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The call for a new paradigm in politics and governance has become a planetary imperative. Humanity is at a critical juncture; unless we mature as a species and become net-positive to nature the human experiment may (soon) end. We have become our own biggest threat. This chapter explores the foundations, as well as systemic barriers, for the shift to a new and life-centred paradigm in politics and governance. Offering a systemic exploration of the root causes of our sustainability crises and how to address this, based on the cosmology and evolutionary principles of complex living systems. Applying Living Systems Protocols from the EARTHwise Constitution for a Planetary Civilization, and its framework of five Future Archetypes, for developing our transformative capacities to address the systemic thrivability barriers of mechanistic systems and worldviews. With case-study examples of new paradigm tools, systems and technologies that enable a decentralization of governance and democratization of ownership. As such empowering the systemic conditions and maturation pathways for a thriving planetary civilization. The chapter completes with a brief practice for developing our future human capacities and inner consciousness shifts for a new paradigm in politics and governance.

This study aims to design and validate a theoretical model for capacitive imaging (CI) sensors that incorporates the interelectrode shielding and surrounding shielding electrodes. Through experimental verification, the effectiveness of the theoretical model in evaluating CI sensors equipped with shielding electrodes has been demonstrated.

The study begins by incorporating the interelectrode shielding and surrounding shielding electrodes of CI sensors into the theoretical model. A method for deriving the semianalytical model is proposed, using the renormalization group method and physical model. Based on random geometric parameters of CI sensors, capacitance values are calculated using both simulation models and theoretical models. Three different types of CI sensors with varying geometric parameters are designed and manufactured for experimental testing.

The study’s results indicate that the errors of the semianalytical model for the CI sensor are predominantly below 5%, with all errors falling below 10%. This suggests that the semianalytical model, derived using the renormalization group method, effectively evaluates CI sensors equipped with shielding electrodes. The experimental results demonstrate the efficacy of the theoretical model in accurately predicting the capacitance values of the CI sensors.

The theoretical model of CI sensors is described by incorporating the interelectrode shielding and surrounding shielding electrodes into the model. This comprehensive approach allows for a more accurate evaluation of the detecting capability of CI sensors, as well as optimization of their performance.

This article offered two meshfree algorithms, namely the local radial basis functions-finite difference (LRBF-FD) approximation and local radial basis functions-differential quadrature method (LRBF-DQM) to simulate the multidimensional hyperbolic wave models and work is an extension of Jiwari (2015).

In the evolvement of the first algorithm, the time derivative is discretized by the forward FD scheme and the Crank-Nicolson scheme is used for the rest of the terms. After that, the LRBF-FD approximation is used for spatial discretization and quasi-linearization process for linearization of the problem. Finally, the obtained linear system is solved by the LU decomposition method. In the development of the second algorithm, semi-discretization in space is done via LRBF-DQM and then an explicit RK4 is used for fully discretization in time.

For simulation purposes, some 1D and 2D wave models are pondered to instigate the chastity and competence of the developed algorithms.

The developed algorithms are novel for the multidimensional hyperbolic wave models. Also, the stability analysis of the second algorithm is a new work for these types of model.

An ecologically sustainable future calls for fruitful dialogues between spirituality, modern science and policymaking at large. What could be that connects them all? We found out that ideas about holism exist across time, space, culture and thinkers – ranging from mathematics, philosophy, sociology, medicine, education, religion and quantum physics to finding its roots in ancient Indian Vedic tradition and later usage in Greek and Roman cultures.

This chapter takes a look at the history and intricacies of two seemingly distinct but interconnected fields – spirituality and modern science, particularly quantum science – with an aim to uncover what these fields can teach us about the idea of holism. This chapter, therefore, highlights one of the most fundamental and profound spiritual principles of the unity and interconnectedness of the entire universe – encapsulated in the concept of holism – and its practical applications in approaching sustainable development. We hope to ignite further research on this topic.

Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

This study aims to explore the interplay between community dynamics and knowledge production using the quantum computing research field as a case study. Quantum computing holds the promise of dramatically increasing computation speed and solving problems that are currently unsolvable in a short space of time. In this highly dynamic area of innovation, computer companies, research laboratories and governments are racing to develop the field.

After constructing temporal co-authorship networks, the authors identify seven different events affecting communities of researchers, which they label: forming, growing, splitting, shrinking, continuing, merging, dissolving. The authors then extract keywords from the titles and abstracts of their contributions to characterize the dynamics of knowledge production and examine the relationship between community events and knowledge production over time.

The findings show that forming and splitting are associated with retaining in memory what is currently known, merging and growing with the creation of new knowledge and splitting, shrinking and dissolving with the curation of knowledge.

Although the link between communities and knowledge has long been established, much less is known about the relationship between the dynamics of communities and their link with collective cognitive processes. To the best of the authors’ knowledge, the present contribution is one of the first to shed light on this dynamic aspect of community knowledge production.

This study aims to assess the use of variational quantum imaginary time evolution for solving partial differential equations using real-amplitude ansätze with full circular entangling layers. A graphical mapping technique for encoding impulse functions is also proposed.

The Smoluchowski equation, including the Derjaguin–Landau–Verwey–Overbeek potential energy, is solved to simulate colloidal deposition on a planar wall. The performance of different types of entangling layers and over-parameterization is evaluated.

Colloidal transport can be modelled adequately with variational quantum simulations. Full circular entangling layers with real-amplitude ansätze lead to higher-fidelity solutions. In most cases, the proposed graphical mapping technique requires only a single bit-flip with a parametric gate. Over-parameterization is necessary to satisfy certain physical boundary conditions, and higher-order time-stepping reduces norm errors.

Variational quantum simulation can solve partial differential equations using near-term quantum devices. The proposed graphical mapping technique could potentially aid quantum simulations for certain applications.

This study shows a concrete application of variational quantum simulation methods in solving practically relevant partial differential equations. It also provides insight into the performance of different types of entangling layers and over-parameterization. The proposed graphical mapping technique could be valuable for quantum simulation implementations. The findings contribute to the growing body of research on using variational quantum simulations for solving partial differential equations.

Gallic acid is a substance that is widely found in nature. Initially, it was only used as a corrosion inhibitor to retard the rate of corrosion of metals. In recent years, with intensive research by scholars, the modification of coatings containing gallic acid has become a hot topic in the field of metal protection. This study aims to summarize the various preparation methods of gallic acid and its research progress in corrosion inhibitors and coatings, as well as related studies using quantum chemical methods to assess the predicted corrosion inhibition effects and to systematically describe the prospects and current status of gallic acid applications in the field of metal corrosion inhibition and protection.

First, the various methods of preparation of gallic acid in industry are understood. Second, the corrosion inhibition principles and research progress of gallic acid as a metal corrosion inhibitor are presented. Then, the corrosion inhibition principles and research progress of gallic acid involved in the synthesis and modification of various rust conversion coatings, nano-coatings and organic resin coatings are described. After that, studies related to the evaluation and prediction of gallic acid corrosion inhibition on metals by quantum chemical methods are presented. Finally, new research ideas on gallic acid in the field of corrosion inhibition and protection of metals are summarized.

Gallic acid can be used as a corrosion inhibitor or coating in metal protection.

There is a lack of research on the synergistic improvement of gallic acid and other substances.

The specific application of gallic acid in the field of metal protection was summarized, and the future research focus was put forward.

To the best of the authors’ knowledge, this paper systematically expounds on the research progress of gallic acid in the field of metal protection for the first time and provides new ideas and directions for future research.

The purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational agility capability in Industry 4.0 manufacturing and logistics operations.

A multi-case study approach is used to determine the impact of quantum-inspired computing technology in manufacturing and logistics processes from the supplier perspective. A literature review provides the basis for a framework to identify a set of flexibility and agility operational capabilities enabled by Industry 4.0 Information and Digital Technologies. The use cases are analyzed in depth, first individually and then jointly.

Study results suggest that quantum-inspired computing technology has the potential to harness and boost companies' operational flexibility to enhance operational agility in manufacturing and logistics operations management, particularly in the Industry 4.0 context. An exploratory model is proposed to explain the relationships between quantum-inspired computing technology and the deployment of operational agility capabilities.

This is study explores the use of quantum-inspired computing technology in Industry 4.0 operations management and contributes to understanding its potential to enable operational agility capability in manufacturing and logistics operations.