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To contribute to a growing global research interest that has evolved toward augmenting the economic, environmental, and societal values of Industry 4.0 in the manufacturing context, this study is intended to (1) survey the applicability of Industry 4.0 technologies in each of the triple bottom lines at the product level and (2) scrutinize the technologies based on product sustainability criteria using the application of the fuzzy Technique for Order of Preference by Similarity to Ideal Solution. Yet, there is a significant paucity of knowledge and uncertainty about the applicability of these technologies to developing sustainable products, hence providing an opportunity for innovative research. To be a sound assessment, this study investigates the perceptions of professional technologists, who play an important role as both internal and external stakeholders in addressing technological issues within organizations including multinationals. The findings obtained by the survey indicated the applicability level of six major technologies in contributing to product-level sustainability. The findings obtained by the fuzzy-based application revealed that 'Big Data Analytics' has the highest performance for developing sustainable products. Such an assessment, which is of critical importance to sustainable development, would be beneficial to policy-and decision-makers seeking to get a better understanding of the technologies and their applicability to sustainable products development. [Display omitted] • Industry 4.0 potential for developing sustainable products has been discussed. • Applicability of Industry 4.0 technologies for product-level sustainability was surveyed. • Applicable technologies were further scrutinized based on product sustainability criteria. • To be a sound assessment, professional technologists were involved in the project. • Big data analytics had the highest performance for developing sustainable products. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a novel control algorithm for the rotor-side converter of Doubly-Fed Induction Generators. The main goal is to endow the system with effective Low Voltage Ride Through capability, under harsh balanced and unbalanced grid voltage sags, without relying on dedicated auxiliary hardware, which is commonly adopted to sustain severe line faults. In this respect, nonlinear control theory arguments are applied to design a controller capable of mitigating oscillations (particularly on rotor currents and voltages) arising during line faults, therefore preventing the system from disconnecting for protection. The proposed solution adopts both feedforward and feedback terms. The former stems from a thoughtful analysis of the system internal dynamics, taking into account the effects of line voltage perturbations, which is exploited to design feasible state trajectories for the generator electromagnetic variables. Specifically, such references do not contain poorly-damped oscillatory modes of the machine natural dynamics, expressed in synchronously rotating frames (such components turn into slowly varying DC ones in a stationary frames). Then, a state feedback unit is designed according to modern saturated control techniques, accounting for constraints on rotor voltage, and steering real variables toward references, where priority given to rotor currents, to avoid rotor-side converter tripping due to overcurrent. In addition, a non standard line voltage reconstruction and dip detection scheme, based on adaptive state observers, is designed, to reliably cope with challenging faulty conditions. Detailed numerical simulations validate the proposed method benefits under severe symmetric and asymmetric dip scenarios. [ABSTRACT FROM AUTHOR]

Abstract: The study evaluated the potential mismatch between classroom furniture dimensions and anthropometric characteristics of 978 Iranian high school students (498 girls, 480 boys), aged 15–18 years. Nine anthropometric measurements (stature, sitting height, sitting shoulder height, popliteal height, hip breadth, elbow–seat height, buttock–popliteal length, buttock–knee length and thigh clearance) and five dimensions from the existing classroom furniture were measured and then compared together (using match criterion equations) to identify any potential mismatch between them. The results indicated a considerable mismatch between body dimensions of the students and the existing classroom furniture, with seat height (60.9%), seat width (54.7%) and desktop height (51.7%) being the furniture dimensions with a higher level of mismatch. The levels of mismatch varied between the high-school grade levels and between genders, indicating their special requirements and possible problems. The proposed dimensions of the classroom furniture more appropriate for the students were given. This additional information on students’ anthropometry can be used by local furniture industries as a starting point for designing more appropriate furniture for school children, or used by schools to aid in furniture selection. [Copyright &y& Elsevier]

We evaluated groundwater quality, pollution, and its effects on human health in the eastern part of the Lake Urmia basin, the largest lake in the Middle East. Although groundwater quality is suitable for drinking and irrigation purposes, an index-based approach quantifying heavy metal pollution revealed that most sampling sites exhibited moderate to high pollution levels in the northern and southern regions. The positive matrix factorization (PMF) and principal component analysis-multi linear regression (PCA-MLR) receptor models suggest that the main contributors to the observed groundwater pollution, expressed as percentages by model, were: lake water infiltration and dissolution of minerals and fertilizers (46% and 63%), infiltration of leachates from solid wastes (29% and 15%), mixing with industrial-municipal wastewaters (18% and 13%), and vehicular emissions (7% and 9%). The PMF model indicated better correlations between observed and predicted concentrations (R2 = 0.96) than the PCA-MLR (R2 = 0.89). Our results from the human health risk assessments (HHRA) highlight non-carcinogenic and carcinogenic risks for Pb and Cr, respectively. Also, the PMF-based assessment of human health risk indicated that wastewaters and solid waste leachates are responsible for the cancer risk from Cr for children. [Display omitted] • Groundwater pollution by heavy metals indicated a moderate to high level. • The chemical composition of Lake Urmia groundwaters reflects a combination of natural and anthropogenic sources. • The PMF receptor model is preferred for estimating the source apportionment. • Pollution by wastewaters and solid waste leachates are responsible for the cancer risk from Cr for children. [ABSTRACT FROM AUTHOR]

We evaluated groundwater quality, pollution, and its effects on human health in the eastern part of the Lake Urmia basin, the largest lake in the Middle East. Although groundwater quality is suitable for drinking and irrigation purposes, an index-based approach quantifying heavy metal pollution revealed that most sampling sites exhibited moderate to high pollution levels in the northern and southern regions. The positive matrix factorization (PMF) and principal component analysis-multi linear regression (PCA-MLR) receptor models suggest that the main contributors to the observed groundwater pollution, expressed as percentages by model, were: lake water infiltration and dissolution of minerals and fertilizers (46% and 63%), infiltration of leachates from solid wastes (29% and 15%), mixing with industrial-municipal wastewaters (18% and 13%), and vehicular emissions (7% and 9%). The PMF model indicated better correlations between observed and predicted concentrations (R2 = 0.96) than the PCA-MLR (R2 = 0.89). Our results from the human health risk assessments (HHRA) highlight non-carcinogenic and carcinogenic risks for Pb and Cr, respectively. Also, the PMF-based assessment of human health risk indicated that wastewaters and solid waste leachates are responsible for the cancer risk from Cr for children. [Display omitted] • Groundwater pollution by heavy metals indicated a moderate to high level. • The chemical composition of Lake Urmia groundwaters reflects a combination of natural and anthropogenic sources. • The PMF receptor model is preferred for estimating the source apportionment. • Pollution by wastewaters and solid waste leachates are responsible for the cancer risk from Cr for children. [ABSTRACT FROM AUTHOR]