Transformed System Research Articles

New View on Nonlinear Picture Fuzzy Integral Equations

In this article, we solve the second type of nonlinear Volterra picture fuzzy integral equation (NVPFIE) using an accelerated form of the Adomian decomposition method (ADM). Based on (α,δ,β)-cut, we convert the NVPFIE to the nonlinear Volterra integral equations in a crisp form. An accelerated version of the ADM is used to solve this transformed system, which is based on a new formula for the Adomian polynomial. The sufficient condition that guarantees a unique solution is obtained using this new Adomian polynomial, error estimates are given, and the convergence of the series solution is proven. Numerical cases are discussed to illustrate the effectiveness of this approach.

Feedback on clinical team performance: how does it work, in what contexts, for whom, and for what changes? A critical realist qualitative multiple case study

BackgroundFeedback on clinical performance aims to provide teams in health care settings with structured results about their performance in order to improve these results. Two systematic reviews that included 147 randomized studies showed unresolved variability in professional compliance with desired clinical practices. Conventional recommendations for improving feedback on clinical team performance generally appear decontextualized and, in this regard, idealized. Feedback involves a complex and varied arrangement of human and non-human entities and interrelationships. To explore this complexity and improve feedback, we sought to explain how feedback on clinical team performance works, for whom, in what contexts, and for what changes. Our goal in this research was to present a realistic and contextualized explanation of feedback and its outcomes for clinical teams in health care settings.MethodsThis critical realist qualitative multiple case study included three heterogeneous cases and 98 professionals from a university-affiliated tertiary care hospital. Five data collection methods were used: participant observation, document retrieval, focus groups, semi-structured interviews, and questionnaires. Intra- and inter-case analysis performed during data collection involved thematic analysis, analytical questioning, and systemic modeling. These approaches were supported by critical reflexive dialogue among the research team, collaborators, and an expert panel.ResultsDespite the use of a single implementation model throughout the institution, results differed on contextual decision-making structures, responses to controversy, feedback loop practices, and use of varied technical or hybrid intermediaries. Structures and actions maintain or transform interrelationships and generate changes that are in line with expectations or the emergence of original solutions. Changes are related to the implementation of institutional and local projects or indicator results. However, they do not necessarily reflect a change in clinical practice or patient outcomes.ConclusionsThis critical realist qualitative multiple case study offers an in-depth explanation of feedback on clinical team performance as a complex and open-ended sociotechnical system in constant transformation. In doing so, it identifies reflexive questions that are levers for the improvement of team feedback.

Is Doctoral Education Not for Everyone? How the University Reforms Led to Centralization of Doctoral Programs in the Leading Universities

The last decade brought a number of reforms to the higher education system in Russia: restructuring of the higher education system, creation of national research and federal universities, and the launch of the “5-100” excellence program. The results of these transformations system have stimulated a plethora of research in the field of higher education. However, the effects of these changes on doctoral education have been less often in researchers’ focus. In this paper, we have examined the changes and effects of the reform period on doctoral education based on the data from the Monitoring of the Universities’ Effectiveness. The analysis showed that during the last five years there has been a redistribution of the doctoral students towards the leading universities. Moreover, there are magnet universities in the federal districts which attract a significant part of the doctoral students. Regions with no leading universities face the most difficult situation: the dynamic of the studied indicators in these regions is either negative or significantly lags behind other regions.

Design and analysis of leading one/zero detector based approximate multipliers

Approximate multipliers are widely used in error-tolerant applications to improve circuit performance. For signed multiplication, previous approximate Booth multipliers usually have a large relative error with operands around “0”, while approximate leading one detector based (LOD-based) multipliers are not energy-efficient due to the extra preprocessing module. In this paper, a low relative error leading one/zero detector based approximate multiplier (LOZDAM) is proposed for signed multiplication, which dynamically truncates the operands according to the location of their most significant bits for signed complement data. Its accuracy can be configured to suit fault-tolerant applications with different accuracy requirements. A compensation strategy is proposed to reduce the calculation error of LOZDAMs at a low cost. All proposed designs are evaluated in 28nm/0.9 V/TT/25 °C CMOS. Compared with the exact design, the proposed LOZDAM6/7/8/9 with the width of Booth multiplier being 6/7/8/9-bit reduces average power by 64%/43%/33%/21%, with the mean relative error distance by 2.94%/1.46%/0.73%/0.36%, respectively. Case studies of image sharpening and serial Fast Fourier Transform system both show acceptable error and good power/area savings, which verifies the feasibility of our designs. In general, our proposed LOZD-based approximate multipliers achieve both high accuracy and low power.

Hospitality as the bridge: advancing transformative service research towards human flourishing

ABSTRACT As an increasingly important paradigm in the services domain, transformative service research (TSR) emphasizes the need for improving the well-being of entities inside and outside the service organization. The present article offers that hospitality – as an ethic and experience – offers compelling avenues to move the TSR agenda to its next stage of evolution. Specifically, given its indelible connections to the fledging paradigm of human flourishing, hospitality provides tangible pathways for service organizations to effect transformative value creation as systemic human flourishing at the individual, collective, and ecosystem levels. The article examines this proposition in the context of research at the intersection of hospitality and healthcare. It then offers a novel conceptual framework – Hospitality-Oriented Systems of Transformation In Services (HOSTIS) – that uses hospitality as the starting point and the bridge between the two paradigms of TSR and human flourishing. The article concludes with opportunities for future research that addresses the key conceptual and empirical considerations of the framework. The HOSTIS framework recognizes the potential of service organizations to contribute to a flourishing society.

Diffeomorphism-Based Robust Bounded Control for Permanent Magnet Linear Synchronous Motor With Bounded Input and Position Constraints

This article develops a diffeomorphism-based robust bounded control (DRBC) for the permanent magnet linear synchronous motor system subject to inequality constraints (i.e., bounded input and position constraints) and uncertainties. The uncertainties, including parameter uncertainties and external disturbances, are potentially nonlinear and fast time varying. The bound of the uncertainty is described by a fuzzy set. To overcome the bounded input constraint, a robust bounded control is proposed based on a novel input diffeomorphism scheme, which is in a deterministic form and not if–then rule based. Furthermore, to overcome the bounded position constraint, a transformed system is formulated by a state diffeomorphism scheme, which transforms the bounded state-constrained system to an unconstrained one. Thus, the output of the controlled system can be restricted to a prescribed range. The DRBC guarantees both the uniform boundedness and the uniform ultimate boundedness of the transformed system. A fuzzy performance index, which combines the steady-state performance (the average fuzzy performance) and control effort, is then established based on the fuzzy description of uncertainty. As a result, the design parameter optimization can be solved by minimizing the performance index. Experimental results demonstrate that the DRBC is of superior tracking performance and robustness without violating the prescribed inequality constraints.

Health Systems Need to Transform Data Collection to Advance Health Equity.

Health Systems Need to Transform Data Collection to Advance Health Equity.

Transportation of Fe3O4-SiO2-Al2O3/EO and SiO2-Al2O3/EO nanoparticles in magnetized Reiner–Philippoff liquid, including modified fluxes via Galerkin algorithm: Significance of EMHD

This developing study is focused on mass diffusion and thermal energy enhancement in Reiner–Philippoff martial across a vertical-surface under an exposed Lorentz force. Characterization of the thermal energy and mass diffusion are modified utilizing non-Fourier’s theory in the presence of a heat source. Three types of nanoparticles — Al2O3, titanium dioxide, and TiO2 — in engine oil are inserted for production of heat energy. Darcy’s Forchheimer theory is used to analyze behavior flow and heat energy. Moreover, effects related to Dufour and Soret are added. A transformed system of ODEs is achieved regarding the developed model using similarity variables. Numerically developing models in the form of ODEs are handled with the aid of the finite element method (FEM). Fluidic thermal energy is augmented against upshot values of time relaxation number. Fluidic concentration declines against changes in Schmidt number and chemical reaction number.

Health Care Natural Language Processing (NLP) Using MOORA Method

The field of natural language processing (NLP) is being increasingly applied to the realm of healthcare. This abstract delves into the intersection of health care and NLP, highlighting how this technology is being used to enhance various aspects of the healthcare industry. From analyzing medical records and extracting relevant information to aiding in diagnosis and treatment recommendations, NLP is playing a pivotal role in transforming how healthcare professionals interact with data and make informed decisions. This abstract provides an overview of the key applications and benefits of employing NLP in healthcare, showcasing its potential to improve patient outcomes and streamline medical processes. This research seeks to harness the power of advanced computational linguistics to revolutionize various aspects of the healthcare industry. By enabling computers to understand and interpret human language, NLP has the potential to drive transformative changes NLP-powered systems can analyze vast amounts of medical literature, patient records, and research findings to provide healthcare practitioners with timely and relevant information. This assists in making well-informed decisions regarding diagnoses, treatment plans, and prognoses. NLP techniques facilitate the extraction of pertinent information from unstructured medical records, including patient histories and doctor's notes. This structured data can then be used for research, trend analysis, and epidemiological studies, contributing to evidence-based medicine. Versatile with unique alternatives a new method for optimization is proposed MOORA. This method is objective denotes the matrix of responses of the alternatives, however, proposing better policies, which rates are used. Well established. Multi-objective another method for optimization is used for comparison, reference point method. Then, various competitions this proved to be the best choice among the methods. From the result BC2GM is in 1st rank whereas BC5- Disease is in lowest rank.

Health Care Natural Language Processing (NLP) Using MOORA Method

The field of natural language processing (NLP) is being increasingly applied to the realm of healthcare. This abstract delves into the intersection of health care and NLP, highlighting how this technology is being used to enhance various aspects of the healthcare industry. From analyzing medical records and extracting relevant information to aiding in diagnosis and treatment recommendations, NLP is playing a pivotal role in transforming how healthcare professionals interact with data and make informed decisions. This abstract provides an overview of the key applications and benefits of employing NLP in healthcare, showcasing its potential to improve patient outcomes and streamline medical processes. This research seeks to harness the power of advanced computational linguistics to revolutionize various aspects of the healthcare industry. By enabling computers to understand and interpret human language, NLP has the potential to drive transformative changes NLP-powered systems can analyze vast amounts of medical literature, patient records, and research findings to provide healthcare practitioners with timely and relevant information. This assists in making well-informed decisions regarding diagnoses, treatment plans, and prognoses. NLP techniques facilitate the extraction of pertinent information from unstructured medical records, including patient histories and doctor's notes. This structured data can then be used for research, trend analysis, and epidemiological studies, contributing to evidence-based medicine. Versatile with unique alternatives a new method for optimization is proposed MOORA. This method is objective denotes the matrix of responses of the alternatives, however, proposing better policies, which rates are used. Well established. Multi-objective another method for optimization is used for comparison, reference point method. Then, various competitions this proved to be the best choice among the methods. From the result BC2GM is in 1st rank whereas BC5- Disease is in lowest rank.

Composite structure of human mind revealed by HuPoTest

IntroductionHuPoTest is a mental test and training procedure as well discovered incidentally in 1967 during developing color photos in complete dark in successive baths for seconds. I observed that I was able to count seconds mentally with high repeatability. I was curious to check my skill by comparing my count with a commercial stopwatch with the help of another person. The results were very interesting, so I extending progressively this experiment to other persons and I was able to establish the correlation between more and more calculated parameters with the particular psychic patterns of the persons under test (PUT). In fact, HuPoTest is a calibration of personal mental-timer compared to a standard stopwatch. I test myself periodically and the results are published (Dragan, GDF Databanks Bull., 2021; 25(6), 1-4).ObjectivesStudy of a large variety and number of systems in transformation revealed their composite structure, namely these have one component in transformation (Ctr) and an inert one (Cin) (Dragan, GDF Databanks Bull., 2011; 15(2), 1-19).This is the case of the human mind which is in permanent transformation, i.e. in continuous more or less coherent thinking. HuPoTest can establish the size of Ctr, Cin, ctr – the size of kinetic unit constituting Ctr and the coupling strength (CS) between Ctr and Cin.MethodsPUT has to count mentally 5, 10, 15 and 20 seconds for 8-10 times each value by using a standard stopwatch and comparing the statistically retrieved matrix of measured values with the above mentioned imposed standard values. I was able to test face-to-face approximately 4000 persons during more than 50 years by collecting a huge databank. I explained in many publications the exact procedure, the majority of calculations and the significance of the resulted parameters by correlating the obtained results with the PUT mental pattern (Dragan, GDF Databanks Bull., 2019; 23(1) 1-6).ResultsThe final results obtained by myself in the period of 28.05 – 03.07.2022 (A to CII) with overall of 48 tests are presented in attached figures by using a standard stopwatch created by Mihai Dornea developer at National Instruments on LabView® platform with an accuracy of 10 μs. Four distinct behaviors are revealed showing the good evolution of mind by decreasing Ctr and CS and increasing ctr by correct and continuous training.Image:ConclusionsHuPoTest is a highly efficient test and mental training procedure as well applied periodically in view to achieve a good and stable mental performance ensuring also a stable and good body health according to the well known quotations “sound mind in sound body” and "mind is the builder and body is the temple”. Such mental training becomes absolutely necessary taking into account that the survivors of the already started global war culminating at around 2035 will be persons with properly trained minds. I am available without any obligation for help anyone willing to try and practice HuPoTest.Disclosure of InterestNone Declared

Finite Block Method with Chebyshev Polynomials Applied to Cracked Plate in Functionally Graded Materials

The finite block method (FBM) with Chebyshev polynomials is developed in this paper for the functionally graded material (FGM) of two-dimensional fracture problem. The main idea is to divide domain into few blocks. By introducing the mapping technique, a block of quadratic type is transformed from Cartesian coordinate to normalised coordinate with eight seeds two dimensions. The differential matrices in physical domain are determined from that in the normalised transformed system. The accuracy of the FBM with Chebyshev polynomials is demonstrated with two examples and comparisons have been implemented with different numerical approaches.

A Gateway Framework to Guide Major Health System Changes Comment on "'Attending to History' in Major System Change in Healthcare in England: Specialist Cancer Surgery Service Reconfiguration".

Recent events - on both a global scale and within individual countries - including the lockdowns associated with COVID-19 pandemic, inflation concerns, and political tensions, have increased pressure to reconfigure social services for ongoing sustainability. Healthcare services across the world are undergoing major system change (MSC). Given the complexity and different contextual drivers across healthcare systems, there is a need to use a variety of perspectives to improve our understanding of the processes for MSC. To expand the knowledge base and develop strategies for MSC requires analysing change projects from different perspectives to distil the elements that drove the success. We offer the Gateway Framework as a collaborative transformational system tool to assess and reorganise operations, services, and systems of healthcare organisations. This framework and guiding questions, accounts for past events whilst being proactive, future orientated, and derived from externally defined and a standardised requirements to promote safe, high-quality care.

Penetration of DWT & ANFIS to Power Transmission Disturbances

This study proposes a hybrid method to classify and estimate the location of short circuit disturbance on power transmission lines. The hybrid method uses Discrete Wavelet Transform (DWT) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The transmission system is implemented in a real system, in which the electric power transmission system on the KP bus to the GS bus is with a length of 64 Km. The DWT is used to process information from each phase voltage and current transient signal as well as the zero-sequence current for one cycle after the disturbance has started. The ANFIS classification is designed to detect disturbance on each phase and ground in determining the type of short circuit disturbance. ANFIS estimation is used to measure the location of disturbance that occur on the transmission line. The training and testing data are generated by simulating the types of short circuit disturbance using software with variations in disturbance location and fault resistance. The result is that the disturbance classification is with 100% accuracy and the estimated disturbance location is with the lowest error of 0.0006% and the highest error is 0.03%.

The development direction of educational leadership in the context of globalization

Information and communication technology, represented by computer and network technology, is greatly changing the way of life and communication of human beings. Therefore, in the 21st century, traditional schools and traditional education systems around the world will be presented with both opportunities and challenges for new development prospects. The construction of educational leadership will be an important key to improve the quality and charm of teachers. The United Nations Educational, Scientific and Cultural Organization (UNESCO) brings together transformative visions, transformative knowledge systems and transformative skills, It is regarded as the core point in the goal framework of educational leadership construction. The improvement of educational "leadership" is mainly carried out by improving the ability to construct multi-dimensional "change vision", expanding change knowledge based on diversified knowledge system, and improving "change skills" based on optimization management. The above concepts and practices reflect the characteristics of emphasizing the organic combination of international and local strategic thinking, the organic combination of knowledge mastery and innovation, and the organic combination of professional and scientific teaching management, which have an important impact on the development trend of China's educational leadership.

Control strategies and dynamic experimental tests on the wide-range and rapid load regulation of a first pilot multi-megawatts fossil-fired supercritical CO2 power system

Supercritical CO2 (sCO2) power system is a research front in recent years due to its high efficiency and flexibility which is considered as a transformative power system in terms of consumption of the fluctuated and intermittent renewables. The merits of sCO2 power systems have been widely shown by small-scale test loops. However, it is still very lack of the investigations on the control strategies based on real-time dynamic operational data of large-scale multi-megawatts pilot power system, especially for wide-range and rapid load regulation to demonstrate the feasibility of large-scale utilization and commercialization. A worldwide first pilot multi-megawatts SMART (Supercritical CO2 Modular Advanced Research and Test) fossil-fired power system has been built and operated for more than 1000 h at TPRI (Thermal Power Research Institute), Xi’an, China with turbine inlet parameters of 20 MPa/600 °C/600 °C. The influence of key parameters on the dynamics of the system are experimental studied. In-depth tests of the wide-range load regulation and rapid load regulation of the SMART@TPRI power system are performed. The test results show that the key target parameters such as turbine inlet temperatures, compressor inlet temperature and pressure, sCO2 mass flow rate and exhaust flue gas temperature can be well regulated by a set of well-developed control modules to ensure an efficient and safe operation during load variations. The SMART@TPRI power system can run stably and flexibly within the whole range from 0 %Pe to 100 %Pe. The averaged load ramp and load reduction rate achieves 6.35 %Pe/min and −6.37 %Pe/min, respectively, which is almost 3 ∼ 4 times than that of steam power system, under the control strategy of sliding pressure with fixed turbine inlet temperature by a combination of several novel well-developed control modules.

Pyrate: a novel system for data transformations, reconstruction and analysis

The Pyrate framework provides a dynamic, versatile, and memory-efficient approach to data format transformations, object reconstruction and data analysis in particle physics. The system is implemented with the Python programming language, allowing easy access to the scientific Python ecosystem and commodity big data technologies. Developed within the context of the SABRE South experiment for dark matter direct detection, Pyrate relies on a blackboard design pattern where algorithmic trees are dynamically generated throughout a run where root nodes are managed by a central control unit. The system guarantees an economical usage of memory allocated by algorithms where individual algorithmic instances can be reused for multiple objects. The framework is intended to improve upon the user experience, portability and scalability of offline software systems currently available in the particle physics community with particular attention to medium to small-scale experiments.

Let's Not Reinvent the Wheel: Using Communities of Learning and Practice to Address SDOH and Advance Health Equity.

Despite advances in knowledge and science, evidence indicates that health care disparities and inequities continue to exist across diverse populations. Educating and training the next generation of health professionals to focus on addressing social determinants of health (SDOH) and advancing health equity is a key priority. This aim requires educational institutions, communities, and educators to strive for change in health professions education, to attain the goal of creating transformative educational systems that better meet the public health needs of the 21st Century. Communities of practice (CoPs) are groups of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly. The National Collaborative for Education to Address Social Determinants of Health (NCEAS) CoP is focused on integrating SDOH into the formal education of health professionals. The NCEAS CoP is one model to replicate how health professions educators can work together for transformative health workforce education and development. The NCEAS CoP will continue to advance health equity by sharing evidence-based models of education and practice that address SDOH and help build and sustain a culture of health and well-being through sharing models for transformative health professions education. Our work is an example that shows we can build partnerships across communities and professions, thereby freely sharing ideas and curricular innovations that address the systemic inequities that continue to fuel persistent health disparities and inequities, and contribute to moral distress and burnout of our health professionals.

Core-Shell Type Lipidic and Polymeric Nanocapsules: the Transformative Multifaceted Delivery Systems.

Amongst the several nano-drug delivery systems, lipid or polymer-based core-shell nanocapsules (NCs) have garnered much attention of researchers owing to its multidisciplinary properties and wide application. NCs are structured core-shell systems in which the core is an aqueous or oily phase protecting the encapsulated drug from environmental conditions, whereas the shell can be lipidic or polymeric. The core is stabilized by surfactant/lipids/polymers, which control the release of the drug. The presence of a plethora of biocompatible lipids and polymers with the provision of amicable surface modifications makes NCs an ideal choice for precise drug delivery. In the present article, multiple lipidic and polymeric NC (LNCs and PNCs) systems are described with an emphasis on fabrication methods and characterization techniques. Far-reaching applications as a carrier or delivery system are demonstrated for oral, parenteral, nasal, and transdermal routes of administration to enhance the bioavailability of hard-to-formulate drugs and to achieve sustained and targeted delivery. This review provide in depth understanding on core-shell NC's mechanism of absorption, surface modification, size tuning, and toxicity moderation which overshadows the drawbacks of conventional approaches. Additionally, the review shines a spotlight on the current challenges associated with core-shell NCs and applications in the foreseeable future.

GRF–GIF chimeric proteins enhance in vitro regeneration and Agrobacterium-mediated transformation efficiencies of lettuce (Lactuca spp.)

Key messageGRF–GIF chimeric proteins from multiple source species enhance in vitro regeneration in both wild and cultivated lettuce. In addition, they enhance regeneration in multiple types of lettuce including butterheads, romaines, and crispheads.The ability of plants to regenerate in vitro has been exploited for use in tissue culture systems for plant propagation, plant transformation, and genome editing. The success of in vitro regeneration is often genotype dependent and continues to be a bottleneck for Agrobacterium-mediated transformation and its deployment for improvement of some crop species. Manipulation of transcription factors that play key roles in plant development such as BABY BOOM, WUSCHEL, and GROWTH-REGULATING FACTORs (GRFs) has improved regeneration and transformation efficiencies in several plant species. Here, we compare the efficacy of GRF–GIF gene fusions from multiple species to boost regeneration efficiency and shooting frequency in four genotypes of wild and cultivated lettuce (Lactuca spp. L.). In addition, we show that GRF–GIFs with mutated miRNA 396 binding sites increase regeneration efficiency and shooting frequency when compared to controls. We also present a co-transformation strategy for increased transformation efficiency and recovery of transgenic plants harboring a gene of interest. This strategy will enhance the recovery of transgenic plants of other lettuce genotypes and likely other crops in the Compositae family.