Practical Issues Research Articles

Current issues in doctoral supervision practice in the UK

ABSTRACT Doctoral study remains the most popular form of research degree globally. The student and supervisor relationship is an integral part of the postgraduate researcher (PGR) experience. Supervisory relationships can be complex and multi-faceted, with differing expectations from both supervisor and PGR. However, comparing different perspectives of the PGR supervisory journey is relatively unexplored. This study aimed to explore how both PGRs and supervisors perceive the evolution of supervisory relationships throughout the doctoral journey. Employing a mixed methods design, the findings indicate that there is a transition in the dynamics of the relationship between the supervisor and the student which changes during this process. The role of the supervisor moves from being a more knowledgeable other operating in an advisory capacity, described by one participant as a ‘balance of expertise’ that ‘swings’ as the relationship evolves. Drawing upon Jindal-Snape’s multiple and multi-dimensional transitional theory, the results suggest that managing expectations, supporting the transition to doctoral study, the role of peer support for PGRs and supervisors are fundamental to a positive supervisory experience. The global pandemic affected the supervisory relationship and research journey posing some challenges for data collection; however, it facilitated opportunities to adapt and evolve supervisory practice.

3D DYNAMIC CULTURE OF TENDON STEM CELLS FROM TENDINOPATHIC EXPLANT: A NEW TOOL FOR ADVANCED IN VITRO STUDIES

Poor tendon repair is an unsolved issue in clinical practice, due to complex tendon structure. Tendon stem/progenitor cells (TSPCs) play key roles in homeostasis, regeneration, and inflammation regulation in acute tendon injuries, and rely on TGF-β signaling for recruitment into degenerative tendons. In this study, we aimed to develop an in vitro model for tenogenesis adopting a dynamic culture of a fibrin 3D scaffold, bioengineered with human TSPCs collected from both healthy and tendinopathic surgery explants (Review Board prot./SCCE n.151, 29 October 2020). 3D culture was maintained for 21 days under perfusion provided by a custom-made bioreactor, in a medium supplemented with hTGF-β1 at 20 ng/mL. The data collected suggested that the 3D in vitro model well supported survival of both pathological and healthy cells, and that hTGF-β signaling, coupled to a dynamic environment, promoted differentiation events. However, pathological hTSPCs showed a different expression pattern of tendon-related genes throughout the culture and an impaired balance of pro-inflammatory and anti-inflammatory cytokines, compared to healthy hTSPCs, as indicated by qRT-PCT and immunofluorescence analyses. Additionally, the expression of both tenogenic and cytokine genes in hTSPCs was influenced by hTGF-β1, indicating that the environment assembled was suitable for studying tendon stem cells differentiation. The study offers insights into the use of 3D cultures of hTSPCs as an in vitro model for investigating their behavior during tenogenic events and opens perspectives for following the potential impact on resident stem cells during regeneration and healing events.

Optimization of Cloud-Based Multi-Agent System for Trade-Off Between Trustworthiness of Data and Cost of Data Usage

This paper considers the cloud-based multi-agent system (MAS) in which for any agent to obtain the most trustworthy data (MTD) that best matches the agents’ personalized demands on the trusted attributes of data, the agents’ data usage often comes with cost, and the better the trustworthiness of data (TOD), the higher the cost of data usage (CDU). Therefore, under the environments where the budgets for data usage are constrained, there may exist a trade-off between the TOD and CDU for the cloud-based MAS, and how to optimally make such trade-off arises as an interesting issue in practice. To address this issue, this paper first formulates the trade-off as a mathematical constrained optimization problem, then explores out the theoretical foundations, both using the fuzzy similarity computing, and finally proposes an algorithm to guarantee the agents to obtain the MTD within the acceptable level of CDU. The experiment results illustrate its effectiveness. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> — This paper addresses the interesting trade-off between TOD and CDU for the cloud-based MAS that operates in the cloud environments where the TOD and CDU are positively correlated with each other. By establishing the mathematical constrained optimization model and designing the algorithm for the MTD recommendation within the acceptable CDU based on the theoretical foundations using fuzzy similarity computing, it helps the MAS with cloud settings to achieve the MTD that best matches their personalized demands on the trusted attributes within the acceptable CDU, which could push the development of cloud-based MAS by benefiting from the optimal trade-off between TOD and CDU. The experiments show that the solution proposed here outperforms existing solutions.

Synthesis Load Model With Renewable Energy Sources for Transient Stability Studies

Increased penetration of renewable energy sources (RES) has brought challenges to load modelling techniques. This paper proposes a synthesis load model with RES (SLMR), and elaborates related industrial practice conducted by China Electric Power Research Institute. Several practical issues are addressed in designing and implementing SLMR, such as load survey and representation of different types of RESs. Besides, three new modelling concerns brought by RESs are novelly addressed in the paper, i.e., aggregation of various RES parameters, consideration of various RES terminal voltage, and additional line loss due to RES response. Parameterization of the SLMR calibrates widely varied node voltage in distribution grid, and aggregates them to one equivalent node. The proposed SLMR is practically applied in industrial works, which is demonstrated in the paper.

Exploring 2-D temporal patterns of individual mobility using non-negative matrix factorization

Understanding human mobility patterns is important for sustainable mobility development. One practical issue is about observing individual mobility regularity and variability over time and space. After the extraction of pre-treated travel attributes from a geolocation dataset, a further exploration of individual mobility profiles with multiple features is always required. The big challenge on this is to deal with a large number of mobility variables in order to find fine-grained temporal patterns. This paper aims to identify temporal mobility patterns with the two-dimensional (i.e., 2-D) trip attributes, i.e., departure time and distance. We use the three-month journey data from thousands of mobile phone users in the Paris region, France. For the pattern detection, the non-negative matrix factorization (NMF) method is suggested. According to the decompositions of our observation matrix, five types of temporal mobility patterns are obtained. The users’ mobility profiles represented by the impact ratios of these patterns are then interpreted. Beyond these, individual mobility variability is measured correspondingly by the day-to-day and week-to-week mobility divergences. Based on our findings, the impacts of the Covid-19 pandemic and the importance of time-to-time mobility variability are discussed with special concerns on mobility modeling.

Unveiling practical considerations for reliable and standardized SERS measurements: lessons from a comprehensive review of oblique angle deposition-fabricated silver nanorod array substrates.

Recently, there has been an exponential growth in the number of publications focusing on surface-enhanced Raman scattering (SERS), primarily driven by advancements in nanotechnology and the increasing demand for chemical and biological detection. While many of these publications have focused on the development of new substrates and detection-based applications, there is a noticeable lack of attention given to various practical issues related to SERS measurements and detection. This review aims to fill this gap by utilizing silver nanorod (AgNR) SERS substrates fabricated through the oblique angle deposition method as an illustrative example. The review highlights and addresses a range of practical issues associated with SERS measurements and detection. These include the optimization of SERS substrates in terms of morphology and structural design, considerations for measurement configurations such as polarization and the incident angle of the excitation laser, and exploration of enhancement mechanisms encompassing both intrinsic properties induced by the structure and materials, as well as extrinsic factors arising from wetting/dewetting phenomena and analyte size. The manufacturing and storage aspects of SERS substrates, including scalable fabrication techniques, contamination control, cleaning procedures, and appropriate storage methods, are also discussed. Furthermore, the review delves into device design considerations, such as well arrays, flow cells, and fiber probes, and explores various sample preparation methods such as drop-cast and immersion. Measurement issues, including the effect of excitation laser wavelength and power, as well as the influence of buffer, are thoroughly examined. Additionally, the review discusses spectral analysis techniques, encompassing baseline removal, chemometric analysis, and machine learning approaches. The wide range of AgNR-based applications of SERS, across various fields, is also explored. Throughout the comprehensive review, key lessons learned from collective findings are outlined and analyzed, particularly in the context of detailed SERS measurements and standardization. The review also provides insights into future challenges and perspectives in the field of SERS. It is our hope that this comprehensive review will serve as a valuable reference for researchers seeking to embark on in-depth studies and applications involving their own SERS substrates.

A Robust Initialization of Residual Blocks for Effective ResNet Training Without Batch Normalization.

Batch normalization is an essential component of all state-of-the-art neural networks architectures. However, since it introduces many practical issues, much recent research has been devoted to designing normalization-free architectures. In this brief, we show that weights initialization is key to train ResNet-like normalization-free networks. In particular, we propose a slight modification to the summation operation of a block output to the skip-connection branch, so that the whole network is correctly initialized. We show that this modified architecture achieves competitive results on CIFAR-10, CIFAR-100 and ImageNet without further regularization nor algorithmic modifications.

Can AI pass the written European Board Examination in Neurological Surgery? - Ethical and practical issues

IntroductionArtificial intelligence (AI) based large language models (LLM) contain enormous potential in education and training. Recent publications demonstrated that they are able to outperform participants in written medical exams. Research questionWe aimed to explore the accuracy of AI in the written part of the EANS board exam. Material and methodsEighty-six representative single best answer (SBA) questions, included at least ten times in prior EANS board exams, were selected by the current EANS board exam committee. The questions’ content was classified as 75 text-based (TB) and 11 image-based (IB) and their structure as 50 interpretation-weighted, 30 theory-based and 6 true-or-false. Questions were tested with Chat GPT 3.5, Bing and Bard. The AI and participant results were statistically analyzed through ANOVA tests with Stata SE 15 (StataCorp, College Station, TX). P-values of <0.05 were considered as statistically significant. ResultsThe Bard LLM achieved the highest accuracy with 62% correct questions overall and 69% excluding IB, outperforming human exam participants 59% (p = 0.67) and 59% (p = 0.42), respectively. All LLMs scored highest in theory-based questions, excluding IB questions (Chat-GPT: 79%; Bing: 83%; Bard: 86%) and significantly better than the human exam participants (60%; p = 0.03). AI could not answer any IB question correctly. Discussion and conclusionAI passed the written EANS board exam based on representative SBA questions and achieved results close to or even better than the human exam participants. Our results raise several ethical and practical implications, which may impact the current concept for the written EANS board exam.

The paradox of seeking help: Socioeconomic inequality in medical crowdfunding in the era of the mobile internet

In recent years, the emergence of mobile-internet-based crowdfunding has provided a new way for the poor to obtain emergency relief for medical needs. Despite a number of reported scams, medical crowdfunding has made an important contribution to society. Public opinion and sentiment highlight two practical issues: Are the resources being directed to the people who need them the most? And how can we optimize medical crowdfunding? To tackle these questions, we focus on the issue of how the socioeconomic status (SES) of help-seekers affects their online medical crowdfunding outcomes. We ask three research questions: What is the correlation between the SES of help-seekers and their fundraising outcomes? What are the underlying mechanisms? Is there a possible path for the optimization of medical crowdfunding outcomes? Our dataset includes 1930 fundraising cases from a large medical crowdfunding platform in China. The study finds significant differences in crowdfunding outcomes among different socioeconomic groups. Higher SES brings higher donation amounts, higher proportions of fundraising targets reached, a higher number of donations received, and more shares on social media. This socioeconomic gradient in crowdfunding outcomes contradicts the social expectation of prioritizing help to the neediest in medical crowdfunding. Mediation analysis also shows that offline interpersonal networks play an important intermediary role. While appealing case narratives are helpful, they are not an intermediary mechanism that links family SES with crowdfunding outcomes. Further analysis also finds that such a socioeconomic gradient seems to weaken when crowdfunding that begins within a private network of offline acquaintances on WeChat moves to public platforms.

Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA.

Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever-growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi-society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools. This article is simultaneously published in Insights into Imaging (DOI 10.1186/s13244-023-01541-3), Journal of Medical Imaging and Radiation Oncology (DOI 10.1111/1754-9485.13612), Canadian Association of Radiologists Journal (DOI 10.1177/08465371231222229), Journal of the American College of Radiology (DOI 10.1016/j.jacr.2023.12.005), and Radiology: Artificial Intelligence (DOI 10.1148/ryai.230513). Keywords: Artificial Intelligence, Radiology, Automation, Machine Learning Published under a CC BY 4.0 license. ©The Author(s) 2024. Editor's Note: The RSNA Board of Directors has endorsed this article. It has not undergone review or editing by this journal.

Solid Waste Generation and Characterization in a State University

This study investigated the solid waste generation and characterization at Mindanao State University (MSU) - Main Campus in Marawi City, addressing the critical issues of unsustainable waste management practices. Despite the recent establishment of waste management facilities in Marawi City, including a Central Material Recovery Facility (CMRF) and a Category 4 Sanitary Landfill (SLF), the campus and much of the city need help with effective waste disposal. This has led to environmental challenges such as clogged drainage systems, open dumping, and air pollution from waste burning. The study fills an essential gap in solid waste generation and characterization data, which is crucial for effective solid waste management (SWM) planning as mandated by the Ecological Solid Waste Management Act of 2000 (RA 9003). Using a descriptive-comparative research design, the study surveyed 216 units, including residential buildings, rental properties, commercial establishments, and university facilities. The findings reveal that the MSU-Main Campus generates 9438.011 kg of waste daily, with a per capita waste generation rate of 0.9371 kg/day— significantly higher than the national average. Residential buildings are the primary waste generators, contributing nearly half of the total waste, followed by lodgings. Waste characterization reveals a substantial proportion of non-biodegradable waste (38.29%), with biodegradable waste accounting for 35.46% of the total. These findings highlight the urgent need for systematic waste management strategies, particularly focusing on waste segregation, recycling, and waste reduction to mitigate the environmental impact on campus. The study provides a comprehensive data foundation for developing a solid waste management plan and underscores the role of academic institutions in leading sustainable practices.

ENVIRONMENTALLY FRIENDLY CONSUMER BEHAVIOR OF MILLENNIALS IN KAZAKHSTAN

This research explores the environmentally friendly consumer behavior of Millennials in Kazakhstan through a quantitative approach. The study targets the pressing issue of sustainable consumption prac-tices among this generation, which holds significant implications for environmental conservation. This study is aimed at exploration of determinants, patterns, and motivations behind environmentally friendly consumer behavior among Millennials in Kazakhstan. It seeks to identify the main factors influencing their choices, the extent to which eco-consciousness guides their decisions, and the influence of external factors, such as marketing strategies and peer influence.This research holds both scientific and practical significance contributing to the existing literature and offering insights into the emerging trends of green consumerism among Millennials in a Central Asian context. Moreover, it provides a quantitative assessment of the factors shaping their eco-friendly consumption, allowing for a nuanced understanding of their behavior. The research methodology in-volves the administration of structured surveys to a representative sample of Millennials in Kazakhstan. Data analysis performed with the use of such statistical methods as regression analysis and hypothesis testing to draw meaningful conclusions.Preliminary findings suggest that while environmental awareness plays a role in Millennials’ con-sumer choices, other factors such as affordability and convenience also significantly influence their be-havior. The research underscores the need for targeted strategies to encourage more sustainable con-sumption practices among this demographic. In conclusion, this research contributes valuable insights into the environmentally friendly consumer behavior of millennials in Kazakhstan, shedding light on the factors driving their choices and serving as a basis for the development and implementation of effective sustainability campaigns. It has the potential to inform policymakers, marketers, and businesses seeking to align their strategies with the preferences of this eco-conscious generation.

Contemporary Concept of Anticoagulant and Antiplatelet Therapies A Fresh Perspective on Laboratory and Instrumental Assessment Methods

Statement of the Problem: Impairment of the blood coagulation system remains a relevant issue in clinical practice. A striking example of this is the fact that despite the administration of anticoagulant therapy, up to 35% of COVID-19 patients were hospitalized in the intensive care unit with thromboembolic complications. Prophylactic and therapeutic methods for the hemostatic system, recommended by various protocols, have a general nature. Moreover, they introduce dissonance into the clinical clarity of appropriate anticoagulant and antiplatelet use and fail to provide practitioners with the necessary fundamental knowledge to understand the aspects of clinical tactics for correcting the hemostatic system. Uncertainties remain regarding how to correctly choose a specific anticoagulant and determine its effective dose based on individual clinical and laboratory data, which laboratory markers of the coagulation system should be investigated, and whether they always reflect the true picture of hemostasis. Methodology and Theoretical Orientation: This article briefly presents the main aspects of the functioning of the blood coagulation system, points of application for pharmacological agents, and provides objective information for clinicians about the mechanisms of action of major anticoagulants and antiplatelets. Effective and practical methods for assessing the hemostatic system are recommended. Findings: The proper correction of the hemostatic system can only be carried out by a highly qualified specialist - a clinical transfusiologist, who possesses a comprehensive understanding of the functioning of the coagulation and anticoagulation systems, the platelet and fibrinolysis systems, knows the points of application and mechanisms of action of the pharmacological agents and blood components used, and takes into account internal and external factors that influence hemostasis. Conclusion and Significance: Empirical prescription of anticoagulant and antiplatelet therapies, based solely on instructions and clinical protocols without objective comprehensive analysis of the hemostatic components, is not only ineffective but also life-threatening for the patient. Coagulogram and D-dimer measurements cannot serve as the sole determining markers for monitoring the coagulation system. Evaluation of the blood coagulation system should only be carried out based on a comprehensive analysis of coagulogram data, complete blood count, thromboelastography (TEG), and data from all relevant systems.

Telepsychiatry in Australia: A Scoping Review.

Telepsychiatry formed part of the Australian mental health response to COVID-19, but relevant reviews pre- and post-pandemic are sparse. This scoping review aimed to map the literature on telepsychiatry in Australia and identify key research priorities. We searched databases (Medline, PubMed, PsycINFO, Scopus, Web of Science, EBSCO Psychology & Behavioral Sciences Collection, Proquest databases, and Cochrane Central Register of Controlled Trials) and reference lists from January 1990 to December 2022. Keywords included telepsychiatry, videoconferencing, telephone consultation, psychiatry, mental health, and Australia. Two reviewers independently screened titles, abstracts, and full texts. We identified 96 publications, one-third of which appeared since 2020. Extracted data included article types, service types, usage levels, outcome measures, perceptions, and research gaps. Most publications were quantitative studies (n = 43) and narrative reports of services (n = 17). Seventy-six papers reported mostly publicly established services. Videoconferencing alone was the most common mode of telepsychiatry. There was increased use over time, with the emergence of metropolitan telepsychiatry during the pandemic. Few papers used validated outcome measures (n = 5) or conducted economic evaluations (n = 4). Content analysis of the papers identified perceptions of patient (and caregiver) benefits, clinical care, service sustainability, and technology capability/capacity. Benefits such as convenience and cost-saving, clinical care issues, and implementation challenges were mentioned. Research gaps in patient perspectives, outcomes, clinical practice, health economics, usage patterns, and technological issues were identified. There is consistent interest in, and growth of, telepsychiatry in Australia. The identified perception themes might serve as a framework for future research on user perspectives and service integration. Other research areas include usage trends, outcome measures, and economic evaluation.

Exploration of Practical Teaching Issues in the Course of Edible Mushroom Cultivation in Local Applied Universities

Exploration of Practical Teaching Issues in the Course of Edible Mushroom Cultivation in Local Applied Universities

Asymmetric integral barrier function-based tracking control of constrained robots

&lt;abstract&gt;&lt;p&gt;In this paper, a new-type time-varying asymmetric integral barrier function is designed to handle the state constraint of nonlinear systems. The barrier Lyapunov function is developed by building an integral upper limit function with respect to transformation errors over an open set to cope with the position constraint of the robotic system. We know that the symmetric time-invariant constraint is only a particular situation of the asymmetric time-variant constraint, and thus compared to existing methods, it is capable of handling more general and broad practical engineering issues. We show that under the integral barrier Lyapunov function combining a disturbance observer-based tracking controller, the position vector tracks a desired trajectory successfully, while the constraint boundary is never violated. It can certify the exponential asymptotic stability of the robotic tracking system by using the given inequality relationship on barrier function and Lyapunov analysis. Finally, the feasibility of the presented algorithm is indicated by completing the simulations.&lt;/p&gt;&lt;/abstract&gt;

Plasma nitrogen fixation system with dual-loop enhancement for improved energy efficiency and its efficacy for lettuce cultivation

Plasma nitrogen fixation (PNF) has been emerging as a promising technology for greenhouse gas-free and renewable energy-based agriculture. Yet, most PNF studies seldom address practical application-specific issues. In this work, we present the development of a compact and automatic PNF system for on-site agricultural applications. The system utilized a gliding-arc discharge as the plasma source and employed a dual-loop design to generate from air and water under atmospheric conditions. Experimental results showed that the system with a dual-loop design performs well in terms of energy costs and production rates. Optimal operational parameters for the system were determined through experimentation, resulting in an energy cost of 13.9 MJ mol−1 and an energy efficiency of 16 g kWh−1 for production, respectively. Moreover, the concentration of exhausted NO x was below the emission standards. Soilless lettuce cultivation experiments demonstrated that produced by the PNF system could serve as liquid nitrate nitrogen fertilizer. Overall, our work demonstrates the potential of the developed PNF system for on-site application in the production of green-leaf vegetables.

Archiving Archaeological Data: Understanding Current Practice through Case Studies from Established Repositories

The workflows examined are representative of operational workflows around data assessment and data removal that are common to all data repositories, as well as specific strategies of dealing with Microsoft Access Databases, a commonly deposited file format used by archaeologists for assessment and analysis. The paper will present each workflow as a succinct case study with an emphasis on why the decisions have been made to follow a certain method. This will be followed by a discussion on similarities and differences in approach and implementation so as to bring together core recommendations that can be used by others currently building or scoping the development of new digital repositories in the archaeological sector. The paper will link out to copies of the detailed workflows and policies to be deposited within COPTR, a finding aid for helping find tools to deal with practical data management issues.

Optimizing PV integration: Addressing energy fluctuations through BIPV and rooftop PV synergy

The widespread availability and affordability of photovoltaic (PV) systems are driving the future of demand-side generation towards end-user-based PV plants. Building-integrated PV systems offer an additional source of electrical energy, but their power output depends on external factors like solar insolation, weather conditions, geographical location, and earth’s rotation, causing non-constant energy generation, even in ideal weather conditions. In grid-connected systems, this variability leads to fluctuations in grid demand. Both BIVP and rooftop PV systems are photovoltaic-based, but their installation differences result in distinct energy generation characteristics. To address this, we propose an innovative approach to optimally integrate BIPV and rooftop PV systems by leveraging their contradictory energy generation nature. By employing mathematical and evolutionary algorithms to design an optimal system and develop a multi-objective optimization model, we address practical design issues. The outcome of these single and multi-objective systems helps minimize fluctuations in grid dependency throughout the year. The proposed system is validated on the IEEE-33 bus radial distribution network using the B&amp;R X20CP1586 PLC, confirming its effectiveness in ensuring a stable and reliable grid performance while mitigating energy fluctuation impacts.

Non-inferiority Clinical Trials: Treating Margin as Missing Information

Non-inferiority (NI) clinical trials’ goal is to demonstrate that a new treatment is not worse than a standard of care by a certain amount called margin. The choice of non-inferiority margin is not straightforward as it depends on historical data, and clinical experts’ opinion. Knowing the “true”, objective clinical margin would be helpful for design and analysis of non-inferiority trials, but it is not possible in practice. We propose to treat non-inferiority margin as missing information. In order to recover an objective margin, we believe it is essential to conduct a survey among a group of representative clinical experts. We introduce a novel framework, where data obtained from a survey are combined with NI trial data, so that both an estimated clinically acceptable margin and its uncertainty are accounted for when claiming non-inferiority. Through simulations, we compare several methods for implementing this framework. We believe the proposed framework would lead to better informed decisions regarding new potentially non-inferior treatments and could help resolve current practical issues related to the choice of the margin.