Search Results (26)

The increasing complexity and digitization of scientific research require Electronic Laboratory Notebooks (ELNs) that are adaptable, sustainable, and compliant across heterogeneous laboratory environments. In response to the limitations of proprietary, inflexible, and cost-intensive ELN solutions, this study systematically derives comprehensive requirements and proposes a modular solution concept for self-configurable ELNs that is explicitly platform-agnostic and broadly accessible. The methodological approach combines a structured requirements analysis with a modular architectural design, followed by theoretical validation through stepwise implementation walkthroughs on Microsoft SharePoint and Google Workspace. These walkthroughs demonstrate the feasibility of deploying self-configurable ELN modules using widely available low-code/no-code tools and native platform extensibility mechanisms. Based on a rigorous literature-driven analysis, key requirements, including modularity, usability, regulatory compliance, interoperability, scalability, auditability, and cost efficiency, are explicitly mapped to concrete architectural features within the proposed framework. The results show that essential ELN functionalities can, in principle, be realized across diverse digital platforms, enabling researchers and local administrators to independently assemble, configure, and adapt ELNs to their specific operational and regulatory contexts. Beyond technical feasibility, the proposed approach fundamentally democratizes ELN deployment and substantially mitigates vendor lock-in by leveraging existing digital infrastructures. Identified limitations, particularly with respect to advanced workflow orchestration and real-time data integration, delineate clear directions for future development. Overall, this work provides a systematic theoretical validation of a modular, self-configurable ELN concept, establishing it as a robust, scalable, and future-ready foundation for digital laboratory infrastructures. Full article

The Technology-Enhanced Learning (TEL) Marketplace was a joint initiative by the vice rectorate for academic affairs and the vice rectorate for digitization and change management at Graz University of Technology to modernize lectures. As part of this initiative, an exercise course on chemical thermodynamics was redesigned as a learner-centered course and enriched with interactive learning materials designed to promote self-directed learning. The core of the method used to implement this redesign is interactive notebooks created in Wolfram Mathematica to enable students to work through the examples independently, in depth, and irrespective of time, with the required theoretical background integrated into the notebooks. In this paper, we ask the following questions: RQ1: How did students use and accept the interactive notebooks? RQ2: What was the impact of the interactive notebooks and the corresponding course design as perceived by the students? To answer these questions, we conducted a questionnaire-based survey with 45 course students and statistically analyzed the results. Key results for RQ1 show that $93.33\%$ of the participating students reported using the interactive notebooks, and technology acceptance (1 = low TA, 5 = high TA) was high in both the dimensions of perceived usefulness ($m=3.88$) and attitude ($m=4.24$). Regarding RQ2, our key results show that students perceived the notebooks to have a positive impact on their learning experience, especially regarding their self-directed learning. The results of this work are in alignment with observations by lecturers, which showed that this more student-centric course design and the integration of the interactive learning materials made it possible to clarify detailed questions during the independent learning phase, allowing the interactive part of the course to focus on the tactical approaches, solutions, and problems that arose during the calculations, which raised the overall level of content teaching. Full article

Background: Mild cognitive impairment (MCI) is a precursor to dementia, with a prevalence of over 15% among community dwellers, with significant economic and social implications. Despite preserved autonomy in daily living, individuals with MCI face challenges in handling everyday technology and memory-related tasks, necessitating digital interventions, such as digital planning-based technologies to support cognitive functioning. Objective: The aim of this study is to identify and summarize available research literature on available digital planning-based technologies to support memory-related functioning in older adults with MCI. Specifically, this study seeks to (1) document the types and functions of these technologies, (2) report their effectiveness, and (3) identify gaps in the current evidence. Methods: A comprehensive literature search of four databases (Medline, Embase, APA PsycINFO, and CINAHL) was conducted in accordance with Arksey and O’Malley’s scoping review methodological framework from inception to February 6, 2024, without restrictions. Inclusion criteria focused on peer-reviewed studies involving adults aged 50 or older with diagnosed cognitive impairment, specifically using digital planning-based technologies for memory support. Results: From 1854 sources, 8 studies were included. Five categories of digital planning-based technologies were identified: (1) reminders and alarms, (2) electronic calendars, (3) digital memory notebooks, (4) digital visual mapping, and (5) smart-home integration. Several studies reported improved task performance, memory recall, and executive function, with digital memory notebooks and visual mapping software showing greatest impact on functional independence. While interventions were generally well-received, usability challenges and low adherence were common, often linked to technological familiarity and motivation. Conclusions: Digital planning-based technologies show promise in supporting memory-related functioning in older adults with MCI. While studies report positive outcomes, more research is needed to refine these tools, evaluate long-term effects, and ensure integration into daily life. Expanding the evidence base will be key to improving accessibility and effectiveness for this population. Full article

We present a new method for trend analysis that integrates traditional foresight techniques with advanced data processing and artificial intelligence. It addresses the challenge of analyzing large volumes of information while preserving expert insight. The hybrid methodology combines computational analysis with expert validation across four phases: literature review, information systematization, trend identification, and analysis. Tools like Voyant Tools 2.6.18 and NotebookLMare used for semantic and statistical exploration. Among them, we highlight the use of the Defly Compass tool, a natural language processing tool based on semantic projections and developed by our team. The method produces mixed results, including both conceptual conclusions and quantifiable, reproducible outcomes adaptable to diverse contexts. Comparative case studies in agriculture, education, and public health identified key patterns within and across sectors. Cross-domain validation revealed universal trends such as digital infrastructure, data integration, and equity. Designed for accessibility, the method enables small, non-specialized teams to combine computational tools with expert knowledge for strategic decision making in complex environments. Full article

With the rapid advancement of information technology and the increasing maturity of online shopping platforms, cross-border shopping has experienced rapid growth. Online consumer reviews, as an essential part of the online shopping process, have become a vital way for merchants to obtain user feedback and gain insights into market demands. The research employs Python tools (Jupyter Notebook 7.0.8) to analyze the 14,078 pieces of review text data from the top four best-selling products in a certain product category on a certain cross-border e-commerce platform. By applying social network analysis, constructing LDA (Latent Dirichlet Allocation) topic models, and establishing LSTM (Long Short-Term Memory) sentiment classification models, the topics and sentiment distribution of the review set are obtained, and the evolution trends of topics and sentiments are analyzed according to different periods. The research finds that in the overall review set, consumers’ focus is concentrated on five aspects: functional features, quality and cost-effectiveness, usage effectiveness, post-purchase support, and design and assembly. In terms of changes in review sentiments, the negative proportion of the topics of functional features and usage effects is still relatively high. Given the above, this study integrates the 4P and 4C theories to propose strategies for enhancing the marketing capabilities of cross-border e-commerce in the context of digital cross-border operations, providing theoretical and practical marketing insights for cross-border e-commerce enterprises. Full article

Since the late 1990s, Chinese internet publishing has seen a surge in literary production in terms of danmei, which are webnovels that share many of the features of Anglophone fanfiction. Thanks in part to recent live-action adaptations, there has been an influx of new Western and Chinese diaspora readers of danmei. Juxtaposing these bodies of literature in English in particular enables us to examine the complexities of how danmei are newly circulating in the Anglophone world and have become available themselves for transformative work, as readers also write fanfiction based on danmei. This paper offers a comparative reading of the following three such texts, which explore trauma recovery through the arc of romance: Tianya Ke, a danmei novel by Priest; Notebook No. 6 by magdaliny, a novella-length piece of fanfiction based on Marvel characters; and orange_crushed’s Strays, a fanfiction based on the live-action drama that was, in turn, based on Tianya Ke. The space described by Lotman’s semiosphere offers an additional model in which these texts reflect on one another; furthermore, along the porous digital border between fanfiction, danmei in translation, and fan novels based on danmei, readers and writers negotiate and vex contemporary culture. Full article

To ensure and to demonstrate the mechanical integrity of a welded structure, precise ultrasonic testing (UT) is often mandatory. The importance of the link between nondestructive testing (NDT) and the assessment of structural integrity is recalled. However, it is difficult to achieve great efficiency as the welding of thick and heavy structural part produces heterogeneous material. Heterogeneity results from the welding process itself as well as from the material solidification laws. For thick components, several welding passes are deposited, and temperature gradients create material grain elongation and/or size variations. In many cases, the welded material is also anisotropic, this anisotropy being due to the metal used, for example, austenitic stainless steel. At the early stages of ultrasonic testing, this kind of welded material was considered too unpredictable, and thus too difficult to be tested by ultrasounds without possible diagnosis errors and misunderstandings. At the end of the 1990s, an algorithmic solution to predict the material organisation began to be developed using data included in the welding notebook. This algorithm or modelling solution was called MINA. This present work recalls, in a synthetic form, the path followed to create this algorithm combining the use of solidification laws and the knowledge of the order of passes in the case of shielded metal arc welding (SMAW). This work describes and questions the simplifications used to produce a robust algorithm able to give a digital description of the material for wave simulation code. Step by step, advances and demonstrations are described as well as the limitations, and ways to progress are sketched. Recent developments are then explained and discussed for modelling in the case of gas tungsten arc welding (GTAW), in addition to discussions about 3D modelling for the future. The discussion includes alternative ways to represent the welded material and challenges to continue to produce more and more convincing weld material model to qualify and to make use of UT methods. Full article

The digitization of classrooms has enormously changed teaching during the COVID-19 lockdowns. The rapid introduction of tablet classes subsequently raised questions about potential learning outputs, as only a few studies had produced quite contradicting outcomes. Consequently, our study was set up to monitor cognitive learning outcomes of conventional and digital teaching interventions by explicitly paying attention to short- and long-term knowledge retention rates. Both modules covered the very same classroom content in focusing on the curricular content of the forest ecosystem. Subjects were eighth-graders from seven Bavarian secondary schools (analog: n = 74; digital: n = 225). We analyzed the knowledge gained by applying a multiple-choice questionnaire (online, 25 items) in a pre–post-retention design. For the statistical analyses SPSS was used, and a Rasch analysis was based on the ACERQuest software (Version 2.1). The Rasch calibration of the ad hoc knowledge items assured solid scores (Rel = 0.72). Both interventions significantly increased knowledge (analog and digital: p < 0.001; Cohen’s d: d_analog = 0.59, d_digital = 0.42) compared to the pre-test scores. Even after 6–9 weeks, there was no significant drop in the acquired knowledge scores (analog: p = 0.619; digital: p = 0.092) compared to the immediate post-test observed. Furthermore, there was no significant difference between the knowledge levels reached after both interventions. The knowledge scores showed typical learning profiles of earlier studies including its consistency even after several weeks. Since no significant differences appeared for the knowledge gain of both groups, the kind of teaching seemingly does not originate any influence independent of participation in the digital or analog module. The same seems to be valid for notebook entry options. Full article

The development of a portable device created by 3D printing for colorimetric and fluorometric measurements is an efficient tool for analytical applications in situ or in the laboratory presenting a wide field of applications in the environmental and food field. This device uses a light-emitting diode (LED) as radiation source and a webcam as a detector. Digital images obtained by the interaction between the radiation source and the sample were analyzed using a programming language developed in Matlab (Mathworks Inc., Natick, MA, USA), which builds the calibration curves in real-time using the RGB colour model. In addition, the entire system is connected to a notebook which serves as an LED and detector power supply without the need for any additional power source. The proposed device was used for the determination in situ of norfloxacin, allura red, and quinine in water and beverages samples, respectively. For the validation of the developed system, the results obtained were compared with a conventional spectrophotometer and spectrofluorometer respectively with a t-test at a 95% confidence level, which provides satisfactory precision and accuracy values. Full article

Blockchain is a method of recording information that makes it not feasible for the system to be replaced, attacked, or manipulated. A blockchain is equipped with a notebook that copies and processes the various procedures across the network of computers participating in the blockchain. Digital signature algorithm is one of the cryptographic protocols used by the blockchain. In this work, we introduce a new digital signature scheme based on error correcting codes. In the scheme constructed on a [n, k, d]− code over ${𝔽}_q$, which is d ≥ 2t + 1, and the size of the signature length is n − k. The signature verification is based on the bounded distance decoding of the code. Since the verification space is ${{𝔽}_q}^n$, the proposed scheme has an improved performance in terms of working in a wider space. Full article

Deep learning-based algorithms have led to tremendous progress over the last years, but they face a bottleneck as their optimal development highly relies on access to large datasets. To mitigate this limitation, cross-silo federated learning has emerged as a way to train collaborative models among multiple institutions without having to share the raw data used for model training. However, although artificial intelligence experts have the expertise to develop state-of-the-art models and actively share their code through notebook environments, implementing a federated learning system in real-world applications entails significant engineering and deployment efforts. To reduce the complexity of federation setups and bridge the gap between federated learning and notebook users, this paper introduces a solution that leverages the Jupyter environment as part of the federated learning pipeline and simplifies its automation, the Notebook Federator. The feasibility of this approach is then demonstrated with a collaborative model solving a digital pathology image analysis task in which the federated model reaches an accuracy of 0.8633 on the test set, as compared to the centralized configurations for each institution obtaining 0.7881, 0.6514, and 0.8096, respectively. As a fast and reproducible tool, the proposed solution enables the deployment of a cross-country federated environment in only a few minutes. Full article

In recent years, the strategy of co-designing Hardware/Software (HW/SW) systems has been widely adopted to exploit the synergy between both approaches thanks to technological advances that have led to more powerful devices providing an increasingly better cost–benefit trade-off. This paper presents an HW/SW system for the detection of multiple circles in digital images based on a genetic algorithm. It is implemented on an Ultra96-v2 development board, which contains a Xilinx Zynq UltraScale+ MPSoC device and supports a Linux operating system that facilitates application development. The design is powered by developing an interactive computing environment by means of the Jupyter Notebook platform, in which different programming languages coexist. The specific advantages of each of these languages have been used to describe the hardware component that accelerates the evolutionary computation for circle detection (VHDL), to execute SW-HW interaction functions, as well as the pre- and post-processing of the images (ANSI-C) and to code, evaluate, and document the system execution process (Python). As a result, a computationally efficient application was obtained, with high accuracy in the detection of circles in synthetic and real images, and with a high degree of reconfigurability that provides the user with the necessary tools to incorporate it in a specific area of interest. Full article

The purpose of this study is to examine the risks of learning through digital technology and to design the individual and academic responsibilities. We propose answering the following research questions: Are higher education students and their families equipped with digital devices? What strategy do students use in their individual learning? How frequently do they get involved in various added digital activities (gaming, social media communication, surfing the Internet)? What are the risks of excess time spent online? A total of 2210 higher education students from five European countries, Romania, Slovakia, Hungary, Serbia, and Ukraine, participated in the quantitative study, the data being collected by the Center of Higher Education Research and Development at the University of Debrecen, Hungary in 2019. The analysis of the data is based on the advanced statistical test carried out with the SPSS program. The results indicated that most students come from families that possess essential digital devices (smartphone, PC, notebook) with an internet connection, regardless of the country of origin. The students’ learning strategy is mixed: they use the virtual and real environment. More than half of the students declared that they never learn by watching tutorials or listening to audio recordings. Reflecting on themselves, more than a third of them stated that they generally spend too much time online. Daily surfing, gaming, and communicating on social networks are those added activities that significantly multiply their chance of spending too much time in a virtual environment. The binary logistic regression analysis proves that these students have a four times greater chance of developing a concentration crisis. In addition, it is characteristic for there to be a general time management crisis that implicitly contributes to the development of a deadline crisis in learning, and another risk is the duplication of intention to drop out of university. Full article

Polymer gel sensors on 96-well plates were successfully used to detect four different multi-explosives, including 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), nitrite, and perchlorate. The products of reactions between the explosives and the polymer gel sensors were digitally captured, and the images were analyzed by a developed Red–Green–Blue (RGB) analyzer program on a notebook computer. RGB color analysis provided the basic color data of the reaction products for the quantification of the explosives. The results provided good linear range, sensitivity, limit of detection, limit of quantitation, specificity, interference tolerance, and recovery. The method demonstrated great potential to detect explosives by colorimetric analysis of digital images of samples on 96-well plates. It is possible to apply the proposed method for quantitative on-site field screening of multi-explosives. Full article

The requirements imposed on schools and the competencies of teachers change depending on the development of society, and currently their constant growth is considerable. These facts lead to the need to continuously innovate pre-service teacher training, especially with a focus on creating professional digital literacy. The creation of a proposal of an optimal model of pre-service teacher training in the field of teacher trainees’ professional didactic-technological competency development was the subject of the research, which is described in the article. The described research examined the importance of the integration of various kinds of digital didactic tools into pre-service teacher training curricula with regard to the successful performance of the teaching profession. The necessary research data were obtained on the basis of screening the opinions of teacher trainees in Slovakia and the Czech Republic (n = 280). The respondents of the research survey expressed, in terms of various aspects, their opinions on the importance of integrating the issue of working with specified kinds of the given digital means into the curricula of teacher trainees’ study programs. The obtained research data were analysed depending on three segmentation factors of the respondents, which were the nationality of the student (i.e., the COUNTRY of his/her study), the GENDER of the respondent, and the combination of these two factors, i.e., COUNTRY X GENDER. According to the achieved results, there is a need to include or strengthen the teaching of software applications such as ActivInspire, FreeMind, SMART Notebook, Google Docs and, if possible, Prezi and Mindomo, and also a need to emphasize the methodological aspects of the use of these technical means in teaching. Full article