Two-level Factorial Experiments Research Articles

Synergistic effects (adsorption and biodegradation) of Streptomyces hydrogenans immobilization on nano-reed biochar for further application in upflow anaerobic sludge blanket.

Water pollution due to wastewater is a serious issue that needs to be studied as many organic compounds are released from wastewater, affecting the ecosystem. Therefore, appropriate treatment methods should be used to prevent these effects. Phragmites australis biochar immobilized with bacteria was prepared in this study for use as an adsorbent in a pilot-scale up-flow anaerobic sludge blanket (UASB) to remove organic matter from wastewater in a buffalo farm. Combining reed biochar and immobilized Streptomyces hydrogenans introduces a synergistic effect: reed biochar serves as a substrate for microbial colonization and provides a conducive environment for microbial growth while Streptomyces hydrogenans, immobilized on the biochar, enhances the degradation of organic matter through its metabolic activities. Suitable techniques were employed, including infrared spectroscopy (FTIR) to determine the functional groups before and after adsorption, scanning electron microscopy (SEM) to determine the morphology of the composite before and after adsorption, X-ray diffraction (XRD) to examine the mineralogical changes through reflectometry, high-resolution diffraction and Brunauer-Emmett-Teller (BET) analyses to determine the surface area that always carried out by nitrogen adsorption/desorption technique based on the BET isotherm. Two-level factorial design experiments optimized using biochar, immobilized with bacteria, were employed to enhance the UASB performance. Chemical oxygen demand (COD) removal and biogas production were studied as a function of four experimental parameters: biochar dose, buffalo sludge dose, pH, and bacteria type. The buffalo sludge (manure) dose negatively affected the model's performance. The results showed better COD removal with Streptomyces hydrogenans S11 inoculation. The optimum biochar dose, buffalo sludge dose, and pH were 20 g L-1, 0%, and 7.5, respectively. The COD removal efficiency under these experimental conditions reached 92.70% with a biogas production of 5.0 mL. The experimental results of a validated point from the model were 90.80% for COD removal ratio and 4.80 mL for biogas production at 2 g L-1 biochar dose, 0% buffalo sludge dose, and pH 7.5 using Streptomyces hydrogenans S11 bacteria. A buffalo wastewater (BWW) anaerobic digestion experimental model was best fitted to the data under optimal conditions. This study aligns with the United Nations Sustainable Development Goals (SDGs), specifically SDG 6 (clean water and sanitation) and SDG 12 (responsible consumption and production). The implications of our work extend to large-scale applications, promising a greener and more sustainable future for wastewater treatment.

Bacterial Consortium-Mediated Hydrocarbon Degradation of Waste Engine Oils

The automotive and industrial activities are considered one of the important sources of pollution with the increasing amount of WEO released to the environment. One of the ways to solve this problem is through bioremediation. It is, however, challenging since used engine oil contains complex hydrocarbon compounds and is toxic towards the environment and living organisms. Biodegradation by single species bacterium is limited to a small range of hydrocarbon compounds. Hence, a better strategy is to use a synergistic action of different microbial members in a consortium. Different waste engine oils from the motorcycle workshop (MW), urban vehicle workshop (UVW), and heavy vehicle workshop (HVW) were tested for degradation by a bacterial consortium culture. A two-level factorial design experiment was carried out to evaluate the effect of different WEO and nitrogen concentrations towards the growth of the bacterial culture and hydrocarbon degradation in shake flask fermentation. The bacterial consortium culture grown in mineral salts medium (MSM) supplemented with MW (Viscosity, 82 mPa.s) was shown to exhibit the highest biomass with 0.37 (OD600) with 8% (v/v) WEO and 5 g/L nitrogen from ammonium chloride (NH4Cl). Pareto chart of biomass with WEO and nitrogen concentration showed a positive effect for MW and UVW, while a negative effect for HVW which was presumed due to the toxicity, higher complexity of hydrocarbon composition and higher viscosity of WEO from heavy vehicles. Subsequently, GC-MS analysis indicated the degradation of various polyaromatic hydrocarbon (PAH) and BTEX compounds such as naphthalene, benzene, and toluene in the three WEO samples. Assessment of cell hydrophobicity of the culture grown on all three WEO exhibited high cell hydrophobicity, with HVW showing the highest cell hydrophobicity of 81%. This suggests that the bacterial culture altered cell hydrophobicity to facilitate hydrocarbon uptake.

Optimizing the generation of mature bone marrow-derived dendritic cells in vitro: a factorial study design

BackgroundFactorial design is a simple, yet elegant method to investigate the effect of multiple factors and their interaction on a specific response simultaneously. Hence, this type of study design reaches the best optimization conditions of a process. Although the interaction between the variables is widely prevalent in cell culture procedures, factorial design per se is infrequently utilized in improving cell culture output. Therefore, we aim to optimize the experimental conditions for generating mature bone marrow-derived dendritic cells (BMDCs). Two different variables were investigated, including the concentrations of the inducing factors and the starting density of the bone marrow mononuclear cells. In the current study, we utilized the design of experiments (DoE), a statistical approach, to systematically assess the impact of factors with varying levels on cell culture outcomes. Herein, we apply a two-factor, two-level (22) factorial experiment resulting in four conditions that are run in triplicate. The two variables investigated here are cytokines combinations with two levels, granulocyte–macrophage colony-stimulating factor (GM-CSF) alone or with interleukin-4 (IL4). The other parameter is cell density with two different concentrations, 2 × 106 and 4 × 106 cells/mL. Then, we measured cell viability using the trypan blue exclusion method, and a flow cytometer was used to detect the BMDCs expressing the markers FITC-CD80, CD86, CD83, and CD14. BMDC marker expression levels were calculated using arbitrary units (AU) of the mean fluorescence intensity (MFI). ResultsThe current study showed that the highest total viable cells and cells yield obtained were in cell group seeded at 2 × 106 cells/mL and treated with GM-CSF and IL-4. Importantly, the expression of the co-stimulatory molecules CD83 and CD80/CD86 were statistically significant for cell density of 2 × 106 cells/mL (P < 0.01, two-way ANOVA). Bone marrow mononuclear cells seeded at 4 × 106 in the presence of the cytokine mix less efficiently differentiated and matured into BMDCs. Statistical analysis via two-way ANOVA revealed an interaction between cell density and cytokine combinations. ConclusionThe analysis of this study indicates a substantial interaction between cytokines combinations and cell densities on BMDC maturation. However, higher cell density is not associated with optimizing DC maturation. Notably, applying DoE in bioprocess designs increases experimental efficacy and reliability while minimizing experiments, time, and process costs.

Investigating the combined effects of role assignment and discussion timing in a blended learning environment

Asynchronous online discussion (AOD) is an essential component of blended learning, and role assignment and timing are two important discussion design considerations. With the purpose of improving blended learning through effective AOD design, this study conducted a two-level factorial experiment to explore the main effects and interaction effects of role assignment and timing on blended learning outcome and experiences. In addition, this experiment examined the influence of role assignment and timing on participants' social communication in AOD and the effects of timing on individual role performance in role-based discussion. A total of 114 participants in a blended course were randomly assigned to four experimental conditions: role-based pre-class discussion (n = 29), role-free pre-class discussion (n = 29), role-based post-class discussion (n = 28), and role-free post-class discussion (n = 28). The results showed that the role assignment strategy featured by initiator, supporter, and arguer has led to improved learning experiences in terms of affection, sense of community, and forum experiences, as well as enhanced social communication in AOD; while timing affected the enactment, contribution, and participation of assigned roles in role-based discussions. However, there was no significant interaction between the two AOD strategies. In general, role-based post-class AOD is recommended after face-to-face lesson because of the better learning experience and role performance.

Calibration and Experiments on the Parameters of the Bonding Particle Model of Eucommia ulmoides Oliver Samara Based on the Discrete Element Method

The calibration of the discrete element model of EUO samara was conducted in response to the lack of discrete element simulation models and parameters in the development of mechanical hulling technology and equipment of EUO samara. The EUO samara was modeled based on the Hertz–Mindlin with bonding model, and its relevant parameters were measured by physical experiments. Among them, maximum shear force was used as the evaluation index, virtual calibration experiments were conducted for the bonding parameters by the single-factor experiments, and the two-level factorial experiment, the steepest climb experiment, and the Box–Behnken response surface experiment were also used. The results showed that the relative error between the simulated and measured maximum shear force is 0.93%; the model and parameter calibration results established by this research can be used for discrete element simulation research, which is of guiding significance for the research and development of hulling equipment of EUO samara.

Dual-Orthogonal Arrays for Order-of-Addition Two-Level Factorial Experiments

A new class of orthogonal arrays called dual-orthogonal arrays is proposed in this paper to design order-of-addition two-level factorial experiments in which both component addition orders and component levels can be varied over treatments. Dual-orthogonal arrays can be viewed as an optimal combination of order-of-addition orthogonal arrays and two-level orthogonal arrays. Based on these two different concepts of orthogonality, when a compound model is used to fit the observed data, both pairwise order effects and component main effects can be estimated with optimal efficiency. Under the assumption of normality, these two kinds of parametric effects can also be inferred independently. A three-drug combination study is first used to show that dual-orthogonal arrays can be practical for real-world studies. Both combinatorial and computational methods are then introduced to construct dual-orthogonal arrays. Additionally, a design catalogue is generated for future work.

Design optimization of the gallium nitride high electron mobility transistor with graphene and boron nitride heat-spreading elements

The self-heating effect has long been a persistent issue for high electron mobility transistors based on gallium nitride due to their inherently poor heat dissipation capability. Although a wide variety of thermal management solutions has to date been proposed, the problem of the extremely non-uniform heat dissipation at the micrometer scale is still challenging. It has recently been demonstrated, however, that the performance of gallium nitride high electron mobility transistors can be substantially improved by the introduction of various heat-spreading elements based on graphene, boron nitride or diamond. In this paper, using numerical simulation, we carried out a design optimization procedure for a normally-off gallium nitride high electron mobility transistor containing both graphene and cubic boron nitride layers. First, a screening experiment based on a very economical Plackett-Burman design was performed in order to find the most critical geometric parameters that influence the dc characteristics. After that, a full two-level factorial experiment consisting of three factors was implemented and an optimized parameter set was yielded. By applying this set, the output power was increased by 11.35%. The combination of the most significant parameters does not include any factors related to the heat-spreading layers. Keywords: gallium nitride, high electron mobility transistor, optimization, Plackett-Burman design, screening experiment, self-heating.

Impact of role assignment and group size on asynchronous online discussion: An experimental study

Role assignment and group size are important design considerations for conducting effective asynchronous online discussion (AOD). While these two design considerations have been investigated separately in literature, few studies have examined their combined effects in AOD. To address this research gap, this study conducted a two-level factorial experiment to determine the main effect and interaction of role assignment and group size on AOD participation, learning experience, and learning achievement. A total of 112 participants from an undergraduate blended course were randomly assigned to four experimental conditions: role-based small-group (n = 27), role-based medium-group (n = 30), role-free small-group (n = 27), and role-free medium-group (n = 28). The ANOVA results showed that the simple role structure of initiator, supporter, and arguer increased the overall participation and peer interaction in AOD, while the group size of three members led to slightly better learning achievement. No significant interaction effects or role-specific effects were identified, indicating that students can benefit from role-based AOD regardless of group size and role script. The study results can inform the design and implementation of effective AOD.

Effect of rotary ultrasonic machining parameters on surface integrity of advanced ceramics

The commercial use of advanced ceramics has been hampered by the lack of an efficient, low-cost machining process. Two of the most important requirements for making machining of ceramics economically viable are: i) obtaining high enough material removal rates and ii) developing a machining process that does not cause surface and subsurface damage to the ceramic component. Therefore, it is important to study, in-depth, machining processes that have the potential to machine advanced ceramics efficiently and reliably. In this study, two-level full factorial experiments were designed and run to determine the effect of rotary ultrasonic machining process parameters (grit size, vibration amplitude, and feed rate) on the process outputs (cutting force, surface roughness, and surface compressive residual stresses). The materials under investigation were sintered silicon nitride and sintered reaction-bonded silicon nitride. The experiments reveal the main effects as well as the interaction effects of the process parameters on the process outputs such as cutting force, surface roughness, and surface compressive residual stresses. Using a larger grit size has been found to decreases the tool axial force. Samples that had a rougher surface finish also showed the highest surface residual compressive stresses. Surface compressive residual stresses were present in all samples after rotary ultrasonic machining irrespective of the conditions used. The presence of surface residual compressive stresses was found to be independent of the direction of machining.

Optimization of technological parameters of the sintering process based on experimental and statistical models of hot strength and recovery of sinter

This paper presents the results of developing experimental-statistical models of the influence of technological parameters of the sintering process on the reducibility and hot strength of the sinter based on the results of experimental sintering. The statistical data was processed by the method of a two-level factorial experiment (2k or Design Of Experiments) using the Minitab 19 software package for obtaining the regression dependences. The possibility of solving the problem of optimizing the technological mode of the process by the mass fraction of FeO in the sinter with a change in charge conditions based on the obtained regularities is shown

Ultrasonic-assisted extraction of polyphenolic compounds from Paederia scandens (Lour.) Merr. Using deep eutectic solvent: optimization, identification, and comparison with traditional methods

Ultrasonic-assisted extraction (UAE) coupled with deep eutectic solvent (DES) is a novel, efficient and green extraction method for phytochemicals. In this study, the effects of 16 DESs coupled with UAE on the extraction rate of polyphenols from Paederia scandens (Lour.) Merr. (P. scandens), an edible and medicinal herb, were investigated. DES synthesised with choline chloride and ethylene glycol at a 1:2 M ratio resulted in the highest extractability. Moreover, the effects of extraction parameters were investigated by using a two-level factorial experiment followed by response surface methodology The optimal parameters (water content in DES of 49.2%, the actual ultrasonic power of 72.4 W, and ultrasonic time of 9.7 min) resulted in the optimal total flavonoid content (TFC) (27.04 mg CE/g DW), ferric-reducing antioxidant power (FRAP) value (373.27 μmol Fe(Ⅱ)E/g DW) and 2,2′-azino-bis(3-ethylbenzthiazoline)-6-sulfonic acid radical (ABTS+) value (48.64 μmol TE/g DW), closely matching the experimental results. Furthermore, a comparison study demonstrated that DES-UAE afforded the higher TFC and FRAP value than traditional extraction methods. 36 individual polyphenolic compounds were identified and quantified by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) in P. scandens extracts, and of which 30 were found in the extracts obtained by DES-UAE. Additionally, DES-UAE afforded the highest sum of individual polyphenolic compound content. These results revealed that DES-UAE enhanced the extraction efficiency for polyphenols and provided a scientific basis for further processing and utilization of P. scandens.

Comparative Study on Conventional and Microwave-Assisted Ethanol Extraction of Phenolics and Flavonoids from Waste Onion Leaves

This study explored the utilization of waste onion leaves for the extraction of important bioactive compounds known for their health benefits such as phenolics and flavonoids. Conventional solvent (CSE) and microwave extraction (MAE) of flavonoids and phenolics from waste onion leaves using aqueous ethanol as solvent were performed. The effects of different factors such as ethanol concentration (50 %v/v &amp; 80 %v/v), temperature (60 °C &amp; 80 °C for CSE) or power level (10 % &amp; 50 % for MAE), and extraction time (1 hr &amp; 4 hrs for CSE, 10 sec &amp; 60 sec for MAE) on the total flavonoid yield (TFY) yield and total phenolic yield (TPY) were evaluated via a two-level factorial experiment. Results showed that for CSE, ethanol concentration, extraction time and the interactions of the factors significantly affected the TFY (p ≤ 0.05), while all the three factors, ethanol concentration-temperature interaction and ethanol concentration-extraction time interaction significantly affected the TPY (p ≤ 0.05). On the other hand, for MAE, ethanol concentration and power level have significant effects on the TFY (p ≤ 0.05) while the ethanol concentration significantly affected the TPY (p ≤ 0.05). The maximum extractable flavonoid and phenolic yields from the onion leaves were found to be 8.61 mg quercetin equivalent (QE)/g dry weight (DW) and 8.95 mg gallic acid equivalent (GAE) /g DW, respectively. For CSE, high levels of both ethanol concentration (80 %v/v) and low level of extraction time (1 hr) resulted in higher values of TFY (2.63 mg QE/g DW) and TPY (6.15 mg GAE/g DW). For MAE, higher values of TFY (2.98 mg QE/g DW) and TPY (4.24 mg GAE/g DW) were obtained at the high level of ethanol concentration (80 %v/v ethanol), high power level (50 %), and high level of extraction time (50 sec). MAE was found to be a more advantageous extraction method than the conventional one, because of its comparable flavonoids and phenolics recovery at a shorter extraction time.

Statistical Optimizing of Medium for Clavulanic Acid Production by Streptomyces clavuligerus Using Response Surface Methodology.

Clavulanic acid (CA) is a naturally occurring antibiotic produced by Streptomyces clavuligerus. Statistical optimization of the fermentation medium for CA production by Streptomyces clavuligerus was carried out. Multiple carbon sources, glycerol, dextrin, and triolein, were considered simultaneously. A two-level fractional factorial design experiment was conducted to identify the significant components of medium on CA production. Statistical analysis of the results showed that soybean meal, dextrin, and triolein were the most significant medium ingredients on CA production. The optimal level of these screened components was obtained by RSM based on the result of a Box-Behnken design, in which the values of dextrin, soybean meal, and triolein in CA fermentation medium were 12.37g/L, 39.75g/L, and 26.98ml/L, respectively. Using the proposed optimized medium, the model predicted 938mg/L of CA level and via experimental rechecking the model, 946mg/L of CA level was attained in shake flask fermentation, significantly high than 630mg/L of original medium. The optimized medium was further verified in 50-L stirred fermenter, and compared with performance of original medium in parallel, CA titer was increased from 889 to 1310mg/L; a 47% increase was achieved through medium optimization by statistical approaches.

Effects of parasites and predators on nociception: decreases analgesia reduces overwinter survival in root voles (Rodentia: Cricetidae)

Growing evidence suggests that parasite-infected prey is more vulnerable to predation. However, the mechanism underlying this phenomenon is obscure. In small mammals, analgesia induced by environmental stressors is a fundamental component of the defensive repertoire, promoting defensive responses. Thus, the reduced analgesia may impair the defensive ability of prey and increase their predation risk. This study aimed to determine whether coccidia infection increases the vulnerability to predation in root voles, Microtus oeconomus (Pallas, 1776), by decreased analgesia. Herein, a predator stimulus and parasitic infection were simulated in the laboratory via a two-level factorial experiment, then, the vole nociceptive responses to an aversive thermal stimulus were evaluated. Further, a field experiment was performed to determine the overwinter survival of voles with different nociceptive responses via repeated live trapping. The coccidia-infected voles demonstrated reduced predator-induced analgesia following exposure to predator odor. Meanwhile, pain-sensitive voles had lower overwinter survival than pain-inhibited voles in enclosed populations throughout the duration of the experiment. Our findings suggest that coccidia infection attenuates predator-induced analgesia, resulting in an increased vulnerability to predation.

Recovery of Bioactive Compounds from Industrial Exhausted Olive Pomace through Ultrasound-Assisted Extraction.

Simple SummaryExhausted olive pomace (EOP) is the main residue of the pomace oil extraction industry, which is generated in large quantities and has limited applications. Thus, this study aimed to obtain bioactive compounds from EOP using ultrasound-assisted extraction as a potential first valorization step. Two types of devices were tested: bath- and probe-type UAE. The operational parameters were studied and optimized to maximize the antioxidant compounds. In particular, hydroxytyrosol was the main phenolic compound identified and its content was 5.16 mg/g EOP (bath-type UAE) and 4.96 mg/g EOP (probe-type UAE). Mannitol was also detected in the extract, 59.53 mg/g EOP (bath-type UAE) and 69.73 mg/g EOP (probe-type UAE). The results highlight the great potential EOP has as a source of bioactive compounds, with applicability in several sectors. Moreover, the probe-type UAE shows potential to be applied for obtaining these bioactive compounds in a continuous and faster manner.Exhausted olive pomace (EOP) is the main agro-industrial waste of the olive pomace extracting industries. It contains phenolic compounds and mannitol, so the extraction of these bioactive compounds should be considered as a first valorization step, especially if EOP is used as biofuel. Therefore, EOP was subjected to bath-type ultrasound-assisted extraction (UAE), and the effects of the acetone concentration (20–80%, v/v), solid load (2–15%, w/v), and extraction time (10–60 min) on the extraction of antioxidant compounds were evaluated according to a Box–Behnken experimental design. By means of the response surface methodology, the optimum conditions were obtained: 40% acetone, 8.6% solids, and 43 min. For all the extracts, the total phenolic content (TPC), flavonoid content (TFC), and antioxidant activity (DPPH, ABTS, and FRAP) were determined. With the aim of shortening the extraction time, a two-level factorial experiment design was also carried out using a probe-type UAE, keeping the solid load at 8.6% (w/v) and the acetone concentration at 40% (v/v), while the amplitude (30–70%) and the extraction time (2–12 min) were varied to maximize the aforementioned parameters. Finally, a maximum of phenolic compounds was reached (45.41 mg GAE/g EOP) at 12 min and 70% amplitude. It was comparable to that value obtained in the ultrasonic bath (42.05 mg GAE/g EOP), but, remarkably, the extraction time was shortened, which translates into lower costs at industrial scale. Moreover, the bioactive compound hydroxytyrosol was found to be the major phenolic compound in the extract, i.e., 5.16 mg/g EOP (bath-type UAE) and 4.96 mg/g EOP (probe-type UAE). Other minor phenolic compounds could be detected by capillary zone electrophoresis and liquid-chromatography–mass spectrometry. The sugar alcohol mannitol, another bioactive compound, was also found in the extract, and its content was determined. Thus, the use of this technology can support the valorization of this waste to obtain bioactive compounds, including mannitol, hydroxytyrosol, and other derivatives, before being applied for other uses.

Mass optimisation of 3D-printed specimens using multivariable regression analysis

Fused deposition modelling popularity is attributed to equipment affordability, materials availability and open-source software. Given the variety of optimisation combinations, process parameters can be elaborate. This paper provides methods for optimisation of mass calculation using multivariable regression analysis. Layer thickness, extrusion temperature and speed were considered independent variables for a two-level factorial experiment. DOE was used for 12 sets of programs and analysis (two stages) undertaken using Design-Expert® V11 Software. In stage-1, four models were found to be significant. Stage-2 involved redesigning the remaining eight models, iteratively increasing the number of replicates and blocks. Adequacy of models was analysed, demonstrating that: model is significant, F-value is large, p < 0.05; lack of fit is insignificant; adequate precision >4.00; residuals are well behaved; R2 is as close as possible to 1.00 or for models with multiple replicates, the adjusted R2 and predicted R2 differential <0.2. All models were validated through measured, calculated responses.

Rider's Head Injury Risks in Relation to Dynamics of Motorcycle in Frontal Crashes

&#x0D; &#x0D; &#x0D; Motorcycle frontal crashes usually cause serious and fatal head injuries to riders. This paper presents a two-level factorial experiment through finite element simulations of motorcycle-rigid wall impact scenario to investigate the effects of motorcycle layout design variations on rider's relative head injury risks, and also of the deformation mechanisms of motorcycle frontal structures on dynamics of the motorcycle. The motorcycle layout design variations were represented by the changes of three design factors, namely location of the engine block, location of air filter casing and its orientation. Head Injury Criteria (HIC15) based on a time interval of 15 ms were selected as the response variable to evaluate the effects of the corresponding changes. The analysis showed that HIC15 values were significantly influenced by the changes of these factors, with the differences ranging from -21% to +11% for seven different designs of motorcycle layout as compared to the original one. Such influences on HIC15 values were mainly due to the changes in motorcycle dynamics caused by different deformation mechanisms of the wheel, which was attributed to interactions between the frontal structures and the engine block and also air filter casing. It was also found that HIC15 values were significantly influenced by the vertical component of motorcycle accelerations, but not by the horizontal component. A regression model for predicting the HIC15 value was established and the effect plots of the factors were also produced from the factorial analysis and it was found that there were interactions between the effect of the design factors. The outcomes of the present study provide an insight into how the structural response of the frontal structures of motorcycles could be taken into consideration as part of design elements in reducing rider's head injury risks in frontal crashes.&#x0D; &#x0D; &#x0D;

Control scheme selection and optimal tuning in industrial process control using factorial experiment design

In this study, a novel experimental approach for the optimal selection of an actuator-based control strategy is presented. The proposed approach is a two-stage method: first, a two-level factorial experiment design with n factors (2n) was applied to compare different control schemes. Schemes comparison was carried out in terms of energy consumption and closed-loop performance. For the best relative scheme, a Central Composite Face-centered (CCF) design was completed obtaining the controller parameters that optimize the performance in terms of the Integral Absolute Error (IAE) while operating in a region of low energy consumption. The proposed approach was experimentally tested using real data obtained from a laboratory prototype plant. Some experimental tests illustrating the suitability of our method are shown at the end of this article.

Artificial Neural Networks (ANNs) and Partial Least Squares (PLS) Regression in the Quantitative Analysis of Respirable Crystalline Silica by Fourier-Transform Infrared Spectroscopy (FTIR).

Respirable crystalline silica (RCS) overexposure can lead to the development of silicosis which is a chronic, irreversible, potentially fatal respiratory disease. The most significant prerequisite for any silica exposure control plan is an accurate occupational exposure assessment. The results of crystalline silica analysis are often affected by other mineral interferences and are influenced by an analyst's knowledge of mineralogy to accurately interpret infrared spectra and correct matrix interferences. Partial least squares (PLS) and artificial neural networks (ANNs) are two multivariate calibration methods to overcome the problem of spectral interferences without the need for an analyst intervention. The performance of these two methods in quantitative analysis of quartz in the presence of mineral interferences was evaluated and compared in this study. Fifty mixtures with different crystalline silica content ratios were prepared by mixing quartz with four common mineral interferences including kaolinite, albite, muscovite, and amorphous silica. Fourier-transform infrared spectra of the mixtures were split into training and test datasets. The optimal architecture of the ANN model was achieved using a two-level full factorial design experiment and data were modeled using ANN and PLS regression analysis. Root mean squared error of prediction values of 1.69 and 6.12 µg quartz for ANN and PLS models, respectively, revealed the fact that the both models performed very well in quantitative analysis of quartz in the presence of mineral interferences, with a better relative performance of the ANN model which can be related to the inherent nonlinear predictive ability of ANNs. Given the excellent predictive ability of the ANN model which can deal with a completely overlapped peak without any need of user's intervention, it is recommended that the ANN model be optimized in future studies and utilized for reliable and rapid on-field assessment of RCS exposure.

Identifying Significant Effects in Unreplicated Regular Two-level Factorial Experiments

The paper gives a new method to identify significant effects in two-level factorial experiments, and compares the new method with the exiting methods using Monte Carlo simulation. The existing methods only perform well under the assumption of effect sparsity, but the new method performs well without effect sparsity.