Transformation Approach Research Articles

Revolutionizing Healthcare Information Systems through Blockchain Technology

Integrating blockchain technology in healthcare represents a transformative approach to addressing critical data security, interoperability, and patient privacy challenges. This comprehensive article examines the implementation of blockchain solutions across various healthcare domains, including clinical trials, pharmaceutical supply chains, and personalized medicine. The technology's distributed ledger architecture enables secure patient data sharing, enhances clinical trial management, and revolutionizes pharmaceutical supply chain oversight. Blockchain demonstrates significant potential in improving healthcare delivery efficiency through smart contracts and consensus mechanisms while maintaining regulatory compliance. The article explores the transformative benefits and implementation challenges, highlighting the technology's role in advancing patient-centric care and medical research while addressing concerns regarding scalability, system integration, and regulatory requirements.

A Transformative Leadership Approach to Public Education in South Africa

Leadership at the school level is vital for creating a positive learning environment, guiding transformative practices, and fostering collaboration among staff, students, and the community to achieve success and overall school improvement.

Motivational interviewing: a framework for healthcare assistants to improve patient-centred care

Healthcare assistants are integral to patient care in the UK healthcare system, and often the first point of contact for patients to access care. This article explores the application of motivational interviewing as a transformative approach for healthcare assistants to foster patient engagement and wellbeing. Motivational interviewing is a patient-centred and goal-oriented communication method that addresses ambivalence and resistance, empowering patients to make informed health decisions. By embracing the principles of the approach, which are capability, opportunity and motivation, healthcare assistants can shift from directive methods to a collaborative partnership model.

Transformative Islamic Education Management in Responding to Environmental and Humanitarian Challenges in the Digital Age

Transformative Islamic education has an important role in responding to environmental and humanitarian challenges in the digital era. In this dynamic and rapidly changing era, a transformative approach in the management of Islamic education is very necessary to ensure that students are able to face the changes that occur wisely and sustainably. Transformative Islamic education teaches Islamic values that prioritize support for the environment and humanity. Through this approach, it is hoped that students can become agents of change who are responsible for protecting the environment and solving various humanitarian problems that exist in the world today. One of the environmental problems that is the main focus in transformative Islamic education is plastic waste. Plastic waste is a serious environmental problem with significant negative impacts on human life and other living things on earth. This research is library research, analyzed qualitatively using inductive thinking methods. The findings of this research are that, with a transformative approach, students are taught to care about the surrounding environment and understand the importance of preserving nature. Apart from that, transformative Islamic education also teaches the importance of empathy and concern for fellow humans. In this fast-paced and individualistic digital era, the values of caring for others are often neglected. Through a transformative approach, students are taught to be sensitive to the suffering of fellow humans and try to help others.

Polymers for mRNA Delivery.

mRNA delivery has emerged as a transformative approach in biotechnology and medicine, offering a versatile platform for the development of novel therapeutics. Unlike traditional small molecule drugs or protein-based biologics, mRNA therapeutics have the unique ability to direct cells to generate therapeutic proteins, allowing for precise modulation of biological processes. The delivery of mRNA into target cells is a critical step in realizing the therapeutic potential of this technology. In this review, our focus is on the latest advancements in designing functional polymers to achieve efficient mRNA delivery. Biodegradable polymers and low molecular weight polymers in addressing the balance in mRNA binding and release are summarized. Benefiting from the excellent performance of lipid nanoparticles in mRNA delivery, polymer/lipid hybrid nanostructures are also included. Finally, the challenges and future prospects in the development of polymer-based mRNA delivery systems are discussed.

Optimizing keratoconus treatment with AI‐driven lenticule matching using pentacam indices

Aims/Purpose: The aim of this study is to develop an advanced artificial intelligence (AI) methodology to optimize the matching of donor and recipient lenticules for the treatment of keratoconus. This approach leverages Pentacam indices related to corneal thickness and topography to minimize the preparatory modifications required for stromal lenticule implantation.Methods: We will construct a comprehensive database of donor and recipient lenticules by systematically collecting Pentacam‐derived indices, including central corneal thickness (CCT), anterior and posterior corneal elevation, and corneal curvature, at preoperative, intraoperative, and postoperative stages. Using these datasets, an AI algorithm capable of identifying the most compatible lenticule pairs will be trained and validated. The algorithm's performance will be assessed based on its accuracy in predicting optimal matches and the practical effectiveness of the process.Results: As this project is in its preliminary phase, no results are currently available. However, we hypothesize that the AI‐assisted matching system will significantly enhance the compatibility of donor and recipient lenticules. Expected outcomes include increased postoperative central corneal thickness, improved corrected distance visual acuity (CDVA), and reduced corneal irregularity.Conclusions: This study aims to validate the potential of AI‐assisted matching of donor and recipient lenticules using Pentacam indices as a transformative approach in the treatment of keratoconus. By refining the customization process, we anticipate improvements in surgical efficiency and patient outcomes.

Dynamic Modeling and Configuration Transformation of Origami with Soft Creases

Origami has attracted much attention from scientists and engineers in recent years. Classic origami only permits rotations around creases, while origami-like structures in nature can also undergo a certain degree of extension at creases. In this paper, an earwig-inspired origami with rotational symmetry is proposed and analyzed by introducing soft creases. Such a soft crease is equivalent to a combination of a rotational spring and an extensional spring. The motion of the earwig-inspired origami is described using spherical triangles. Based on Lagrange's Equation, the nonlinear dynamic equation of the system is formulated. It is then solved by using the fourth-order Runge-Kutta method. The results of theoretical calculations are consistent with those of simulations in ADAMS. With the established framework, the bifurcation behaviors of the equilibria of the proposed system, including supercritical pitchfork and saddle-node bifurcations, are investigated. Such origami can realize both mono-stable and bi-stable mechanisms, while the corresponding design parameters are demonstrated in the design map. In particular, the properties of the bi-stable origami can vary with different equilibria. The configuration transformation could be achieved using a continuous excitation. However, it is sometimes sensitive to the initial conditions. Inspired by the working mechanism of earwig wings, a simple control approach for origami configuration transformation is proposed. The key is to stop exciting the origami when its deformation crosses an energy barrier. This work lays a foundation for the design and study of novel multi-stable and morphing structures and provides an efficient approach for their configuration transformation.

Developing soil quality indices to investigate degradation impacts of different land use types in Northern Ethiopia.

Assessing soil quality is imperative to diagnose soil functioning and recognize inappropriate soil managements. However, the absence of defined indicators and their scoring methods and lack of universally accepted soil quality indexing frameworks complicate soil quality assessment, given soil systems complexity and diversity caused by variation in soil formation factors. This study was aimed to assess soil quality of three land use managements (CL, cropland; GR, grassland; SL, shrubland) in Northern Ethiopia, using two data sets (Total data set (TDS) and minimum data set (MDS)), linear and non-linear indicator transformation techniques and three indexing scenarios (Additive (SQIa), nemoro (SQIn) and weighted additive (SQIw)). To screen MDS and TDS members, one-way analysis of variance and principal component analysis were applied. Twenty-two soil indicators responsible to changes in land use were screened as members of TDS. Four indicators (silt, mean weight diameter, visual evaluation of soil structure, and exchangeable calcium) were selected to establish MDS. The study results demonstrated a clear impact by land use managements to SQ in the study area. In all cases, CL soils scored significantly lower SQI values than those of GL and SL. Moderate (III) and low (IV) quality grade soils have the largest spatial share in the area. Soil organic carbon and structural stability were found to be the most important indicators explaining soil quality and its spatial variability. Overall, it was demonstrated by the study that soil quality deterioration is a serious issue particularly for soils in CL and GL, suggesting the essentiality to consider revisions and improvements in soil management. A positive and significant correlation was demonstrated among SQIs, revealing that all SQIs were sensitive to measure land use management impacts to soil quality. However, SQI was estimated and differentiated better when using non-linear indicator transformation and MDS indicator selection approach in the SQIw (SQI_NLw_MDS) than other SQIs, and thus was suggested for future soil quality studies in areas of similar soil and climate environments.

Noncoding RNA Lipotherapeutics: A Promising Breakthrough in Pulmonary Hypertension Treatment.

Pulmonary Hypertension (PH) is a complex cardiovascular disorder characterized by elevated blood pressure in the pulmonary arteries. Current therapeutic approaches for PH have limitations in addressing the underlying molecular mechanisms. This article explores the potential of noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), delivered through Lipid-Based Nanoparticles (LNPs) as a novel treatment strategy. These ncRNAs play critical roles in regulating vascular function and are implicated in PH pathogenesis. LNPs provide a promising method for the efficient and targeted delivery of ncRNAs. Advances in LNP technology, including the incorporation of R8 peptide modification, have shown promise in enhancing the delivery and efficacy of ncRNAs in PH models. Challenges such as biocompatibility, toxicity, and precise targeting must be addressed as these therapies move toward clinical application. The potential of personalized medicine and the integration of artificial intelligence in LNP design are discussed as prospects. In conclusion, ncRNA lipotherapeutics delivered via LNPs offer a transformative approach to treating PH, potentially leading to more effective management and improved patient outcomes in the future. However, continued research and clinical trials are necessary to fully realize their therapeutic potential in the field of PH treatment.

Micro-Electro Nanofibrous Dressings Based on PVDF-AgNPs as Wound Healing Materials to Promote Healing in Active Areas.

The purpose of this study is to develop an innovative solution for chronic wounds in high-mobility areas, such as joints, where conventional treatments are hindered by passive healing mechanisms and the need for immobilization. By designing a micro-electro-Nanofiber dressing composed of piezoelectric polyvinylidene fluoride (PVDF) integrated with antimicrobial silver nanoparticles (AgNPs), this research aims to address the dual challenges of promoting effective wound healing and maintaining joint mobility. Herein, we developed a novel micro-electro-Nanofiber dressing using electrospinning technology, incorporating polyvinylidene fluoride (PVDF) with silver nanoparticles (AgNPs). The optimized PVDF-AgNPs Nanofiber dressings exhibited strong piezoelectric effects suitable for joint wounds. In vitro experiments demonstrated that the dressing effectively promoted fibroblast migration and collagen synthesis. In vivo, the dressing exhibited a trend of rapid healing in infected wounds within 12 days while modulating macrophage differentiation toward the anti-inflammatory M2 phenotype. Additionally, the incorporation of antimicrobial nanosilver effectively controlled local infections, further facilitating the healing process. To sum up, by harnessing the piezoelectric effect to stimulate endogenous healing mechanisms without restricting joint mobility, the developed PVDF-AgNPs Nanofiber dressings represent a transformative approach for the treatment of wounds in highly mobile body areas.

Beyond Averaging: A Transformer Approach to Decoding Event Related Brain Potentials.

The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. Traditional methods involve averaging the EEG signal of multiple trials to extract valuable neural signals from the high noise content of EEG data. However, this averaging technique may conceal relevant information. Our investigation focuses on determining whether a transformer-based deep learning approach, specifically utilizing attention maps, an essential component of transformer networks, can provide deeper insights into ERP data compared to traditional averaging-based analyses. We investigated the data of an experiment on loudness perception. In the study, 29 normal-hearing participants between 18 and 30 years were presented with acoustic stimuli at five different sound levels between 65 and 95 dB and provided their subjective loudness rating, which was categorized as "too loud" and "not too loud". During the sound presentation, EEG signals were recorded. A convolutional transformer was trained to categorize the EEG data into the two classes ("not too loud" and "too loud"). The classifier exhibited exceptional performance, achieving over 86% accuracy and an Area under the Curve (AUC) of up to 0.95. Through the utilization of the trained networks, attention maps were generated. Those attention maps provided insights into the time windows relevant for classification within the EEG data. The attention maps above all showed a focus on the time window around 150 to 200 ms, where the average based analysis did not indicate relevant potentials. Employing these attention maps, we were able to gain new perspectives on the ERPs, discovering the attention maps potential as a tool for delving deeper into the analysis of event-related potentials.

Small cell lung cancer unveiled: Exploring the untapped resource of circulating tumor cells-derived organoids.

Small cell lung cancer (SCLC) remains a challenge in oncology due to its aggressive behavior and dismal prognosis. Despite advances in treatments, novel strategies are urgently needed. Enter liquid biopsy-a game-changer in SCLC management. This revolutionary non-invasive approach allows for the analysis of circulating tumor cells (CTCs), offering insights into tumor behavior and treatment responses. Our review focuses on a groundbreaking frontier: harnessing CTCs to create three-dimensional (3D) organoid models. These models, derived from CTCs that break away from the primary tumor or metastatic locations, hold immense potential for revolutionizing cancer research, especially in SCLC. We explore the essential conditions for successfully establishing CTC-derived organoids-a transformative approach with profound implications for personalized medicine. Our evaluation spans diverse isolation techniques, shedding light on their advantages and limitations. Furthermore, we uncover the critical factors governing the cultivation of 3D organoids from CTCs, meticulously mimicking the tumor microenvironment. This review comprehensively elucidates the molecular characterization of these organoids, showcasing their potential in identifying treatment targets and predicting responses. In essence, our review amalgamates cutting-edge methodologies for isolating CTCs, establishing transformative CTC-derived organoids, and characterizing their molecular landscape. This represents a promising frontier for advancing personalized medicine in the complex realm of SCLC management and holds significant implications for translational research.

Rational design strategies for innovative small-molecule scaffolds inspired by three pivotal protein secondary structures.

We developed a design strategy focusing on pivotal secondary structural motifs-α-helix, β-strand, and β-turn-critical for PPI recognition, using a common core skeleton. The resulting peptide-inspired pyrimidodiazepine scaffolds were further subjected to comprehensive phenotypic screening to evaluate their efficacy. Our strategy offers a transformative approach to developing small-molecule PPI modulators with broad therapeutic potential.

Adaptive Prescribed-Time Filtered Control Design for a Full-State Constrained Nonlinear System.

In this article, an adaptive prescribed-time neural controller is developed for the tracking problem of a class of high-order nonlinear systems with full-state constraints. First, a prescribed-time bounded stability criterion is designed. Then, to handle the "explosion of complexity" problem of the backstepping method, an adaptive prescribed-time filter is constructed, in which the filter error is prescribed-time stable. Compared with existing methods, the newly designed transformation approach can accommodate a broader range of state constraint types. Then, the unknown nonlinear function is handled by radial basis function neural networks (RBFNNs). The adaptive prescribed-time neural control scheme is developed based on above. It can guarantee that the closed-loop system achieves the prescribed-time stability, and all states do not transgress the constraints. To demonstrate the effectiveness of the control strategy, comparative simulations are provided at the end.

Transformative approaches for clinical trials in ophthalmology: Virtual reality as a metric for functional vision in inherited retinal diseases

Determining the efficacy of therapeutic interventions in ophthalmology requires not only the assessment of retinal structure and visual function but also a comprehensive evaluation of functional vision. Functional vision pertains to the patient's capacity to execute essential, vision‐dependent tasks, thereby maintaining autonomy. Traditional measures like visual acuity, contrast sensitivity, and visual field evaluations can fall short in encapsulating the full spectrum of visual deficits experienced by patients. To address this gap, translational researchers are increasingly focusing on developing performance outcomes (PerfOs) that provide a holistic measure of the therapy's impact on daily life activities.PerfOs are designed to strike a balance between measurement precision, relevance to the patient's daily life, and ecological validity, all while being adaptable for use in multicenter studies. A promising approach to achieving these objectives is the use of virtual reality (VR) for performance assessment. VR offers unparalleled control over experimental conditions, such as lighting, and enables rapid, objective behavioral measurements. Additionally, its reproducibility across various assessment centers and the safety it provides to participants make VR an ideal tool for this context.In this presentation, we introduce two innovative PerfOs developed for inherited retinal diseases, employing VR to enhance clinical endpoint accuracy in ophthalmology. The first is a mobility test, validated extensively in both real‐world and virtual settings. It demonstrates high reproducibility and reliability, effectively differentiates between retinitis pigmentosa patients and healthy controls, and accurately categorizes disease stages. The second is a VR‐based visual search task, specifically designed for the same patient population. These studies collectively affirm the potential of VR in establishing novel, meaningful clinical endpoints, significantly advancing the field of ophthalmology and enhancing patient‐centric care.

Fast Adaptive Optimization for UAV-Assisted MEC: A Constrained Decision Transformer Approach

Fast Adaptive Optimization for UAV-Assisted MEC: A Constrained Decision Transformer Approach

Emerging trends in nano-sensors: A new frontier in food safety and quality assurance.

The rapid evolution of nanotechnology has catalyzed significant advancements in the design and application of nano-sensors, particularly within the food industry, where ensuring safety and quality is of paramount concern. This review explores the multifaceted role of nano-sensors constructed from diverse nanomaterials in detecting foodborne pathogens and toxins, offering a comprehensive analysis of their operational principles, sensitivity, and specificity. Nano-sensors leverage unique physical and chemical properties at the nanoscale to enhance the detection of microbial contamination, actively contributing to food safety protocols. With applications ranging from real-time monitoring of pathogenic bacteria, such as Escherichia coli and Salmonella, to assessing environmental factors affecting food quality, these innovative devices demonstrate unparalleled advantages over conventional detection methods. Recent research illustrates the integration of nano-sensors with biosensing techniques, enabling multiplex analysis and rapid detection. Furthermore, the review addresses current challenges in the commercialization and regulatory landscape of nano-sensor technology, emphasizing the need for ongoing research to optimize their performance and facilitate widespread adoption in food safety systems. Overall, the incorporation of nano-sensors represents a transformative approach to safeguarding public health by proactively managing food safety risks and enhancing the efficiency of food quality assurance processes.

From runway to success: Unravelling business transformation approaches in India’s aviation industry

From runway to success: Unravelling business transformation approaches in India’s aviation industry

Effectiveness of an embedded oral health educational intervention in an undergraduate nursing program: A mixed methods study.

This study aims to evaluate the effectiveness of an oral health educational intervention designed for undergraduate nursing students. The role of oral health promotion and screening has been extended to non-dental health professionals, for example, nurses. To prepare the future workforce for these responsibilities, an educational intervention underpinned by Mezirow's Transformative Learning Theory was codesigned and implemented in an Australian undergraduate nursing program. A concurrent mixed methods design was used to evaluate the educational intervention Semi-structured interviews with second-year nursing students and faculty staff along with pre-post-test surveys (validated tool) were used to assess changes in attitude and confidence among nursing students regarding oral healthcare. Directed Content Analysis and univariate and bivariate analyses were used to analyse the data. Nursing students experienced a positive change in attitude following the educational intervention, which was also observed by faculty staff. This was corroborated by statistically significant improvements in attitude (5.89 versus 6.22, p=0.002) with the main area of improvement being a positive recognition of the role that nurses have in oral health assessment (21% increase). Students demonstrated a positive shift in confidence, which was supported by the quantitative data which showed an increase in mean scores post intervention (4.73 versus 5.26, p<0.001). Marked improvement in confidence was observed around the recognition of periodontitis (24-25% increase) which was the key focus of the educational intervention. This is the first time an oral health educational intervention has been implemented and found to be effective in improving the attitude and confidence of nursing students when undertaking oral healthcare activities in Australia. Adopting a transformative approach to teaching oral health is recommended for undergraduate nursing education providers as this learning approach can positively influence practice and behaviour changes.

Stepping stones to transformative participatory governance capabilities in a rural landscape restoration project

ABSTRACT Local participation in managing natural resources is key to ensuring that community members living within and relying upon ecosystems can influence planning and decision-making. Transformative and inclusive governance towards sustainable outcomes requires the presence of local actors with appropriate capabilities. This paper identifies means (or stepping stones) to cultivate transformative participatory governance capabilities. We analyse the outcomes of a learning system involving researchers and participants (collectively co-learners) employed within a transdisciplinary landscape restoration project – the Tsitsa Project, in the rural Tsitsa River Catchment in the Eastern Cape of South Africa. Developing governance capabilities enhanced the sustainability of the project’s localised impact. We conducted a qualitative analysis of the learning outcomes and process documentation, using a value creation framework. We found three stepping stones particularly effective at enabling transformative value creation: i) consistently adapting to novel and evolving constraints, ii) investing in effective, fair facilitation from the beginning, and iii) promoting participatory confidence through exposure to diverse governance spaces. The active, engaged development of participatory capabilities is a foundational step in the process of developing participatory governance practice. The insights can inform the development of transformative participation approaches in natural resource governance, particularly for rural communities.