Essential Concepts Research Articles

Molecular Engineering and Microstructure Modulation of High‐Performance Organic Batteries

Organic electrode materials (OEMs) featuring high abundance, structural designability, and eco‐friendliness, are considered promising candidates for rechargeable metal‐ion batteries. Nevertheless, the realization of efficient metal‐ion batteries based on OEMs is plagued by the poor intrinsic electronic conductivity and low insolubility of OEMs in common organic electrolytes. Herein, we present a systematic discussion of advancements in the design of OEMs from the perspective of molecular engineering and microstructure modulation, aiming at tuning the electrochemical, physical, and chemical properties of OEMs. Additionally, we elucidate the reaction mechanism of regulation strategies and provide new design directions for OEMs. This review offers essential concepts and perspectives on the development of advanced OEMs for rechargeable batteries.

Interferenzen und Überschreitungen von Literatur und Welterbediskurs am Beispiel von Judith Schalanskys Verzeichnis einiger Verluste (2018)

The present article looks at how the contemporary discourses concerning cultural and natural heritage are literarily reworked in Judith Schalansky’s book An Inventory of Losses (Verzeichnis einiger Verluste, 2018). Schalansky’s hybrid book which consists of twelve micro-narratives around natural and art objects that have been destroyed or lost over the course of time partakes in the cultural discourse on preservation, memory and intergenerational dialogue, contributing its own views on the practices of valuation of old artefacts and knowledge. The present paper focuses on the common aspects – first of all the intertwining of nature and culture – and the key differences – such as the critique on the essentialist concept of sustainability – between Schalansky’s book and the preservation discourse as it is articulated in collective texts such as the World Heritage Convention.

From Software Management to Software Ecosystem Governance: A Bibliographic Review on Software Governance Practices Within Organizations and Their Evolution

Objective: The objective of this study is to map the publications that deal with IT Governance and the main aspects of Software development, acquisition and maintenance, identifying when the concepts related to software governance emerged and the main search sources for publications on the subject, highlighting the central issues of each of the emerging contexts. Theoretical Framework: A theoretical framework was used on the organizational structure of IT governance areas, focused on directing, analyzing and monitoring software development, differentiating the typical management activities designed by Juiz and Colomo-Palacios (2020). Method: The methodology adopted for this research comprises a qualitative-quantitative approach, using bibliometrics, bibliographic analysis and the application of a fractional authorship algorithm to identify the main authors to publish on the topic. Data collection was done using a set of search databases such as the Web of Science database and the Scopus database. Results and Discussion: The results obtained revealed the main authors identified in each of the databases searched, as well as the central themes of the searched themes, indicating the first appearance of each term and its main article. It is also possible to analyze the academic production related to each of these themes. Research Implications: The practical and theoretical implications of this research indicate fields of research that have become popular, bringing perspectives for future work, as well as fields that are being poorly explored in software development governance and management. Originality/Value: This study contributes to the area of ​​Information Technology management as the main themes studied in governance and management of software development formalize essential concepts for these fields of research and promote process improvement.

Machine Learning Approaches in Advancing Perovskite Solar Cells Research

AbstractThe integration of machine learning (ML) with perovskite solar cells (PSCs) signifies a groundbreaking era in photovoltaic (PV) technology. The traditional iterative approaches in PSC research are often time‐consuming and resource‐intensive. In contrast, ML leverages available data and sophisticated algorithms to quickly identify properties and optimize parameters for novel materials and devices. This review explores how ML‐driven approaches are improving various facets of PSCs research, including the rapid screening of novel compositions, enhancing stability, refining device architectures, and deepening the understanding of underlying physics. The paper is structured to gradually familiarize readers with essential terminologies and concepts, ensuring a solid foundation before delving into more intricate topics. A concise workflow and various introductory toolkits for ML are also briefly discussed. Through a detailed analysis of compelling case studies, a basic research framework within ML‐PSC‐integrated research is provided. This comprehensive review can serve as a valuable reference for researchers aiming to understand and leverage ML‐driven approaches in PSCs research, advancing the path for more efficient and sustainable PV technologies.

Metacognitive training for algebra teaching to high school students: An action research study

Metacognition is an essential concept in mathematics education research. Studies indicate that high school students in Turkey must demonstrate expected success in learning mathematics in general and algebra in particular. To this end, the Ministry of National Education has initiated a mathematical mobilization in Turkey. Mathematics mobilization is a project that will adapt the learning of mathematics to daily life skills, making learning more accessible and ensuring that students love this course from an early age. In the initial interviews with teachers as part of this mobilization, teachers stated that high school students needed to exhibit sufficient metacognitive planning and monitoring strategies. Therefore, they required assistance in planning and monitoring their learning processes and motivating them to learn. The literature shows that metacognitive planning and monitoring are effective in teaching algebra. In this context, the research “How can metacognitive strategies be developed in high school students’ algebra learning?” seeks an answer to this problem. Based on preliminary teacher interviews, the researchers created action plans in collaboration with teachers. In the circular model, researchers tested these action plans and revised them. As a result of the cycle being repeated three times, researchers developed a teaching technique based on metacognitive planning and monitoring for high school students. The study’s findings demonstrate that metacognitive training taught students metacognitive planning, monitoring, prediction, awareness, and motivation strategies.

Literature Review: Analysis of the Relationship between Employer Branding, Employee Engagement, and Employee Retention

Employer branding is an essential concept that significantly influences employees' perceptions and experiences within an organization, ultimately affecting employee retention and engagement. This research aims to explore the importance of employer branding by employing a Systematic Literature Review (SLR) methodology, analyzing a diverse range of academic sources from reputable databases, including Scopus, Emerald, and Google Scholar. The inclusion criteria focused on open-access journals published in both English and Indonesian, ensuring a comprehensive understanding of the topic. The findings indicate a strong correlation between effective employer branding and increased employee retention rates. Employees are more likely to remain with organizations that present a positive brand image, showcasing a strong cultural identity and aligning with their values. Furthermore, the study highlights the significance of emotional factors, particularly employee engagement, in influencing retention. Engaged employees tend to be more productive and committed to their work, fostering a sense of belonging and loyalty to the organization. These insights underscore the necessity for companies to invest in employer branding strategies, as a well-defined employer brand not only attracts top talent but also retains valuable employees. By prioritizing employer branding, organizations can enhance workforce stability and overall performance, ultimately leading to a more motivated and dedicated workforce that drives success.

Development of a Virtual Pediatric Holistic Comfort Care Clinic.

Guided by the tenets of Kolcaba's holistic comfort theory, we developed, implemented, and evaluated a simulated online pediatric advanced practice health center. The Pediatric Comfy Care Clinic (PCCC) was created to enhance person-centered diagnostic reasoning and holistic advanced management skills for family nurse practitioner students. Our interprofessional team used a standardized approach to online design and development while integrating essential holistic comfort theory concepts for student engagement and assessment of learning. We explored outcomes of pre- and postclinic quizzes and student reflection data using mixed methods. Significant differences (P<.001) were noted in all postpractice quizzes in each affiliated PCCC module with variable student outcomes on graded clinic encounters. Important student perspectives on teaching and learning in the virtual clinic were noted. A comfort theory-driven, simulated, and digitally enhanced virtual clinic is feasible and valuable with important implications for holistic advanced practice.

A Study of Bases, Continuity and Homeomorphism in Hausdorff Topology

This paper surveys the essential concepts of bases, continuity, and homeomorphism within the context of Hausdorff topology. We examine the characterization of Hausdorff spaces through various types of bases, including minimal generative bases, which serve to illuminate the intrinsic properties of these spaces. The interplay between bases and morphisms is explored, emphasizing how morphisms facilitate continuity of mappings between Hausdorff spaces and their quotient images. We investigate the implications of these relationships for determining homeomorphisms, establishing conditions under which two Hausdorff spaces can be deemed equivalent. Key results include the construction of quotient images using equivalence relations, as well as criteria for continuity and homeomorphism that are uniquely suited to Hausdorff spaces. The findings on bases also demonstrate that a topological space X is Hausdorff if and only if there exists a minimal generative base BM for X such that for any Subfamily B′M of BM that is also a base for X, every element of BM can be expressed as a union of elements from B′M . This result provides an important tool for studying the properties of Hausdorff spaces and their relationships with other topological spaces.

Bringing brain into the game: introducing the brain-based view of dynamic capabilities

Purpose Change lies at the heart of the dynamic capability theory; however, the essence of concept of change is antithetical to the brain's predominant mode of operation i.e. maintenance of internal homeostasis. Since very little is known about the connection between neurology and dynamic capabilities, the present study aims to open this black box and propose a novel brain-based view of developing dynamic capabilities. Design/methodology/approach This study draws on the insights from neuroscience to offer propositions that not only provide realistic approaches for building dynamic capabilities, but also explain what would cause the brain to enter a state of plasticity to facilitate the development of managerial dynamic capabilities. Findings This study explains that dynamic capabilities are shaped by both lower-level neural processes and higher-level organizational processes, and that both these levels must be brought together to provide a holistic explanation about the complex phenomena of dynamic capabilities. Originality/value This study proposes a novel brain-based view of dynamic capabilities that provides neuroscientific explanations regarding how managerial capabilities can be leveraged to form organization-level capabilities without holding a priori assumptions about the application of the aggregation principle.

Student Uncertainty as a Pedagogical Resource (SUPeR): an approach for phenomena-based science teaching

This paper presents a phenomenon-based teaching approach, termed Student Uncertainty as Pedagogical Resource (SUPeR), designed to help teachers create classroom lessons that leverage the inherent students’ scientific uncertainties within various phenomena. We outline three types of phenomena, each serving distinct roles in engaging students with essential scientific concepts and practices: anchoring phenomena provide a foundational context, investigative phenomena drive inquiry, and assessment phenomena evaluate understanding. In tandem with these phenomena, the SUPeR approach introduces three categories of scientific uncertainty: conceptual, procedural, and epistemic. The approach is implemented in four phases: (1) problematizing a phenomenon, (2) investigating through material practice, (3) participating in argumentative practice, and (4) engaging in reflection, transformation, and application. To demonstrate the practical application of the SUPeR teaching approach, we describe a seventh-grade, two-week project focused on understanding how light and heat affect the electrical output of a solar panel. The SUPeR approach equips teachers to weave different types of phenomena throughout the inquiry process, creating a unified and engaging narrative in their lessons. Most importantly, it emphasizes that students’ scientific uncertainties should be harnessed as a key pedagogical resource to guide and enrich the learning process.

“I Was in No Mood for People Who Tried to Lay Claims on Me”: Community, Hospitality, and Friendship in Teju Cole’s Open City

This article examines community, friendship, and hospitality in Teju Cole’s novel Open City, drawing on Nancy’s The Inoperative Community, Blanchot’s The Unavowable Community, and Derrida’s The Politics of Friendship and Of Hospitality. I aim to show how the representation of migratory experiences in this novel revolves around the contrast between operative communities based on immanence, fusion, and essentialist concepts such as race and ethnicity, and inoperative and elective communities characterized by openness and exposure to alterity. I examine how friendship and hospitality prove to be the necessary force in the novel to transform New York and Brussels into truly “open cities” hospitable to people of different races.

Prediction of electron-solid interaction parameters using machine learning.

Electron backscattering coefficient and electron-stopping power are essential concepts in many disciplines, from radiation to materials science, semiconductor manufacturing, and space exploration. They enable precise calculations, measurements, and simulations of electron interactions with matter, which contribute to advancing science, technology, and safety in a variety of applications. The availability of these data is fundamental to scientific research to validate hypotheses, conduct experiments, and explore new theories. A relatively novel machine learning approach has demonstrated notable success in enhancing data quality and completeness, significantly contributing to the facilitation of data discovery. Using fundamental material property data, the stacking ensemble machine learning (EML) technique was established in this study to generate electron-solid interaction parameters for any target material over a wide range of energies. The final stacking EML was built using the base and meta learners bagging regressor (BR), K-nearest neighbors (k-NN), random forest (RF), support vector regression (SVR), and eXtreme Gradient Boosting (XGB). In this study, two publicly available databases with a total of 4030 data points were used. Training datasets have 785 and 525 data points for electron backscattering coefficient and stopping power, respectively, whereas testing datasets contain 262 and 175 data points. Fivefeatures were used as input variables to train different individual algorithms and their combinations. On both the training and test datasets, the model was evaluated using different error metrics, including R-squared (R2), mean-absolute-error (MAE), root-mean-squared-error (RMSE), and mean-absolute-percentage-error (MAPE). Our model evaluation tests revealed that combining RF and XGB with a k-NN meta-learner outperformed other algorithms. The analysis of error metrics demonstrated a very close fit to all samples in each training dataset. Furthermore, predictions made by the model on unseen test data indicated accurate estimations of new backscattering and stopping power data. The developed model achieved high prediction accuracy for various target materials across the broad electron energy spectrum. The outcomes demonstrate the effectiveness of machine learning methodology and the chosen models' suitability for addressing substantial physics challenges.

Deep Learning in Hematology: From Molecules to Patients.

Deep learning (DL), a subfield of machine learning, has made remarkable strides across various aspects of medicine. This review examines DL's applications in hematology, spanning from molecular insights to patient care. The review begins by providing a straightforward introduction to the basics of DL tailored for those without prior knowledge, touching on essential concepts, principal architectures, and prevalent training methods. It then discusses the applications of DL in hematology, concentrating on elucidating the models' architecture, their applications, performance metrics, and inherent limitations. For example, at the molecular level, DL has improved the analysis of multi-omics data and protein structure prediction. For cells and tissues, DL enables the automation of cytomorphology analysis, interpretation of flow cytometry data, and diagnosis from whole slide images. At the patient level, DL's utility extends to analyzing curated clinical data, electronic health records, and clinical notes through large language models. While DL has shown promising results in various hematology applications, challenges remain in model generalizability and explainability. Moreover, the integration of novel DL architectures into hematology has been relatively slow in comparison to that in other medical fields.

Formalising the Double-Pushout Approach to Graph Transformation

In this paper, we utilize Isabelle/HOL to develop a formal framework for the basic theory of double-pushout graph transformation. Our work includes defining essential concepts like graphs, morphisms, pushouts, and pullbacks, and demonstrating their properties. We establish the uniqueness of derivations, drawing upon Rosens 1975 research, and verify the Church-Rosser theorem using Ehrigs and Kreowskis 1976 proof, thereby demonstrating the effectiveness of our formalisation approach. The paper details our methodology in employing Isabelle/HOL, including key design decisions that shaped the current iteration. We explore the technical complexities involved in applying higher-order logic, aiming to give readers an insightful perspective into the engaging aspects of working with an Interactive Theorem Prover. This work emphasizes the increasing importance of formal verification tools in clarifying complex mathematical concepts.

THE RELATIONSHIP BETWEEN TOURIST EXPERIENCE, PLACE ATTACHMENT, AND POST-VISIT INTENTIONS: AN APPLICATION OF S-O-R PARADIGM IN THE CONTEXT OF HANGZHOU, CHINA

A key challenge facing destination practitioners and policymakers is to sustain a competitive advantage and to ensure its destination’s success and prosperity under the impact of globalisation. Evidence suggests that the tourist experience can enhance tourists’ attachment and post-visit intention, which is an essential concept in travel and tourism study, as well as destination positioning. Still, there are limitations in the research concerning the relationship between these three factors. This study investigates the mediating effect of place attachment on the relationship between tourist experience and post-visit intention using Stimulus–Organism–Response (S-O-R) paradigm. The data were gathered from 213 respondents among the West Lake Heritage Site users in Hangzhou, China, using the self-administered questionnaires. According to statistical findings, tourist experience influences post-visit intention both directly and indirectly through the mediating role of place attachment. Drawing from these findings, practical information on design, marketing, and experiences for tourism destinations is offered.

Essential instructional communication concepts for effective health campaigns

Essential instructional communication concepts for effective health campaigns

Conceptual images and learning obstacles in exponentiation and logarithms: A hermeneutic phenomenological analysis

The concept of exponentials and logarithms is one of the essential concepts in mathematics as part of transcendent functions. However, students' understanding of these two concepts has yet to be fully mastered, so there are still errors in solving problems related to these two concepts. This study aims to describe the meaning and meaning process and explore the potential learning obstacles of students based on the meaning and experience of students in obtaining the meaning of exponents and logarithms in senior high school. This qualitative study uses a hermeneutic phenomenological approach with student participants and high school mathematics teachers. Data was collected using tests, documentation, and interviews with students and teachers. Data were analyzed qualitatively to identify learning obstacles and the meaning of exponentials and logarithms. The results showed the meaning of exponents and logarithms according to students, namely exponents as power numbers and logarithms as the opposite of power numbers. In addition, the results also show the existence of learning obstacles in students, both ontogenic, epistemological, and didactic. Based on the findings, these learning obstacles can be considered when developing an appropriate didactic design.

Fast generation of high-dimensional spatial extremes

Widespread extreme climate events cause many fatalities, economic losses and have a huge impact on critical infrastructure. It is therefore of utmost importance to estimate the frequency and associated consequences of spatially concurrent extremes. Impact studies of climate extremes are severely hampered by the lack of extreme observations, and even large ensembles of climate simulations often do not include enough extreme or record-breaking climate events for robust analysis. On the other hand, weather generators specifically fitted to extreme observations can quickly generate many physically or statistically plausible extreme events, even with intensities that have never been observed before. We propose a Fourier-based algorithm for generating high-resolution synthetic datasets of rare events, using essential concepts of classical modelling of (spatial) extremes. Here, the key feature is that the stochastically generated datasets have the same spatial dependence as the observed extreme events. Using high-resolution gridded precipitation and temperature datasets, we show that the new algorithm produces realistic spatial patterns, and is particularly attractive compared to other existing methods for spatial extremes. It is exceptionally fast, easy to implement, scalable to high dimensions and, in principle, applicable for any spatial resolution. We generated datasets with 10000 gridpoints, a number that can be increased without difficulty. Since current impact models often require high-resolution climate inputs, the new algorithm is particularly useful for improved impact and vulnerability assessment.

TEACHER’S INNOVATION IN TEACHING LINGUISTIC KNOWLEDGE: EXPLORING STUDENTS’ REFLECTIONS IN LEARNING EFL WITH TECHNOLOGY

The foundation of competence for English teachers in the EFL context, as well as for any language teacher, lies in linguistic knowledge (Chang &amp; Kanno, 2010; Kemaloglu-Er, 2017; Marfui, 2016; Medgyes, 1992). However, due to English being a foreign language in Indonesia, teachers who work with EFL learners require innovative strategies to achieve teaching goals and fulfill the profile of future EFL teachers (Chun et al., 2016; Hoopingarner, 2009; Kern, 2006; Kessler, 2018; Köksal, 2004; Salaberry, 2001). This study aims to explore EFL students' reflections on their experience of learning Linguistics with technology and its impact on their linguistic knowledge, which is valuable for their future. A total of 156 prospective teacher students participated in the study. They provided reflections on the learning process for Phonetics and Phonology courses at the end of the semester, using the Three What’s reflection writing concept guide: What, So What, Now What (Borton, 1969; Rolfe, 2014). Based on the reflection results, linguistic competence is acquired through a systematic learning process, both offline and online, which incorporates various technology-based learning resources (such as Google Classroom, Quizizz, YouTube, Padlet, etc.), with relevant linguistic content. The use of technology as a teaching strategy to aid student comprehension represents an innovation in language learning, as students become more creative in discussing and creating projects related to the course. Furthermore, they continue to utilize the technology they have experienced in other learning activities. By incorporating technology into the process of understanding essential linguistic concepts, teachers can model the target language being taught, demonstrating that teacher innovation is an integral part of professionalism and contributes to the improvement of learning continuity. In line with this notion of sustainability, it is recommended that further research be conducted to investigate the effectiveness of using technology in assisting and motivating students in assessment as learning, assessment for learning, and assessment of learning.

The Therapeutic Use of Self: A Concept Analysis

Background: The therapeutic use of self is an essential concept in nursing, involving the intentional use of personal qualities, emotional intelligence, and interpersonal skills to promote healing and improve patient outcomes.Objective: This study aims to conduct a comprehensive concept analysis of the therapeutic use of self, identifying its defining attributes, antecedents, consequences, and empirical referents in nursing practice.Methods: Using Walker and Avant's eight-step concept analysis methodology, we systematically reviewed existing literature. Data were collected from databases such as PubMed, Google Scholar, and Sci-Hub. Key defining attributes, antecedents, consequences, and empirical referents were identified and analyzed. The data were synthesized to present both qualitative and quantitative insights. The analysis included five main attributes: interpersonal skills, use of self, emotional intelligence, empathy, and self-disclosure. Additionally, we reviewed empirical referents for measuring this concept’s practical efficacy.Results: The analysis revealed that integrating therapeutic use of self in nursing significantly enhances patient satisfaction by 40%, improves nurse-patient communication by 35%, and reduces nurse burnout by 25%. Moreover, the concept's impact on patient outcomes was positively correlated with the presence of empathy and emotional intelligence.Conclusion: The therapeutic use of self is a critical factor in improving patient-centered care and reducing nurse burnout. Incorporating it into nursing education and practice will likely yield better patient outcomes and healthcare delivery.