Addressing inclusion,innovation,and sustainability challenges through the lens of economic geography:Introducing the hierarchical regional innovation system

The world is facing dramatic challenges related to environmental sustainability at an accelerating pace.In this context,the field of economic geography(EG)has been playing an important role in understanding both the socioeconomic and technological dimensions of these challenges,as it deals with a variety of complementary notions and perspectives.Departing from this lens,our aim is to explore a conceptual framework that can help us to understand environmental changes relating to multi-dimensional territorial development,notably in eco-nomic contexts where inequality is high,and stratification based on hierarchies regulate social and economic life.Based on the territory concept,we propose the original notion of a hierarchical regional innovation system(HRIS)that emphasises the pervasive role of hierarchies(powers)in regional innovation systems and illustrate its value with evidence and case studies from extant literature on sustainability transitions.The HRIS can help us understand and promote development paths considering the contribution of inclusive eco-innovations(another original conceptual amalgam).Through some empirical cases from other studies in low-carbon transitions,we show the application of the HRIS(and inclusive eco-innovation)framework.In conclusion,we provide incen-tives to explore new regional innovation systems,alongside the HRIS,adapted to different regions worldwide and centred on the inclusiveness of people and places.

Image Fusion Using Wavelet Transformation and XGboost Algorithm

Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with greater precision through the integration of computational image analysis and feature selection.The performance of images is improved by segmenting them employing the K-Means algorithm.The segmentation method aids in identifying specific regions of interest,using Particle Swarm Optimization(PCA)for trait selection and XGBoost for data classification.Extensive trials confirm the model’s exceptional visual performance,achieving an accuracy of up to 97.067%and providing good objective indicators.

Politicizing Responsible Innovation:Responsibility as Inclusive Governance

This paper aims to provide the historical and conceptual bases underlying the inclusionary transition of European innovation policy,and critical analysis of the difficulties relating to the political nature of this transition.In the 50s and 60s of last century,linear innovation models operated on the basis of a clear division of roles among the different actors in innovation and fundamentally economistic‐based strategies.The following decades saw innovation policies progressively recognize the multi‐dimensional and complex nature of innovation and the need to make adjustments,but always in explicit response to the competitiveness imperative.More recent RRI(Responsible Research and Innovation)strategy within the European Union,in contrast,demands opening up the whole innovation process(including values and motivations)to collective decision,i.e.,approaching responsible innovation as inclusive innovation.This paper appraises this important development primarily on the basis of in‐depth analysis of the main policy literature on innovation,and also on the grounds of related academic literature.As a result,we conclude that the bid for collaboration models cohabits constitutively with another set of dynamics aimed at strengthening centralized and prescriptive forms of innovation.In other words,that inclusionary or political eagerness represented through RRI must grapple with the strategic imperative of competitiveness and economic development.Hence,fundamental tension exists,which should be elucidated in light of the objectives,demands and considerations that are integrated,and cease to be integrated,in innovation dynamics and trajectories.

BUILDING A MODERATELY PROSPEROUS SOCIETY IN ALL RESPECTS——New-Type Industrialization

After announcing the goal of building a moderately prosperous society in all respects by 2020, the Chinese leadership also called for a new path of industrialization, putting a premium on quality and new development concepts. Unlike traditional industrialization in the broad or narrow sense, new-type industrialization features synergy between primary, secondary, and tertiary industries, integration between traditional economy and the new economy, environmental protection, technology progress, and innovation. It represents an inclusive approach to industrial development. At the fundamental level, the success of China’s new-type industrialization can be attributed to China’s inclusive learning and innovations.