Hybrid Solution Research Articles

Innovative approaches in discussions of diabetes among healthcare sector actors in Germany.

The dramatic growth in the rate of diabetes prompts serious debates about awareness, early diagnosis, and care interventions. This Viewpoint aims to explore, from the perspectives of healthcare sector representatives, what challenges and difficulties they face in dealing with diabetes and how these can be overcome. We applied the World Café method for group discussions, which enabled us to bring together 50 stakeholders. They identified challenges at institutional and structural levels under the concepts of awareness, digitalisation, and new forms of care and shared their suggestions for feasible solutions. We learned there is a need for a diabetes map of Germany to identify risk groups and that hybrid solutions should be implemented for treatment, care, prevention, and early diagnosis, considering digital infrastructure. Also, the demand for digital innovation in the healthcare system raised concerns about information transparency and data management.

Cold chain distribution network design with heterogeneous fleet under carbon reduction policy application effect

ABSTRACT To integrate cold chain distribution network design problem with heterogeneous fleet, a multi-objective optimisation model is proposed to simultaneously optimise distribution routes, the quantity of internal combustion and electric refrigerated trucks (ERTs), and the number and location of distribution centres and charging stations with time window constraints, where the cold chain distribution operating cost and the customer dissatisfaction cost are minimised. A hybrid solution methodology, combining a multi-objective artificial fish swarm algorithm with a label-based optimisation algorithm, is presented to address this model. Extensive computational experiments verify the effectiveness of the proposed method. Moreover, a sensitivity analysis, focusing on the range of ERTs, the purchase subsidy for ERTs, the carbon tax and the carbon emission quota, informs the development of diverse carbon reduction policies. A comparative analysis of the implementation effect of carbon reduction policies can provide optimisation decision support for promoting sustainability in the electrification of cold chain distribution.

Adaptive evolution and dynamic mechanism of resort socioecological system in tourism cities: The case of Qinhuangdao, China

Resort socioecological systems (SESs) have changed significantly worldwide because of rapid urbanisation and tourism development. Exploring the dynamics and driving mechanisms of resort SES at different stages is beneficial for understanding urban adaption to future pressure, creating elaborate strategies for tourism innovation, and achieving sustainable resort development. Therefore, this study proposed the Adaptive-TALC model as a novel analytical framework for resort evolution, using Qinhuangdao Resort as an empirical case study. The results revealed that 1) from 1979 to 2023, Qinhuangdao tourism resort had been gradually transformed from a simple socioecological system based on natural resource utilization to a complex adaptive system integrating natural and human resource utilization, 2) governance systems played a pivotal role in resort evolution, and business utilized digital technology to innovate resort products, thereby accelerating system renewal and reorganisation, and 3) within the context of panarchy, Aranya's holiday products serve as a model for local businesses to improve and innovate their products and ultimately promote Qinhuangdao's sustainable development. This study contributes to theories of tourist destination evolution by providing a novel framework for the cognition of the tourism resource sustainable utilization in resorts and provides insights into innovative approaches such as nature-cultural hybrid solutions, adaptive urban planning, and digital tourism, enabling tourism cities to enhance their adaption and mitigate potential risks.

Nonlinear waves and transitions mechanisms for (2+1)-dimensional Korteweg–de Vries-Sawada-Kotera-Ramani equation

In this paper, state transition waves are investigated in a (2+1)-dimensional Korteweg–de Vries-Sawada-Kotera-Ramani equation by analyzing characteristic lines. Firstly, the N-soliton solutions are given by using the Hirota bilinear method. The breather and lump waves are constructed by applying complex conjugation limits and the long-wave limit method to the parameters. In addition, the transition condition of breather and lump wave are obtained by using characteristic line analysis. The state transition waves consist of quasi-anti-dark soliton, M-shaped soliton, oscillation M-shaped soliton, multi-peak soliton, W-shaped soliton, and quasi-periodic wave soliton. Through analysis, when solitary wave and periodic wave components undergo nonlinear superposition, it leads to the formation of breather waves and transformed wave structures. It can be used to explain the deformable collisions of transformation waves after collision. Furthermore, the time-varying property of transformed waves are studied using characteristic line analysis. Based on the high-order breather solutions, the interactions involving breathers, state transition waves, and solitons are exhibited. Finally, the dynamics of these hybrid solutions are analyzed through symbolic computations and graphical representations.

Towards a distributed nodes selection mechanism for federated learning applied to blockchain-based IoT

Integrating blockchain (BC) with Federated Learning (FL) shows promise but presents challenges, particularly in the selection of the most appropriate IoT nodes for sensitive tasks. Existing Artificial Intelligence (AI) based approaches are tailored to dynamic environments, but they are complex and resource-intensive. On the other hand, score-based methods are faster to implement but lack flexibility. In this paper, we propose a two-step hybrid solution which uses the reputation score approach to train a DRL model, creating a framework that combines the efficiency of deterministic methods with the adaptability of AI-based solutions. In fact, we designed a score-based method relying on devices attributes and behavior making the system operational from the outset. Also, this allows the gathering of relevant real-time data for training the DRL model. Besides, the variations in the performances of IoT devices pose a challenge in achieving synchronous aggregation. To address this, we designed a multi-level aggregation mechanism, which allows local models to be uploaded to the BC, where an aggregator is in charge of validation. The validated models are then aggregated into intermediate models. This process continues until a global model is formed. To evaluate our approach, we created several simulation scenarios including the number of nodes to assess scalability, the dropout rate to estimate availability, and the percentage of malicious nodes to evaluate the robustness of the system against attacks. These experiments aimed to demonstrate the effectiveness of our approach. The obtained results are promising highlighting its robustness and flexibility showing improved performance, security, and availability.

Numerical studies on the effects of the hybrid cooling and dust suppression solution in hot fully-mechanized mining face

With the increasing depth of coal mining, the hot and humid environment at the mining faces is becoming more severe. Mining in these conditions, coupled with the hazardous effects of coal dust, poses a significant risk to the health of coal miners. To improve the working conditions in underground coal mines, this study proposes a hybrid solution that combines evaporative cooling and dust suppression in fully mechanized working faces. Numerical models of the mining face are also created to simulate the cooling effects of the proposed solution. Additionally, the migration laws of water droplets from the spray system are also studied. The results indicate that the proposed solution can effectively improve thermal environments and suppress coal dust. This research can enhance the workplace safety in underground coal mines and provide valuable insights for addressing high airflow temperatures and concentrated dust levels.

Recent Trends and Future Prospects in Electric Vehicle Technologies: A Comprehensive Review

In addressing sustainability challenges within the transportation sector, the integration of electric vehicles (EVs) with renewable energy sources, notably solar and wind power, presents a promising solution. This comprehensive review delves into recent advancements and trends in EV technologies, covering crucial areas such as battery innovations, charging infrastructure, vehicle design, and market dynamics. Various EV technologies, including Plug-in Hybrid Electric Vehicles (PHEVs), battery-based EVs, Solar-powered EVs, and solar-wind hybrid EVs, are meticulously examined, with a particular focus on the feasibility and efficacy of solar-wind hybrid solutions. The review extends to battery technologies, emphasizing advancements in lithium-ion batteries and emerging chemistries like solid-state and lithium-sulfur batteries, which address barriers to EV adoption through enhanced energy density, charging efficiency, and cost-effectiveness. Additionally, the review scrutinizes the expansion of charging infrastructure, encompassing fast-charging stations, wireless charging technologies, and initiatives integrating smart grids, all aimed at providing convenient and efficient charging solutions to alleviate range anxiety and bolster EV attractiveness. Economic considerations, including initial investments, operational savings, and government incentives, are thoroughly analyzed alongside environmental benefits such as reduced greenhouse gas emissions and air pollution. Furthermore, a critical examination of the regulatory and policy framework supporting EVs sheds light on future policy directions, tax incentives, and regulatory measures. Real-world case studies showcasing successful implementations of solar-wind hybrid EV projects underscore their effectiveness and multifaceted impacts across diverse geographical areas. In conclusion, this review underscores the recent trends in EV technologies, emphasizing the feasibility and benefits of solar-wind hybrid EVs in achieving minimal emissions and incentivizing sustainable transportation practices.

An experimental investigation of a solar chimney integrated with a bladeless wind turbine for sustainable energy harvesting

The current study explores the potential of combining small-scale solar chimney systems with blade-less wind turbines for sustainable energy solutions in Egypt through mathematical modelling, numerical simulation, and experimental work. The integration of a vortex bladeless turbine and a conventional horizontal axis wind turbine in a hybrid energy harvester solar chimney system (VBSCS) was evaluated, as well as the effect of changing the absorber material on improving the system's performance. Shredded rubber improves heat absorption in solar chimney collectors, optimizing energy conversion and providing a sustainable, eco-friendly solution while addressing challenges and cost-effectiveness in implementing this hybrid solution. The mathematical model predicted the highest power at 0.38 W, while the CFD model yielded 0.298 W. Experimental results showed power outputs of 0.18 and 0.25 W for the SCS with concrete and shredded rubber absorbers, respectively. In addition, the VBSCS with a concrete absorber produced 0.29 W. The determined percentage improvement over the SCS with a concrete absorber was 61.1 % for the VBSCS and 38.9 % for the SCS with a black rubber absorber. These findings demonstrate the delicate interplay of design aspects and material choices that influence the performance of both bladeless wind turbines and solar collector systems.

Optimizing the integration of renewable energy sources, energy efficiency, and flexibility solutions in a multi-network pharmaceutical industry

In the contemporary landscape, roughly one-fourth of worldwide carbon dioxide emissions stem from industrial energy usage. In the industrial sector, improving the efficient and flexible coupling among different energy demands (electricity, heating, and cooling) and exploiting the integration of Renewable Energy Sources (RESs) and waste heat can lead to a drastic reduction in CO2 emissions, these are also the goals of the EU founded Horizon Europe FLEXIndustries project. This study aims to establish a cost-optimized decarbonization strategy for an energy-intensive industry, focusing on an Italian pharmaceutical company. It delves into the exploration of potential pathways and diverse energy mix configurations. The approach undertaken involves coupling a customized energy system simulation framework, specifically designed for the industrial site, with a Multi-Objective Evolutionary Algorithm (MOEA). The study, conducted with a focus on the year 2024, involves a comparative analysis of three distinct scenarios. Within the intricate and challenging constraints of the industrial demo site, 13 technologies were investigated. The outcomes of each scenario identify a set of 500 Pareto optimal solutions, obtained through 40,000 simulations. These results shed light on the compelling potential of hybrid solutions, showcasing the feasibility of achieving substantial decarbonization with only moderate increases in costs. The availability of land for RES technologies, along with the existence of a biomass supply chain in the region, emerge as pivotal determinants.

Aging effects in the COMPASS hybrid GEM-Micromegas pixelized detectors

Large-size hybrid and pixelized GEM-Micromegas gaseous detectors (40 × 40 cm2 active area) were developed and installed in 2014 and 2015 for the COMPASS2 physics program which started at the same time. That program involved in particular two full years of Drell-Yan studies using a high-intensity pion beam on a thick polarized target. Although the detectors were placed behind a thick absorber, they were exposed to an important flux of low energy neutrons and photons. The detectors were designed to drastically reduce the discharge rate, a major issue for non-resistive Micromegas in high hadron flux, by a factor of more than 100 compared to the former ones. A hybrid solution was chosen where a pre-amplifying GEM foil is placed 2 mm above the micromesh electrode. A pixelized readout was also added in the center of the detector, where the beam is going through, in order to track particles scattered at very low angles. The combination of the hybrid structure and the pixelized central readout allowed the detector to be operated in an environment with particle flux above 10 MHz/cm2 with very good detection efficiencies and spatial resolution. The performance has remained stable since 2015 in terms of gain and resolution, showing the interest of hybrid structures associating a GEM foil to a Micromegas board to protect gaseous detectors against discharges and aging effects.

Physical internet enabled sustainable and resilient production-routing problem with modular capacity

PurposeModular capacity units enable rapid reconfiguration, providing tactical flexibility to efficiently meet customer demand during disruptions and ensuring sustainability. Moreover, the Physical Internet (PI) enhances the potential of modular capacity in addressing efficiency, sustainability, and resilience challenges. To evaluate the sustainability and resilience advantages of the PI-enabled reconfigurable modular system (PI-M system), this paper studies a PI-enabled sustainable and resilient production-routing problem with modular capacity.Design/methodology/approachWe develop a multi-objective optimization model to assess the sustainability and resilience benefits of combining PI and modular capacity in a chemical industry case study. A hybrid solution approach, combining the augmented e-constraint method, construction heuristic, and hybrid adaptive large neighborhood search, is developed.FindingsThe experimental results reveal that the proposed solution approach is capable of obtaining better solutions than the Gurobi and the existing heuristic in a shorter running time. Moreover, compared with the traditional system, the PI only and traditional with modular capacity systems, PI-M system has significant advantages in both sustainability and resilience.Originality/valueTo the best of our knowledge, this study is the first to integrate the PI and modular capacity and investigate sustainability and resilience in the production-routing problem.

Coastal resilience and shoreline dynamics: assessing the impact of a hybrid beach restoration strategy in Puducherry, India

Puducherry, a Union Territory of India, has been strongly affected by severe erosion after the construction of the Puducherry port in 1989. To mitigate this cause, the National Institute of Ocean Technology, Chennai, and the Puducherry government implemented a beach restoration strategy involving a hybrid solution in 2017 for coastal protection/stabilization and the restoration of the lost beach. The strategy involved deploying a steel reef into the nearshore sea and implementing beach nourishment processes. To monitor the coastal morphological changes after implementing the coastal protection strategy, the Digital Shoreline Analysis System, was adopted to calculate the rate of shoreline change statistics for the years 2016 to 2022. It uses spatio-temporal shoreline positions from multi-temporal satellite imagery. The shorelines are extracted from the Sentinel-2A satellite images by a Normalized Differential Water Index based semi-automated model. Statistical parameters in DSAS analyze the shorelines to determine the shoreline changes in this area. The results reveal the remarkable resilience of a newly restored beach, where the linear regression rate statistics in Zone A show an average accretional rate of 2.92m/yr. Alternatively, Zone B exhibits an average erosion rate of -0.23m/yr, with intermittent sandy beaches experiencing maximum erosion rates of -1.63m/yr. The influence of longshore current direction and sediment transport on shoreline movement is evident in seasonal analysis, with shoreline development and recession primarily observed near shore protection structures. The study’s outcome provides valuable insights for coastal management, offering a reliable approach for shoreline monitoring post-implementation of mitigation projects.

MHD radiating flow in a hybrid solution of C2H6O2–H2O to disperse Ag–Al2O3 hybrid nanoparticles taking into account the effects of nanoparticle shapes

MHD radiating flow in a hybrid solution of C2H6O2–H2O to disperse Ag–Al2O3 hybrid nanoparticles taking into account the effects of nanoparticle shapes

The dynamics of some exact solutions to a [formula omitted]-dimensional sine-Gordon equation

In this paper, a (3+1)-dimensional sine-Gordon equation is systematically investigated. Firstly, the integrability of the equation is demonstrated by Painlevé analysis. Secondly, based on the Hirota bilinear method, the N-soliton solution of the (3+1)-dimensional sine-Gordon equation is derived. Then, by selecting and establishing conjugate relationships between parameters, the kink solutions, the breather solutions and their hybrid solutions were obtained. Finally, the lump solutions of equation are derived by selecting appropriate functions in the solution. In addition, the dynamic behavior of these solutions is systematically analyzed by their respective density profile plots and three-dimensional diagrams.

SoC-FPGA Based Concept of Hardware Aided Quantum Simulation

Contemporary industry and science expectations towards technological solutions set the bar high. Current approaches to increasing the computing power of standard systems are reaching the limits of physics known to humankind. Fast, programmable systems with relatively low power consumption are a different concept for performing complex calculations. Highly parallel processing opens up a number of possibilities in the context of accelerating calculations. Application of SoC (System On Chip) with FPGA (Field-Programmable Gate Array) enables to delegate of a part of computations to the gates matrix, thereby expediting processing by using parallelization of hardware operations. This paper presents the general concept of using SoC FPGA systems to support CPU (Central Processing Unit) in many modern tasks. While some tasks might be really hard to implement on an FPGA in a reasonable time, the SoC FPGA platform allows for easy low-level interconnections, and with such virtualized access to the hardware computing resources, it is seen as making FPGAs, or hardware in general, more accessible to engineers accustomed to high-level solutions. The concept presented in the article takes into account the limited resources of cheaper educational platforms, which, however, still provide an interesting and alternative hybrid solution to the problem of parallelization and acceleration of data processing. This allows to overcome encountered limitations and maintain the flexibility known from high-level solutions and high performance achieved with low-level programming, without the need for a high financial background.

Flexible allocation and optimal configuration of multi-level energy exploitation units for heterogeneous energy systems considering resource distribution

The energy systems are evolving into heterogeneous energy systems (HESs) with complicated integration of sources, networks, loads, and storage towards a decarbonized future of human beings. This paper develops the flexible allocation and optimal configuration of multi-level energy exploitation units (MEEUs) for the HES considering resource distribution including local energy conditions and actual coupled relationship of various energy networks. A bi-level optimal planning model of MEEUs for the HES considering initial investment cost, carbon emission cost, operation cost and line loss is developed to figure out the optimal location, structure, configuration and corresponding operation strategy. To address the non-convex and non-linear model, a novel hybrid solution method considering the mixing characteristics of mixed-integer second-order cone programming (MISOCP) model and quadratic non-convex model is proposed. The solution method adopts MISOCP model for figuring out the optimal location, structure and configuration of MEEUs and quadratic non-convex model for optimal operation strategy of MEEUs, which not only improves the computational efficiency but also ensures the solution accuracy. Finally, the related case studies are conducted to compare the proposed MEEU and distributed energy storage unit (DESU) in terms of energy consumption, renewable energy absorbency, carbon emission and line loss. The results verify the significant improvement of the comprehensive energy efficiency, the investment potentiality and the environmental benefits obtained by the proposed planning model.

ScribFormer: Transformer Makes CNN Work Better for Scribble-Based Medical Image Segmentation.

Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with the local receptive field, which makes it difficult to learn global shape information from the limited information provided by scribble annotations. To address this issue, this paper proposes a new CNN-Transformer hybrid solution for scribble-supervised medical image segmentation called ScribFormer. The proposed ScribFormer model has a triple-branch structure, i.e., the hybrid of a CNN branch, a Transformer branch, and an attention-guided class activation map (ACAM) branch. Specifically, the CNN branch collaborates with the Transformer branch to fuse the local features learned from CNN with the global representations obtained from Transformer, which can effectively overcome limitations of existing scribble-supervised segmentation methods. Furthermore, the ACAM branch assists in unifying the shallow convolution features and the deep convolution features to improve model's performance further. Extensive experiments on two public datasets and one private dataset show that our ScribFormer has superior performance over the state-of-the-art scribble-supervised segmentation methods, and achieves even better results than the fully-supervised segmentation methods. The code is released at https://github.com/HUANGLIZI/ScribFormer.

Better integrating battery and fuel cells in electric vehicles

AbstractThis paper presents an innovative approach to enhancing the range of battery electric vehicles (BEVs) through the integration of a hydrogen fuel cell range extender. By combining the high energy efficiency of BEVs with the rapid refueling capability and extended range of hydrogen fuel cells, this hybrid system addresses the limitations of current electric vehicles in scenarios demanding longer driving ranges or quicker refueling options. Our study encompasses both experimental and theoretical analyses, leading to the proposal of a BEV configuration that includes a smaller battery complemented by a fuel cell range extender. The conventional fuel cell electric vehicle (FCV) examined relies exclusively on hydrogen fuel and features a minimal battery without plug‐in functionality, resulting in suboptimal energy economy. In contrast, our proposed BEV with a fuel cell range extender employs a larger battery capacity of 12 to 16 kWh alongside a downsized fuel cell stack and reduced hydrogen tank size. This configuration significantly improves energy recovery during braking and extends electric operation, thereby doubling the vehicle's energy economy. The proposed system not only enhances energy efficiency but also reduces the weight and volume of the overall energy storage system. Preliminary estimates suggest that the miles‐per‐gallon equivalent (MPGe) of this hybrid solution could exceed 140 over the US EPA certification cycle, outperforming existing PHEVs, BEVs, and FCVs.

Information technology integration implementation in public sector organizations: Exploring challenges, opportunities, and future trends

This paper provides an overview of challenges, opportunities, and future trends in implementing IT integration within public sector organizations. Employing an exploratory research approach, the study conducts a case study and reviews pertinent literature (2019–2023) on IT integration implementation. Following the PRISMA flow chart, electronic searches in various databases used keywords related to IT integration. The study identifies inadequate technical facilities, insufficient technology, infrastructure, and unsupportive policies as primary barriers. Conversely, the digital era prompts opportunities, compelling organizations to adopt innovative technologies for enhanced productivity and quality service delivery. The paper's uniqueness lies in developing a framework assessing the success of technology integration, allowing for the incorporation of remote and hybrid work models. Future trends in IT integration implementation focus on remote and hybrid work solutions. Contributing to existing literature, the framework emphasizes that failure to extend IT integration implementation to include remote and hybrid work solutions may lead to additional constraints, creating gaps in organizational operation. The review analyzes research gaps and suggests future directions, ensuring effective IT integration implementation, especially in developing countries with significant gaps. This review is particularly relevant given the global surge in technology use over the past two years. Fueled by rapid technological advancements and the constraints of COVID-19, a systematic literature review (SLR) is imperative to demonstrate how IT integration implementation helps public sector organizations improve employee performance, financial outcomes, productivity, and service delivery.

Dual-drive energy conversion plasmonic Ag@MXene thermal management textiles inspired by bearing structure

Multifunctional wearable textiles can simulate human perception and convert it into visual data, which has advanced application prospects. As an important branch, thermal management wearable textiles have been widely concerned in the aspects of thermal insulation, flame retardant, photothermal anti-icing, electrothermal deicing and even water evaporation. Here, inspired by the bearing structure, we simply soaked the PET textile in Ag@MXene hybrid solution several times to form a Ag@MXene conductive network with Ag NPs as the connection point on the textile fiber, and finally carry out hydrophobic modification. Based on plasma effect, the synergistic action of Ag NPs and MXene enhances the photothermal response of the material. In addition, the addition of Ag NPs effectively reduces the stacking between MXene layers and forms a Ag@MXene conductive network with Ag NPs as the connection point on the textile fibers. The stable temperature range of PDMS/Ag@MXene PET textile is 70–80 °C under one solar illumination intensity, and the stable temperature of PDMS/Ag@MXene PET textile can reach 117 °C at a constant voltage of 3 V. Based on the excellent thermal effect, this textile achieves photothermal anti-icing, electric thermal de-icing, keeping warm and removing sweat. The textile has a water evaporation efficiency of about 0.58 g h−1, which can achieve excellent anti-sweat function. Finally, the textile also achieved rapid flame retardant within 7 s. PDMS/Ag@MXene PET textile processes excellent photothermal and electrothermal conversion ability, acid/water stability and flame retardant ability, and has promising application prospects in thermal management textiles such as deicing and anti-icing, fire prevention, warmth and water evaporation.