Huaping Sun, Bless Kofi Edziah, Anthony Kwaku Kporsu
et al.
Abstract It is widely accepted that technological innovation reduces energy intensity and carbon emissions without compromising global economic growth. Although new innovative developments tend to be concentrated in a few developed countries, transboundary spillover of technological innovation influences the energy efficiency and sectoral performance of other countries. A more thorough assessment of international knowledge spillover related to energy intensity reduction can enhance understanding of mitigation opportunities and costs. This study investigated, therefore, the effects of technological innovation within certain countries on the energy efficiency performance of neighboring countries. We used data from the OECD Triadic Patent Families database for 24 innovating countries between the years 1994 and 2013. Accounting for geographical distance, our results showed a positive, significant relationship between knowledge spillover and country-specific energy efficiency performance. All countries showed a sustainable efficiency growth trend, which indicates a steady increase in energy efficiency. Germany, France, the UK, the Netherlands, and Switzerland are the most energy efficient countries. These results have policy implications for sustainable energy management and environmental sustainability, highlighting the need to develop domestic research and development capabilities that increase innovation-based infrastructure.
Function offloading is a promising solution to address limitations concerning computational capacity and available energy of Connected Automated Vehicles~(CAVs) or other autonomous robots by distributing computational tasks between local and remote computing devices in form of distributed services. This paper presents a generic function offloading framework that can be used to offload an arbitrary set of computational tasks with a focus on autonomous driving. To provide flexibility, the function offloading framework is designed to incorporate different offloading decision making algorithms and quality of service~(QoS) requirements that can be adjusted to different scenarios or the objectives of the CAVs. With a focus on the applicability, we propose an efficient location-based approach, where the decision whether tasks are processed locally or remotely depends on the location of the CAV. We apply the proposed framework on the use case of service-oriented trajectory planning, where we offload the trajectory planning task of CAVs to a Multi-Access Edge Computing~(MEC) server. The evaluation is conducted in both simulation and real-world application. It demonstrates the potential of the function offloading framework to guarantee the QoS for trajectory planning while improving the computational efficiency of the CAVs. Moreover, the simulation results also show the adaptability of the framework to diverse scenarios involving simultaneous offloading requests from multiple CAVs.
María Isabel Rivas Ginel, Janiça Hackenbuchner, Alina Secară
et al.
This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on interview data from twenty-nine industry stakeholders collected within the LT-LiDER project, the study analyses how human value, technological value, efficiency, and adaptability are articulated across different professional roles. Using Chesterman's framework of translation ethics and associated values as an analytical lens, the paper shows that efficiency-oriented technological values aligned with the ethics of service have become baseline expectations in automated production environments, where speed, scalability, and deliverability dominate evaluation criteria. At the same time, human value is not displaced but repositioned, emerging primarily through expertise, oversight, accountability, and contextual judgment embedded within technology-mediated workflows. A central finding is the prominence of adaptability as a mediating value linking human and technological domains. Adaptability is constructed as a core professional requirement, reflecting expectations that translators continuously adjust their skills, roles, and identities in response to evolving tools and organisational demands. The paper argues that automation reshapes rather than replaces translation value, creating an interdependent configuration in which technological efficiency enables human communicative work.
A well-functioning supply chain is a key to success for every business entity. Having an accurate projection on inventory offers a substantial competitive advantage. There are many internal factors like product introductions, distribution network expansion; and external factors such as weather, extreme seasonality, and changes in customer perception or media coverage that affects the performance of the supply chain. In recent years Artificial Intelligence (AI) has been proved to become an extension of our brain, expanding our cognitive abilities to levels that we never thought would be possible. Though many believe AI will replace humans, it is not true, rather it will help us to unleash our true strategic and creative potential. AI consists of a set of computational technologies developed to sense, learn, reason, and act appropriately. With the technological advancement in mobile computing, the capacity to store huge data on the internet, cloud-based machine learning and information processing algorithms etc. AI has been integrated into many sectors of business and been proved to reduce costs, increase revenue, and enhance asset utilization. AI is helping businesses to get almost 100% accurate projection and forecast the customer demand, optimizing their R&D and increase manufacturing with lower cost and higher quality, helping them in the promotion (identifying target customers, demography, defining the price, and designing the right message, etc.) and providing their customers a better experience. These four areas of value creation are extremely important for gaining competitive advantage. Supply-chain leaders use AI-powered technologies to a) make efficient designs to eliminate waste b) real-time monitoring and error-free production and c) facilitate lower process cycle times. These processes are crucial in bringing Innovation faster to the market.
Win Sithu Maung, Satoshi Tsuyuki, Takuya Hiroshima
et al.
Abstract Estimating Above Ground Biomass (AGB) of mangroves provides crucial information for regional and global blue carbon strategies. Despite growing interest in mangrove AGB estimation using a remote sensing approach, the effectiveness of this advanced method has not been evaluated for mangrove forests in Myanmar. This study estimated the AGB of Wunbaik Mangrove Forest (WMF) in Myanmar using machine learning models with data from Sentinel-2, Sentinel-1, and Advanced Land Observing Satellite Phased Arrayed L-band Synthetic Aperture Radar (ALOS-PALSAR) HH and HV polarizations and Canopy Height Model. Reference AGB information was derived from field inventory plots via an allometric equation. Initially, we tested machine learning models such as Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boost (XGBoost). The results revealed that the RF model outperformed the other models, yielding a higher coefficient of determination (R2) of 0.33 and a Root Mean Square Error (RMSE) of 32.05 Mg ha−1. We then set up different scenarios to improve the performance of the RF model for AGB estimation. Through different feature selection approaches, we identified features highly correlated with the field AGB, enhancing the RF model’s performance and resulting in the highest improvement in R2: 0.48 and RMSE: 28.12 Mg ha−1. In this study, an AGB map of the WMF was generated using the best RF model. The predicted AGB distribution ranged from 22.266 Mg ha−1 to 181.948 Mg ha−1 in 2019. Compared with global datasets such as GEDI L4B and ESA CCI predictions, the proposed method provides a more accurate prediction of AGB for Wunbaik Mangrove, enhancing blue carbon information in Myanmar.
General. Including nature conservation, geographical distribution, Technological innovations. Automation
This paper presents a deep neural network (DNN)-embedded mixed-integer linear programming (MILP) model for fault prediction and production optimization in tablet pressing machines. The DNN predicts the probability of failures during the tablet pressing process by analyzing key operational parameters such as pressure, temperature, humidity, speed, vibration, and number of maintenance cycles. The MILP model optimizes the temperature and humidity settings, production schedules, and maintenance planning to maximize total profit while minimizing penalties for fault pressing, energy consumption, and maintenance costs. To integrate DNN into the MILP framework, Big-M constraints are applied to linearize the Rectified Linear Unit (ReLU) activation functions, ensuring solvability and global optimality of the optimization problem. A case study using the Kaggle dataset demonstrates the model’s ability to dynamically adjust production and maintenance schedules, enhancing profitability and resource utilization under fluctuating electricity prices. Sensitivity analyses further highlight the model’s robustness to variations in maintenance and energy costs, striking an effective balance between cost efficiency and production quality, which makes it a promising solution for intelligent scheduling and optimization in complex manufacturing environments.
Engineering machinery, tools, and implements, Technological innovations. Automation
This paper systematically explores the current research status and application potential of digital twin technologies (DTs) in sustainable development management, using bibliometric and segmented regression analyses to reveal the field’s dynamic trends and research hotspots. Based on the analysis of 421 papers extracted from the Scopus database, this paper summarises the vital role of DTs in smart cities, circular economy, and Industry 4.0. It identifies the key challenges to their implementation, including the digital divide, high cost, data privacy protection, and technical complexity. The paper further suggests future research directions through case studies and theory: exploring the integration of DTs with AI, enhancing interdisciplinary collaboration, and developing low-cost implementations. The contribution of this paper is to provide comprehensive academic support and practical suggestions for the application and development of DTs.
As large-scale social data explode and machine-learning methods evolve, scholars of entrepreneurship and innovation face new research opportunities but also unique challenges. This chapter discusses the difficulties of leveraging large-scale data to identify technological and commercial novelty, document new venture origins, and forecast competition between new technologies and commercial forms. It suggests how scholars can take advantage of new text, network, image, audio, and video data in two distinct ways that advance innovation and entrepreneurship research. First, machine-learning models, combined with large-scale data, enable the construction of precision measurements that function as system-level observatories of innovation and entrepreneurship across human societies. Second, new artificial intelligence models fueled by big data generate 'digital doubles' of technology and business, forming laboratories for virtual experimentation about innovation and entrepreneurship processes and policies. The chapter argues for the advancement of theory development and testing in entrepreneurship and innovation by coupling big data with big models.
Edward D. Lee, Christopher P. Kempes, Manfred D. Laubichler
et al.
Innovation and obsolescence describe the dynamics of ever-churning social and biological systems, from the development of economic markets to scientific and technological progress to biological evolution. They have been widely discussed, but in isolation, leading to fragmented modeling of their dynamics. This poses a problem for connecting and building on what we know about their shared mechanisms. Here we collectively propose a conceptual and mathematical framework to transcend field boundaries and to explore unifying theoretical frameworks and open challenges. We ring an optimistic note for weaving together disparate threads with key ideas from the wide and largely disconnected literature by focusing on the duality of innovation and obsolescence and by proposing a mathematical framework to unify the metaphors between constitutive elements.
Purpose of review In this review, we discuss the timeline of innovation and technologic development in home hemodialysis (HHD) in the United States and the legislative approvals that accompanied them. Recent findings The most recently FDA-approved home hemodialysis devices provide features that include on-demand and batch dialysate generation, access disconnect for venous needle dislodgement, touchscreen interface with visual and auditory prompts and animations, drop-in sterilized cartridges with prestrung tubing, hot water disinfection of tubing allowing extended-use, dialysate flow rates as high as 500 ml/min, as well as remote treatment monitoring capabilities. Furthermore, wearable/portable dialysis devices are currently under development to simplify dialysis delivery to patients with end-stage kidney disease. Summary Home hemodialysis devices providing longitudinal hemodialysis across different clinical settings, virtual reality headsets for more personalized training, automated patient support, as well as wearable device development and innovations give hope for a future where home hemodialysis is more accessible and seamless.
M. Isabel Sánchez Hernández, Francisca Castilla-Polo
This study aims to provide a preliminary estimate of the degree of implementation of Responsible Research and Innovation (RRI) in agri-food cooperatives; to that end, it proposes an instrument for measuring RRI as a reflective construct. A secondary aim is to demonstrate the direct and positive relationship between RRI and international market orientation. Data were sourced from 60 managers from the top 100 reputable agri-food cooperatives in Spain. By conducting a descriptive statistical analysis, exploratory factor analysis, confirmatory tetrad analysis, and consistent PLS path modelling, it has been demonstrated that the RRI construct is reflective and unidimensional and has a direct relationship with the international orientation of cooperatives. While future research is required to refine the empirical application of RRI indicators to agri-food cooperatives, they can play a significant role in bridging the divide between theoretical RRI concepts and the development of pragmatic indicators for use in business environments.
The present article aims to empirically confirm the role of start-up ecosystems in shaping and increasing the role of entrepreneurial activity in the socio-economic development of the Baltic countries (Latvia, Lithuania, Estonia). The following tasks were addressed sequentially: determining the relevance of the topic of start-up ecosystems, reflecting the given multifaceted phenomenon in the socio-economic works by contemporary authors, and examining the experience of teams of international research projects focused on start-up ecosystems. Subsequently, the role of start-up ecosystems in the Baltic countries was assessed from a comparative standpoint. The paramount factors that serve as significant positive conditions for their impact on start-up ecosystems and the factors that hinder their positive dynamics were identified. The empirical basis for the research was international research projects: Global Start-up Ecosystem Report, data science competition platform Kaggle, Global Entrepreneurship Monitor (GEM), Global Talent Competitiveness Index (GTGI)), Global Competitiveness Report by World Economic Forum, as well as the authors’ own research studies on entrepreneurial activity and entrepreneurial universities. Causal and comparative analyses were used as the main research methods. During the research work, the terminology used was clarified so that it matched the main subject of the study – start-up ecosystems as the most important factor in the development of the innovative economy of countries and regions. A ranking of the factors that most positively influence the effectiveness of start-up ecosystems, especially from the perspective of their financing opportunities, were carried out. The study results showed the importance of start-up ecosystems among other drivers of the country’s socio-economic growth. The role of higher education, state and municipal support in expanding the practice of start-up ecosystems was also shown. In this aspect, it is extremely important to expand the practice of entrepreneurial education for students of all specialities, gradually transforming educational and research higher schools into entrepreneurial universities.
Florian Saling, Andrea Emanuele Maria Casini, Andreas Treuer
et al.
The use of eXtended Reality (XR) technologies in the space domain has increased significantly over the past few years as it can offer many advantages when simulating complex and challenging environments. Space agencies are currently using these disruptive tools to train astronauts for Extravehicular Activities (EVAs), to test equipment and procedures, and to assess spacecraft and hardware designs. With the Moon being the current focus of the next generation of space exploration missions, simulating its harsh environment is one of the key areas where XR can be applied, particularly for astronaut training. Peculiar lunar lighting conditions in combination with reduced gravity levels will highly impact human locomotion especially for movements such as walking, jumping, and running. In order to execute operations on the lunar surface and to safely live on the Moon for an extended period of time, innovative training methodologies and tools such as XR are becoming paramount to perform pre-mission validation and certification. This research work presents the findings of the experiments aimed at exploring the integration of XR technology and parabolic flight activities for astronaut training. In addition, the study aims to consolidate these findings into a set of guidelines that can assist future researchers who wish to incorporate XR technology into lunar training and preparation activities, including the use of such XR tools during long duration missions.
The main objective of the article was to find out what the situation is with Fairtrade products on the Czech and Slovak markets in relation to consumed primary raw materials and their Fairtrade epremium, and also the supply of these products in retail chains operating in the Czech Republic (including products that are marked with their private labels). To meet the first part of the objective, secondary data taken from the Fairtrade Czech Republic and Slovakia annual reports involving the 2017 – 2021 period were used. These reports showed that the consumption of cocoa beans and coffee beans in the production of Fairtrade products was on an upward trend in the years under review. The opposite was true for cane sugar, which was also reflected in the evolution of the Fairtrade premium for this commodity. To meet the second part of the objective, a qualitative mystery shopping method was used. On the basis of this method it was found that Kaufland has the highest number of Fairtrade products among the retail chains operating in the Czech Republic, followed by Penny, while Albert supplies only one product. Another important fact was that most of the Fairtrade products provided by the retail units surveyed were sold under their private labels and yet not from well-known manufacturers. It is the increase in the number of Fairtrade products offered under private labels, based on negotiations with the producers of these products, which would ultimately lead to an increase in Fair trade premiums for growers' cooperatives.
Ozdemir Cetin, Murat Cakiroglu, Cüneyt Bayılmış
et al.
In today's world, many technologically advanced countries have realized that real power lies not in physical strength but in educated minds. As a result, every country has embarked on restructuring its education system to meet the demands of technology. As a country in the midst of these developments, we cannot remain indifferent to this transformation in education. In the Information Age of the 21st century, rapid access to information is crucial for the development of individuals and societies. To take our place among the knowledge societies in a world moving rapidly towards globalization, we must closely follow technological innovations and meet the requirements of technology. This can be achieved by providing learning opportunities to anyone interested in acquiring education in their area of interest. This study focuses on the advantages and disadvantages of internet-based learning compared to traditional teaching methods, the importance of computer usage in internet-based learning, negative factors affecting internet-based learning, and the necessary recommendations for addressing these issues. In today's world, it is impossible to talk about education without technology or technology without education.