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Orthogonality and optimality of run order are two important and worthy to be considered criteria in design of experiment. For the mixed-level designs commonly used in the case of unequal levels of factors in the experiment, both orthogonality and optimality of run order are taken into account at the same time in this paper. The construction methods of mixed-level designs with orthogonality and relatively minimum or maximum level changes are respectively proposed. Based on such designs, the orthogonal main-effect plans with relatively minimum or maximum level changes are obtained by the method of collapsing factor. The designs with relatively minimum or maximum level changes constructed in this paper guarantee the cost minimum or the time trend most robust in the actual experiment arrangement.

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The aims of this paper are to estimate the monetary value of informal care for people with Alzheimer's disease (AD) in Spain, to compare results with those obtained in 2008 and to analyse the main determinants of the time of the value of informal care. The Survey on Disabilities, Autonomy and Dependency carried out in Spain in 2020/21 was used to obtain information about disabled individuals with AD and their informal caregivers. Assessment of informal care time was carried out using two alternative approaches: the replacement method, and the contingent valuation method (willingness to pay & willingness to accept). The number of people with AD residing in Spanish households and receiving informal care rose to more than 200,000, representing an increase of 43% compared with 2008. The average number of hours of informal care per week ranged from 86 to 101 h, with an estimated value of between €31,584 - €37,019 per year per caregiver (willingness to accept) or €71,653 - €83,984 per year (replacement). The annual total number of caregiving hours ranged between 896 and 1,061 million hours, representing between 0.52 and 0.62 of GDP in 2021 (willingness to accept) or 1.19-1.40 of GDP (replacement). The level of care needs plays a central role in explaining heterogeneity in estimates. These results should be taken into account by decision-makers for long-term care planning in the coming years.

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Brewer's spent yeast (BSY), derived from Saccharomyces cerevisiae used in beer production, is a valuable protein source for aquafeeds. Estimations of apparent digestibility coefficients (ADC) for nutrients in BSY are crucial for its inclusion in aquafeeds. ADC estimations for Saccharomyces cerevisiae protein in rainbow are hardly comparable from a methodological point of view, whereas the ADC estimations for BSY protein in Atlantic salmon are only based on stripped feces, which are known to produce underestimations. Therefore, new determinations of ADC of BSY nutrients are necessary for the inclusion of this ingredient in practical diets for salmonids. This study is focused on determining unbiased ADC values for protein and energy from BSY in juvenile Salmo salar. To reduce systematic biases, fecal samples were collected using stripping and decantation methods, which are known to produce under-and overestimations, respectively. 780 fish (25.16 ± 4.88 g) were stocked in six tanks. A reference diet (50% protein, 20% lipid, 1% Cr2O3) was provided to three tanks, and a test diet (70,30 reference diet to BSY) to the other three. ADC for BSY protein was 84.70 ± 1.04% (decantation) and 70.50 ± 4.03% (stripping). For gross energy, stripped feces yielded an ADC of 52.04 ± 5.30%, while decantation resulted in 63.80 ± 1.17%. Thus, ADC estimates were taken as the average of the stripping-value and the decantation-value, resulting in 77.6% for BSY crude protein, which is appreciably higher than previously measured values in S. salar fed undisrupted S. cerevisiae, and in 57.9% for gross energy.

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PdNi nanoalloy catalysts were prepared by a carbon-promoted galvanic replacement method. Characterizations and control experiments show the increased replacement rate of metal Ni with Pd2+ ion can be attributed to the higher electrode potential and smaller crystalline sizes caused by carbon doping. Introduction of carbon (C) into Ni particles not only accelerates the formation process of PdNi nanoalloys, but also enables C atoms to successfully enter the lattice interstices of PdNi nanoalloys. C regulates the surface electronic properties of PdNi nanoalloys by the electron transfer between different elements and improves their activity. The PdNi@C-650 exhibits extraordinary activity and long-term stability for hydrogenation reduction of hexavalent chromium (Cr (VI)) and hydrodechlorination of chlorophenols in comparison with PdNi/CNTs (carbon nanotubes) and commercial Pd/C. Density functional theory calculations together with investigations of mechanism reveal that the high electron-deficient PdNi nanoalloys from the redistribution of electron between Ni, Pd and C of the PdNi@C-650 promote the surface adsorption of substrate molecules and H2, which accordingly enhances the hydrogenation activity. This study brings a new method for the design and preparation of high active noble metal nanoalloy.

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Recently, the massive accumulation of waste iron tailings powder (WITP) has resulted in significant environmental pollution. To solve this problem, this paper proposes an original mortar replacement (M) method to reuse waste solids and reduce cement consumption. In the experiment, the author employed an M method which replaces water, cement, and sand with WITP under constant water/cement and found that the strength development can be significantly improved. Specifically, a mortar with 20% WITP replacement can obtain a 30.95% improvement in strength development. To study the internal mechanism, we performed experiments such as thermogravimetric analysis (TGA), mercury intrusion porosimetry (MIP), and SEM. The results demonstrate that the nucleation effect and pozzolanic effect of WITP can help promote cement hydration, and MIP reveals that WITP can effectively optimize pore structure. In addition, 1 kg 20% WITP mortar reduced cement consumption by 20%, which saves 19.98% of the economic cost. Comprehensively, our approach achieves the effective utilization of WITP and provides a favorable reference for practical engineering.

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Bridge expansion and contraction installation (BECI) has proved to be an indispensable component of bridge structures due to its stability, comfort, and durability benefits. At present, conventional replacement technologies for modular-type, comb plate-type, and seamless-type BECIs are widely applied worldwide. However, it is unfortunate that there remains no systematic research on quantitative assessment approaches for evaluating the overall technical status and selecting optimal replacement methods for existing BECIs. Therefore, considering the installation performance according to functional index evaluations and the economic cost based on life-cycle value assessment (LCVA), a standardized quantitative assessment approach is proposed for optimal replacement method selection in this article. Simultaneously, the other new quantitative assessment method is developed for evaluating the overall technical status of BECIs, which provides a basis for the necessity of replacement. A BECI replacement decision system is constructed, and a corresponding case study illustrates that the proposed system based on the analytic hierarchy process (AHP) in this article proves to be reasonable and feasible. The results reveal that the selected replacement method with both a higher function coefficient and a lower economic coefficient can not only fulfil the performance requirements but also pursue a cost reduction, which leads to a considerable value increment. This system can effectively assist bridge managers in making appropriate operation and maintenance (O and M) decisions in actual engineering projects.

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Although the need for non-animal alternatives has been well recognised for the human health hazard assessment of chemicals in general, it has become especially pressing for cosmetic ingredients due to the full implementation of testing and marketing bans on animal testing under the European Cosmetics Regulation. This means that for the safety assessment of cosmetics, the necessary safety data for both the ingredients and the finished product can be drawn from validated (or scientifically-valid), so-called "Replacement methods". In view of the challenges for safety assessment without recourse to animal test data, the Methodology Working Group of the Scientific Committee on Consumer Safety organised a workshop in February 2019 to discuss the key issues in regard to the use of animal-free alternative methods for the safety evaluation of cosmetic ingredients. This perspective article summarises the outcomes of this workshop and reflects on the state-of-the-art and possible way forward for the safety assessment of cosmetic ingredients for which no experimental animal data exist. The use and optimisation of "New Approach Methodology" that could be useful tools in the context of the "Next Generation Risk Assessment" and the strategic framework for safety assessment of cosmetics were discussed in depth.

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We establish a QSPR analysis for the bioconcentration factor of 851 heterogeneous structural compounds. Linear models are proposed via two different approaches: i. the optimal descriptor method implemented in CORAL, and ii. multivariable linear regressions on the best molecular descriptors found with the Replacement Method on 44,216 structural descriptors. Such variables are derived with different freely available softwares, such as PaDEL, PyDescriptor, Mold2 , QuBiLs-MAS and ISIDA/Fragmentor. The same validation set is employed in order to compare the predictive performance between the so-obtained CORAL and RM based models. Finally, the comparison of several models for the bioconcentration factor confirms the ability of the so-called index of ideality of correlation to be a criterion of predictive potential in Quantitative Structure-Property Relationships.

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As a promising alternative approach to industrial N2 fixation process, electrocatalytic N2 reduction reaction (NRR) can achieve efficient, sustainable, and eco-friendly ammonia production under ambient conditions. Developing efficient NRR catalysts is critical for the electrochemical ammonia synthesis. Herein, self-supported mesoporous Au3Pd film on Ni foam (mAu3Pd/NF) has been in situ synthesized via a micelle-assisted replacement strategy. Combination of bimetallic compositions, interconnected mesoporous structure, and binder-free characteristic, the mAu3Pd/NF shows a superior NRR performance in 0.1 M Na2SO4. This micelle-assisted replacement route is very important to construct efficient self-supporting mesoporous films for the NRR and other fields.

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Cathepsins have been proposed as biomarkers of chemical exposure in the zebrafish embryo model but it is unclear whether they can also be used to detect sublethal stress. The present study evaluates three cathepsin types as candidate biomarkers in zebrafish embryos. In addition to other functions, cathepsins are also involved in yolk lysosomal processes for the internal nutrition of embryos of oviparous animals until external feeding starts. The baseline enzyme activity of cathepsin types H, C and L during the embryonic development of zebrafish in the first 96 h post fertilisation was studied. Secondly, the effect of leupeptin, a known cathepsin inhibitor, and four embryotoxic xenobiotic compounds with different modes of action (phenanthrene-baseline toxicity; rotenone-an inhibitor of electron transport chain in mitochondria; DNOC (Dinitro-ortho-cresol)-an inhibitor of ATP synthesis; and tebuconazole-a sterol biosynthesis inhibitor) on in vivo cathepsin H, C and L total activities have been tested. The positive control leupeptin showed effects on cathepsin L at a 20-fold lower concentration compared to the respective LC50 (0.4 mM) of the zebrafish embryo assay (FET). The observed effects on the enzyme activity of the four other xenobiotics were not or just slightly more sensitive (factor of 1.5 to 3), but the differences did not reach statistical significance. Results of this study indicate that the analysed cathepsins are not susceptible to toxins other than the known peptide-like inhibitors. However, specific cathepsin inhibitors might be identified using the zebrafish embryo.

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Gold nanostructures that can be synthetically articulated to adapt diverse morphologies, offer a versatile platform and tunable properties for applications in a variety of areas, including biomedicine and diagnostics. Among several conformational architectures, gold nanoshells provide a highly advantageous combination of properties that can be fine-tuned in designing single or multi-purpose nanomaterials, especially for applications in biology. One of the important parameters for evaluating the efficacy of gold nano-architectures is their reproducible synthesis and surface functionalization with desired moieties. A variety of methods now exist that allow fabrication and chemical manipulation of their structure and resulting properties. This review article provides an overview and a discussion of synthetic methodologies to a diverse range of gold nanoshells, and a brief summary of surface functionalization and characterization methods employed to evaluate their overall composition.

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The Quantitative Ion Character-Activity Relationship (QICAR) method was used for correlating metal ionic characteristics with the maximum adsorption capacity (qmax) of multi-walled carbon for heavy metals. The experimental values of qmax for 25 heavy metal ions, estimated by the Langmuir isotherm model, were used to construct a QICAR model. The genetic algorithm, enhanced replacement method and successive projection algorithm procedures were applied as variable selection algorithms to choose the optimal subsets of descriptors. The selected variables were correlated with qmax values by using partial least squares (PLS) regression. Orthogonal signal correction was applied as a pre-processing technique. Among of different variable selection methods, the enhanced replacement method displayed noticeable statistical parameters of the final model. The results of the enhancement replacement method-orthogonal correction signal-PLS model, with RMSEC = 0.733, r2c = 0.999 and r2p = 0.946, were excellent and dramatically better than those of other models. The developed QICAR model satisfied the internal and external validation criteria. The importance of electronegativity, ionic radius and atomic number of the heavy metal ions indicated the impact of the tendency to accept electrons and the size of ions in adsorption on carbon nanotubes.

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A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the ChEMBL database and studied by means of a conformation-independent quantitative structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. The structural descriptors are derived with different freeware, such as PaDEL, Mold², and QuBiLs-MAS; such descriptor software complements each other and improves the QSAR results. The best multivariable linear regression models are found with the replacement method variable subset selection technique. The balanced subsets method partitions the dataset into training, validation, and test sets. It is found that the proposed linear QSAR model improves previously reported models by leading to a simpler alternative structure-activity relationship.

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The ANTARES dataset is a large collection of known and verified experimental bioconcentration factor data, involving 851 highly heterogeneous compounds from which 159 are pesticides. The BCF ANTARES data were used to derive a conformation-independent QSPR model. A large set of 27,017 molecular descriptors was explored, with the main intention of capturing the most relevant structural characteristics affecting the studied property. The structural descriptors were derived with different freeware tools, such as PaDEL, Epi Suite, CORAL, Mold2, RECON, and QuBiLs-MAS, and so it was interesting to find out the way that the different descriptor tools complemented each other in order to improve the statistical quality of the established QSPR. The best multivariable linear regression models were found with the Replacement Method variable sub-set selection technique. The proposed QSPR model improves previous reported models of the bioconcentration factor in the present dataset.

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In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k OH) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: [Formula: see text], RMS train = 0.21, while for the test set is [Formula: see text], RMS test = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.

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A prediction of quantitative structure-property relationships is developed to model the polarity parameter of a set of 146 organic compounds in acetonitrile in reversed-phase liquid chromatography. Enhanced replacement method and support vector machine regressions were employed to build prediction models based on molecular descriptors calculated from the structure alone. The correlation coefficients between experimental and predicted values of polarity parameter for the test set by enhanced replacement method and support vector machine were 0.970 and 0.993, respectively. The obtained results demonstrated that the support vector machine model is more reliable and has a better prediction performance than the enhanced replacement method.

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In the present work, enhanced replacement method (ERM) and support vector machine (SVM) were used for quantitative structure-property relationship (QSPR) studies of polarity parameter (p) of various organic compounds in methanol in reversed phase liquid chromatography based on molecular descriptors calculated from the optimized structures. Diverse kinds of molecular descriptors were calculated to encode the molecular structures of compounds, such as geometric, thermodynamic, electrostatic and quantum mechanical descriptors. The variable selection method of ERM was employed to select an optimum subset of descriptors. The five descriptors selected using ERM were used as inputs of SVM to predict the polarity parameter of organic compounds in methanol. The coefficient of determination, r2, between experimental and predicted polarity parameters for the prediction set by ERM and SVM were 0.952 and 0.982, respectively. Acceptable results specified that the ERM approach is a very effective method for variable selection and the predictive aptitude of the SVM model is superior to those obtained by ERM. The obtained results demonstrate that SVM can be used as a substitute influential modeling tool for QSPR studies.

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We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538 molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. The best predictive three-descriptors QSPR is developed on a reduced training set of 93 chemicals, having an acceptable predictive capability on 550 test set compounds. We also establish a model with a single optimal descriptor derived from CORAL freeware. The present approach compares fairly well with a previously reported one that uses Dragon descriptors.

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Mer receptor tyrosine kinase is a promising novel cancer therapeutic target in many human cancers, because abnormal activation of Mer has been implicated in survival signaling and chemoresistance. 3D-QSAR analyses based on alignment independent descriptors were performed on a series of 81 Mer specific tyrosine kinase inhibitors. The fractional factorial design (FFD) and the enhanced replacement method (ERM) were applied and tested as variable selection algorithms for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. The data set was split into 65 molecules as the training set and 16 compounds as the test set. All descriptors were generated by using the GRid INdependent descriptors (GRIND) approach. After variable selection, GRIND were correlated with activity values (pIC50) by PLS regression. Of the two applied variable selection methods, ERM had a noticeable improvement on the statistical parameters of PLS model, and yielded a q (2) value of 0.77, an [Formula: see text] of 0.94, and a low RMSEP value of 0.25. The GRIND information contents influencing the affinity on Mer specific tyrosine kinase were also confirmed by docking studies. In a quantum calculation study, the energy difference between HOMO and LUMO (gap) implied the high interaction of the most active molecule in the active site of the protein. In addition, the molecular electrostatic potential energy at DFT level confirmed results obtained from the molecular docking. The identified key features obtained from the molecular modeling, enabled us to design novel kinase inhibitors.

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A quantitative structure-property relationship (QSPR) was developed for modeling the retention index of 1184 flavor and fragrance compounds measured using a Carbowax 20M glass capillary gas chromatography column. The 4885 molecular descriptors were calculated using Dragon software, and then were simultaneously analyzed through multivariable linear regression analysis using the replacement method (RM) variable subset selection technique. We proceeded in three steps, the first one by considering all descriptor blocks, the second one by excluding conformational descriptor blocks, and the last one by analyzing only 3D-descriptor families. The models were validated through an external test set of compounds. Cross-validation methods such as leave-one-out and leave-many-out were applied, together with Y-randomization and applicability domain analysis. The developed model was used to estimate the I of a set of 22 molecules. The results clearly suggest that 3D-descriptors do not offer relevant information for modeling the retention index, while a topological index such as the Randic-like index from reciprocal squared distance matrix has a high relevance for this purpose.

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