Search

Building a local supply chain requires separating the regions and creating alliances with local partners and customers, resulting in a new business model. In local supply chains, the factory procures material, parts, and preassembled elements from local suppliers and sells the final products to local customers. Three-dimensional printing (3DP) has the potential to enable a more local, globally connected, and efficient supply chain through reduced inventory and transportation costs transforming the make-to-stock to the make-on-demand production cycle. In this study, we use an integrated Interpretive Structural Model and Decision-making Trial and Evaluation Laboratory technique to explore and assess the challenges faced by the 3DP companies to become enabling partners in the localized supply chains. The scope of the study, which was limited to 3DP of medical parts and components, identified that regulatory compliance, stringent quality standards, and lack of design expertise are significant barriers to developing localized three-dimensional printing ecosystems. Furthermore, the study identified immediate support from the local government, the high collaboration between the stakeholders, and the need for change in business approach as the key drivers for developing 3DP-enabled localized supply chain ecosystems. Post-print / Final draft

Determining pore sizes of porous media accurately is essential for many reasons. The standard ASTM F316 describing calculations used in gas-liquid displacement (GLD) porometry includes a factor B or a capillary constant. The standard does not explain the nature of this factor and the reasons for using its value. This work aims to investigate the capillary constant and to understand its meaning and applicability in calculating the pore diameter. Another goal is to assess the pore diameter measured in GLD porometry by comparing it with pore diameters measured with image analysis and cut point test methods. Seven filter media samples with as simple a structure as possible were analyzed. An investigation of the capillary constant revealed at least five different approaches, of which all are by no means applied for the calculations of pore size. Using the approach described in standard ASTM F316 to adjust the values obtained by GLD porometry was found unsuitable for the simply structured samples studied in this work. This work shows that the pore diameters measured by GLD porometry are most comparable with the other studied techniques when using Silwick as the wetting liquid. The raw data of bubble point pore and mean flow pore diameters measured by GLD porometry are similar to the largest pore sizes and mean pore diameters measured by image analysis and cut point test methods. This, in turn, confirms the absence of the need to use any constants for calculating the pore diameters for the samples studied in this work. Post-print / Final draft

In this paper, a novel integrated SHE-NLC control is proposed for the mitigation of unwanted lower-order harmonics in the cascaded H-bridge multilevel inverter. The proposed algorithm has been developed by hybridizing the NLC and SHE methods, in an attempt to keep the merits of both the individual control. The switching angles and nearest levels are calculated by applying the Genetic Algorithm (GA). The proposed technique reduces the calculation time and implementation complexity, thus can be a viable alternative to the real time implementation for SHE. Integrated NLC-SHE control is tested by varying the modulation index and load dynamics. This technique resulted in the reduction in Total Harmonic Distortion (THDs) in load voltage and current. Comparative analysis of NLC, SHE and Integrated NLC-SHE technique is also performed on the CHB nine-level inverter. There is significant reduction in voltage and current THD values and power losses. Efficiency of the inverter is increased. The efficacy of the proposed control CHB nine-level is tested on MATLAB Simulink environment and further validated by experimental results. Publishers version

The required purchasing skills have been evolving due to supply chain globalization, sustainability, and environmental requirements. Modern purchasing skills are also influenced by the expanding adaptation of complex Information Systems (IS) in enterprises. Complex technology purchasing requires the management of multiple organizations and unique competences, hence the needed IS purchasing skills required studies from a different angle. Compared to previous studies, the purpose of this study was to identify the skills required from a purchaser to manage complex IS purchases and address their risks. In-depth qualitative research reveals that the IS purchaser is required to understand SW methodologies and possess strong interorganizational skills in addition to traditional purchasing skills in order to run successful IS purchases. Based on the findings, the study proposes additional technical and project methodological training for educators and purchasing professionals to succeed in IS purchases. Publishers version

Finland is experiencing a startup boom. Startups are innovative young companies aimed at rapid revenue growth. Unfortunately, most of them fail within the first years, leaving their founders without a job and possibly in debt. Previous research did not yet establish how the founders fare after founding their company. This study explores whether founding a high-growth startup constitutes a new social risk, that is, a work situation in a postindustrial society that lowers the founder’s welfare. This study analyzes data collected in interviews with founders and experts and in participant observations. In an innovative approach, this study explores the difficulties of high-growth startup founders from the time of founding their companies on. Findings show that founders experience social isolation and financial and health problems from the moment of founding their startups. This decline in welfare is limited to founders who were not in precarious situations when founding their companies. Findings enhance our understanding of high-growth startups and of new social risks. Discussions on positive economic effects of the startup boom should also consider the negative effects on the founders’ welfare. Publishers version

Transparent, flexible, and chemically stable conducting electrodes are the most important key components for fabricating optoelectronic devices. However, in conventional bulk metal–semiconductor (MS) junctions, Fermi-level pinning is a major concern that limits the charge transport properties of the devices. In this work, we have designed MS junctions using two-dimensional (2D) MXene nanosheets and Al-doped ZnO nanoparticles as a metal and an n-type semiconductor, respectively. The heterojunction was formed by layer-by-layer self-assembly on an indium tin oxide (ITO) substrate and probed by the Pt/Ir scanning tunneling microscopy (STM) tip at room temperature. By recording the tunneling current of the components that in turn yielded the density of states of the materials, we could identify their energy positions to determine the band alignments. We then proceeded to form heterojunctions and characterized their current–voltage characteristics through scanning tunneling spectroscopy. The junctions showed rectification, and the rectification ratio varied with the semiconductor doping concentrations. However, the shift of the Fermi level toward the conduction band edge of the semiconductor reduces the Schottky barrier width and consequently lowers the rectification ratio. Additionally, the MS junction with the poly-allylamine (PAH)-functionalized MXene nanosheets and the ZnO layer show a nonrectifying nature with low contact resistance at the interface. This work shows how a functionalized 2D-metal MXene and doped ZnO nanoparticle can tune the MS junction properties, used for implementing various flexible optoelectronic devices and transistor applications. Post-print / Final draft

PurposeThis meta-analytic study tries to synthesize the mixed relationships between knowledge management technologies (KMT) and organizational performance as well as aims to explore the impacts of contextual elements, such as national culture, economy and industries, on these relationships.Design/methodology/approachFindings on various subjects from 40 previous empirical studies were examined using meta-analysis.FindingsIt was found that KMT are positively related to overall organizational performance as well as financial and nonfinancial performance and that the relationship between KMT and financial performance is stronger in developing economies than in developed economies.Practical implicationsIt helps practitioners better understand the role of KMT in organizational performance in various contexts and provides practical suggestions for KMT implementation.Originality/valueAs the first meta-analytic study to address the generalizability of KMT–organizational performance relationships, this paper offers an improved understanding of the benefits of KMT. It also expands knowledge about how contextual issues related to national culture, economies and industries affect KMT payoffs.

While the work realm moves toward digital environments, the antecedents of knowledge worker digital creativity remain poorly understood. This study investigated the digital work environment as a sociotechnical environment and contextual enhancer of knowledge worker digital creativity. We proposed a research model that links perceived organizational support, sense of virtual community and digital creativity. Furthermore, we proposed an indirect moderation model suggesting that the relationship between organizational support and digital creativity is moderated by the sense of virtual community that, in turn, is facilitated by technology ease of use. We tested the model with data collected from platform knowledge workers (N = 159) using partial least squares structural equation modelling (PLS-SEM). The results indicate that organizational support positively relates to digital creativity, and that the sense of virtual community moderates the effect of organizational support for digital creativity, whereas technology ease of use facilitates a sense of virtual community. Post-print / Final draft

Plastic waste disposal is among the most challenging problems of the current era. Therefore, new methods and applications for the utilization of waste plastics are increasingly needed. To find them, it is essential to research and develop the material properties of recycled plastics. The effect of different ultraviolet light (UV) stabilizers on the color stability, melt properties and tensile properties of mixed waste plastics blends was studied in this paper. The mixed waste plastics collected from two different waste sources were prepared as specimens by injection molding, and studied with two different types and loading amounts of UV stabilizers. UV absorbers (UVAs) and hindered amine light stabilizers (HALS) were used as UV stabilizers. A specimen produced without the addition of a UV stabilizer was used as a reference specimen of both the blends. After the accelerated weathering, the addition of a UVA provided an improved, smaller change in color than the addition of HALS. Among the tensile properties, the addition of UV stabilizers clearly improved the tensile strength and tensile modulus for almost all the studied specimens. Additionally, the melt properties of both the studied plastic blends were found to be increased by the addition of UV stabilizers. Post-print / Final draft

Wide-area measurement systems (WAMS) are efficient tools to estimate the fault location in the large-scale power systems. In this study, a fast and accurate deep learning based structure is proposed to detect the faulty lines and locate the fault based on the measured data of WAMS including phasor measurement units. To this end, a modulated gated recurrent unit deep learning based network named improved gated recurrent neural network has been proposed. The designed network, which has a recurrent neural network based structure, benefits from one update gate that can capture sudden changes in transient voltage and current signals and also enhance computational efficiency. Furthermore, to enhance robustness of the designed network under noisy conditions, a new informative-based loss function is formulated. The proposed loss function utilizes generalized form of mutual information to enhance robustness of designed network in the presence of Gaussian and non-Gaussian noises. The numerical results on IEEE 68-bus system verifies the effectiveness and superiority of the proposed method considering several operational conditions and comparison by two combined shallow-based networks and one deep learning based networks. Post-print / Final draft

Sector coupling has a remarkable role in the optimal fulfilment of the energy transition. In order to reduce emissions of the energy sector, but also to increase the flexibility of the electricity system, clean energy production solutions offering multi-sector flexibility are needed, such as power-to-heat technologies and various thermal energy storages. In this paper, the participation of power-to-heat technologies and thermal energy storages in the electricity market are examined. In particular, the paper aims to review the key enablers, barriers, and drivers for power-to-heat and thermal energy storages in the context of electricity markets. Additionally, the technical potential of power-to-heat technologies combined with thermal energy storages are examined. The study is based on a literature review and examines especially the context of Finnish energy system and market. Post-print / Final draft

Many gamification approaches use a one size fits all approach. Different gamification player types and associated preferences have been proposed, such as the gamification player type Hexad. According to the Hexad, people prefer different gameful activities, such as exploration, social activities, or competition. Similarly in hobbies, different things motivate and interest different people, such as some finding board games interesting, while others like hiking and going on camping trips. We propose that a person’s hobbies and interests provide an insight into what type of person they are, indicating what they might like, and could have a connection to gameful system preferences. In this paper, we explore the relationship between free-time activities and gamification player types, to enable earlier and faster detection of the player types and their preferences. The research was conducted by building a survey to measure the free-time activities of people and also measure the Hexad player type as defined by Marczewski and Tondello et al. Significant relationships were found between free-time activity variables “Active physical exerciser”, “Audience of cultural events”, and the player type Philanthropist. Overall, these results indicate that free-time activities can have correlations with player types and reported hobbies can be used as a proxy when selecting personalized gamification approaches. Post-print / Final draft

The project strength to industrial 3D printing via networking and research, VERKOTA (Verkostoitumisella voimaa 3D-tulostukseen) is funded by the European Regional Development Fund (ERDF). This project is a partnership between LUT University (Research group of Laser Material Processing & Additive Manufacturing, and Steel Structures), and University of Turku. Several industrial partners have also joined this project to upscale the R&D activities. The project started on 1.1.2021 and continued until 31.3.2023. The project comprised of educational events and research cases in the field of additive manufacturing (AM). Educational events were organized in the form of online webinars and a practical hands-on type of workshop, which were free to register and join. Webinars concluded a variety of presentations of present state of AM from industry experts to research and case studies conducted in LUT and UTU Universities. Practical workshop concluded basics of AM processes and design for additive manufacturing (DfAM), and an individual assignment, which comprised of designing, manufacturing, and post-processing of own AM parts from start to finish. Workshop was aimed at designers with little to no earlier experience in AM. Research content for the project concluded various research and case studies focusing on metal AM. Studies included distinct topics in the field of material science and characterization, and design and structural optimization. Studies introduced and discussed in this report were conducted in LUT Laser processing & Additive manufacturing and Steel structures facilities. Verkostoitumisella voimaa 3D-tulostukseen (VERKOTA) on Euroopan aluekehitysrahaston (EAKR) rahoittama projekti. Tämä projekti on yhteistyö LUT-yliopiston (Laser Material Processing & Additive Manufacturingin ja Steel Structures -tutkimusryhmä) ja Turun yliopiston välillä. Myös useat teolliset kumppanit ovat liittyneet tähän hankkeeseen T&K-toiminnan tehostamiseksi. Hanke alkoi 1.1.2021 ja jatkui 31.3.2023 saakka. Hanke koostui lisäävän valmistuksen (AM) alan koulutustilaisuuksista ja tutkimustapauksista. Koulutustilaisuuksia järjestettiin verkkoseminaarien ja käytännönläheisen työpajan muodossa, joihin oli vapaa rekisteröityminen ja osallistuminen. Webinaarit sisälsivät erilaisia esitelmiä AM:n teknologiasta ja nykytilasta alan asiantuntijoilta sekä LUT:n ja UTU:n yliopistoissa toteutettuja tutkimuksia ja tapaustutkimuksia. Käytännön työpaja sisälsi AM-prosessien ja lisäävän valmistuksen suunnittelun (DfAM) perusteet sekä yksilöllisen tehtävänannon, joka koostui omien AM-osien suunnittelusta, valmistuksesta ja jälkikäsittelystä alusta loppuun. Työpaja oli suunnattu suunnittelutyötä tekeville henkilöille, joilla ei ollut aiempaa kokemusta lisäävästä valmistuksesta. Hankkeen tutkimussisältö koostui erilaisista metallien lisäävään valmistukseen keskittyvistä tutkimuksista ja tapaustutkimuksista. Tutkimuksiin sisältyi erillisiä aiheita materiaalitieteen ja karakterisoinnin sekä suunnittelun ja rakenteiden optimoinnin alalla. Tässä raportissa esitellyt ja käsitellyt tutkimukset tehtiin LUT Laser Processing & Additive manufacturing sekä Steel structures -tutkimusryhmien toimesta. Publishers version

Purpose This study aims to build on social capital theory (SCT) and its dimensions by examining the role of social capital in the public procurement process and by identifying related contingencies that may influence procurement performance. Design/methodology/approach A systematic literature review and a thematic analysis regarding social capital in procurement are conducted. The antecedent–behaviour–consequence (ABC) model is used for illuminating linkages between social capital, contingencies and procurement performance. Findings The dimensions of social capital are investigated in the procurement process; however, the extent of social capital role can vary between the phases of the process. It is concluded that the contingencies of social dynamics are linked with social capital and may influence the outcomes and performance of the procurement process. Practical implications Social capital can ease interactions between public buyers and private suppliers by contributing to effective tendering, improving social interaction in negotiations and balancing rigidity in contract management, supporting the interests of both parties. The provided framework helps decision makers to comprehend the social dynamics in public procurement. Social implications Improving social dynamics and solutions in public procurement. Originality/value This study extends social capital research in the field of public procurement and creates a framework connecting social capital and prevailing contingency factors to procurement process performance. Publishers version

Differential protection, as the key protection element in the power transformers, has always been threatened with sending false trips subjected to external transient disturbances. As a result, differential protection needs an additional block to distinguish between internal faults and external transient disturbances. The protection system should i) be able to perform based on raw data, ii) be able to learn fully temporal features and sudden changes in the transient signals, and iii) impose no assumption on noise. To address these challenges, a fast recurrent neural network, namely fast gated recurrent neural network (FGRNN). By removing the reset gate in the gated recurrent unit (GRU), the proposed network is capable of learning abrupt changes in addition to significantly reducing the computational time. Furthermore, a loss function based on an information theory concept is formulated in this paper to enhance the learning ability as well as robustness against non-Gaussian/Gaussian noises. A generalized form of mutual information is also adopted to form a noise model-free loss function, then incorporated with the designed deep network. Simulated and experimental examinations engaging various external factors, in addition to a comparison between the proposed fast GRNN, GRU, and seven firmly-established methods indicates the faster and more reliable performance of the proposed algorithm. Post-print / Final draft

Publisher Copyright: © 2022 CIRP Friction stir welding of dissimilar thickness aluminum and copper alloys was carried out without offsets by placing the copper at different positions, with horizontal and inclined bed conditions. The influence of the copper plate positions and bed conditions on macro-structure, microstructure, and mechanical properties were investigated. Optical microscopy, FE-SEM, EBSD, Tensile test, bending test, micro-hardness, and XRD analysis were carried out to understand the joint formation mechanism. The joint efficiency of 90% and 80.08% and bending angles of 93˚ and 35˚ were obtained, respectively, when the copper was placed at the middle position with horizontal and inclined bed conditions.

The increasing importance of artificial intelligence (AI) in everyday work also means that new insights into team collaboration must be gained. It is important to research how changes in team composition affect joint work, as previous theories and insights on teams are based on the knowledge of pure human teams. Especially, when AI-based systems act as coequal partners in collaboration scenarios, their role within the team needs to be defined. With a multi-method approach including a quantitative and a qualitative study, we constructed four team roles for AI-based teammates. In our quantitative survey based on existing team role concepts (n = 1.358), we used exploratory and confirmatory factor analysis to construct possible roles that AI-based teammates can fulfill in teams. With nine expert interviews, we discussed and further extended our initially identified team roles, to construct consistent team roles for AI-based teammates. The results show four consistent team roles: the coordinator, creator, perfectionist and doer. The new team roles including their skills and behaviors can help to better design hybrid human-AI teams and to better understand team dynamics and processes.

Social media influencers are integral to contemporary organizations’ marketing strategies. Despite growing interest in the topic, there is scant knowledge of how organizations manage and collaborate with influencers in their content production during commercial collaborations. Drawing on semi-structured interviews and a semiotic analysis of social media content, this study elucidates the dynamics of organizations’ commercial collaborations with influencers and discusses how influencers decode and transmit organizations’ commercial messages to their followers in the destination marketing context. Social reality and commercial messages are enmeshed in the content narrative and interpreted by the influencer and their knowledge of their audience into what they could mean and become in the semiotic and symbolic landscapes of social media environments. Thus, an influencer’s interpretation of organization’s commercial messages is embedded in the social media environment. Post-print / Final draft

Concerns about climate change call for a careful assessment of the environmental impact of the supply chain of critical materials such as magnesium (Mg) which has a broad range of applications. Enhancing the circularity of this material is vital for ensuring its sustainable use. However, systematic analysis of the sustainability of the global production of magnesium and its circularity is still missing. We propose a novel dynamic model based on geology and processing routes to quantify the key environmental concerns across the life cycle of primary and secondary magnesium. Energy consumption, water use and related emissions are assessed for recycling including functional (recovered Mg reused in the closed-loop supply chain) and nonfunctional (recovered Mg as an element used in aluminum alloys as open-loop supply chain), as well as casting and molding. Results show a significant potential contribution of circularity of magnesium to energy (up to 31 billion GJ) and water (up to 2.7 Km3) savings, as well as the mitigation of greenhouse gas (GHG) emissions (up to 3 billion tonnes CO2 eq), globally. However, the analysis indicates that 87% of secondary magnesium comes from nonfunctional recycling. The result shows the possible increase of nonfunctional recycling of magnesium from 612 kt in 2020 to 1 mt in 2050, and the growth of functional recycling of magnesium from 96 kt in 2020 to 161 kt in 2050. The finding highlights the necessity for improving supply chain policies of Mg through technological developments and operational changes to ensure its sustainable circular economy. Post-print / Final draft

The demand for printed electronics (PE) is expected to increase for improved functionality and autonomy of products in the context of the Internet of Things, especially for sensing and communication. With this trend, the environmental performance of novel technologies is of growing importance, and researchers are exploring ways to make them more environmentally friendly using bio-based substrates and additive printing methods. Conductive inks have the highest environmental impact in the life cycle of printed electronics, and there are two options to decrease the impact: increase recycling rates or replace commonly used silver inks with less impactful materials such as copper or graphite. With the current mixed waste management system, a higher recycling rate for silver is not achievable. Copper and graphite have a lower environmental impact than silver, however, the electrical conductivity of copper and graphite inks is lower than silver ink. This article introduces a double-parameter comparison to simultaneously assess the environmental and electrical conductivity of printed electronics using three inks of silver, copper, and graphite inks. Then based on the technical feasibility, this study proposes suitable applications for each substrate and ink combination.

Finland is committed to aim for a carbon-neutral energy system by 2023. The transition is in progress with increasing shares of various forms of low-carbon production and significant reductions in the share of energy production from coal and natural gas, for example. Finland has traditionally been strong in the use of renewable energy thanks to wood-based fuels availability. However, a significant part of the energy is still produced from fossil fuels in Finland. The energy system has been in constant evolution throughout history. Recently, climate change mitigation has made carbon neutrality the single biggest goal in energy system development, which has a major impact on current decision-making. In addition to carbon neutrality, the change must consider two other particularly important and ongoing societal objectives such as security of supply and service of the energy system, and cost-effectiveness. The future energy system will be affected by many expectations and parallel developments. These include the arrival of new energy sources on the market and their integration into the system, the progress of electrification, the development of energy technologies and changes in cost-efficiency, the growing importance of energy storage, the carbon capture development, and plans for the hydrogen economy. There are numerous possible directions for development, and they are not mutually exclusive. However, it creates science-based, urgent information needs and challenges for energy system decision-making. As decisions have to be taken that simultaneously create the conditions for the achievement of several objectives, partly cross-impacting each other. This report offers a clear and comprehensive overview of energy system status in Finland including the main trends. The report provides basic general information of the different types of energy production, energy storage, energy efficiency and savings as well as the entire energy system, including system integration. In addition, the aim is to present basic information of the different types of energy production, the current state of the energy system and future trends. The report is intended for all those who are interested in the trends in the energy system and aims to present relatively complex entities in an understandable way and to provide an overview of the factors involved in the development of the energy system. The report has been written by 19 experts in their field from the Faculty of Energy Systems at LUT University. The report starts with a summary of the views of public organisations on future trends and scenarios for energy systems. The most relevant of these are the views and scenario calculations of the Intergovernmental Panel on Climate Change (IPCC), the EU, the Nordic Council of Ministers' organisation called Nordic Energy Research (NER) and the Finnish Climate and Energy Strategy. The views contain the same basic elements related to energy systems and also partly contain many different future scenarios. For example, the evaluation models reviewed by the IPCC include more than 2 500 scenarios. The report presents basic information on the technologies and characteristics of all the main energy production methods in Finland, considering the sustainability of the production method and the different needs of society. In addition, reports covers topics such as energy system integration costs, hydrogen economy, carbon capture and utilisation, energy storage and carriers, energy efficiency, energy savings and consumption flexibility. The intention is to provide the reader as comprehensive a basic understanding as possible of the main technologies of the energy system and the most important elements of its development. Besides presenting the different forms of energy production and the main technologies, the report also considers the energy system as a whole and the various priorities for the future. The current state of the energy system is examined in particular for electricity and heat and also briefly for industry and transport. The report also is discussed the significance and role of the three main energy sources in the development of the national energy system. In Finland, the main energy sources for the energy system development are variable renewable energy, nuclear power and biomass. In addition, the report provides information on important elements of system integration, such as sector integration, system infrastructure, the functioning of the energy market and system-level investments, and export opportunities related to carbon neutrality expertise in Finland. The main issues of the energy system development are currently related to variable renewable energy, especially wind power in Finland. It plays an important role in transforming energy consumption in many sectors towards carbon neutrality and will grow significantly in the coming years. As the wind dependent and variable production share increases, ensuring operational reliability will require significant structural changes and system development to maintain a balance between production and consumption under all conditions. The main tools to achieve these purposes include energy storage in different time periods, weather-independent and controllable forms of energy production, power reserves, consumption flexibility and integration between different sectors. This report aims to provide the basic information needed to understand the whole picture and its various components. Publishers version

The current global energy crisis, emphasises the need to simultaneously reduce fossil energy consumption, accelerate renewable energy development, and mitigate global warming, which may arise from situations of dirtier fuel usage. Consequently, this work highlights how captured carbon dioxide from fossil power and manufacturing plants, together with hydrogen purportedly produced via water electrolysis (powered by residual energy from fossil and renewable power plants), can be used to synthesize methanol. Therefore, a methanol plant model was proposed and designed. Multivariable regressions for the plant model were developed and optimised. Furthermore, deduced optimal were used to develop a Langmuir-Hinshelwood-Hougen-Watson (LHHW) kinetic equivalent to the Gibbs reaction model used in the simulation. Also, the plant cost analysis was performed at the optimal, and hydrogen cost was found to constitute the highest manufacturing cost component, hence the cost-determining factor of the plant. Finally, cost-to-size models for various cost components were also deduced. Publishers version

PurposeThis study aims to identify and prioritize the challenges to adopting blockchain in supply chain management and to make its taxonomic model. Moreover, validate whether these challenging factors exist in the real world and, if they exist, then in what percentage.Design/methodology/approachThis research adopted the fuzzy best-worst method (F-BWM), which integrates fuzzy set theory with the best-worst method to identify and prioritize the prominent challenges of the blockchain-based supply chain by developing a weighted multi-criteria model.FindingsA total of 20 challenges (CH's) were identified. Lack of storage capacity/scalability and lack of data privacy challenges were found as key challenges. The findings of this study will provide a robust framework of the challenges that will assist academic researchers and industry practitioners in considering the most significant category concerning their working area.Practical implicationsBlockchain provides the best solution for tracing and tracking where RFID has not succeeded. It can improve quality management in a supply chain network by improving standards and speeding up operations. For inventory management, blockchain provides transparency of documentation for both parties within no time.Originality/valueTo the best of the authors' knowledge, no previous research has adopted the fuzzy best-worst method to prioritize the identified challenges of blockchain implementation in the supply chain. Moreover, no study provides a taxonomic model for the challenges of implementing a blockchain-based supply chain.

Circular economy (CE) business models provide solutions for sustainable development goals by closing, slowing, intensifying, de-materializing, and narrowing resource loops. Addressing CE needs a strategic redefinition of the way companies are creating and capturing value, which leads in designing a new value creation system and innovative business models. For a full circular value creation, circular products should be designed and developed specifically for repair, refurbishing, and remanufacturing purposes to close the loop. Hence, companies need to radically change their business models and the way they create value towards more innovative solutions based on CE strategies. However, implementation of circular business models in business practices has not been widely utilized and requires fundamental changes within the value chain. In a successful circular value creation, a higher degree of transparency and high-quality data for the entire value chain is required for further development of the products and processes, hence enabling design optimization and management of supply chain. Recent debates show that artificial intelligence (AI) can be considered as an enabler of CE to help companies in innovating circular business models. Different applications of AI such as machine learning, automation and robotics, and machine visions have the capability of collecting, analyzing, and storing digital data. AI-enhanced products and services can tackle environmental problems through independent interactions with their surroundings and self-learning capabilities, which results in improved environmental performance characteristics. In this chapter, we identify the role of AI in circular value creation for sustainable development goals. Post-print / Final draft

Early detection and proper treatment of epilepsy is essential and meaningful to those who suffer from this disease. The adoption of deep learning (DL) techniques for automated epileptic seizure detection using electroencephalography (EEG) signals has shown great potential in making the most appropriate and fast medical decisions. However, DL algorithms have high computational complexity and suffer low accuracy with imbalanced medical data in multi seizure-classification task. Motivated from the aforementioned challenges, we present a simple and effective hybrid DL approach for epileptic seizure detection in EEG signals. Specifically, first we use a K-means Synthetic minority oversampling technique (SMOTE) to balance the sampling data. Second, we integrate a 1D Convolutional Neural Network (CNN) with a Bidirectional Long Short-Term Memory (BiLSTM) network based on Truncated Backpropagation Through Time (TBPTT) to efficiently extract spatial and temporal sequence information while reducing computational complexity. Finally, the proposed DL architecture uses softmax and sigmoid classifiers at the classification layer to perform multi and binary seizure-classification tasks. In addition, the 10-fold cross-validation technique is performed to show the significance of the proposed DL approach. Experimental results using the publicly available UCI epileptic seizure recognition data set shows better performance in terms of precision, sensitivity, specificity, and F1-score over some baseline DL algorithms and recent state-of-the-art techniques. Post-print / Final draft

PurposeThe aim of this study was to identify interventions for and mechanisms of the digital transformation of purchasing and supply management (PSM) processes. The digital transformation of tactical and operational PSM processes has often progressed slowly despite the solid knowledge of advanced technologies.Design/methodology/approachThis study used a qualitative exploratory approach based on 14 interviews with PSM executives from firms that are continuously working toward using advanced technologies in their PSM processes but have not yet gained full strategic benefits from digital transformation.FindingsThis study formulates five propositions regarding interventions and mechanisms that can positively influence the digital transformation of PSM processes. The main intervention in this regard is the renewal of data infrastructure, including platforms. PSM-related data should meet needs from both tactical and operational viewpoints. When applications serve as a source of data, they support digital transformation. Mechanisms such as supplier measurement and process improvement are outcomes of the digital transformation of PSM processes.Practical implicationsThis study highlights the importance of common data sets for tactical and operational purchasing. These purchasing data should be owned and served by a cross-functional team. To create this interoperability, a firm needs global governance of open standards.Originality/valueThis study makes a theoretical contribution to the discussion of what kind of interventions positively influence on the digital transformation of PSM processes. Specifically, this study explains the integration needs of data and applications.

”Tulevaisuuden hiilineutraali ja omavarainen lähiö” -tutkimushankkeen tavoitteena oli tuottaa tietoa lähiön nykytilasta ja mahdollisuuksista sen kehittämiseen hiilineutraalisuuden ja omavaraisuuden näkökulmasta. Tutkimus tarkasteli lähiöasukkaan kulutusperusteista hiilijalanjälkeä keskittyen asumisen, liikkumisen ja ravintoon. Erityisenä kohderyhmän tarkasteltiin ikääntyviä asukkaita ja heidän näkökulmaansa kulutusperusteisen hiilijalanjäljen pienentämiseen. Tutkimuksen kohdelähiönä tarkasteltiin Mukkulaa Lahdessa. Erityisesti tuotettiin tietoa kohdelähiön eli Lahden kaupungin Mukkulan tilasta kaupungin kehittämistoimille tilanteessa, jossa alueperustaiset, maankäytön perinteiset keinot kuten täydennysrakentaminen tai purkava saneeraus, eivät ole mahdollisia. Tutkimus perustui kahdella postikyselyillä vuosina 2021 ja 2022 kerättyihin aineistoihin, joiden pohjalta laskettiin kulutusperusteisen hiilijalanjäljen nykytilannetta ja muutosmahdollisuuksia käyttäen hyväksi elinkaariarviointia ja taselaskentaa. Lisäksi tehtiin haastatteluita ikääntyneiden asukkaiden näkökulmien täydentämiseksi. Lahden Mukkulan asukkaan nykyinen hiilijalanjälki on 6,2 tonnia CO2-ekv. asukasta kohden. Näin ollen myös Mukkulan asukkaiden hiilijalanjäljen nykytaso on vielä kaukana kestävästä tasosta, jonka ilmastotavoitteiden mukaan tulisi olla alle 3 tonnia CO2-ekv. vuoteen 2030 mennessä. Aineiston perusteella Mukkulan asukkaat ovat tehneet monia helppoja toimia, kuten esimerkiksi kotitalousjätteen kierrättäminen ja ruokahävikin vähentäminen, omassa arjessaan vähentääkseen ilmastokuormaansa. Kuitenkin tehokkaammat ilmastotoimet, kuten asuntojen energiaremontit, polttomoottoriauton vaihtaminen sähköautoon ja kasvis- tai vegaaniruokavalioon siirtyminen ovat olleet vähemmän suosittuja toimenpiteitä asukkaiden keskuudessa, sillä ne vaativat mm. suurempia taloudellisia ponnistuksia sekä merkittävää tapojen muutosta. Ikääntyneet näyttäytyivät tutkimuksen perusteella aktiivisina ilmastotoimijoina niin omassa arjessaan kuin myös esimerkiksi taloyhtiöissään. Kierrättäminen, jätteiden lajittelu sekä ruokahävikin vähentäminen olivat keskeisiä tekoja. Ikääntymisen mukanaan tuomat toimintakyvyn haasteet, esimerkiksi liikkumisessa, estävät esimerkiksi julkisen liikenteen käyttämistä. Lisäksi tunnistettiin ohjauskeinoja, joilla voidaan edistää ja tukea lähiön hiilineutraaliutta ja omavaraisuutta. Tutkimuksen mukaan Mukkulan asukkaista selkeä enemmistö piti omavaraisuuden kasvattamiseen liittyviä toimenpiteitä tärkeinä ja tavoittelemisen arvoisina. Monet omavaraisuuden kasvattamiseen tähtäävät toimet ovat samoja kuin ilmastopäästöjen vähentämiseen liittyvät toimet. Näin ollen viestittäessä erilaisista ilmastotoimenpiteistä olisi tärkeää viestiä samalla niiden vaikutuksista omavaraisuuteen. Publishers version

Sustainability-oriented social entrepreneurship is called on to support our society in solving global social and environmental challenges. Such entrepreneurial efforts have received acknowledgment in the context of developing economies, where essential social needs are still to be met. However, emerging economies – which still struggle with the availability of such resources as electricity, water, affordable healthcare, and education – currently struggle with entrepreneurship rates in general and with sustainability-oriented social entrepreneurship in particular. Accordingly, the related literature lacks evidence on sustainability-oriented social entrepreneurship in the context of emerging economies. Following the notion of bottom-up social innovation and a process perspective, in this research, we provide an overview of social entrepreneurship in emerging economies, relying on several inspiring cases. Aiming at a comprehensive overview of sustainability-oriented social entrepreneurship in an emerging economy context, we develop an overarching framework that combines multiple theoretical streams and concepts around this rapidly growing phenomenon. Furthermore, we discuss and share implications on how bottom-up initiatives could complement global top-down approaches, such as the United Nations Sustainable Development Goals, in the emerging economy context. Post-print / Final draft

The importance of renovations is widely recognized, for example, due to renovation backlogs in the developed countries. The urbanization megatrend, among many other factors, is still increasing the need for renovations in the long run. One approach to review the renovation issue is the profitability of the companies that will tackle the increasing demand in the sector. By applying mainly quantitative methods, using the 15-year timeframe (2005–2019) and earnings before interest, taxes, depreciation, and amortization (EBITDA) and return on assets (ROA) as measures, this study reviewed the profitability of the building renovation (BR) companies from two perspectives: how does focusing on certain special services (specialized BR) fare compared to focusing on a wide range of services (wide BR) and what are the profitability differences among specialized BR companies? The results show that, when reviewing the research timeframe in total, there are no differences in profitability between wide BR and specialized BR companies. However, an annual review reveals that specialized BR companies are profitability-wise more vulnerable to economic cycles. Among the specialized BR companies, there are several differences in profitability; classically, specialization in a niche market with a deliberate customer base and low competition level is gainful. The research provides new information about an unresearched area encouraging companies to re-think their strategic choices considering service specialization and performance. Post-print / Final draft

This chapter develops a typology of B2B platform business models. B2B platforms can be divided into three types depending on the nature of the platform market structures they enable. (1) The product-service platformizer business model creates a platform-like interface on top of a product or service and helps bring in production-side complements to join the focal firm’s value proposition. (2) The platform ecosystem orchestrator opens a multi-sided market on top of a B2B product-service value proposition and enables customers to select complements from an ecosystem. (3) The platform market guardian creates an open or semi-open platform marketplace for other B2B firms to transact products or services. For each type, we discuss and illustrate the B2B firm’s value creation and capture logic, platform governance, and platform architecture characteristics. Post-print / Final draft

This study investigates the soft total quality management (soft TQM) dimensions that affect the environmental and social sustainability of Finnish small and medium-sized enterprises (SMEs), considering the company‘s business, size, and possible certificates as control variables. Sustainable business has been found to be key to the success of companies, so investing in it is essential for companies. With the help of extensive literature research, the TQM dimensions covering the entire business activity were determined, from which detailed issues were identified. To ascertain the level of implementation of detailed issues, the survey was constructed and sent to 6889 randomly selected CEOs in autumn 2020. A total of 271 responses were received. Based on prior literature and studies, 10 hypotheses were proposed. The collected data were analyzed using regression analysis. The results reveal that two practices—business management systems and human resources (HR) practices—were related to environmental sustainability, while only business management system was related to social sustainability. None of the control variables affected environmental sustainability; however, the industrial sector influenced social sustainability. The study presents recommendations for company managers and the government to support sustainable development, especially in Finnish SMEs. As a practical contribution, the study demonstrates the importance of designing and implementing business management systems for enhanced sustainability. Management should also appreciate that sustainability will not automatically be set at a high level upon certification; thus, the performance of operations and processes should be monitored. Post-print / Final draft

This chapter focuses on ownership innovation, especially on family owners’ role in conducting innovative activities in their pursuit of control and development of the family business. Using a qualitative case study, we show how family firm owners create, develop, and adopt new organizational structures, practices, and tools to manage their family business ownership. Our analysis shows that the ownership innovation process is path dependent and seems to be associated with the professionalization of ownership management in the family business. We propose that as a novel innovation concept, ownership innovation is needed to better understand ownership in family business research. More empirical research is encouraged to uncover family business owners’ innovations regarding the ownership arrangement in their family businesses. Post-print / Final draft

Chromatographic separation of rare earth elements (REE) as anionic complexes with chelating aminopolycarboxylate ligand methylglycine N,N-diacetate (MGDA) was studied experimentally. A synthetic mixture of La, Nd, and Eu were used to model a REE mixture obtained from processed secondary sources such as phosphogypsum (PG). In the REE extraction from PG, the REEs can be recovered with MGDA to obtain the REE–MGDA mixture. Three strong base anion exchange resins (Dowex 1X8, IRA-402, and IRA-410) were used as the separation materials. Successful separation of the REEs by elution with dilute HNO3 and HCl was attributed to differences in the stabilities of the REE–MGDA complexes. The pKa values of the complexes were determined by titration to be 3.81, 3.25, and 2.96 for La, Nd, and Eu, respectively. Fractionation of the ternary La-Nd-Eu mixture (with a 1:1:1 mole ratio) were studied. La was recovered at approximately 80% purity and 80% yield, but strong trade-offs between the yield and the purity of Nd and Eu must be made. Chromatographic separation was found to be an efficient process option, considering its simplicity and the recovery of several product fractions. The initial process design offers a promising starting point for investigating more advanced process configurations for the efficient recovery of pure REE from phosphogypsum. Publishers version

The telecare medicine information systems (TMIS) offer a networking channel across public networks to access remote medical services and enable health care professionals and medical staff to make the best clinical decisions and treatments quickly. The verified-based three-party authentication protocol in TMIS for data exchange, authorizations only two patients/users to accumulation their verifiers in the record of authentication server calculated exhausting own password. The authentication scheme will then verify the verifiers of the patients/users and allow them to exchange electronic medical records securely and easily. In this paper, we provide an effective, provably secure, verified-based three-party authentication protocol for data exchange in TMIS utilising fractional chaotic maps. The authentication protocol provided does not use any public server keys and does not require the number of additional messages and rounds for key validation. The projected protocol is appropriate for TMIS because it has stronger security and cheaper communication costs than the corresponding verified-based approach. The development of smart cities can be accelerated with the proposed protocol. Post-print / Final draft

The development of continuous oil-water separation processes has applications in the treatment of industrial oily wastewater and effective management of oil spills. In this research, the performance of a superhydrophobic-superoleophilic (SHSO) membrane in oil-water separation is investigated through dynamic tests. We investigate the effects of the total flow rate and oil concentration on the separation efficiency using an as-fabricated SHSO mesh tube. To construct the SHSO membrane, a tubular stainless steel mesh is dip-coated into a solution, containing a long-chain alkyl silane (Dynasylan F8261) and functionalized silica nanoparticles (AEROSIL R812). The as-prepared SHSO mesh tube illustrates a water contact angle of 164° and an oil contact angle of zero for hexane. A maximum oil separation efficiency (SE) of 97% is obtained when the inlet oil-water mixture has the lowest flow rate (5 mL/min) with an oil concentration of 10 vol %, while the minimum oil SE (86%) is achieved for the scenario with the highest total flow rate (e.g., 15 mL/min) and the highest oil concentration (e.g., 50 vol %). The water SE of about 100% in the tests indicates that the water separation is not affected by the total flow rate and oil concentration, due to the superhydrophobic state of the fabricated mesh. The clear color of water and oil output streams also reveals the high SE of both phases in dynamic tests. The outlet oil flux increases from 314 to 790 (L/m2·h) by increasing the oil permeate flow rate from 0.5 to 7.5 (mL/min). The linear behavior of the cumulative amounts of collected oil and water with time demonstrates the high separation performance of a single SHSO mesh, implying no pore blocking during dynamic tests. The significant oil SE (97%) of the fabricated SHSO membrane with robust chemical stability shows its promising potential for industrial-scale oil-water separation applications. Post-print / Final draft

Bioenergy plays an important role in the climate neutrality targets of the EU. However, the status of bioenergy implementation varies greatly across the EU. The aim of this paper is to assess the role of bioenergy in different EU countries using EU experts’ opinions of bioenergy implementation in their own country. The paper identifies leading and lagging countries in biomass development by focusing on the current share of bioenergy in the total energy supply. The study shows differences in bioenergy development between Southern and Western EU countries with Northern and Eastern EU countries. The anti-bioenergy movement and continuing political support for the fossil fuel industry are important barriers inhibiting biomass development in many EU countries, especially in Southern Europe and Western Europe. Our analysis finds that the EU needs more factual bioenergy information and improved promotion of bioenergy throughout society, especially in southern and western parts of the EU. Bioenergy development in the EU can be looked at optimistically, especially in Northern and Eastern Europe. The experience of societal acceptance of bioenergy in countries such as Finland and Sweden is applicable to countries that have thus far seen less progress in bioenergy implementation such as Poland and the Netherlands. Publishers version

A fundamental challenge for interorganizational innovation projects is employing diverse actors’ knowledge, expertise and perspectives for situation-specific demands of complex innovation. Innovation advancement is dependent on the degree to which knowledge is used and synthesized to address emerging and situation-specific demands of innovation. The goal of this study is to shed light on organizing for joint knowledge creation in a strategic interorganizational innovation project. Based on an inductive analysis of interview data from one strategic interorganizational innovation project, we identified the iterative process, self-organizing working groups and dynamic participation as practices through which the actors involved arranged and enacted their joint efforts, namely, knowledge creation and progress of innovation. This study contributes to research on managing strategic interorganizational projects by suggesting that organizing, which involves structural and informal organizing practices, supports managing strategic interorganizational projects where the diverse actors’ knowledge integration is at the core of the innovation project's goals. Post-print / Final draft

Automated wildlife reidentification has attracted increasing attention in recent years as it provides a non-invasive tool to identify and to track individual wild animals over time. In this paper, the first steps are taken towards the automatic photo-identification of the Ladoga ringed seals (Pusa hispida ladogensis). A method is proposed that takes a sequence of images, each containing multiple individuals as the input, and produces cropped images of seals grouped based on one certain individual per group. The method starts by detecting each seal from the images and proceeds to matching the individual seals between the images. It is shown that high grouping accuracy can be obtained with a general-purpose image retrieval method on an image sequence taken from the same location within a relatively short period of time. Each resulting group contains multiple images of one individual with slightly different variations, for example, in pose and illumination. Utilizing these images simultaneously provides more information for the individual re-identification compared to the traditional approach, i.e., which utilizes just one image at a time. It is further demonstrated that a convolutional neural network based method can be used to extract the unique pelage patterns of the seals despite the low contrast. Finally, a method is proposed and experiments with the novel Ladoga ringed seals data are carried out to provide a proof-of-concept for the individual re-identification.

Millions of people experience mental health issues each year, increasing the necessity for health-related services. One emerging technology with the potential to help address the resulting shortage in health care providers and other barriers to treatment access are conversational agents (CAs). CAs are software-based systems designed to interact with humans through natural language. However, CAs do not live up to their full potential yet because they are unable to capture dynamic human behavior to an adequate extent to provide responses tailored to users’ personalities. To address this problem, we conducted a design science research (DSR) project to design personality-adaptive conversational agents (PACAs). Following an iterative and multi-step approach, we derive and formulate six design principles for PACAs for the domain of mental health care. The results of our evaluation with psychologists and psychiatrists suggest that PACAs can be a promising source of mental health support. With our design principles, we contribute to the body of design knowledge for CAs and provide guidance for practitioners who intend to design PACAs. Instantiating the principles may improve interaction with users who seek support for mental health issues.

In this paper, we identify hybrid heating systems on a single residential customer’s premises using smart meter data. A comprehensive methodology is developed at a generic level for residential sector buildings to identify the type of primary and support heating systems. The methodology includes the use of unsupervised and supervised learning algorithms both separately and combined. It is applied to two datasets that vary in size, quality of data, and availability and reliability of background information. The datasets contain hourly electricity consumption profiles of residential customers together with the outdoor temperature. The validation metrics for the developed algorithms are elaborated to provide a probabilistic evaluation of the model. The results show that it is possible to identify the types of both primary and support heating systems in the form of probability of having electric- or non-electric type of heating. The results obtained help estimate the flexibility domain of the residential building sector and thereby generate a high value for the energy system as a whole. Publishers version

Individuals tend to hold back their ideas because they feel concerned about being evaluated. This leads to the untapped creative potential for organizations that depend on the creative abilities and ideas of their employees, as idea evaluation is essential for further developing and assessing creative ideas that inhibit the potential to turn into innovative products or services. In our research, we propose the use of AI-based computer systems for idea evaluation to address evaluation apprehension. With the help of an experiment (n=228), we test whether individuals feel concerned about evaluation when a computer evaluates their idea. Our results show that people do not feel evaluation apprehension when they present their idea to an AI-based system, but in contrast, feel concerned when they present their idea to a human. These findings contribute to the theory of evaluation apprehension but also to theories of human-computer collaboration and hold potential for companies to increase their creative outcome. Post-print / Final draft

In this letter, a reconfigurable intelligent surface (RIS)-enabled successive interference cancellation (SIC)-based spectrum sharing (SS) scheme is proposed for SS networks where multiple transceiver pairs communicate over the same spectrum at the same time. The key idea is to apply the SIC technique at each receiver and utilize RIS simultaneously, so as to reduce the interference among different transceiver pairs and to focus energy. Specifically, to minimize the total power consumption at all the transmitters under given data rate constraints, the decoding order at each receiver, the reflection coefficients at RIS, and the transmit power at each transmitter are jointly optimized. The formulated problem is a mixed-combinatorial-and-continuous optimization problem and thus is difficult to solve. To address this, a low-complexity but effective decoding order determining method is first proposed. Given the decoding orders, the reflection coefficients and the transmit power are alternately optimized with the help of the semidefinite relaxation method. Substantial performance gains are shown compared with traditional RIS-enabled SS scheme without SIC. Post-print / Final draft

The rapid expansion of the Industrial Internet of Things (IIoT) necessitates the digitization of industrial processes in order to increase network efficiency. The integration of Digital Twin (DT) with IIoT digitizes physical objects into virtual representations to improve data analytics performance. Nevertheless, DT empowered IIoT generates a massive amount of data that is mostly sent to the cloud or edge servers for real-time analysis. However, unreliable public communication channels and lack of trust among participating entities causes various types of threats and attacks on the ongoing communication. Motivated from the aforementioned discussion, we present a blockchain and Deep Learning (DL) integrated framework for delivering decentralized data processing and learning in IIoT network. The framework first present a new DT model that facilitates construction of a virtual environment to simulate and replicate security-critical processes of IIoT. Second, we propose a blockchain-based data transmission scheme that uses smart contracts to ensure integrity and authenticity of data. Finally, the DL scheme is designed to apply the Intrusion Detection System (IDS) against valid data retrieved from blockchain. In DL scheme, a Long Short Term Memory-Sparse AutoEncoder (LSTMSAE) technique is proposed to learn the spatial-temporal representation. The extracted characteristics are further used by the proposed Multi-Head Self-Attention (MHSA)-based Bidirectional Gated Recurrent Unit (BiGRU) algorithm to learn long-distance features and accurately detect attacks. The practical implementation of our proposed framework proves considerable enhancement of communication security and data privacy in DT empowered IIoT network. Post-print / Final draft

Artificial intelligence and mechanical engineering are two mature fields of science that intersect more and more often. Computer-aided mechanical analysis tools, often multibody system software, are very versatile and have revolutionalized many industries. However, as shown by the literature presented in this review, combining the advantages of multibody system dynamics and machine learning creates new and exciting possibilities. For example, the multibody method can assist machine learning by providing synthetic data, while machine learning can provide fast and accurate subsystem models. The intersection of both approaches results in surrogate and hybrid modeling techniques, advanced control algorithms, and optimal design applications. A notable example is the development of autonomous systems for vehicles, robots, and mobile machinery. In our review we have found nontrivial, innovative, and even surprising applications of machine learning and multibody dynamics. This review focuses on applying neural networks, mainly deep learning, in connection with the multibody system method. Over one hundred and fifty papers are covered, and three main research areas are identified and introduced: data-driven modeling, model-based control and estimation, and data-driven control. The paper starts with a primer on machine learning and concludes with future research directions. The main goal is to provide a comprehensive and up-to-date review of existing literature to inspire further research. Post-print / Final draft

Fully superconducting generators (FSCGs) use superconducting wires for both the field and armature windings to reach a high torque density for wind turbine applications. The AC armature winding of an FSCG design mostly employed racetrack tooth-coils to form fractional-slot concentrated windings. This winding type has high leakage flux and excessive harmonics, especially when used in superconducting machines. Other attempts like applying full-pitch racetrack coils can only be with one slot per pole per phase which also has significant slotting harmonics. This paper proposes an innovative concept of double-layer concentric coils to enable distributed windings with a larger integral number of slots per pole per phase. The concept successfully breaks the limitation that racetrack coils cannot be built with such integral slots. This paper then assesses the performance of the proposed winding concept within a context 20 MW FSCG design. The assessment finds out that the proposed concept has balanced three phases but reduces inductance compared to single-layer windings. The force on each concentric coil can significantly be different, thereby complicating the mechanical design of these superconducting coils. Post-print / Final draft

The Research Racetrack Dipole Demonstrator (R2D2) is being studied as a demonstrating magnet for future FCC magnets. The R2D2 is meant to prove the feasibility of grading in block-coil Nb3Sn dipoles and explore quench behaviors at a very high current. This short model provides an opportunity to study quench protection concepts which will be needed for the full-scale FCC magnets. Both quench heaters and CLIQ (coupling loss induced quench) are under study. This paper presents the research work on the CLIQ protection. The work includes CLIQ design methods and configurations, and comparative studies of various CLIQ configurations for maximizing the CLIQ effectiveness. The results show that the most effective CLIQ configuration is able to quench 80% of the coil turns at the nominal current within 3 ms, leaving 20 ms for detection and validation time while keeping the maximum hotspot temperature within 350 K. The study shows that protection of R2D2 using only CLIQ may be feasible under certain assumptions. Post-print / Final draft

Agile has become a popular term in organisations and businesses, beyond the IT sector. Characteristics of agile ways of working such as the assumption that boundary conditions and requirements might (and will) change make them attractive to applications in dynamic environments in general. Methods such as Scrum or Xtreme Programming turn agile values into actionable descriptions, originally intended for software development. This work offers a literature-based assessment of the suitability of agile methods for the maintenance of industrial production systems. In addition a process draft for the introduction of agile methods into maintenance practices is outlined. The findings show that so far there has been a relatively limited attention to agile methods in an industrial maintenance context but at the same time suggest the potential for their application. Post-print / Final draft

Due to their biodegradability, biocompatibility, non-toxicity, and affordable manufacture from renewable resources, hydroxyethyl cellulose (HEC) and its derivatives have gained growing interest in a variety of sectors. In light of this, HEC and HEC-branched-amide (HECA) were used to develop new polyurethane and polycarbamoyle amide-based microcapsules. The structure of the HECA prepolymer and the elaborated microcapsules were examined using FT-IR, NMR, DRX, DLS, SEM, TGA, and Zeta Potential. The Polycarbamoyle amide microcapsules were prepared by catalyzed interfacial polymerization between the diisocyanate and the amide group of HECA. The enhanced kinetics of carbamoyle amide membrane formation using copper catalyzed polymerization is shown to have an advantage in maintaining the characteristics of the microcapsules. The stability and resistance of the microcapsules under temperature and pH conditions were also investigated. Due to strong bidentate interactions between the carbamoyle amide groups in the membrane, the microcapsules based on these groups display great stability in front of the microcapsules made of polyurethane. Theoretical studies have demonstrated these interactions, while the FT-IR results have supported these findings. The obtained results prove a positive enhancement in limonene encapsulation efficiency as the amount of carbamoyle amide groups within the membrane of the microcapsules is increased, reaching a maximum value of 96.84%. The shape has developed into a perfectly spherical, hard shape with a typical microcapsule diameter of 9 μm. Post-print / Final draft

Various water treatment processes make extensive use of porous polymeric membranes. A key objective in membrane fabrication is to improve membrane selectivity without sacrificing other properties such as permeability. Herein, LiCl (0–2 wt.%) was utilised as a preforming agent in fabricating biomass-derived cellulosic membranes. The fabricated membranes were characterised by dope solution viscosity, surface and cross-sectional morphology, pure water flux, relative molecular mass cut-off (MWCO, 35 kDa), membrane chemistry, and hydrophilicity. The results demonstrated that at the optimum LiCl concentration (0.4 wt.%), there is an interplay of thermodynamic instability and kinetic effects during membrane formation, wherein the membrane morphology and hydrophilicity can be preferably altered and thus lead to the formation of the membrane with better rejection at no detriment to its permeability. Publishers version

This study examines how small and medium-sized enterprises (SMEs) leverage social media affordances in their internationalisation pursuits. A multiple case study of eight SMEs representing business-to-business and business-to-consumer firms from Australia and Finland reveals that social media affordances are used for internationalisation pursuits via three core activities: 1) generation of market intelligence; 2) marketing communications; 3) relationship marketing. Furthermore, when conducting these activities, SMEs were found to employ either firm-centric or market-centric logic that led to the identification of six unique social media business affordances. The study contributes to theory by demonstrating how social media business affordances are harnessed for internationalisation and showing the implications of firm-centric and market-centric logics in the execution of social media activities. Post-print / Final draft