Cross-disciplinary Efforts Research Articles

Photoactivated Chromophore for Keratitis-Corneal Cross-linking (PACK-CXL)-A Scoping Review Based on Preclinical Studies.

Photoactivated chromophore for keratitis-corneal cross-linking (PACK-CXL) stabilizes the corneal stroma and eliminates microorganisms. Numerous PACK-CXL protocols, using different energy sources and chromophores, have been applied in preclinical studies, including live animal studies, with various experimental designs and endpoints. So far, a systematic mapping of the applied protocols and consistency across studies seems lacking but is essential to guide future research. The scoping review protocol was in line with the JBI Manual for Evidence Synthesis. Electronic databases were searched (Embase, MEDLINE, Scopus, Web of Science) to identify eligible records, followed by a two-step selection process (title and abstract screening, full text screening) for record inclusion. We extracted information on (1) different PACK-CXL protocol characteristics; (2) infectious pathogens tested; (3) study designs and experimental settings; and (4) endpoints used to determine antimicrobial and tissue stabilizing effects. The information was charted in frequency maps. The searches yielded 3654 unique records, 233 of which met the inclusion criteria. With 103 heterogeneous endpoints, the researchers investigated a wide range of PACK-CXL protocols. The tested microorganisms reflected pathogens commonly associated with infectious keratitis. Bacterial solutions and infectious keratitis rabbit models were the most widely used models to study the antimicrobial effects of PACK-CXL. If preclinical PACK-CXL studies are to guide future translational research, further cross-disciplinary efforts are needed to establish, promote, and facilitate acceptance of common endpoints relevant to PACK-CXL. Systematic mapping of PACK-CXL protocols in preclinical studies guides future translational research.

Leveraging co-production within ecosystem restoration to maximize benefits to coastal birds

Coastal Louisiana's ecosystems are threatened by anthropogenic factors exacerbated by climate change induced sea-level rise. The 2010 Deepwater Horizon oil spill resulted in injuries and deaths to coastal birds in Louisiana, and the ongoing loss of habitat has limited the potential for successful nesting of resident birds throughout the coast. Habitat loss is being addressed through increased large-scale ecosystem restoration as a result of settlement funds from the Deepwater Horizon oil spill. To further inform bird restoration in Louisiana, an avian restoration guidance document (Guidance for Coastal Ecosystem Restoration and Monitoring to Create or Improve Bird-NestingHabitat, 2023) was developed to maximize restoration benefits for coastal breeding birds while also achieving broader habitat restoration objectives. The developed restoration guidance was co-produced by subject-matter experts and professionals, including avian experts, engineers, and coastal restoration project managers. The result of this cross-disciplinary effort was specific and targeted guidance that presents designable habitat features that are in the control of project engineers and are also important high-value bird nesting habitats (e.g., shoreline access, elevation heterogeneity and edge habitat). For the first time in Louisiana, defined nest-site characteristics and monitoring approaches are readily available to inform ecosystem restoration project implementation. The restoration document specifically emphasizes bird species that breed and nest in coastal habitats in Louisiana, and restoration managers can use these guidelines to explicitly incorporate bird nesting habitat features into coastal restoration planning, design, and implementation. In developing this guidance, many knowledge gaps and data needs were identified specific to engineering and project design, enabling the research community to frame research questions around specific coastal restoration questions. The co-production of science model applied here for avian resources is applicable to a wide range of other living marine resources that may benefit from large-scale ecosystem restoration and is an example of the benefits of working relationships, communications, and common goal setting.

Fairness, AI & recruitment

The ever-increasing adoption of AI technologies in the hiring landscape to enhance human resources efficiency raises questions about algorithmic decision-making's implications in employment, especially for job applicants, including those at higher risk of social discrimination. Among other concepts, such as transparency and accountability, fairness has become crucial in AI recruitment debates due to the potential reproduction of bias and discrimination that can disproportionately affect certain vulnerable groups. However, the ideals and ambitions of fairness may signify different meanings to various stakeholders. Conceptualizing fairness is critical because it may provide a clear benchmark for evaluating and mitigating biases, ensuring that AI systems do not perpetuate existing imbalances and promote, in this case, equitable opportunities for all candidates in the job market. To this end, in this article, we conduct a scoping literature review on fairness in AI applications for recruitment and selection purposes, with special emphasis on its definition, categorization, and practical implementation. We start by explaining how AI applications have been increasingly used in the hiring process, especially to increase the efficiency of the HR team. We then move to the limitations of this technological innovation, which is known to be at high risk of privacy violations and social discrimination. Against this backdrop, we focus on defining and operationalizing fairness in AI applications for recruitment and selection purposes through cross-disciplinary lenses. Although the applicable legal frameworks and some research currently address the issue piecemeal, we observe and welcome the emergence of some cross-disciplinary efforts aimed at tackling this multifaceted challenge. We conclude the article with some brief recommendations to guide and shape future research and action on the fairness of AI applications in the hiring process for the better.

Towards an Integrative Framework for Robot Personality Research

Within human-robot interaction (HRI), research on robot personality has largely drawn on trait theories and models, such as the Big Five and OCEAN. We argue that reliance on trait models in HRI has led to a limited understanding of robot personality as a question of stable traits that can be designed into a robot plus how humans with certain traits respond to particular robots. However, trait-based approaches exist alongside other ways of understanding personality, including approaches focusing on more dynamic constructs such as adaptations and narratives. We suggest that a deep understanding of robot personality is only possible through a cross-disciplinary effort to integrate these different approaches. We propose an Integrative Framework for Robot Personality Research (IF), wherein robot personality is defined not as a property of the robot, nor of the human perceiving the robot, but as a complex assemblage of components at the intersection of robot design and human factors. With the IF, we aim to establish a common theoretical grounding for robot personality research that incorporates personality constructs beyond traits and treats these constructs as complementary and fundamentally interdependent.

Service provision conditions for foreign residents in municipalities in Japan.

Objectives: This study examined the actual conditions of service provision to foreign residents (FRs) addressing prevention of lifestyle-related diseases (LRDs) and disaster preparedness/disaster responses (DPRs) in Japanese municipalities. Materials and Methods: A cross-sectional study was performed using a self-administered questionnaire with representatives of public health nurses in each municipality in Japan from December 2021 to January 2022. Results: Services considering FRs are more likely to be implemented in cities than in towns, and in municipalities where FRs account for ≥2.2% of the population (proportion of FRs in the Japanese population at the time of the study) than in those with fewer FRs. Cities have larger populations and greater financial resources than towns. Factors associated with the implementation of services and measures necessary for providing services to FRs were the classification of the municipality as a city, a high percentage of FRs, and large variation in corresponding nationalities/countries of origin. Conclusions: Cross-disciplinary efforts and collaborations need to be strengthened to share available resources within local governments and experiences in providing services for FRs in other divisions/sections, rather than considering only how to provide services for FRs in the public health division/section.

AI-Based Facial Emotion Recognition Solutions for Education: A Study of Teacher-User and Other Categories

Existing information on artificial intelligence (AI)-based facial emotion recognition (FER) is not easily comprehensible by those outside the field of computer science, requiring crossdisciplinary effort to determine a categorisation framework that facilitates exploration of the impact this technology has on users. Most proponents classify FER in terms of methodology, implementation and analysis; relatively few by its application in education; and none by its users. This paper is concerned primarily with users of FER for education, particularly teachers. It proposes a three-part classification of these teachers, by orientation, condition, and preference, based on theoretical traditions in educational psychology and philosophy, as well as on teacher surveys. It also compiles and organises the types of FER found in or inferred from the literature into technology and applications categories, as a prerequisite for structuring the proposed teacher-user category. This work has implications for the understanding of the relationship between teachers and FER among its proponents and critics, as well as for education practitioners.

Open and distance learning: a bibliometric analysis using scopus database and vosviewer

This study presents a bibliometric analysis of open and distance learning (ODL) literature to explore the impact of new technologies, temporal trends in research, and the influence of open pedagogy and educational resources on learner engagement and inclusion. Utilizing Scopus as the primary data source for its comprehensive coverage and analytical capabilities, a dataset was curated using specific keywords and analyzed through VosViewer. The results demonstrate a significant increase in ODL publications, indicative of growing scholarly interest and a diverse, global research community. Key findings reveal a network of influential institutions and scholars central to ODL, with highly cited documents highlighting foundational research and prevalent themes. The analysis underscores the importance of technological, pedagogical, strategic, and evaluative themes, signifying the complex and interdisciplinary nature of ODL. Suggestions for future research include qualitative analyses to understand ODL's progression and longitudinal studies to gauge the influence of global events on ODL practices. Collaborative and cross-disciplinary efforts are encouraged to innovate educational modalities. The study’s implications reflect ODL's growing relevance in educational policy and practice, the influence of key scholars and institutions in shaping ODL discourse, and the strategic research focus that may dictate future educational developments. This analysis charts the trajectory of ODL, contributing to its strategic evolution and enduring relevance in education.

The Effect of Therapeutic Adherence on the Effectiveness of a Digital Therapeutic Exercise Program: A Propensity Score Matching Analysis.

This study used a PSM model to comparatively assess the achievement of a clinically relevant pain improvement among patients who exhibit a high use (HU), intermediate use (IU), low use (LU), or sub-LU use profile. Sensitivity analyses with commonly accepted thresholds for clinically relevant improvements were conducted. Higher use profiles show a higher probability of achieving a clinically relevant improvement of self-reported pain intensities. Additionally, the achievement of any higher use level is associated with a significant increase in the probability of achieving a clinically relevant improvement. To enable the optimal effectiveness of DTx home exercise programs, an HU use profile should be pursued. This finding is in line with earlier guidance for the achievement of optimal therapeutic benefit from conventional movement and exercise therapy and underscores the importance of a cross-disciplinary effort from patients, healthcare professionals and system stakeholders alike to maximize the therapeutic effect from DTx.

Pathogen Emergence As Complex Biological Invasion: Lessons From Dynamical Systems Modeling

Infectious disease emergence has become the target of cross-disciplinary efforts that aim to understand and predict the shape of outbreaks. The many challenges involved with the prediction of disease emergence events is a characteristic that in- fectious diseases share with biological invasions in many subfields of ecology (e.g., how certain plants are able to successfully invade a new niche). Like infectious diseases, biological invasions by plants and animals involve interactions between agents (pathogens and plants in their respective cases) and a recipient niche. In this study, we examine the problem of pathogen emergence through the lens of a framework first developed for the study of plant invasions, restructured to apply to pathogen invaders. We utilize mathematical techniques to examine how com- plex dynamics emerge between the various actors in a multi-component pathogen invasion process, which implies invasion frameworks can offer new insight on the particulars of infectious disease emergence. Summarizing, we consider these re- sults in context of their application to epidemiology, and more broadly with regards to modern efforts to bring the vernacular of complex systems to more real-world systems and problems. In doing so, we demonstrate the potential power in math- ematizing conceptual models, and connecting ideas across disparate fields, toward a more rigorous picture of the nuances that underlie the dynamics of biological systems

Men of color in the health professions: Proceedings from the 2022 ADEA Men of Color in the Health Professions Summit.

The purpose of the American Dental Education Association (ADEA) Men of Color in the Health Professions Summit, held in August 2022 at ADEA's headquarters in Washington, DC, was to gather key thought leaders across a myriad of health professions and healthcare organizations and schools to cultivate intentional cross-disciplinary efforts in championing the need to address the low number of men of color entering not only dental, but also medicine, pharmacy, and health-related research careers. A pivotal follow-up step from the inaugural ADEA President's Symposium on Men of Color in the Health Professions at the March 2022 ADEA Annual Session & Exhibition in Philadelphia, the summit brought together academic health professions leaders, government agencies, health professions associations, and other key stakeholders to develop an action plan to support men of color entering the health professions. Moving the needle forward and increasing opportunities for underrepresented men of color in the health professions requires all academic health professions to work together. Highlights of the Summit included a keynote presentation by David Satcher, MD, PhD, the 16th Surgeon General of the United States; workgroup consensus statement development; health career pathways program presentations; strategic forecasting regarding challenges and opportunities in developing a coalition of health professions organizations to support men of color in the health professions; and frameworks for exploring coalition building.

Special Issue on Human Digital Twin Technology

With the advancement of information technologies such as the Internet of Things and artificial intelligence, cyber-physical systems are being introduced into society. At the core of these systems is the digital twin, a computer model (twin) of a physical entity built in cyberspace for simulation-based prediction. Currently, the digital twin mainly targets artificial objects, such as aircraft engines and factories. However, if it can be extended to humans, it could lead to the realization of human-machine cooperative systems and health promotion services, thereby solving social issues stemming from the aging of society. However, humans are the weakest link in the system, and many technical problems remain to be solved, such as realizing the measurement, modeling, and prediction of human behavior, if the human digital twin is to become reality. This special issue contains 9 papers on developing essential technologies for the human digital twin and constructing human-machine systems for specific applications. The topics covered include learning algorithms, motion measurement and analysis techniques, human perception, system development, and platform software for system development. These clearly show that cross-disciplinary efforts are essential to the realization of the human digital twin. We thank the authors of the papers submitted for this special issue. We are confident that the information provided by the authors is suggestive and informative for both specialists and non-specialists alike. We also sincerely appreciate the efforts of the reviewers. Their contributions helped to make this special issue possible. We hope that this special issue will catalyze sharing across the boundaries of research fields along the path to realizing a human digital twin.

Chemical safety and the exposome

Air pollution and rapid chemical intensification are major threats to the environment and human health. Today, we have produced over 350,000 chemicals, and current testing strategies do not meet the demands. Therefore, it is important to develop new approach methodologies (NAMs) that can help fill current information gaps. Toxicology needs to evolve from hazard and risk assessments based on morphological endpoints in animal tests towards a mechanism-driven integrated approach that better includes computational modelling as well as molecular, human, and in vitro data. The application of new science and technology such as different types of imaging and omics methods can allow faster collection of high-quality toxicological data for hazard identification and better prediction of toxicological potential using advanced in silico approaches including machine learning. A shift toward active prevention of pollution through a safe and sustainable-by-design approach based on cutting-edge science could significantly help safeguard the population and planetary health. Moreover, it is necessary to improve the understanding of how interactions among chemical mixtures, climate change, infectious agents, and other stressors that constitute the exposome, may affect biota and human health. Individual responses to current exposures and susceptibility to disease are influenced by factors such as genetics, epigenetics, physiology, and health status, which involve changes in biological pathways caused by own previous exposures or even ancestral exposures. It is therefore important to better consider individual exposomes and susceptibility in future risk assessments and precision medicine. This review describes the central role of mechanistic toxicology in chemical safety and in the cross-disciplinary efforts needed to characterize the exposome and its complex interactions in detail.

Modeling Bilingualism as a Dynamic Phenomenon in Healthy and Neurologically Affected Speakers Across the Lifespan: A Commentary on "Computational Modeling of Bilingual Language Learning: Current Models and Future Directions".

Modeling Bilingualism as a Dynamic Phenomenon in Healthy and Neurologically Affected Speakers Across the Lifespan: A Commentary on "Computational Modeling of Bilingual Language Learning: Current Models and Future Directions".

Product involvement and routine use of a niche product from a well-known company: The moderating effect of gender

Contemporary well-known companies are making cross-disciplinary efforts to promote niche products outside the scope of their core businesses. However, little is known about the routine use of these niche products. Based on the theory of involvement, we proposed a research model and conducted an online survey regarding Apple Pay to validate the hypotheses. Several insights were obtained through empirical analysis. Specifically, (1) routine use can be affected by product involvement, which in turn is positively influenced by ideal self-congruence and social influence, and (2) the effects of ideal self-congruence and social influence on product involvement are moderated by gender.

Communication-Efficient Federated Edge Learning via Optimal Probabilistic Device Scheduling

Federated edge learning (FEEL) is a popular distributed learning framework that allows privacy-preserving collaborative model training via periodic learning-updates communication between edge devices and server. Due to the constrained bandwidth, only a subset of devices can be selected to upload their updates at each training iteration. This has led to an active research area in FEEL studying the optimal device scheduling policy for communication time minimization. However, owing to the difficulty in quantifying the exact communication time, prior work in this area can only tackle the problem partially and indirectly by minimizing either the iteration rounds or per-round latency, while the total communication time is determined by both metrics. To close this research gap, we make the first attempt in this paper to formulate and solve the communication time minimization problem. We first derive a tight bound to approximate the remaining communication time through cross-disciplinary effort that combines the learning theory for convergence rate analysis and communication theory for per-round latency analysis. Building on the novel analytical result, an optimized probabilistic device scheduling policy is derived in closed-form by solving the approximate communication time minimization problem. It is found that the optimized policy gradually turns its priority from suppressing the remaining communication rounds to reducing per-round latency as the training process evolves. Extensive experiments based on real-world dataset and a use case on collaborative 3D objective detection in autonomous driving are provided to verify the superiority of the proposed policy over three benchmark policies based on the indirect solution approaches.

Protecting Three-Dimensional Museum Collections During Transport: Engineering and Evaluation of Transport Crates Featuring Wire-Rope Isolators for Improved Vibration Mitigation

ABSTRACT Shock and vibration generated during transport can lead to overload failure and fatigue fracture in museum objects. Damage can be prevented using transport packing providing both adequate shock absorption and vibration isolation. This research demonstrated that standardized packing with enhanced vibration mitigation is achievable for three-dimensional objects in a busy museum environment. Based on state-of-the art predictive modelling, extensive engineering and collection care expertise, a calculator tool was developed that allows users to create packing with improved vibration isolation by using the overall dimensions and weight of an object. This research highlighted that effective vibration mitigation can only be designed in a concerted cross-disciplinary effort by engineers and collection care professionals.

A systematic review of human-AI interaction in autonomous ship systems

Automation is increasing in shipping. Advancements in Artificial Intelligence (AI) applications like collision avoidance and computer vision have the potential to augment or take over the roles of ship navigators. However, implementation of AI technologies may also jeopardize safety if done in a way that reduces human control. In this systematic review, we included 42 studies about human supervision and control of autonomous ships. We addressed three research questions (a) how is human control currently being adopted in autonomous ship systems? (b) what methods, approaches, and theories are being used to address safety concerns and design challenges? and (c) what research gaps, regulatory obstacles, and technical shortcomings represent the most significant barriers to their implementation? We found that (1) human operators have an active role in ensuring autonomous ship safety above and beyond a backup role, (2) System-Theoretic Process Analysis and Bayesian Networks are the most common risk assessment tools in risk-based design, and (3) the new role of shore control center operators will require new competencies and training. The field of autonomous ship research is growing quickly. New risks are emerging from increasing interaction with AI systems in safety–critical systems, underscoring new research questions. Effective human-AI interaction design is predicated on increased cross-disciplinary efforts, requiring reconciling productivity with safety (resilience), technical limitations with human abilities and expectations (interaction design), and machine task autonomy with human supervisory control (safety management).

Cross-Disciplinary Efforts in Treating Diabetes

Genetic Engineering & Biotechnology NewsVol. 42, No. 2 Drug DiscoveryCross-Disciplinary Efforts in Treating DiabetesResearchers are leveraging stem cell technology, developing miniature pancreases, and tucking blood-sugar-sensing cells into bioinert capsulesRichard A. SteinRichard A. SteinSearch for more papers by this authorPublished Online:14 Feb 2022https://doi.org/10.1089/gen.42.02.10AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 42Issue 2Feb 2022 Information© 2022 by GEN PublishingTo cite this article:Richard A. Stein.Cross-Disciplinary Efforts in Treating Diabetes.Genetic Engineering & Biotechnology News.Feb 2022.28-31.http://doi.org/10.1089/gen.42.02.10Published in Volume: 42 Issue 2: February 14, 2022PDF download

First Report of Testicular Replantation Following Wrong-Site Surgery

Testicular replantation represents a unique circumstance. There are very few reports documenting their experience with testicle replantation and to the best of the authors’ knowledge, this is the first case that has been reported in the peer-reviewed literature following a wrong site surgery. Therefore, we detail our technique and outcome when faced with such a rare event. In addition we review the literature, in order to compare and report the experience of others. This case highlights the value of applied microsurgical knowledge and the importance of cross-disciplinary efforts to improve patient outcomes.

Invasive alien species as simultaneous benefits and burdens: trends, stakeholder perceptions and management

In addition to being a major threat to biodiversity and ecosystem functioning, biological invasions also have profound impacts on economies and human wellbeing. However, the threats posed by invasive species often do not receive adequate attention and lack targeted management. In part, this may result from different or even ambivalent perceptions of invasive species which have a dual effect for stakeholders—being simultaneously a benefit and a burden. For these species, literature that synthesizes best practice is very limited, and analyses providing a comprehensive understanding of their economics are generally lacking. This has resulted in a critical gap in our understanding of the underlying trade-offs surrounding management efforts and approaches. Here, we explore qualitative trends in the literature for invasive species with dual effects, drawing from both the recently compiled InvaCost database and international case studies. The few invasive species with dual roles in InvaCost provide evidence for a temporal increase in reporting of costs, but with benefits relatively sporadically reported alongside costs. We discuss methods, management, assessment and policy frameworks dedicated to these species, along with lessons learned, complexities and persisting knowledge gaps. Our analysis points at the need to enhance scientific understanding of those species through inter- and cross-disciplinary efforts that can help advance their management.