Innovative Features Research Articles

Innovations in abortion care in France, Germany and the UK following the COVID-19 pandemic

Abstract Background Through an international comparison of health systems and policies, we aim at assessing the contextual and circumstantial characteristics of abortion care innovation in three European countries following the upheaval of the COVID-19 pandemic. The three contrasting care models pre-pandemic constitute an interesting baseline for observing different systems’ reaction to health crises. Methods We conducted a review of the recent (2020 onward) peer-reviewed and grey literature, including national policy documents and guidelines. We then carried a comparative analysis of innovations implemented during the pandemic and their sustainability post-crisis. Results In France and the UK, where abortion care was more accessible before the pandemic than in Germany, a series of innovations were officially introduced to facilitate access during the pandemic. They included teleconsultations and the mailing of abortion medication. Most changes have been sustained since then, contributing to addressing historic and systemic health inequities in terms of access (e.g. due to geography and the existence of “medical deserts”). In Germany, innovations during the pandemic have been crafted by the civil society through NGOs offering for the first time teleabortion services (e.g. Balance Berlin and Doctors for Choice). The legitimation of those practices by professional bodies is still in the making, highlighting the limitations of the catalyst role of crises in the face of cultural barriers and resistance of health systems to innovation. Conclusions The COVID-19 pandemic provoked or accelerated innovation in terms of abortion care in France, Germany and the UK. Yet, its sustainability, as well as its scaling up, remains fragile, especially in Germany, where the disruptive approach of civil society organisations has not yet found its way into mainstream health care services. Key messages • International comparison of health systems’ reaction to the COVID-19 pandemic in terms of abortion care shows different paths to innovation. • The sustainability of innovation beyond the first pandemic years pertains to the wider debate on equity in access to abortion care.

Safety profile, electrical performances and clinical outcomes of a novel leadless pacemaker; first results from real-world clinical practice in Saudi Arabia

Abstract Introduction Leadless pacemakers (LP) are emerging as an effective and safe alternative to transvenous pacemakers to reduce lead-related and pocket-related complications and to improve patient experience. A new LP system, the Aveir VR, has been approved in 2022 for US and other countries, and in 2023 for Europe, and features innovative characteristics such as the active fixation helix mechanism and the possibility to measure sensing/pacing parameters before LP deployment. Purpose Evaluate safety, electrical performances and clinical outcomes associated with the first Aveir VR LP implants in 2 Hospitals in Saudi Arabia. Methods We performed a prospective evaluation of all-comer patients who received Aveir VR LP. Decision for LP implant was based on conditions such as cardiac pacing indication, lack of upper extremity venous access, risk of device infection, and life expectancy, and using shared decision-making. Clinical and electrical data were collected at implant and at 1st and 6th month visits. Results A total of 54 patients (25 female, mean age 69 years) were included between December 2022 and October 2023. Pacemaker implant indication was AV block in 25 (46%) patients, sinus node disease in 19 (35%) patients, atrial fibrillation and slow ventricular response in 9 (17%) patients and left bundle branch block in 1 (2%) patient. Implant was successful in all attempted cases. Final device position was lower septum in 51/54 (94.4%) patients and mid-septum in 3/54 (5.6%) patients. Mean procedure time was 48±22 minutes and showed a decreasing trend as a function of operator experience with a mean of 55, 50 and 36 minutes in the first, second and third group of consecutive implants, respectively. Mean fluoroscopic time was 11±8 minutes and showed a decreasing trend as a function of operator experience with a mean of 13, 13 and 6 minutes in the first, second and third group of consecutive implants, respectively. Final device position was achieved at first attempt in 42/54 (77.8%) cases and at first or second attempt in 51/54 (94.4%) cases. At implant mean R wave sensing was 7.6±3.7 mV, mean impedance was 724±335 Ohm, mean threshold was 1.0±0.6 V at 0.4 ms. During implant there was one patient with pericardial effusion treated with pericardiocentesis. In a mean follow-up of 73 days there were no procedure-related or device-related complications, electrical parameters showed acceptable values, and all implanted devices performed as expected. Median longevity, estimated at last follow-up visit, was 19 years (interquartile range: 12-20 years). Conclusion First real-world cases of use of a novel leadless pacemaker in Saudi Arabia show optimal feasibility and good safety profile and electrical performances. Procedure and fluoroscopic times were acceptable and decreased as a function of operator experience. Longevity estimations predict very long service life-times.

Study on the Influence of Star Activity on Economic Pull

Abstract: With the change in times, the business model of star activities presents the characteristics of rich diversity and innovation. The rapid development of the entertainment industry makes the star activities gradually become a significant commercial phenomenon, and the commercial value behind it is increasingly prominent. The goal of this paper is to find ways to drive the economy by studying the impact of star activities on the economy. This paper mainly uses Taylor Swift's "The Eras Tour" as the case to analyze the main business model of star activities, and the impact of star activities on the prosperous age economy. The research on its impact mainly focuses on where the impact on international tourism and the pattern of the economy are mainly reflected. Through research, it is found that the star activity is the economy, and the economic recovery needs a prosperous economy, and the star activity, as the representative of the prosperous economy, is the main force to promote the economy. Through the research, the cooperation between the government and the stars has a great role in promoting the economy. This study not only allows us to identify the main business model of star activities but also to find out the impact of the nature of star activities on people's lives and even on the global economy. To better grasp the economic trend and better economic development.

INNOVATIONS IN HUMAN RESOURCE MANAGEMENT IN THE PUBLIC SECTOR OF UKRAINE

The article examines the characteristics of innovations in human resource management within Ukraine’s public sector. It defines the concept of innovation in human resource management as the introduction of new ideas, methods, technologies, and processes aimed at enhancing the efficiency and effectiveness of managing human resources. The importance of studying this topic is highlighted, particularly in light of the need for the public sector and government bodies to adapt to the demands of wartime and the socio-political crisis, as well as the necessity to develop a strategy for advancing the public sector through the implementation of various international agreements. The main objective of the study is to analyze the specific features of introducing innovations in the human resource management system of Ukraine’s public sector. This includes identifying successful practices for implementing electronic systems, key areas for the digitalization of public administration, and promising research directions. The study demonstrates that several organizational, technological, and social variables influence the interactions between employees, management, and other stakeholders. For instance, technological innovations enable the automation of HR processes (e.g., talent management systems, HR analytics, electronic document management platforms) and the use of online tools for employee training and development (e-learning, webinars). Organizational innovations promote the adoption of new management models. The study highlights several priority areas for further development: strategic communications in public policy, shaping the corporate culture of government agencies, defining their mission, strategic goals, values, and vision; fostering innovative leadership; developing horizontal connections within organizations through innovation; and ensuring principles such as fairness, transparency, openness, and equal access through the digital transformation of public administration.

Innovative Feature Analysis of Electric Vehicle Technology, Charging Infrastructure, Power management, and Control Methods

Lowering the dependence on fossil fuels and reducing pollution from greenhouse gas (GHG) emissions is incredibly achievable through electric vehicle (EVs) technology. EV technology is an innovation that uses electricity, rather than fossil fuels, to power and refuel (recharge) vehicles. The adoption and development of EVs should lead to a decline in future demand for fossil fuels, which are finite in supply and exhaustible. Inherent challenges in EV technology, such as inadequate supply of critical minerals, power grid overload, battery technology constraints, extended charging durations, insufficient charging infrastructures, high initial costs, and limited driving range, must be addressed. The technology of charging infrastructures cannot be over-emphasized in EV technology. EV technology, charging infrastructures, vis-à-vis the impact of their integration into the grid is investigated. Effective control strategies and power management systems (PMSs) are required to optimize energy use to improve EVs' efficiency and lifetime. This research uses comprehensive analysis methods to assess various control strategies, PMSs, and their effects on EV integration into the grid.

Vortex Nanodiscs Functionalization to Overcome Macrophage Recognition for Efficient Theragnosis Applications

Biological barriers prevent nanotherapeutics successful accumulation at target cells, limiting diagnosis and treatment responses. Magnetic nanodiscs with a spin‐vortex ground state have shown great promise for magnetomechanical cancer cells annihilation and for neuronal stimulation, requiring very low concentrations for an effective result. However, the biological barriers that these particles encounter upon intravenous administration remain a challenge. Herein, the synthesis of biocompatible multilayered Au/Fe/Au nanodiscs with a spin‐vortex ground state and their inert surface modification is reported. Two different surface modifications with two distinct polyethylene glycol (PEG) molecules are performed, which successfully reduce macrophage uptake, while maintaining the nanodiscs’ biocompatibility. By effectively preventing nanodisc uptake, innovative design features can be rationally incorporated to create a new generation of specific nanotherapeutics by modifying the PEG surface with specific targeting molecules.

Assessing innovative and responsive young leaders in public service: Lens from community clientele

Youth leadership brings new perspectives, innovative ideas, and a dynamic approach to addressing contemporary issues. Young leaders often possess a deep understanding of the unique challenges and opportunities faced by their generation, enabling them to develop solutions that are relevant and impactful. Their involvement in public service fosters a sense of responsibility and civic engagement, encouraging a culture of active participation and community building. This study examined the innovative and responsive characteristics of young leaders in the Philippines. This exploratory paper expected to provide understanding on how community clientele like community residents, elderly people, persons with disability, perceived innovative and responsive traits of community youth leaders. Convenience sampling (n=12) was carried out to select the participants seeking assistance from barangays leaders. Findings indicated that the community clienteles described these young leaders as possessing creative minds capable of ‘thinking outside the box’ to address evolving challenges and meet community needs. Youth leaders were noted for their commitment to effective communication, gathering feedback, and working collaboratively with the community to resolve issues. They are accessible and approachable, demonstrating empathy and attentiveness to the concerns of those they serve. The perception of community clientele emphasized how young leaders integrate creative and innovative approaches to problem-solving with proactive and empathetic engagement to the community, and their commitment to transparency and effective communication. These qualities collectively contribute to the community's positive view of youth leadership, recognizing the potential of young leaders to bring about meaningful and lasting change.

Different forms of fablab organization and their impact on collaboration and innovation

The aim of this paper is to identify some of the characteristics of innovation and collective work in different fablab organizations. We first define fablabs through a review of literature, situating related questions in the field of ergonomics and focusing our point of view on individual and collective activity. Secondly, we show how the results of our qualitative analyses (performed on data from interviews and observations of fablab managers, users, and projects from 13 fablabs) reveal 3 main types of fablab organization: community-oriented fablabs, academic fablabs and industrial fablabs, in which different activities are carried out. Fablab activity depends on lab users and the type of design projects carried out. The discussion will focus on the fablab organization findings, including the links between design/innovation project work, collective work and evolving rules, and how all of these aspects might direct activity-centered ergonomics research and actions in the future.

Objectives pursued by European football clubs: compete for income through victories and media exposure

PurposeThe paper aims to revisit the debate on the priorities of football clubs in talent hiring with respect to maximizing sporting performance or economic profitability. Based on the degree of media exposure of the clubs, we examine whether the clubs’ objectives include, in addition to the classic twofold choice, the aspiration of club managers to gain popularity through media exposure.Design/methodology/approachThis paper applies structural equation modelling (path analysis) techniques to re-examine what is the more realistic description of football club owners’ decisions when hiring talent. Our database comprises teams from the first division of four top European football leagues: 80 observations per season during the pre-COVID period spanning from 2009/10 to 2017/18.FindingsThe results suggest that, when recruiting players, in addition to considering the two classic objectives (wins and profits), club owners also seem to aim expanding the media exposure and popularity of their clubs. Our study reveals that, to explain talent-hiring decisions in football, the ability to attract media attention is as crucial as sporting performance could be. Furthermore, by examining the direct, indirect and total effects on annual revenue, we found that our media visibility index performs a mediation effect connecting sports performance and revenue.Originality/valueAn innovative feature of our analysis is the use of the MERIT media visibility index, which jointly captures the on-field and off-field players’ skills. The consistency and robustness of the results derive from the various specifications of the estimated models.

Waste classification strategy based on multi-scale feature fusion for intelligent waste recycling in office buildings

Waste classification is an important measure to protect the environment. Existing waste classification methods mainly focus on scientific research, but lack attention to the challenges of waste classification in actual scenarios. For example, wastes with similar contours, similar textures, or contaminated appearance are difficult to be classified in actual scenarios. To address these issues, this paper proposes an innovative multi-scale feature fusion strategy (MFFS) to improve the classification accuracy of these wastes. MFFS combines local fine-grained features with global coarse-grained features to improve the feature expression ability of waste. However, how to effectively fuse these two features is a key challenge. This paper proposes a dual-scale feature fusion strategy, first fusing fine-grained features in the first dimension, then fusing coarse-grained features in the second dimension, and introducing spatial features to further enhance feature expression capabilities. In order to reduce the interference of background information, the model in this paper models global relationships based on convolutional features. The MFFS strategy achieved a classification accuracy of 95.5% on the self-built dataset and 94.1% on the public dataset TrashNet. The number of parameters of our model is reduced by 57.2% compared with the classic VGG16 and by 34.2% compared with the Vision Transformer. In addition, we designed an intelligent waste sorting device and deployed the MFFS model on the device to implement the application. Experiments show that our model has ideal accuracy and stability and can be promoted and applied.

A sociotechnical history of an AI video chatbot: Mapping AI chatbot innovation trajectory for information policy design

This study traces the patent citation network of U.S. Patent 11,107,465 Natural Conversation Storytelling System (Gustman et al, 2021) to map the innovation trajectory of AI Chatbots. This patented AI video chatbot enables the reanimation or digital resurrection of humans in video form. As GLAMs continue to experiment with new technologies such as historical figure chatbots to increase engagement through gamification and empathy, a critical examination of technologies that are designed to appear human-like is warranted as they often skirt credibility, accuracy, and likely insert bias. Furthermore, the rise of generative AI tools and the propensity for producing hallucinations (Christensen et al, 2024) increases ethical issues for the implications on humans and truth (Ranalli, 2022; Stahl and Eke, 2024). Patent citation network analysis is frequently conducted as a competitive strategy for mapping the trajectory of technological development and patented inventions (Érdi et al, 2013; Jain et al, 2020). Drawing from this method, innovation trajectory routes or pathways will be traced through the patent citations to identify the most prominent or critical patents in the AI video chatbot innovation trajectory and analyze which features of technical innovation are retained across its pathway. These methods are frequently utilized to understand changes, patterns, and development in innovation to predict economically viable futures and can be utilized to predict the needs for information policy (Frohmann, 1995) by understanding the implications asymmetrical power on society.

Drivers of digital currency adoption and their configurational impact assessment in tourism and hospitality: loss aversion under prospect theory

ABSTRACT With accelerated digitalisation in all business sectors, digital currencies (DC) are increasingly popular. This study aimed to identify the effects of central bank digital currency (CBDC) innovation characteristics and perceived risks on CBDC adoption intention in the tourism and hospitality field. This study devised a research model incorporating research hypotheses addressing CBDC customers’ perceptions of CBDC's innovative technology and risks. To test the hypotheses, data were obtained from the USA, Korea, and China. CBDC's innovation characteristics and perceived risks affected the adoption of CBDC for transactions during travel. The results have academic and practical value because they aid understanding of customers’ reactions to the new transaction system and establish proactive marketing strategies such as promotional message development to reduce perceived risks in lieu of strengthening innovative characteristics.

Performing Gender in Late Spanish Folk Revival

This article focuses on modern musical practices from Art al Quadrat, A Banda da Loba and Nun Tamos Toes which relate in a variety of ways to the idea of tradition and folklore. These musical practices represent a part of the folk revival process, revitalizing a countercultural movement, which portrays a clash of ideologies and identities. Identities and ideologies related with feminism are acted out through performance aesthetics, its staging, and musical references. Adapting, renewing and introducing new gender models and innovative main characters as part of the musical discourse are some of the main features of this reinvention. In this case, the research is focused on reshaping and reconstructing gender imaginaries of women through music. Popular music’s need to update to current social issues in order for it to become an element of social relevance is presented through the reinvention of popular music.

Advanced Personal Budget Analytics: Combining Optical Character Recognition and Natural Language Processing for Automated Budget Categorization and Insight Extraction

A budget tracking system is a tool designed to help users monitor their financial resources, categorize expenses and control their financial resources. An Intelligent Personal Budget Analysis System is designed to redefine personal finance management. IntelliFinance is a user- friendly app designed for seamless and efficient daily expense management removing the necessity for conventional paper documentation. This project inculcates the concepts of Computer Vision, Machine Learning and Data Analytics, aims to surpass traditional budget tracking by incorporating innovative features such as receipt scanning and analysis. The project is implemented using Android Studio and Firebase, incorporating advanced features such as Optical Character Recognition (OCR) to capture receipt images, extract text, and process it for further analysis. Firebase ML Kit is utilized for scanning and text recognition, while Natural Language Processing (NLP) is applied for categorizing the extracted text. The system provides a personal budget analysis that enhances the accuracy of financial tracking by offering users a comprehensive overview of their spending habits, complemented by detailed reports and visualizations. Ultimately, this project serves as a financial companion, empowering users to take control of their finances, make informed decisions, and achieve their financial goals.

TCM-Centric Innovations in WHO's International Standard Terminologies: A Qualitative Exploration

Abstract: Traditional Chinese medicine (TCM) is increasingly recognized worldwide as a valuable complementary and alternative medicine. To facilitate global research and collaboration in this field, the World Health Organization (WHO) introduced the International Standard Terminologies on Traditional Chinese Medicine on March 3, 2022. This international terminology translation standard, IST 2022, goes beyond conventional translation by embracing three innovative features: 1) It reflects TCM's foundational philosophy of unity and opposition, emphasizing the interconnectedness among TCM terms during translation. This approach transcends individual term translations to explore the interrelationships among them. 2) It meticulously preserves the integrity of TCM theory. It achieves this by retaining transliterations for unique TCM terms that possess distinct features, thus upholding the essence of TCM. 3) It employs innovative Xiang (Image) cognition, a concept rooted in traditional Chinese thought by helping readers grasp visual and mental imagery associated with each term. This study presents a qualitative analysis based on interviews with 11 TCM translation experts, examining their perspectives on these features and their translational preferences across IST 2007 and 2022 versions. The findings contribute to the standardization and global harmonization of TCM terminology, advocating for clarity, precision, and the advancement of TCM in the international healthcare arena.

NUTRIFLEX

The NUTRIFLEX project is a comprehensive AI-powered application designed to provide personalized nutrition and health management solutions. The goal of the project is to assist individuals in optimizing their diet based on their unique biological and emotional needs, including gut health, mood, and overall well-being. By combining artificial intelligence (AI) and user input, NUTRIFLEX offers tailored meal plans, calorie predictions, mood-enhancing food recommendations, and a gamified approach to motivate users to maintain a healthy lifestyle. The problem addressed by NUTRIFLEX is the growing challenge people face in maintaining a balanced and healthy diet. Modern lifestyles, characterized by fast-paced routines and unhealthy food choices, contribute to poor physical and mental health. Many individuals struggle to find the right balance between their nutritional intake and their health goals, whether it's weight loss, muscle gain, or general wellness. Furthermore, gut health, which plays a critical role in overall health, is often neglected in conventional meal planning applications. Mood fluctuations also significantly impact people's food choices, leading to stress eating or energy dips. NUTRIFLEX solves these problems by offering a holistic, AI-driven solution that adapts to users' unique needs. By using machine learning models, NUTRIFLEX predicts the calorie content of meals and creates personalized meal plans based on user-specific data such as Basal Metabolic Rate (BMR) and Total Energy Expenditure (TEE). The application also provides mood-based meal suggestions, helping users manage their emotional state through food choices that boost energy, focus, and relaxation. One of the most innovative features of NUTRIFLEX is its gut health functionality. By allowing users to input microbiome data, the app generates personalized meal recommendations designed to improve gut health, which in turn enhances overall physical and mental well-being. This focus on gut health distinguishes NUTRIFLEX from traditional meal planners. In addition, NUTRIFLEX integrates gamification to keep users engaged and motivated. Users can set health goals, track their progress, and earn rewards, making the health journey enjoyable and sustainable.

Landmark-aware autonomous odometry correction and map pruning for planetary rovers

Planetary rover autonomous localization is paramount for a planetary surface exploration mission. However, existing methods demonstrate limited localization accuracy, mostly due to the unstructured texture characterization of planetary surface. In response, this study presents a novel Neural Radiance Field (NeRF) driven visual odometry correction method that allows for high-precision 6-DoF rover pose estimation and local map pruning. First, an innovative image saliency evaluation approach, combining binarization and feature detection, is introduced to meticulously select landmarks that are conducive to rover re-localization. Subsequently, we conduct 3D reconstruction and rendering of the chosen landmarks based on a-priori knowledge of planetary surface images and their Neural Radiance Field (NeRF) models. High-precision odometry correction is achieved through the optimization of photometric loss between NeRF rending images and real images. Simultaneously, the odometry correction mechanism is employed in an autonomous manner to refine the NeRF model of the corresponding landmark, leading to an improved local map and gradually enhanced rover localization accuracy. Numerical simulation and experiment trials are carried out to evaluate the performance of the proposed method, results of which demonstrate state-of-the-art rover re-localization accuracy and local map pruning.

Hashtivism as media discourse: analysing pioneer environmental action in Public Service Media through transmedia formula

Various studies have analysed the news media’s participation in debates generated in the public digital sphere represented by social media, particularly X (formerly Twitter) and Instagram. Some of these debates have gained strength and become authentic movements linked to certain social struggles, such as feminism. Similarly, the so-called ‘environmental hashtivism’ or ‘eco-hashtivism’ is acquiring increasing importance in the context of this digital sphere. In view of this, the focus of this article is the distinctive area of public radio and television channels in Europe to examine the transmedia action #EKIN_klima, developed by the Basque public audiovisual corporation Euskal Irrati Telebista (EITB). The study of this pioneering initiative allows us to understand just how the eco-activism actions of the public news media can help to reposition it within the hybrid media system and contribute to the modernisation of its social function, along the lines of other actions, such as those carried out by the BBC against disinformation. In this way, it has been noted that the environmental issue is not only something to be included in the news media agenda, but also an opportunity for the public news media to legitimise its social and innovative character through transmedia branding actions.

Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia.

Biliary atresia (BA) is a severe congenital biliary developmental abnormality threatening neonatal health. Traditional diagnostic methods rely heavily on experienced radiologists, making the process time-consuming and prone to variability. The application of deep learning for the automated diagnosis of BA remains underexplored. This study introduces GallScopeNet, a deep learning model designed to improve diagnostic efficiency and accuracy through innovative architecture and advanced feature extraction techniques. The model utilizes data from a carefully constructed dataset of gallbladder ultrasound images. A dataset comprising thousands of ultrasound images was employed, with the majority used for training and validation and a subset reserved for external testing. The model's performance was evaluated using five-fold cross-validation and external assessment, employing metrics such as accuracy and the area under the receiver operating characteristic curve (AUC), compared against clinical diagnostic standards. GallScopeNet demonstrated exceptional performance in distinguishing BA from non-BA cases. In the external test dataset, GallScopeNet achieved an accuracy of 81.21% and an AUC of 0.85, indicating strong diagnostic capabilities. The results highlighted the model's ability to maintain high classification performance, reducing misdiagnosis and missed diagnosis. GallScopeNet effectively differentiates between BA and non-BA images, demonstrating significant potential and reliability for early diagnosis. The system's high efficiency and accuracy suggest it could serve as a valuable diagnostic tool in clinical settings, providing substantial technical support for improving diagnostic workflows.

Vision-sharing system for android avatars to enable remote eye contact

Maintaining eye contact is a fundamental aspect of non-verbal communication, yet current remote communication tools, such as video calls, struggle to replicate the natural eye contact experienced in face-to-face interactions. This study presents a cutting-edge vision-sharing system for android avatars that enables remote eye contact by synchronizing the eye movements of the operator and the avatar. Our innovative system features an eyeball integrated with a wide-angle lens camera, meticulously designed to mimic human eyes in both appearance and functionality. This technology is seamlessly integrated into android avatars, enabling operators to perceive the avatar’s surroundings as if physically present. It provides a stable and immersive visual experience through a head-mounted display synchronized with the avatar’s gaze direction. Through rigorous experimental evaluations, we demonstrated the system’s ability to faithfully replicate the operator’s perspective through the avatar, making eye contact more intuitive and effortless compared with conventional methods. Subjective assessments further validated the system’s capacity to reduce operational workload and enhance user experience. These compelling findings underscore the potential of our vision-sharing system to elevate the realism and efficacy of remote communication using android avatars.