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This study aims to simulate the dendritic growth in Stokes flow by iteratively coupling a domain and boundary type meshless method.

A preconditioned phase-field model for dendritic solidification of a pure supercooled melt is solved by the strong-form space-time adaptive approach based on dynamic quadtree domain decomposition. The domain-type space discretisation relies on monomial augmented polyharmonic splines interpolation. The forward Euler scheme is used for time evolution. The boundary-type meshless method solves the Stokes flow around the dendrite based on the collocation of the moving and fixed flow boundaries with the regularised Stokes flow fundamental solution. Both approaches are iteratively coupled at the moving solid–liquid interface. The solution procedure ensures computationally efficient and accurate calculations. The novel approach is numerically implemented for a 2D case.

The solution procedure reflects the advantages of both meshless methods. Domain one is not sensitive to the dendrite orientation and boundary one reduces the dimensionality of the flow field solution. The procedure results agree well with the reference results obtained by the classical numerical methods. Directions for selecting the appropriate free parameters which yield the highest accuracy and computational efficiency are presented.

A combination of boundary- and domain-type meshless methods is used to simulate dendritic solidification with the influence of fluid flow efficiently.

Improving productivity and efficiency has always been crucial for industrial companies to remain competitive. In recent years, the topic of environmental impact has become increasingly important. Published research indicates that environmental and economic goals can enforce or rival each other. However, few papers have been published that address the interaction and integration of these two goals.

In this paper, we identify both, synergies and trade-offs based on a systematic review incorporating 66 publications issued between 1992 and 2021. We analyze, quantify and cluster examples of conjunctions of ecological and economic measures and thereby develop a framework for the combined improvement of performance and environmental compatibility.

Our findings indicate an increased significance of a combined consideration of these two dimensions of sustainability. We found that cases where enforcing synergies between economic and ecological effects were identified are by far more frequent than reports on trade-offs. For the individual categories, cost savings are uniformly considered as the most important economic aspect while, energy savings appear to be marginally more relevant than waste reduction in terms of environmental aspects.

No previous literature review provides a comparable graphical treatment of synergies and trade-offs between cost savings and ecological effects. For the first time, identified measures were classified in a 3 × 3 table considering type and principle.

Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both human health and economic activity, and thus are receiving increasing research attention. Understanding the hazards posed by extreme high temperatures are important for selecting intervention measures targeted at reducing socioeconomic and environmental damage.

In this study, detrended fluctuation analysis is used to identify extreme high-temperature events, based on homogenized daily minimum and maximum temperatures from nine meteorological stations in a major grassland region, Hulunbuir, China, over the past 56 years.

Compared with the commonly used functions, Weibull distribution has been selected to simulate extreme high-temperature scenarios. It has been found that there was an increasing trend of extreme high temperature, and in addition, the probability of its indices increased significantly, with regional differences. The extreme high temperatures in four return periods exhibited an extreme low hazard in the central region of Hulunbuir, and increased from the center to the periphery. With the increased length of the return period, the area of high hazard and extreme high hazard increased. Topography and anomalous atmospheric circulation patterns may be the main factors influencing the occurrence of extreme high temperatures.

These results may contribute to a better insight in the hazard of extreme high temperatures, and facilitate the development of appropriate adaptation and mitigation strategies to cope with the adverse effects.

Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been conducted on the design of co-innovation platforms, there is still a need for a more comprehensive understanding of the co-innovation phenomenon. To address this gap, this research aims to identify the critical success factors of co-innovation platforms and provide an extensive analysis of the variables that determine their effectiveness.

This study presents a systematic literature review of co-innovation platforms based on an analysis of 89 articles published in 50 scholarly journals in the disciplines of information systems, marketing and business, covering the years from 2006 to 2022.

The review synthesizes the current state of scientific knowledge and groups prior studies thematically as critical success factors of co-innovation platforms. As a result, eight success factors have been identified in terms of quantity and quality of contributions. These factors include product involvement, perceived fairness, sense of community, interactive environment, employee involvement, participant diversity, assessment structure and task design.

The study consolidates existing research about the critical success of co-innovation platforms. It also provides a research framework that incorporates a diverse set of variables that can be used to assess co-innovation performance in future studies.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

The purpose of this paper is to provide insights into the current practice, challenges and future development trends of intelligent compaction (IC) technology from a bibliometric perspective.

A bibliometric analysis on IC-relevant studies is presented. Through this quantitative manner, insights into the current IC research practice and development trends have been derived from the perspectives of publications and citations, spatial distribution, knowledge construction, structural variations, existing problems, and conclusions and recommendations.

Currently, IC applications are confronted with the issues of intelligent compaction measurement values (ICMVs) applicability, autonomous control, specifications and applications. To address the issues, three potential research directions are identified: a comprehensive ICMV measurement system that is designated for single layer analysis; autonomous control mechanisms with integrated management capabilities that can efficiently collaborate all stakeholders; and a standardized application workflow and the cost-benefit evaluation of IC in the context of the full life cycle.

The literature used in this paper is collected from the Web of Science. Although the database covers almost all the important publications in IC field, studies not indexed by the database are not considered.

This research quantitatively analyzes the current IC practice and development trends from the perspectives of bibliometric analysis. It provides an overview of the knowledge construction and development of IC technology. The discussions about the problems and the suggested solutions can be useful for those interested in this field.

This study explores the response of consumer confidence in policy uncertainty in the Japanese context. The study also considers the dynamism of stock market behavior and financial stress and its impact on consumer confidence, which has remained unaddressed in the literature. The role of these control variables has important implications for policy discussions, particularly when other countries can learn from Japanese experiences.

The nonlinear autoregressive distributed lag model postulated by Shin et al. (2014) was used for studying the asymmetric response of consumer confidence to policy uncertainty. This method has improved estimates compared to traditional linear cointegration methods.

The findings confirm the asymmetric impact of policy uncertainty on the consumer confidence index in Japan. The impact of the rise in policy uncertainty is greater than that of a fall in asymmetry on consumer confidence in Japan. Furthermore, the Wald test confirmed asymmetric behavior.

The contribution of this study is threefold. First, this study contributes to the extant literature by analyzing the asymmetric response of consumer confidence to policy uncertainty, controlling for both the financial stress and stock price indices. Second, to test the robustness of the exercise, the study utilized different frequencies of observations. Third, this study is the first to utilize the concept of Arbatli et al. (2017) to formulate a combined index of uncertainty based on economic policy uncertainty index, along with uncertainty indices such as fiscal, monetary, trade and exchange rate policies to study the overall impact of policy uncertainty.