Traditional Research Research Articles

Wives, Daughters and Sisters: Noble Women in Medieval Lithuania (13th–15th Centuries)

The history of medieval women in Lithuania a little-known topic. This is due to two reasons. Firstly, the long-dominant research tradition, which has given the main role to the history of “great men”, has undoubtedly left women on the margins of studies. Secondly, the state of research has been, and continues to be, largely determined by the availability of the sources. Of all the rulers of Lithuania during the pagan period, only the names of Mindaugas’ wife and both of Algirdas’ wives are known with certainty. Sensing this gap, some of the rulers’ wives were “given” names by later chroniclers.The situation concerning the sources regarding the wives and daughters of the nobility is similar. For example, of the 26 most influential nobles of the time of Grand Duke Vytautas, in 14 cases, we do not know the name or origin of the wife. Nevertheless, the processing and compilation of the rather scattered material on the Lithuanian noble women allows us to draw some conclusions about the political and social system of the Lithuanian medieval state.Women played an important role in the world of the nobility. As wives, daughters, and sisters, they established and maintained ties between relatives, both at home and (in the case of rulers) abroad. Successful marriages often determined the trajectories of men’s careers, and sometimes even of individual families. However, they mostly remained in the silence of the sources and, thanks to the conjuncture of the sources, they appear before us first of all as pious foundresses, preservers of the memory of the family, and guardians of children.

The role of thematic specialization in international scientific collaboration: the case of Chagas research

Abstract Scientists are increasingly specializing to manage the vast knowledge bases within their domains, making knowledge-sharing strategies essential for scientific progress. Among these strategies, international scientific collaboration has increased markedly. We analyse the role of thematic specialization as one of its drivers in the context of Chagas research, a neglected disease. Since there is a strong research tradition in Latin America on this topic, it is an interesting context to study centre-periphery research dynamics. Using a novel bibliometric database on Chagas research during 1990–2019, we exploit its panel structure in a gravity-type econometric model. The findings show that the degree of specialization and its proximity among partners boost joint publications. Both effects are particularly important for country dyads involving authors from the periphery linked to authors in the centre. This paper is the first empirical study to assess the role of specialization as a driver of international scientific collaboration.

Multimodal Embodiment Research of Oral Music Traditions: Electromyography in Oud Performance and Education Research of Persian Art Music

With the recent advent of research focusing on the body’s significance in music, the integration of physiological sensors in the context of empirical methodologies for music has also gained momentum. Given the recognition of covert muscular activity as a strong indicator of musical intentionality and the previously ascertained link between physical effort and various musical aspects, electromyography (EMG)—signals representing muscle activity—has also experienced a noticeable surge. While EMG technologies appear to hold good promise for sensing, capturing, and interpreting the dynamic properties of movement in music, which are considered innately linked to artistic expressive power, they also come with certain challenges, misconceptions, and predispositions. The paper engages in a critical examination regarding the utilisation of muscle force values from EMG sensors as indicators of physical effort and musical activity, particularly focusing on (the intuitively expected link to) sound levels. For this, it resides upon empirical work, namely practical insights drawn from a case study of music performance (Persian instrumental music) in the context of a music class. The findings indicate that muscle force can be explained by a small set of (six) statistically significant acoustic and movement features, the latter captured by a state-of-the-art (full-body inertial) motion capture system. However, no straightforward link to sound levels is evident.

Predicting compressor mass flow rate using various machine learning approaches

Abstract A major focus of the present study is to construct high-fidelity models for predicting corrected mass flow rates based on the collected compressor map data. Both traditional machine learning research and modern deep learning techniques have been employed to obtain well-fitted regression models of compressor mass flow rate. As traditional machine learning methods, Multiple Linear Regression and Random Forest, are conducted on compressor maps for prediction of corrected mass flow rate. The time series-based deep learning models are able to capture the overall trend of a given input for specific map data. Therefore, a time series-based deep learning technique, namely Gated Recurrent Unit has been employed to improve regression results. Besides, the prediction capabilities of the models, results also show that the proposed models can be used for the development of dynamic aero-thermal mathematical models of gas turbine engines and mass flow rate models created for dynamic compressors in other disciplines.

REVITALIZING THERAPEUTICS: DRUG REPURPOSING AS A COST-EFFECTIVE STRATEGY FOR DRUG DEVELOPMENT

The process of developing new drugs is known for being drawn-out, expensive, risky, and having a high attrition rate. Drug repurposing has grown in favor recently as a practical way to speed up the development of new medicines while reducing the costs and time constraints associated with traditional drug research. The description of this study's pharmacological repurposing highlights its promise as a practical method to fill gaps in the market and revitalize treatment options. This review provides a full analysis of the ground-breaking tactic of repurposing medications, supported by numerous cases that demonstrate its revolutionary potential. We examine instances of repurposed drugs, such as thalidomide, sildenafil, and metformin, that have performed astoundingly well in a range of therapeutic settings despite being used outside of their original scope. Overall, the paper's main goal-to study pharmacological repurposing as a potentially successful strategy for revitalizing treatments-is, succinctly summarized in this abstract. It highlights the potential benefits of this approach and how it might be used in the pharmaceutical industry's ongoing quest for more inexpensive and effective medicine development.

Landscape Design and Green Space Perception Enhancement Based on Panoramic Imaging and Segnet

Green view rate is an intuitive evaluation criterion used for green space perception. Traditional research on green view rate is mostly calculated based on flat images, which cannot fully reflect the subjective human perception of green volume in three-dimensional space. Based on the panoramic image, we propose the concept of panoramic green perception rate, obtain spherical panoramic photos by panoramic camera, convert isometric cylindrical projection into isoprojective cylindrical projection, and use the convolutional neural network model based on semantic segmentation to automatically identify the area of vegetation to achieve automatic recognition and measurement of panoramic green perception rate. The results were compared with manual discrimination and showed that the average intersection ratio (mIoU) of greenery recognition using Dilated ResNet-105 was 62.53%, and the average difference with manual recognition was 9.17%.

NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics.

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.

Mind the gap: The fissure between aspirations and actions in climate change governance at a local government level: A study of the Eastern Cape Province of South Africa

AbstractIt is no longer a myth that climate change‐related disasters are on the rise globally, with severe and devastating consequences in developing countries, particularly in Sub‐Saharan Africa, where many of the world's poor people reside. Thus, the emphasis on adaptation to climate change is no longer a choice or a deferred problem into the future, but rather an urgent matter of concern which must be considered a policy priority. As a response to retrogressive climate change challenges on social‐economic development and environmental degradation, the government of South Africa has in the last two and half decades, embarked on the progressive formulation of different policy instruments and strategic frameworks to curb and minimize the impacts of climate change on all sub‐sectors of the economy. Although much remains to be achieved, some level of success has been realized, particularly in the space of policy formulation, albeit the poor record of implementation. Using research methods inspired by the tradition of qualitative research and an appraisal of existing literature, this paper discusses the complexities of climate change adaptation governance at a local government level in South Africa, focusing on the Eastern Cape Province. It is argued in the paper that one of the major challenges for climate change governance at local municipality levels in South Africa emanates from the gap between aspirations and actions across the entire national governance system. The absence of an integrated climate change governance system has posed significant systemic challenges, and these have tended to constrain decision‐making and implementation processes. These issues have been discussed within the broader discourse of the sustainable development goals, particularly goals number 13, 16 and 17.

Open Science Practices in Traditional, Complementary, and Integrative Medicine Research: A Path to Enhanced Transparency and Collaboration

This educational article delves into the convergence of open science practices and traditional, complementary, and integrative medicine (TCIM), shedding light on the potential benefits and challenges of open science for the development, dissemination, and implementation of evidence-based TCIM. We emphasize the transformative shift in medical science towards open and collaborative practices, highlighting the limited application of open science in TCIM research despite its growing acceptance among patients. We define open science practices and discuss specific open science practices applicable to TCIM, including study registration, adherence to reporting guidelines, data sharing, preprinting, and open access publishing. We explore the benefits of open science in TCIM, spanning improved research quality, increased public trust, accelerated innovation, and enhanced evidence-based decision-making. We also acknowledge challenges such as data privacy concerns, limited resources, and resistance to cultural change. We propose strategies to overcome these challenges, including ethical guidelines, education programs, funding advocacy, interdisciplinary dialogue, and patient engagement. Looking to the future, we envision the maturation of open science in TCIM, the development of TCIM-specific guidelines for open science practices, advancements in data sharing platforms, the integration of open data and artificial intelligence in TCIM research, and the role of policy and regulation. We foresee a future where open science in TCIM leads to a better evidence base for integrative medicine, informed decision-making, interdisciplinary collaboration, and transformative impacts on healthcare and research methodologies, highlighting the promising synergy between open science and TCIM for holistic, evidence-based healthcare solutions.

Effect of synergistic fermentation of Saccharomyces cerevisiae and Lactobacillus plantarum on thermal properties of hyaluronic acid-wheat starch system

Hyaluronic acid (HA), as a multifunctional hydrophilic polysaccharide, is potentially beneficial in improving the thermal stability of fermented modified starches, but relevant insights at the molecular level are lacking. The aim of this study was to investigate the effect of different levels (0 %, 3 %, 6 %, 9 %, 12 % and 15 %) of HA on the structural, thermal and pasting properties of wheat starch co-fermented with Saccharomyces cerevisiae and Lactobacillus plantarum. We found that the addition of HA increased the median particle size of fermented starch granules from 16.387 to 17.070 μm. Meanwhile, the crystallinity of fermented starch was negatively correlated with the HA content, decreasing from 14.70 % to 12.80 % (p < 0.05). Fourier transform infrared spectroscopy results confirmed that HA interacted with starch granules and water molecules mainly through hydrogen bonding. Thermal analyses showed that the thermal peak of the composite correlated with the HA concentration, reaching a maximum of 73.17 °C at 12 % HA. In addition, HA increases the pasting temperature, reduces the peak, breakdown and setback viscosities of starch. This study demonstrates the role of HA in improving the thermal stability of fermented starch, providing new insights for traditional fermented food research and the application of HA in food processing.

Is the EU steering national social and health policy making? A case-study on Finland's national reform Is the EU steering national social and health policy making? A case-study on Finland's national reform

As part of the European Semester, Finland received country-specific recommendations (CSRs) in 2013–2020 that encouraged the reform of national social and health services. These recommendations were part of efforts to balance public finances and implement public-sector structural reforms. Finland has been struggling to reform the national social and health care system since 2005. Only on 1 January 2023 did the new wellbeing services counties become liable for organizing social, health, and rescue services. Studying the CSRs for Finland enables us to understand better what genuinely occurs at the EU member state level. This data-driven case study aims to disclose the relevance of the European Semester for Finland in the pursuit of a national social and health system reform. The mixed-method approach is based on the research tradition of governance, and the study contains features of data sourcing and methodological triangulation. Empirically, the research material consists of Finland's official policy documents and anonymous semi-structured elite interviews. The study highlights that although the received CSRs on the need to restructure social and health services corresponded to Finland's views, their influence to national reform efforts was limited. The CSRs were administered according to the established formal routines, but separately from the national reform preparations. The CSRs, however, delivered implicit steering, which were considered to affect social and health policy making in various ways.

Illustrating Tomorrow: The Role of Comics in Engaging Research Participants in Disruptive Futures Research

This study examines the application of comics in futures research to involve stakeholders in infrastructure strategy discussions for disruptive futures. It employs a graphic novel called “Vanishing Point! Our Built World,” which augments generative AI art with human storytelling to transport participants into a speculative 2150 with a solarpunk theme. The narrative applies the concept of future-self continuity and a temporal discontinuity framework to promote visions of sustainability for both humanity and the environment. The research emphasises the ability of comics to foster meaningful discussions on future infrastructure coordination by incorporating Social Construction Theory, Social Construction of Technology Theory, and Actor Network Theory. Comics being adapted into videos and used in workshops highlight their effectiveness in promoting engagement and facilitating semi-structured discussions. This demonstrates comics as a dynamic tool in futures research and participatory methodologies. Relevant themes: Anthropocene, Ecocene and Climate Change/Post-capitalism/Utopias, Eutopias and Dystopias/Solar Punk and its relations/Artificial Intelligence and Automation/Wicked Problems/Futures and Metaphor/Reimagining Futures Tools and Methodologies. Statement acknowledging use of Generative AI Art and copyright ownership: “Vanishing Point! Our Built World” graphic novel artwork was created with Midjourney generative AI. These images were created using the author’s prompts and ideas. The author owns these AI-generated photos and their derivatives. Synthesia was used to create animated films and AI-generated avatars from comic artwork. Statement on the use of Generative AI in the production of this manuscript: Referring to Author Guidelines on Using Generative AI and Large Language Models| Sage Learning Resources (sagepub.com ), this manuscript employed various AI tools to assist with research and writing. ChatGPT4 and its plugin, Scholar AI, helped identify relevant literature in addition to traditional research. Litmaps revealed article linkages, clarifying the research landscape. ChatGPT4 critiqued the manuscript. Quillbot improved the manuscript's clarity and consistency by improving its language.

Arbitrary Digital DNA Computing: A Programmable Molecular Perceptron Driven by Lambda Exonuclease for Lighting up Concatenated Circuits.

DNA circuits, as a type of biochemical system, have the capability to synchronize the perception of molecular information with a chemical reaction response and directly process the molecular characteristic information in biological activities, making them a crucial area in molecular digital computing and smart bioanalytical applications. Instead of cascading logic gates, the traditional research approach achieves multiple logic operations which limits the scalability of DNA circuits and increases the development costs. Based on the interface reaction mechanism of Lambda exonuclease, the molecular perceptron proposed in this study, with the need for only adjusting weight and bias parameters to alter the corresponding logic expressions, enhances the versatility of the molecular circuits. We also establish a mathematical model and an improved heuristic algorithm for solving weights and bias parameters for arbitrary logic operations. The simulation and FRET experiment results of a series of logic operations demonstrate the universality of molecular perceptron. We hope the proposed molecular perceptron can introduce a new design paradigm for molecular circuits, fostering innovation and development in biomedical research related to biosensing, targeted therapy, and nanomachines.

Evolving Attitudes of Science Graduate Students Toward Science Policy and Communication

Widespread changes in the exchange and politicization of science have made it imperative for scientists to be prepared to engage in science communication and science policy. Separately, science graduate students express interest in a more diverse array of career trajectories beyond the traditional academic research path. These forces together inspire changes to graduate education to develop critical science communication and policy skills. However, universities remain focused on training students in primarily academic research skills. This case study measured changes to beliefs about and participation in science communication and policy among science graduate students over three years to better understand the evolution of interest in these practices. Importantly, not only did students report a significantly increased interest in and belief in the importance of science communication and policy, but also these increases were observed regardless of their initial beliefs. Graduate students also provided qualitative feedback about the reasons behind these changes and perceived barriers to participating in science communication and policy. These data help to both motivate universal changes to graduate education to include science communication and policy and to inform stakeholders on how these changes can be optimally designed to address barriers and interests. Finally, corresponding policy changes are recommended to departments, universities, scientific societies, and other stakeholders to enact effective change to graduate training.

Research Hidden in Plain Sight: Theorizing Latent Use as a Form of Research Use

Calls for evidence-based practice are pervasive. In response, extensive scholarship has employed four categories of research use—instrumental, symbolic, conceptual, and imposed—to examine how research is used in schools and districts. We draw on sociocultural learning theory and empirical data from one school district to newly theorize latent use as another category of research use. We define latent use as when educators participate with a research-embedded tool in ways that guide their work practice. We call this “latent” use because educators use research via their participation with tools embedded with research quotes, citations, and/or summaries rather than directly engaging with traditional research products (e.g., journal articles). We then discuss latent use's potential merits and limitations.

Improvements in viral gene annotation using large language models and soft alignments

BackgroundThe annotation of protein sequences in public databases has long posed a challenge in molecular biology. This issue is particularly acute for viral proteins, which demonstrate limited homology to known proteins when using alignment, k-mer, or profile-based homology search approaches. A novel methodology employing Large Language Models (LLMs) addresses this methodological challenge by annotating protein sequences based on embeddings.ResultsCentral to our contribution is the soft alignment algorithm, drawing from traditional protein alignment but leveraging embedding similarity at the amino acid level to bypass the need for conventional scoring matrices. This method not only surpasses pooled embedding-based models in efficiency but also in interpretability, enabling users to easily trace homologous amino acids and delve deeper into the alignments. Far from being a black box, our approach provides transparent, BLAST-like alignment visualizations, combining traditional biological research with AI advancements to elevate protein annotation through embedding-based analysis while ensuring interpretability. Tests using the Virus Orthologous Groups and ViralZone protein databases indicated that the novel soft alignment approach recognized and annotated sequences that both blastp and pooling-based methods, which are commonly used for sequence annotation, failed to detect.ConclusionThe embeddings approach shows the great potential of LLMs for enhancing protein sequence annotation, especially in viral genomics. These findings present a promising avenue for more efficient and accurate protein function inference in molecular biology.

Increasing SAR Imaging Precision for Burden Surface Profile Jointly Using Low-Rank and Sparsity Priors

The synthetic aperture radar (SAR) imaging technique for a frequency-modulated continuous wave (FMCW) has attracted wide attention in the field of burden surface profile measurement. However, the imaging data are virtually under-sampled due to the severely restricted scan time, which prevents the antenna being exposed to high temperatures and heavy dust in the blast furnace (BF) for an extended period. In traditional SAR imaging algorithm research, the insufficient accumulation of scattered energy in reconstructing the burden surface profile leads to lower imaging precision, and the harsh smelting increases the probability of distortion in shape detection. In this study, to address these challenges, a novel rotating SAR imaging algorithm based on the constructed mechanical swing radar system is proposed. This algorithm is inspired by the low-rank property of the sampled signal matrix and the sparsity of burden surface profile images. First, the sparse FMCW signal is modeled, and the position transform matrix, calculated according to the BF dimensions, is embedded into the dictionary matrix. Then, the low-rank and sparsity priors are considered and reformulated as split variables in order to establish a convex optimization problem. Lastly, the augmented Lagrange multiplier (ALM) is employed to solve this problem under double constraints, and the imaging results are obtained using the alternating direction method of multipliers (ADMM). The experimental results demonstrate that, in the subsequent shape detection, the root mean square error (RMSE) is 15.38% lower than the previous algorithm and 15.63% lower under low signal-to-noise (SNR) conditions. In both enclosed and harsh environments, the proposed algorithm is able to achieve higher imaging precision even under high noise. It will be further optimized for speed and reliability, with plans to extend its application to 3D measurements in the future.

Strengthen Financial Risk Prevention and Control Capabilities and Improve the Quality and Efficiency of Financial Supervision

The book Research on the Formation and Prevention of Systemic Risks in the Banking Industry from the Perspective of Platform Finance combines the complex network characteristics of the real banking industry and brings the two relatively independent financial markets of platform finance and banking industry into the same complex network framework. The analysis breaks through the traditional systemic risk research paradigm, fills the shortcomings of traditional economic methods in analyzing the internal structure of the system, provides a new way to study the topological structure characteristics of bank networks, and broadens the perspective of systemic risk research.

The role of linguistic factors in the retention of verbatim information in reading: An eye-tracking study on L1 and L2 German

Abstract We investigated the retention of surface linguistic information during reading using eye-tracking. Departing from a research tradition that examines differences between meaning retention and verbatim memory, we focused on how different linguistic factors affect the retention of surface linguistic information. We examined three grammatical alternations in German that differed in involvement of changes in morpho-syntax and/or information structure, while their propositional meaning is unaffected: voice (active vs. passive), adverb positioning, different realizations of conditional clauses. Single sentences were presented and repeated, either identical or modified according to the grammatical alternation (with controlled interval between them). Results for native (N = 60) and non-native (N = 58) German participants show longer fixation durations for modified versus unmodified sentences when information structural changes are involved (voice, adverb position). In contrast, mere surface grammatical changes without a functional component (conditional clauses) did not lead to different reading behavior. Sensitivity to the manipulation was not influenced by language (L1, L2) or repetition interval. The study provides novel evidence that linguistic factors affect verbatim retention and highlights the importance of eye-tracking as a sensitive measure of implicit memory.

Exploring the ship operation safety indicators of international ports in Taiwan

Port safety plays an important role in port operations. Ship size has become larger and the port environment has rapidly changed in recent years. Ship accidents occur in the port area due to the complex environment in the port area. To improve past decision analysis methods on port operation safety fields and reduce fatalities and financial loss for potential accidents, the novelty of this study is to construct a safety index of ports with the application of the Best Worst Method (BWM). Four dimensions and 14 indicators were summarized based on an intensive literature review. The BWM was implemented to prioritize the weights of dimensions and indicators. Based on 21 expert questionnaires, the results indicate that the ranking of dimensions is ‘human’, ‘ship facilities’, ‘port facilities’, and ‘documentation check’. Regarding the ranking of indicators, the top three are ‘fire-fighting and life-saving equipment’, ‘captain’, and ‘pilot’. Safety improvement strategies (e.g. revising inappropriate operational rules and strengthening human safety education and training) based on these research findings are provided. The merits of this paper are presenting a simpler questionnaire-filling method and overcoming the traditional complicated questionnaire survey process and research limitations (e.g. indicator independence problems in the Analytic Hierarchy Process, and the complexation of filling out a questionnaire in the Analytic Network Process). In addition, the findings can help decision-making for port management authorities, port practitioners, and shipping operators (shipowners) regarding policy implementations of port safety.