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This paper proposes an asymmetric hybrid tri-stable piezoelectric energy harvester for rotational motion (RHTPEH). The device features an asymmetric tri-stable piezoelectric cantilever beam positioned at the edge of a rotating disk. This beam is uniquely configured with an asymmetric arrangement of magnets. Additionally, an elastic amplifier composed of a vertical and a rotating spring connects the beam's fixed end and the disk. This setup enhances both the rotational amplitude and vertical displacement of the beam during motion. A comprehensive dynamical model of the RHTPEH was developed using Lagrange's equations. This model facilitated an in-depth analysis of the system's behavior under various conditions, focusing on the influence of key parameters such as the asymmetry in the potential well, the stiffness ratio of the amplifier springs, the radius of the disk, and the disk's rotational speed on the nonlinear dynamic response of the system. The results show that the asymmetric hybrid tri-stable piezoelectric energy harvester makes it easier to harvest the vibration energy in rotational motion and has excellent power output performance compared with the symmetric tri-stable piezoelectric energy harvester. The output power magnitude of the system at higher rotational speeds increases as the radius of rotation expands, but when the rotational speed is low, the steady-state output power magnitude of the system is not sensitive to changes in the radius of rotation. Theoretical analysis and numerical simulations validate the effectiveness of the proposed asymmetric RHTPEH for energy harvesting in low-frequency rotating environments. [ABSTRACT FROM AUTHOR]

To harness the full potential of the exhaust heat produced by an alkaline fuel cell (AFC), a novel coupling system that combines an AFC with an inhomogeneous thermoelectric generator (ITEG) is proposed. Detailed models of both the AFC and ITEG are developed, accounting for various irreversible losses. Following model validations, mathematical expressions for the power output density (POD) and energy efficiency (EE) of the hybrid system are derived. Though performance comparisons, the hybrid system's effectiveness and competitiveness are demonstrated. Our calculation results reveal that the hybrid system achieves a 31.19% increase in its maximum POD and 54.61% improvement in its corresponding EE compared to that of the standalone AFC. Furthermore, numerous parametric studies are conducted. Some findings indicate that the POD of the hybrid system can be improved by elevating the operating temperature of the AFC and the environmental temperature, and that it can be optimized using the geometric characteristics of an ITEG. However, the EE of the hybrid system gains improvement via increasing the operating temperature of the AFC or decreasing both the environmental temperature and geometric characteristics of the ITEG. Additionally, the coefficient of the spatial inhomogeneity of the ITEG determines the optimal operating current density of the AFC. These insights offer valuable guidance for the integration and operation of practical hybrid systems. [ABSTRACT FROM AUTHOR]

Experimental results obtained using a photovoltaic thermal hybrid solar system are presented and discussed. This hybrid combination is an emerging technology that combines photovoltaic panels and solar thermal collectors in one bi-functional component providing both electrical and thermal energy. The main objective of this coupling is to improve the efficiency of the photovoltaic panels by reducing their operating temperatures and recovering the thermal energy they dissipate, using heat transfer fluids (water in the present study). A theoretical energy and exergy analysis of photovoltaic thermal hybrid solar system is presented. Both electrical and thermal performances of the proposed photovoltaic thermal prototype system are evaluated and analyzed under local weather conditions of Essaouira, Morocco (latitude: 31.51, longitude: –9.76). A comparative study in terms of overall energy efficiency of photovoltaic thermal and conventional photovoltaic systems is conducted and discussed. The obtained experimental findings show that, unlike the conventional photovoltaic panel for which the overall efficiency does not exceed 8.22%, the hybrid system makes it possible to achieve a maximum overall efficiency of about 42.72%. The extracted energy’s quality and efficiency are evaluated through the exergy analysis of the proposed photovoltaic thermal system. The electrical and thermal exergy efficiencies recorded for the studied sytem are 9.78% and 3.07%, respectively. [ABSTRACT FROM AUTHOR]

The advancement of novel water treatment technologies requires the implementation of both accurate data measurement and recording processes. These procedures are essential for acquiring results and conducting thorough analyses to enhance operational efficiency. In addition, accurate sensor data facilitate precise control over chemical treatment dosages, ensuring optimal water quality and corrosion inhibition while minimizing chemical usage and associated costs. Under this framework, this paper describes the sensoring and monitoring solution for a hybrid system based on a cooling tower (CT) connected to mechanical vapor compression (MVC) equipment for desalination and brine concentration purposes. Sensors connected to the data commercial logger solution, Almemo 2890-9, are also discussed in detail such as temperature, relative humidity, pressure, flow rate, etc. The monitoring system allows remote control of the MVC based on a server, GateManager, and TightVNC. In this way, the proposed solution provides remote access to the hybrid system, being able to visualize gathered data in real time. A case study located in Cartagena (Spain) is used to assess the proposed solution. Collected data from temperature transmitters, pneumatic valves, level sensors, and power demand are included and discussed in the paper. These variables allow a subsequent forecasting process to estimate brine concentration values. Different sample times are included in this paper to minimize the collected data from the hybrid system within suitable operation conditions. This solution is suitable to be applied to other desalination processes and locations. [ABSTRACT FROM AUTHOR]

The remaining useful life (RUL) prediction of RF circuits is an important tool for circuit reliability. Data-driven-based approaches do not require knowledge of the failure mechanism and reduce the dependence on knowledge of complex circuits, and thus can effectively realize RUL prediction. This manuscript proposes a novel RUL prediction method based on a gated recurrent unit–convolutional neural network (GRU-CNN). Firstly, the data are normalized to improve the efficiency of the algorithm; secondly, the degradation of the circuit is evaluated using the hybrid health score based on the Euclidean and Manhattan distances; then, the life cycle of the RF circuits is segmented based on the hybrid health scores; and finally, an RUL prediction is carried out for the circuits at each stage using the GRU-CNN model. The results show that the RMSE of the GRU-CNN model in the normal operation stage is only 3/5 of that of the GRU and CNN models, while the prediction uncertainty is minimized. [ABSTRACT FROM AUTHOR]

Concentrated solar towers are commonly designed as high-rise hybrid structures, which exhibit properties of non-uniform mass and rigidity along the height of the tower, and consequently are vulnerable to strong seismic ground motions. This study presents a comprehensive analysis of the seismic performance of a hybrid solar tower, which is one of the tallest hybrid solar towers in the world. The hybrid solar tower includes a reinforced concrete tube at the bottom and a steel-truss tube at the top and is subjected to near-fault pulse-like ground motions. A simulation technique that utilizes the stochastic point-source model and a velocity pulse model was introduced to generate stochastic pulse-like ground motions. The stochastic response of the hybrid solar tower to near-fault pulse-like ground motions was computed to estimate the tower's reliability. To enhance the efficiency of reliability estimation, an algorithm combining the Kriging surrogate and subset simulation (K-SS) was presented. The aggregate response of the tower was found to be significantly more damaging over the border of the reinforced concrete tube and the steel-truss tube than below the border. The study found that the hybrid solar tower has a reliability of 90.53% when subjected to stochastic near-fault pulse-like ground motions with a peak ground acceleration of 0.62 g. The findings of this study contribute to the understanding of the seismic performance of high-rise hybrid solar towers under near-fault pulse-like ground motions. [ABSTRACT FROM AUTHOR]

This paper describes the implementation of a control algorithm for MIMO system, which is mostly used in industries and it is a highly nonlinear system, the main aim is to control the level of a liquid in a tank. A challenge in process industries is naturally multi-input and multi-output systems, compared to the single input and single output systems. The process parameters change with the operating point and it is a difficult task in different tanks to control the level of liquid for (ITTHS). The output of the level process is nonlinear, it should be linearized by the Taylor Series method, which converts nonlinear equations to linear equations for MIMO system. The transfer function for ITTHS is derived and tuning parameters in the case of PI, PID controller. The objective is to analyse the various tuning controllers by simulation using the MATLAB SIMULINK platform. [ABSTRACT FROM AUTHOR]

The interpretation of breast magnetic resonance imaging (MRI) in the healthcare field depends on the good knowledge and experience of radiologists. Recent developments in artificial intelligence (AI) have shown advances in the field of radiology. However, the desired levels have not been reached in the field of radiology yet. In this study, a novel model structure is proposed to characterize the diagnostic performance of AI technology for individual breast dynamic contrast material-enhanced (DCE) MRI sequences. In the proposed model structure, Inception-v3, EfficientNet-B3, and DenseNet-201 models were used as hybrids together with the Yolo-v3 algorithm to detect breast and cancer regions. In the proposed model, DCE-MRI sequences (T2, ADC, Diffusion, Non-Contrast Fat Non-Suppressed T1, Non-Contrast Fat Suppressed T1, Contrast Fat Suppressed T1, and Subtraction T1) were evaluated separately and validation was made, thus providing a unique perspective. According to the validation results, the model structure with the best performance was determined as Yolo-v3 + DenseNet-201. With this model structure, 92.41% accuracy, 0.5936 loss, 92.44% sensitivity, and 92.44% specificity rates were obtained. In addition, it was determined that the results obtained without using contrast material in the best model were 91.53% accuracy, 0.9646 loss, 92.19% sensitivity, and 92.19% specificity. Therefore, it is predicted that the need for contrast material use can be reduced with the help of this model structure. [ABSTRACT FROM AUTHOR]

This article examines the claims that the unique public-private television system of the 1980s provided space for the development of a national sense of community-based on common narratives and decentralization. The sources for the analysis included a revision of its contemporary discussion in printed media coupled with an analysis of TV shows currently available on streaming services and interviews with relevant figures of the time. The television content shot on location was praised for representing the nation, while simultaneously giving rise to debates about decentralization, which was finally addressed by the creation of regional broadcasters. The hybrid system fostered diversity, production quality, and a national representation that was strongly contested from the regions. At the same time, the system unintendedly hampered the creation of an audiovisual archive, and complaints about its tender systems resonate with the plight of contemporary public service broadcasting in Colombia. [ABSTRACT FROM AUTHOR]

Virtual Machine Placement (VMP) plays a significant role in improving efficiency of Cloud Data Center (CDC). With the dramatic increase in the use of cloud computing, it seems necessary to apply effective algorithms to reduce the power consumption of CDC. VMP is known as a NP-Hard problem that cannot be solved by deterministic algorithms in polynomial time. In this paper, an algorithm named Combinated Random Best First Fit (CRBFF) is proposed with the aim of increasing the Quality of Service (QoS), in which Virtual Machines (VMs) are optimally placed on heterogeneous Physical Machines (PMs). The effectiveness of CRBFF is evaluated by different metrics on Google Compute Engine (GCE), Amazon Web Service Elastic Compute Cloud (AWS EC2) and Microsoft Azure scenarios and the results show that CRBFF performs better than other common algorithms. [ABSTRACT FROM AUTHOR]

In this paper, fixed-time stability (FxTS) of time-varying (TV) hybrid systems with time-delay (TD) is investigated. Starting with TV nonlinear systems with TD, some sufficient conditions are given to verify the FxTS of systems by using TV Lyapunov–Krasovskii functional and integral technique. Then, the obtained results are extended to the case of hybrid systems, several FxTS conditions are provided by using the multiple TV Lyapunov–Krasovskii functional and the function-dependent minimum dwell time technique. Comparing with the existing results, the obtained results can provide the more accurate estimation of the convergence time of systems, and can be applied to a wider class of systems. Finally, two numerical examples are given to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

In the medical field, refrigeration systems are used to store and transport vaccines, blood, and other medical supplies that require specific temperature ranges to remain effective. As technology continues to advance, the demand for more efficient and sustainable refrigeration systems is also increasing. The freezer compartment is typically designed to maintain a temperature of −18°C to −23°C for storing frozen items. Consequently, this work aims to develop a hybrid refrigeration system that combines a thermoelectric cooler system (TEC) and a vapor compression refrigeration cycle (VCC) system to achieve lower temperatures than conventional refrigerators. Also, the performance of the proposed hybrid refrigeration system is experimentally assessed with various operating conditions, including varying the voltage delivered to the system. The experimental results exhibited that the temperature inside the freezer room reached −33°C, while the cold side temperature is −47°C. Also, the maximum coefficient of performance of the VCC system, TEC, and hybrid system is 2.07, 1.06, and 0.37, respectively, at a DC voltage applied of 6 V. Moreover, the results revealed that the hybrid system combining a TEC and a VCC system can be a valuable technology for specific applications with low temperatures and limited capacity requirements. [ABSTRACT FROM AUTHOR]

A hybrid genetic algorithm (GA)–Kohonen map, with its three variants, is explored for the first time for the decision‐making system in a porous ceramic matrix (PCM)‐based burner through determination of the regime of operation. Four different attributes of PCMs such as convective coupling (P2), extinction coefficient (β), downstream porosity (ϕ2), and scattering albedo (ω) are selected for determining the regime of operation of a PCM‐based burner. Changes in any of these attributes of a PCM lead to significant changes in the temperature profiles of the gas and solid phases. Temperature profiles of the gas and solid phases are computed by developing a numerical model. Various samples corresponding to different regimes are generated and used in a hybrid GA–Kohonen map. The best architectural details such as the neuron number and training epochs are obtained from GA as output. The best Kohonen map is trained with the input data, and regimes of operation for new temperature profiles are predicted. A supervised Kohonen map is able to provide the highest average class prediction of more than 40%. All the variants are assessed under two different types of neuron grids: hexagonal and rectangular. Comparative assessments of the three different variants of Kohonen maps, in terms of CPU time and average class prediction, are carried out. [ABSTRACT FROM AUTHOR]

Energy generation and pollutant emissions are two faces of the same coin, as the current energy sources i.e., fossil energy, are still considered to be major sources of greenhouse gases (GHG). Therefore, shifting to cleaner energy sources imposes itself as an inevitable solution to reduce this environmental cost. In this paper, a hybrid system based on the multi-agent approach and Long Short-Term Memory (LSTM) neural networks to forecast the energy production and its carbon dioxide (CO2) emissions and simulate the potential emission reduction in case of switching to renewable energy sources is presented. The proposed system's architecture consists of combining LSTM models with the agent-based technology, where multiple LSTM forecasting models were trained to forecast the production of each type of the studied energies and then estimate the equivalent emitted CO2 and calculate the influence of the renewable energy inputs on the carbon emissions and the fossil fuels consumption. The simulation process consists of two phases: firstly, each forecasting agent uses a specific LSTM model to forecast short-term energy production. Secondly, these agents send the forecasted values to the coordination agent who is responsible for calculating the total CO2 emissions and the benefits of the renewable energy inputs. [ABSTRACT FROM AUTHOR]

Distributed micro‐energy harvesting devices offer the flexibility, sustainability, and multi‐scenario applicability that will be critical to wearable electronic products in the Internet of Things. The radiofrequency and triboelectric (RF‐TE) hybrid energy harvester (HEH) concept and prototype is presented for the first time, to simultaneously capture the energy from ambient electromagnetic waves and biological motions. The proposed hybrid energy harvesting system consists of a wearable rectenna, a triboelectric nanogenerator (TENG), and a power management circuit (PMC). Among them, the all‐fabric rectenna exhibits good impedance matching characteristics in the ISM frequency. The flexible TENG unit can generate a maximum power density of 0.024 µW cm−2. The designed multifunctional fabric‐based PMC can considerably enhance the controllability of harvested hybrid energy. Additionally, a normalizable fabric circuit board quasi surface mount technology (FCB‐SMT) is proposed to integrate all modules on the same fabric substrate in one step, making the entire system superior mechanical robustness. The proposed wearable fabric‐based RF‐TE hybrid energy harvester is capable of successfully driving consumer electronics (such as sensors, watches, etc.). It provides a new energy solution strategy for self‐powered wearable electronic devices and is anticipated to encourage the efficient utilization of renewable energy. [ABSTRACT FROM AUTHOR]

SUMMARY: F1 hybrids derived from a cross between two inbred parental lines often display widespread changes in DNA methylation patterns relative to their parents. To which extent these changes drive non‐additive gene expression levels and phenotypic heterosis in F1 individuals is not fully resolved. Current mechanistic models propose that DNA methylation remodeling in hybrids is the result of epigenetic interactions between parental alleles via small interfering RNA (sRNA). These models have strong empirical support but are limited to genomic regions where the two parental lines differ in DNA methylation status. However, most remodeling events occur in parental regions with similar methylation patterns, and seem to be strongly conditioned by distally acting factors, even in isogenic hybrid systems. The molecular basis of these distal interactions is currently unknown, and will likely emerge as an active area of research in the future. Despite these gaps in our molecular understanding, parental DNA methylation states are statistically associated with heterosis, independent of genetic information, and may serve as biomarkers in crop breeding. Significance Statement: The genomes of F1 hybrids display substantial non‐additive DNA methylation changes relative to their parental lines. Here we review our current understanding of the molecular mechanisms underlying these events and discuss the extent to which they trigger transcriptional changes in phenotypic heterosis. [ABSTRACT FROM AUTHOR]

The global iron ore price is influenced by numerous factors, thus showcasing a complex interplay among them. The collective expectations of market participants over time shape the variations and trends within the iron ore price time series. Consequently, devising a robust forecasting model for the volatility of iron ore prices, as well as for other assets connected to this commodity, is critical for guiding future investments and decision-making processes in mining companies. Within this framework, the integration of artificial intelligence techniques, encompassing both technical and fundamental analyses, is aimed at developing a comprehensive, autonomous hybrid system for decision support, which is specialized in iron ore asset management. This approach not only enhances the accuracy of predictions but also supports strategic planning in the mining sector. [ABSTRACT FROM AUTHOR]

Unveiling the underlying governing equations of nonlinear dynamic systems remains a significant challenge. Insufficient prior knowledge hinders the determination of an accurate candidate library, while noisy observations lead to imprecise evaluations, which in turn result in redundant function terms or erroneous equations. This study proposes a framework to robustly uncover open-form partial differential equations (PDEs) from limited and noisy data. The framework operates through two alternating update processes: discovering and embedding. The discovering phase employs symbolic representation and a novel reinforcement learning (RL)-guided hybrid PDE generator to efficiently produce diverse open-form PDEs with tree structures. A neural network-based predictive model fits the system response and serves as the reward evaluator for the generated PDEs. PDEs with higher rewards are utilized to iteratively optimize the generator via the RL strategy and the best-performing PDE is selected by a parameter-free stability metric. The embedding phase integrates the initially identified PDE from the discovering process as a physical constraint into the predictive model for robust training. The traversal of PDE trees automates the construction of the computational graph and the embedding process without human intervention. Numerical experiments demonstrate our framework's capability to uncover governing equations from nonlinear dynamic systems with limited and highly noisy data and outperform other physics-informed neural network-based discovery methods. This work opens new potential for exploring real-world systems with limited understanding. [ABSTRACT FROM AUTHOR]

This study addresses the pressing issue of quality electricity access in remote regions, with a specific focus on Tumbatu Island in Tanzania. Most studies on quality improvement concentrate on low‐voltage distribution lines and leave high‐voltage (HV) transmission lines behind. It is essential to address quality issues in HV lines due to their critical role in electricity transmission and distribution infrastructure. The objective of the study is to improve the voltage profile on the island's HV transmission line by identifying the optimal hybrid energy system comprising solar PV, wind turbine, and battery technologies. The study begins by presenting the total power demand and consumption on Tumbatu Island, which are important factors in designing an efficient energy system. The findings reveal a power demand of 7173 kW and a consumption of 28540 kWh/day, with an average scaled value of 1507.9 and 6000 kWh/day. To achieve the desired voltage profile improvement, the research incorporates HOMER Pro software for simulating and analyzing various hybrid system configurations. Essential input parameters, such as costs, resources, technology components, and load, are considered in the simulation process. The software generates a ranked list of options based on the system's net present cost (NPC). The simulation results demonstrate that the integration of solar PV, wind turbine, and HV lines provides a substantial improvement in the voltage profile, increasing it from 29.6 to 31.23 kV during peak demand periods. This solution proves to be the most economically viable, with the lowest NPC of $4,003,851 and a relatively short payback period of 3.79 years. In addition, a sensitivity analysis is performed to identify the most influential parameter in the system's performance. Wind speed is found to have the greatest impact, emphasizing its significance in the design and operation of the hybrid energy system. The implementation of this optimal hybrid renewable energy system on Tumbatu Island will not only improve the voltage profile and meet the island's energy needs but also shall contribute to global efforts in reducing pollution and the cost of electricity to the Tumbatu Island population. Moreover, it addresses the current and future demands for clean energy, underlining its importance in achieving sustainable and accessible electricity in sub‐Saharan Africa and beyond. [ABSTRACT FROM AUTHOR]

In this paper, we investigate various stabilisation problems of a hybrid system of elasticity, consisting of a thin tape, which moves axially between two sets of rollers. We present a control solution, which works simultaneously, for three variants of the tape model. In particular, we design boundary feedback control laws via Lyapunov's second method. The resulting closed-loop system for the general case is then analysed, where we prove the existence and uniqueness of solution using the semigroup theory of linear operators; furthermore, we prove the exponential decay of the solution via a frequency domain theorem. The stabilisation of the two other special cases is derived implicitly from the general case proofs presented in the paper. Finally, the paper is concluded by presenting computer simulations to support the theoretical results. [ABSTRACT FROM AUTHOR]

This paper addresses the exponential stability problem of singularly perturbed hybrid systems with multi-rate sampling. Firstly, a hybrid model is established to describe a class of nonlinear singularly perturbed systems by designing a data-driven mechanism and multi-rate sampling controller. Secondly, a novel error function and several inequalities are proposed to obtain the properties of the error subsystems. Thirdly, we estimate the bounds of fast and slow sampling intervals, and analyze the effect of the perturbation parameter and fast-slow sampling ratio on the sampling intervals. Finally, a DC motor model is illustrated to demonstrate the effectiveness of the proposed results. • A hybrid model is established to describe a class of singularly perturbed systems with multi-rate sampling, continuous dynamics and discrete dynamics. • The relationship is established among the sampling ratio, the singular perturbation parameter and the fast sampling interval. • Some sufficient conditions are presented to analyze the exponential stability of the established model. [ABSTRACT FROM AUTHOR]

To achieve simple and reliable conversion from constant current (CC) charging mode to constant voltage (CV) charging mode in wireless power transfer systems, this paper proposes a hybrid topology equipped with a reconfigurable rectifier. An AC switch is adapted to simultaneously realize the change from half-bridge rectification to full-bridge rectification and achieve the shift from a topology with capacitors in the series compensated primary and secondary sides to a topology with capacitors in the series compensated primary side and the inductor-capacitor-inductor (LCL) compensated secondary side. Notably, communication between the transmitter and receiver sides is not necessary in the proposed method. Furthermore, the zero phase angle characteristic is successfully maintained in both charging modes. The experimental results obtained using the 48 V/0.7 A experimental prototype, which was built to validate the relevant theoretical analysis, show that output current/voltage can be achieved in CC/CV charging mode independent of load resistance. Notably, the maximum power transfer efficiency of the system during the charging process reached 95.33%. [ABSTRACT FROM AUTHOR]

Active magnetic bearings feature advantages of frictionlessness, low loss, and high reliability, making them extensively utilized in fields such as flywheel energy storage, aerospace, and beyond. However, conventional modulation strategies applied to digital control systems suffer from control delays, reducing current control precision and resulting in increased current ripple. To address the aforementioned issues, firstly, the operating principle of the active magnetic bearing drive system is analyzed. Based on hybrid systems theory, a mix logical dynamic model of the drive system is established by introducing auxiliary logical variables and auxiliary continuous variables to achieve three-level modulation. Secondly, integrating model predictive control theory, the established model is utilized as a predictive model to forecast and compensate for control delays in controlling current. Finally, a cost function is established based on the error between predicted current and reference current, and optimal control signals are generated to achieve precise control of the active magnetic bearings. The simulation results demonstrate that under light load conditions, the modulation strategy proposed in this paper reduces current ripple by 49.94% compared to traditional modulation strategies. Under moderate load conditions, the proposed modulation strategy reduces current ripple by 49.96%, while under heavy load conditions, it reduces current ripple by 49.99%. This validates the effectiveness of the proposed modulation strategy in compensating for control delays while retaining the three-level modulation scheme. [ABSTRACT FROM AUTHOR]

Solar panels' efficiency is highly affected by high‐operating temperatures, especially in semi‐arid and arid regions. This outdoor experimental study aimed to enhance the energy performance of the photovoltaic module by integrating two fans at the outlet of the thermal/photovoltaic hybrid system to ensure forced ventilation. The work novelty depending on achieving low energy consumption by DC fans, so that there is a proportional relationship between the intensity of solar radiation and the energy produced and consumed. The influence of the reduced temperature, operating temperature, and solar radiation intensity on the energy performance of the photovoltaic/thermal hybrid system was analyzed experimentally. The obtained results showed an improvement in electrical and overall efficiency of the new hybrid system by about 4% and 60%, respectively, compared to the conventional photovoltaic module. On the contrary, a decrease in the temperature of the PV module installed in the hybrid system was measured by about 9°C, compared to the conventional photovoltaic module. In addition to the effectiveness of the new technology air cooling proposed at the lowest consumption cost, the thermal energy generated from the proposed system can be invested in solar drying and building applications. [ABSTRACT FROM AUTHOR]

The space industry is known as an economic driver for many world economies. In Iran, the acquisition of satellite technology knowledge is one of the achievements of the country's scientific and technological indicators in recent years, but the position and importance of optimal investment in this industry in Iran have been ignored. The optimal technology portfolio is one of the tools that can cover this gap and lead to better decision-making by policymakers. In this paper, the optimum technology portfolio determination regarding its goals, attributes and challenges is addressed for Iran's space industry with a hybrid quantitative–qualitative method in two short and medium-term periods. We formulate a technology portfolio selection model with these multi-objective functions: maximization of benefits in using different technologies comprising of both short and medium-term portfolios, maximizing the total summation of all Technology Readiness Levels (TRLs) of technologies, maximizing the acquisition speed for the technologies, and minimizing the acquisition risk of technologies in each portfolio. In the proposed model, the usability, acquisition cost, and complexity of each technology are considered meticulously. Also, the goal programming method is used to integrate the objective functions. Another novelty of this paper is the formulation of two portfolios with two different periods in which their corresponding inputs and outputs affect the other. This research can significantly help in directing the country's investment in the space industry, spatial ecosystem orientation, facilitating the creation of space-based businesses, improving economic growth, and also providing guidelines to improve the related policies in this area. In addition, this research can be an inspiration for other developing countries in the space industry. [ABSTRACT FROM AUTHOR]

The development of single‐platform qubits, predominant for most of the last few decades, has driven the progress of quantum information technologies but also highlighted the limitations of various platforms. Some inherent issues, such as charge/spin noise in materials hinder certain platforms, while increased decoherence upon attempts to scale up severely impacts qubit quality and coupling on others. In addition, a universal solution for coherent information transfer between quantum systems remains lacking. By combining one or more qubit platforms, one could potentially create new hybrid platforms that might alleviate significant issues that current single‐platform qubits suffer from, and in some cases, even facilitate the conversion of static to flying qubits on the same hybrid platform. While nascent, this is an area of rising importance that could shed new light on robust and scalable qubit development and provide new impetus for research directions. Here, the requirements for hybrid systems are defined with artificial atoms in the solid state, exemplified with systems that are proposed or attempted, and conclude with the outlook for such hybrid quantum systems. [ABSTRACT FROM AUTHOR]

Residual stress is one of the critical evaluation factors as well as machining accuracy and surface finish in cutting. From the perspective of the fastening strength of parts, residual stress in drilling has an influence on the product or part life. Especially in the aircraft manufacturing, the tensile residual stress is crucial as it can cause major accidents. However, few studies have focused on residual stress in drilling so far. Most of them investigated the characteristics of residual stress based on the experimental data. This paper discusses residual stress in drilling in terms of its mechanical effect. The residual stresses in the inner surfaces of holes were measured in the depth direction from the top of the plate. The change in the residual stress has good correlation with the chip flow direction and the load applied to the inner surface, which acts as a counter force to the cutting force near the outermost ends of the lips. The cutting force is determined using an analytical model based on the minimum cutting energy. The correlation between the residual stress and the direction of the load applied to the inner surface depends on the margin width and back taper on the peripheral sides of a drill. The effect of the margin contact on the residual stress is characterized by linear regression analysis. Finally, an analysis-neural network hybrid system was developed to estimate the residual stresses in drilling. In the system, the mechanical effects of the drilling process, which are the magnitude and direction of the load applied to the inner surface, are obtained through analytical simulation. Meanwhile, the margin effects are expressed as the coefficients in the linear functions, which are associated with the margin width and back taper angle by a neural network. Then, another neural network, working as a post process, estimates the residual stresses using the information of mechanical and margin effects. The developed system is validated by presenting a comparison between the estimated and the actual residual stresses. [ABSTRACT FROM AUTHOR]

This paper investigates the complex dynamical behavior of a discrete prey-predator system with a fear factor, a strong Allee effect, and prey refuge. The existence and stability of fixed points in the system are discussed. By applying the central manifold theorem and bifurcation theory, we have established the occurrence of various types of bifurcations, including flip bifurcation and Neimark-Sacker bifurcation. Furthermore, to address the observed chaotic behavior in the system, three controllers were designed by employing state feedback control, OGY feedback control, and hybrid control methods. These controllers serve to control chaos in the proposed system and identify specific conditions under which chaos or bifurcations can be stabilized. Finally, the theoretical analyses have been validated through numerical simulations. [ABSTRACT FROM AUTHOR]

Introduction: The study presents an integrated system comprising a central platform and four wave-energy converters, with a focus on investigating their coupled motions induced by ocean waves. The interaction between the buoys and the central platform is achieved through the implementation of spring components. The power take-off system is simulated by incorporating damping coefficients and stiffness into these spring components, enabling a detailed analysis of the energy conversion of such system. Methods: Numerical simulations based on the continuity equation and the Reynolds-Averaged Navier-Stokes (RANS) equations, coupled with the realizable k -- e turbulence model, are conducted. The two-phase flow model employs the Volume of Fluid (VOF) method to accurately capture free surface elevations. Additionally, frequency-domain predictions, based on the linearized velocity potential flow theory, are provided for a single central platform and buoy for comparative purposes. Results: Detailed results regarding the effects of wave frequency and the damping coefficient of the power take-off system are presented. Discussion: The results reveal that while both the platform's motion and the relative motions between buoys and the platform are suppressed, the absolute motion of buoys varies depending on their respective locations within the system and ocean waves. This variation is deeply influenced by the interaction between incident, reflected and diffracted waves within the system. [ABSTRACT FROM AUTHOR]

Due to the scarcity of freshwater resources in many arid regions of the world, as well as rapidly growing populations and industrialization, various desalination technologies have been developed and enhanced to improve the performance of saline water purification with high quality. Integrating solar energy technologies with desalination systems would alleviate the running out of fossil fuel sources, reduce costs, and improve energy efficiency. Solar‐powered desalination systems could be a viable and efficient method for treating highly saline water for human consumption. Obtaining reliable and accurate design parameters for such hybrid systems plays a significant role in determining the system performance of solar‐driven desalination systems. The present review provides a comprehensive review of various solar‐driven membrane‐based desalination systems to investigate the impact of design and operation parameters for solar and desalination units on the effectiveness of the hybrid solar/desalination system. Recent advancements in utilizing numerous solar energy sources for desalination are analyzed herein. The economic implications of various membrane desalination operations for different solar energy sources are also discussed. It was revealed that the solar system design parameters, desalination unit characteristics, feed water properties, and climate conditions all affect the functionality and productivity of the membrane‐based solar‐powered desalination system. The feed pressure, number and shape of membranes, and the integrated solar system, all have significant impacts on the performance of the hybrid system. This article provides a pathway for desalination researchers to select the optimal design and operation parameters for hybrid solar‐powered membrane‐based desalination systems. Notably, they are found more feasible and sustainable than traditional desalination processes. Several related conclusions and future perspectives are reported herein. This article is categorized under:Sustainable Energy > Solar Energy [ABSTRACT FROM AUTHOR]

The vulnerability of powerful power generation facilities and the transmission system to military, man-made, and natural impacts, and the extreme complexity of protecting these facilities from the mentioned impacts necessitate the search for new solutions to provide reliable power supply to consumers. Obvious direction in this aspect is the practical implementation of elements of a decentralized approach to ensuring the functioning of the Interconnected Power System (IPS) of Ukraine. The intensive development of renewable energy in Ukraine in recent years has been driven, among other things, by the sources of relatively low power (in particular, solar power plants (SPP) with an installed capacity of up to 100 kW), which created the preconditions for the practical implementation of the microgrid concept, which enables to provide long-term power supply of local consumers even in the event of disconnection of power grid from the ІPS, which supplies power to microgrid consumers under normal operating conditions. This article presents the results of modeling the functioning of a microgrid created on the base of a real electric grid of a settlement with the corresponding daily profiles of power consumption and generation by local sources. The modeling was carried out in the MATLAB software environment. Two model configurations were considered in the study: a hybrid microgrid with a SPP and a diesel generators and a hybrid microgrid with a SPP and energy storage unit. The objective of the study to achieve stable operation of the power grid in the conditions of loss of electrical connection with the external power system, providing priority power supply to critical infrastructure facilities and consumers of the 1-st category in terms of reliability is ensured. Two main scenarios of isolated microgrid operation were modeled: winter (including cloudy and sunny days) and summer periods of maximum consumption. The results of the study show the possibility of practical organization of microgrids based on existing distribution power grids with local energy sources using Distributed Energy Resource Management Systems (DERMS), which ensure high efficiency of the local energy infrastructure and sustainability of the created microgrid. [ABSTRACT FROM AUTHOR]

This research discusses incorporating a single magnesium porphyrin molecule into a semiconducting single‐walled carbon nanotube (SWCNT) for solar cell applications. Using density functional theory (DFT), the study examines the optical and electronic properties of the isolated magnesium porphyrin molecule and two configurations of the hybrid system. Results show structural stability due to charge transfer between the molecule and the nanotube. Different exchange‐correlation functionals (GGA and HSE06) yield varied bandgap results, affecting light absorption. Integration of the molecule into the SWCNT reduces the bandgap. Encapsulation of the molecule influences absorption and stability under irradiation. These encapsulated systems exhibit type II heterojunction characteristics, making them promising for organic solar cells based on SWCNTs, offering potential for highly efficient solar cells. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) offer many advantages over ground vehicles, including quadruped robots, based on high maneuverability when performing exploration in complex and unknown environments. However, due to their limited computational capability, UAVs require lightweight but accurate state estimation algorithms for reliable exploration. In this paper, we propose a segmented map‐based exploration system based on light detection and ranging (LiDAR)‐based state estimation for UAVs. The proposed system includes capabilities such as exploration, obstacle avoidance, and object detection with localization using three‐dimensional (3D) dense maps generated by tightly coupled LiDAR Inertial Odometry (LIO). Our proposed system is a hybrid system that can switch between guided and exploration modes, making it practical for search and rescue missions in disaster scenarios. The proposed LIO algorithm adapts to its surroundings, allowing for fast and accurate state estimation in complex environments. The proposed exploration algorithm is designed to cover specific regions in the 3D dense map generated by the proposed LIO, with the UAV determining if map points are included within the coverage area. We tested the proposed system in both simulation and real‐world environments and validated that the proposed system outperforms state‐of‐the‐art algorithms in various aspects such as localization accuracy and exploration efficiency in complex environments. [ABSTRACT FROM AUTHOR]

This paper, a hybrid method, is proposed for protecting the hybrid photovoltaic (PV) and wind turbine (WT) system. The proposed protecting method is the hybrid wrapper of both the multiple support vector machine (MSVM) and firebug swarm optimization (FSO), commonly named as MSVM-FSO method. The proposed technique is diagnosing the appropriate fault occurring in the hybrid system. The main purpose of the proposed system is to assure the system with lower complexity for the fault diagnosis and detection (FDD) for improving the power quality (PQ) of hybrid method. Here, the MSVM approach is used to detect the fault conditions of grid-tied system. To evaluate the events of voltages, fault and the currents of hybrid systems are analyzed at the feeder of buses. The FSO categorizes the types of fault, which is occurred in grid-connected system. By then, the proposed method's performance is done in the MATLAB software and it is contrasted with different existing methods. From this, the proposed method provides accuracy as 99.7% and efficiency as 98%, which is high compared to existing methods. [ABSTRACT FROM AUTHOR]

Modern cryptography is a key element of data security, ensuring the confidentiality and integrity of information. In an increasingly digital world, cryptography remains crucial for the protection of sensitive data. In this context, we propose a novel hybrid security system for encrypted color images using a DNA model, chaotic systems, and SHA256-MD5 hash functions as a basis. The proposed hybrid system includes DNA permutation and diffusion. In DNA permutation, we unpredictably rearrange the location of DNA image elements by using the logistic map of low computational complexity. In DNA diffusion, we diffuse the permuted image of DNA with the DNA image key generated by a 5D hyper-chaotic system, using a variety of algebraic operators such as the circular offset in both directions. Considering the experimental outcomes and security evaluation, we can infer that the proposed hybrid security system demonstrates a high level of security, resistance to existing attacks, and practical application suitability while maintaining speed. [ABSTRACT FROM AUTHOR]

This paper introduces details of a new hybrid beam system connected to a reinforced concrete (RC) column. The hybrid beam system is a wide-flange steel beam embedded in RC beams on both ends without any shear connectors. The wide-flange steel beam does not penetrate through the beam-column joint, which reduces the fabrication cost compared to the typical steel beam-RC column hybrid system. A total of 10 hybrid beam specimens were designed with a slab-web interface. Four specimens were used to examine the shear sliding capacity at the slab-web interface, and an equivalent coefficient of friction at the interface, together with a method to evaluate the shear sliding capacity, was proposed. The remaining six specimens were used to examine the flexural capacity and plastic deformation capacity of the hybrid beam, and shear-friction reinforcement details required for ductile flexural behavior were proposed. [ABSTRACT FROM AUTHOR]

Vertical isolation by dividing the building into two soft and stiff sub-systems benefits from the period shifts and the damping mechanism across the height. However, the displacement demand imposed on the soft sub-system is less applicable in congested urban areas. As a result, in this study, a hybrid system of vertical isolation system benefiting from a tuned soft subsystem divided into upper and lower portions is investigated. A parametric linear 3-Degree of Freedom (DoF) model of the system incorporating mass and frequency ratio of the sub-systems was introduced and analyzed by response spectrum in MATLAB. A closed-form solution for the system frequency and mode shapes was also established. Response spectrum analysis indicates increasing the Tuned Mass Damper (TMD)'s fundamental period to 2.5 times the soft sub-system's, reduces its displacement to more than 40 percent. The Multi Degree of Freedom (MDoF) model of the system is parametrically generated in MATLAB. Time history analysis of the building subjected to 40 records with 2 and 10 percent probabilities of exceedance in 50 years compared with conventional vertical isolation reveals the lower soft sub-system displacement can be reduced up to 45 percent by shifting drift to upper stories. The innovative tuned vertical isolation by demonstrating superior control performance as comprises lower floors' drift may be an applicable solution for adjacent high- and low-rise buildings. [ABSTRACT FROM AUTHOR]

Photocatalytic water treatment is an advanced and efficient technology for water purification. Among various photocatalysts, iron-based metal–organic frameworks (Fe-MOFs) are widely applied for mineralizing organic wastewater due to their excellent water stability and photocatalytic activity. However, their practical application is impeded by insufficient photocatalytic performance, irreversible collapse of the framework structure during repeated use, and difficulty in recovery. In this study, we fabricated a Graphene oxide (GO) structure-oriented NH2-MIL-88B(Fe)/graphene oxide/sodium alginate (NM88B/GO/SA) aerogel for the removal of dyes and antibiotics, using GO interface regulation and dual-network crosslinking methods. In this hybrid system, a NM88B/GO heterostructure was formed through the directional growth of NM88B on the surface of GO. The introduction of sodium alginate (SA) enhanced the robustness and stability of the matrix, and effectively avoided aerogel fragmentation. With 30 wt% catalyst loading, the composite aerogel exhibited excellent photocatalytic degradation performance towards high-concentration (50 ppm) tetracycline hydrochloride (TC-HCl), achieving over 99% removal rate in 150 min. It also effectively degraded methylene blue (MB) at 10–30 ppm with over 99% removal rate. Furthermore, the aerogel showed excellent shape recovery ability, stability, and reusability. After five repeated tests, it maintained over 95% degradation efficiency for both TC-HCl and MB. This advanced aerogel holds great promise as a highly efficient and reusable photocatalyst for removing antibiotics and dyes from wastewater. [ABSTRACT FROM AUTHOR]

Due to global climate change and energy market turmoil, the world is seriously pushing to switch to renewable and diversifying energy sources. The building sector consumes an amount of energy, accounting for approximately 40 % of global energy. Therefore, the concept of zero-energy buildings has become more realistic than before. This study reveals the latest developments in zero-energy buildings through a comprehensive literature review of the past ten years. Emphasis has been placed on buildings' heating, ventilation, and cooling systems, as they constitute the most important part of the energy demand. Also, the role of negative energy resulting from an improved building envelope through the design of a building compatible with the surrounding environment, thermal insulation materials, phase change materials, vegetation cover, etc. A review was also made of the most significant renewable energy technologies, which include solar energy installations, wind turbines, and geothermal heat exchangers. The study showed that three main axes must be achieved to reach an energy-free building: Reducing energy waste through the energy-conserving building envelope and improving HVAC systems. Raising the efficiency of the performance of renewable energy facilities by using hybrid systems with the ability and flexibility to respond to changing energy demand. These three axes are an integrated approach to achieving ZEBs; none can be neglected. This study provides important references for researchers, institutions, and decision-makers to unify efforts to achieve ZEBs. It also aims to attract attention and focus research by raising questions and identifying gaps that future research efforts can address.

The integration of renewable energy sources into the power grid is essential for sustainable development, yet it presents significant dependability challenges, particularly in terms of reliability, stability, and robustness due to the inherent variability of these sources. This research introduces a novel hybrid methodology that combines Monte Carlo simulation with Newton-Raphson power flow analysis to enhance the reliability assessment of grid-connected hybrid renewable energy systems. This innovative approach uniquely addresses the limitations of existing methodologies by merging the probabilistic handling of uncertainties with precise deterministic power flow analysis. Our hybrid method significantly reduces the Loss of Load Expectation (LOLE) to 5 h per year and the Loss of Load Energy Expectation (LOEE) to 200 MWh per year, outperforming traditional methods which typically report LOLEs of 2020 h/year and LOEEs of 10001000 MWh/year. Additionally, the hybrid method achieves a reduction in power losses to 1.2%, showcasing its superior efficiency compared to the 2.5% losses seen with standalone Monte Carlo methods. Real-time validation using the IEEE-30 bus model further confirms the practical applicability and robustness of our approach, making it a pivotal tool for enhancing grid stability and optimizing renewable energy integration. This research not only advances the methodology for reliability assessment but also sets a new standard for balancing accuracy and computational efficiency in energy system management. The implications of this work are far-reaching, offering significant contributions to both grid reliability and the sustainable management of renewable energy resources.

This work shows relevant interactions between cells and drug-delivery systems based on vesicles crucial for therapeutic activity. This interplay drives strategies for the design of new drug-carry. Among the described systems are found liposomes, extracellular vesicles, and hybrid systems. The text details their properties, advantages, and constraints, and eventually, a perspective about the future of these formulations is proposed. [ABSTRACT FROM AUTHOR]

The article presents the discussion on new hybrid system combining ceria nanoparticles and mesenchymal stem cell nanovesicles to effectively treat rheumatoid arthritis by reducing symptoms and promoting regulatory T cells in a collagen-induced arthritis model. Topics include the challenges of rheumatoid arthritis, the role of reactive oxygen species in disease progression; and the therapeutic potential of nanotechnology for immune regulation.

This letter, published in the Journal of Neurology, discusses a case report of a patient with deep brain stimulation (DBS) who experienced a relapse of dystonia despite normal impedance measurements. The patient had a complete unilateral extension fracture, which was not detected by impedance testing. The delay in diagnosing the fracture could have had serious consequences for the patient. The authors emphasize the importance of radiological examination in cases of sudden deterioration in DBS patients, as normal impedance measurements do not rule out hardware malfunction. They also highlight the potential risks of performing an MRI in patients with broken leads or cables. [Extracted from the article]

Coupling-induced transparency (CIT) and absorption (CIA) of transmission signals were experimentally observed in a single planar hybrid structure specially designed to consist of a yttrium iron garnet film and three concentric inverted-split-ring resonators (ISRRs). The observation of both CIT and CIA was ascribed to the cooperative effect of the interaction of magnons with three decoupled ISRRs' photon modes and the traveling waves along the microstripline. An analytical model developed based on the balance between the coherent and dissipative multiple-paths interactions precisely reproduced both CIT and CIA experimentally observed from a single hybrid system. This work, promisingly, can provide guidance for the design of efficient, flexible, and well-controllable magnon–photon hybrid devices that are highly in demand for applications to quantum technologies currently under development. [ABSTRACT FROM AUTHOR]