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Two studies were conducted to address the potential nonlinear relationship between emotional exhaustion and voice. Study 1 developed and tested a model rooted in conservation of resources theory in which responses to emotional exhaustion are determined by individual-level and group-level conditions that influence the perceived safety and efficacy of voice and drive prohibitive voice behaviors by giving rise to either resource-conservation-based or resource-acquisition-based motivation. Specifically, there was a curvilinear (U-shaped) relationship between emotional exhaustion and prohibitive voice under conditions of (i) high job security and (ii) high interactional justice climate, but a linearly negative relationship when these resources were low. Study 2 replicated and extended these findings to include an empirical examination of these effects on promotive versus prohibitive voice. Results confirmed the findings of Study 1, provided evidence of differences in the nomological networks of promotive and prohibitive voice, and indicated that prohibitive voice is more salient to the experience of high emotional strain. Implications of the findings and areas for future research are discussed.

Porous materials, from macroscopic bulk materials (MBs) with (sub‐)millimeter‐scale pores to tiny particles (TPs) with (sub‐)nanometer‐scale pores, have attracted ever‐growing interest in various fields. However, the integration of multi‐scale pores in one composite is promising but challenging, owing to the considerable gap in the scale of the pores. Inspired by blood coagulation, a fibrin‐based dynamic bridging strategy is developed to fabricate a multiscale‐assembled hierarchical porous material (MHPM), in which fibrin formed as the sub‐framework for the weaving‐narrow of MBs and the enwinding‐load of TPs. The bio‐polymerization nature makes the fabrication rapid, facile, and universal for the customizable integration of seven kinds of TPs and four kinds of MBs. Besides, the integration is controllable with high load capacity of TPs and is stable against external shock forces. The unique multi‐level structure endows the MHPM with large and accessible surface area, and efficient mass transfer pathways, synergistically leading to high adsorption capacity and rapid kinetics in multiple adsorption models. This work suggests a strategy for the rational multi‐level design and fabrication of hierarchical porous architectures. A bio‐inspired fibrin‐based strategy is reported to integrate macro‐porous bulk materials and nano‐porous particles into a multiscale‐assembled hierarchical porous material. The unique multi‐level porous structure endows the material with the compatibility of large and accessible surface area and efficient mass transfer pathways, synergistically leading to high adsorption capacity and rapid kinetics in multiple adsorption models.

A general theoretical and numerical framework for the strength and mass optimisation of variable-stiffness composite laminates (VSCLs) is presented in this work. The optimisation is performed in the context of the first-level problem of the multi-scale two-level optimisation strategy (MS2LOS) for VSCLs. Both the failure load maximisation problem (subject to a constraint on the mass) and the mass minimisation one (with a constraint on the VSCL strength) are solved for two benchmark structures. The effect of the presence of a constraint on the maximum tow curvature is also investigated. The solutions are searched by means of a deterministic algorithm by considering different scenarios in terms of the VSCL macroscopic behaviour: the orthotropy type and shape, the direction of the main orthotropy axis and the thickness of the laminate are tailored either globally (uniform over the structure) or locally. The polar method is used to represent the point-wise elastic response of the VSCL at the macroscopic scale. The distributions of the polar parameters and of the thickness are described through B-spline entities: their properties are exploited in computing physical and geometrical response functions of the VSCL as well as their gradient. The VSCL strength at the macroscopic scale is assessed using a laminate-level failure criterion in the space of polar parameters. Numerical results show considerable improvements with respect to both quasi-homogeneous isotropic structures and an optimised VSCL solution taken from the literature obtained by using the design approach based on lamination parameters. These results confirm the effectiveness of the proposed strategy and the great potential of VSCLs.

In 2018, the discovery of carcinogenic nitrosamine process related impurities (PRIs) in a group of widely used drugs led to the recall and complete withdrawal of several medications that were consumed for a long time, unaware of the presence of these genotoxic PRIs. Since then, PRIs that arise during the manufacturing process of the active pharmaceutical ingredients (APIs), together with their degradation impurities, have gained the attention of analytical chemistry researchers. In 2020, favipiravir (FVR) was found to have an effective antiviral activity against the SARS-COVID-19 virus. Therefore, it was included in the COVID-19 treatment protocols and was consequently globally manufactured at large-scales during the pandemic. There is information indigence about FVR impurity profiling, and until now, no method has been reported for the simultaneous determination of FVR together with its PRIs. In this study, five advanced multi-level design models were developed and validated for the simultaneous determination of FVR and two PRIs, namely; (6-chloro-3-hydroxypyrazine-2-carboxamide) and (3,6-dichloro-pyrazine-2-carbonitrile). The five developed models were classical least square (CLS), principal component regression (PCR), partial least squares (PLS), genetic algorithm-partial least squares (GA-PLS), and artificial neural networks (ANN). Five concentration levels of each compound, chosen according to the linearity range of the target analytes, were used to construct a five-level, three-factor chemometric design, giving rise to twenty-five mixtures. The models resolved the strong spectral overlap in the UV-spectra of the FVR and its PRIs. The PCR and PLS models exhibited the best performances, while PLS proved the highest sensitivity relative to the other models.

In the context of Industry 4.0 and Industry 5.0, the introduction of collaborative workplaces, where humans and robots work together, represents a growing trend to improve the productivity, adaptability, and flexibility of production plants. Indeed, human–robot collaboration (HRC) is a very deepened topic in the scientific community and the designing of collaborative workplaces is a challenging issue due to the high level of complexity and multidisciplinary of its features. This work tackles the complexity of collaborative workplaces and proposes a structured framework to support strategic decisions in designing. A multi-level designing framework is proposed as a supporting tool for designers. Within five domains of collaborative robotics, the elements of a collaborative workplace are identified and proposed in a framework in order to better consider human safety and working conditions during the designing process. A decomposition matrix and an adjacency matrix are used to develop a multi-level designing workflow. Finally, an interactive tool is presented, named “Smart Graph Interface” (SGI), to read and exploit the contents of the framework. The SGI is applied to three case studies from the literature, to spread out principal outcomes in terms of applicability and robustness.

Self-centering shear wall systems (SCSWSs) exhibit superior seismic capacities with low-damage and self-centering features. However, the cumulative effect under long duration earthquakes would diminish robustness of the system and lead to increased unrecoverable damage. Thus, it should be considered in seismic designs for SCSWSs. This paper applies an energy-based design procedure (EBDP) to SCSWSs in accordance with the Chinese code. A step-by-step design procedure is presented to conduct multi-level designs for SCSWSs using EBDP, while detailed explanations are elaborated corresponding to SCSWS features. A design example is presented to verify the applicability of the EBDP in SCSWSs. The performance of the designed SCSWS is then assessed and compared with a SCSWS designed by the direct displacement-based design method. Results show that the EBDP designed structure has 13% enhanced strength capacity with better controllability in the damage development. The damage index equaling to 0.35 and 0.46 are quantified with two groups of earthquakes, which consists with the performance demands. In addition, deformations are in good agreement with the design objectives, implying reasonable application of the EBDP in SCSWSs.

While the orthogonal design of split-plot fractional factorial experiments has received much attention already, there are still major voids in the literature. First, designs with one or more factors acting at more than two levels have not yet been considered. Second, published work on nonregular fractional factorial split-plot designs was either based only on Plackett-Burman designs, or on small nonregular designs with limited numbers of factors. In this article, we present a novel approach to designing general orthogonal fractional factorial split-plot designs. One key feature of our approach is that it can be used to construct two-level designs as well as designs involving one or more factors with more than two levels. Moreover, the approach can be used to create two-level designs that match or outperform alternative designs in the literature, and to create two-level designs that cannot be constructed using existing methodology. Our new approach involves the use of integer linear programming and mixed integer linear programming, and, for large design problems, it combines integer linear programming with variable neighborhood search. We demonstrate the usefulness of our approach by constructing two-level split-plot designs of 16-96 runs, an 81-run three-level split-plot design, and a 48-run mixed-level split-plot design. Supplementary materials for this article are available online.

Water resources systems are associated with a variety of complexities and uncertainties due to socio-economic and hydro-environmental impacts. Such complexities and uncertainties lead to challenges in evaluating the water resources management alternatives and the associated risks. In this study, the factorial analysis and fuzzy random value-at-risk are incorporated into a two-stage stochastic programming framework, leading to a factorial-based two-stage programming with fuzzy random value-at-risk (FTSPF). The proposed FTSPF approach aims to reveal the impacts of uncertainty parameters on water resources management strategies and the corresponding risks. In detail, fuzzy random value-at-risk is to reflect the potential risk about financial cost under dual uncertainties, while a multi-level factorial design approach is used to reveal the interaction between feasibility degrees and risk levels, as well as the relationships (including curvilinear relationship) between these factors and the responses. The application of water resources system planning makes it possible to balance the satisfaction of system benefit, the risk levels of penalty and the feasibility degrees of constraints. The results indicate that decision makers would pay more attention to the tradeoffs between the system benefit and feasibility degree, and the water allocation for agricultural section contributes most to control the financial loss of water. Moreover, FTSPF can generate a higher system benefit and more alternatives under various risk levels. Therefore, FTSPF could provide more useful information for enabling water managers to identify desired policies with maximized system benefit under different system-feasibility degrees and risk levels.

Die Persistenz geschlechtlicher Arbeitsteilung im Anschluss an die Familiengründung fordert sowohl familienpolitische Steuerungsstrategien als auch deren Untersuchung heraus. Häufig wird in Wirkungsanalysen deterministisch vorausgesetzt, dass sich die staatliche Steuerungsfunktion unmittelbar auf die Handlungen von Subjekten auswirkt; das greift jedoch zu kurz. Ob ein Steuerungsziel erreicht wird, hat wesentlich mit den Interpretationen des Steuerungsinstrumentes und der entsprechenden Bedeutungszuschreibung auf unterschiedlichen Ebenen der Vermittlung und nicht zuletzt durch die adressierten Eltern zu tun. Letztere erzeugen insofern die Wirkung staatlicher Steuerung, statt sie nur zu beziehen. Der Beitrag fragt, wie Wirkung – begriffen als Übersetzung der Steuerungsabsicht durch interpersonelle Deutungen verschiedener Akteur*innen auf unterschiedlichen Ebenen der Politikvermittlung – konzeptualisiert werden kann. Dazu werden der Stand der Auseinandersetzung um die Analyse und Feststellung von Wirkung, Einfluss und Folgen staatlicher Steuerungsinstrumente dargestellt und der Nutzen der jeweiligen Ansätze anhand der Konzeptualisierung eines feministischen Mehrebenendesigns umrissen.

This article uses the Comprehensive Mixed-Methods Participatory Evaluation (CMMPE; Nastasi and Hitchcock Transforming school mental health services: Population-based approaches to promoting the competency and wellness of children, Thousand Oaks, CA: Corwin Press with National Association of School Psychologists 2008 ; Nastasi et al. School-based mental health services: creating comprehensive and culturally specific programs. Washington, DC: American Psychological Association 2004 ) model as a framework for addressing the multiplicity of evaluation decisions and complex nature of questions related to program success in multilevel interventions. CMMPE defines program success in terms of acceptability, integrity, social or cultural validity, outcomes (impact), sustainability and institutionalization, thus broadening the traditional notions of program outcomes. The authors use CMMPE and an example of a community-based multilevel sexual risk prevention program with multiple outcomes to discuss challenges of evaluating multilevel interventions. The sexual risk program exemplifies what Schensul and Tricket (this issue) characterize as multilevel intervention–multilevel evaluation (M–M), with both intervention and evaluation at community, health practitioner, and patient levels. The illustration provides the context for considering several challenges related to M–M designs: feasibility of randomized controlled trials within community-based multilevel intervention; acceptability and social or cultural validity of evaluation procedures; implementer, recipient, and contextual variations in program success; interactions among levels of the intervention; unanticipated changes or conditions; multiple indicators of program success; engaging multiple stakeholders in a participatory process; and evaluating sustainability and institutionalization. The complexity of multilevel intervention and evaluation designs challenges traditional notions of evaluation research and experimental designs. Overcoming these challenges is critical to effective translation of research to practice in psychology and related disciplines.