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Background: Vaccines offer arguably the most cost-effective public health intervention. Vaccine supply chain management which is a critical building block faces many Human resources challenges mainly due to the special attributes of vaccines. Objective: This study attempted to measure the effect of training on vaccine cold chain handler knowledge and practices. Methods: A cross-sectional research design, using predominantly quantitative data collection techniques, was used. Facilities that have offered vaccination services for more than a year and report through the HMIS system were eligible for selection. Observation checklists and structured questionnaires were used. SPSS was used to analyse data. Results: Vaccine cold chain management among the study group had an average score of 65.33% range (31–85%). The average knowledge score among the study respondents was 62.42% with a range (45–95%). The knowledge of respondents generally increases with an additional increase in the number of training modalities. Conclusions: The status of VCCM is at about 65.33% below the target of 80% set by the EVM. The trainings have an effect on both knowledge of handlers and their practice especially when deployed in a multi-pronged design and thus these trainings need to be aligned to achieve synergy. ABBREVIATIONS: CCE, Cold Chain Equipment; DHIS2, District Health Information Systems 2; DHO, District Health Officer; DPT, Diphtheria, Pertussis, Tetanus; DVS, District Vaccine Stores; EPI, Expanded Program for Immunisation; EVM, Effective Vaccine Management; FEFO, First Expiry First Out; GAVI, Global Alliance for Vaccines and Immunisation; HMIS, Health Information Management Systems; IRC, International Rescue Committee; KII, Key Informant Interview; LIAT, logistics indicator assessment tool; PATH, Program for Appropriate Technology in Health; PHC, Primary Health Care; QPPU, Quantification and Planning and Procurement Unit; SOPs, Standard Operating Procedures; SPSS, Statistical Package for Social Sciences; UNEPI, Uganda National Expanded Program for Immunisation; UNICEF, United Nations Children's Fund; VPD, Vaccine Preventable Diseases; VVM, Vaccine Vial Monitors; WHO, World Health Organisation [ABSTRACT FROM AUTHOR]

The mass adoption of ICT for online delivery of education due to the COVID-19 pandemic has brought many opportunities but also challenges for the education sector. In this paper, we conducted a scientometric analysis to provide insights into research trends and present bibliometric indicators of 5810 publications on blended learning to contribute to the knowledge base on the use of ICT in education management, during and after the COVID-19 pandemic, from 2020 to 2023. The number of citations and publications increased rapidly. Content analysis of the publications and keyword analysis revealed important and emerging topics such as the challenges and experiences of students, teachers and institutions with blended learning, especially in higher education, from implementation and use to digital literacy, attitudes, performance, self-regulation and learning outcomes. The main journals focused on the use of technology in education and health education. Blended learning has likely moved beyond the pandemic and has become an integral part of management in educational organizations. [ABSTRACT FROM AUTHOR]

Context.--Workup of the poorly differentiated or undifferentiated tumor remains a significant and challenging entity in the practice of anatomic pathology. Particularly in the setting of small biopsies and limited material, these cases demand a balanced approach that considers the patient's clinical and radiologic presentation, a basic assessment of tumor morphology, a reasonably broad immunohistochemical panel, and diligent preservation of tissue for prognostic and therapeutic studies. Objective.--To illustrate some of the new and emerging immunohistochemical markers in the evaluation of tumors with undifferentiated or poorly differentiated morphology, with a focus on the workup in limited tissue samples to raise awareness of the issues involved with the pathologic workup in these challenging tumors. Data Sources.--A literature review of new ancillary studies that can be applied to cytologic specimens was performed. Conclusions.--Knowledge of the patient's history and communication with the patient's clinical team is essential in formulating a differential diagnosis that can appropriately limit the differential diagnosis based on morphology, especially in small specimens. This information, in conjunction with classifying the tumor morphology (eg, epithelioid, spindled, neuroendocrine, basaloid/biphasic, mixed) gives a logical approach to choosing an initial immunohistochemical panel. Fortunately, immunohistochemistry is evolving quickly in the wake of groundbreaking molecular studies to develop new and better markers to further classify these difficult tumors beyond where we traditionally have been able to go. [ABSTRACT FROM AUTHOR]

A 14-year-old spayed female mixed-breed cat weighing 3.4 kg was admitted to the Tokyo University of Agriculture and Technology Animal Medical Center for syncope after vomiting. Echocardiography, electrocardiography, and thoracic radiography revealed no abnormalities. Holter electrocardiography showed a paroxysmal high-grade atrioventricular block coinciding with the vomiting. Based on these findings, the cat was diagnosed as having situational syncope with paroxysmal high-grade atrioventricular block triggered by vomiting, which improved with antiemetic treatment alone. The cat subsequently died of chronic kidney disease approximately 3 years and 4 months after the initial diagnosis. This is the first reported case of situational syncope triggered by vomiting in a cat. [ABSTRACT FROM AUTHOR]

The innovative application of emerging mobile and wearable health information and sensing technologies (mHealth) holds great promise for lowering healthcare costs and enhancing well-being in various ways. Numerous fields are seeing the development of these applications. Still, to fully understand the opportunities and difficulties associated with using mobile technologies to enhance health outcomes, more thorough research is required. There is currently little data supporting the effectiveness of mHealth. Even though these technologies seem harmless and enticing, more research is required to determine the best times, locations, and users for mHealth methods, applications, and devices. As a result, a remote medical hub waitperson is essential to sustainably providing high-quality telemedicine services. This paper offers a thorough analysis of the delivery of medical services through telemedicine applications, with a focus on medical center servers. It also draws attention to the problems and obstacles that still need to be resolved to deliver health services via telehealth in the medical center. These ideas are used in this work to define a high standard for the developing field of mHealth research, explore potential future directions, and describe existing assessment standards. [ABSTRACT FROM AUTHOR]

Background and Aim: Chatbots are computer programs, which are devised to simulate conversations through voice or textual interactive forms. These applications offer multiple benefits in patient education, clinical decision-making, interpersonal communication, research activities, data analysis and administrative affairs. The present scoping review aims to analyse the current role, pitfalls, challenges and future scope of these modalities in diverse fields of medical science. Methods: Literature search was made on 9 April 2024, on five databases (PubMed, Scopus, Web of Science, Embase and Google Scholar). A narrative approach was used for the synthesis of results. Results: Our literature search yielded 1024 studies. After the de-duplication of manuscripts using Endnote, 342 articles were identified. After title and abstract screening, 74 articles were included for the next round of screening. Finally, 14 articles were selected for this scoping review.Diverse chatbot applications have been developed at a growing rate for use in medical science. There is a gradual shift towards employing machine learning-based strategies to develop chatbot programs. Chatbots have a significant potential to revolutionise diverse aspects of medicine including patient care, academic activities, and research endeavours. Conclusion: Artificial Intelligence can be highly effective in streamlining the routine functions and activities in medical care. Chatbots have the potential to meliorate the accessibility, efficiency and standard of medical care. However, the need for further validation through high-quality studies to ensure patient privacy, strategies to conform to patients' data security, accuracy and precision of the technology and mitigating potential pitfalls in its routine utilisation globally are warranted. [ABSTRACT FROM AUTHOR]

This article reviews the evolution of noninvasive hemodynamic monitoring technologies, highlighting their importance in perioperative and critical care settings. Initially dominated by invasive methods, the field has shifted toward noninvasive techniques to reduce risks and improve patient safety. These advancements encompass various technologies, including bioimpedance/bioreactance, pulse contour analysis, and photoplethysmography, offering anesthesiologists dynamic tools for patient management. The article explores historical developments, traditional and advanced noninvasive monitors, and future trends, emphasizing the potential of integrating artificial intelligence and wearable technology in patient care. [ABSTRACT FROM AUTHOR]

Copyright of Akademik Hassasiyetler is the property of Huzeyfe Suleyman Arslan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Infodemic requires a quick and efficient response and Health Technologies Assessment (HTA) can offer relevant information. Even if the members of the infodemic management (IM) team have competencies in dealing with public health emergencies, they may need support in selecting the appropriate interventions. This paper aims to a analyse HTA as a frameworkfor selecting infodemic management interventions and integrate it into the decision-making process, by illustrating the process of assessment and appraisal. It uses a qualitative approach, by "So analysing both concepts and illustrating them through graphic representation, with examples for practical application. Joint research on HTA and IM can be found only indirectly, mostly regarding applying HTA in public health interventions, particularly in public health emergencies. It is important to promote the benefits of merging these concepts. It is recommended to integrate HTA and IM, and seek support from HTA structures available in the country or develop one. [ABSTRACT FROM AUTHOR]

Copyright of Balikesir Health Sciences Journal / Balıkesir Sağlık Bilimleri Dergisi is the property of Balikesir Health Sciences Journal (BAUN Health Sci J) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The concept of "platform technology" gained prominence after the Ebola outbreak and since then has become essential to international vaccine (prophylactic vaccines against infectious disease) regulatory frameworks. Its significance was further amplified during the COVID-19 pandemic, where platform technology enabled the rapid development and approval of vaccines, optimizing regulatory processes, and enhancing global public health responses. As a transformative tool, platform technology streamlines product development, allowing for the reduction in the number of clinical trials or exemption from certain clinical trials and facilitating cross-referencing in regulatory submissions. Despite significant efforts to establish standardized regulatory procedures, challenges remain, particularly in achieving a unified definition and application of platform technology across regions. This paper explores the evolution, applications, and regulatory strategies of platform technology, with a focus on China's experience in this field. China's approach, encompassing risk assessment, and the expedited approval of emergency vaccines, offers valuable insights into global regulatory coordination. By analyzing China's regulatory contributions and international practices, this paper highlights the potential of platform technology to address future pandemics, including "Pathogen X", and underscores the importance of harmonizing global regulatory efforts to strengthen public health preparedness and response. [ABSTRACT FROM AUTHOR]

Preventive medicine has proven its long-term effectiveness and economic feasibility. Over the last century, vaccination has saved more lives than any other medical technology. At present, preventative measures against most infectious diseases are successfully used worldwide; in addition, vaccination platforms against oncological and even autoimmune diseases are being actively developed. At the same time, the development of medicine led to an increase in both life expectancy and the proportion of age-associated diseases, which pose a heavy socio-economic burden. In this context, the development of vaccine-based approaches for the prevention or treatment of age-related diseases opens up broad prospects for extending the period of active longevity and has high economic potential. It is well known that the development of age-related diseases is associated with the accumulation of senescent cells in various organs and tissues. It has been demonstrated that the elimination of such cells leads to the restoration of functions, rejuvenation, and extension of the lives of experimental animals. However, the development of vaccines against senescent cells is complicated by their antigenic heterogeneity and the lack of a unique marker. In addition, senescent cells are the body's own cells, which may be the reason for their low immunogenicity. This mini-review discusses the mechanisms of central and peripheral tolerance that may influence the formation of an anti-senescent immune response and be responsible for the accumulation of senescent cells with age. [ABSTRACT FROM AUTHOR]

Purpose: Using a community-engaged approach, we adapted a human immunodeficiency virus (HIV) prevention smartphone app, Transpire, to meet the HIV and sexually transmitted infection (STI) prevention needs of transgender men and other transmasculine people. We conducted a pilot study to assess the feasibility and acceptability of the app among participants in two cities in the southeastern United States. Methods: Participants were recruited online and through community partners. Eligible and consenting participants used the Transpire app for 3 months and completed surveys at the beginning and end of the follow-up period. Transpire gave participants access to HIV and STI prevention information; the ability to order HIV and STI at-home self-test kits, condoms, and lube; and mental health and substance use resources. The primary feasibility outcome was the System Usability Scale (SUS), which measures the usability of technology-based products. Results: Sixty participants were enrolled. Most were 18–24 years old (n=33, 55%) and identified as non-Hispanic white (n=46, 77%). The mean SUS score was 72.4, which meets established criteria for acceptability. Fifteen (32%) participants conducted an HIV test during the 3-month follow-up period and 2 (4%) initiated pre-exposure prophylaxis. Conclusions: Following a community-engaged adaptation process, the Transpire app was found to be acceptable in a pilot study conducted among transmasculine participants. These pilot data indicate that app-based interventions have the potential to increase awareness of and access to sexual health resources for transmasculine people. Additional studies will be needed to assess the efficacy of Transpire or similar apps to improve sexual health outcomes. [ABSTRACT FROM AUTHOR]

Copyright of Obere Extremitat is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing demand for reliable and safe Lithium-ion (Li-ion) batteries requires more accurate estimation of state of health (SOH) and remaining useful life (RUL) prediction. However, the inherent complexity and non-linear dynamics of Li-ion batteries present specific challenges to traditional methods of SOH modeling. Although particle filter (PF) techniques can handle nonlinear dynamics, they still face challenges, including particle degeneracy and loss of diversity, that reduce their ability to effectively model the nonlinear degradation mechanisms of batteries. To tackle these limitations, this paper presents a novel artificial intelligence-driven PF (AI-PF) technology for battery health modeling and prognosis. The main contributions of the AI-PF technique are as follows: (1) A novel dynamic sample degeneracy detection method is proposed to provide real-time assessment of particle weights so as to promptly identify degeneracy and improve computational efficiency. (2) An adaptive crossover and mutation strategy is proposed to reallocate low-weight particles and maintain particle diversity to improve modeling and RUL forecasting accuracy. The effectiveness of the AI-PF framework is validated through systematic evaluations carried out using benchmark models and well-recognized battery datasets. [ABSTRACT FROM AUTHOR]

Many countries around the world use health technology assessment (HTA) to inform reimbursement and pricing decisions. HTA is often split into two steps, called assessment and appraisal. While the term HTA itself has been defined by international consortia, there is heterogeneity in the way different stakeholders use the terms assessment and appraisal. This creates ambiguity regarding which activities are included in technology assessment. With the new EU HTA Regulation, the HTA community should urgently seek to clarify the distinction between assessment and appraisal, as the regulation aims to centralize the clinical part of technology assessment at the European level. Failure to clarify this terminology will put the ambition of the regulation such as increased efficiency and reduction in duplication at risk. In this article, we argue that the distinction between assessment and appraisal should be seen as a science/value dichotomy. We discuss the transition from centralized assessment activities to country-level appraisal, which should culminate in a categorization of the overall added benefit in a local context. Finally, we touch on the important dimension of uncertainty always present in medical decision making. [ABSTRACT FROM AUTHOR]

In recent years regenerative agriculture has attracted growing attention as a means to improve soil health and farmer livelihoods while slowing climate change. With this attention has come increased policy support as well as the launch of private sector programs that promote regenerative agriculture as a form of carbon farming. In the United States many of these programs recruit primarily in regions where large-scale commodity production prevails, such as the Great Plains. There, a decades-old regenerative agriculture movement is growing rapidly, but not due to the incentives offered by companies' carbon programs. On the contrary, farmers are adopting regenerative practices to cut their dependence on corporate agrochemical inputs and expertise, and to thereby achieve technology sovereignty. These practice changes often strain farmers' existing social relationships while drawing them into new and previously neglected ones, including the more-than-human relations necessary for building soil health. These new relationships and the knowledge they generate may in turn lead farmers to think differently about their own autonomy. These findings provide insight into farmers' skepticism of private sector carbon farming programs, and highlight the value of attention to the multiple types of relationship change that accompany and facilitate regenerative transitions. [ABSTRACT FROM AUTHOR]

This paper examines our collective exploratory research on Anthropology and Sociology students at Concordia University. As teaching faculty members at Concordia, we have all observed a significant shift in our student population over the past fifteen years. They appear to be more detached and less involved in their studies, a phenomenon that has piqued our collective curiosity. Our first insight into the possible reasons behind this shift came from Rob Beamish's The Promise of Sociology (2010), where he explored the relationship between technology and knowledge. Inspired by Beamish, we sought to understand the relationship between technology and students' performance. At the beginning of this research, we never imagined that the world would be under lockdown because of a pandemic (2020–2022) and forced to rely on technology; anyone teaching at the height of COVID-19 was obligated to use technology, which makes Beamish's argument an even more relevant place to start. Lastly, we delved into the potential impact of technology on students' health. [ABSTRACT FROM AUTHOR]

Copyright of Enfermería Neonatal is the property of Fundacion para la Salud Materno Infantil (FUNDASAMIN) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background/Objectives: The use of coercive measures (CMs) and security technologies (STs) in mental healthcare continues to raise ethical and practical concerns, affecting both patient and staff well-being. Mental health nurses (MHNs) and nursing students (NSs) play a key role in the decision-making process regarding these interventions. However, their attitudes, particularly toward STs, remain underexplored in Italy. This study protocol aims to introduce a new conceptual framework and investigate Italian MHNs' and NSs' attitudes toward CMs and STs in mental health settings. Additionally, it will explore the influence of sociodemographic and psychological factors, including stress, anxiety, depression, stigma, and humanization on these attitudes. Methods: The research will be conducted in two phases. Phase 1 involves a national survey of a convenience sample of MHNs and NSs to assess their attitudes and related factors. Phase 2 includes qualitative interviews with a purposive sample of MHNs and NSs to explore participants' perspectives on STs in more depth. Quantitative data will be analyzed using descriptive and inferential statistics, while qualitative data will be examined through thematic analysis. Conclusions: This study protocol seeks to enhance our understanding of MHNs' and NSs' attitudes toward the use of CMs and STs in mental health settings, identifying key factors influencing these attitudes. The findings aim to inform policy development, education programs, and clinical practices in both the Italian and international panoramas. Additionally, the proposed conceptual framework could guide future research in this field. [ABSTRACT FROM AUTHOR]

(1) Background: Urinary tract infections (UTIs) are caused by the proliferation of pathogenic microorganisms, and they are the second most common hospital-acquired infections, with catheter-associated UTIs (CAUTIs) accounting for about 40% of these nosocomial infections. This review aims to identify the impact of technology on preventing infections in patients with urinary catheters; (2) Methods: The search was conducted in April 2024 through the EBSCOhost platform, with access to the American Search Complete, CINHAL Ultimate, Medline databases, and through the Scopus database; (3) Results: In total were included eight articles in this review. Technology interventions can significantly reduce the incidence of CAUTIs, decrease the duration of catheter use, improve diagnosis, and enhance patient safety; (4) Conclusions: Technological advancements show significant benefits in reducing infection rates and improving patient outcomes, like shorter hospital stays and comfort. Multidisciplinary approaches and educational strategies are essential to maximize these benefits. [ABSTRACT FROM AUTHOR]

Head and neck reconstruction poses challenges requiring stable coverage and optimal appearance and functionality. In complex cases, and beyond the right choice of flap, Virtual Reality (VR) surgical software and preoperative planning, are needed to optimize outcomes. Our patient is a 16-year-old with a history of rhabdomyosarcoma necessitating maxillary-mandibular defect reconstruction. VR-based preoperative planning facilitated the intervention by creating 3D-VR models of facial anatomy and fibula, simulating resection margins, and creating surgical guides for intraoperative use. Our 2-team surgeons opted for a single-staged reconstruction using a vascularized fibula free flap. This case demonstrates successful single-flap reconstruction of a maxillary-mandibular defect, addressing challenges of recipient vessel scarcity, fibrotic scarring, and poor tissue quality. It also underscores the efficacy of a 2-team approach and VR-based preoperative planning in achieving successful outcomes in complex maxillary-mandibular reconstruction. The use of a single fibula flap minimized possible complications and operative time, and the 2-team approach helped by combining the expertise and training of craniofacial and microsurgical trained surgeons. Acknowledging limitations in imaging quality and real-time adaptability, we advocate for continued exploration of VR technologies in enhancing surgical precision in challenging cases. [ABSTRACT FROM AUTHOR]

Background The evolution of neuroendovascular technologies has progressed substantially. Over the last two decades, the introduction of new endovascular devices has facilitated treatment for more patients, and as a result, the regulatory environment concerning neuroendovascular devices has evolved rapidly in response. Objective To examine trends in the approval of neuroendovascular devices by the United States Food and Drug Administration (FDA) over the last 20 years. Methods Open-access US FDA databases were queried between January 2000 and December 2022 for all devices approved by the Neurological Devices Advisory Committee. Neuroendovascular devices were manually classified and grouped by category. Device approval data, including approval times, approval pathway, and presence of predicate devices, were examined. Results A total of 3186 neurological devices were approved via various US FDA pathways during the study period. 320 (10.0%) corresponded to neuroendovascular devices, of which 301 (94.1%) were approved via the 510(k) pathway. The percentage of 510(k) pathway neuroendovascular devices increased from 6.9% to 14.3% of all neuro devices before and after 2015, respectively. There was an increase in approval times for neuroendovascular devices cleared after 2015. Conclusion Over the last two decades, the neuroendovascular device armamentarium has rapidly expanded, especially after positive stroke trials in 2015. Regulatory approval times are significantly affected by device category, generation, company size, and company location, and a vast majority are approved by the 510(k) pathway. These results can guide further innovation in the endovascular device space and may act as a roadmap for future regulatory planning. [ABSTRACT FROM AUTHOR]

A brain-computer interface (BCI) serves as a direct communication channel between brain activity and external devices, typically a computer or robotic limb. Advances in technology have led to the increasing use of intracranial electrical recording or stimulation in the treatment of conditions such as epilepsy, depression, and movement disorders. This indicates that BCIs can offer clinical neurological rehabilitation for patients with disabilities and functional impairments. They also provide a means to restore consciousness and functionality for patients with sequelae from major brain diseases. Whether invasive or non-invasive, the collected cortical or deep signals can be decoded and translated for communication. This review aims to provide an overview of the advantages of endovascular BCIs compared with conventional BCIs, along with insights into the specific anatomical regions under study. Given the rapid progress, we also provide updates on ongoing clinical trials and the prospects for current research involving endovascular electrodes. [ABSTRACT FROM AUTHOR]

In 2020, the World Health Organization (WHO) estimated that 2.3 million women worldwide were diagnosed with breast cancer, which resulted in 685,000 deaths. According to the projections, the number of women who have been diagnosed with breast cancer over the last five years before and by the end of 2020 was expected to reach 7.8 million, making it the most common type of cancer worldwide. Early diagnosis could prevent the ailment, however, lack of availability of health facilities and the cost of accessing treatment, especially in developing nations, are among the challenges confronting the solution. With the advent of artificial intelligence and machine learning models, specifically Convolutional Neural Networks (CNNs), considering their multiple architectures is highly promising to address the challenge of early diagnosis. Therefore, this study aims to propose an architecture of CNNs that gives the best accuracy, F1 score, and Cohen Kappa score among the Custom Optimized CNN, ResNet, and EfficientNet architectures. From the results, ResNet's performance across the five metrics outweighs the other two architectures. While ResNet reported an accuracy, precision, and F1 score of 0.9987, 0.9934, and 0.9950, respectively, EfficientNet, which has the second performance, reported 0.9977, 0.9914, and 0.9939 as accuracy, precision, and F1 score, respectively. Therefore, the best-performing architecture can be deployed for other available breast cancer datasets in order to ensure its total efficiency. [ABSTRACT FROM AUTHOR]

With the continuous development and maturation of the era of intelligent manufacturing, there is a perpetual emergence of new information technology, control technology, and material technology, which are constantly accelerating 3D printing technology to advance to an unprecedented level. To achieve the safety perception interaction ability of auxiliary medical service robots, this study develops a direct write hybrid 3D printing auxiliary medical service robot system, enabling it to achieve temperature sensing function. Moreover, combined with linear interpolation algorithms, 3D printing technology has been improved to achieve improvement of system control accuracy. The results indicate that the apparent viscosity of the printing material Ag‐TPU is still greater than 2000 Pa s at a rate of 87 s−1. The change in resistance during 20% stretching is within 1.2 Ω, and the change is around 3 Ω during 30% stretching. When the preset temperature is 39.2°C, the absolute deviation is the smallest, about 0.03. When the preset temperature is 41.7°C, the maximum value is approximately 0.17. The absolute error of real‐time temperature collection for auxiliary medical service robots is less than 0.2°C at temperatures ranging from 38 to 42°C. Over the past 30 days of overall operation, the system has had 970 users, 3270 interactions, and 99.4% availability. This system improves the perception and interaction ability of auxiliary medical service robots, which has certain practical potential in the field of medical services. [ABSTRACT FROM AUTHOR]

Purpose: Surface electromyography (sEMG) has been used by speechlanguage pathologists (SLPs) as a biofeedback tool to enhance the benefits of dysphagia rehabilitation since as early as 1976. Despite being noninvasive and user-friendly, sEMG biofeedback is not widely adopted by clinicians, potentially due to challenges such as insufficient knowledge about its appropriate clinical applications and the burden of acquiring this technology for a busy clinician. This article aims to support SLPs in utilizing sEMG as a simple biofeedback tool for dysphagia management by providing an overview of the physiological and technological underpinnings of sEMG as well as practical guidance on interpreting sEMG signal, optimizing signal quality, and documenting findings at the end of a session. Moreover, the article emphasizes the vital role clinicians have in promoting ongoing innovation in their field by advocating for modern solutions. It provides a framework and examples of how to request technologies in the clinic to foster an environment of continuous improvement in the service provided to patients. Conclusion: This article aims to equip clinicians with the knowledge and skills necessary to utilize sEMG technology effectively and help their patients achieve optimal outcomes in dysphagia management. [ABSTRACT FROM AUTHOR]

Background: Cost-utility analysis typically relies on preference-based measures (PBMs). While generic PBMs are widely used, disease-specific PBMs can capture aspects relevant for certain patient populations. Here the EORTC QLU-C10D, a cancer-specific PBM based on the QLQ-C30, is validated using Dutch trial data with the EQ-5D-3L as a generic comparator measure. Methods: We retrospectively analysed data from four Dutch randomised controlled trials (RCTs) comprising the EORTC QLQ-C30 and the EQ-5D-3L. Respective Dutch value sets were applied. Correlations between the instruments were calculated for domains and index scores. Bland–Altman plots and intra-class correlations (ICC) displayed agreement between the measures. Independent and paired t-tests, effect sizes and relative validity indices were used to determine the instruments' performance in detecting clinically known-group differences and health changes over time. Results: We analysed data from 602 cancer patients from four different trials. In overall, the EORTC QLU-C10D showed good relative validity with the EQ-5D-3L as a comparator (correlations of index scores r = 0.53–0.75, ICCs 0.686–0.808, conceptually similar domains showed higher correlations than dissimilar domains). Most importantly, it detected 63% of expected clinical group differences and 50% of changes over time in patients undergoing treatment. Both instruments showed poor performance in survivors. Detection rate and measurement efficiency were clearly higher for the QLU-C10D than for the EQ-5D-3L. Conclusions: The Dutch EORTC QLU-C10D showed good comparative validity in patients undergoing treatment. Our results underline the benefit that can be achieved by using a cancer-specific PBM for generating health utilities for cancer patients from a measurement perspective. [ABSTRACT FROM AUTHOR]

The integration of Artificial Intelligence (AI) into healthcare represents a transformative shift, offering opportunities for enhancing patient care, diagnostic accuracy, process optimization and treatment pathways. This research sets out to forge a strategic management decision support framework for leveraging AI within the healthcare sector, aimed at systematically exploring and integrating AI innovations to bolster the patient health outcomes. By creating a comprehensive categorization system, we attempt to navigate the complex array of possible AI applications within the field of healthcare, hence enabling the identification, selection, and advancement of AIdriven initiatives. Through a blend of systematic literature review and expert insights, this study maps possible AI applications across dimensions like 'medical disciplines', 'healthcare processes', 'AI research areas', and 'user groups'. By reflecting the diverse perspectives, this system transcends mere classification and stands as a cornerstone for identifying, selecting, and developing AI-driven medical use cases to guide strategic implementations of AI within clinical settings. This multidimensional system offers a blueprint for healthcare entities to strategically navigate the AI landscape, enabling them to make informed decisions about technology adoption and change management processes, ultimately leading to improved patient care and operational efficiency. [ABSTRACT FROM AUTHOR]

In vitro test setups for simulated application testing are necessary for physician training as well as for development and benchmarking of various devices in interventional neuroradiology. Within the current study, we implemented a test setup for in vitro simulated application testing. Trackability in the distal catheter area, which was positioned inside a complex 3D vascular model was analyzed for two neurovascular stent systems (Neuroform EZ 4.0x20 mm and Enterprise VRD 4.5x14 mm) combined with different microcatheters (Excelsior XT-27 Flex, PX Slim Delivery Microcatheter and Prowler Select Plus Infusion Catheter). The described test setup allows for a diffentiation of neurovascular stent systems with regard to the trackability force as a major procedure related indicator for device handling. Therefore, the simulated application system presented within the current work represents an indispensable tool for safely and efficiently developing and evaluating new technologies for interventional neuroradiology prior to clinical implementation. [ABSTRACT FROM AUTHOR]

This paper introduces the Transformative Philosophy (T:Phil) program, an initiative designed to embed ethical and socio-political literacy into the technological development process. T:Phil, developed within the Digitalized Lifeworld research cluster and in partnership with leading international technology reflection experts, provides a comprehensive framework for integrating philosophical insights with technical expertise. Aimed at decision-makers in the tech industry, T:Phil delivers tailored content through modular series such as Re:Thinking Technology, which challenge participants to reconsider their approaches to AI, digital infrastructures, and our language of technology. The paper highlights two key modules of the T:Phil program: The first, AI in an Atlas-View, promotes a holistic understanding of AI by examining its technical, human, and environmental aspects. This module encourages participants to view AI as a complex socio-technical ensemble rather than merely a technical innovation. The second module, AI as a Metaphor, explores the metaphorical language used to describe AI, fostering critical awareness of how these metaphors shape our perceptions and influence the ethical considerations of AI deployment. Through innovative delivery methods, including hybrid keynote- discussion events, short series, and intensive Thinkathons, T:Phil engages technical professionals in reflective practices that enhance their understanding of technology's - especially AI's - broader implications. The program aims to help cultivate a new cadre of ethically and philosophically informed tech experts capable of designing AI systems that promote equitable and just outcomes. This paper briefly introduces the T:Phil program and provides examples of its application, demonstrating its potential to transform the way we integrate ethical reflection into technology development. [ABSTRACT FROM AUTHOR]

Additive manufacturing with Arburg Plastic Freeforming (APF), an extrusion-based additive manufacturing process, was used to produce biomimetic bone scaffolds for assistance of osteosynthesis made of poly-caprolactone (PCL) with channel structures for the ingrowth of blood vessels. The specific creation of defined channel structures is very important to support the ingrowth of blood vessels, which significantly supports the regeneration of natural tissue. The tibia model used was divided into the corticalis and the spongiosa to be able to compare the realization of the different requirements of the two natural structures with the printed structures separately. Microtome cuts of the manufactured bone scaffolds with channels were prepared for characterization with light microscopy. Compression tests were carried out on a tensile testing machine. It was found that the channels in the tibial cortex led to a slightly higher stiffness compared to those without channels due to the frame outlines. Overall, however, the stiffness of the Polycaprolactone (PCL) scaffolds was significantly lower than that of natural bone. In the spongiosa scaffolds, the stiffness with channels was lower than that without channels, but still within the physiological range, as was the model without channels. The porosity was within the required range for both scaffold types. [ABSTRACT FROM AUTHOR]

It is recognized that teaching and embracing entrepreneurial skillsets lead to more valuable and impactful innovations in biomedical engineering. Unfortunately only very few institutions globally have started to integrate innovation generation methods and entrepreneurial mindset development in their curricula. A novel approach was developed and tested for the IEEE CASS society. A 6 week online training program was developed (30 videos, worksheets, deliverables, and regular tests) and subsequently advertised leading the participants, accompanied by weekly personal guidance, to create a real innovation project. This was embedded in a competition to allow the best teams to receive funding to be able to attend the annual society conference and participate in a competition. The learners all reported a changed mindset towards innovation generation and the presented results were stimulating and exciting. The paper provides details on the free training program and shows some of the results. This could - and maybe should - become a standard training and program event point at future biomedical engineering conferences. [ABSTRACT FROM AUTHOR]

The European Artificial Intelligence Act (AI Act) has profound implications for technological innovation in the medical and health care sector, transcending the boundaries of existing legal frameworks such as the Medical Device Regulation (MDR) and the General Data Protection Regulation (GDPR). This paper examines basic regulatory choices of the AI Act relevant for the field of digital health innovations by contextualizing its main goals, key obligations, and addressed actors. In light of these considerations, we present a scoping literature review that identifies potential regulatory challenges for stakeholders engaged in research, innovation and healthcare. Building on this, we point to concepts and methodologies to overcome such challenges in a way fostering innovation while realizing key constitutional and societal interests at the same time. [ABSTRACT FROM AUTHOR]

Functionality of state-of-the-art medical devices often depends on high-end materials. Today, a large spectrum of medical devices like heart valves, vascular grafts, sutures or endoscopic devices consist of or incorporate fluoropolymers like polytetrafluoroethylene (PTFE). Fluoropolymers offer unique mechanical, electrical and chemical properties. Based on their chemical constitution, fluoropolymers are assigned to the group of per- and polyfluorinated substances (PFAS). The aim of the current restriction proposal within Europe (EU) is to limit and/or fully ban the persistent PFAS substances known as forever chemicals. The restriction proposal concerns all PFAS substances beyond further subdividing and evaluating their hazardous potential and with just short-term derogations depending on the application. The consequences of the impending restriction proposal on PFAS is shown from a medical device industry viewpoint. Literature data on annual material consumption and supply chain are collected and evaluated, especially pointing to future problems assuming an entry into force of the pending restriction proposal. Furthermore, the short derogation times are contextualized with current timelines of Medical Device Regulation (MDR) approval processes to highlight the impact on product availability assuming a PFAS ban. Selected examples of affected products illustrate, how patient treatment options are limited by the PFAS restriction. It can be clearly shown that the PFAS restriction will critically affect the medical device sector through collapsed supply chain and insufficient derogation times for product approvals, thus limiting the availability of medical products and setting back the gold standards in medical treatment. [ABSTRACT FROM AUTHOR]

Inpatient care facilities globally are facing a critical shortage of staff, posing significant challenges to resident well-being and care quality. This issue is further compounded by demographic shifts and increasing care demands. While technological advancements offer promise in alleviating nursing staff burdens, their effective integration remains complex, with nursing staff acceptance playing a pivotal role. This paper describes a systematic approach designed to streamline the process of identifying, categorizing, and prioritizing suitable technologies in inpatient care settings. By taking into account the specific needs and requirements of nursing staff, this approach, validated through a comprehensive case study, aims to facilitate targeted technology adoption, thereby contributing to the successful digitization of this occupational domain. [ABSTRACT FROM AUTHOR]

Goal: This paper investigates using Low-Rank Adaptation (LoRA) to adapt large vision models (LVMs) pretrained with self-supervised learning (SSL) for lung nodule malignancy classification. Inspired by LoRA's success in the field of Natural Language Processing, we hypothesized that such an adaptation technique can significantly improve classification performance, parameter efficiency, and training speed for the novel application of lung image cancer diagnostic. Methods: Utilizing two comprehensive lung nodule datasets, NLSTx and LIDC, which together encompass a diverse array of biopsy- and radiologist-confirmed lung CT scans, our rigorous experimental setup demonstrates that LoRA-adapted models markedly surpass traditional fine-tuning methods. Results: The best LoRA-adapted model achieved a 3% increase in ROC AUC over the state-of-the-art model, utilized 89.9% fewer parameters, and reduced training times by 36.5%. Conclusions: Integrating LoRA with out-of-domain pretrained LVMs offers a promising avenue for enhancing performance of lung nodule malignancy classification. The annotations for the NLSTx dataset are also released with this paper on GitHub at https://github.com/benVZ/NLSTx.

Epilepsy patients with drug-resistant seizures emanating from two or more distinct regions of left and right hemispheres are the primary candidates for neurostimulation treatment. Stereo-electroencephalography (SEEG) is a minimally invasive technique to monitor and evaluate brain activities during seizures before stimulator implantation. This work proposes a seizure network modeling method using SEEG to analyze the functional connectivity of epileptogenic zone during bilateral seizures. Network nodes are selected subset of SEEG contact points, and network edges are directed signal correlations calculated from directed transfer function. Based on signal directionality, four connectivity values are extracted to measure the intra- and inter-activities that are within or between the left and right hemispheres, respectively. Statistical difference between connectivity values is used to quantify the seizure impact of each hemisphere. A subset of network nodes is selected from impactful side as stimulation target candidates. Experimental results are validated on ten patients having different seizure types with bilateral onset. Each seizure type has specific connectivity patterns that show different importance from each brain side. Selection of neurostimulation targets from primary side are consistent with clinicians’ decision. Relationships are found among connectivity differences, seizure types and stimulation outcomes. Using SEEG signals, we can capture specific connectivity differences associated with bilateral seizure networks. Such differences are related with corresponding neurostimulation targets and stimulating outcomes. The proposed work elucidates the difference of network connectivity for bilateral patients, and assists clinicians to choose the stimulation targets and to predict the potential outcomes.

Mastication plays an important role in effective food digestion and nutrient absorption. Therefore, regulating masticatory force in people with declining mastication function is significant for maintaining health and quality of life. In this study, we tested the effect of tactile augmentation on mastication force. To augment tactile feedback during mastication, we applied closed-loop electrical stimulation onto the mandibular vestibule using an intraoral tooth-borne electronic system. We hypothesized that closed-loop electrical stimulation, timed with mastication and applied to the nerves delivering tactile feedback to the brain, would evoke an increase in masticatory force. Experiments were completed using the intraoral system with six healthy human subjects who masticated soft and hard foods with and without stimulation during the experiment. Their mastication forces were recorded ten times per condition. The recorded mastication force profile showed that mastication force was higher with the harder food. Also, mastication force increased when electrical stimulation was applied, compared to the non-stimulated condition. These results support the hypothesis that tactile augmentation by intraoral closed-loop electrical stimulation will increase masticatory force. Other mastication parameters including period, spike width, and duty cycle are also changed by electrical stimulation. Further, stimulation left a strong aftereffect on these mastication parameters.

Previous studies have validated that different balance tasks induce different cortical responses, which are key indexes of balance assessment. Assessing balance is crucial for stroke survivors to prevent falls and improve rehabilitation outcomes. However, it was unclear whether these tasks may affect the balance assessment, particularly regarding the relationship between task difficulty and the corresponding cortical responses involved in balance control. Therefore, we sought to explore the effects of different challenge-level balance tasks on balance assessment. Eighteen participants with stroke and thirteen healthy individuals were recruited in this study. The EEG was collected during sitting, standing and perturbation tasks. The pairwise-derived Brain Symmetry Index (pdBSI), and Granger Causality (GC) were analyzed with a two-way (task $\times $ group) RMANOVA. Finally, a multiple linear regression analysis was applied to predict the BBS score with the above parameters. We found a significant interaction effect on pdBSI and GC. In the frontal lobe, participants with stroke exhibited significantly higher pdBSI (standing: p =0.042, perturbation: p =0.013) and lower GC (standing: p $^{{2}}=0.938$ ) and perturbation tasks (p =0.001, adjusted R $^{{2}}=0.644$ ). It was discovered that the more challenging balance tasks better revealed the difference in the power distribution and the directional functional connection between groups. The pdBSI and GC during standing and perturbation tasks, could be used as biomarkers for stroke balance assessment.

Most commercially available foot prostheses are passive ESR feet, which store and release energy to reduce metabolic costs and improve comfort but cannot adjust to varying walking conditions. In contrast, bionic feet adapt to different tasks but are hindered by high weight, power consumption, and cost. This paper presents MyFlex- $\zeta $ , an ESR foot with a variable stiffness system, as a compromise between these two categories. MyFlex- $\zeta $ adjusts stiffness by varying the sagittal-plane distance between two key points, altering force interactions within the prosthesis and affecting overall stiffness. Clinical tests with three transfemoral amputees evaluated stiffness variation across two sessions: the first subjective, where participants assessed stiffness settings during different tasks, and the second biomechanical, measuring performance parameters. Two participants selected different stiffness settings for various tasks, while the third, with limited perception of stiffness changes, showed less distinction in outcomes. Greater sagittal-plane rotation and higher energy absorption were observed in most tasks with more compliant settings, although one participant’s results were limited due to selecting close stiffness settings. Overall, these findings suggest MyFlex- $\zeta $ offers adaptability and performance improvements over traditional ESR feet. With further actuation and control system development, MyFlex- $\zeta $ could mark significant progress in prosthesis technology.

Background: Identification of hemoglobin (Hb) variants is valuable in clinical testing. A common issue with conventional methods for identifying Hb variants is their subpar ability to provide structural breakdowns of the variants. Reports have surfaced of high-resolution mass spectrometry (HR-MS) methods that improve on traditional methods; however, ambiguities may arise without separation of Hb subunits prior to HR-MS analysis. Methods: We report a liquid chromatography-high-resolution mass spectrometry (LC-HR-MS) method to separate several pairs of normal and variant Hb subunits with mass shifts of less than 1 Da and successfully identify them in intact-protein and top-down analyses. LC separation was facilitated by a C4 reversed-phase column. Results: Seven heterozygous Hb variant samples (Hb C with α-thalassemia trait, Hb E, Hb D-Punjab, Hb G-Accra, Hb G-Siriraj, Hb Tarrant, and Hb G-Waimanalo) were selected to demonstrate the LC separation of Hb variant and normal subunits with mass shifts of less than 1 Da. The analytes could be explicitly observed in the deconvoluted MS1 mass spectra. The top-down analysis matched the amino acid sequences of the correct Hb variant subunits. Conclusions: The LC-HR-MS method described can effectively separate and identify Hb subunits, especially when the variant subunits have mass deviations of less than 1 Da from their corresponding normal subunits. With further evaluation to prove the clinical utility, the HR-MS methods including CE-HR-MS have the potential to complement or partially replace conventional methods of Hb variant identification in clinical laboratories.

Active brain-computer interface (BCI) provides a natural way for direct communications between the brain and devices. However, its detectable intention is very limited, let alone of detecting dual intentions from a single electroencephalography (EEG) feature. This study aims to develop time-based active BCI, and further investigate the feasibility of detecting time-movement dual intentions using a single EEG feature. A time-movement synchronization experiment was designed, which contained the intentions of both time (500 ms vs. 1000 ms) and movement (left vs. right). Behavioural and EEG data of 22 healthy participants were recorded and analyzed in both the before (BT) and after (AT) timing prediction training sessions. Consequently, compared to the BT sessions, AT sessions led to substantially smaller absolute deviation time behaviourally, along with larger high-frequency event-related desynchronization (ERD) in frontal-motor areas, and significantly improved decoding accuracy of time. Moreover, AT sessions achieved enhanced motor-related contralateral dominance of event-related potentials (ERP) and ERDs than the BT, which illustrated a synergistic relationship between the two intentions. The feature of 20–60 Hz power can simultaneously reflect the time and movement intentions, achieving a 73.27% averaged four-classification accuracy (500 ms-left vs. 500 ms-right vs. 1000 ms-left vs.1000 ms-right), with the highest up to 93.81%. The results initiatively verified the dual role of high-frequency (20–60 Hz) power in representing both the time and movement intentions. It not only broadens the detectable intentions of active BCI, but also enables it to read user’s mind concurrently from two information dimensions.

High-risk infants in the neonatal intensive care unit often encounter the problems with hemodynamic instability, and the poor blood circulation may cause shock or other sequelae. But the appearance of shock is not easy to be noticed in the initial stage, and most of the clinical judgments are subjectively dependent on the experienced physicians. Therefore, how to effectively evaluate the neonatal blood circulation state is important for the treatment in time. Although some instruments, such as laser Doppler flow meter, can estimate the information of blood flow, there is still lack of monitoring systems to evaluate the neonatal blood circulation directly. Based on the technique of near-infrared spectroscopy, an intelligent neonatal blood perfusion assessment system was proposed in this study, to monitor the changes of hemoglobin concentration and tissue oxygen saturation simultaneously and further estimate the neonatal blood perfusion. Several indexes were defined from the changes of hemoglobin parameters under applying and relaxing pressure to obtain the neonatal perfusion information. Moreover, the neural network-based classifier was also used to effectively classify the groups with different blood perfusion states. From the experimental results, the difference between the groups with different blood perfusion states could exactly be reflected on several defined indexes and could be effectively recognized by using the technique of neural network. Clinical and Translational Impact Statement—An intelligent neonatal blood perfusion assessment system was proposed to monitor the changes of hemoglobin concentration and tissue oxygen saturation simultaneously and further estimate the neonatal blood perfusion (Category: Preclinical Research)

Recordings of electrical activity from muscles allow us to identify the activity of pools of spinal motor neurons that send the neural drive for muscle activation. Decoding motor unit and motor neuron activity from muscle recordings can be performed by high-density (HD) electrode systems, both non-invasively (surface, HD-sEMG) and invasively (intramuscular, HD-iEMG). HD-sEMG recordings are obtained by grids placed on the skin surface while HD-iEMG signals can be acquired by micro-electrode arrays. While it has been shown that HD-iEMG allows the accurate decoding of a larger number of motor units when compared to HD-sEMG, the dependence of motor unit yield on the parameters of the micro-electrode arrays is still unexplored. Here, we used recently developed HD-iEMG electrodes to record from hundreds of recording sites within the muscle. This allowed us to investigate the impact of electrode number, inter-electrode distance, and the number of muscle insertions on the ability to sample motor units within the muscle. Specifically, we recorded both HD-sEMG and HD-iEMG from the Tibialis Anterior muscle of two healthy subjects at various contraction intensities (10%, 30%, and 70% of maximum voluntary contraction, MVC). For the first time, we present intramuscular recordings with more than 140 electrodes inside a single muscle, achieved through multiple implants of high-density micro-electrode arrays. Through systematic offline analyses of these recordings, we tested different electrode configurations to identify optimal setups for accurately capturing motor unit activity. The results revealed that the density of electrodes in the micro-electrode arrays is the most critical factor for maximising the number of identified motor units and ensuring very high accuracy. Comparisons between intramuscular and surface recordings also confirmed that HD-iEMG consistently captures larger and more stable numbers of motor units across subjects and contraction levels. These results underscore the potential of HD-iEMG as a powerful tool for both clinical and research settings, particularly when precise motor unit decomposition is crucial.

It is evident that voluntary effort plays a crucial role in electrical stimulation rehabilitation, facilitating neuroplasticity enhancement in patients with neurological disorders. In this paper, we present a multichannel system designed for simultaneous functional electrical stimulation (FES) and volitional EMG (vEMG) acquisition using shared electrodes. The system employs hardware blanking with electrodes shorting to suppress stimulation artifacts and accelerate residual charge dissipation. Additionally, we adapt the Savitzky-Golay filter to extract high-quality, real-time vEMG from FES-contaminated signals, with the optimal filter parameters for different stimulation and blanking periods determined using a genetic algorithm and semi-synthesized signals. Simulation and experimental results confirm that the proposed system ensures robust and high-quality vEMG acquisition, even under varying parameters and across different individuals. In summary, this work advances the development of closed-loop rehabilitation applications and enables further investigation of neuromuscular characteristics under FES.

Spinal reflex circuitry-based controllers have shown promising capabilities in controlling the biomechanics of locomotion in simulation. Studies have been done to tune or identify reflex circuitry from imposed objectives, such as metabolic energy efficiency, maintaining balance or mimicking experimental data. However, in those works, the reflex structure was predefined by the authors. This may limit the generalizing capabilities of such circuits and prevent a better understanding of the dominant reflex loops in human locomotion. In this work we propose an identification framework that can identify personalized sparse-structure reflex circuitry directly from experimental data. This is achieved by first performing muscle model personalization via optimization and consequently extensive model regularization when optimizing a densely connected neural reflex network. Trajectory optimization is used in both steps, namely direct collocation formulated as a non-linear program. Multi-speed walking and running data of five subjects was used to test the framework. Results show that personalized sparse reflex circuitry was identified that show exceptional torque and muscle activation reproduction for multiple walking speeds with a speed-independent, but phase-dependent, reflex network. Furthermore, similar sparse structures were found between subjects, but different structures between walking and running gait. However, due to the use of data of unperturbed locomotion, the actual plausibility of the found circuitry remains an open question. The controllers use slightly more reflex gain parameters than those chosen and designed in other studies, but the benefit of our method is that the structures were found automatically.