Fractional Factorial Experiment Research Articles

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine

BackgroundMetabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed. ResultsSystematic optimization was performed using fractional factorial experiments for both serum (n=57) and urine (n=24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n=76) and untargeted (n=1,949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2≥0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n=69) and untargeted (n=2,348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n=41 significant metabolites for serum, and n=55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y)>0.95, Q2(Y)>0.65, p-value<0.001 for both matrices). SignificanceThis study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

Empirical Development of a Behavioral Intervention for African American/Black and Latino Persons with Unsuppressed HIV Viral Load Levels: An Application of the Multiphase Optimization Strategy (MOST) Using Cost-Effectiveness as an Optimization Objective.

We used results from an optimization randomized controlled trial which tested five behavioral intervention components to support HIV antiretroviral adherence/HIV viral suppression, grounded in the multiphase optimization strategy and using a fractional factorial design to identify intervention components with cost-effectiveness sufficiently favorable for scalability. Results were incorporated into a validated HIV computer simulation to simulate longer-term effects of combinations of components on health and costs. We simulated the 32 corresponding long-term trajectories for viral load suppression, health related quality of life (HRQoL), and costs. The components were designed to be culturally and structurally salient. They were: motivational interviewing counseling sessions (MI), pre-adherence skill building (SB), peer mentorship (PM), focused support groups (SG), and patient navigation (short version [NS], long version [NL]. All participants also received health education on HIV treatment. We examined four scenarios: one-time intervention with and without discounting and continuous interventions with and without discounting. In all four scenarios, interventions that comprise or include SB and NL (and including health education) were cost effective (< $100,000/quality-adjusted life year). Further, with consideration of HRQoL impact, maximal intervention became cost-effective enough to be scalable. Thus, a fractional factorial experiment coupled with cost-effectiveness analysis is a promising approach to optimize multi-component interventions for scalability. The present study can guide service planning efforts for HIV care settings and health departments.

Mid-infrared emission of germanium-tin films produced by sputtering

In this work, the synthesis of germanium-tin (GeSn) films by magnetron sputtering is reported. A fractional factorial experiment was conducted; the varied factors were temperature, power applied to Ge target by a radio-frequency source, and power applied to the Sn target by a direct-current source. Vibrational modes, film composition, morphology, deposition rate, dark conductivity, Raman spectra, and Fourier-transform infrared (FTIR) spectra of the GeSn films were analyzed. Mid-infrared spectrum of emission and absorption was obtained by FTIR electroluminescence (EL) spectroscopy in the range of 400–4000cm−1, thermal emission was monitored by a FLIR camera in the range of 8–14μm, and power emitted from the GeSn films was measured in the range of 2.7–5.3μm by means of a InAsSb photodetector; results obtained by these approaches at room temperature and low-field bias were consistent. Sample Ge0.71Sn0.29 exhibited Ge Raman crystalline fraction of 85%; from FTIR EL spectrum were observed peaks of absorption located at 1084, and 606 cm−1 that was attributed to Si−Si bonds from the c-Si substrate, as well as broadband attenuation of 2% in the range of 1500−3500cm−1, this behavior was associated to the self-heating of this sample at 90 °C. Sample Ge0.3Sn0.7 showed Raman crystalline fraction of 16 and 22% for Ge and Sn, respectively; from FTIR EL spectrum were observed peaks of emission located at 2.74 μm (0.452 eV) and 6.66 μm (0.186 eV), as well as broadband emission in the range of 600–2000 cm−1 attributed to Planck’s law at a temperature of 45 °C; these results were correlated to the proper content of Ge and Sn, fluctuating current, and polymorphic morphology of this sample.

PRACTICAL APPLICATION OF A FRACTIONAL FACTOR EXPERIMENT FOR ASSESSING THE INFLUENCE OF FACTORS ON THE SENSITIVITY OF A CAPACITIVE HUMIDITY SENSOR OF A TWO-LAYER STRUCTURE

The work uses a fractional factorial experiment in order to reduce the number of experiments. Capacitive humidity sensors of a two-layer structure made on a sitall substrate served as experimental samples. Hygroscopic salt NaCl was used to create a moisture-sensitive layer that would perform the function of a dielectric. Solutions of this salt with concentrations of 0,89 mol/l and 5,33 mol/l were applied by spraying on the surface of capacitive humidity sensors with thicknesses of 5,0 μm and 10.0 μm. In order to prevent the drop of the dew point, a protective layer was created − it is a moisture-absorbing polymethyl methacrylate film with thicknesses of 40 μm and 80 μm. According to the Cochrane’s test, it is proved that the fractional factorial experiment is reproducible. Using regression analysis, a quantitative assessment of the influence of factors on the sensitivity of the capacitive humidity sensor of the two-layer structure was carried out. Based on the developed regression equation, it was established that the concentration of the NaCl salt solution significantly affects the sensitivity of the capacitive humidity sensor of the two-layer structure. Significant coefficients of the regression equation were determined using the Student's test. Adequacy of the adjusted regression equation to the results of the factorial experiment was proved using Fisher's test. Based on the regression equation on the scale of real factors, which contributes to the optimization of the humidity sensor manufacturing parameters, it was established that the sensitivity of the capacitive humidity sensor of the two-layer structure depends on such factors as the thickness of the protective layer and the concentration of the NaCl salt solution. However, the sensitivity of the capacitive humidity sensor of the two-layer structure is significantly affected by the concentration of the hygroscopic NaCl salt solution. The highest sensitivity of 2,46 nF/% is provided with the following optimal parameters of the manufacturing process of the capacitive humidity sensor of the two-layer structure: the concentration of the hygroscopic NaCl salt solution is 5,33 mol/l, the thickness of the protective layer is 80 μm. Considering that the thickness of the moisture-sensitive layer does not significantly affect the sensitivity of the capacitive humidity sensor, the thickness of this layer can be taken in the range from 5,0 μm to 10,0 μm.

Performance evaluation of a simple electrochemical treatment model for saline wastewaters: Part B

This paper investigated the performance of the electrochemical treatment technique in removing chloride from saline wastewater (brine) with the critical objective of purifying the wastewater, evaluated the efficacies of selected mathematical models and particular attention to selected polynomial regression models as a follow-up to previous studies. The saline wastewaters were prepared and subjected to electrochemical treatment using developed carbon–resin (anode) and aluminium (cathode) electrodes. Electrochemical treatment of the synthesised saline wastewaters (between 10 x 10^3 mg/l and 40 x 10^3 mg/l of chloride) was conducted on a laboratory scale. The influences of selected or picked-out operational factors on the functioning or efficacy of the electrochemical purification process of the wastewater were monitored using fractional factorial experiments. Three mathematical models were formulated using Microsoft Excel Solver and evaluated statistically. The study revealed that the current, the time and the interval distance between the electrodes were significant and vital factors that impacted on the performance of the electrochemical purification treatment of brine. The factors with negative special effects on the performance of the treatment process of brine were separation distance between the electrodes, pH, the depth of the electrode, the initial and primary concentration of the chloride and the flow and discharge rate of the wastewater. The performances or efficacy of the polynomial regression models in predicting the performance of the treatment technique were with average errors of 2.99 %, 2.97 % and 2.94% and accuracy of 97.01 %, 97.03 % and 97.06 % for Models A, B and C, respectively. It was concluded that the electrochemical treatment of brine with carbon-resin electrodes is efficient in removing chloride from brine and the selected models predicted the performance of the treatment technique well.

Tourist choice of sustainable hot springs tourism under post‐COVID‐19 pandemic period: A case in Colorado

AbstractHot springs tourism has increasingly attracted tourists who pursue wellness and harmony with the natural environment. This paper investigates how four sustainability‐related attributes influence tourist choice and estimates their marginal willingness to pay for Colorado hot springs tourism under the post‐COVID‐19 pandemic period. A fractional factorial choice experiment design and conditional logit model were used to analyze the choice data of 303 retained respondents collected from the online surveys. The results show the importance of sustainability‐related attributes on tourist choice and suggest the hot springs tourism sector improves destination sustainability to maintain market competitiveness under the post‐COVID‐19 pandemic period.

Using the multiphase optimization strategy to adapt cognitive processing therapy (CPT MOST): study protocol for a randomized controlled factorial experiment

BackgroundApproximately ten percent of US military veterans suffer from posttraumatic stress disorder (PTSD). Cognitive processing therapy (CPT) is a highly effective, evidence-based, first-line treatment for PTSD that has been widely adopted by the Department of Veterans Affairs (VA). CPT consists of discrete therapeutic components delivered across 12 sessions, but most veterans (up to 70%) never reach completion, and those who discontinue therapy receive only four sessions on average. Unfortunately, veterans who drop out prematurely may never receive the most effective components of CPT. Thus, there is an urgent need to use empirical approaches to identify the most effective components of CPT so CPT can be adapted into a briefer format.MethodsThe multiphase optimization strategy (MOST) is an innovative, engineering-inspired framework that uses an optimization trial to assess the performance of individual intervention components within a multicomponent intervention such as CPT. Here we use a fractional factorial optimization trial to identify and retain the most effective intervention components to form a refined, abbreviated CPT intervention package. Specifically, we used a 16-condition fractional factorial experiment with 270 veterans (N = 270) at three VA Medical Centers to test the effectiveness of each of the five CPT components and each two-way interaction between components. This factorial design will identify which CPT components contribute meaningfully to a reduction in PTSD symptoms, as measured by PTSD symptom reduction on the Clinician-Administered PTSD Scale for DSM-5, across 6 months of follow-up. It will also identify mediators and moderators of component effectiveness. DiscussionThere is an urgent need to adapt CPT into a briefer format using empirical approaches to identify its most effective components. A brief format of CPT may reduce attrition and improve efficiency, enabling providers to treat more patients with PTSD. The refined intervention package will be evaluated in a future large-scale, fully-powered effectiveness trial. Pending demonstration of effectiveness, the refined intervention can be disseminated through the VA CPT training program.Trial registrationClinicalTrials.gov NCT05220137. Registration date: January 21, 2022.

Companion Animal Cadaver Donation for Teaching Purposes at Veterinary Medicine Colleges: A Discrete Choice Experiment

Veterinary training programs rely on animal cadavers for a variety of important educational activities, yet ethical sourcing can present considerable challenges. Public sentiment has rendered traditional sources (e.g., euthanized shelter animals or purpose-bred animals) increasingly tenuous throughout the United States, leaving many schools to search for alternatives. One such alternative is to establish a cadaver donation program, with a handful of institutions implementing such programs in recent years. Still, there have been few to no studies evaluating the factors that influence pet owners’ decisions about whether to participate that could inform the establishment of such programs to date. In the present study, a nationally (United States) representative sample of current and potential dog and cat owners was asked to complete a survey capturing various demographic factors as well as their existing attitudes toward both veterinary medicine and veterinary education in addition to selecting among hypothetical cadaver donation programs with varying attribute levels in a blocked, orthogonal, fractional factorial discrete choice experiment to determine the characteristics that correlate with higher participation rates. Although initial interest was strong, our results suggest that younger pet owners, individuals with more formal education, and individuals with positive relationships with their current veterinarian are most likely to participate in a donation program. Concerningly, however, dog owners were somewhat less likely than other respondents to participate. The return of pet ashes was the most important attribute to respondents, suggesting that cadaver donation administrators should consider inclusion of this service to maximize participation.

Investigation of Active Ingredients Within Internet-Delivered Cognitive Behavioral Therapy for Depression

There is limited understanding of how complex evidence-based psychological interventions such as cognitive behavioral therapy (CBT) for depression work. Identifying active ingredients may help to make therapy more potent, brief, and scalable. To test the individual main effects and interactions of 7 treatment components within internet-delivered CBT for depression to investigate its active ingredients. This randomized optimization trial using a 32-condition, balanced, fractional factorial optimization experiment (IMPROVE-2) recruited adults with depression (Patient Health Questionnaire-9 [PHQ-9] score ≥10) from internet advertising and the UK National Health Service Improving Access to Psychological Therapies service. Participants were randomized from July 7, 2015, to March 29, 2017, with follow-up for 6 months after treatment until December 29, 2017. Data were analyzed from July 2018 to April 2023. Participants were randomized with equal probability to 7 experimental factors within the internet CBT platform, each reflecting the presence vs absence of specific treatment components (activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, absorption, and self-compassion training). The primary outcome was depression symptoms (PHQ-9 score). Secondary outcomes include anxiety symptoms and work, home, and social functioning. Among 767 participants (mean age [SD] age, 38.5 [11.62] years; range, 18-76 years; 635 women [82.8%]), 506 (66%) completed the 6-month posttreatment follow-up. On average, participants receiving internet-delivered CBT had reduced depression (pre-to-posttreatment difference in PHQ-9 score, -7.79 [90% CI, -8.21 to -7.37]; 6-month follow-up difference in PHQ-9 score, -8.63 [90% CI, -9.04 to -8.22]). A baseline score-adjusted analysis of covariance model using effect-coded intervention variables (-1 or +1) found no main effect on depression symptoms for the presence vs absence of activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, or self-compassion training (posttreatment: largest difference in PHQ-9 score [functional analysis], -0.09 [90% CI, -0.56 to 0.39]; 6-month follow-up: largest difference in PHQ-9 score [relaxation], -0.18 [90% CI, -0.61 to 0.25]). Only absorption training had a significant main effect on depressive symptoms at 6-month follow-up (posttreatment difference in PHQ-9 score, 0.21 [90% CI, -0.27 to 0.68]; 6-month follow-up difference in PHQ-9 score, -0.54, [90% CI, -0.97 to -0.11]). In this randomized optimization trial, all components of internet-delivered CBT except absorption training did not significantly reduce depression symptoms relative to their absence despite an overall average reduction in symptoms. The findings suggest that treatment benefit from internet-delivered CBT probably accrues from spontaneous remission, factors common to all CBT components (eg, structure, making active plans), and nonspecific therapy factors (eg, positive expectancy), with the possible exception of absorption focused on enhancing direct contact with positive reinforcers. isrctn.org Identifier: ISRCTN24117387.

Optimization of a medium composition for the heterologous production of Alcaligenes faecalis penicillin G acylase in Bacillus megaterium

Penicillin G acylase (PGA) is a strategic enzyme in the production processes of beta-lactam antibiotics. High demand for β-lactam semisynthetic antibiotics explain the genetic and biochemical engineering strategies devoted towards novel ways for PGA production and application. This work presents a fermentation process for the heterologous production of PGA from Alcaligenes faecalis in Bacillus megaterium with optimization. The thermal stability from A. faecalis PGA is considerably higher than other described PGA and the recombinant enzyme is secreted to the culture medium by B. megaterium, which facilitates the separation and purification steps. Media optimization using fractional factorial design experiments was used to identify factors related to PGA activity detection in supernatant and cell lysates. The optimized medium resulted in almost 6-fold increased activity in the supernatant samples when compared with the basal medium. Maximum enzyme activity in optimized medium composition achieves values between 135 and 140 IU/ml. The results suggest a promising model for recombinant production of PGA in B. megaterium with possible extracellular expression of the active enzyme.

Field measures of strengthen plant-microbial remediation of PAHs-FQs compound pollution.

In this study, five PAHs (benzo [b] fluoranthene (BbF), phenanthrene (Phe), fluoranthene (Flu), fluorene (Fl), benzo [A] pyrene (Bap)), and five FQs (ofloxacin (OFL), enrofloxacin (ENR), ciprofloxacin (CIP), norfloxacin (NOR), lomefloxacin (LOM)) were selected as ligands; peroxidase (1NML) was selected as receptor degrading protein. In the plant-microbial degradation, the factors with significant inhibitory effects are NOR, Bap, CIP, ENR, OFL, Flu, LOM, Phe, Fl, and BbF by the fractional factorial design experiment and molecular docking-assisted molecular dynamics methods. Using Taguchi experiment and molecular dynamics simulation methods, the main external field measures were designed and screened to effectively promote the degradation of PAHs-FQs under the combined pollution scenarios of Bap-CIP and BbF-NOR, respectively. The peroxidase mutation design plans with enhanced substrate affinity were then designed and screened using the DS software by predicting the virtual key amino acid of peroxidase. The novel biodegradable enzymes 2YCD-1, 2YCD-4, 2YCD-5, 2YCD-7, and 2YCD-9 had better structures and showed excellent degradability for PAHs and FQs. This study explored the degradation rules of the composite pollutants in the coexistence systems of multiple PAHs and FQs, providing the best external field measures for the control and treatment of the combined pollution effects of different PAHs and FQs. Overall, the current study has important practical significance for promoting the plant-microbial joint remediation of PAHs-FQs pollution and for reducing the combined pollution of PAHs and FQs in farmland systems.

Conspicuity of Various Colored Express Lane Delineators: Matching or Contrast?

Express lanes (ELs) are an increasingly accepted traffic management tool for congestion relief and traffic efficiency. White, yellow, and orange vertical delineators are typically used for lane separation and channelization applications. However, upcoming changes to sections of the Manual on Uniform Traffic Control Devices that would affect the current use of the orange retroreflective delineators will have a statewide impact on current and future ELs. The availability of a wide array of delineator colors and the potential range of application purposes brings into question this blanket requirement. The ineffective use of color in roadway design could lead to an increase in driving errors/response time, driver fatigue, loss of situational awareness, and increased workload. Driver perception and reaction time is shown to be affected by visual factors, such as color, luminance, distractions, and speed. The objective of this study is to determine the impact of color usage and other environmental and demographic factors on driver perception. A fractional factorial experiment was designed to study the EL delineator color selection using a driving simulator and an eye-tracking device. The potential factors included time of day (night versus day), visibility (high versus low), traffic density (high versus low), and road surface type (concrete versus asphalt). Some 176 subjects were selected to participate in the experiment. It was found that, in general, white was the quickest to be noticed, while black took the longest time to perceive. Furthermore, it was found that delineators were generally more noticeable under night-time conditions, likely because of the standard use of retroreflective striping on delineators.

ВЛИЯНИЕ РЕЖИМОВ ПРОЦЕССА МИКРОДУГОВОГО ОКСИДИРОВАНИЯ НА СТРУКТУРУ ФОРМИРУЕМЫХ ПОКРЫТИЙ

The effect of microarc oxidation process modes on porosity and thickness of coatings formed on an hypereutectic aluminum alloy was studied. The process factors were the concentration of liquid glass and caustic potassium in the electrolyte, as well as the installation capacity. A fractional factorial experiment of type 23-1 was planned.The study of the coating structure was carried out by processing images obtained using a scanning electron microscope in the JmageJ program. The influence of various process factors on the thickness and porosity of coatings was established.

Monoethanolamine Treatment of Fish Wastes and Salmon Guts to Increase It Palmitoylethanolamide and Anandamide Contents

This study was carried out to determine the palmitoylethanolamide (PEA) and arachidonoylethanolamide (AEA) or anandamide contents in selected fish wastes, treating the fish wastes with highest PEA and AEA with different concentration of monoethanolamine (MEA) solution, incubation temperature and time, as well as the ratio of MEA solution to fish waste to further increase its PEA and AEA contents.&#x0D; Based on the results of the preliminary experiment, a fractional factorial design experiments was done with 4 factors including MEA concentration, incubation time, incubation temperature and dosing ratio (MEA solution:salmon guts). The results showed that the MEA content ranged from 2.25 to 8.06 mg/g sample, the PEA content ranged from 17.4 to 300.2 µg/g sample while the AEA content ranged from 1.3 to 19.0 µg/g sample all on a wet weight basis of all the FD treated samples. The FD treated sample with the highest MEA, PEA and AEA using an MEA solution concentration of 250mM from pure MEA chemical, incubation time of 0.5 hour, incubation temperature of 6oC and a dose ratio of 6 mL MEA solution:100 g salmon guts. The MEA, PEA and AEA contents of the different samples were analysed using the Yates algorithm to determine which of the four factors were more important. The results showed that MEA, PEA and AEA contents were significantly affected by the concentration of MEA solution used in dosing the salmon guts, followed by the incubation time and then a slight effect of dosing ratio while the incubation temperature has no significant effect.

Construction of Optimal Split-Plot Designs for Various Design Scenarios

When performing fractional factorial experiments in a completely random order is impractical, fractional factorial split-plot designs are suitable options as an alternative. It is well recognized that the more there are lower order effects of interest at lower order confounding, the better the designs. From this viewpoint, this paper considers the construction of optimal regular two-level fractional factorial split-plot designs. The optimality criteria for two different design scenarios are proposed. Under the newly proposed optimality criteria, the theoretical construction methods of optimal regular two-level fractional factorial split-plot designs are then proposed. In addition, we also explore the theoretical construction methods of some optimal regular two-level fractional factorial split-plot designs under the widely adopted general minimum lower order confounding criterion.

Causal inference for multiple treatments using fractional factorial designs

AbstractWe consider the design and analysis of multi‐factor experiments using fractional factorial and incomplete designs within the potential outcome framework. These designs are particularly useful when limited resources make running a full factorial design infeasible. We connect our design‐based methods to standard regression methods. We further motivate the usefulness of these designs in multi‐factor observational studies, where certain treatment combinations may be so rare that there are no measured outcomes in the observed data corresponding to them. Therefore, conceptualizing a hypothetical fractional factorial experiment instead of a full factorial experiment allows for appropriate analysis in those settings. We illustrate our approach using biomedical data from the 2003–2004 cycle of the National Health and Nutrition Examination Survey to examine the effects of four common pesticides on body mass index.

Binary toxicity of polystyrene nanoplastics and polybrominated diphenyl ethers to Arctic Cyanobacteria under ambient and future climates

Cyanobacteria are the predominant biota in the Arctic. Interactive effects on Arctic cyanobacteria between climate-change-shifting parameters and anthropogenic contaminants are largely unknown. We utilized a fractional factorial experiment and Arctic cyanobacteria Pseudanabaena biceps Strain PCCC_O-153 to capture the complexity of interacting climate factors, nano-polystyrene (nano-PS) and 2,2´,4,4´-tetrabromodipenyl ether (BDE-47). The short-term binary toxicity of nano-PS and BDE-47 was then examined through experiments, toxicity units, and reference models. The toxic mechanism was further revealed through biochemical analyses and multivariate statistics. We found that BDE-47 and nano-PS had more hazardous effects than changing climate conditions. The mixture had antagonistic effects on PCCC_O-153, attributing to the aggregation of nano-PS, the adsorption of BDE-47, and the wrapping of both contaminants by released extracellular polymeric substances. Binary toxicity was caused by the chain reactions triggered by combining individual contaminants. Total protein was a sensitive target and positively correlated to chlorophyll pigment. Oxidative stress for the mixture mainly resulted from the presence of nano-PS. This is the first study to access the hazardous effects of a mixture of anthropogenic contaminants on Arctic cyanobacteria under ambient and future climates.

Improved Approximation Scales for Unreplicated Factorial Experiments

Assessing the sizes of active contrasts in un-replicated factorial and fractional factorial experiments by quick and powerful methods are required in analyzing the big data in various research areas of Human endeavors. One of the old methods based on Lenth (1989) is being used in some statistical and data analytical applications which is fast and less efficient. We propose a new class of tests which are simpler, faster, and more powerful using the location median-function ({psi }_{med}left({varvec{x}}right)) after being skipped one and/or two times. An empirical study of simulation experiments to compute the critical values, sizes and powers using various sample sizes demonstrate the superiority of our methods. The proposed methods are illustrated in examples which can be employed in various fields of research in conducting data analytics using high computing power and machine learning.

An effective statistical process control scheme for industrial environmental monitoring

One major source of environmental pollution is industrial effluents, especially the heavy metal pollutants, including zinc, in the wastewater discharged from manufacturing industries (hereinafter known as an environmental process). The safe disposal of such effluents into aquatic environments is very crucial and of great health and environmental concerns worldwide. To safeguard the quality of the receiving waters, continuous and effective monitoring of zinc in industrial effluents before discharging it into the environment is essential. However, the real-life environmental data are often skewed and do not follow the normal distribution. Therefore, classical statistical process monitoring techniques based on normality assumptions cannot be used directly to monitor the environmental processes. To overcome this limitation, this study designs an optimal X‾ scheme for monitoring non-normal zinc data in industrial effluents. This scheme minimizes the total cost, including quality and manpower costs, based on optimal deployment of manpower. The optimization process ensures that the false alarm rate of the monitoring scheme meets the allowable value. A fractional factorial experiment considering different design specifications shows that the proposed optimal X‾ scheme reduces the associated costs by about 69% and 36% compared to the basic X‾ and improved X‾ schemes, respectively. The robustness of the performance of the optimal X‾ scheme is further investigated under different non-normal, and process shift distributions. A sensitivity analysis is also conducted to explore the impact of the input parameters on the associated cost of the optimal X‾ scheme. Lastly, the design and application of the proposed optimal X‾ scheme are presented using real data on zinc content in the wastewater emitted from a steel production plant.

Split-Plot Designs with Few Whole Plot Factors Containing Clear Effects

Fractional factorial split-plot designs are widely used when it is impractical to perform fractional factorial experiments in a completely random order. When there are too many subplots per whole plot, or too few whole plots, fractional factorial split-plot designs with replicated settings of the whole plot factors are preferred. However, such an important study is undeveloped in the literature. This paper considers fractional factorial split-plot designs with replicated settings of the WP factors from the viewpoint of clear effects. We investigate the sufficient and necessary conditions for this class of designs to have clear effects. An algorithm is proposed to generate the desirable designs which have the most clear effects of interest. The fractional factorial split-plot design with replicated settings of the WP factors is analysed and the results are discussed.