Good Application Research Articles

Facile Synthesis of Acyl-Hydrazone Composites Based on Hydrazide-Modified Formylated Polystyrene for Effective Removal of Heavy Metal Ions and Sulfides from Water.

In this study, waste polystyrene was modified and upgraded to prepare formylated polystyrene, and the modified polystyrene acetyl hydrazone (LT-HPA) was synthesized by condensation with polymethyl-propionyl-hydrazine. It is proven that the modification of the adsorption material is successful by various characterization methods. In the subsequent pollutant removal study, pH, mass, concentration, contact time, and salt ion interference were investigated. The optimal pH for Cu(II) and sulfide removal was 5 and 11, respectively, and the optimal mass of adsorbent was 1 g/L. It was found that the maximum removal rate of Cu (II) was 231.51 mg/g. The adsorption equilibrium time was less than 40 min. This is due to the good adsorption activity of acyl hydrazide groups on the skeleton for Cu (II) through coordination. The maximum desulfurization amount in 60 min was 370.21 mg/g, which was mainly caused by the oxidation of sulfides by surface oxidizing groups. Isotherm and kinetic studies show that the adsorption processes of Cu (II) and sulfides are consistent with the Langmuir model and pseudo-second-order kinetic model. Thermodynamic parameters show that the removal of Cu (II) and sulfides is a spontaneous endothermic process. The adsorption mechanism is mainly chemical adsorption, supplemented by physical adsorption. After 10 regenerated adsorption/desorption cycles, the removal rates of Cu (II) and sulfides remained above 85%, indicating that polystyrenesulfonate acetylhydrazone (LT-HPA) adsorption materials have good reusability. In addition, the adsorbent has good thermal stability, salt resistance, and environmental friendliness. In summary, the modified formylated polystyrene acetyl hydrazone (LT-HPA) has a good application prospect in the removal of copper(II) and sulfides and provides a fresh way for upgrading polystyrene.

Artificial Intelligence in Nursing: Technological Benefits to Nurse’s Mental Health and Patient Care Quality

Nurses are frontline caregivers who handle heavy workloads and high-stakes activities. They face several mental health issues, including stress, burnout, anxiety, and depression. The welfare of nurses and the standard of patient treatment depends on resolving this problem. Artificial intelligence is revolutionising healthcare, and its integration provides many possibilities in addressing these concerns. This review examines literature published over the past 40 years, concentrating on AI integration in nursing for mental health support, improved patient care, and ethical issues. Using databases such as PubMed and Google Scholar, a thorough search was conducted with Boolean operators, narrowing results for relevance. Critically examined were publications on artificial intelligence applications in patient care ethics, mental health, and nursing and mental health. The literature examination revealed that, by automating repetitive chores and improving workload management, artificial intelligence (AI) can relieve mental health challenges faced by nurses and improve patient care. Practical implications highlight the requirement of using rigorous implementation strategies that address ethical issues, data privacy, and human-centred decision-making. All changes must direct the integration of artificial intelligence in nursing to guarantee its sustained and significant influence on healthcare.

Mapping typical LULC classes using spatiotemporal analysis and the thresholds of spectral optical satellite imagery indices: a case study in Algiers city.

Land use and land cover (LULC) dynamics have a substantial impact on human-environment interactions. Nowadays, remote sensing imagery has emerged as a useful tool for mapping and tracking LULC changes. Spectral optical indices derived from remote sensing data can provide insightful information about vegetation health, urban expansion, water bodies, deforestation patterns, and many other applications. The present study examines the use of popular optical spectral indices: vegetation index (NDVI), water indices (NDWI and MNDWI), urban indices (UI and NDBI), and bare land index (MNDBI) in threshold-based classification for LULC mapping using Algiers (Algeria) as a case study, and assesses the potential impacts of their spatiotemporal (at a seasonal and annual temporal scales) variations associated with natural seasonal changes and/or the evolution of the city's fabric. Here, a geo-statistical analysis of the values of the selected spectral indices at the level of each LU-class is conducted, threshold values (that account for seasonal variations) are proposed, and a classification approach (making use of best performing indices) is proposed and tested. Although fast and easy to implement, the proposed threshold-based LULC classification approach was successfully used for mapping LULC for the study zone with a high accuracy (an overall accuracy of 90.20 and a kappa of 0.84 for the demonstration year of 2017). The outcomes of the study heighten the potential and the limitations of the use of spectral indices for LULC mapping practices and consequent applications in environmental and urban studies.

Environmental impact study of the sightseeing electric vehicle supply chain based on the B2C e-commerce model and LCA framework

Studying the impact of the electric vehicle supply chain on the environment is crucial for determining the future development direction of the industry. We have developed a method for evaluating the impact of supply chains on the environment based on a lifecycle framework. This method innovatively seeks the connection between the lifecycle process of physical products and the supply chain, and organizes the environmental impact assessment factors of the electric vehicle supply chain from three aspects: physical resources, power energy, and waste emissions, in order to construct an LCA fuzzy comprehensive evaluation model for the electric vehicle supply chain. For the first time, the research method of transforming qualitative analysis into quantitative data was introduced into the life cycle environmental impact assessment, and empirical research was conducted using the supply chain of sightseeing electric vehicles as an example. The results indicate that the scrapping stage of electric vehicles has the most severe impact on the environment. Strengthening research on strategies or technologies for handling waste batteries and automobiles is key to improving the environmental performance of the supply chain. This method breaks through the requirements and limitations of traditional life cycle assessment methods on data sources and parameters, avoids large-scale calculations that cannot be separated from subjective factors in traditional methods, simplifies the process of supply chain environmental impact assessment, shortens the evaluation time, and improves the efficiency of environmental impact assessment. It is more practical and has good application prospects.

Effectiveness Study of a Cultural Adaptation of Cognitive-Behavioural Therapy-Based Application for Depressive Symptoms in College Students: A Randomised Controlled Trial.

Studies on mental health applications among college students lack empirical evidence regarding mobile application usage's intensity, duration and frequency. To evaluate the effectiveness of a cognitive-behavioural therapy (CBT)-based mobile application in ameliorating depressive symptoms among college students. A randomised controlled trial was conducted at three universities. Undergraduates aged ≥ 20 years with self-reported depressive symptoms were recruited and randomly assigned to the control and intervention groups. The outcomes include changes in depressive symptoms, suicidal ideation, help-seeking attitudes and emotional self-awareness at 4 (T1), 8 (T2) and 12 (T3) weeks. An intention-to-treat analysis was conducted. Of the 91 participants, 46 in the intervention group exhibited a significant decline in depressive symptoms at T1 and lower patterns of symptom changes at T2 and T3. No significant differences were observed in the other outcomes; however, higher help-seeking attitude, emotional self-awareness and lower suicidal ideation after T0 were observed for those who used the application for 12 weeks. The advantages of a brief application-based intervention to promote college students' psychological health are outlined. School nursing managers could use the application to improve the college mental health systems and support collegial teacher-student relationships. Further studies should enhance application usage to manage depressive symptoms. The study was approved by the Research Ethics Committee of the National Taiwan University Hospital (No. 202108098RINB, Date of approval: Oct 27, 2021) and the National Institutes of Health (No. NCT05188950).

Longitudinal Assessment of Pain in Rheumatoid Arthritis: Increases in Pain and Their Relationship to Functional Declines and Medication Changes.

Electronic health applications (apps) allow patients with rheumatoid arthritis (RA) to report patient-reported outcomes (PROs) between visits. However, almost no data exist on patients' report of pain between visits and how that correlates with change in function and/or modifications to medication. Patients with RA from one rheumatology practice provided data as part of a study of an app. Patients answered PRO short forms using the app, including the Patient-Reported Outcomes Measurement Information System pain interference and physical function questionnaires. Each PRO was answered every eight days. We assessed the frequency of significant worsening in pain using the minimally clinically important difference (MCID) of ≥5 points. Logistic regression assessed whether worsening in pain was associated with functional declines and/or RA medication changes. Among 150 patients with RA using the app, 83 patients qualified for analysis; the mean age was 62 years, and 82% were female. The median number of pain interference PROs answered per patient was 37 over 52 weeks. Using the first five pain interference PRO responses as the baseline, 60 (72%) patients experienced worsening of at least the MCID, with a median duration of 16 days. The odds ratio (OR) relating significantly worsening pain to declines in function over the next 42 days was 2.71 (95% confidence interval [CI] 1.12-6.89). Worsening pain was not significantly associated with changes to RA medication (OR 1.59, 95% CI 0.62-4.17). Clinically significant increases in pain among patients with RA are commonly associated with reductions in function but not with RA medication changes.

Design and Evaluation of a Mobile Health Application for Self-Care of Diabetic Retinopathy Patients: Participatory Design Study

Background: Diabetic retinopathy (DR) is a significant complication of diabetes, potentially leading to vision loss. Effective self-care and management are crucial to prevent its progression. Mobile Health (mHealth) applications offer a promising solution for supporting DR patients in self-care by providing continuous monitoring, education, and reminders. Objectives: This Participatory Design study aimed to create and assess a mobile health app to help diabetic retinopathy patients manage their condition through self-care. Methods: This practical research was carried out in 2024 over two stages: Design and Evaluation. First, we determined the functional requirements and developed a conceptual model of the application using Microsoft Visio 2021. In the next stage, we evaluated the application using the Mobile Application Usability Questionnaire (MAUQ) and gathered feedback from patients with diabetic retinopathy to understand their views on the application's usability. Results: The application's main features included reminders, alerts, educational content, and useful links. Thirty users with diabetic retinopathy participated in the usability testing. The participants expressed a high level of satisfaction with the application (mean score: 5.67 ± 1.04 out of a maximum of 7.00). Conclusions: The mHealth application for diabetic retinopathy self-care demonstrated high usability and potential to support patients in managing their condition. Future work should focus on integrating more advanced features and conducting long-term studies to assess the app's impact on clinical outcomes.

Artificial Intelligence and Environmental Impact: Moving Beyond Humanizing Vocabulary and Anthropocentrism.

Artificial intelligence (AI) and its applications in digital health, bioengineering, and society have significant material impacts on the environment owing to AI's vast energy demands and energy consumption, carbon footprints, and water usage to cool data centers and generate electricity to power the data centers. Yet, the environmental footprints of AI remain underappreciated and inadequately acknowledged. This is significant, particularly in this era of climate emergency and ongoing threats to planetary energy and water supplies. The vocabulary attached to AI often aims to mimic positive human capacities such as "warmness" and "care." However, these attempts to humanize AI and digital technology come with an anthropocentric gaze and blind spots that bracket out the environmental impacts and footprints of AI and privilege humans and technology over nonhuman animals and planetary ecological limits. In medicine, the environmental impacts of large language models range from water consumption and carbon emission to rare mineral usage. This commentary and innovation analysis question and queer the popular imagination of AI and digital technology as things that only exist in the immaterial world of cyberspace. In the course of research on AI in planetary health, we must be cognizant of its materiality, ecological impacts, and massive energy and water demands. We argue that moving away from anthropocentric narratives and vocabulary in AI design and praxis would bode well to live within planetary ecological limits so that AI and emerging digital technologies best serve robust and responsible science and all life on the planet Earth.

Application status and considerations of unilateral biportal endoscopy technique

To review the application status, clinical advantages, and complications of unilateral biportal endoscopy (UBE) technique and explore its future development direction. By reviewing recent domestic and international literature, the evolution history of UBE technique, its surgical advantages, and its application effectiveness in various spinal diseases were analyzed, providing a comprehensive review. UBE technique, with its unique dual-channel design, provides a clearer surgical field and more flexible operating space, significantly reduces surgical trauma and postoperative recovery time. UBE technique has demonstrated high safety and effectiveness in the treatment of lumbar disc herniation, spinal stenosis, lumbar instability, and cervical spondylosis. Additionally, the complication incidence of UBE surgery is lower than that of traditional open surgery. In recent years, UBE technique has shown good clinical application prospects and efficacy, but further technical optimization and large-scale clinical research are still needed to ensure the safety and effectiveness. In the future, the combination of UBE technique and intelligent medical and surgical robotics technology is expected to promote the further development of spinal surgery.

A Comprehensive Review of Herbal Granules in the Mouth Freshener

Herbal granules have gained significant attention as an alternative to conventional mouth fresheners due to their natural composition, potential health benefits, and minimal side effects. This review aims to comprehensively examine the role of herbal granules in oral care, focusing on their efficacy, ingredients, and consumer acceptance. The granules often contain a blend of herbal extracts, such as mint, fennel, cardamom, and clove, which are known for their antimicrobial, antioxidant, and digestive properties. The review also highlights the advantages of these herbal formulations over synthetic mouth fresheners, including their ability to promote oral hygiene, reduce bad breath, and provide therapeutic benefits like improving digestion and soothing oral irritation. Moreover, the environmental sustainability of herbal products and their market trends are discussed. Challenges such as the standardization of dosage, product consistency, and consumer perceptions are also addressed. Overall, this review underscores the promising potential of herbal granules as an effective and eco-friendly alternative to traditional mouth fresheners, emphasizing the need for further research to optimize formulations and enhance their therapeutic application in oral health.

Gamified Mobile Health Strategies for Promoting Physical Activity in Autistic Adults.

Physical inactivity and sedentarism among autistic adults are a growing public health concern. Focusing on the integration of behavior change theories and emphasizing the unique preference for visuospatial learning and gaming technology, we hypothesize that gamified mobile health (mHealth) applications can be effective at increasing free-living physical activity and reducing sedentary behavior in autistic adults.

MHealth Apps in German Outpatient Mental Health Care: Protocol for a Mixed Methods Approach

Background Mental disorders are complex diseases that affect 28% (about 17.8 million people) of the adult population in Germany annually. Since 2020, certain mobile health (mHealth) apps, so-called digital health applications (DiGA), are reimbursable in the German statutory health insurance system. A total of 27 of the 56 currently available DiGA are approved for the treatment of mental and behavioral diseases. An indicator of existing problems hindering the use of DiGA is the rather hesitant prescribing behavior. Objective This project aims to develop health policy recommendations for the optimal integration of DiGA into outpatient psychotherapeutic care. The project is funded by the Innovation Fund of the Joint Federal Committee (grant 01VSF22029). The current status quo of the use of DiGA will be analyzed. Furthermore, concepts for the integration of mHealth apps, as well as their transfer into the care process will be investigated. In addition, barriers will be identified, and existing expectations of different perspectives captured. Methods The project will be based on a mixed methods approach. A scoping review and a qualitative analysis of focus groups and expert interviews will be carried out. Additionally, an analysis of claims data of the statutory health insurance will be conducted. This will be followed by a written survey of insured persons and health care providers. Finally, health policy recommendations will be derived in cooperation with stakeholders. Results The scoping reviews and qualitative analyses have been completed, and the quantitative surveys are currently being carried out. The target number of responses in the survey of insured persons has already been achieved. Furthermore, the analysis claims data of the statutory health insurance is currently being conducted. Conclusions There is a need for research on how DiGA can be optimally integrated into the care process of patients with mental disorders as evidence regarding the topic is limited and prescribing behavior low. Although the potential of DiGA in mental health care has not yet fully unfolded, Germany serves as a model for other countries regarding reimbursable mHealth apps. This project aims to explore the potentials of DiGA and to describe the organizational, institutional, and procedural steps necessary for them to best support mental health care. International Registered Report Identifier (IRRID) DERR1-10.2196/56205

Advancing public understanding of epigenetics: the EPIBOOST project’s video science outreach

ABSTRACT The public’s growing interest in epigenetics, particularly its applications in human health, underscores the significance of epigenetic mechanisms in regulating gene activity and promoting phenotypic diversity without altering DNA sequences. Within the framework of the Extended Evolutionary Synthesis, epigenetics is regarded as a non-genetic contributor to evolution. The EPIBOOST project, “BOOSting excellence in environmental EPIgenetics,” investigates epigenetic changes induced by contaminants in aquatic organisms and aims to enhance public understanding of epigenetics through science outreach videos. A multidisciplinary team comprising Biology, Education, and Design researchers produced the video “What is Epigenetics?” using a design-based research methodology and a design thinking approach. This process involved storyboard design, audio recording, image production, video editing, testing, refinement, and public dissemination. The interactive development of the storyboard and script aimed to efficiently communicate the significance of epigenetics, fostering public understanding of this emerging research area through an effective science communication strategy. This paper focuses on the development process for the first video, which aims to promote public awareness of epigenetics using the AEIOU framework (Awareness, Enjoyment, Interest, Opinions, and Understanding) to elucidate epigenetic concepts such as DNA methylation, gene expression, and phenotype, and their integration in environmental assessment frameworks.

Diagnosis of Acute Versus Chronic Thoracolumbar Vertebral Compression Fractures Using CT Radiomics Based on Machine Learning: a Preliminary Study.

The purpose of this study is to evaluate the performance of radiomic models in acute thoracolumbar vertebral compression fractures (VCFs) and their impact on radiologists. In this monocentre retrospective study, eligible for inclusion were adults who underwent emergent thoracic/lumbar CT between May 2022 and November 2023 in our hospital diagnosed with thoracolumbar VCFs. The lesions were randomly divided at a ratio of 7:3 into a training set and test set. For external validation, consecutive patients who underwent emergent thoracic/lumbar CT between January 2022 and April 2022 were included. MRI and previous imaging were used as reference standard. The vertebral body area was manually segmented. Logistic regression was used to construct a CT radiomic model and a combined model, including Relief-selected radiomic features and clinical information. The radiologists' diagnosis with and without the models was recorded. The performance was assessed using receiver operating characteristic curves (ROC), calibration curves (CC) and decision curve analysis (DCA). Of 235 VCFs in 147 patients (median age, 73years, 66 male) included, the diagnosis of acute VCFs was confirmed in 126. The area under the ROC of the CT radiomics model and the combined model in the external validation set were 0.883 (95% CI 0.777, 0.998) and 0.875 (95% CI 0.768, 0.982), respectively. CC and DCA showed good clinical application of the models. The less experienced reader achieved a higher accuracy with the help of the models (p = 0.027). The radiomic models showed high accuracy for diagnosing acute VCFs and helped radiologists improve the accuracy of diagnosis.

The Potential of Flavonoid Antioxidants in Dragon Fruit Skin (Selenicereus undatus) for Cardiovascular Health

This study aims to examine the potential of flavonoid antioxidants found in dragon fruit peel (Selenicereus undatus) in supporting cardiovascular health. Flavonoids, as bioactive compounds with antioxidant properties, have an important role in protecting the body from oxidative stress that can damage cells and tissues, including the cardiovascular system. With a qualitative approach through literature studies and library research, this study analyzes secondary data from various scientific sources to explore the effects of flavonoids on reducing the risk of cardiovascular disease. Studies show that the flavonoid content in dragon fruit peel is able to suppress the lipid oxidation process, lower cholesterol levels, and inhibit inflammation which is a major risk factor for cardiovascular disease. In addition, the high antioxidant activity of these flavonoids has the potential to strengthen the walls of blood vessels and improve blood circulation, so that it can prevent atherosclerosis and hypertension. The results of this study support the use of dragon fruit peel as a source of natural antioxidants that have the potential to be used as a supplement in the prevention of cardiovascular diseases. A further recommendation is to conduct clinical research to test the effectiveness of flavonoids from dragon fruit peel in cardiovascular health applications in more depth.

Commentary: Expanding the horizons of RE-AIM framework in public health research

Objective: This commentary critically examines Yuliawati et al.’s 2024 review, “Analysis of research public health trends with the RE-AIM model and VOSviewer: A literature review,” which investigates the application of the “Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM)” framework in public health research. The review highlights trends in 279 studies conducted between 2017 and 2022 and draws attention to the insufficient focus on environmental health and sanitation interventions within the RE-AIM framework. The objective is to address these gaps and propose future directions for broadening the framework's application. Methods: The commentary evaluates the methodology used by Yuliawati et al., with particular attention to their utilization of the VOSviewer tool to map trends in RE-AIM-based research. It also explores the identified research gaps and incorporates insights from existing literature to examine the barriers that limit RE-AIM’s application in environmental health and sanitation. Results: Yuliawati et al.’s review demonstrates growing interest in the RE-AIM framework, but points out a notable deficiency in its application to environmental health and sanitation interventions. This commentary identifies potential reasons for this gap, such as limited interdisciplinary collaboration and resource constraints, and suggests that addressing these challenges could improve RE-AIM’s effectiveness in these fields. Conclusion: This commentary advocates for future research to overcome the barriers to RE-AIM’s application in environmental health and sanitation. It emphasizes the importance of interdisciplinary approaches and the need for a more adaptable framework to evaluate complex, multi-faceted public health challenges.

In Situ Grown Li2Te Enhanced Lithium Metal Anode Interfacial Kinetics.

Lithium metal anode (LMA) is expected to be the ideal anode material for future high-energy-density batteries, but regulating the complex electrolyte-anode interface remains a challenge. In this work, a stable Li2Te coating is formed on the surface of commercial copper mesh (LTCM) using a simple and quick method to improve lithium metal anode interfacial kinetics. Li2Te possesses a strong affinity for both Li+ and TFSI- anions, which reduces the lithium nucleation barrier and guides the formation of inorganic-rich SEI, accelerates the diffusion of Li+, and promotes the growth of lithium metal along the plane. The highly conductive Li2Te and Cu generated by in situ lithiation reaction together constitute an effective electron-conducting network, which synergistically enhances the interfacial kinetics and the cycling stability of LMA. As a result, the LTCM maintains high Coulombic efficiency (98%) even after 2200 cycles at 1 mA cm-2, whereas the symmetric cell has a long cycle life of over 5400h at 1 mA cm-2. In addition, the full cells with LFP display a high capacity retention ratio (80%) after 480 cycles at 1 C and the corresponding pouch cell can cycle steadily more than 464 cycles at 1 C, which has good application prospects.

Exploring university staff experiences gained during COVID-19 in the provision of digital mental health services through e-health tools: A case of a selected South African University

The recent COVID-19 pandemic significantly exacerbated mental health issues worldwide, with South African university staff facing unique stressors that led to the adoption of e-health tools for digital mental health services. This study explores the university staff experiences gained during COVID-19 pandemic in the provision of digital mental health services through e-health tools. We conducted a case study at a public university in Cape Town, South Africa complemented by a survey using quantitative methods. Data from 348 respondents were collected via voluntary response sampling and analysed with Statistical Software Package for Social Sciences (SPSS) version 28, employing exploratory factor analysis. High factor loadings above 0.4 confirmed significant contributions from seven items: perceived usefulness of e-health tools, perceived usefulness of social media, user experience and satisfaction, university commitment, variety of digital mental health services, post-COVID-19 delivery mode preference and ethical considerations. These seven items revealed that during COVID-19, e-health tools provided significant benefits to university staff including increased access to digital mental services. However, the study findings revealed that university staff were concerned about the lack of a legal framework during COVID-19, and the role of AI-powered mental health applications did not significantly influence their experiences during the pandemic. Our study provides theoretical insights into the effectiveness and perceived usefulness of e-health tools for digital mental health services during COVID-19, reinforcing their significance in reducing anxiety, stress, and depression while enhancing emotional resilience. Practically, our study findings suggest that universities should integrate e-health tools into the provision of digital mental health services given that these tools proved effective during COVID-19.

Architecture Design of Distributed Encrypted Storage and Computing Based on Fog Computing

With the progress of informatization, the problems of data transmission delay, untimely response and theft and tampering of user privacy data are becoming increasingly prominent. This paper proposes a distributed encryption storage and computing architecture based on fog computing, which uses the scalability and low latency of fog computing to solve the problems of data silos and response delays. Blockchain technology is introduced to build decentralized storage to prevent data tampering and ensure secure transmission and sharing. Hierarchical privacy protection measures are designed to store data in a hierarchical and classified manner to accurately control the scope of information acquisition. This method has good application characteristics and can effectively solve the problems of government data collection and calculation.

Utilizing geospatial analytics of cancer catchment area data for targeted recruitment of underserved populations for cancer prevention research: a precision public health application

Utilizing geospatial analytics of cancer catchment area data for targeted recruitment of underserved populations for cancer prevention research: a precision public health application