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In a biological signal analysis system, signals of the same type may exhibit significant variations in their feature waveforms. Biological signals are typically weak, which increases the complexity of their analysis. Furthermore, clinical biomedical signals are susceptible to various interferences from the human body itself, including muscle movements, respiration, and heartbeat. These interference factors further escalate the complexity and difficulty of signal analysis. Therefore, precise and targeted preprocessing is often required before analyzing these clinical biomedical signals to enhance the accuracy and reliability of subsequent feature extraction and classification. Here, we have established an effective and practical algorithm model that integrates preprocessing with the initial localization of target feature waveforms, achieving the following four objectives: 1. Determining the periodic positions of target feature waveforms. 2. Preserving the original amplitude and shape of target feature waveforms while eliminating negative interference. 3. Reducing or eliminating interference from other feature waveforms in the input signal. 4. Decreasing noise in the input signal, such as baseline drift, powerline interference, and muscle artifacts commonly found in biological signals. We have validated the algorithm on clinical electrocardiogram (ECG) data and the authoritative MIT-BIH open-source ECG database demonstrating its effectiveness and reliability. [ABSTRACT FROM AUTHOR]

The electricity consumption behavior of the inhabitants is a major contributor to the uncertainty of the residential load system. Human-caused uncertainty may have a distributional component, but it is not well understood, which limits further understanding the stochastic component of load forecasting. This study proposes a short-term load-interval forecasting method considering the stochastic features caused by users' electricity consumption behavior. The proposed method is composed of two parts: load-point forecasting using singular spectrum analysis and long short-term memory (SSA-LSTM), and load boundaries forecasting using statistical analysis. Firstly, the load sequence is decomposed and recombined using SSA to obtain regular and stochastic subsequences. Then, the load-point forecasting LSTM network model is trained from the regular subsequence. Subsequently, the load boundaries related to load consumption consistency are forecasted by statistical analysis. Finally, the forecasting results are combined to obtain the load-interval forecasting result. The case study reveals that compared with other common methods, the proposed method can forecast the load interval more accurately and stably based on the load time series. By using the proposed method, the evaluation index coverage rates (CRs) are (17.50%, 1.95%, 1.05%, 0.97%, 7.80%, 4.55%, 9.52%, 1.11%), (17.95%, 3.02%, 1.49%, 5.49%, 5.03%, 1.66%, 1.49%), (19.79%, 2.79%, 1.43%, 1.18%, 3.37%, 1.42%) higher than the compared methods, and the interval average convergences (IACs) are (−18.19%, −8.15%, 3.97%), (36.97%, 21.92%, 22.59%), (12.31%, 21.59%, 7.22%) compared to the existing methods in three different counties, respectively, which shows that the proposed method has better overall performance and applicability through our discussion. [ABSTRACT FROM AUTHOR]

In this study, the notch effect of different types of 304 stainless steel rod notch is studied because of the problem of difficulty in measuring the notch root strain of 304 rod stainless steel, and the parameters of the annular notch root are analyzed. The notch angle, notch depth, and notch root radius are the main parameters of the stress field affecting the annular notch, and the mathematical expression of the strain rate concentration factor is derived. In order to verify the accuracy of the theory, the mechanical model of 304 stainless steel bar is established by finite element and numerical simulation calculation. The results show that the theoretical and finite elements have a high degree of agreement. When the notch angle increases, both theoretical and finite elements show a downward trend. When the notch depth of 304 stainless steel bar increases, both theoretical and numerical simulations show an increasing trend. The notch root radius of 304 stainless steel bar increases with decreasing numerical simulation. [ABSTRACT FROM AUTHOR]

The regular performance deterioration of P-type crystalline silicon solar modules and module strings caused by potential-induced degradation in a photovoltaic power plant was found in the field. The PID-affected solar modules dismounted from the photovoltaic power plant were further investigated systematically in the laboratory. For the first time, we found that the neutral point of voltage in a module string moved forward to the positive pole for a PID-affected module string as time goes on. Even if low positive voltage is applied to a PID-prone module, it could cause PID. The thermographic and electroluminescence (EL) images of a PID-affected module string also exhibit a regular degradation pattern. This is in good agreement with the measured power loss of the dismounted solar modules under standard test conditions. The results obtained in this paper show that the maximum power degradation rate of solar modules was as high as 53.26% after only one year of operation because of PID in the field. Due to the vast amount of solar modules and incomplete recovery, this is a terrible catastrophe for the owner of a power plant and module producer. [ABSTRACT FROM AUTHOR]

The purpose of this study is to find out the effects of light-emitting diode (LED) lighting on elderly people's color discrimination and preference, to improve the lighting environment for elderly people. In this study, experiments were conducted under LED lighting with two different spectra (with color-correlated temperature [CCT] of 2800K and 6000K), and three different illuminance levels (30lx; 100lx; 1000lx). Six elderly observers (aged 55-65 years) participated in the experiments and were exposed to each lighting condition to finish one trial of a color discrimination test (Farnsworth-Munsell 100-Hue Test) and a 7-scale, 6-item preference evaluation test. We conclude that elderly people perform better in color discrimination with higher CCT of LED light sources, which compensate for their decreased lens transmission at short wavelength. Their performance also increases with higher illuminance (30lx-1000lx) of LED lighting. Meanwhile, they prefer higher illuminance, which makes them find the lighting environment more comfortable, brighter, and better for reading; but for CCT, although they feel a higher CCT is better for reading, they still have different tastes regarding CCT of light sources. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

To improve the estimation accuracy of spectral reflectance from the given trichromatic value, a new two-step k-nearest neighbors locally weighted linear regression method is proposed. The algorithm has good local learning ability and can take into account the similarity of colorimetric and spectral reflectance space. The simulated and practical imaging experiments were carried out with Munsell matte and glossy dataset, respectively. Experimental results show that the mean root mean square error values of the spectral reflectance estimated by our model in simulated RGB, practical imaging Adobe RGB. and raw RGB data experiments are 0.00731, 0.01519, and 0.01453, respectively, and the mean color difference values under CIE standard illuminant D65 are 0.380, 1.311, and 1.180, respectively. In addition, we showed the calculation time cost of various models in the practical experiment. The calculation time of one sample for the proposed method is 0.094 s. The proposed method is better than several state-of-the-art methods in terms of comprehensive estimation performance and running efficiency. [ABSTRACT FROM AUTHOR]

In this paper, an isolated series asymmetrical half-bridge converter (SA-HBC) is proposed to satisfy the high power and high input-voltage requirements. In the proposed converter, two half-bridge modules with series configuration are adopted in the primary side to reduce the switch voltage stress to half of the input voltage. Moreover, the series half-bridge cells share the same transformer and leakage inductance, which simplifies the circuit structure. Zero-voltage-switching transition is achieved for all the active switches by employing the asymmetrical control scheme to reduce the switching losses. Furthermore, the voltages of the input capacitors are automatically balanced without any additional components or complex control methods. In addition, a family of dc–dc converters with series half-bridge structure is explored to give a universal discussion and extensive applications of the proposed contributions for the high input-voltage systems. Finally, a 500–600-V input 48-V output 1-kW prototype operating with 100 kHz switching frequency is built and tested to demonstrate the effectiveness of the proposed SA-HBC converter. The efficiency of 95% at full load is realized. [ABSTRACT FROM AUTHOR]

To achieve the goal of carbon neutrality, the demand for energy saving by the residential sector has witnessed a soaring increase. As a promising paradigm to monitor and manage residential loads, the existing studies on non-intrusive load monitoring (NILM) either lack the scalability of real-world cases or pay unaffordable attention to identification accuracy. This paper proposes a high accuracy, ultra-sparse sample, and real-time computation based NILM method for residential appliances. The method includes three steps: event detection, feature extraction and load identification. A wavelet decomposition based standard deviation multiple (WDSDM) is first proposed to empower event detection of appliances with complex starting processes. The results indicate a false detection rate of only one out of sixteen samples and a time consumption of only 0.77 s. In addition, an essential feature for NILM is introduced, namely the overshoot multiple (which facilitates an average identification improvement from 82.1% to 100% for similar appliances). Moreover, the combination of modified weighted K-nearest neighbors (KNN) and overshoot multiples achieves 100% appliance identification accuracy under a sampling frequency of 6.25 kHz with only one training sample. The proposed method sheds light on highly efficient, user friendly, scalable, and real-world implementable energy management systems in the expectable future. [ABSTRACT FROM AUTHOR]

Optimal operation of energy storage systems plays an important role in enhancing their lifetime and efficiency. This paper combines the concepts of the cyber–physical system (CPS) and multi-objective optimization into the control structure of the hybrid energy storage system (HESS). Owing to the time-varying characteristics of HESS, combining real-time data with physical models via CPS can significantly promote the performance of HESS. The multi-objective optimization model designed in this paper can improve the utilization of supercapacitors, reduce energy consumption, and prevent the state of charge (SOC) of HESS from exceeding the limitation. The new control scheme takes the characteristics of the components of HESS into account and is beneficial in reducing battery short-term power cycling and high discharge currents. The rain-flow counting algorithm is applied for battery life prediction to quantify the benefits of the HESS under the control scheme proposed. A much better power-sharing relationship between the supercapacitor and the lithium–ion battery (LiB) can be observed from the SIMULINK results and the case study with our new control scheme. Moreover, compared to the traditional low-pass filter control method, the battery lifetime is quantifiably increased from 3.51 years to 10.20 years while the energy efficiency is improved by 1.56%. [ABSTRACT FROM AUTHOR]

The reliable operation of photovoltaic (PV) power generation systems is related to the security and stability of the power grid and is the focus of current research. At present, the reliability evaluation of PV power generation systems is mostly calculated by applying the standard failure rate of each component, ignoring the impact of thermal environment changes on the failure rate. This paper will use the fault tree theory to establish the reliability assessment method of PV power plants, model the PV power plants working in the variable environment through the hardware-in-the-loop simulation system, and analyze the influence of the thermal characteristics of the inverter's key components on the reliability of the PV power plant. Studies have shown that the overall reliability of bus capacitors, inverters, and PV power plants is reduced by 18.4%, 30%, and 18.7%, respectively, compared to when the thermal characteristics of bus capacitors are not considered. It can be seen that thermal attenuation has a great influence on the reliability of the PV power generation system. [ABSTRACT FROM AUTHOR]

Power systems optimization is generally subject to the compromise between performance and cost. The 2021 Texas grid outage illustrates the worldwide dangers for the regional-centralized power grid, with comparable advantages to safety and flexibility for the distributed energy system. The storage of household batteries helps balance grid load and increase system stability and flexibility. However, household storage battery is still not widely used today because of its high costs. Currently, research on increasing household battery storage applicability is focused largely on optimizing economic strategies, such as configuration, dispatching and subsidy policies, which rely substantially more on technologies and financial perspectives. Consumers are not 'rational' individuals, and non-economic incentives can affect their decisions without raising prices. This paper consequently proposes to encourage users to acquire household battery storage to increase efficiency of power dispatching and economic advantages based on behavioral economics. In this paper, an empirical research builds upon the utility model of behavioral economics incentives and purchase willingness. Moreover, the multi-objective genetic algorithm is utilized to optimize the dispatching of household battery storage by using grid variance and user revenues as optimizing goals. The results of this paper show that the behavioral economics incentive improves intention to buy the household battery energy storage by 10.7% without raising subsidies. By improving the energy dispatching strategy, peak-load shifting performance and user revenues are improved by 4.2% and 10.6%, respectively. [ABSTRACT FROM AUTHOR]

The increased installation capacity of grid-connected household photovoltaic (PV) systems has been witnessed worldwide, and the power grid is facing the challenges of overvoltage during peak power generation and limited frequency regulation performance. With the dual purpose of enhancing the power grid safety and improving the PV utilization rate, the maximum feed-in active power can be regulated by modifying the maximum power point tracking (MPPT) algorithm and battery energy storage (BES) accessibility as control instructions. However, the existing methods not only waste installed PV capacity, but it becomes no longer accessible when the state of charge (SOC) of the BES approaches its upper limit. In response to the above problem, this paper proposes a power limit control strategy to coordinate the MPPT algorithm and the BES accessibility. The proposed strategy directly controls the inverter output current according to the power limit instructions from the electric operation control centers, leading to a bus voltage difference. The difference serves as a control signal for BES and PV. Under a power-limiting scenario, priority is given to power regulation through energy storage to absorb the limited active power. When the SOC of the BES reaches the upper limit of charging, modification of the PV MPPT algorithm facilitates the inverter output power to meet the power limit requirements. To further verify the effectiveness of the proposed power limit control strategy, both simulation and experimental studies are conducted, which consistently indicated a synchronized inverter current with grid voltage and a rapid power response of the power-limiting instruction within 0.2 s. The power limit control strategy not only improves the PV energy utilization but also supports the safe and reliable operation of the power gird in the context of soaring renewable energy penetration. [ABSTRACT FROM AUTHOR]

In recent years, the application of traceability systems in the food and drug industry has developed rapidly, but it is rarely used for wind turbines. From the aspects of low information transparency and information islands in the supply chain process for wind turbines, a reliable traceability system is essential. However, the existing traceability systems are not suitable to be directly applied to wind turbines. Consequently, according to the characteristics of the wind power industry, a semi-centralized traceability architecture based on Internet of Things technology was proposed. Furthermore, a traceability platform was constructed by analyzing the information collected in each stage related to various user needs of wind turbines, and various applications, including manufacturing management and spare parts management, were developed. Compared with the existing systems, the proposed platform was wind-turbine-oriented, effectively improved traceability efficiency and enterprises' information security, and extended the length of the traceability chain by integrating the after-sales information. The traceability of key components of wind turbines during their life cycle provides a useful reference for further improving the parts quality management system of the wind power industry. [ABSTRACT FROM AUTHOR]

Life cycle assessment (LCA) is conducive to the change in the wind power industry management model and is beneficial to the green design of products. Nowadays, none of the LCA systems are for wind turbines and the concept of Internet of Things (IoT) in LCA is quite a new idea. In this paper, a four-layer LCA platform of wind turbines based on IoT architecture is designed and discussed. In the data transmission layer, intelligent sensing of wind turbines can be achieved and their status and location can be monitored. In the data transmission layer, the LCA platform can be effectively integrated with enterprise information systems through the object name service (ONS) and directory service (DS). In the platform layer, a model based on IMPACT 2002+ is developed, and four management modules are designed. In the application layer, different from other systems, energy payback time (EPBT) is selected as an important evaluation index for wind turbines. Compared with the existing LCA systems, the proposed system is specifically for wind turbines and can collect data in real-time, leading to improved accuracy and response time. [ABSTRACT FROM AUTHOR]

Despite the rapid development of photovoltaic (PV) industry, direct current (DC) fault arc remains a major threat to the safety of PV system and personnel. While extensive research on DC fault arc has been conducted, little attention has been paid to the long-time interactions between the PV system and DC arc. In this paper, a simulation system with an arc model and PV system model is built to overcome the inconvenience of the fault-arc experiments and understand the mechanism of these interactions. For this purpose, the characteristics of the series DC arc in a small grid-connected PV system are first investigated under uniform irradiance. Then, by comparing with different arc models, the Habedank model is selected to simulate the fault arc and a method to determine its parameters under DC arc condition is proposed. The trends of simulated arc waveforms are consistent with the measured data, whose fitting degree in adjusted R-squared is between 0.946 and 0.956. Finally, a phenomenon observed during the experiment, that the negative perturbation of the maximum power point tracking (MPPT) algorithm can reduce the arc current, is explained by the proposed model. [ABSTRACT FROM AUTHOR]

Potential induced degradation (PID) leads to power degradation, and reduces durability and reliability of solar modules. However, this problem has not been thoroughly solved so far. The results from interlaboratory and field study show contradictory fault phenomenon for PID. In this paper, PID of crystalline silicon photovoltaic power plants distributed in various climate conditions was investigated. These photovoltaic power plants consist of two types of crystalline silicon solar modules, which cover almost all kinds of front glass, ethyl vinyl acetate (EVA) and backsheet available commercially. It was found that only a few of power plants were affected by PID. By measuring current voltage characteristics of PID-affected solar modules, the real faults phenomenon was uncovered and classified into regular and irregular power degradation in a module string. The results obtained in this work show that the negative potential caused by high system voltage and stacking faults are necessary and sufficient conditions for PID occurrence for the first time. The anomalous power degradation is related to the stacking fault, which appears randomly during the crystal growth. [ABSTRACT FROM AUTHOR]

The model parameter identification based on real operation data is a means to accurately determine the simulation parameters of the microgrid, but the real operation data cannot guarantee the exact agreement with the required data for parameter identification, which has become an important restriction factor in the accurate simulation and analysis of the dynamics of the microgrid. This paper provides a method of modeling of microgrid based on data testing and parameter identification. In this paper, the method of parameter trajectory sensitivity is first introduced. Then, the data testing scheme for parameter identification is presented, and the parameter identification flow chart is given. Thirdly, a microgrid demonstration system in China is taken as an example, the important parameters of the distributed photovoltaic, direct-drive wind turbine and energy storage unit in the system are obtained by data testing and parameter identification, and in the end, the accuracy of the model is verified through the comparison of the simulation data and the test data of the microgrid during grid-connection/island switching process. The obtained microgrid model provides a base model for the analysis of the overall characteristics, such as the transient stability, as well as power quality of the microgrid. [ABSTRACT FROM AUTHOR]

A transparent and anti-corrosive coating is of great importance for the protection of valuable articles, historical relics, and metal. However, there is a significant challenge due to the trade-off between high transparency and pleased anti-corrosive performance. The barrier function of skin, derived from the "brick and mortar" microstructure where hydrophobic corneocytes are parallelly embedded in lipids of the skin stratum corneum, offers an admirable concept to solve the problem. Herein, a novel bio-inspired assembly strategy is implemented to fabricate transparent and high-performance anti-corrosive epoxy nanocomposite coatings (Bio-MFICs), cooperating with superhydrophobic magnetic responsive graphene oxide nanosheets (FSO-GO) parallelly aligned in epoxy resin via magnetic-field-induced assembly and bridging structure further forming during curing process. The structure of Bio-MFICs is highly consistent with the "brick and mortar" structure of the skin stratum corneum, where FSO-GO nanosheets act as "corneocytes" and epoxy matrix acts as "lipids". The subtle skin-mimetic structure contributes to the excellent anti-corrosive performance of Bio-MFICs because of the prolonged and blocked diffusion pathway of corrosive media. As a result, the resistance of Bio-MFIC- 3 (0.75 wt% filler content) remains 4.17×107 Ω·cm−2, which is 43 times that of the pure epoxy coating, and the logarithm of breaking point frequency is quite low as −1.05 after immersion in 3.5 wt% NaCl solution for 28 days. Moreover, the transparency of the Bio-MFIC- 3 is highly close to that of the pure epoxy coating. This work provides an effective method of constructing transparent protective materials to reduce the loss of materials and achieve the goal of energy-saving and greenhouse gas emissions reduction. • A novel skin-mimetic strategy is proposed to fabricate transparent coatings with excellent barrier performance. • Magnetic-field-induced assembly is applied to construct the parallelly-aligned structure of graphene oxide sheets in epoxy. • Superhydrophobic magnetic responsive graphene oxide is synthesized by an in-situ method. • The anti-corrosion is realized by the prolonged diffusion pathway and higher diffusion resistance. [ABSTRACT FROM AUTHOR]

Carbon superstructures with exquisite morphologies and functionalities show appealing prospects in energy realms, but the systematic tailoring of their microstructures remains a perplexing topic. Here, hydrangea-shaped heterodiatomic carbon superstructures (CHS) are designed using a solution phase manufacturing route, wherein machine learning workflow is applied to screen precursor-matched solvent for optimizing solvent-precursor interaction. Based on the established solubility parameter model and molecular growth kinetics simulation, ethanol as the optimal solvent stimulates thermodynamic solubilization and growth of polymeric intermediates to evoke CHS. Featured with surface-active motifs and consecutive charge transfer paths, CHS allows high accessibility of zincophilic sites and fast ion migration with low energy barriers. A anion-cation hybrid charge storage mechanism of CHS cathode is disclosed, which entails physical alternate uptake of Zn 2+ /CF 3 SO 3 - ions at electroactive sites and chemical bipedal redox of Zn 2+ ions with carbonyl/pyridine motifs. Such a beneficial electrochemistry contributes to all-round improvement in Zn-ion storage, involving excellent capacities (231 mAh g -1 at 0.5 A g -1 ; 132 mAh g -1 at 50 A g -1 ), high energy density (152 Wh kg -1 ), and long-lasting cyclability (100 000 cycles). This work expands the design versatilities of superstructure materials and will accelerate experimental procedures during carbon manufacturing through machine learning in the future., (© 2024 Wiley‐VCH GmbH.)

Modern miniaturized intelligent electronics call for smart switchable and flexible electromagnetic interference (EMI) shielding material for highly precise applications. However, most switchable EMI shielding materials are based on an explicit structural change. Herein, we report a succulent-inspired smart switchable MXene (WR-MXene) coating film realized by inner implicit structural change, which benefits from the insertion of our reversible large-cavity yolk-shell biomicrospheres. The novel switchable yolk-shell biomicrospheres contain a soft N -isopropylacrylamide (PNIPAM) hydrogel core, an "ON/OFF" switchable cavity (over 30% volume fraction), and a porous polydopamine (p-PDA) shell. The yolk-shell biomicrospheres can be obtained by a facile two-step polymerization and a simple drying-dehydration treatment. Because of the "ON/OFF" switchable void space brought by the smart biomicrospheres and conductive framework of MXene, an optimized ultralight and flexible WR-MXene coating film (vWR-coating film) showed both large switchable change (over 60 dB) and extraordinary EMI shielding effectiveness, reaching 95 and over 50 dB in the whole X band (8.2-12.4 GHz). These novel reversible yolk-shell biomicrospheres and the succulent-inspired switchable coating films are promising for smart flexible wearable devices and many advanced multifunctional systems needing dynamic real-time response.

Purpose: Involuntary physiological responses offer an alternative means to psychophysical procedures for objectively evaluating discomfort glare. This study examined eye movement and pupil size responses to glare discomfort using new approaches to analysis: relative pupil size and speed of eye movement., Methods: Participants evaluated glare discomfort using the standard de Boer rating scale under various conditions manipulated to influence glare discomfort. Eye movement was recorded using an electro-oculogram (EOG), and pupil size was recorded using Tobii glasses. Ten young (mean age: 24.5 years old) and 10 senior (mean age: 61 years old) participants were recruited for this experiment., Results: Subjective evaluation of glare discomfort was highly correlated with eye movement (multiple correlation coefficient [R(2)] of >0.94, P < 0.001) and pupil constriction (R(2) = 0.38, P < 0.001). Severe glare discomfort increased the speed of eye movement and caused larger pupil constriction. Larger variations of eye movement were found among seniors., Conclusions: The two physiological responses studied here to characterize discomfort glare under various lighting conditions had significant correlation with the subjective evaluation. The correlation between discomfort glare and physiological responses suggests an objective way to characterize and evaluate discomfort glare that may overcome the problems of conventional subjective evaluation. It also offers an explanation as to why long-term exposure to discomfort glare leads to visual fatigue and eyestrain., (Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.)

To model discomfort glare from LED road lighting, the effect of four key variables on perceived glare was explored. These variables were: the average glare source luminance (Lg), the background luminance (Lb), the solid angle of the glare source from the perspective of the viewer (ω) and the angle between the glare source and the line of sight (θ). Based on these four variables 72 different light conditions were simulated in a scaled experimental set-up. Participants were requested to judge the perceived discomfort glare of these light conditions using the deBoer rating scale. All four variables and some of their interactions had indeed a significant effect on the deBoer rating. Based on these findings, we developed a model, and tested its general applicability in various verification experiments, including laboratory conditions as well as real road conditions. This verification proved the validity of the model with a correlation between measured and predicted values as high as 0.87 and a residual deviation of about 1 unit on the deBoer rating scale. These results filled the gap in estimating discomfort glare of LED road lighting and clarified similarities of and differences in discomfort glare between LED and traditional light sources.