Field Of Practice Research Articles

Determinants of Problem-Solving Skills of Nursing Students: Solution-Focused Thinking Skills and Emotional Intelligence.

Problem-solving skills are some of the leading strategies for dynamism in the content and quality of nursing care. The present study is aimed at determining nursing students' problem-solving, solution-focused thinking, and emotional intelligence levels and investigating the relationship between their problem-solving skills and these variables. The study comprised 305 nursing students in Turkey. Data were collected between May and June 2021, using the personal information form, problem-solving inventory, solution-focused inventory and Schutte emotional intelligence scale. One-way ANOVA, t-test and multiple regression were used for data analysis. The mean age of the participants was 21.81 ± 5.93 years, 75.7% of them were women, 35.1% were senior students and 58.0% perceived their academic achievement as moderate. The mean scores from the overall problem-solving inventory, solution-focused inventory, and emotional intelligence scale were 92.93 ± 19.30, 50.26 ± 8.43 and 128.22 ± 14.11, respectively. Variables such as sex, perceived academic achievement, emotional intelligence and solution-focused thinking levels affected problem-solving skills (p < 0.01). The effective predictive factors accounted for 50.2% of the change in participants' problem-solving skill levels. For this reason, revising the national nursing curriculum with programmes that develop emotional intelligence and solution-focused thinking skills will enable nursing students to better manage the nursing process in clinical and field practices.

A strong, excellent water resistance, and anti-ultraviolet poly(vinyl alcohol)/lignocellulose/poly(butylene adipate-co-terephthalate) composite with "sandwich" structure.

Renewable materials derived from lignocellulose are promising materials for different practical applications, including biomedical, food, and agricultural fields. However, the poor mechanical performance and wet stability restrict their applications. Herein, we fabricated PVA/lignocellulose/PBAT (PVA/CLM/PBAT) composite with a "sandwich" structure. Cellulose-lignin mixture (CLM) was prepared by deep eutectic solvent (DES) pretreatment of corn straw. It served as a reinforcing scaffold of Poly (Vinyl Alcohol) (PVA) film for improving mechanical properties, UV blocking and decrease water permeability. Poly (butylene adipate-co-terephthalate) (PBAT) was used as "protector" with PVA/CLM composites by solvent coating method. The tensile strength of PVA/CLM/PBAT is 63.92MPa. The results show that 27.93MPa of tensile strength and 179.98% of elongation at break of PVA/CLM/PBAT are achieved after immersing in water for 2h, which was remarkable higher than that of PVA/CLM without PBAT coating (4.78MPa and 111.43%, respectively). The bonding strength of PVA/CLM/PBAT is 2.44±0.06N/15mm. The hydrogen bonds, π-π interaction between PBAT, PVA, and CLM enhance the bonding strength of PVA/CLM/PBAT composites. The water absorption rate of PVA/CLM/PBAT is only 4.4% after 20h, which showed a remarkable water resistance. 25wt% CLM content in PVA/CLM/PBAT composite can fully shield ultraviolet at 200-800nm, indicating that the remarkable UV shielding capability.

Awareness of physical changes occurring in adolescent period: an interventional study among girls 13-17 years of age in rural field practice area Government Medical College, Amritsar

Awareness of physical changes occurring in adolescent period: an interventional study among girls 13-17 years of age in rural field practice area Government Medical College, Amritsar

Impact of gas composition, pressure, and temperature on interfacial Tension dynamics in CO₂-Enhanced oil recovery.

Climate change policies are driving the oil and gas industry to explore CO2 injection for carbon dioxide storage in reservoirs. In the United States, a substantial portion of oil production relies on CO2-enhanced-oil-recovery (CO2-EOR), demonstrating a growing interest in using CO2 to address various production challenges like condensate mitigation, pressure maintenance, and enhancing productivity in tight reservoirs. CO2 injection introduces gases like natural gas and N2, either pre-existing or as impurities in the injected CO2 gas. These gases alter the interaction of CO2 with the oil or condensate in the reservoir, with interfacial tension playing a crucial role in governing miscibility, mobilization, and phase distribution. Effectively implementing gas injection techniques requires a precise understanding of interfacial tension between injected gases and reservoir fluid under reservoir conditions. This study aims to evaluate the effects of oil composition, gas composition, pressure, and, temperature on interfacial tension and provides a comprehensive understanding of IFT dynamics for CO2-EOR implementation. The study utilizes the pendant drop analysis technique to assess the impact of pressure, temperature, and gas composition on crude oil and condensate interfacial tension. Measurements span a range of temperature (30-85 oC), pressure (0.7-7MPa), and mixture composition (CO2: N2 ratios of 90:10 and 10:90), including pure CO2 and N2 with crude oil and condensate. Accurate measurement of interfacial tension incorporates changes in oil and gas density as functions of pressure and temperature. Results show that interfacial tension is significantly influenced by pressure, temperature, and gas composition. It decreases with increasing pressure at constant temperature and gas composition for both crude oil and condensate. While temperature-induced reductions in interfacial tension occur, they are overshadowed by the more pronounced effect of pressure. Gas composition significantly affects system interfacial tension; an increase in CO2 mole fraction decreases it, while an increase in N2 mole fraction causes an upturn. Changes in CO2 mole fraction result in concave downward trends, whereas changes in N2 mole fraction lead to concave upward trends. These findings are crucial for understanding the interaction of injected gas with reservoir fluid and can be applied to model interfacial tension with hydrocarbon fluid. This study offers an in-depth understanding of interfacial tension dynamics in CO2-EOR, a process that is increasingly attracting global attention for CO2 utilization. The research stands out for its innovative experimentation and detailed analysis, which focus on evaluating the impact of individual parameters crucial for modeling. Additionally, it sheds light on the combined effects of these parameters, which are essential for practical field applications. This knowledge is instrumental in designing processes such as CO2-EOR and condensate banking, incorporating the effects of pressure, temperature, and gas composition at the reservoir scale.

Groupwork skills training in social work education: practicing skills training in a Norwegian context

ABSTRACT In research as well as in the field, concerns have been raised that the academization of education in social work contributes to an increased distance from the field of practice. As a core element in the education of social workers, skills training serves an important function in integrating theoretical knowledge and bridging a gap between education and professional practice. Using Vygotsky’s concept of the zone of proximal development, this article takes as its starting point the experiences of BA social work students with skills training and its potential to integrate and activate theoretical knowledge in their training. The students’ evaluations provide a starting point for discussing the importance of their attitudes toward the place of theoretical knowledge in skills training, as well as their own contribution to the integration of theory work. In addition, the teacher’s tasks as a mediator of knowledge about the relationship between theory and practice and how theoretical knowledge can be transferred to, integrated and activated in skills training activities are explored, focusing on dialogue and reflection in the group. Such knowledge might inspire further research on the importance of skills training as a learning arena.

Who talks about climate, peace and security? A social media analysis to identify key global actors

Uncovering key actors within a policy network provides pathways for engagement, consensus-building, partnership development, and understanding the diffusion of knowledge in a given debate. Given the unprecedented scale of the climate emergency, the emerging field of climate security has rapidly gained centrality in academic and policy fora, as well as in the public debate. Yet, a systematic analysis of the main actors engaged in this space is missing. This study draws from digital methods and network analysis techniques to employ a method for identifying relevant actors, focusing on Twitter (now X) from 2014 to 2022, with the objective of systematically spotting the major actors driving and shaping public discussions around climate security. The research also demonstrates how institutions can position themselves within such issue networks through a case study of the CGIAR, the largest publicly funded global research partnership for a food-secure future dedicated to transforming food, land, and water systems in a climate crisis that has recently positioned itself in this community. Results reveal that the climate security debate on social media is predominantly institutional, with research bodies and international organizations from the Global North as central elements. While CGIAR is a relatively new actor, it is already centrally located in the network, maintaining strong connections with other major players, which places it in a strategic position to enhance its influence and reach. Understanding this discursive landscape is crucial for institutions and organizations to identify opportunities for effective engagement, partnership, and positioning in such an increasingly salient field of research and practice.

State-of-the-Art Personalized Therapy Approaches for Chronic Non-Specific Low Back Pain: Understanding the Mechanisms and Drivers.

Chronic non-specific low back pain (CNSLBP) is a debilitating condition that affects millions of people worldwide, significantly impacting quality of life and imposing a substantial socioeconomic burden. Traditional treatment approaches often rely on a one-size-fits-all strategy, failing to account for individual variations in pathophysiological mechanisms, drivers, and the principles of personalized medicine. Furthermore, an overemphasis on biomechanical findings from imaging may lead to ineffective interventions and unnecessary surgical procedures, obscuring other important factors that contribute to pain perception. While highlighting the limitations of universal treatment approaches, in this review we present a practical clinical approach aimed at elucidating the main pathophysiological mechanisms and various factors underlying the development and maintenance of CNSLBP in order to create a personalized treatment program. In conclusion, this review underscores the need for personalized therapeutic strategies that take into account the unique characteristics of each patient, recognizing the complex interaction of biological, psychological, social, and other factors that contribute to the development of individual pain. By combining a comprehensive understanding of the complexities of this condition, we aim to improve clinical outcomes and provide information on the development of effective personalized treatment algorithms, particularly in the field of neurological practice.

Unveiling carbon dynamics in year-round waterlogged pond fields: insights into soil organic carbon accumulation and sustainable management

Agri-ecosystems with flooded fields are pivotal in global carbon (C) dynamics. Although extensive research has focused on carbon sequestration in paddy fields, year-round waterlogged pond fields remain underexplored. This study investigates carbon dynamics in pond fields planted with Semen Euryales for 0, 24, and 60 years, examining soil organic carbon (SOC) accumulation and shifts in its composition. The results revealed a progressive increase in SOC, driven by particulate organic C (POC) and mineral-associated organic (MAOC). SOC increased significantly from 7.49 g kg–1 to 46.10 g kg–1 over the 60 years, with particulate organic carbon (POC) rising from 12.0% to 42.0% and mineral-associated organic carbon (MAOC) decreasing from 87.8% to 58.0%. Lignin phenols, reflecting plant-derived carbon, surged from 11.0% to 68.8%, while amino sugars, indicative of microbial residues, declined from 89.0% to 31.2%, suggesting reduced microbial activity under prolonged anaerobic conditions. Total microbial phospholipid fatty acid (PLFA) decreased by 40.6% and 43.8% after 24 and 60 years, respectively, further supporting the conclusion that anaerobic conditions limit microbial survival. The prolonged waterlogging reduced microbial decomposition, enhancing the accumulation of POC, particularly from plant-derived carbon such as Semen Euryales residues. The accumulation of microbial residues, especially fungal necromass, played a significant role in forming MAOC. That is, continuous waterlogging promoted POC accumulation and also contributed to MAOC stabilization. The findings provide valuable insights into sustainable carbon management practices in pond fields and contribute to climate change mitigation.Graphical

Secured Network Architectures Based on Blockchain Technologies: A Systematic Review

Blockchain applications have emerged in recent decades, among which blockchain secured-networks serve as a prevalent application. This paper provides the potential of networks secured by blockchain technology to enhance various domains and provides a structured view of the current landscape of blockchain applications, capturing the practical applications and potential of blockchain technology. Followed by a background overview, a survey analysis of the latest advancements in blockchain-secured networks is presented, categorized by six application fields: Vehicular Ad-Hoc, Health Care, Smart Home, Unmanned Aerial Vehicle (UAV), Internet of Things (IoT), and Industrial IoT Networks. An in-depth discussion on these key research topics within blockchain-secured networks is provided, enhancing understanding of their application and influence across multiple disciplines. The study overall conveys the versatility of blockchain-secured networks, highlighting their immense potential for application in various practical fields. A comprehensive structured survey analysis of recent advancements in blockchain-secured networks is conducted, and categorized by application fields. By providing a comprehensive understanding of the current trends in blockchain application, this paper enables readers to navigate information effectively and identify key areas of interest, facilitating further exploration and research opportunities in the field of blockchain technology.

A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness

Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them. The construction and comparison methods of predictive models by machine learning algorithms are investigated to evaluate the level of predictive models in order to determine the optimal predictive model. The results show that the PSO-SVR model performs best in predicting athlete engagement, with a prediction accuracy of 0.9262, along with low RMSE (0.1227), MSE (0.0146) and MAE (0.0656). The prediction accuracy of the PSO-SVR model exhibits an obvious advantage. This advantage is mainly attributed to its strong generalization ability, nonlinear processing ability, and the ability to optimize and adapt to the feature space. Particularly noteworthy is that the PSO-SVR model reduces the RMSE (7.54%), MSE (17.05%), and MAE (3.53%) significantly, while improves the R2 (1.69%), when compared to advanced algorithms such as SWO. These results indicate that the PSO-SVR model not only improves the accuracy of prediction, but also enhances the reliability of the model, making it a powerful tool for predicting athlete engagement. In summary, this study not only provides a new perspective for understanding athlete engagement, but also provides important practical guidance for improving athlete engagement and overall performance. By adopting the PSO-SVR model, we can more accurately identify and optimise the key factors affecting athlete engagement, thus bringing far-reaching implications for research and practice in sport science and related fields.

Anemia Across Lifespans in Rural South India: A Comprehensive Study of Age and Gender Dynamics From the Field Practice Area of Centre for Rural Health (CRHA), Nutakki, Andhra Pradesh

Anemia Across Lifespans in Rural South India: A Comprehensive Study of Age and Gender Dynamics From the Field Practice Area of Centre for Rural Health (CRHA), Nutakki, Andhra Pradesh

Equine temporomandibular joint diseases: A systematic review.

The temporomandibular joint (TMJ) is a unique joint that enables mandibular movement. Temporomandibular diseases (TMDs) impair joint function, leading to more or less specific clinical signs. To compile and disseminate clinical data and research findings from existing publications on equine TMD. Systematic review. Following PRISMA 2020 guidelines, literature searches were conducted in PUBMED, Scopus, and Web of Knowledge. The inclusion criteria covered case reports and research articles on equine TMDs. The selected records were grouped considering septic TMJ arthritis, primary TMJ osteoarthritis (OA), and non-arthritic TMDs. A risk of bias assessment was performed for the research articles. Equine TMD has been described in 51 publications to date, with septic TMJ arthritis accounting for 41.2% of TMD cases, fractures/luxations for 29.4%, and primary TMJ OA for 21.6%. Trauma was confirmed or suspected in 54.9% of TMD cases. The severity of clinical signs was mild to moderate in primary TMJ OA and mild to severe in septic TMJ arthritis and non-arthritic TMDs. Clinical signs were related to the underlying cause, particularly in terms of TMJ swelling, pain, and masticatory problems. Among diagnostic imaging modalities, CT was utilised in 92.2% of horses, radiography in 84.4%, and ultrasonography in 21.6%. The lack of clinical data in some reports. A risk of bias due to missing data. TMDs are infrequently described, with trauma being the most common TMD cause. TMDs are associated with TMJ dysfunction; however, the diagnostic protocol is varied. Regardless of the TMD type, a detailed diagnostic protocol should include a thorough history, detailed TMJ examination, and radiography as the first imaging choice in field practice, with CT as the 'gold standard' in clinical settings. For septic TMJ arthritis, a bacterial culture is recommended, while for primary TMJ OA, functional tests and local analgesia.

Generative Literature: The Role of Artificial Intelligence in the Creative Writing Process

This study explores the emerging phenomenon of AI-generated literature and its implications for creative writing, focusing on the characteristics of AI-generated texts, the impact of AI-human collaboration on the creative process, and the challenges posed by these technologies for traditional concepts of authorship, originality, and creativity. Through a comparative analysis of selected AI-generated literary works and a case study of the "Pharmako-AI" project, this research reveals the distinct stylistic, thematic, and structural features of AI-generated literature, as well as the complex dynamics of AI-human collaboration in the creative process. The findings suggest that while AI can serve as a powerful tool for creative exploration and experimentation, it also has limitations in terms of consistency, coherence, and emotional depth, and requires significant human input and judgment to shape the final literary output. The study contributes to the understanding of AI in creative writing by providing concrete insights into the capabilities and limitations of these technologies, and by highlighting the need for new frameworks and models to understand the nature of creative agency in the age of AI. The implications of AI-generated literature for the field of literature and future literary practices are discussed, including the potential for new forms of literary expression, new modes of authorship and collaboration, and new challenges to traditional concepts of originality and creativity. The study concludes with recommendations for future research, emphasizing the need for interdisciplinary collaboration and the development of new theoretical and methodological approaches to analyze and evaluate AI-generated literature.

High serum CA19-9 predicts severe cholecystitis in calculous cholecystitis patients

BackgroundCA19-9 is a classical tumor marker and plays an important role in the diagnosis of biliary and pancreatic cancer. However, a few cases reported that the tumor maker CA19-9 is abnormally elevated in patients with calculous cholecystitis, but the relation between severity of calculous cholecystitis and serum CA19-9 level are still unknown.MethodsTotal 105 calculous cholecystitis patients from first hospital were collected and divided into high serum CA19-9 group(high group, n = 35) and normal serum CA19-9 group(normal group, n = 70). Perioperative data including blood cell count, inflammatory markers, liver function, imaging and operation-related parameters from these patients were collected for analysis and verified with second group of 105 calculous cholecystitis patients from second hospital. Besides, the gallbladder specimens were collected for immunohistochemical staining and mRNA sequencing.ResultsAbdominal pain occur in more than 90% patients in high group, which is similar with that of normal group. But WBC, neutrophils count, NLR, CRP level and IL-6 level is higher in high group than that of normal group. In addition, the gallbladder wall thickness, the operation duration and the operation conversion rate is also higher in high group, which is verified from second hospital. Higher expression of CA19-9 was found by immunohistochemical staining in gallbladder specimen and more autophagy pathway related genes enriched in high group.ConclusionsThis study demonstrated that higher level of serum CA19-9 correlates with more severe cholecystitis in calculous cholecystitis patients for the first time, which will provide helpful information for clinical practice and basic research in related field.

Synthesis and performance analysis of novel SiO2 Janus nanoparticles for enhancing gas foam injection in oil reservoirs

Gas foam injection offers a viable solution to challenges faced in oil reservoirs, yet ensuring optimal foamability and stability remains a pivotal hurdle in practical field operations. This study presents a novel synthesis procedure to create silica (SiO2) Janus nanoparticles (JNPs) and examines their potential to enhance gas foam stability for enhanced oil recovery (EOR) applications. Two variations of SiO2 JNPs were synthesized via a masking procedure, employing oleic acid and ascorbic acid within a Pickering emulsion, marking a pioneering approach. These nanoparticles underwent comprehensive analysis for a deeper understanding. The investigation sought to unravel the mechanisms behind these JNPs’ performance in the foam injection process, probing various operational parameters such as JNP type, concentration, and gas medium (air, CO2, and CH4) impact on surface tension reduction, foamability, and stability through static tests. Results uncovered remarkable efficiency in SiO2-oleic acid JNPs, showcasing a substantial edge in reducing surface tension compared to bare SiO2 nanoparticles. Specifically, at a concentration of 15,000 ppm, SiO2-oleic acid JNPs demonstrated a 25 mN/m greater reduction in surface tension than bare SiO2 within a CH4 medium. Notably, while the gas type had limited influence on surface tension under standard pressure, the synthesized JNPs showed superior foam stabilization in air compared to CO2 and CH4 environments. SiO2-oleic JNPs exhibited outstanding foamability, stabilizing 80% of the foam generator cell’s height and remaining stable for 122 min during the EOR process. Conversely, ascorbic acid-SiO2-oleic acid JNPs displayed elevated foamability but reduced stability compared to SiO2-oleic acid JNPs. Despite achieving full height in the foam generator cell, stability was limited to 26 min in the CO2 medium.

The Afterlives of Transitional Justice

ABSTRACT∞ Rising authoritarianism, far-right parties and violent political movements in the 21st century prompt scholars and practitioners to revisit two foundational assumptions in the transitional justice field, which was established in the 20th century amid the third wave of democratization. The first is that transitional justice is a consequence and a cause of democratic transition and consolidation. The second is that transitional justice has been a successful global project. Current political developments challenge us to take stock of the field and consider the implications for current and future scholarship and practice. In this introduction to the ‘Afterlives of Transitional Justice’ special issue of the International Journal of Transitional Justice (IJTJ), we first reflect on the many forms (‘lives’) that transitional justice has taken over the decades. The contributions address transitional justice’s life in three ways: as the transition to democracy, as the tools and processes themselves and as an academic and practice field. We then consider evolution and change in transitional justice (‘afterlives’). In increasingly perilous times for human rights, we hope that the insights gathered in these pages will help affected communities, activists, practitioners, policymakers and scholars look back in order to move forward and uphold the promise ‘Never again!’

Interdisciplinary Perspectives: Rethinking Communication for Development and Social Change in Health Communication

Communication for development and social change is an evolving field both in research and practice, transcending paradigms of conventional communication towards engaging and somewhat exposing some of the real-life communicative disorders experienced by communities. While public health and communication for development and social change operate from diverse paradigmatic thinking and are applied quite independently as disciplinary fields of study, health communication converges these fields in research and practice. In this paper, I discuss these interdisciplinary perspectives that draw from communication for development and social change principles and public health through a process of divergence and convergence towards new ways of thinking about decision making. Much of this discourse stems from understanding many health problems as a development problem first, one that recognises the role of community responses during pandemics yet at the same time places the agency back with individuals to make informed choices. Communicating for health decision making from this perspective is what I call Communicating for Health-as-Development (C4HD). C4HD foregrounds health as development, which caters to the messy, unidirectional, non-process-orientated, non-measurable and often non-data-driven approaches to health outcomes. It is in these messy health communication efforts that real development takes place. This paper, using examples from HIV and COVID-19, discusses these ongoing developments in the field and the convergence of public health and communication for development and social change from an interdisciplinary perspective, by exploring three key concepts: community engagement to influence decision making, community agency and ownership, and context and collaboration, which contribute to understanding communication for health-as-development.

Microbiome Engineering for Sustainable Rice Production: Strategies for Biofertilization, Stress Tolerance, and Climate Resilience

The plant microbiome, found in the rhizosphere, phyllosphere, and endosphere, is essential for nutrient acquisition, stress tolerance, and the overall health of plants. This review aims to update our knowledge of and critically discuss the diversity and functional roles of the rice microbiome, as well as microbiome engineering strategies to enhance biofertilization and stress resilience. Rice hosts various microorganisms that affect nutrient cycling, growth promotion, and resistance to stresses. Microorganisms carry out these functions through nitrogen fixation, phytohormone and metabolite production, enhanced nutrient solubilization and uptake, and regulation of host gene expression. Recent research on molecular biology has elucidated the complex interactions within rice microbiomes and the signalling mechanisms that establish beneficial microbial communities, which are crucial for sustainable rice production and environmental health. Crucial factors for the successful commercialization of microbial agents in rice production include soil properties, practical environmental field conditions, and plant genotype. Advances in microbiome engineering, from traditional inoculants to synthetic biology, optimize nutrient availability and enhance resilience to abiotic stresses like drought. Climate change intensifies these challenges, but microbiome innovations and microbiome-shaping genes (M genes) offer promising solutions for crop resilience. This review also discusses the environmental and agronomic implications of microbiome engineering, emphasizing the need for further exploration of M genes for breeding disease resistance traits. Ultimately, we provide an update to the current findings on microbiome engineering in rice, highlighting pathways to enhance crop productivity sustainably while minimizing environmental impacts.

Interprofessional Collaboration as a Best Practice Across the Care Continuum.

Interprofessional teams are increasingly being recognized as a best practice for enhancing cooperation among multiple disciplines in delivering person-centered care and improving outcomes. Unlike previous models, such as the multidisciplinary team in which each profession or discipline remained largely siloed, with interprofessional teams collaboration occurs across disciplines. For case managers, the interprofessional team concept aligns with the collaborative, professionally diverse nature of the field of practice. As the Commission for Case Manager Certification (CCMC) states: "The practice of case management is professional and collaborative, occurring in a variety of settings where medical care, mental health care, and social supports are delivered. Services are facilitated by diverse disciplines in conjunction with the care recipient and their support system" (2024b, CCMC Definition and Philosophy, p.1). Although interprofessional teams may be more familiar in settings such as acute care, this dynamic can be found, formally and informally, across health and human services. Professional case managers who actively participate in interprofessional teams will likely find more opportunities to optimize collaboration and collective decision-making that bring out the best of every profession and discipline. Interprofessional teams can be found in multiple care settings including acute care, subacute care, community-based care, palliative/end-of-life and other settings that benefit from a person-centered approach that supports successful transitions of care and improved outcomes. Professional case managers are valued members of interprofessional teams, in that they are typically collaborative, promote open communication, and encourage cooperation among various disciplines. Interprofessional teams, however, may require a shift in thinking away from the former multidisciplinary model, in which case managers often acted as the hub connecting the spokes of each discipline. Within interprofessional teams, the individual is at the center, and every discipline will share leadership based on the individual's needs or the treatment protocol or other intervention needed in the moment. In this way, interprofessional teams become a model for empowering and allowing each discipline to step up and address specific aspects of treatment or other interventions.

Electrokinetic Enhancement of Membrane Techniques for Efficient Nanoparticle Separation and Preconcentration.

Efficient separation and preconcentration of nanoparticles are crucial in a wide range of biomedical applications, particularly as target substances continue to diminish in size. In this study, we introduce an electric field-assisted membrane system that synergistically combines oversized-pore membranes with an electrokinetic particle retention mechanism. Utilizing Ti/Au-coated poly(tetrafluoroethylene) (PTFE) membranes, our approach generates electrokinetic forces to effectively separate and retain charged nanoparticles even smaller than the pores, achieving a separation efficiency over 99% and a preconcentration factor of 1.76 within 10 min. Additionally, membrane fouling and transmembrane pressure are significantly reduced compared to conventional filtration techniques, offering advantages such as lower driving pressure and improved particle recovery. Rigorous experimental analysis and theoretical modeling reveal that this method establishes a critical balance between drag and electrokinetic forces acting on the nanoparticles, thereby enhancing separation and concentration efficiencies. Our research outcome paves the way for advanced particle manipulation techniques, potentially transforming biomolecule enrichment practices in diverse biomedical fields, including point-of-care diagnostics, highly sensitive biochemical detection, and bioprocessing applications.