Academic Sectors Research Articles

Energy Storage Performance of Polymer-Based Dielectric Composites with Two-Dimensional Fillers.

Dielectric capacitors have garnered significant attention in recent decades for their wide range of uses in contemporary electronic and electrical power systems. The integration of a high breakdown field polymer matrix with various types of fillers in dielectric polymer nanocomposites has attracted significant attention from both academic and commercial sectors. The energy storage performance is influenced by various essential factors, such as the choice of the polymer matrix, the filler type, the filler morphologies, the interfacial engineering, and the composite structure. However, their application is limited by their large amount of filler content, low energy densities, and low-temperature tolerance. Very recently, the utilization of two-dimensional (2D) materials has become prevalent across several disciplines due to their exceptional thermal, electrical, and mechanical characteristics. Compared with zero-dimensional (0D) and one-dimensional (1D) fillers, two-dimensional fillers are more effective in enhancing the dielectric and energy storage properties of polymer-based composites. The present review provides a comprehensive overview of 2D filler-based composites, encompassing a wide range of materials such as ceramics, metal oxides, carbon compounds, MXenes, clays, boron nitride, and others. In a general sense, the incorporation of 2D fillers into polymer nanocomposite dielectrics can result in a significant enhancement in the energy storage capability, even at low filler concentrations. The current challenges and future perspectives are also discussed.

Valuation in emerging technoscience business: a case study of Finnish biobank research

PurposeThe paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.Design/methodology/approachThe authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.FindingsThe results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.Research limitations/implicationsAs research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.Practical implicationsThe study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.Social implicationsAs managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.Originality/valueThis study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

Assessing Vulnerability to Health Impacts of Climate Change in French Municipalities

Abstract Background Climate change significantly threatens human health, particularly in vulnerable municipalities. Multiple climatic, environmental, and socioeconomic factors influence municipal vulnerability. To effectively reduce this vulnerable, evidence-based tools for local decision-makers are needed. This study aims to present the development and application of a multicriteria decision analysis (MCDA) model to assess vulnerability to the health impacts of climate change in French municipalities. Methods We selected 59 municipalities to develop and apply the model. The development of the MCDA model involved a literature review on climate change and health, as well as active participation from an interdisciplinary committee composed of members from academic, associative, and professional sectors. This led to identifying 38 indicators to characterize vulnerability based on three components: climatic exposure, environmental and socioeconomic sensitivity, and adaptive capacity. These indicators were used as input to the MCDA model, which applied an outranking method to rank municipalities from most to least vulnerable. Results The MCDA model generated partial rankings by the components of vulnerability, as well as a complete ranking that integrated the three components. The results revealed the main indicators that explained the rankings and allowed for a typology of municipalities. The results helped prioritize interventions by identifying the indicators that have the greatest impact on the vulnerability of each municipality studied. Conclusions This study highlights the importance of considering multiple criteria and their interdependencies when assessing vulnerability. The results of the MCDA model provide an evidence-based tool to support decision-making processes at the local level. The MCDA model is a valuable tool for identifying and prioritizing effective interventions to reduce vulnerability in the studied municipalities. Key messages • The developed MCDA model is a valuable tool for local decision-makers to prioritize interventions and reduce vulnerability. • The developed MCDA model provides a robust evidence-based tool to support decision-making processes.

Automated Interlayer Wall Height Compensation for Wire Based Directed Energy Deposition Additive Manufacturing.

Part quality monitoring and control in wire-based directed energy deposition additive manufacturing (w-DEDAM) processes has been garnering continuous interest from both the academic and industrial sectors. However, maintaining a consistent layer height and ensuring that the wall height aligns closely with the design, as depicted in computer-aided design (CAD) models, pose significant challenges. These challenges arise due to the uncertainties associated with the manufacturing process and the working environment, particularly with extended processing times. To achieve these goals in an industrial scenario, the deposition geometry must be measured with precision and efficiency throughout the part-building process. Moreover, it is essential to comprehend the changes in the interlayer deposition height based on various process parameters. This paper first examines the behaviour of interlayer deposition height when process parameters change within different wall regions, with a particular focus on the transition areas. In addition, this paper explores the potential of geometry monitoring information in implementing interlayer wall height compensation during w-DEDAM part-building. The in-process layer height was monitored using a coherent range-resolved interferometry (RRI) sensor, and the accuracy and efficiency of this measurement were carefully studied. Leveraging this information and understanding of deposition geometry, the control points of the process parameters were identified. Subsequently, appropriate and varied process parameters were applied to each wall region to gradually compensate for wall height. The wall height discrepancies were generally compensated for in two to three layers.

ComEdge: Cloud-Native Platform for Integrated Computing and Communication in Satellite–Terrestrial Network

Leveraging technological advancements such as containers, microservices, and service mesh, cloud-native edge computing (CNEC) has become extensively discussed and applied in both academia and industry. The integration of mobile edge computing and communication is crucial for the future communication architecture in order to fully utilize distributed and fragmented communication resources and computing power. The potential for cloud-native integration can help merge mobile edge computing and communication, enhancing network flexibility and resource utilization. This paper investigates the implementation plan for extending cloud-native capabilities to integrated computing and communication (INCCOM) in the satellite–terrestrial network. We construct an experimental verification platform called ComEdge in a real-world setting. Subsequently, we analyze the architecture, functional characteristics, and deployment of the platform in a real-world environment. Furthermore, we explore the solution of deep reinforcement learning in the deployment of cloud-native core network and conduct a preliminary verification of the platform’s potential to enable artificial intelligence in a real production environment, which will provide guidance to both academic and industry sectors. Finally, we conduct an analysis on the challenges and opportunities encountered by the cloud-native INCCOM network system.

Erratum to “Profiling the Australasian paramedicine tertiary academic sector and workforce: A cross-sectional study.”

Erratum to “Profiling the Australasian paramedicine tertiary academic sector and workforce: A cross-sectional study.”

Pollination supply models from a local to global scale

Abstract. Ecological intensification has been embraced with great interest by the academic sector but is still rarely taken up by farmers because monitoring the state of different ecological functions is not straightforward. Modelling tools can represent a more accessible alternative of measuring ecological functions, which could help promote their use amongst farmers and other decision-makers. In the case of crop pollination, modelling has traditionally followed either a mechanistic or a data-driven approach. Mechanistic models simulate the habitat preferences and foraging behaviour of pollinators, while data-driven models associate georeferenced variables with real observations. Here, we test these two approaches to predict pollination supply and validate these predictions using data from a newly released global dataset on pollinator visitation rates to different crops. We use one of the most extensively used models for the mechanistic approach, while for the data-driven approach, we select from among a comprehensive set of state-of-the-art machine-learning models. Moreover, we explore a mixed approach, where data-derived inputs, rather than expert assessment, inform the mechanistic model. We find that, at a global scale, machine-learning models work best, offering a rank correlation coefficient between predictions and observations of pollinator visitation rates of 0.56. In turn, the mechanistic model works moderately well at a global scale for wild bees other than bumblebees. Biomes characterized by temperate or Mediterranean forests show a better agreement between mechanistic model predictions and observations, probably due to more comprehensive ecological knowledge and therefore better parameterization of input variables for these biomes. This study highlights the challenges of transferring input variables across multiple biomes, as expected given the different composition of species in different biomes. Our results provide clear guidance on which pollination supply models perform best at different spatial scales – the first step towards bridging the stakeholder–academia gap in modelling ecosystem service delivery under ecological intensification.

Work–Life Balance, Supervisor Support, and Life Satisfaction in the Higher Education Sector

Abstract The study explores the relationship between work–life balance and supervisor support in the Indian higher education sector. More specifically, the study explores the effects of supervisor support on the work–life balance of female employees working in academia. We used online panel data comprised of 300 employees working in various universities, which we analysed by employing structural equation modelling. Results reveal that supervisor support is positively related to employee work–life balance and ultimately their life satisfaction. The findings also stress the importance of supervisor support for female employees, as its presence is a major boost in helping women reach the desired work–life balance. With the objective to augment work–life balance of women academicians, the work would guide managers as well as decision makers involved in the academic sector to implement women-friendly policies and programmes.

ORBIS project – where have we arrived?

The Open Research Biopharmaceutical Internships Support project (ORBIS) was a response to the scientific, economic, and social challenge of increasing the effectiveness and productivity of the drug development process, both for innovative and (super)generic drugs. The overarching objective of the ORBIS project was to form a transnational and intersectoral cooperation network of academic and industrial organisations delivering a joint research programme. The research aimed at improving the preclinical pathway of drug development and manufacturing, focusing on technological and methodological improvements of the existing processes. The participating staff from all institutions have developed new skills, were exposed to new work and research environments, and have significantly broadened their career perspectives. More than 450 months of secondments were completed, and over 175 early-stage and experienced researchers participated in the exchange. This review aims to present some aspects of the scientific, training, and organisational activities of the consortium, bringing together representatives of both the academic sector as well as small and medium-sized pharmaceutical enterprises.

Investigation of the effect of electron beam irradiation on tensile, thermal and gas barrier properties of graphene nanoplatelet loaded thermoplastic nanocomposite films

Packaging materials based on lightweight and flexible thermoplastic/graphene composite films are gaining popularity in both the academic and industrial sectors. In this research work, graphene nanoplatelet (GNP) of 1–5 wt% was integrated into linear low density polyethylene (LLDPE) by employing melt compounding technique at 160 °C to produce flexible composite films. The LLDPE/GNP nanocomposite films were irradiated with doses up to 50 kGy using a 2.5 MeV electron beam accelerator in air at ambient temperature. The uniform distribution of GNP in the thermoplastic matrix obtained from FESEM analysis improved the samples' mechanical characteristics. As the GNP concentration in the LLDPE matrix increases, both the thermal stability and impermeability qualities (oxygen and water vapor) get significantly improved. Electron beam irradiation of film samples further enhances the physico-mechanical, thermal and gas barrier properties compared to non-irradiated composite films and neat LLDPE film. The tighter connections between graphene and LLDPE chains as well as the development of cross-linked networks by E-beam irradiation are responsible for the improved performance properties. Therefore, GNP incorporation as well as electron beam irradiation of thermoplastic nanocomposite films could be a viable alternative for producing high-performance and high-barrier flexible LLDPE/GNP composite films for packaging applications.

Impact of ORBIS on public policies – open consultations of draft regulatory documents and the Pharmaceutical Strategy for Europe

Public policies and regulations strongly influence research and manufacturing in pharmaceutical sector. Therefore, it is of critical importance that these policies and regulations are of high quality as well as appropriately balanced between general rules and detailed solutions. The process of public consultations prolongs adoption of novel documents. On the other hand, comments from different stakeholders like academia, industry, public administration and patients allow 360-degree critical evaluation of the document and a better understanding of the topic. This mini-review summarizes the contributions of numerous members of ORBIS project team in open consultations of draft regulatory documents published by European Medicines Agency (EMA) and the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). ORBIS project feedback on the Pharmaceutical Strategy for Europe is also presented. ORBIS project members contributed to open consultations of two ICH draft guidelines, and three EMA draft documents. ORBIS project was also active during the European Commission’s efforts to develop Pharmaceutical Strategy for Europe. The interaction between representatives of academic and industrial sectors allowed to form balanced comments. We hope that this paper will inspire more researchers to participate in future open consultations on public policies.

Exploring the hidden demands for patients’ resources: How health researchers risk excluding patients from patient and public involvement in health research during recruitment

Patient involvement in health research is widely recognized to promote effective collaboration between health researchers and patients in endeavors to develop healthcare systems. Policy documents and research strategies stress the benefits of collaborative health research with patients. However, patient recruitment depends not only on health researchers' decisions but also on other key factors: patients' competencies and the structural framework of the healthcare and academic sectors. This article is a modest attempt to explain challenges connected to recruitment, as health researchers seek to involve citizens in health research. Through interviews with nurses and doctors who conduct research, I describe how and why different patients are recruited into research in the Danish healthcare system. I apply Bourdieu's concepts of field, cultural capital, and habitus to analyze how health researchers assess patients' social competencies as part of the recruitment process. I conclude that health researchers' positions shape the competencies and knowledge that are considered legitimate and can operate as capital in this complex and dynamic arena. Therefore, forms of competencies that can function as capital are unequally distributed and recruitment risks excluding marginalized and disadvantaged groups from becoming involved. The study contributes to the literature on participatory practices and highlights the hidden social demands that are produced between the healthcare sector and academic sector by understanding the experiences of health researchers and how they value communicative skills and knowledge about the healthcare sector. The paper ends with suggestions for future directions.

Latest Advancements in the Development of High-Performance Lignin- and Tannin-Based Non-Isocyanate Polyurethane Adhesive for Wood Composites.

The depletion of natural resources and increasing environmental apprehension regarding the reduction of harmful isocyanates employed in manufacturing polyurethanes (PUs) have generated significant attention from both industrial and academic sectors. This attention is focused on advancing bio-based non-isocyanate polyurethane (NIPU) resins as viable and sustainable substitutes, possessing satisfactory properties. This review presents a comprehensive analysis of the progress made in developing bio-based NIPU polymers for wood adhesive applications. The main aim of this paper is to conduct a comprehensive analysis of the latest advancements in the production of high-performance bio-based NIPU resins derived from lignin and tannin for wood composites. A comprehensive evaluation was conducted on scholarly publications retrieved from the Scopus database, encompassing the period from January 2010 to April 2023. In NIPU adhesive manufacturing, the exploration of substitute materials for isocyanates is imperative, due to their inherent toxicity, high cost, and limited availability. The process of demethylation and carbonation of lignin and tannin has the potential to produce polyphenolic compounds that possess hydroxyl and carbonyl functional groups. Bio-based NIPUs can be synthesized through the reaction involving diamine molecules. Previous studies have provided evidence indicating that NIPUs derived from lignin and tannin exhibit enhanced mechanical properties, decreased curing temperatures and shortened pressing durations, and are devoid of isocyanates. The characterization of NIPU adhesives based on lignin and tannin was conducted using various analytical techniques, including Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), matrix-assisted laser desorption/ionization with time-of-flight (MALDI-TOF) mass spectrometry, and gel permeation chromatography (GPC). The adhesive performance of tannin-based NIPU resins was shown to be superior to that of lignin-based NIPUs. This paper elucidates the potential of lignin and tannin as alternate sources for polyols in the manufacturing of NIPUs, specifically for their application as wood adhesives.

NGHIÊN CỨU ỨNG DỤNG KỸ THUẬT TRÍ TUỆ NHÂN TẠO TRONG BÀI TOÁN DỰ BÁO GIÁ MỘT SỐ MẶT HÀNG

The global economy is significantly impacted by changes in the price of primary commodities. As a result, both the academic and professional sectors have paid attention to price predictions for major commodities. The goal of this study is to build an artificial intelligence-based model for one-day market price predictions for important commodities like copper, crude oil, gas, and silver. The information on commodity trading was gathered between 01/2000 and 10/2019. Different models based on group method of data handling (GMDH), long short-term memory (LSTM), artificial neural network (ANN), and adaptive neuro fuzzy inference system (ANFIS) were developed. Theil's U, RMSE, MAPE, MAE, R, and other performance indices were used to compare the models. The findings demonstrated that, in terms of commodity price prediction, the suggested model based on GMDH technique performs better than alternative approaches. A viable alternative for price prediction is the GMDH-based model. For economists and professionals involved in commodity price forecasting, the GMDH can be a useful tool.

Lived Experience of Business School Faculty in post COVID-19 New Normal

Two years of COVID-19 pandemic was a unique experience for many of us. The impact of the pandemic in the academic sector was distinct. This study explored the impact of pandemic on business schools and business school teaching through the examination of the lived experience of business school faculty members. The Hermeneutic phenomenology was used to capture the lived experience of the faculties who were involved in online teaching during pandemic and are teaching in the post COVID-19 new normal at graduate and undergraduate level in different business schools in Nepal. The data were collected through in depth interviews. The analysis of the data revealed four themes: (1) Not ready for hybrid mode, (2) Possibility opened up by online experience, (3) Challenge to maintain academic standard, and (4) Measures to tackle behavioral change among students. The findings suggest that COVID-19 and the time after directed business education towards transformation. However, the Nepali business school and business school faculty members have a long ground to cover. The implication and limitation of the study have been indicated.

The opportunities and challenges of ChatGPT in education

ABSTRACT The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the use of AI-generated text to cheat on assignments is a new type of cheating that poses unique challenges. This study used the Latent Dirichlet Allocation (LDA) method for topic modeling and the Valence Aware Dictionary for Sentiment Reasoning (VADER) method for sentiment analysis. After data preprocessing, 3870 tweets were still available out of the originally 10,000 tweets that were extracted for the study. The VADER sentiment analysis results revealed that 2013 tweets were categorized as “positive,” with the remaining 804 and 1053 tweets categorized as “negative” and “neutral.” The analysis's findings indicate that the majority of people have favorable things to say about ChatGPT. As a result, educational institutions can mitigate the disruptive effects of this technology and promote academic integrity by developing clear policies and guidelines and designing assessments that include limited AI-generated text.

Impact of Mobile Technology and Use of Big Data in Physics Education During Coronavirus Lockdown

The speed of spread of Coronavirus Disease 2019 led to global lockdowns and disruptions in the academic sector. The study examined the impact of mobile technology on physics education during lockdowns. Data were collected through an online survey and later evaluated using regression tools, frequency, and an analysis of variance (ANOVA). The findings revealed that the usage of mobile technology had statistically significant effects on physics instructors' and students' academics during the coronavirus lockdown. Most of the participants admitted that the use of mobile technologies such as smartphones, laptops, PDAs, Zoom, mobile apps, etc. were very useful and helpful for continued education amid the pandemic restrictions. Online teaching is very effective during lock-down with smartphones and laptops on different platforms. The paper brings the limelight to the growing power of mobile technology solutions in physics education.

Surveillance of laboratory exposures to human pathogens and toxins, Canada, 2022.

The Laboratory Incident Notification Canada (LINC) surveillance system was launched in 2015 to monitor the mandated national reporting of laboratory incidents. This report describes the laboratory exposures reported in 2022. Exposure incidents were analyzed by activity, occurrence, sector, root cause and pathogens/toxins implicated, while affected individuals were analyzed by education, exposure route, role and years of laboratory experience. An analysis of the median number of exposures per month was conducted, and time between the exposure incident date and the date the incident was reported to LINC was examined. Forty confirmed laboratory exposure incident reports were received, with two suspected laboratory-acquired infections. The exposure incident rate per 100 active licences was 3.8, and the number of exposure incidents was highest in September. The majority of exposure incidents involved risk group 2 pathogens (n=27; 63%) and non-security sensitive biological agents (n=36; 84%). Microbiology was the most cited activity occurring during the exposure event (n=20; 50%), and sharps and procedure-related issues were the most common occurrences (n=15; 24.2% each). Most incidents were reported by the academic sector (n=16; 40%). Human interaction was the most common root cause (n=20; 23.8%) and most affected individuals were technicians/technologists (n=68; 73.1%). The median time delay between the incident date and reporting date was 5.5 days. The exposure incident rate was lower in 2022 than in 2021. Incidents related to sharps and standard operating procedures remained the most common occurrence types. The most cited root cause of exposure incidents involved human interaction.

Using Extended Reality in Flight Simulators: A Literature Review.

Virtual reality has long been utilized in the games industry and is emergent for pilot training in the military and commercial airline sectors. Its usefulness as a mechanism of skills transfer to the real world has not been well researched or considered. This paper follows the PRISMA methodology to present a systematic quantitative literature review (SQLR) on the use of extended reality in flight simulators. It also encompasses recent studies of teaching and learning in immersive, virtual environments in non-aviation disciplines. The review identified 39 papers spanning all areas of the virtuality continuum across academic, commercial, and military aviation sectors, as well as engineering and medicine. The SQLR found that extended reality in flight simulators is being introduced in the commercial and military aviation sectors. However, within academia, hardware constraints have hindered the ability to provide positive empirical evidence of simulator effectiveness. While virtual reality may not replace traditional flight simulators in the near future, the technology is available to supplement classroom training activities and some aspects of simulator procedure training with promising cognitive learning outcomes.

Anomaly Detection for Internet of Things Security Attacks Based on Recent Optimal Federated Deep Learning Model

The mushrooming of IoTs (Internet of Things) and decentralised paradigm in cyber security have attracted a lot of interest from the government, academic, and business sectors in recent years. The use of MLT-assisted techniques in the IoT security arena has attracted a lot of attention in recent years. Many current studies presume that massive training data is readily accessible from IoT devices and transferable to main servers. However, since data is hosted on single servers, security and privacy concerns regarding this data also increase. It is suggested to use decentralised on-device data in OFDL (Optimal Federated Deep Learning) based anomaly detections to proactively identify infiltration in networks for IoTs. The GRUs (Gated Recurrent Units) used in OFDL's training rounds share only learned weights with the main OFDL servers, protecting data integrity on local devices. The model's training costs are reduced by the use of appropriate parameters, which also secures the edge or IoT device. In order to optimise the hyper-parameter environments for the limited OFDL environment, this paper suggests an MSSO (Modified Salp Swarm Optimisation) approach. Additionally, ensembles combine updates from multiple techniques to enhance accuracies. The experimental findings show that this strategy secures user data privacy better than traditional/centralized MLTs and offers the best accuracy rate for attack detection.