University of South-Eastern Norway

Self-determination theory (SDT) is a macro theory of human motivation that evolved from research on intrinsic and extrinsic motivations and expanded to include research on work organizations and other domains of life. We discuss SDT research relevant to the workplace, focusing on (a) the distinction between autonomous motivation (i.e., intrinsic motivation and fully internalized extrinsic motivation) and controlled motivation (i.e., externally and internally controlled extrinsic motivation), as well as (b) the postulate that all employees have three basic psychological needs—for competence, autonomy, and relatedness—the satisfaction of which promotes autonomous motivation, high-quality performance, and wellness. Research in work organizations has tended to take the perspectives of either the employees (i.e., their well-being) or the owners (i.e., their profits). SDT provides the concepts that guide the creation of policies, practices, and environments that promote both wellness and high-quality performance. We examine the relations of SDT to transformational leadership, job characteristics, justice, and compensation approaches.

Photodynamic therapy (PDT) is a minimally invasive therapeutic modality that has gained great attention in the past years as a new therapy for cancer treatment. PDT uses photosensitizers that, after being excited by light at a specific wavelength, react with the molecular oxygen to create reactive oxygen species in the target tissue, resulting in cell death. Compared to conventional therapeutic modalities, PDT presents greater selectivity against tumor cells, due to the use of photosensitizers that are preferably localized in tumor lesions, and the precise light irradiation of these lesions. This paper presents a review of the principles, mechanisms, photosensitizers, and current applications of PDT. Moreover, the future path on the research of new photosensitizers with enhanced tumor selectivity, featuring the improvement of PDT effectiveness, has also been addressed. Finally, new applications of PDT have been covered.

at least one indicator of health behaviour, physical health, or psychological health. Seventy-three studies met these criteria and provided sufficient data for the purposes of the review. A random-effects meta-analytic model showed that SDT-based interventions produced small-to-medium changes in most SDT constructs at the end of the intervention period, and in health behaviours at the end of the intervention period and at the follow-up. Small positive changes in physical and psychological health outcomes were also observed at the end of the interventions. Increases in need support and autonomous motivation (but not controlled motivation or amotivation) were associated with positive changes in health behaviour. In conclusion, SDT-informed interventions positively affect indices of health; these effects are modest, heterogeneous, and partly due to increases in self-determined motivation and support from social agents.

Artificial Intelligence (AI) reshapes companies and how innovation management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel management to rethink a company's entire innovation process. In response, we review and explore the implications for future innovation management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for innovation management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of innovation. We conclude our study by exploring directions for future research.

This study extends the discussion of digital servitization business models by adopting the perspective of the theory of the firm. We use four theories of the firm (industrial organization, the resource-based view, organizational identity, and the transaction cost approach) to understand digital servitization business models of firms in the context of ecosystems. Digitalization transforms the business models of solution providers and shapes their firm boundary decisions as they develop digital solutions across organizational boundaries within ecosystems such as harbors, mines, and airports. Thus, digitalization not only affects individual firms' business models but also requires the alignment of the business models of other firms within the ecosystem. Hence, business models in digital servitization should be viewed from an ecosystem perspective. Based on a rigorous literature review, we provide suggestions for future research on digital servitization business models within ecosystems.

The UN COP26 2021 conference on climate change offers the chance for world leaders to take action and make urgent and meaningful commitments to reducing emissions and limit global temperatures to 1.5 °C above pre-industrial levels by 2050. Whilst the political aspects and subsequent ramifications of these fundamental and critical decisions cannot be underestimated, there exists a technical perspective where digital and IS technology has a role to play in the monitoring of potential solutions, but also an integral element of climate change solutions. We explore these aspects in this editorial article, offering a comprehensive opinion based insight to a multitude of diverse viewpoints that look at the many challenges through a technology lens. It is widely recognized that technology in all its forms, is an important and integral element of the solution, but industry and wider society also view technology as being part of the problem. Increasingly, researchers are referencing the importance of responsible digitalization to eliminate the significant levels of e-waste. The reality is that technology is an integral component of the global efforts to get to net zero, however, its adoption requires pragmatic tradeoffs as we transition from current behaviors to a more climate friendly society.

Multiple regression analysis on an extended dataset has been performed to refine the relationship between temperature, pressure, composition and the Fe–Mg distribution between garnet and clinopyroxene. In addition to a significant dependence between the distribution coefficient K D and X Grt Ca and X Grt Mg# , as shown by the experimental data, the effect of X Grt Mn has also been incorporated using data from natural Mn‐rich garnet–clinopyroxene pairs. Multiple regression of data ( n =360) covering a large span in pressure, temperature and composition from 27 experimental datasets, combined with 49 natural high‐Mn granulites from Ruby Range, Montana, USA, and Karnataka, India, yields the P–T –compositional relationship ( r 2 =0.98): where K D =(Fe 2+ /Mg) Grt /(Fe 2+ /Mg) Cpx , X Grt Ca =Ca/(Ca+Mn+Fe 2+ +Mg) in garnet, X Grt Mn = Mn/(Ca+Mn+Fe 2+ +Mg) in garnet, and X Grt Mg# =Mg/(Mg+Fe 2+ ) in garnet. The Fe 2+ –Mg equilibrium between garnet and clinopyroxene does not seem to be affected by variations in the sodic content of the co‐existing clinopyroxene in the range X Cpx Na =0–0.51. Comparisons between the new and former calibrations of the garnet–clinopyroxene Fe 2+ –Mg geothermometer clearly demonstrate how the various parameters in each case affect the calculated temperatures. Application of the new expression gives reasonable results for natural garnet–clinopyroxene pairs from various rock types and settings, and should be preferred to previous formulations. Using the new calibration to the self‐consistent dataset of Pattison & Newton ( Contributions to Mineralogy and Petrology , 1989, 101, 87–103) suggests a systematic deviation with regard to both temperature and composition between their dataset and the datasets used in the present calibration.

The circular economy (CE) has the potential to capitalise upon emerging digital technologies, such as big data, artificial intelligence (AI), blockchain and the Internet of things (IoT), amongst others. These digital technologies combined with business model innovation are deemed to provide solutions to myriad problems in the world, including those related to circular economy transformation. Given the societal and practical importance of CE and digitalisation, last decade has witnessed a significant increase in academic publication on these topics. Therefore, this study aims to capture the essence of the scholarly work at the intersection of the CE and digital technologies. A detailed analysis of the literature based on emerging themes was conducted with a focus on illuminating the path of CE implementation. The results reveal that IoT and AI play a key role in the transition towards the CE. A multitude of studies focus on barriers to digitalisation-led CE transition and highlight policy-related issues, the lack of predictability, psychological issues and information vulnerability as some important barriers. In addition, product-service system (PSS) has been acknowledged as an important business model innovation for achieving the digitalisation enabled CE. Through a detailed assessment of the existing literature, a viable systems-based framework for digitalisation enabled CE has been developed which show the literature linkages amongst the emerging research streams and provide novel insights regarding the realisation of CE benefits.

In this paper, we explore how manufacturing firms and their customers co-create digital service innovations in an attempt to address the digitalization paradox. We present empirical insights from a case study of four manufacturers and their customer relationships. The results suggest that value co-creation in digital servitization is best managed through an agile micro-service innovation approach. Such an approach requires incremental micro-service investments, sprint-based micro-service development, and micro-service learning by doing to ensure customized and scalable digital service offerings. The proposed agile co-creation model provides insight into the phases, activities, and organizational principles of a micro-service innovation approach. Relational teams that pool knowledge from providers’ and customers’ strategic, technological, and operational areas are crucial to ensure successful cooperation and governance for agile co-creation. This paper offers insight into how companies engage in agile co-creation processes, with important recommendations for innovation in manufacturing firms in the era of digitalization.

The COVID-19 pandemic has forced a shift to online teaching and learning (OTL) in colleges and universities across the globe, requiring teachers to adapt their teaching in a very short time—independent of whether they were prepared. Drawing from an international sample of N = 739 higher education teachers in 58 countries, the present study sheds light on teachers' readiness for OTL at the time of the pandemic by (a) identifying teacher profiles based on a set of key dimensions of readiness; (b) explaining profile membership by individual teacher characteristics, contextual aspects of the shift to OTL, and country-level indicators representing educational innovation and cultural orientation. We conducted latent profile analysis and identified three teacher profiles with consistently high or low readiness or an inconsistent readiness profile—hence, teachers in higher education are not a homogeneous group. Importantly, key individual and contextual variables, such as teachers’ gender and prior OTL experience, the context of the OTL shift, the innovation potential in education, and cultural orientation, explained profile membership. We discuss these findings with respect to the nature of the profiles, how they can be understood with respect to key determinants, and their implications for OTL in higher education.

Artificial intelligence (AI) is predicted to radically transform the ways manufacturing firms create, deliver, and capture value. However, many manufacturers struggle to successfully assimilate AI capabilities into their business models and operations at scale. In this paper, we explore how manufacturing firms can develop AI capabilities and innovate their business models to scale AI in digital servitization. We present empirical insights from a case study of six leading manufacturers engaged in AI. The findings reveal three sets of critical AI capabilities: data pipeline, algorithm development, and AI democratization. To scale these capabilities, firms need to innovate their business models by focusing on agile customer co-creation, data-driven delivery operations, and scalable ecosystem integration. We combine these insights into a co-evolutionary framework for scaling AI through business model innovation underscoring the mechanisms and feedback loops. We offer insights into how manufacturers can scale AI, with important implications for management.

Versatile photoluminescence tuning in carbon dots through heteroatom doping and surface passivation and/or functionalization (SPF).

Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, risk factor analysis ideally needs to be carried through to demonstration of a causal connection, with a defined mechanism. Statistical analysis is often complicated by covariation of variables, and demonstration of a causal relationship between a factor and myopia using Mendelian randomization or in a randomized clinical trial should be aimed for. When strict analysis of this kind is applied, associations between various measures of educational pressure and myopia are consistently observed. However, associations between more nearwork and more myopia are generally weak and inconsistent, but have been supported by meta-analysis. Associations between time outdoors and less myopia are stronger and more consistently observed, including by meta-analysis. Measurement of nearwork and time outdoors has traditionally been performed with questionnaires, but is increasingly being pursued with wearable objective devices. A causal link between increased years of education and more myopia has been confirmed by Mendelian randomization, whereas the protective effect of increased time outdoors from the development of myopia has been confirmed in randomized clinical trials. Other proposed risk factors need to be tested to see if they modulate these variables. The evidence linking increased screen time to myopia is weak and inconsistent, although limitations on screen time are increasingly under consideration as interventions to control the epidemic of myopia.

BACKGROUND: Most vaginal births are associated with trauma to the genital tract. The morbidity associated with perineal trauma can be significant, especially when it comes to third- and fourth-degree tears. Different interventions including perineal massage, warm or cold compresses, and perineal management techniques have been used to prevent trauma. This is an update of a Cochrane review that was first published in 2011. OBJECTIVES: To assess the effect of perineal techniques during the second stage of labour on the incidence and morbidity associated with perineal trauma. SEARCH METHODS: We searched Cochrane Pregnancy and Childbirth's Trials Register (26 September 2016) and reference lists of retrieved studies. SELECTION CRITERIA: Published and unpublished randomised and quasi-randomised controlled trials evaluating perineal techniques during the second stage of labour. Cross-over trials were not eligible for inclusion. DATA COLLECTION AND ANALYSIS: Three review authors independently assessed trials for inclusion, extracted data and evaluated methodological quality. We checked data for accuracy. MAIN RESULTS: Twenty-two trials were eligible for inclusion (with 20 trials involving 15,181 women providing data). Overall, trials were at moderate to high risk of bias; none had adequate blinding, and most were unclear for both allocation concealment and incomplete outcome data. Interventions compared included the use of perineal massage, warm and cold compresses, and other perineal management techniques.Most studies did not report data on our secondary outcomes. We downgraded evidence for risk of bias, inconsistency, and imprecision for all comparisons. Hands off (or poised) compared to hands onHands on or hands off the perineum made no clear difference in incidence of intact perineum (average risk ratio (RR) 1.03, 95% confidence interval (CI) 0.95 to 1.12, two studies, Tau² 0.00, I² 37%, 6547 women; moderate-quality evidence), first-degree perineal tears (average RR 1.32, 95% CI 0.99 to 1.77, two studies, 700 women; low-quality evidence), second-degree tears (average RR 0.77, 95% CI 0.47 to 1.28, two studies, 700 women; low-quality evidence), or third- or fourth-degree tears (average RR 0.68, 95% CI 0.21 to 2.26, five studies, Tau² 0.92, I² 72%, 7317 women; very low-quality evidence). Substantial heterogeneity for third- or fourth-degree tears means these data should be interpreted with caution. Episiotomy was more frequent in the hands-on group (average RR 0.58, 95% CI 0.43 to 0.79, Tau² 0.07, I² 74%, four studies, 7247 women; low-quality evidence), but there was considerable heterogeneity between the four included studies.There were no data for perineal trauma requiring suturing. Warm compresses versus control (hands off or no warm compress)A warm compress did not have any clear effect on the incidence of intact perineum (average RR 1.02, 95% CI 0.85 to 1.21; 1799 women; four studies; moderate-quality evidence), perineal trauma requiring suturing (average RR 1.14, 95% CI 0.79 to 1.66; 76 women; one study; very low-quality evidence), second-degree tears (average RR 0.95, 95% CI 0.58 to 1.56; 274 women; two studies; very low-quality evidence), or episiotomy (average RR 0.86, 95% CI 0.60 to 1.23; 1799 women; four studies; low-quality evidence). It is uncertain whether warm compress increases or reduces the incidence of first-degree tears (average RR 1.19, 95% CI 0.38 to 3.79; 274 women; two studies; I² 88%; very low-quality evidence).Fewer third- or fourth-degree perineal tears were reported in the warm-compress group (average RR 0.46, 95% CI 0.27 to 0.79; 1799 women; four studies; moderate-quality evidence). Massage versus control (hands off or routine care)The incidence of intact perineum was increased in the perineal-massage group (average RR 1.74, 95% CI 1.11 to 2.73, six studies, 2618 women; I² 83% low-quality evidence) but there was substantial heterogeneity between studies). This group experienced fewer third- or fourth-degree tears (average RR 0.49, 95% CI 0.25 to 0.94, five studies, 2477 women; moderate-quality evidence).There were no clear differences between groups for perineal trauma requiring suturing (average RR 1.10, 95% CI 0.75 to 1.61, one study, 76 women; very low-quality evidence), first-degree tears (average RR 1.55, 95% CI 0.79 to 3.05, five studies, Tau² 0.47, I² 85%, 537 women; very low-quality evidence), or second-degree tears (average RR 1.08, 95% CI 0.55 to 2.12, five studies, Tau² 0.32, I² 62%, 537 women; very low-quality evidence). Perineal massage may reduce episiotomy although there was considerable uncertainty around the effect estimate (average RR 0.55, 95% CI 0.29 to 1.03, seven studies, Tau² 0.43, I² 92%, 2684 women; very low-quality evidence). Heterogeneity was high for first-degree tear, second-degree tear and for episiotomy - these data should be interpreted with caution. Ritgen's manoeuvre versus standard careOne study (66 women) found that women receiving Ritgen's manoeuvre were less likely to have a first-degree tear (RR 0.32, 95% CI 0.14 to 0.69; very low-quality evidence), more likely to have a second-degree tear (RR 3.25, 95% CI 1.73 to 6.09; very low-quality evidence), and neither more nor less likely to have an intact perineum (RR 0.17, 95% CI 0.02 to 1.31; very low-quality evidence). One larger study reported that Ritgen's manoeuvre did not have an effect on incidence of third- or fourth-degree tears (RR 1.24, 95% CI 0.78 to 1.96,1423 women; low-quality evidence). Episiotomy was not clearly different between groups (RR 0.81, 95% CI 0.63 to 1.03, two studies, 1489 women; low-quality evidence). Other comparisonsThe delivery of posterior versus anterior shoulder first, use of a perineal protection device, different oils/wax, and cold compresses did not show any effects on perineal outcomes. Only one study contributed to each of these comparisons, so data were insufficient to draw conclusions. AUTHORS' CONCLUSIONS: Moderate-quality evidence suggests that warm compresses, and massage, may reduce third- and fourth-degree tears but the impact of these techniques on other outcomes was unclear or inconsistent. Poor-quality evidence suggests hands-off techniques may reduce episiotomy, but this technique had no clear impact on other outcomes. There were insufficient data to show whether other perineal techniques result in improved outcomes.Further research could be performed evaluating perineal techniques, warm compresses and massage, and how different types of oil used during massage affect women and their babies. It is important for any future research to collect information on women's views.

Microbial communities are responsible for biological wastewater treatment, but our knowledge of their diversity and function is still poor. Here, we sequence more than 5 million high-quality, full-length 16S rRNA gene sequences from 740 wastewater treatment plants (WWTPs) across the world and use the sequences to construct the 'MiDAS 4' database. MiDAS 4 is an amplicon sequence variant resolved, full-length 16S rRNA gene reference database with a comprehensive taxonomy from domain to species level for all sequences. We use an independent dataset (269 WWTPs) to show that MiDAS 4, compared to commonly used universal reference databases, provides a better coverage for WWTP bacteria and an improved rate of genus and species level classification. Taking advantage of MiDAS 4, we carry out an amplicon-based, global-scale microbial community profiling of activated sludge plants using two common sets of primers targeting regions of the 16S rRNA gene, revealing how environmental conditions and biogeography shape the activated sludge microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 966 genera and 1530 species that represent approximately 80% and 50% of the accumulated read abundance, respectively. Finally, we show that for well-studied functional guilds, such as nitrifiers or polyphosphate-accumulating organisms, the same genera are prevalent worldwide, with only a few abundant species in each genus.

This study provides a bibliometric review of 279 studies on the applications of big data and artificial intelligence (AI) in the maritime industry, published in 214 academic outlets, authored by 842 scholars. We extracted bibliographical data from the Web of Science database and analysed it using the Bibliometrix tool in R software. Based on citation analysis metrics, we revealed the most influential articles, journals, authors and institutions. Using the bibliographic coupling methodology, we identified four underlying research clusters: (1) digital transformation in maritime industry, (2) applications of big data from AIS, (3) energy efficiency and (4) predictive analytics. We analysed these clusters in detail and extracted future research questions. Besides, we present research collaboration networks on the\ninstitution and author level.

Firms are faced with increased dynamism due to rapid technological development, digitalization, and sustainability requirements, creating novel opportunities for ecosystem innovation. This is particularly prevalent in smart city contexts where initiatives concerning, for example, energy efficient buildings and smart energy grids drive new kinds of ecosystem formation. Orchestrating emerging innovation ecosystems can offer a path to sustained competitive advantage for ecosystem leaders. Yet, it calls for the development of new capabilities to sense, seize, and reconfigure digitalization opportunities in a highly dynamic ecosystem environment. Yet, prior research lacks insights into the dynamic capabilities and routines required for ecosystem innovation. Therefore, this study investigates how firms can develop dynamic capabilities to orchestrate ecosystem innovation and, thus, gain from it. Through a multiple case study of smart city initiatives, we offer insights into the specific micro-foundations or sub-routines underlying the ecosystem leader's sensing, seizing, and reconfiguring capabilities, which are necessary to orchestrate ecosystem innovation. We develop a capability-based framework demonstrating three orchestration mechanisms – namely, configuring ecosystem partnerships, value proposition deployment, and governing ecosystem alignment. Our findings carry implications for the literature on innovation ecosystems and dynamic capabilities, as well as for managers.

Rapid growth of the aged population has caused an immense increase in the demand for healthcare services. Generally, the elderly are more prone to health problems compared to other age groups. With effective monitoring and alarm systems, the adverse effects of unpredictable events such as sudden illnesses, falls, and so on can be ameliorated to some extent. Recently, advances in wearable and sensor technologies have improved the prospects of these service systems for assisting elderly people. In this article, we review state-of-the-art wearable technologies that can be used for elderly care. These technologies are categorized into three types: indoor positioning, activity recognition and real time vital sign monitoring. Positioning is the process of accurate localization and is particularly important for elderly people so that they can be found in a timely manner. Activity recognition not only helps ensure that sudden events (e.g., falls) will raise alarms but also functions as a feasible way to guide people's activities so that they avoid dangerous behaviors. Since most elderly people suffer from age-related problems, some vital signs that can be monitored comfortably and continuously via existing techniques are also summarized. Finally, we discussed a series of considerations and future trends with regard to the construction of "smart clothing" system.

Abstract. Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land–sea contrast and high-latitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last Interglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.

Industrial manufacturers increasingly develop digital platforms in the business-to-business (B2B) context. This emergent form of digital platforms requires a profound yet little understood holistic perspective that encompasses the co-evolution of platform architecture, platform services, and platform governance. To address this research gap, our study examines multiple platform sponsors from an industrial manufacturing context. The study demarcates three platform archetypes: product platform, supply chain platform, and platform ecosystem. We argue that each platform archetype involves a gradual development of platform architecture, platform services, and platform governance, which mirror each other. We also find that each platform archetype is characterized by a specific innovation mechanism that contributes to the platform service discovery and expands the platform value. Our study extends the co-evolution perspective of platform ecosystem literature and digital servitization literature.