Research Efforts Research Articles

Exploring the Roles, Functions, and Work Experiences of Nurse Scientists in the Veterans Health Administration.

The aim of this project was to describe nurse scientists' roles, functions, and work experiences in the Veterans Health Administration (VHA). Nurse scientists play a critical role in shaping the culture of clinical inquiry and closing the gap between knowledge and practice. A cross-sectional survey was used to collect information on sociodemographics, workload, research, clinical practice, education, and time/effort. Data were examined using descriptive statistics and χ2 analyses. One hundred forty-four nurse scientists completed the survey. These nurse scientists serve dynamic and critical roles in conducting research, implementing evidence-based practice, and reforming policy. Research effort was limited due to workload and infrastructure constraints. Better research infrastructure was associated with higher research productivity and funding. This survey highlights the needs and challenges nurse scientists experience in conducting research and advancing VHA's mission. Given the national shortage of PhD-prepared nurses, long-term strategies are needed to attract, hire, and retain nurse scientists in healthcare systems.

Financial medicine: A multi-dimensional concept moving towards contextually specific working definitions for use in the South African prehospital setting

IntroductionThe phenomenon that has been described as Financial Medicine has been occurring within the South African Healthcare sector for at least the last decade. Despite the ongoing effect of this phenomenon, there is no organised body of knowledge or formulated working definitions to guide knowledge sharing and theorisation within this research focus area. The practice of Financial Medicine exerts a deleterious effect on the South African prehospital healthcare system, and represents an area in dire need of focused research efforts. Establishing appropriate working definitions and associated taxonomy is an important first step in supporting further research efforts into this aspect of South African prehospital healthcare systems. MethodsA qualitative research methodology following a constructivist grounded theory design was used. Participants voluntarily consented to be enrolled into one-on-one in-depth interviews, and were selected using purposive and theoretical sampling techniques. Data was subjected to validated coding procedures and analysed using the constant comparative analysis approach, analytical diagramming, and supported by researcher theoretical sensitivity. ResultsA working definition for Financial Medicine is provided. Six new terms are introduced, with associated working definitions, namely Financial Medicine Practices, Treatment-based profiteering, Cost-of-care-aversion, Personal-gain-at-patient-expense, Money-racketeering-in-healthcare, and Impoverishing-healthcare-earning. ConclusionThe working definitions and suggested taxonomy presented in this article are the first step in formally conceptualising and theorising the phenomenon of Financial Medicine, in order to support further research and collaboration in this space.

A Comprehensive Review of the Benzimidazole Scaffold as a Potential Nucleus for Anti-Ulcer Activity

Abstract: The benzimidazole scaffold is a promising nucleus for developing novel therapeutic agents for ulcer treatment. Its unique chemical structure provides desirable pharmacological properties, such as excellent bioavailability, metabolic stability, and low toxicity, making it an attractive candidate for ulcer treatment. Several benzimidazole derivatives have shown significant anti-ulcer activity in preclinical and clinical studies, acting through multiple pathways, including inhibition of gastric acid secretion, suppression of gastric inflammation, and promotion of mucosal protection. Some benzimidazole derivatives have also demonstrated anti-Helicobacter pylori activity, suggesting their potential for eradicating bacteria associated with ulcer formation. However, challenges such as poor solubility and limited selectivity remain. Various approaches, such as prodrug design and formulation optimization, have been explored to overcome these issues and improve the therapeutic profile of benzimidazole derivatives. Overall, the benzimidazole scaffold holds great promise as a nucleus for developing novel anti-ulcer agents. Further research and optimization efforts are needed to harness its full potential and translate it into effective treatments for ulcers. With continued advancements in medicinal chemistry and drug design, benzimidazole-based compounds may offer new therapeutic options for patients suffering from ulcers and related gastrointestinal disorders. Hence, this review highlights the knowledge about benzimidazole scaffold, the mechanism of ulcer formation, and various benzimidazole derivatives with anti-ulcer activity, which can be further studied in pre-clinical and clinical trials.

Harnessing the power of blockchain technology to support decision-making in e-commerce processes

Technology, such as blockchain, has emerged as a promising solution for addressing the challenges of e-commerce decision-making. In this study, we explore the potential benefits of integrating blockchain technology into e-commerce and its role in supporting decision-making in e-commerce. We also examine blockchain’s benefits in terms of enhanced security, transparency, and efficiency for e-commerce platforms. Furthermore, the study discusses the challenges of implementing blockchain for e-commerce, including scalability, integration, regulatory frameworks, user experience, privacy, interoperability, and sustainability. By analyzing these challenges, the study provides valuable insights for future research and development efforts to facilitate a seamless adoption of blockchain technology in e-commerce decisions. Blockchain technology holds the potential to transform an e-commerce ecosystem by overcoming these challenges and unlocking its transformative potential.

Meeting Report for the 2023 International Scientific Conference on Complex Lymphatic Anomalies

Objectives: Complex lymphatic anomalies (CLAs) are rare diseases with variable clinical manifestations caused by the abnormal development of lymphatic vessels. The Lymphatic Malformation Institute (LMI), Lymphangiomatosis & Gorham’s Disease Alliance (LGDA), and LGD Alliance Europe sponsored an international conference on CLAs so leaders in the field could discuss recent advances in research on CLAs. Methods: The conference occurred in Dallas, Texas, between September 29th and September 30th, 2023. The event had 22 distinguished speakers and 38 attendees. Additional researchers, clinicians, and patients attended the conference virtually. Results: In this article, we summarize the key takeaways from the meeting. The conference emphasized the crucial role of the patient voice in guiding research, and attendees heard stories from patients and parents of children with CLAs. The conference covered topics such as the genetic causes of CLAs, preclinical models, clinical advances, new technologies for CLA research, lymphatic imaging, and patient-centered research. Videos of all the presentations can be found on the LGDA website. Conclusions: The meeting revealed that while progress has been made, many challenges still exist surrounding the diagnosis and treatment of CLAs. Sustained research efforts are necessary to fill the gaps in knowledge and improve the care and quality of life of CLA patients.

Innovations in science education: A bibliometric exploration of trends and future directions

This article carries out a bibliometric research review to present the evolving landscape of innovations in science education. The study acknowledges the dynamism of the contemporary educational practices and uses the bibliometric analyses for identification of trends, assessment of impacts of scholarly outputs, and mapping the future directions in the field of science education innovation. Starting with a review of the standard bibliometric indicators, e.g., citation analysis and co-authorship, the review lays down the theoretical basis for the understanding of the scientific impact of the innovations in science education. The analysis, moreover, consists of identifying thematic foci and emerging topics through keyword mapping, which together present a holistic picture of the intellectual map of the field. The review points to seminal works and trends, demonstrating the nature of interdisciplinarity in research in science education innovation. By the analysis of collaborative networks and research hotspots the research not only demonstrates the present status of the field, but also predicts its future directions, which could help researchers and educators at the same time. Also, as a retrospective tool, the article explores the general relevance of bibliometric insights for educators, administrators, and other researchers. It highlights the application of bibliometrics in evidence-based decision-making, curricula design and international collaboration, because it is common knowledge that it can trigger the great revolution in innovative science education. This bibliometric review generates useful outcomes, which are beneficial to academic discussions and provide guidelines for future research efforts as a key reference for researchers who would like to have a deep, general overview of the innovations in science education.

Feature selection techniques for microarray dataset: a review

For many researchers working on feature selection techniques, finding an appropriate feature from the microarray dataset has turned into a bottleneck. Researchers often create feature selection approaches and algorithms with the goal of improving accuracy in microarray datasets. The main goal of this study is to present a variety of contemporary feature selection techniques, such as Filter, Wrapper, and Embedded methods proposed for microarray datasets to work on multi-class classification problems and different approaches to enhance the performance of learning algorithms, to address the imbalance issue in the data set, and to support research efforts on microarray dataset. This study is based on Critical Review Questions (CRQ) constructed using feature election methods described in the review methodology and applied to a microarray dataset. We discussed the analysed findings and future prospects of feature selection strategies for multi-class classification issues using microarray datasets, as well as prospective ways to speed up computing environment

Analysis of Manifold and its Application

Manifold learning is a field of study in machine learning and statistics that is closely associated with dimensionality reduction algorithmic techniques is gaining popularity these days. There are two types of manifold learning approaches: linear and nonlinear. Principal component analysis (PCA) and multidimensional scaling (MDS) are two examples of linear techniques that have long been staples in the statistician's arsenal for evaluating multivariate data. Nonlinear manifold learning, which encompasses diffusion maps, Laplacian Eigenmaps, Hessian Eigenmaps, Isomap, and local linear embedding, has seen a surge in research effort recently. A few of these methods are nonlinear extensions of linear approaches. A nearest search, the definition of distances or affinities between points (a crucial component of these methods' effectiveness), and an Eigen problem for embedding high-dimensional points into a lower dimensional space make up the algorithmic process of the majority of these techniques. The strengths and weaknesses of the new method are briefly reviewed in this article. In the field of computer graphics, we utilize a particular manifold learning method was first presented in statistics and machine learning to create a global, Spectral-based shape descriptor.

Uncovering sources, distribution, and seasonal patterns of trace element deposition: the elemental puzzle of the western Himalayas.

The transport and deposition of atmospheric pollutants in the Himalayas have a adverse impact on the climate, cryosphere, ecosystem, and monsoon patterns. Unfortunately, there is a insufficiency of data on trace element concentrations and behaviors in the high-altitude Himalayan region, leading to limited research in this area. This study presents a comprehensive and detailed comprehension of trace element deposition, its spatial distribution, seasonal variations, and anthropogenic signals in the high-altitude Kashmir region of the Western Himalayas. Our investigation involved the analysis of 10 trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in glacier ice, snow pits, surface snow, and rainwater collected at various sites including Kolahoi, Thajwas, Pahalgam (Greater Himalayan ranges), and Kongdori and Shopian (Pir Panjal Ranges) during 2021.The study reveals distinct ranges of concentrations for the trace elements at different sampling sites. Our analysis of trace element concentration depth profiles in snow pits reveals seasonal fluctuations during the deposition year. The highest concentrations were found in the autumn(below 20cm) and summer (top layer), compared to the winter concentration (10-20cm). The high enrichment factors (EFs) suggest the severity of human-induced trace metal deposition in the western Himalayan region, relative to surrounding regions. Surprisingly, the concentrations and EFs of trace elements showed seasonal contradictions, with lower concentration values and higher EFs during the non-monsoon season and vice versa. A source apportionment analysis using the positive matrix factorization (PMF) technique identified five sources of trace element deposition in the region, including crustal sources (32.33%), coal combustion (15.62%), biomass burning (17.63%), traffic emission (18.8%), and industrial sources (15.6%). Additionally, the study incorporated backward trajectories coupled with δ18O using the NOAA HYSPLIT model to estimate moisture sources in the region, which suggests atmospheric pollutants predominately deposited from the large-scale atmospheric circulation from westerlies (75%) during non-monsoon season. These findings underscore the urgent need for enhanced monitoring and research efforts in the future.

Smart textiles: Paving the way to sustainability

As an emerging technology, smart textiles can bring solutions to many problems, but also create new ones, especially related to their disposal and their impact on the environment. That is why it is important to address this problem at this stage of technological development when smart textiles have not yet pervaded the mass markets. In this article, first, an attempt is made to understand the chronological development of smart textiles: the reasons for a weak breakthrough in the commercial markets throughout the decades, starting from the 1990s until today, but also the emergence of new driving forces that should inevitably lead to a bright future for smart textiles. In addition, we explore the contemporary possibilities for sustainable materials, manufacturing techniques, and end-of-life solutions for developing sustainable smart textiles based on a broad literature review, online sources, and a questionnaire survey among textile experts. Finally, an overview of the latest developments related to the standardization of smart textiles is given. This research was spurred by participation in CONTEXT COST Action (CA17107 - European Network to connect research and innovation efforts on advanced Smart Textiles).

Room Temperature Reduction of Nitrogen Oxide on Iron Metal-Organic Frameworks.

Nitrogen oxides represent one of the main threats for the environment. Despite decades of intensive research efforts, a sustainable solution for NOx removal under environmental conditions is still undefined. Using theoretical modelling, material design, state-of-the-art investigation methods and mimicking enzymes, we have found that selected porous hybrid iron(II/III) based MOF material are able to decompose NOx, at room temperature, in the presence of water and oxygen, into N2 and O2 and without reducing agents. This paves the way to the development of new highly sustainable heterogeneous catalysts to improve air quality. This article is protected by copyright. All rights reserved.

Anomaly Detection for Video Surveillance

Anomaly detection in video surveillance is critical for identifying abnormal behaviours or events that deviate from typical patterns. This abstract explores various techniques used to detect anomalies in surveillance videos, including traditional methods like motion detection and background subtraction, as well as advanced approaches such as deep learning and anomaly scoring algorithms. By leveraging these techniques, surveillance systems can automatically detect suspicious activities such as trespassing, theft, or violence, enabling timely intervention and improved security measures. Highlighting the challenges in anomaly detection, such as dealing with complex scenes, occlusions and discusses ongoing research efforts to enhance the accuracy and efficiency of anomaly detection systems in real-world surveillance scenarios. Key Words: anomaly, suspicious, pattern, motion, detection, security measure

A Cross-Cultural Examination of Young Children’s Attitudes Towards Peers with Disabilities in South Korea and the United States

ABSTRACT Despite much research effort in promoting young children’s positive attitudes towards peers with disabilities, little is known about cultural influences on the attitude formation. In this study, data were collected from 111 kindergarten aged children from South Korea (n = 59) and the United States (n = 52) to measure the participating children’s attitudes towards peers with disabilities and compare their responses to an attitude measure, the Acceptance Scale for Kindergarteners-Revised (ASK-R). Results revealed that American children had significantly more positive attitudes towards peers with disabilities than Korean children did. When comparing children’s responses to each item in the ASK-R, larger differences were found on the items that did not specifically ask about peers with disabilities (e.g. Do you play with kids even if they look different?). Based on the results, cultural influences on children’s understanding and acceptance of peers with disabilities are discussed.

Unveiling Key Factors Shaping Energy Storage Strategies for Sustainable Energy Communities

This research delves into a case study of a photovoltaic (PV) energy community, leveraging empirical data to explore the integration of renewable energy sources and storage solutions. By evaluating energy generation and consumption patterns within real-world energy communities (a nominal generation capacity of 33 kWn) in Gipuzkoa, Spain, from May 2022 to May 2023, this study comprehensively examines operational dynamics and performance metrics. This study highlights the critical role of energy consumption patterns in facilitating the integration of renewable energy sources and underscores the importance of proactive strategies to manage demand fluctuations effectively. Against the backdrop of rising energy costs and environmental concerns, renewable energies and storage solutions emerge as compelling alternatives, offering financial feasibility and environmental benefits within energy communities. This study emphasizes the necessity of research and development efforts to develop efficient energy storage technologies and the importance of economic incentives and collaborative initiatives to drive investments in renewable energy infrastructure. The analyzed results provide valuable insights into operational dynamics and performance metrics, further advancing our understanding of their transformative potential in achieving a sustainable energy future. Specifically, our study suggests that storage capacity should ideally support an average annual capacity of 23%, with fluctuations observed where this capacity may double or reduce to a minimum in certain months. Given the current market conditions, our findings indicate the necessity of significant public subsidies, amounting to no less than 67%, to facilitate the installation of storage infrastructure, especially in cases where initial investments are not covered by the energy community.

Visualizing dementia and stigma: a scoping review of the literature

Discursive choices are recognized by both academic and dementia communities as being central to the perpetuation (or challenging) of dementia-related stigma. Yet, the focus of the vast majority of research on the discursive dynamics of dementia stigma to date has been on the role of language only, effectively failing to regard the multimodal reality of discourse. The present study aims to address this gap by conducting a scoping review of the smaller, and relatively more recent, body of literature that has examined visual modes of communication. The authors ask the following questions: (1) What theories of stigma have informed or guided studies of visual representations of dementia and people with dementia? (2) What visual features of representations of dementia and people with dementia might contribute to and/or challenge dementia stigma? Using Scopus, PubMed, PsychInfo and Google Scholar, 10 papers published between January 2000 and July 2023 were selected and thematically synthesized. The authors found that most studies had limited or no engagement with specific stigma theories, although the general principle of establishing or challenging distance between an in-group (‘us’) and out-group (‘them’) informed many of the analyses. Visual features with the potential to contribute to stigma tended to impersonalize people with dementia through foregrounding visual markers of dementia (oftentimes emphasizing loss and/or the brain) and establishing symbolic distance between viewers/other represented participants and people with dementia. This distance could be achieved through visual framing techniques (regarding angle, gaze, colour, setting) which, for instance, could subtly position people with dementia as the ‘living dead’. There was much less focus on visual features with the potential to challenge stigma, which together emphasized social connection, transformation and taking the perspective of someone with dementia. Turning to reception, another potential aspect of challenging stigma was reinterpreting supposedly ‘stigmatizing’ images. In this article, these findings are interpreted in relation to the broader stigma literature and implications for future research and advocacy efforts are discussed.

Lymph node tuberculosis‐associated paradoxical immune reconstitution inflammatory syndrome in a non‐HIV patient: Case report and review of literature

AbstractTuberculosis (TB) is a global health threat, especially in HIV patients who may experience immune reconstitution inflammatory syndrome (IRIS) upon Mycobacterium tuberculosis infection. Diagnosing and defining IRIS in non‐HIV patients remains challenging. A 63‐year‐old male with acute leukaemia underwent induction therapy with a regimen containing fludarabine. Febrile neutropenia led to further investigations, revealing non‐cavitary pulmonary TB, prompting anti‐tuberculosis therapy (ATT) alongside resumed leukaemia treatment with sorafenib. Persistent extra‐pulmonary TB, specifically lymph node involvement, were observed and IRIS was suspected, evidenced by enlarged lymphadenopathies, scrofula, and skin lesions that developed during the 13‐month course of ATT, with no recurrence after its cessation. This article explores a case of lymph node TB‐associated paradoxical IRIS in a non‐HIV leukaemia patient, revealing the intricate interplay between tuberculosis and haematological malignancies and emphasizing the lack of standardized diagnostic criteria and treatment consensus. Challenges in lymph node TB diagnosis and management highlight the need for tailored therapeutic approaches. The report explores the potential immunomodulatory effects of fludarabine and sorafenib, questioning their roles in TB‐IRIS. This case illuminates TB‐IRIS dynamics in non‐HIV patients, urging further research and collaborative efforts to enhance understanding and outcomes. As medical complexities persist, personalized therapeutic approaches and advancements in TB‐IRIS research are crucial.

Updating and validating seagrass ecosystem knowledge in the gulf of California: a comprehensive review

Seagrasses are globally acknowledged as crucial habitats as they provide a variety of ecosystem services. Mexico’s legislation protects most of these marine plants; however, the protection often fails in application. The Gulf of California, despite being a biodiversity hotspot, has scant data on seagrasses. Here, human activity and climate change increasingly threaten these coastal ecosystems, with conservation and research efforts lacking coordination at a regional level. Our manuscript aimed to review and standardize existing data on Gulf of California seagrass species, ensuring open access for data updates; pinpointing conservation deficiencies; and guiding future research. We have added new records to the official public data, but we were able to recapture only 25% of the seagrass locations meaning a potential reduction in their historical distribution of 45.8%. Even though Mexico’s legislation protects some species of seagrasses, it protection often fails in the application. We identified that only 6.1% of the seagrass locations are within protected areas that recognize their presence in their management plans (e.g., the Balandra Flora and Fauna Protected Area and the Upper Gulf of California and Colorado River Delta Biosphere Reserve). At least 55.9% of seagrass records are associated with potentially damaging activities like pollution, coastal modification or biological resources use, while 23% are exposed to higher frequency of marine heatwaves. Given the importance of seagrass meadows under Mexican law and their internationally recognized ecological value, sharing current information and guiding research is essential. Our study seeks to galvanize renewed research initiatives and raise more awareness on the conservation of the Gulf of California’s seagrasses.

MERA: Meta-Learning Based Runtime Adaptation for Industrial Wireless Sensor-Actuator Networks

IEEE 802.15.4-based industrial wireless sensor-actuator networks (WSANs) have been widely deployed to connect sensors, actuators, and controllers in industrial facilities. Configuring an industrial WSAN to meet the application-specified quality of service (QoS) requirements is a complex process, which involves theoretical computation, simulation, and field testing, among other tasks. Since industrial wireless networks become increasingly hierarchical, heterogeneous, and complex, many research efforts have been made to apply wireless simulations and advanced machine learning techniques for network configuration. Unfortunately, our study shows that the network configuration model generated by the state-of-the-art method decays quickly over time. To address this issue, we develop a ME ta-learning based R untime A daptation (MERA) method that efficiently adapts network configuration models for industrial WSANs at runtime. Under MERA, the parameters of the network configuration model are explicitly trained such that a small number of optimization steps with only a few new measurements will produce good generalization performance after the network condition changes. We also develop a data sampling method to reduce the measurements required by MERA at runtime without sacrificing its performance. Experimental results show that MERA achieves higher prediction accuracy with less physical measurements, less computation time, and longer adaptation intervals compared to a state-of-the-art baseline.

Don’t forget your keys when trying to unlock the productivity of low-permeability coals

Low-permeability coal seam gas (CSG) wells have been the subject of laboratory research and modelling studies over the past decade, particularly focusing on the pressure-dependent permeability (PDP) behaviour of coals. These research efforts have progressed diagnostic methods to identify and quantify PDP and provide practical technologies to counter these effects. Firstly, machine learning methods based on drilling and historical well-test data can provide insight into the range of coal permeability during drilling. Next, the process of history-matching the after-closure pressures from a diagnostic fracture injection test (DFIT), using reservoir simulators, can determine best-fit values for fracture compressibility, a key parameter for reservoir models. Finally, these data, along with DFIT reservoir pressure and permeability data, can inform the decision-making process regarding the most applicable completion strategy and aid developmental planning. For areas where vertical or surface-to-inseam (SIS) wells have been unsuccessful, new hydraulic fracturing technologies have been developed to enhance the stimulated reservoir volume (SRV) in coals, using horizontal wells with multi-stage hydraulic fracturing in excess of 20 stages. Recent laboratory and modelling of micro-proppants has extended prior laboratory and modelling studies and provided insight into proppant transport, embedment, and screen-out behaviour. These well stimulation technologies can be co-applied in new or existing CSG fields and are suitable for areas where overlapping tenements limit conventional, steel-based completion strategies. In conclusion, this paper will bring the key findings of these studies together in a cohesive framework and provide the workflows to implement these technologies for better productivity in low-permeability coals.

Systems management strategies for increasing alfalfa use in warm‐humid regions

AbstractAlfalfa use (Medicago sativa L.; “lucerne”) in warm, humid regions of the world represents a potential area of expansion for the alfalfa industry. The objective of this review paper is to demonstrate how alfalfa forage breeding and systems research efforts have identified opportunities for increasing alfalfa contributions in these regions, along with potential pathways for seed industry and farming operations to increase adoption. Our review draws primarily on reports from the Southeast United States and Argentina. Significant technological advancements in plant screening and selection have identified alfalfa plant populations that are more adapted to the growing conditions experienced in these regions, which are often characterized by mild temperature, long growing seasons, and multiple other abiotic and biotic stressors. Management systems research conducted in the United States and Argentina has demonstrated the use of alfalfa for conserved forage, grazing, or dual‐purpose use in monoculture or mixtures with warm‐season grasses such as bermudagrass (Cynodon spp.). These trials report increased forage production, nutritive value, and ecosystem services of alfalfa–grass mixtures when compared with traditionally N‐fertilized warm‐season grass‐based systems. Grazing‐based alfalfa systems in Argentina have demonstrated methods for utilizing alfalfa as part of beef, dairy, and finishing systems. Some approaches for expanding alfalfa production in the region include targeted marketing efforts for adapted varieties and demonstrating alfalfa applications within existing farming frameworks. This includes educational programming efforts and on‐farm demonstrations to promote alfalfa use as a component of the livestock diets, integration into grass‐based systems, crop rotations, and wildlife use. Continued emphasis on a systems approach to alfalfa inclusion represents an opportunity for improved forage and livestock production in warm, humid regions of the world.