Integral Solution Research Articles

Carbon dioxide reduction utilizing a bismuth halide perovskite as immobilized photocatalyst in a 3D printed microreactor

The rising concerns about CO2 levels in the atmosphere and energy dependency on non-renewable sources, such as fossil fuels, could find an integral solution in CO2 photocatalytic reduction. The present work explores two alternatives to the main hindering factors for this reaction, i.e. the reactor configuration and the photocatalyst utilized. A microreactor was designed and 3D printed, providing a cheap and versatile reaction platform. Three bismuth halide perovskites, Cs3Bi2Cl9, Cs3Bi2I9, and Cs4MnBi2Cl12, were synthesized and characterized by their band gaps (Eg ); Cs3Bi2I9 presented the lowest Eg and was therefore chosen for further evaluation as potential CO2-reduction photocatalyst. Aqueous-phase photocatalytic CO2 reduction was achieved using this perovskite in the microreactor, obtaining CO as a reduction product with maximal production rates of 737 μmol gcat −1 h−1. The reaction system was evaluated under different flow rates and light intensities. A balance between space-time and reactant feed was found to define the behavior of CO concentration and production in the microreactor. For the light intensity, it was observed that as it increased, both CO production and concentration increased due to generating more electron–hole pairs, favoring the photocatalytic reaction. With these results, Cs3Bi2I9 perovskite immobilized in the designed microreactor demonstrates having great potential as an effective CO2 photocatalytic reduction system.

Investigation on continuous dependence and regularity solutions of functional integrodifferential equations

In this work, to show the existence and continuous dependence of integral solution for neutral integro-differential equation with finite delay situation. This result established by using integrated resolvent operator with support of Lipschitz continuous and uniqueness part using Banach contraction mapping. Also study the existence of strict solution on reflexive and general Banach spaces. In the last section, an example is provided related to this theory.

Design and real-time implementation of wind–photovoltaic driven low voltage direct current microgrid integrated with hybrid energy storage system

Low-voltage direct current (LVDC) microgrid has emerged as a new trend and smart solution for the seamless integration of distributed energy resources (DERs) and energy storage systems (ESS). This paper presents a coordinated controlled power management scheme (PMS) for wind–solar fed LVDC microgrid equipped with an actively configured hybrid energy storage system (HESS). The comprehensive design, development, implementation and thorough result analysis is presented to validate the proposed PMS performance. It dynamically adapts to different operating modes based on the availability of DERs and load demand. By incorporating the HESS, the scheme effectively handles sudden and gradual power surges, leading to swift regulation of the DC bus voltage, effective power balance and reduced stress on the battery. A laboratory test bench is developed comprising a wind power generating unit (WPGU), solar power generating unit (SPGU), battery energy storage system (BESS), and supercapacitor energy storage system (SCESS). Moreover, the detailed design and testing of various converters, gate drivers, filters, signal conditioning along with calibration of sensors are discussed. The developed PMS is executed using a DS1103 digital controller confirming its effectiveness in facilitating smooth mode transition and proper power sharing among all DERs and loads.

Design of a Modular Energy Production–Storage System for a Sustainable Bicycle

This paper presents a new concept of a modular system for the production and storage of energy in a bicycle at any speed above 9 km/h. User-Centered Design methodology was applied to establish the design premises, and then each component of the modular system was selected, developed, and refined separately, carrying out all component integration (hub dynamo, USB charger, batteries, and solar panel) by means of a simple extension cable. Then, simulations were made with different software tools to create a design candidate. A new design of an integrated modular energy production–storage system was obtained, aiming to cover the needs of long-distance bikers and daily bike commuters. The designed system can charge its own batteries and power devices connected to the USB charger from a speed of 9 km/h. The system entails a modular integration solution that is not only cost-effective but also highly efficient. Its ergonomic design allows users to effortlessly replace batteries as and when needed. Current models on the market do not possess this integration.

Solving a Typical Small Sample Size MRSM Dataset Problem Using a Flexible Hybrid Ensemble Approach for Credibility

Multiresponse surface methodology often involves small data analytics which, statistically, have regression modelling credibility problems. This is worsened by dataset, model selection and solution methodology uncertainties. It is difficult for solution methodologies which select and use single best models per response at simultaneous optimisation to effectively deal with these problems. This paper exploited the fact that model selection criteria choose differently, in a flexible hybrid ensemble system, to generate several solutions for integration and comparison. Mean square prediction error, with bias-variance-covariance decomposition values, was computed and analysed at simultaneous optimisation. Results suggest that the credibility of the final solution is enhanced when working with multiple models, solution methodologies and results. However, the results do not show any significance of small sample size correction to model selection criteria and analysis of bias-variance-covariance decompositions at simultaneous optimisation does not encourage dependence on theoretical optimality for best results.

Modelling and analysis of the horizontal configuration of tidal fences in barrages

Tidal stream turbines are becoming an affordable option for harvesting sustainable energy in coastal areas. They can be retrofitted in barrages, providing an integral solution for flood protection and emission-free power generation, within environmental constraints. To optimize the turbine-barrage configuration with respect to these objectives, simulation tools are needed to predict the efficiency of the turbines as well as their impact on the adjacent tidal system. These tools should be based on an accurate representation of the underlying flow processes, which cover a wide range of spatial scales — from meters at the barrage and turbines to tenths of kilometers in the tidal basin. This article presents the development of such a tool by linking an analytical model for turbine fences in barrage gates to a regional flow model. The turbine model is validated with experimental data, and data from a thoroughly monitored tidal energy pilot project. Simulations reveal how clustering the turbines in small arrays can increase their efficiency, owing to array blockage effects, with only little effect on the tidal exchange. We also demonstrate the potential of using turbine fences to manipulate the tidal jet, issued from the barrage, with benefits for coastal — and wildlife protection in the basin. The presented research helps understanding how turbine fences in barrages can be configured with high energy yield and calculated impact to the environment.

Seamless Integration of Computer-Adaptive Patient Reported Outcomes into an Electronic Health Record.

Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research studies outside the electronic health record (EHR), but growing demand for clinical use of PROs requires creative information technology solutions for integration into the EHR. This paper describes the introduction of PROMIS CATs into the Epic Systems EHR at a large academic medical center using a tight integration; we describe the process of creating a secure, automatic connection between the application programming interface (API) which scores and selects CAT items and Epic. The overarching strategy was to make CATs appear indistinguishable from conventional measures to clinical users, patients, and the EHR software itself. We implemented CATs in Epic without compromising patient data security by creating custom middleware software within the organization's existing middleware framework. This software communicated between the Assessment Center API for item selection and scoring and Epic for item presentation and results. The middleware software seamlessly administered CATs alongside fixed-length, conventional PROs while maintaining the display characteristics and functions of other Epic measures, including automatic display of PROMIS scores in the patient's chart. Pilot implementation revealed differing workflows for clinicians using the software. The middleware software was adopted in 27 clinics across the hospital system. In the first 2 years of hospital-wide implementation, 793 providers collected 70,446 PROs from patients using this system. This project demonstrated the importance of regular communication across interdisciplinary teams in the design and development of clinical software. It also demonstrated that implementation relies on buy-in from clinical partners as they integrate new tools into their existing clinical workflow.

The challenges and solutions of technology integration in rural schools: A systematic literature review

The digital divide between urban and rural schools challenges efforts to promote technology integration in education, and contributes to growing educational inequity in many contexts. Using the most current version of Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA 2020), we identified and extracted 36 articles and conference papers on the use of technology in rural schools from the Scopus and Web of Science databases. We used Critical Interpretive Synthesis to identify the challenges and solutions involved in integrating technology in rural schools. The analysis revealed 29 challenges, which were categorized using the framework of the ecological perspective into macro level, meso level, and micro level challenges. The analysis also identified solutions to the challenges discussed in these studies. By focusing on the challenges and proposed solutions at different contextual levels, this review is intended to identify what constitutes good practices when integrating technology in rural schools. Future research should focus on factors which facilitate the use of technology and how the integration of technology impacts students’ learning experiences and achievement in rural schools.

ОПТИМІЗАЦІЯ ЛОГІСТИКИ ТА РЕАЛІЗАЦІЇ ПРОДУКЦІЇ В СІЛЬСЬКОГОСПОДАРСЬКИХ ПІДПРИЄМСТВАХ НА УМОВАХ КООПЕРАЦІЇ

This extensive article delves into the critical importance of optimizing transport logistics within the agricultural sector, providing a thorough examination of key algorithms and advanced techniques aimed at significantly improving industry efficiency. The primary focus is dedicated to the meticulous selection of optimal routes, involving a detailed review of state-of-the-art routing algorithms and dynamic programming techniques. The article systematically guides readers through concrete steps for determining optimal delivery routes, considering a myriad of factors such as distance, road conditions, transport volume, type, delivery deadlines, and transportation costs. The complexity of this task necessitates an in-depth analysis of various elements, and the article provides valuable insights into how these considerations collectively contribute to the overall efficiency of agricultural transport logistics. Emphasizing the pivotal role of effective resource management, the article underscores the need for strategic allocation, transportation, and utilization of diverse resources, including transport assets, human resources, equipment, time, and more. The integration of modern technologies is identified as a crucial component for achieving optimization goals, ensuring real-time data analysis, efficient communication, and adaptive decision-making. As a practical outcome, the article offers strategic recommendations for the implementation of optimization approaches within the agricultural logistics framework. These recommendations encompass innovative solutions for route planning, resource allocation, and technology integration. The overarching goal is to enhance the viability and productivity of agriculture, positioning logistical optimization as a key driver for sustainable growth in the industry. The synthesis of algorithmic strategies and cutting-edge technologies is positioned as instrumental in fostering advancements within the agricultural landscape. The article serves as a comprehensive guide, catering to various stakeholders, including farmers, logistics professionals, and policymakers, who aspire to leverage logistical optimization for transformative outcomes in agriculture. In conclusion, this in-depth exploration not only highlights the immediate benefits of optimizing transport logistics but also underscores the long-term sustainability and growth potential it brings to the agricultural sector. The integration of advanced algorithms and technologies is positioned as a cornerstone for addressing the evolving challenges and demands of modern agriculture.

M-Srivastava hypergeometric functions: integral representations and solution of fractional differential equations

In this paper, we introduce a new extensions of Srivastava’s triple hypergeometric functions HA, HB and HC, by using an modified beta function, which given with a generalized M-series in its kernel. We also introduce a new extension of Appell’s hypergeometric function of the first kind by using the same modified beta function. Furthermore, we give some integral representations of the new extensions of Srivastava’s triple hypergeometric functions. Finally, we obtain solutions of fractional differential equations involving new extensions of Srivastava’s triple hypergeometric functions.

An Integrated TMR-based Current Sensing Solution for WBG Power Modules and Converters

An Integrated TMR-based Current Sensing Solution for WBG Power Modules and Converters

Исследование динамики свободной поверхности, ограничивающей конечную массу самогравитирующего газа

The work researches the evolution of the free surface which limits the polytropic, isentropic and self-gravitating ideal gas moving in vacuum. Gas currents are described with the mathematical model of gas dynamics, constructed due to the system of nonlinear integro-differential equations, expressed in Euler coordinate system. The transformation of the given system to the Lagrangian coordinates lets reduce it to the equivalent system consisting of integral Voltair’s equations and the equation of continuity in the Lagrangian form, and also it lets break down the unknown boundaries. Free boundary is determined as a great number of points of the system of integral equations solution achieved when depicting the boundary points of the initial area within the point of the moving area. For the system there is the proved theorem of the existence and uniqueness of the solution of the Cauchy problem in the space of the infinitely differentiated functions. Methods of qualitative research of the system of gas dynamics were applied in the work for the research of the evolution of the free surface.

Co-creation in healthcare and research to improve service delivery for young people with chronic pain.

The process of co-creation can enable more effective, agile and integrated healthcare solutions achieving outcomes that effectively translate to healthcare delivery. Collaborative knowledge generation is particularly important in fields such as pediatric chronic pain where there is a complex interplay between biological, social, environmental, emotional, familial and school factors. The co-creation initiative described here was designed to amplify the voices of youth with chronic pain and their families and a variety of key stakeholders and generate novel approaches to the management of chronic pediatric pain in the setting of the South Australian Pediatric Chronic Pain Service. Stakeholders who were identified as influential in this ecosystem were allocated to 6 groups. A skilled facilitator co-prepared and delivered the workshop, engaging participants in three structured activities. Firstly, the challenges to service delivery were outlined, followed by the groups discussing what is currently working. The second activity involved lateral thinking without restrictions on time, resources or system to generate solutions to the key challenges presented. Finally, stakeholders were asked to agree on a generated solution from Activity 2 and build a case for actionable implementation of this solution. Data were summarised by the workshop facilitator and reflexive thematic analysis was used for coding and generating themes. From Activity 1, six themes collectively demonstrated that stakeholders valued many of the existing strengths of the service delivery, but some areas such as pain education was undervalued. Activity 2 generated solutions from high-level ideas to more day-to- day management strategies. Each of six groups generated unique solutions to an identified challenge for Activity 3. Engaging a wide variety of stakeholders in collaborative knowledge generation successfully provided the South Australian Pediatric Chronic Pain Service with a variety of novel, scalable solution across the healthcare continuum. Equally important is that this initiative helped to raise awareness about the complex issues faced in pediatric chronic pain care and helped to establish new partnerships that have led to enhanced service delivery.

Integration Challenges and Solutions for Solar-Powered Electric Vehicle Charging Infrastructure: From Panel to Battery

The integration of solar power with electric vehicle (EV) charging infrastructure presents a promising avenue to foster sustainable transportation. This study delves into the multifaceted challenges encountered in the synthesis of solar-powered EV charging stations and proffers solutions that span the complete energy transfer chain from photovoltaic panels to EV batteries. Initial concerns address the intermittent nature of solar energy and its impact on the reliability of power delivery. Advanced energy management strategies are explored, incorporating predictive analytics and real-time adjustment mechanisms to enhance the consistency and efficiency of power flow. The second part of the investigation scrutinizes the power electronics interface, emphasizing the need for high-efficiency converters that can operate effectively over varied solar insolation levels. Novel circuit topologies are presented, alongside adaptive control algorithms designed to optimize the power conversion process. Collectively, the findings underscore the potential of solar-powered EV charging infrastructure to not only support the decarbonization of transportation but also to contribute to the stability and efficiency of the power grid. The intersection of power electronics, energy management, and grid integration forms the cornerstone of this endeavor, with each domain providing critical components to the holistic solution. It culminates in a set of recommendations for policy, design, and operation that can accelerate the adoption of this technology.

Designing a new integrated control solution for electric power steering systems based on a combination of nonlinear techniques.

An EPS system is used to improve the stability and safety of the car when steering while also simplifying the steering process. This article introduces a novel control solution for the EPS system called BSSMCPID. This algorithm combines two nonlinear techniques, BS and SMC, with the input signal corrected by a PID technique. This algorithm provides three new contributions compared to existing algorithms: reducing system errors and eliminating phase differences, ensuring stability even when exposed to external disturbances, and reducing power consumption. The system's stability is evaluated according to the Lyapunov criterion, while the algorithm's performance is evaluated based on numerical simulation results. According to the article findings, the RMS error of the steering column angle and steering motor angle values (controlled objects) is approximately zero, and the RMS error of the steering column speed and steering motor speed is about 0.01 rad/s, which is much lower than the results obtained with traditional BS and PID controllers. When the EPS system is controlled by the integrated nonlinear method proposed in this work, the output values always closely follow the reference values with negligible errors under all investigated conditions. Additionally, power steering performance increases as speed decreases or driver torque increases, which follows the ideal assisted power steering curve. In general, the responsiveness and stability of the system are always ensured when applying this algorithm.

Определение пожарной опасности большегрузных карьерных транспортных средств

Purpose. Heavy wheel-load mining trucks present a fire hazard. A key distinction from other vehicles, aside from their large size, is the presence of significant volumes (over 3 000 liters) of flammable lubricants and other operating fluids, as well as inaccessible areas in the event of a fire. Based on statistical data on fire locations and combustible materials, this article identifies the main sources of fire hazards in heavy wheel-load mining trucks, using a haul truck as an example. Methods. The study employed the following theoretical methods: analysis, modeling, and deduction. Findings. The analysis of statistical data on fire locations and combustible materials in heavy wheel-load mining trucks revealed that such equipment generates a significant amount of thermal energy and contains large amounts of flammable materials. The study identified the main fire-prone mechanisms and components, which are crucial for further evaluating the effectiveness of automatic fire suppression systems used in this type of trucks. Research application field. The results of this study provide basis for approaches to ensuring fire safety of heavy wheel-load mining trucks. Conclusions. The study identified potential sources of ignition in heavy wheel-load mining trucks. Further research on comprehensive protection measures for heavy wheel-load mining trucks will lead to new integrated design solutions to protect mining equipment from fire, prevent direct and indirect material damage, and reduce the risk of injury or death.

On integrable and approximate solutions for Hadamard fractional quadratic integral equations

<abstract><p>This article addressed the integrable and approximate solutions of Hadamard-type fractional Gripenberg's equation in Lebesgue spaces $ L_1[1, e] $. It is well known that the Gripenberg's equation has significant applications in mathematical biology. By utilizing the fixed point (FPT) approach and the measure of noncompactness (MNC), we demonstrated the presence of monotonic integrable solutions as well as the uniqueness of the solution for the studied equation in spaces that are not Banach algebras. Moreover, the method of successive approximations was successfully applied and, as a result, we obtained the approximate solutions for these integral equations. To validate the obtained results, we provided several numerical examples.</p></abstract>

Perspectives on AI Architectures and Codesign for Earth System Predictability

Abstract Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper. Significance Statement This study aims to provide perspectives on AI architectures and codesign approaches for Earth system predictability. Such visionary perspectives are essential because AI-enabled model-data integration has shown promise in improving predictions associated with climate change, perturbations, and extreme events. Our forward-looking ideas guide what is next in codesign to enhance Earth system models, observations, and theory using state-of-the-art and futuristic computational infrastructure.

Challenges and solutions to system-wide use of precision oncology as the standard of care paradigm.

The personalised oncology paradigm remains challenging to deliver despite technological advances in genomics-based identification of actionable variants combined with the increasing focus of drug development on these specific targets. To ensure we continue to build concerted momentum to improve outcomes across all cancer types, financial, technological and operational barriers need to be addressed. For example, complete integration and certification of the 'molecular tumour board' into 'standard of care' ensures a unified clinical decision pathway that both counteracts fragmentation and is the cornerstone of evidence-based delivery inside and outside of a research setting. Generally, integrated delivery has been restricted to specific (common) cancer types either within major cancer centres or small regional networks. Here, we focus on solutions in real-world integration of genomics, pathology, surgery, oncological treatments, data from clinical source systems and analysis of whole-body imaging as digital data that can facilitate cost-effectiveness analysis, clinical trial recruitment, and outcome assessment. This urgent imperative for cancer also extends across the early diagnosis and adjuvant treatment interventions, individualised cancer vaccines, immune cell therapies, personalised synthetic lethal therapeutics and cancer screening and prevention. Oncology care systems worldwide require proactive step-changes in solutions that include inter-operative digital working that can solve patient centred challenges to ensure inclusive, quality, sustainable, fair and cost-effective adoption and efficient delivery. Here we highlight workforce, technical, clinical, regulatory and economic challenges that prevent the implementation of precision oncology at scale, and offer a systematic roadmap of integrated solutions for standard of care based on minimal essential digital tools. These include unified decision support tools, quality control, data flows within an ethical and legal data framework, training and certification, monitoring and feedback. Bridging the technical, operational, regulatory and economic gaps demands the joint actions from public and industry stakeholders across national and global boundaries.

The robot uprising is here: Is scholarly publishing ready?

Key points Research integrity is impossible to achieve without digital innovation. Humans and machines have complementary strengths, which we should harness for collaboration. We have backed ourselves into a corner with the way we have built current publishing infrastructure. Today's research integrity solutions are downstream, but innovation requires integration throughout publishing infrastructure.