 23,689 patients with advanced NSCLC and 8.2% in 17,436 patients with advanced lung adenocarcinoma. The quality control analysis of IHC-VENTANA-D5F3 revealed an intra-hospital consistency rate of 98.2% (879/895) and an inter-hospital consistency rate of 99.2% (646/651). IHC-VENTANA-D5F3 was used in 53.6%, real-time polymerase chain reaction (RT-PCR) in 25.4%, next-generation sequencing (NGS) in 18.3%, and fluorescence in-situ hybridization (FISH) in 15.9% in the adenocarcinoma subgroup. For specimens tested with multiple methods, the consistency rates confirmed by IHC-VENTANA-D5F3 were 98.0% (822/839) for FISH, 98.7% (1,222/1,238) for NGS, and 91.3% (146/160) for RT-PCR. The overall ALK gene rearrangement rates were higher in females, patients of ≤ 35 years old, never smokers, tumor cellularity of > 50, and metastatic specimens used for testing in the total NSCLC population and adenocarcinoma subgroup (all P < 0.05). This study highlights the real-world variability and challenges of ALK test in advanced NSCLC, demonstrating a predominant use of IHC-VENTANA-D5F3 with high consistency and distinct clinicopathological features in ALK-positive patients. These findings underscore the need for a consensus on optimal test practices and support the development of refined ALK test strategies to enhance diagnostic accuracy and therapeutic decision-making in NSCLC.

Design and Experiment of In-Situ Bionic Harvesting Device for Edible Sunflower

In view of the low degree of mechanization and poor quality of harvesting of edible sunflower after drying, an in situ bionic harvesting device was designed, which can achieve low-loss harvesting of edible sunflower without removing the edible sunflower disc. According to the physical characteristics of sunflower stalks in the field, influencing factors of in situ low-loss feeding were obtained, and the structural parameters of the in situ feeding mechanism were determined. Based on bionic technology and static analysis, the influencing factors on the performance of the bionic threshing mechanism were obtained. By analyzing the mechanical characteristics of edible sunflower seed, the operation parameters of the seed collection mechanism were determined. Based on the structural analysis results of the harvesting device, a response surface optimization test was carried out. The test results show that when the average rotation speed of the bionic loosening roller was 113.57 rpm, the average rotation speed of the simulated artificial striking roller was 230.80 rpm, the average forward speed of the harvesting device was 0.58 m/s, the working quality of the harvesting device was the best, the seed loss rate was 2.12%, and the edible sunflower disc threshing rate was 98.96%. A field verification test further confirms that under the optimal working parameters, the relative deviation between test indexes and response surface optimization test results was less than 2%. During the operation process, the movement of key components of the harvesting device was coordinated and stable. The research results can provide new ideas for the mechanized harvesting of the edible sunflower disc after drying.

Utilization of torrefied date stones with synthesized TiO2 nanoparticles for promoting humidity sensing of PVA/PVP nanocomposites for smart food packaging and biomedical applications

Fabricating smart and active packaging films with affordable cost has become the first demand for serving to market needs, particularly after COVID-19 disaster, for ensuring food security. Therefore, the broader goal of this work was to improve intelligent and active packaging films having humidity-sensing and antibacterial properties for biodegradable poly vinyl alcohol (PVA)/Polyvinylidene (PVP) reinforced with torrefied date stones (DS) and lethal amounts of TiO2 nanoparticles by a solvent-casting approach. Various concentrations of TiO2 NPs (i.e. 0.05, 0.15, and 0.30 %) in presence of 10 % torrefied DS (biochar) as a fixed content were used to fabricate PVA/PVP nanocomposite films. FT-IR spectra were utilized to monitor the DS functional groups before and after torrefaction at 270 °C. The crystal structure of synthesized TiO2 NPs as well as its impact on the PVA/PVP nanocomposites were verified by X-ray diffraction (XRD). The XRD micrographs and FT-IR spectra-based biofilms showcased that the degree of crystallinity and dispersibility of filler in the blend matrix were promoted, when the nanoparticles added. This was evidenced by SEM images. Mechanical testing also manifested that a great improvement in the tensile properties were noticed, especially at 0.30 % NPs and found the tensile strength reached ∼33 MPa compared to PVA/PVP blank (∼23.70 MPa) or PVA/PVP-BC (∼18.20 MPa). The humidity sensing properties were performed over a wide span of relative humidity from (11–97 % RH) and frequency (50 Hz-10 kHz). The data manifested that 100 Hz was the optimum testing frequency. Moreover, the gotten findings from humidity-sensing tests at 100 Hz exhibited that the sensor containing 0.15 % TiO2 NPs had higher sensitivity and could be considered as a nano-sensor for smart food packaging. Furthermore, the impact of TiO2 NPs on antibacterial activity was investigated to probably use these films in active packaging with prolonged shelf-life of food products and other promising applications including biological area.

Optimal conditions, experimentation and drug testing.

Optimal conditions, experimentation and drug testing.

Analysis and Comparison of Three Bending Tests on Phosphogypsum-Based Material According to Peridynamic Theory

Phosphogypsum-based materials have gained much attention in the field of road infrastructure from the economic and sustainable perspectives. The Three-point bending test, the Four-point bending test and the Semi-circular bending test are three typical test methods applied for fracture energy measurement. However, the optimal test method for fracture energy evaluation has not been determined for phosphogypsum-based materials. To contribute to the gap, this study aims to analyze and compare the three test methods for fracture energy evaluation of phosphogypsum materials based on the peridynamic theory. For this purpose, the load–displacement, vertical displacement–Crack Mouth Opening Displacement (CMOD) and fracture energy of the phosphogypsum-based materials were measured and calculated from the three test methods. The simulated load–displacement and vertical displacement–CMOD by PD numerical models, with different fracture energy as inputs, were compared to the corresponding tested values according to simulation error results. The results showed that the Four-point bending test led to minimized errors lower than 0.189 and indicators lower than 0.124, demonstrating the most optimal test method for the fracture energy measurement of phosphogypsum-based material. The results of this study can provide new methodological references for the selection of material fracture energy measurement tests.

Salivary metabolomic biomarkers for esophageal and gastric cancers by liquid chromatography-mass spectrometry.

Early detection of esophageal and gastric cancers is essential for patients' prognosis; however, optimal noninvasive screening tests are currently not available. Saliva is a biofluid that is readily available, allowing for frequent screening tests. Thus, we explored salivary diagnostic biomarkers for esophageal and gastric cancers using metabolomic analyses. Saliva samples were collected from patients with esophageal (n = 50) and gastric cancer (n = 63), and patients without cancer as controls (n = 20). Salivary metabolites were analyzed by liquid chromatography-mass spectrometry to identify salivary biomarkers. We also examined the metabolic profiles of gastric cancer tissues and compared them with the salivary biomarkers. The sensitivity of the diagnostic models based on salivary biomarkers was assessed by comparing it with that of serum tumor markers. Additionally, using postoperative saliva samples collected from patients with gastric cancer, we analyzed the changes in the biomarkers' concentrations before and after surgery. Cytosine was detected as a salivary biomarker for gastric cancer, and cytosine, 2-oxoglutarate, and arginine were detected as salivary biomarkers for esophageal cancer. Cytidine, a cytosine nucleotide, showed decreased concentrations in gastric cancer tissues. The sensitivity of the diagnostic models for esophageal and gastric cancers was 66.0% and 47.6%, respectively, while that of serum tumor markers was 40%. Salivary cytosine concentration increased significantly postoperatively relative to the preoperative value. In summary, we identified salivary biomarkers for esophageal and gastric cancers, which showed diagnostic sensitivity at least comparable to that of serum tumor markers. Salivary metabolomic tests could be promising screening tests for these types of cancer.

Optimizing feedforward neural networks using a modified weighted mean of vectors: Case study chemical datasets

This paper proposes a modified version of the weighted mean of vectors algorithm (mINFO), which combines the strengths of the INFO algorithm with the Enhanced Solution Quality Operator (ESQ). The ESQ boosts the quality of the solutions by avoiding optimal local values, verifying that each solution moves towards a better position, and increasing the convergence speed. Furthermore, we employ the mINFO algorithm to optimize the connection weights and biases of feedforward neural networks (FNNs) to improve their accuracy. The efficacy of FNNs for classification tasks is mainly dependent on hyperparameter tuning, such as the number of layers and nodes. The mINFO was evaluated using the IEEE Congress on Evolutionary Computation held in 2020 (CEC’2020) for optimization tests, and ten chemical data sets were applied to validate the performance of the FNNs classifier. The proposed algorithm’s results have been evaluated with those of other well-known optimization methods, including Runge Kutta optimizer’s (RUN), particle swarm optimization (PSO), grey wolf optimization (GWO), Harris hawks optimization (HHO), whale optimization algorithm (WOA), slime mould algorithm (SMA) and the standard weighted mean of vectors (INFO). In addition, some improved metaheuristic algorithms. The experimental results indicate that the proposed mINFO algorithm can improve the convergence speed and generate effective search results without increasing computational costs. In addition, it has improved the FNN’s classification efficiency.

Improvement of mechanical behavior of cemented soil reinforced with waste sisal fibers: An optimal selection and modification research

In response to escalating environmental concerns, this study explored the use of sisal fiber as a sustainable alternative to traditional cement or synthetic fibers for soft soil stabilization. An optimal selection test was conducted to determine the optimal sisal fiber characteristics and their impact on the mechanical performance of cemented soil. The findings indicated that incorporating sisal fibers into cemented soil inhibits crack propagation, thereby enhancing its strength and ductility. A significant improvement was achieved by incorporating optimal fiber parameters (content = 0.4 %, length = 11 mm) into the cemented-soil, the compressive strength reached 4.4 MPa (by 29.4 %). In addition, to further improve the work performance of sisal fiber-cemented soil (SFCS), alkaline and acetylation treatments were applied, respectively, to prevent volume instability and degradation of sisal fiber. The study also evaluated the effects of these modification methods on the physical properties of sisal fiber and the strength of sisal fiber-cemented soil (SFCS). The results showed that a 6 % NaOH treatment was determined to be the most effective modification method, reducing the moisture affinity of sisal fiber, improving fiber-matrix bonding, and consequently enhancing the mechanical properties of SFCS (by 18.7 %). However, it should be noted that an excessively high concentration may adversely affect fiber properties, negatively impacting the strength of SFCS (by up to 11.59 %).

Performance Optimization and Simulation Test of No-Tillage Corn Precision Planter Based on Discrete Element Method (DEM)

In order to test the influence of the structural design of a no-tillage corn precision planter on vibration stability performance, a vibration model was constructed with the help of MATLAB/Simulink, and it was concluded that the vibration response curve of the no-tillage corn precision planter was relatively smooth. Based on the theory of the discrete element method (DEM), taking the planting apparatus of the no-tillage corn precision planter as the research object, firstly, a DEM single-factor test was carried out to investigate the effects of the slot inclination angle, number of slots, and rotational speed of the planter plate on the disturbance performance. Then, a three-factor, three-level orthogonal test was conducted with the maximum amount of seed discharging, the minimum average speed, and the minimum average kinetic energy as the final optimization objectives, and the qualified rate of seed discharging and the leakage rate as the evaluation indexes. The results show that the larger the inclination angle, the higher the number of slots, and the faster the rotational speed, the more violent the particle disturbance. At the same time, when the slot inclination angle of the planter plate is 60°, the number of slots is 20, and the rotational speed is 55 rpm, the seed discharge efficiency is the highest, at this time, the seed discharge qualification rate of maize particles is 95%, and the leakage rate is 3%; the results of this test can provide technical support for the research of the same kind of precision sowing equipment in the future.

Capturing the dilution effect of risk‐based grouping with application to COVID‐19 screening

AbstractWe investigate the problem of screening a large population for an infectious disease (i.e., classifying subjects as positive or negative) using group testing while considering important test and population‐level characteristics. Group testing, in which multiple samples are pooled together into a master sample and tested simultaneously, has the potential to significantly expand screening efforts, and, owing to the COVID‐19 pandemic, the topic has seen a surge of interest recently. In this paper, we construct optimal group testing designs that consider a heterogeneous population (i.e., with subject‐specific risk), imperfect tests, and while also modeling the dilution effect of grouping (a phenomenon in which the test accuracy of the master sample is affected by the concentration of the virus in the pool), which is often ignored in the literature. We conduct an exhaustive analysis under both a general dilution function and a specific (yet still calibratable) form of the dilution function. Our analytical results of the resulting challenging optimization problems unveil key structural properties that hold in an optimal solution, which we utilize to construct efficient solution schemes. We complement the analysis with two case studies, one on the screening of blood for the Hepatitis B Virus and the other on the screening of subjects for COVID‐19. Our results reveal significant benefits over current practices, individual testing, as well as prior studies that ignore the dilution effect. Such results underscore the importance of incorporating both test and population‐level characteristics into the modeling framework.

Enhancing Reptile search algorithm with shifted distribution estimation strategy for coverage optimization in wireless sensor networks

The rapid development of the Internet of Things (IoT) has extensively promoted the development of Wireless Sensor Networks (WSNs), an essential technology for series displaying perception and data collected from the physical world. In densely distributed areas, sensor nodes are unevenly distributed, which leads to the network coverage build-up and the consequent efficiency and effectiveness of WSNs. To address this issue, this paper proposes a new method for WSN coverage optimization based on the Reptile Search Algorithm (RSA). In the past, the Reptile Search algorithm has been used to solve optimization problems, which means it can improve different processes. However, the RSA needs to track the trajectory of optimal individuals in each iteration, which will ignore non-optimal individuals' bioeconomic characteristics. Therefore, the paper introduces a distribution estimation strategy into the RSA framework, which can fully mine all the positional information hidden in the entire population. We selected several functions as optimization test benchmark functions to evaluate the feasibility of the proposed method. This paper compares the proposed improved RSA with the standard RSA and some traditional optimization algorithms. The result has been calculated through a series of experiments on network coverage optimization, and the change of parameters also determines the effect of the RSA in the optimization of network coverage. The simulated results of the three similar network coverage optimization experiments show that the improved RSA can be used efficiently within different scenarios.

Optimized Design of Material Preparation for Cotton Linters-Based Carbon Black Dispersion Stabilizers Based on Response Surface Methodology.

Carbon black particles possess dimensions on the nanometer or sub-nanometer scale. When utilized, these particles have a tendency to aggregate, which compromises their stability under storage conditions. To address this issue, a dispersant was prepared using cotton short fibers as raw materials through etherification and graft polymerization with acrylamide (AM) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) as raw materials. The dispersant was then used to disperse carbon black to test its dispersing performance. A response surface optimization test was utilized to ascertain the influence of AMPS monomer mass, AM monomer mass, and potassium persulfate (KPS) initiator mass on the dispersibility of carbon black during dispersant preparation, and a set of optimal preparation conditions were obtained. The dispersion stability of carbon black in water was assessed using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), elemental analysis (EA), thermogravimetric analysis (TG), zeta potential analysis, high magnification scanning electron microscopy (SEM), and contact angle measurements. Results revealed that the optimum mass ratio of carboxymethyl cellulose (CMC) to AMPS to AM was 1:0.69:1.67, with the KPS initiator comprising 1.56% of the total monomer mass. By incorporating the dispersant at a concentration of 37.50%, the particle size of carbon black particles was observed to decrease from 5.350 μm to 0.255 μm, and no agglomeration of carbon black particles occurred even after 3 weeks of storage.

A class of sequential multi-hypothesis tests

In this article, we deal with sequential testing of multiple hypotheses. In the general scheme of construction of optimal tests based on the backward induction, we propose a modification which provides a simplified (generally speaking, and suboptimal) version of the optimal test, for any particular criterion of optimization. We call this DBC version (the one with Dropped Backward Control) of the optimal test. In particular, for the case of two simple hypotheses, dropping backward control in the Bayesian test produces the classical sequential probability ratio test (SPRT). Similarly, dropping backward control in the modified Kiefer-Weiss solutions produces Lorden’s 2-SPRTs. In the case of more than two hypotheses, we obtain in this way new classes of sequential multi-hypothesis tests, and investigate their properties. The efficiency of the DBC-tests is evaluated with respect to the optimal Bayesian multi-hypothesis test and with respect to the matrix sequential probability ratio test (MSPRT) by Armitage. In a multihypothesis variant of the Kiefer-Weiss problem for binomial proportions the performance of the DBC-test is numerically compared with that of the exact solution. In a model of normal observations with a linear trend, the performance of the DBC-test is numerically compared with that of the MSPRT. Some other numerical examples are presented. In all the cases the proposed tests exhibit a very high efficiency with respect to the optimal tests (more than 99.3% when sampling from Bernoulli populations) and/or with respect to the MSPRT (even outperforming the latter in some scenarios).

Genetically-Based Active Flow Control And PIV Measurements Of A Circular Cylinder Wake

In the field of flow manipulation, considerable attention is devoted to controlling the wake of bluff bodies, which are characterized by the phenomenon of vortex shedding. Specifically, the control of the wake behind a single circular cylinder has garnered substantial research interest due to its engineering applications, such as reducing aerodynamic drag in the automotive and aerospace industries. Therefore, in the current work, through the application of the planar PIV technique, the fluid dynamic behavior of a circular cylinder wake controlled via synthetic jets (SJ) and Machine Learning (ML) methods is analyzed and discussed. ML algorithms are used to determine the optimal voltage signal for the loudspeaker, which effectively minimizes the aerodynamic drag of the cylinder. This approach overcomes the limitations associated with the a priori assumption of a parametric waveshape. In particular, the gradient-enriched machine learning control (gMLC) algorithm is chosen as optimization tool to search the best open-loop control policy for aerodynamic drag reduction. The cost function for this problem has been defined considering both the drag reduction contribution and the electrical power spent for the actuation. Initial optimization tests are performed by minimizing a cost function considering only the reduction in aerodynamic drag. Subsequently, a term related to the electrical power consumption for actuation is incorporated into the cost function. Once obtained the optimal control policies for these cases (hereinafter renamed CC1 and CC2, respectively), the physical mechanism responsible for reducing the aerodynamic drag is investigated more closely by analyzing the effect of the control laws on the turbulent flow statistics. Figure 1 reports a comparative assessment of the CC1 and CC2 with the baseline configuration and the configuration controlled by a sinusoidal law (CCS). The baseline configuration is characterized by an extended region of localized turbulent fluctuations in the far wake, where the time-averaged signature of von Kármán vortices is found. In contrast, all the controlled configurations show a global reduction in wake turbulence, with a peak of turbulent energy at the rear stagnation point due to the momentum injection from the SJ actuator. Notably, the CCS and CC2 configurations share similar flow field morphologies, while the CC1 configuration shows a greater reduction in turbulent fluctuations compared to the other controlled cases. This control law also achieves the largest drag reduction among all configurations studied reporting a 9.7% of drag reduction, compared to CCS and CC2, which exhibit similar reductions of 8.4% and 8.5%, respectively. Therefore, the optimization procedure has proven the capability of finding control policies able to outperform the traditional sinusoidal control widely studied in literature.