Key Aspects Research Articles

Chasing Deliberation in the Social Science Classroom. A Study of Deliberative Quality in Whole-Class, Small Group, and Pair Discussions

While classroom discussion is often cherished as a cornerstone of effective social science teaching, knowledge on when and where discussions tend to turn deliberative is lacking. To make up for this lack of knowledge, the present study examined classroom discussion in three conditions: a whole-class condition, a small group condition, and a pair condition. The study made use of video observations from a classroom intervention to evaluate how each condition affected the deliberative quality of the discussion process. To this end, 585 student utterances were coded for aspects of deliberation using the Stromer-Galley observation manual. The results showed that both the small group and pair conditions promoted key aspects of deliberation compared to the whole-class condition. The small group condition generated the highest levels of contestation and engagement, whereas the pair condition generated the highest level of equality. While these results suggest that the deliberative quality of classroom discussion might sometimes benefit from the teacher’s absence, more research is needed to determine the circumstances in which this is likely to be the case.

CS=Me: Exploring Factors that Shape Black Women's CS Identity at the Intersections of Race and Gender

Improving equity and inclusion for underrepresented groups in the field of Computer Science (CS) has garnered much attention. In particular, there is a long-standing need for diversity efforts that center on the experiences of Black women, and specific actions to increase their representation—especially given the biases that they often encounter in the field. There is limited research concerning Black women in CS, specifically their conceptions of the field and their overarching CS identity development. More research in this area is especially important given the marginalization that Black women often experience at the intersections of their race and gender. Guided by a combination of critical theoretical lenses, this qualitative study examines Black women's conceptions of what it means to be a computer scientist and the degree to which those conceptions map onto how they see themselves in the field. Moreover, we explore experiences that help to bolster Black women's CS identity. The findings highlight key aspects of what it means to be a computer scientist for the Black women in this study—notably the ability to use computing to make societal contributions. Also, the results accentuate key nuances in the participants’ personal CS identification, particularly as it relates to the resilience required to overcome unique barriers that many Black women encounter when engaging within the field. Moreover, the findings highlight the importance of social support systems to facilitate Black women's CS identity development. Implications for policy and practice within education and industry are discussed.

A New Strategy for the Synthesis of (+)‐Crambescin B Decarboxylate

AbstractCrambescin B decarboxylate is an inhibitor of voltage‐gated sodium channels and a potential biochemical tool. Herein, we report the asymmetric total synthesis of crambescin B decarboxylate using a new synthetic strategy. The key aspects of this new protocol include: 1) the use of an optically pure epoxide, synthesized by the Jacobsen hydrolytic kinetic resolution, as the starting material for guanidino‐aziridine, and 2) the introduction of the THF ring through nucleophilic substitution using an acyl anion equivalent. The synthetic protocol reported herein is nine steps shorter than the previously reported shortest method. We determined the cytotoxicity and protective effects of crambescin B decarboxylate in mouse‐hippocampus‐derived neuronal HT22 cells with an MTS assay. Cell viability was observed to decrease in a concentration‐dependent manner without cell detachment or shrinkage. In addition, crambescin B decarboxylate protected glutamate‐induced cell death.

In the name of interests: A joint consideration of interest development and consequence.

Vocational interests have been an important concept for career decision making and counseling. However, while researchers have separately explored the criterion validity of interest congruence and the formation mechanism of interests, there has been little joint, interactive consideration of the two key aspects of interests. A key issue remains unclear: Could interests with different focal formation mechanisms have different consequences? Drawing on the motivation and vocational literature, this article first explains why it is possible and necessary to differentiate the formation mechanisms of interests in terms of motivational focus (intrinsic, extrinsic-autonomous, and extrinsic-controlled). Then, it formulates how the motivational focus of interests interacts with the performance focus of environments (quality-oriented vs. quantity-oriented) and the value focus of individuals (intrinsic vs. extrinsic satisfaction) in shaping the criterion validity of congruence. By linking what people like with why they like it, the joint interest formation and consequence model (a) delineates the motivational, performance, and value moderators of congruence-criterion links and explains previous results; (b) suggests assessment strategies that can facilitate research and practice related to the joint model and marginalized populations; and (c) provides insights into the flexible use of interests in different scenarios of career selection. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A Machine's ethos? An inquiry into artificial ethos and trust

Every day we trust other individuals as we engage in social interactions in which various desirable outcomes depend on others acting the way we hope, or they have indicated. Trust extends beyond specific individuals, however, as we might trust unknown others – individuals, institutions, corporations, and governments. Some also say that we trust various artifacts, such as machines. But what is the basis of trust, and can we really trust technology? Trust is intimately connected to the notion ethos from the study of rhetoric and human persuasion, which is often used to describe various characteristics of the speaker, the audience, the relationship between the speaker and the audience, and the wider context in which communication and interaction occurs. In this article I explore to what degree machines can be considered to have ethos, and consequently whether ethos is a useful concept for understanding persuasive and credibility-related situations in HMI and by extension key aspects of human-machine trust. This allows us to draw on a long lineage of research from, for example, rhetoric, communication studies, and cognitive and social psychology to better understand the usefulness – or not – of using the notion of trust to describe our relationship with machines.

Enhancing reading and writing instruction in inclusive environments: A meaningful and collaborative approach

n inclusive educational settings, educators often face challenges in effectively allocating time and providing appropriate support for students with disabilities. This research aims to address these challenges by proposing a complementary method that integrates seamlessly with conventional teaching approaches, benefiting both teachers and students in the realm of reading and writing education. The primary objective is to develop a comprehensive design that supports reading and writing instruction within an inclusive environment. The proposed approach adopts a holistic perspective by incorporating classroom walls, cubes, and diverse notebooks into the learning environment. At its core, this approach revolves around two fundamental elements: the utilization of meaningful reading and writing methods and the emphasis on collaborative learning. The study is substantiated by three tiny-research initiatives, providing practical insights into the implementation of inclusive classrooms aligned with the proposed recommendations. This research introduces a holistic design, and through various investigations conducted during its development, addresses key aspects such as the design specifications for the cubes, the functionality of notebooks facilitating interaction between walls and cube surfaces, and strategies for facilitating unhindered reading and writing instruction. The findings contribute to answering crucial questions on considerations for creating an inclusive and effective learning environment for primary reading and writing instruction.

Sign Language Recognition System

Abstract: Sign language serves as a primary mode of communication for the Deaf and hard-of-hearing community. This paper presents a Sign Language Recognition System (SLRS) designed to facilitate seamless communication between individuals proficient in sign language and those who may not share this proficiency. The system employs a multi-faceted approach, integrating computer vision, machine learning, and signal processing techniques to accurately interpret and recognize sign language gestures. The methodology involves data collection from diverse signing styles, preprocessing to enhance data quality, feature extraction capturing key aspects of sign language expressions, and the selection and training of machine learning models. The system aims to represent sign language gestures effectively, providing a foundation for real-time recognition. Integration into hardware or software platforms ensures practical applications in various settings, including education, employment, and public spaces.

Immobilization: the promising technique to protect and increase the efficiency of microorganisms to remove contaminants

AbstractBiodegradation of pollutants is one of the most economical methods for their removal and usually is accompanied by no production of toxic by‐products. In general, this approach is favored over others because it offers reduced expenses and the potential for complete mineralization. In order to enhance the viability and longevity of the bioremediation agents within polluted areas, it becomes necessary to immobilize the cells. Cell immobilization refers to the procedure of confining intact cells to specific areas within a device or material, without compromising their essential biological functions. A wide variety of carriers and approaches have been used for the restriction of various cells. Immobilization techniques, such as microencapsulation, have opened up new possibilities in biotechnology by facilitating the development of artificial organs, cell therapies and drug delivery systems. Researchers have found promising outcomes in various applications through the immobilization of microorganisms. This approach enhances stability, reusability and catalytic efficiency, making immobilization a valuable strategy for biocatalysis, bioremediation and other biotechnological processes. Notably, the use of immobilized microorganisms has led to significant improvements in the removal of pollutants, with some studies achieving 100% efficiency. When comparing the degradation of pollutants between free and immobilized microorganisms over the same time period, the results demonstrated that immobilized microorganisms achieved a removal efficiency >21% more than that of free microbial consortia. The primary objective of this review is to give an overview of the key scientific aspects related to bioremediation of various pollutants using immobilized cells, with a particular focus on the techniques used to entrap the cells. © 2024 Society of Chemical Industry (SCI).

Translational frontiers and clinical opportunities of immunologically-fitted radiotherapy.

Ionising radiations can have a wide range of impacts on tumour-immune interactions, which are being studied with the greatest interest and at an accelerating pace by the medical community. Despite its undeniable immunostimulatory potential, it clearly appears that radiotherapy as it is prescribed and delivered nowadays often alters the host's immunity towards a suboptimal state. This may impair the full recovery of a sustained and efficient anti-tumour immunosurveillance post-treatment. An emerging concept is arising from this awareness and consists in re-considering the way of designing radiation treatment plannings, notably by taking into account the individualised risks of deleterious radio-induced immune alteration that can be deciphered from the planned beam trajectory through lymphocyte-rich organs. In this review, we critically appraise key aspects to consider while planning immunologically-fitted radiotherapy, including the challenges linked to the identification of new dose constraints to immune-rich structures. We also discuss how pharmacological immunomodulation could be advantageously used in combination with radiotherapy to compensate for the radio-induced loss, for example with (i) agonists of interleukin (IL)-2, IL-4, IL-7, IL-9, IL-15 or IL-21, similarly to G-CSF being used for the prophylaxis of severe chemo-induced neutropenia, or with (ii) myeloid-derived suppressive cells (MDSC) blockers.

Методы борьбы с отмыванием средств в транзакциях с цифровым рублем

The article presents a comprehensive analysis of modern methods of combating money laundering in transactions with digital ruble. Given the growing adoption of digital technologies and the increasing role of electronic payments, the need to adapt financial control mechanisms becomes obvious. The article highlights key problematic aspects in the field of security of digital currency transactions and demonstrates actual methods of their solution.

Bridging ethnography and AI: a reciprocal methodology for studying visual political action

ABSTRACT This article proposes a methodological approach to address the analytical challenge of meaningfully studying visual politics in the current abundance of online image data. It proposes a novel methodological process of bridging ethnography and computational methods for analysing visual data in a manner that avoids mixing and blurring the boundaries of the two methods while establishing a continuous interchange between them. The methodological development enables investigating how youth participate through image creation and usage, both online and offline, by outlining repertoires of visual political action. We argue that combining ethnographic research with supervised deep learning-based AI and pre-trained neural networks allows for systematically analysing large image datasets while maintaining interpretative, analytical perspectives and contextual sensitivity. Our results show that the existence of common visual features in images, the re-evaluation of the image categories and the creation of subcategories constitute key aspects for an ethnographically-informed image classification.

Digital perspectives for actor training

This article explores how actor training, and physical actor training especially, can shift fromthe well-established historical norm of live workshop interaction to embrace online possibilities.It briefl y examines some of the contextual issues around institutional approaches to training, includingstudents’ expectations, and charts some digital innovations in the fi eld. It then traces theauthor’s own evolutionary history of publishing using analogue and then digital tools, from drawings,through CD-ROMs and DVDs to online materials. This has culminated in the publicationpre-pandemic, though anticipating subsequent shifts online, of ‘Physical Actor training – an onlineA-Z’ (PATAZ), for Methuen Drama Bloomsbury. PATAZ is introduced as a case study, showing howthe project team developed fi lm material as a means to articulate key aspects of training practice;for example by showing the learning and training process, for presenting voice work and for actors’explorations of space and movement. The article describes how the project’s fi lms were augmentedwith various digital tools, such as on-screen animation and it introduces some of the rangeof approaches in fi lming and editing that were adopted to differentiate each term. It concludesby suggesting that we are only at the beginning of a digital revolution regards actor training,its documentation and analysis and related publishing practices.

Analysis of Integrated Coastal Management (ICM) of Panama

The following document addresses the current situation of coastal management in Panama, using the “Decalogue” proposed by Barragán (2001 and 2004) as a framework to assess coastal management. This Decalogue encompasses key aspects such as policy, regulations, competencies, institutions, tools, training and education, resources, knowledge and information, sustainability education, and participation. Prior to the implementation of Panama’s National Ocean Policy in 2022, challenges were observed in these aspects, including overfishing, coastal degradation, threats to biodiversity, marine pollution, and other issues. Adherence to international agreements and the enactment of policies like the National Ocean Policy have strengthened regulations and promoted participation and knowledge generation in coastal management. As Panama strives to achieve its goals of marine conservation and sustainable development, increased training and education are anticipated, along with a focus on ocean culture and collaboration among entities and stakeholders. Keywords: Coastal management, National Ocean Policy, ICZM Decalogue, Panama, coastal sustainability, marine conservation.

Leveraging Artificial Intelligence for Expediting Implementation Efforts.

Expedited implementation of evidence into practice and policymaking is critical to ensure the delivery of effective care and improve health-care outcomes. Implementation science deals with the designing of methods and strategies for increasing and facilitating the uptake of evidence into practice and policymaking. Nevertheless, the process of designing and selecting methods and strategies for implementing evidence is complicated because of the complexity of health-care settings where implementation is desired. Artificial intelligence (AI) has revolutionized a range of fields, including genomics, education, drug trials, research, and health care. This commentary discusses how AI can be leveraged to expedite implementation science efforts for transforming health-care practice. Four key aspects of AI use in implementation science are highlighted: (a) AI for implementation planning (e.g., needs assessment, predictive analytics, and data management), (b) AI for developing implementation tools and guidelines, (c) AI for designing and applying implementation strategies, and (d) AI for monitoring and evaluating implementation outcomes. Use of AI along the implementation continuum from planning to delivery and evaluation can enable more precise and accurate implementation of evidence into practice.

Breaking Global Diatropic Current to Tame Diradicaloid Character: Thiele's Hydrocarbon Under Macrocyclic Constraints

AbstractA diradical/biradical character of organic derivatives is one of the key aspects of contemporary research focusing on the fundamental studies followed by potential applicability relying on the unique optical, electronic, or magnetic properties assigned to unpaired electrons. A precise involvement of two p‐phenylenes into a cyclophane‐like conjugated, diatropic system creates a flexible molecule with the two different characters of both subunits (benzene and quinone) imprinting into the structure a Kekulé delocalized system. A dynamic of both carbocyclic subunits, and their mutual interaction generates a singlet open‐shell state (J=−1.25 kcal/mol) as documented spectroscopically (NMR and EPR). The extended theoretical analysis has proved a correlation between dihedral angle and the diradicaloid character that shifts from a closed‐shell singlet to an open‐shell state, eventually showing the y0=0.86 for 78 degrees and ΔEST=−0.34 kcal/mol.

Breaking Global Diatropic Current to Tame Diradicaloid Character: Thiele's Hydrocarbon Under Macrocyclic Constraints.

A diradical/biradical character of organic derivatives is one of the key aspects of contemporary research focusing on the fundamental studies followed by potential applicability relying on the unique optical, electronic, or magnetic properties assigned to unpaired electrons. A precise involvement of two p-phenylenes into a cyclophane-like conjugated, diatropic system creates a flexible molecule with the two different characters of both subunits (benzene and quinone) imprinting into the structure a Kekulé delocalized system. A dynamic of both carbocyclic subunits, and their mutual interaction generates a singlet open-shell state (J=-1.25 kcal/mol) as documented spectroscopically (NMR and EPR). The extended theoretical analysis has proved a correlation between dihedral angle and the diradicaloid character that shifts from a closed-shell singlet to an open-shell state, eventually showing the y0=0.86 for 78 degrees and ΔEST=-0.34 kcal/mol.

Mechanism and Kinetics Guided Design of Catalysts for Functionalized Nitroarenes Hydrogenation

AbstractSelective hydrogenation of functionalized nitroarenes to anilines employed with heterogeneous catalysts is a significant process and widely applied in chemical industry. However, designing high‐performance catalysts for these processes remains challenging. Recently, notable advancements have been achieved in synthesis methodologies, characterization techniques, and theoretical calculations, offering opportunities to gain insights into mechanisms. This review summarizes the recent progress in understanding the mechanistic aspects of selective hydrogenation catalysis for functionalized nitroarenes. We initiate by delving into the structure‐performance relationship, with the aim of providing a comprehensive understanding of mechanistic and kinetic details in the selective hydrogenation of functionalized nitroarenes. Subsequently, we introduce various strategies for designing high‐performance catalysts, categorizing them into three key aspects: isolating active sites, synergizing active sites and regulating local environments of active sites. Finally, we conclude with a concise overview of the current state of this field and provide a forward‐looking perspective for future studies, emphasizing the high‐performance design and manipulation of catalysts to achieve precise control over selectivity towards target products.

Analysis of Digital Teacher Education: Key Aspects for Bridging the Digital Divide and Improving the Teaching–Learning Process

The quality of teacher education plays a key role in equipping students with the skills they need and it is important in avoiding learning inequalities. To bridge the digital divide and ensure that all students have equal access to technology and digital resources as well as advanced teaching–learning processes using digital tools, it is crucial to analyse the current state of teacher education in order to identify the key issues. The sample in this research consisted of 325 master of education students and in-service teachers studying at various universities (in Spain, Cyprus, and México) in the 2022–2023 academic year who filled out a questionnaire partly based on DigComEdu and this was expanded with questions relating to other digital and educational aspects. The findings reveal that there is potential for enhancement in many areas. Despite teachers having technical training associated with their profession, they lack the necessary training to overcome inequalities or digital gaps. Moreover, it is striking that those who are already working as teachers are the most pessimistic about aspects such as the use of digital resources, perhaps because of the difficulties they face in their daily work.

ChatGPT Conversations on Oral Cancer: Unveiling ChatGPT's Potential and Pitfalls

BackgroundThe present research investigates the application of Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence (AI)-based language processing model that utilize deep learning programs, in responding to various questions related to oral cancer. Materials and methodsA dataset of 25 questions on oral cancer was compiled from diverse sources and categorized into five groups based on key aspects of the disease. ChatGPT version 3.5 was used through a structured approach of submitting questions individually for evaluation. Two experienced oral cancer surgeons independently assessed response accuracy and reproducibility using a grading scale. ResultsChatGPT demonstrated an overall accuracy rate of 80%, providing “comprehensive/correct" responses for 20 questions. No instances of mixed or misleading responses were observed. The highest accuracy was recorded in questions related to basic knowledge on oral cancer and oral cancer prevention, while questions on oral cancer treatment and post-operative aspects showed a mix of “comprehensive/correct" and “incomplete/partially correct" responses. There were no significant differences in response grades between question categories. ConclusionDespite intrinsic constraints and the potential impact of the freely accessible version used, ChatGPT shows promise as a valuable information source for oral cancer-related queries. Caution is advised in relying solely on ChatGPT for the most current and reliable medical information, emphasizing the need for continuing refinements for its widespread use.

Fabrication and Characterization of Quad-Component Bioinspired Hydrogels to Model Elevated Fibrin Levels in Central Nervous Tissue Scaffolds.

Multicomponent interpenetrating polymer network (mIPN) hydrogels are promising tissue-engineering scaffolds that could closely resemble key characteristics of native tissues. The mechanical and biochemical properties of mIPNs can be finely controlled to mimic key features of target cellular microenvironments, regulating cell-matrix interactions. In this work, we fabricated hydrogels made of collagen type I (Col I), fibrin, hyaluronic acid (HA), and poly (ethylene glycol) diacrylate (PEGDA) using a network-by-network fabrication approach. With these mIPNs, we aimed to develop a biomaterial platform that supports the in vitro culture of human astrocytes and potentially serves to assess the effects of the abnormal deposition of fibrin in cortex tissue and simulate key aspects in the progression of neuroinflammation typically found in human pathologies such as Alzheimer's disease (AD), Parkinson's disease (PD), and tissue trauma. Our resulting hydrogels closely resembled the complex modulus of AD human brain cortex tissue (~7.35 kPa), promoting cell spreading while allowing for the modulation of fibrin and hyaluronic acid levels. The individual networks and their microarchitecture were evaluated using confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). Human astrocytes were encapsulated in mIPNs, and negligible cytotoxicity was observed 24 h after the cell encapsulation.