Hasil untuk "Norwegian literature"

Merethe Dotterud Leiren, Marie Byskov Lindberg, Kacper Szulecki

Historisk har det i stor grad vært samsvar mellom Norges og EUs energipolitikk. Likevel henger Norge et par runder bak EU i å innlemme regelverk i denne sektoren. Hvorfor har det oppstått et slik implementeringsetterslep? Basert på implementeringsteori og innsikt i litteratur om utviklingen og debatter i energisektoren, redegjør vi for hvorfor energisamarbeidet med EU er krevende for Norge. Implementeringsetterslepet kan enten forklares med utilstrekkelig administrativ kapasitet eller med politisk begrunnet forsinkelse. Vi finner at selv om norsk offentlig forvaltning er under press fordi EU har økt hyppigheten på EU-regelverksoppdateringer og fordi regelverkene er blitt mer omfattende og sektorovergripende, er hovedårsakene til etterslepet i energisektoren politiske. Det politiske ordskiftet rundt implementering av EUs energiregelverk er polarisert i Norge. Mens landet er forpliktet til å innlemme EØS-relevant regelverk, brukes forsinket innlemmelse til å utsette vanskelige politiske forhandlinger som er svært splittende i befolkningen. Abstract in English Why Norway has a Large Implementation Backlog in the Energy Sector Historically, Norway’s energy policy has largely aligned with that of the EU. Nevertheless, Norway has not transposed several consecutive packages of EU energy regulation. Seeking to answer the questions why such a delay in implementation has occured, we draw on insights from implementation literature and on developments and debates in the energy sector. We show that energy cooperation with the EU poses challenges for Norway. The lag in implementation can be attributed either to insufficient administrative capacity or to politically motivated delays. We find that Norwegian public administration is under pressure due to the EU’s increased frequency of regulatory updates and the growing complexity and cross-sectoral nature of these regulations; however, the main causes of delays in the energy sector are political. The political discourse surrounding the implementation of EU energy regulations is polarised. While the country is obligated to incorporate EEA-relevant regulations, delayed incorporation is used as a strategy to postpone difficult political negotiations that are highly divisive among the population.

Tengxiao Liu, Deepak Nathani, Zekun Li et al.

Recent progress in large language model (LLM) reasoning has focused on domains like mathematics and coding, where abundant high-quality data and objective evaluation metrics are readily available. In contrast, progress in LLM reasoning models remains limited in scientific domains such as medicine and materials science due to limited dataset coverage and the inherent complexity of open-ended scientific questions. To address these challenges, we introduce WildSci, a new dataset of domain-specific science questions automatically synthesized from peer-reviewed literature, covering 9 scientific disciplines and 26 subdomains. By framing complex scientific reasoning tasks in a multiple-choice format, we enable scalable training with well-defined reward signals. We further apply reinforcement learning to finetune models on these data and analyze the resulting training dynamics, including domain-specific performance changes, response behaviors, and generalization trends. Experiments on a suite of scientific benchmarks demonstrate the effectiveness of our dataset and approach. We release WildSci to enable scalable and sustainable research in scientific reasoning, available at https://huggingface.co/datasets/JustinTX/WildSci.

Hamideh Ghanadian, Amin Kamali, Mohammad Hossein Tekieh

This paper investigates the enhancement of scientific literature chatbots through retrieval-augmented generation (RAG), with a focus on evaluating vector- and graph-based retrieval systems. The proposed chatbot leverages both structured (graph) and unstructured (vector) databases to access scientific articles and gray literature, enabling efficient triage of sources according to research objectives. To systematically assess performance, we examine two use-case scenarios: retrieval from a single uploaded document and retrieval from a large-scale corpus. Benchmark test sets were generated using a GPT model, with selected outputs annotated for evaluation. The comparative analysis emphasizes retrieval accuracy and response relevance, providing insight into the strengths and limitations of each approach. The findings demonstrate the potential of hybrid RAG systems to improve accessibility to scientific knowledge and to support evidence-based decision making.

O.M. Nordaunet, E.R. Gjevjon, H. Aagaard et al.

Background: Nursing practice addressing the physical, psychosocial, and relational needs of older people – the three core dimensions of the fundamentals of care framework along with its overarching dimension, commitment to care – is a complex yet vital aspect of nurses’ scope of practice. However, it is underrepresented in the clinical context of facility-based care, such as nursing homes. Consequently, there is limited understanding of to what extent nurses engage in activities targeting older people’s fundamentals of care needs, the applicability of the framework in practice, and what acts as contextual modulators. Furthermore, contextual modulators of practice require greater attention, especially within increasingly complex healthcare systems, where nursing practice should be studied as a part of a larger system. Objective: To explore nursing practice, its contextual modulators, and the clinical decision-making processes, as aligned with the nursing process of nurses targeting older people’s fundamentals of care needs in nursing homes. Design: An exploratory study. Setting: Four nursing homes across three Norwegian municipalities. Methods: Structured direct observations were conducted. Thus, observations was supported by a protocol developed from established theoretical frameworks and concepts identified in the nursing literature as relevant to practice or as modulators of practice. Data analysis incorporated both textual and numerical analyses in a multimethod approach. Results: A total of 4351 framework activities were observed during 411 sessions (189 hours). On average, nurses engaged in 10.58 activities per observation, often addressing multiple dimensions of the framework simultaneously. Activities related to the dimension commitment to care were less frequently observed than those in the other three dimensions. We found that most observations showed nurses initiating care with activities targeting physical needs, which often expanded to include psychosocial and relational dimensions. Registered nurses primarily focused on the assessment phase of the nursing process. Nursing practice was found to be influenced by a lack of risk management, an unsupportive working environment, and unclear leadership and management of care. Conclusion and implications: This is one of the first studies exploring nursing practice targeting the fundamentals of care framework in this context. We have highlighted the intricate nature of nursing practice, its relationship with clinical decision-making processes, and the functional and performance levels of nursing activities. Contextual modulators were found to negatively influence nursing practice, suggesting the need for improved risk management, a supportive work environment, and clear nursing leadership.

Hongbo Zhang, Han Cui, Yidong Wang et al.

Automatic literature survey generation has attracted increasing attention, yet most existing systems follow a one-shot paradigm, where a large set of papers is retrieved at once and a static outline is generated before drafting. This design often leads to noisy retrieval, fragmented structures, and context overload, ultimately limiting survey quality. Inspired by the iterative reading process of human researchers, we propose \ours, a framework based on recurrent outline generation, in which a planning agent incrementally retrieves, reads, and updates the outline to ensure both exploration and coherence. To provide faithful paper-level grounding, we design paper cards that distill each paper into its contributions, methods, and findings, and introduce a review-and-refine loop with visualization enhancement to improve textual flow and integrate multimodal elements such as figures and tables. Experiments on both established and emerging topics show that \ours\ substantially outperforms state-of-the-art baselines in content coverage, structural coherence, and citation quality, while producing more accessible and better-organized surveys. To provide a more reliable assessment of such improvements, we further introduce Survey-Arena, a pairwise benchmark that complements absolute scoring and more clearly positions machine-generated surveys relative to human-written ones. The code is available at https://github.com/HancCui/IterSurvey\_Autosurveyv2.

Sauhard Dubey

Cross-domain scientific synthesis requires connecting mechanistic explanations across fragmented literature, a capability that remains challenging for both retrieval-based systems and unconstrained language models. While recent work has applied large language models to scientific summarization and question answering, these approaches provide limited control over reasoning depth and structural grounding. We frame mechanistic synthesis as a graph-constrained multi-hop reasoning problem over literature-derived concept graphs. Given a scientific query and a compact, query-local corpus, SciNets constructs a directed concept graph and synthesizes mechanistic explanations by identifying multi-hop reasoning paths that connect concepts that rarely co-occur within individual papers. We systematically compare shortest-path reasoning, k-shortest paths with diversity constraints, stochastic random walks, and a retrieval-augmented language model baseline. Rather than evaluating correctness, which is often indeterminate when synthesizing connections across distributed sources, we introduce a behavioral framework that measures symbolic reasoning depth, mechanistic diversity, and grounding stability. Across machine learning, biology, and climate science tasks, explicit graph constraints enable controllable multi-hop reasoning while revealing a consistent trade-off: deeper and more diverse symbolic reasoning increases grounding instability, whereas shortest-path reasoning remains highly stable but structurally conservative. These findings provide a systematic behavioral characterization of the limits and capabilities of current graph-LLM integration for scientific synthesis.

Mathijs Barkel, Rachael Colley, Maxence Delorme et al.

Kidney exchange is a transplant modality that has provided new opportunities for living kidney donation in many countries around the world since 1991. It has been extensively studied from an Operational Research (OR) perspective since 2004. This article provides a comprehensive literature survey on OR approaches to fundamental computational problems associated with kidney exchange over the last two decades. We also summarise the key integer linear programming (ILP) models for kidney exchange, showing how to model optimisation problems involving only cycles and chains separately. This allows new combined ILP models, not previously presented, to be obtained by amalgamating cycle and chain models. We present a comprehensive empirical evaluation involving all combined models from this paper in addition to bespoke software packages from the literature involving advanced techniques. This focuses primarily on computation times for 49 methods applied to 4,320 problem instances of varying sizes that reflect the characteristics of real kidney exchange datasets, corresponding to over 200,000 algorithm executions. We have made our implementations of all cycle and chain models described in this paper, together with all instances used for the experiments, and a web application to visualise our experimental results, publicly available.

Pablo Barneo, Giuseppe Cabras, Pierre-Francois Cohadon et al.

As members of the Virgo Collaboration -- one of the large scientific collaborations that explore the universe of gravitational waves together with the LIGO Scientific Collaboration and the KAGRA Collaboration -- we became aware of biased citation practices that exclude Virgo, as well as KAGRA, from achievements that collectively belong to the wider LIGO/Virgo/KAGRA Collaboration. Here, we frame these practices in the context of Merton's Matthew effect, extending the reach of this well studied cognitive bias to include large international scientific collaborations. We provide qualitative evidence of its occurrence, displaying the network of links among published papers in the scientific literature related to Gravitational Wave science. We note how the keyword LIGO is linked to a much larger number of papers and variety of subjects than the keyword Virgo. We support these qualitative observations with a quantitative study based on a year-long monitoring of the relevant literature, where we scan all new preprints appearing in the arXiv electronic preprint database. Over the course of one year we identified all preprints failing to assign due credits to Virgo. As a further step, we undertook positive actions by asking the authors of problematic papers to correct them. We also report on a more in-depth investigation which we performed on problematic preprints that appeared in the first three months of the period under consideration, checking how frequently their authors reacted positively to our request and corrected their papers. Finally, we measure the global impact of papers classified as problematic and observe that, thanks to the changes implemented in response to our requests, the global impact (measured as the number of citations of papers which still contain Virgo visibility issues) was halved. We conclude the paper with general considerations for future work in a wider perspective.

Neris Özen, Wenjuan Mu, Esther D. van Asselt et al.

The number of scientific articles published in the domain of food safety has consistently been increasing over the last few decades. It has therefore become unfeasible for food safety experts to read all relevant literature related to food safety and the occurrence of hazards in the food chain. However, it is important that food safety experts are aware of the newest findings and can access this information in an easy and concise way. In this study, an approach is presented to automate the extraction of chemical hazards from the scientific literature through large language models. The large language model was used out-of-the-box and applied on scientific abstracts; no extra training of the models or a large computing cluster was required. Three different styles of prompting the model were tested to assess which was the most optimal for the task at hand. The prompts were optimized with two validation foods (leafy greens and shellfish) and the final performance of the best prompt was evaluated using three test foods (dairy, maize and salmon). The specific wording of the prompt was found to have a considerable effect on the results. A prompt breaking the task down into smaller steps performed best overall. This prompt reached an average accuracy of 93% and contained many chemical contaminants already included in food monitoring programs, validating the successful retrieval of relevant hazards for the food safety domain. The results showcase how valuable large language models can be for the task of automatic information extraction from the scientific literature.

Pablo Moriano, Steven C. Hespeler, Mingyan Li et al.

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks focused on fast data processing and model adaptation. AAD has been researched in the literature extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on the current research within this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS studies from 2013 to 2023 (November). We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our analysis indicates, among other findings, that reviewed works focused on a single aspect of adaptation (either data processing or model adaptation) but rarely in both at the same time. We aim to help researchers to advance the state of the art and help practitioners to become familiar with recent progress in this field. We identify the limitations of the state of the art and provide recommendations for future research directions.

Masudul Hasan Masud Bhuiyan, Berk Çakar, Ethan H. Burmane et al.

Regular Expression Denial of Service (ReDoS) is a vulnerability class that has become prominent in recent years. Attackers can weaponize such weaknesses as part of asymmetric cyberattacks that exploit the slow worst-case matching time of regular expression (regex) engines. In the past, problematic regexes have led to outages at Cloudflare and Stack Overflow, showing the severity of the problem. While ReDoS has drawn significant research attention, there has been no systematization of knowledge to delineate the state of the art and identify opportunities for further research. In this paper, we describe the existing knowledge on ReDoS. We first provide a systematic literature review, discussing approaches for detecting, preventing, and mitigating ReDoS vulnerabilities. Then, our engineering review surveys the latest regex engines to examine whether and how ReDoS defenses have been realized. Combining our findings, we observe that (1) in the literature, almost no studies evaluate whether and how ReDoS vulnerabilities can be weaponized against real systems, making it difficult to assess their real-world impact; and (2) from an engineering view, many mainstream regex engines have introduced partial or full ReDoS defenses, rendering many threat models obsolete. We conclude by highlighting avenues for future work. The open challenges in ReDoS research are to evaluate emerging defenses and support engineers in migrating to defended engines. We also highlight the parallel between performance bugs and asymmetric DoS, and we argue that future work should capitalize more on this similarity and adopt a more systematic view on ReDoS-like vulnerabilities.

Bence Kelemen, Ottó Benczenleitner, László Tóth

This study aimed to give a systematic literature review about the training of elite Norwegian long-distance runners (1500-10.000 meters). After a search in databases, we found 7 articles, that have systematically registered the training volume and intensity distribution of 13 elite runners over longer periods (n = 13). The results were the following: the best long-distance runners run 120 to 180 kilometers per week on average. The waist majority of this training (75-80 %) is done at low intensity (62-82% HRmax). Two to four sessions are done at the anaerobic threshold pace (82-20% HRmax), either in continuous or interval format during the base period, often done twice on the same day. One to two times weekly higher intensity sessions (>97% HRmax) are done, in form of short intervals (>800m) or short sprints. Longer intervals, above the anaerobic threshold (92-97 % HRmax) are rarely used during the base period. The training is closely monitored by a lactate meter or heart rate monitor. Before the racing season, in the pre-competition period, the athletes do fewer workouts at an anaerobic threshold pace and increase the number of sessions at a specific race pace.

Kristian Espeland, Andrius Kleinauskas, Petras Juzenas et al.

Photodynamic therapy (PDT) using 5-aminolevulinic acid (ALA) which is the precursor of the photosensitizer protoporphyrin IX (PpIX) is an available treatment for several diseases. ALA-PDT induces the apoptosis and necrosis of target lesions. We have recently reported the effects of ALA-PDT on cytokines and exosomes of human healthy peripheral blood mononuclear cells (PBMCs). This study has investigated the ALA-PDT-mediated effects on PBMC subsets from patients with active Crohn’s disease (CD). No effects on lymphocyte survival after ALA-PDT were observed, although the survival of CD3−/CD19+ B-cells seemed slightly reduced in some samples. Interestingly, ALA-PDT clearly killed monocytes. The subcellular levels of cytokines and exosomes associated with inflammation were widely downregulated, which is consistent with our previous findings in PBMCs from healthy human subjects. These results suggest that ALA-PDT may be a potential treatment candidate for CD and other immune-mediated diseases.

Kerstin Potthoff, Birgit Kopainsky

Mithil Sai Jakka

The exploration and study of exoplanets remain at the frontier of astronomical research, challenging scientists to continuously innovate and refine methodologies to navigate the vast, complex data these celestial bodies produce. This literature the review aims to illuminate the emerging trends and advancements within this sphere, specifically focusing on the interplay between exoplanet detection, classification, and visualization, and the the increasingly pivotal role of machine learning and computational models. Our journey through this realm of exploration commences with a comprehensive analysis of fifteen meticulously selected, seminal papers in the field. These papers, each representing a distinct facet of exoplanet research, collectively offer a multi-dimensional perspective on the current state of the field. They provide valuable insights into the innovative application of machine learning techniques to overcome the challenges posed by the analysis and interpretation of astronomical data. From the application of Support Vector Machines (SVM) to Deep Learning models, the review encapsulates the broad spectrum of machine learning approaches employed in exoplanet research. The review also seeks to unravel the story woven by the data within these papers, detailing the triumphs and tribulations of the field. It highlights the increasing reliance on diverse datasets, such as Kepler and TESS, and the push for improved accuracy in exoplanet detection and classification models. The narrative concludes with key takeaways and insights, drawing together the threads of research to present a cohesive picture of the direction in which the field is moving. This literature review, therefore, serves not just as an academic exploration, but also as a narrative of scientific discovery and innovation in the quest to understand our cosmic neighborhood.

Muhammad Shoaib Farooq, Shamyla Riaz, Atif Alvi

In the past few years, the Web of Things (WOT) became a beneficial game-changing technology within the Agriculture domain as it introduces innovative and promising solutions to the Internet of Things (IoT) agricultural applications problems by providing its services. WOT provides the support for integration, interoperability for heterogeneous devices, infrastructures, platforms, and the emergence of various other technologies. The main aim of this study is about understanding and providing a growing and existing research content, issues, and directions for the future regarding WOT-based agriculture. Therefore, a systematic literature review (SLR) of research articles is presented by categorizing the selected studies published between 2010 and 2020 into the following categories: research type, approaches, and their application domains. Apart from reviewing the state-of-the-art articles on WOT solutions for the agriculture field, a taxonomy of WOT-base agriculture application domains has also been presented in this study. A model has also presented to show the picture of WOT based Smart Agriculture. Lastly, the findings of this SLR and the research gaps in terms of open issues have been presented to provide suggestions on possible future directions for the researchers for future research.

Bernt Bratsberg, Simen Markussen, Oddbjørn Raaum et al.

Abstract We study assortative mating of Norwegian parents over five decades and its consequences for offspring outcomes. Parents are characterised by the earnings decile of their parents (the offspring's grandparents) as an indicator of social class. While assortative mating has remained stable across decades, parenthood has become more skewed toward the higher classes. Examining the influence on offspring education and employment, we find that the marginal effect of one parent's class is smaller the higher is the class of the other. Overall, mating trends have contributed to slight improvements in average education and employment and reduced inequality in the offspring generation.

Ingrid Marie Garfelt Paulsen, Åshild Ønvik Pedersen, Richard Hann et al.

Conservation of wildlife depends on precise and unbiased knowledge on the abundance and distribution of species. It is challenging to choose appropriate methods to obtain a sufficiently high detectability and spatial coverage matching the species characteristics and spatiotemporal use of the landscape. In remote regions, such as in the Arctic, monitoring efforts are often resource-intensive and there is a need for cheap and precise alternative methods. Here, we compare an uncrewed aerial vehicle (UAV; quadcopter) pilot survey of the non-gregarious Svalbard reindeer to traditional population abundance surveys from ground and helicopter to investigate whether UAVs can be an efficient alternative technology. We found that the UAV survey underestimated reindeer abundance compared to the traditional abundance surveys when used at management relevant spatial scales. Observer variation in reindeer detection on UAV imagery was influenced by the RGB greenness index and mean blue channel. In future studies, we suggest testing long-range fixed-wing UAVs to increase the sample size of reindeer and area coverage and incorporate detection probability in animal density models from UAV imagery. In addition, we encourage focus on more efficient post-processing techniques, including automatic animal object identification with machine learning and analytical methods that account for uncertainties.

Thorunn Gullaksen Endreson

Norwegian contemporary climate fiction often portrays humans as in denial of climate change. In Erlend Nødtvedt’s transgressive novel Vestlandet (2017), an alternative story is presented. In contrast to conventional climate change denial, the two protagonists turn the situation upside down and literally celebrate death and climate change and the exceptional Western Norwegian »sublime« landscape. Drawing on Mikhail Bakhtin’s concept of laughter and the carnivalesque, I will investigate Vestlandet as a response to a world in climate crisis, and thereby transcending the ecocritical reluctance to engage with laughter. Environmental humor offers an alternative vision, a possibility to see ourselves from another perspective. Vestlandet contributes to the creation of new climate change narratives and communicates potential for change, but there is no guarantee that laughter will lead to increased awareness and action. In der zeitgenössischen norwegischen Klimaliteratur wird der Mensch oft als Leugner des Klimawandels dargestellt. In Erlend Nødtvedts transgressivem Roman Vestlandet (2017) wird eine alternative Geschichte präsentiert. Im Gegensatz zur herkömmlichen Leugnung des Klimawandels stellen die beiden Protagonisten die Situation auf den Kopf und feiern buchstäblich den Tod, den Klimawandel und die außergewöhnliche westnorwegische »erhabene « Landschaft. In Anlehnung an Mikhail Bakhtins Konzept des Lachens und des Karnevalesken werde ich Vestlandet als Antwort auf eine Welt in der Klimakrise untersuchen und dabei die ökokritische Zurückhaltung gegenüber dem Lachen überwinden. Umwelthumor bietet eine alternative Vision, eine Möglichkeit, uns selbst aus einer anderen Perspektive zu sehen. Vestlandet trägt zur Schaffung neuer Erzählungen über den Klimawandel bei und vermittelt das Potenzial für Veränderungen, gibt aber keine Garantie dafür, dass Lachen zu mehr Bewusstsein und Handeln führt.

Silviu Miloiu

The inaugural issue of the fourteenth edition of the Romanian Journal for Baltic and Nordic Studies is devoted to perceptions, identity, and alterity, three visible stars in the modern sky. To paraphrase Zygmunt Bauman, who spoke of the unholy trinity of modernity, i.e., uncertainty, unpredictability, and insecurity, we may term our unholy trinity sinful when it is exploited to deprive others of their identity or impose one’s dominance over another. Referencing the British sociologist Gerard Delanty’s concept of “boundary and identities of exclusion,” the first research article examines the “hard borders” in the Baltic Sea Region between 1917 and 1922, concluding that in every instance in which war and violence were used in the Baltic Sea Region to award borders to one state over another or to settle accounts, the arrangements were not permanent and a cycle of warfare with devastating effects on local populations ensued. Andreea Dahlquist also examines the scenario of geographically distant states, which can occasionally lead to the same outcomes. In such circumstances, the number of cultural hubs, mass media, and social mediators across societies is limited, and mutual understanding is incomplete and imbalanced. Analyzing Romanian-Swedish ties during the Second World War, the author also draws attention to the discrepancy between the nearly entirely favorable attitude of Romanians in Sweden and the more circumspect attitude of Swedish society toward Romania. Costel Coroban’s research on the Saga of the People of Laxárdalr through the lenses of historical and literary criticism in order to provide an account of how Norwegian kings or queens were portrayed demonstrates conclusively that perception and representation are social phenomena and play a significant role in shaping the minds of historical figures and their decisions and actions. As in many other similar texts, he finds that the author of the tale either portrays the Norwegian monarchy in an extraordinarily favourable or highly terrible light. According to Valerii Lastovskyi of the Kyiv National University of Culture and Education, the central question in Polish historiography is why the Rzeczpospolita eventually collapsed. The author examines Polish historical literature in order to explain how the function of the Orthodox Church has been viewed in this regard for the past half millennium and what has changed through time. In addition, Polish historians investigated the inner workings of Ukrainian churches and religious activities. Finally, Mihaela Mehedinţi highlights the simultaneity and interdependence of identity and alterity formation among modern Romanians, demonstrating this vantage point with the perception of the British and the Americans in Transylvania, Wallachia and Moldova. Her conclusions warrant citation and attention from a theoretical and methodological standpoint: „Despite the cultural and/or geographical distance between Transylvania, Wallachia and Moldavia, on the one hand, and Great Britain and the United States of America, on the other hand, towards the end of the 19th century average Romanians were able to interwove information gathered from a wide range of sources and to transform it into realistic depictions of these two countries and their inhabitants. This process of defining the Other combined diachronic and synchronous tendencies, fiction and facts, stereotypes and truth.” The editors hope that the journal’s ideas, concepts, and case studies will inspire other academics and readers to reflect once more on perceptions, identity, and difference, and to produce new research for submission to the Romanian Journal for Baltic and Nordic Studies.