Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

An ultra-low power (ULP), power gated static random access memory (SRAM) is presented for Internet of Things (IoT) applications, which operates in sub-threshold voltage ranges from 300mV to 500mV. The proposed SRAM has tendency to operate in low supply voltages with high static and dynamic noise margins. The IoT application involves battery enabled low leakage memory architecture in subthreshold regime which has low power consumption. Therefore, to improve power consumption along with better cell stability, a power gated 10T SRAM is presented. The proposed cell uses a power gated p-MOS transistor to reduce the leakage power or static power in standby mode. Moreover, due to the schmitt triggering and read decoupling of 10T SRAM the static and dynamic behavior in read, write and standby mode has shown enhanced tolerance at different process, voltage and temperature (PVT) conditions. The proposed SRAM shows better results in terms of leakage power, read static noise margin (RSNM), write static noise margin (WSNM), write-ability or write trip point (WTP), read-write energy and dynamic read margin (DRM). Further, these parameters are observed at 8-Kilo bit (Kb) and compared with already existing SRAM architectures. It is observed that the leakage power is reduced by 1/81×, 1/75× of the conventional 6T (C6T) SRAM and read decoupled 8T (RD8T) SRAM, respectively at 300mV VDD. On the contrary, RSNM, WSNM, WTP and DRM values are improved by 3×, 2×, 11.11% and 31.8% as compared to C6T SRAM, respectively. Similarly, proposed 10T has 1.48×, 25% and 9.75% better RSNM, WSNM and WTP values as compared to RD8T SRAM, respectively at 300mV VDD.

In order to achieve its carbon peak and neutrality targets, a high proportion of distributed power sources are connected to the distribution network in China, which greatly increases the risk of distribution network operation. Aiming at the above problems, this paper proposes an active distribution network risk planning model based on multi-source data from carbon capture and power internet of things, and conducts exceeding testing of distribution network based on the stochastic load flow algorithm with semi-invariant and level expansion, calculates the semi-invariant of each order of node state vectors and branch current vectors, and then utilizes the Gram-Charlier level expansion to obtain the exceeding probability density function and probability distribution function of the node voltages and line powers of the distribution network. The probability density function and probability distribution function of the exceeding are obtained using the Gram-Charlier series expansion. Combined with multi-source data, the active distribution network with integrated energy system considering carbon capture is modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model are simplified by the second-order cone relaxation, and the optimal planning scheme of the distribution network is solved by combining the gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verify the effectiveness of the proposed model.

The volatility and uncertainty associated with the high proportion of wind and PV output in the new power system significantly impact power and energy balance, making it challenging to accurately assess the risks related to renewable energy abandonment and supply guarante. Therefore, a probabilistic power and energy balance risk analysis method based on distributed robust optimization is proposed. Firstly, the affine factor and the flexible ramp reserve capacity of thermal power are combined to establish a probabilistic index, which serves to characterize the risk associated with power and energy balance. Drawing upon the principles of conditional value at risk theory, the risk indexes of load shedding power and curtailment power under a certain confidence probability are proposed. Secondly, the probability distribution fuzzy sets of uncertain variables are constructed using the distributionally robust method to measure the Wasserstein distance between different probability distributions. Finally, aiming at minimizing the operation cost of thermal power, the risk cost of power abandonment and the risk cost of load shedding, a distributed robust optimal scheduling model based on flexible ramp reserve of thermal power is established.

Energy from biogas is one of the most promising renewable energy sources. Significant, for technical, economic, and environmental reasons, is the construction of agricultural microgas plants next to households specialising in cattle rearing. The availability of free substrate makes it possible not only to produce one's electricity and heat but also to produce a more environmentally and human-friendly manure. The operation of biogas plants is, unfortunately, associated with technical problems. This paper presents the results of a study of the quality of electricity generated in an agricultural biogas plant built at a farm specialising in dairy cows, where the owner reported a problem with the voltage in the power supply network. Therefore, selected power quality parameters occurring at the connection point of the biogas plant were analysed in detail. As the authors' research showed, in the case in question, the agricultural biogas plant was connected via a cable with too small a conductor cross-section, which resulted in significant voltage exceedances, making it impossible to switch on the second of the biogas plant's generators. Replacement of the feed-in cable has enabled both generators to run, but significant fluctuations in the feed-in voltage values were still noticeable. Analysis of the subsequent measurements revealed the need for changes in the design of the digester itself. The proposal for change is to replace the two current digester mixers (each rated at 9 kW) with more mixers of lower power. The new mixers would operate in an alternating system, where only one would always be activated.

This paper presents a novel approach to power management techniques in energy storage system (ESS) interoperability with the energy power system (EPS) by inserting a SCADA controlled directional protection relay for improving the mode switching sequence. According with latest European standards, all necessary measures for re-synchronization and reconnection for health work of the system must be taken. The proposed approach intends to improve the “interface” between storage systems and electric power grid by using a directional relay which provides interoperability improvement by automatic recognizing and differentiating the switching sequence of the mode of operation from the fault mode. Simulated results from a small scale electrical generating system are provided. The results demonstrate that the proposed power management solution is technically ideal to achieve high quality energy while retaining the stability of the power grid network. The interoperability of PHS systems integrated with the electric power grid usually leads to perturbations in terms of frequency of the generated voltage, and for improving it we designed an automatic treating and re-connecting software module. This work regards the importance of producing electricity from green and renewable energy sources, while retaining the stability and reliability of the power grid. ESS systems are widely used to help balancing of intermittent forms of load demand on the electrical power grid at specific key moments. In this article, the pumped hydro storage (PHS) technologies are proposed as an economical way to utilize smoothly the off-peak energy or surplus energy, by pumping water to a reservoir at a higher level. During peak load periods, the stored water is discharged through the reversible pump-turbine to generate electricity to meet the peak demand controlled by designed SCADA application.

This paper provides a comparative analysis of AES (Advanced Encryption Standard) and Salsa20 algorithm implementations, focusing on power consumption efficiency in passive RFID (Radio Frequency Identification) tags and ultra-low-power devices. The main objective of this work is to determine which of these algorithms is more suitable to operate in these types of devices. For this purpose, ASIC (Application-Specific Integrated Circuit) implementations of AES and Salsa20 based on low-power approaches were developed and their power consumption was evaluated. Results demonstrate that Salsa20 power consumption is lower than AES (2.82μW and 4.01μW, respectively - both in 0.18μm), indicating that Salsa20 is a better choice than AES for passive RFID tags.

A supply chain management (SCM) system is a strategic cooperative that organically integrates all supply chains to improve the performance of a company. The greatest critical success factor of SCM is partnership. Without cooperation between companies, SCM performance is limited. Does this imply, therefore, that companies within the supply chain can achieve mutual transactions equally? If the power between companies is unequal, how does this affect their partnership? The focus of this study is to assess whether power types enhance SCM performance through partnerships. We categorize power types as mediated and non-mediated. Mediated power is categorized based on coercion, reward, and legitimate, while non-mediated power is categorized based on information, expert, and reference. Therefore, this study examines how power types form a causal partnership relationship within the supply chain, and performs an empirical investigation on how the partnerships influence SCM performance.

Along with the increasing industrialization of contries and population growth, the global. With the thougth of overcoming climate change and renducing greenhouse gas emissions in the atmosphere, interest in alternative sloar, wind, water, geothermal, tidal and ocean wave energy has significantly increased. Hydropower is one of the most used inexhaustible sources of energy on a global scale. The efficiency of water turbines can be increased by optimizing the blade cascade and the casing. For this purpose, research is conducted on specialized laboratory benches. The purpose is to determine the influencing parameters which affecting the nature of the power and cavitaion curves This paper presents the results of numerical and laboratoty studies of axial hydrokinetic turbines. A detailed analysis of the influence of the geometric parameters of the blades on the operating curves is made. A mathematica model for synthesis of the blade cascade is derived. An assessment of water energy soures has been made and sites of high energy potential have been pointed. The present material can be used for development of a methodology for calculation of efficient axial hydrokinetic turbines.

Part II, like Part I, discusses geometry, kinematics and statics in detail without taking into account power losses in meshing. The main goal of Part II, however, is to prove that there are complex and structurally coupled planetary gear systems, i.e. containing a closed circuit in which no circulation of power flow is generated. The power flow analysis is also carried out using the direct method, with a slight modification in the way of writing the equations identifying active and passive gears, i.e. at the same time the directions of power flow on all transmission paths. The analysed planetary gear system (PGS) is characterised by mobility equal to 1, i.e. single degree of freedom (DoF). It consists of three subsystems in the form of the 2KH type planetary units connected in series-parallel, specially selected to demonstrate the thesis of this paper. It consists of three subsystems in the form of single planetary subsystems of the 2KH type connected series-parallel, specially chosen to illustrate the thesis of this paper.

The interaction between the grid network and the offshore wind power plant (WPP) network can lead to the amplification of certain harmonics and potentially resonant conditions. Offshore WPP should limit the increment of harmonic voltage distortion at the point of connection to the grid network as well as within their internal network. The harmonic distortion should be limited within the planning level limits using harmonic compensation, which is usually achieved by using static filters. In this paper an active damping compensation strategy with a STATCOM using emulation of resistance at the harmonic frequencies of concern is analysed. Such a compensation is effective for the local bus, though the performance is not guaranteed at the remote bus. This paper investigates the challenges associated with remote harmonic compensation in the offshore WPP, which is connected to the onshore grid through long high-voltage cables and transformers. First, the harmonic distortion and the compensating effects of the filter are theoretically assessed. Afterwards, they are demonstrated using harmonic propagation studies and time domain simulations in PSCAD.

The paper presents modelling of relationships between wind velocity distributions observed in Poland and technical requirements for wind power stations design. The wind velocities distributions for various locations in Poland are determined, and expressed in Weibull distribution parameters. Theoretical computations concerning the dependence of wind power station as function of wind speed and aire physical properties are presented. Conclusions important for design of power stations fitted to atmospheric conditions in Poland are given. Wind power plants have been an important source of electricity generation for many years.Wind power modelling with the use of wind speed is used to improve the accuracy of forecasts and analyses of the power production of wind farms.

Field implementations of inductive power transfer (IPT) face many practical challenges that dramatically reduce power transmission effectiveness. Coil misalignment is a persistent issue in IPT systems, especially in applications involving vehicles or nonvisible coils. Furthermore, magnetic field symmetry convolutes the decomposition of misalignment measurements in multiple dimensions and frequently impedes the efficacy of traditional position correction strategies. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

Day by day, the share of renewable energy-based power plants such as offshore wind farms and photovoltaic power plants, in the present-day power systems is escalating. Nevertheless, most of these power-producing facilities have been located quite far away from the load centers. At this stage, HVDC power systems provide satisfactory options due to qualities such as reduced line losses, substantial controllability, and environmental advantages. Nevertheless, unique converter designs are required to combine asynchronous HVDC networks with each other and with already existing high voltage alternating current (HVAC) networks. In this study, based on the above special cases, a unique DC-DC modular multilevel converter (MMC) architecture is presented that provides an excellent solution for both integrating modern asynchronous HVDC networks and integrating these modern HVDC power systems with existing asynchronous HVAC power systems. The mathematical analysis of the recommended DC-DC MMC design has been examined in detail and the power transfer between two asynchronous power grids has been realized in a simulation environment. Efficient bilateral power transmission has been made achievable by the control system. The recommended DC-DC MMC topology has shown to be a highly successful approach, in the interconnection of HVDC power systems, according to the simulation results.

This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsive-ness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet cur-rent and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.

High-power lasers play an important role in modern science, industry, and medicine. A signifi-cant milestone was reached on December 5, 2022, when Inertial Confinement Nuclear Fusion (ICF) achieved scientific breakeven, releasing more energy than the input laser energy. Additionally, Extreme Ultraviolet Lithography (EUVL) has enabled the development of microchips with 3 nm process nodes, marking a leap in semiconductor technology. These examples together with the recent achievement of a 10 PW (1015 W) laser output heralds remarkable advancements in technology and science soon. Laser systems are broadly classified based on their operating re-gimes into two main categories: Continuous Wave (CW) operation, where the laser is continuously pumped and emits a steady beam of light, and the pulsed regime, in which the laser pro-duces single or multiple pulses at various repetition rates. This review will primarily focus on pulsed laser systems, exploring their various types and recent technological advancements.

Power quality (PQ) plays an important role in ensuring the smooth operation of power systems. PQ disturbances may cause significant consequences, impacting the reliability and efficiency of power networks. This paper presents a comprehensive review of PQ within smart grids and the integration of renewable energy sources. Methods of detecting, classifying, optimizing, and mitigating PQ events are reviewed with providing a brief theoretical explanation for each technique. Related work done in the past two decades, was conducted, presenting a clear view of the development of research in a chronological order serving as a guide for future investigations in this field of study.

Electricity consumption is often the hotspot of life cycle assessment (LCA) of products, industrial activities, or services. The objective of this paper is to provide a consistent, scientific, region-specific electricity-supply-based inventory of electricity generation technology for national and regional power grids. Marginal electricity generation technology is pivotal in assessing impacts related to additional consumption of electricity. China covers a large geographical area with regional supply grids; these are arguably equally or less integrated. Meanwhile, it is also a country with internal imbalances in regional energy supply and demand. Therefore, we suggest an approach to achieve a geographical subdivision of the Chinese electricity grid, corresponding to the interprovincial regional power grids, namely the North, the Northeast, the East, the Central, the Northwest, and the Southwest China Grids, and the China Southern Power Grid. The approach combines information from the Chinese national plans on for capacity changes in both production and distribution grids, and knowledge of resource availability. The results show that nationally, marginal technology is coal-fired electricity generation, which is the same scenario in the North and Northwest China Grid. In the Northeast, East, and Central China Grid, nuclear power gradually replaces coal-fired electricity and becomes the marginal technology. In the Southwest China Grid and the China Southern Power Grid, the marginal electricity is hydropower towards 2030.

The growing attention for plug-in electric vehicles, and the associated high-performance demands, have initiated a development trend towards highly efficient and compact on-board battery chargers. These isolated ac-dc converters are most commonly realized using two conversion stages, combining a non-isolated power factor correction (PFC) rectifier with an isolated dc-dc converter. This, however, involves two loss stages and a relatively high component count, limiting the achievable efficiency and power density and resulting in high costs. In this paper a single-stage converter approach is analyzed to realize a single-phase ac-dc converter, combining all functionalities into one conversion stage and thus enabling a cost-effective efficiency and power density increase. The converter topology consists of a quasi-lossless synchronous rectifier followed by an isolated dual active bridge (DAB) dc-dc converter, putting a small filter capacitor in between. To show the performance potential of this bidirectional, isolated ac-dc converter, a comprehensive design procedure and multi-objective optimization with respect to efficiency and power density is presented, using detailed loss and volume models. The models and procedures are verified by a 3.7 kW hardware demonstrator, interfacing a 400 V dc-bus with the single-phase 230 V, 50 Hz utility grid. Measurement results indicate a state-of-the-art efficiency of 96.1% and power density of 2.2 kW/dm³, confirming the competitiveness of the investigated single-stage DAB ac-dc converter.

The energy supply for isolated systems remains a current challenge in Brazil and worldwide, particularly when known solutions are compared regarding cost, the ability to supply energy on demand, and sustainability. In this context, green hydrogen, which has been considered one of the main paths for the decarbonization of the energy chain, is also seen as a potential solution for energy supply in isolated systems. Based on a literature review of articles addressing the topics of green hydrogen and isolated systems, an analysis is conducted on the application of green hydrogen as an energy supply solution for isolated systems. The review identified and collected data on important parameters for comparing solutions, such as CAPEX, OPEX, energy cost, and the price per kilogram of hydrogen. Using these data, analyses were performed to provide an overview of the application of green hydrogen in isolated systems. One of the objectives of this work is to present a comprehensive analysis of the green hydrogen chain and its application in the context of electricity generation, particularly for isolated systems in Brazil.

There are several challenges on how to attain energy efficiency while maintaining balance among factors affecting energy consumption such as power rating and temperature setpoints of cooling units, room temperature and humidity, and indoor air quality (IAQ). A real-time energy and IAQ monitoring system were installed in an educational building to profile the operational power consumption of inverter-based air condition unit (ACU) installed in each room. Polynomial curve and neural fitting regression analysis were applied to the real-time power consumption, indoor temperature and humidity, and carbon dioxide (CO2) level data. The derived models were able to provide the stabilizing indoor thermal and air conditions of the room to reach steady state ACU power consumption. These collected data and calculated parameters can be used to define rules in automating control of cooling appliances for an efficient energy utilization. The regression approaches, using real-time data, have determined the influence of indoor heat conditions and carbon dioxide levels on ACU power consumption. These parameters were utilized to establish consistent values for temperature, humidity, and carbon dioxide levels under stable settings of inverter-based air conditioning units.

Motor imagery requires mental representation of the body, which is obtained by the integration of exteroceptive and interoceptive information. The aim of the study was to investigate the role of interoceptive sensitivity in motor imagery performed through visual and kinesthetic modalities in participants with low (lows, N = 26), medium (mediums, N = 11) and high hypnotizability scores (highs, N = 16), measured by the Stanford Hypnotic Susceptibility Scale: Form A. These groups display different motor imagery abilities and interoceptive sensitivity. The efficacy of motor imagery was measured by chronometric index and self-reported experience, and interoceptive sensitivity by the Multisensory Assessment of Interoceptive Awareness (MAIA) questionnaire. EEG alpha and beta power spectral densities were extracted from recordings acquired during baseline, actual movement, visually and kinesthetically imagined movements. The chronometric indices did not reveal significant differences among groups and between imagery modalities. In contrast, the self-reported imagery efficacy indicated better kinesthetic imagery in highs and mediums than in lows, and no modality difference among lows. MAIA dimensions sustained the differences in sub-jective experience and almost all the EEG differences, slightly different in highs, mediums and lows. This is the first report of a major role played by interoceptive sensitivity in motor imagery.

The article discusses issues related to the optimization of the operation of medium voltage networks, focusing on the optimization of network division points and the selection of the optimal network configuration aimed at reducing power and energy losses. The article provides a critical review of selected scientific works from recent years on the issue of network configuration optimization. The developed solution uses non-deterministic network models and statistical and probabilistic approaches. Optimization studies were carried out using heuristic optimization methods and proprietary algorithms for forecasting the load and power generated from renewable energy sources. The solution proposed in the article has many application possibilities. It can be used to optimize the location of network division points (reducing economic costs related to the modernization of network infrastructure) as well as to optimize the reconfiguration process in order to reduce power losses while maintaining voltage criteria.

In this paper, single and repetitive frequency UIS characteristics of 1200 V asymmetric (AT)and double trench silicon carbide (DT-SiC) metal–oxide-semiconductor field-effect transistors (MOSFETs) under different working conditions are investigated by experiment and simulation. For asymmetric trench SiC MOSFETs, the failure mode is all thermal runaway under working conditions. However, the failure mode of double trench SiC MOSFETs mostly is gate oxide rupture, which indicates an instable avalanche robustness under UIS stress. The variations of measured parameters are recorded to evaluate typical electrical features of device failure. Furthermore, TCAD simulation is used to reveal the electro-thermal stress inside the device during avalanche. Additionally, failed devices are decapsulated to verify the location of failure point from the perspective of the semiconductor die. Finally, a new type of stepped-oxide vertical power DT MOSFET with P-type shielding and current spread layers is proposed for improvement of gate dielectric reliability.

Synergistic control of emissions of air pollutants and CO2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO2 and NOX emission characteristics of these units, identifies and quantifies the synergistic drivers affecting these emission trends. Inventory data show that between 2010 and 2020, NOX emissions were reduced by 86.1%, while CO2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NOX emissions through measures such as end-of-pipe treatment, controlling CO2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO2 and NOx emission growth, energy intensity reduction is the main driver of CO2 emission reduction, and end-of-pipe treatment is the main driver of NOX emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing-Tianjin-Hebei, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NOX emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, the high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Mother's milk is the complete food of choice and the best nutritional source for its bio-immunological richness and its microbiota composed of lactic acid bacteria. The aim of this study was to assess the probiotic potential of the lactic acid bacteria present in breast milk. 34 samples (colostrum, transition milk, mature milk) were taken from breastfeeding women. They were enriched and inoculated onto MRS and MRS+cysteine agar. The sensitivity profile of the bacterial strains was assessed using the diffusion method. PCR was used to search for resistance genes specific to the target bacteria after extraction of the genomic DNA from the isolated strains. Their probiotic capacity was explored by assessing their ability to develop under different conditions. Forty-nine bacterial strains were isolated and Lactobacillus acidophilus was the most representative species in the three types of milk. These strains were able to develop both in hostile conditions and over a wide range of temperatures. They also showed antibacterial activity against pathogenic strains of Salmonella typhimurium, multi-resistant Staphylococcus aureus and Escherichia coli (ATCC25299). These results show that breast milk has potential probiotic activity that can be explored further to make the most of it, particularly in terms of antibiotic therapy.

In this paper, a method of charging lead acid battery with solar power by flyback converter is proposed. The basic system consists of a buffer circuit, auxiliary power circuit, control circuit, voltage feedback circuit and current feedback circuit. The system is capable of monitoring battery voltage and the current, charging the coupling inductor and automatic control of output duty cycle, overcharging and over-discharging protection. The experiment proves that the charging efficiency is improved by about 83% at full load.

This paper deals with the problem of determining the optimal capacity of Concentrated Solar Power (CSP) plants, especially in the context of hybrid solar power plants. This work presents an innovative analytical approach to optimize the capacity of concentrated solar plants. The proposed method is based on the use of additional non-dimensional parameters, in particular the design factor and the solar multiple factor. The paper presents a mathematical optimization model that focuses on the capacity of concentrated solar power plants where thermal storage plays a key role in the energy source. The analytical approach provides a more complete understanding of the design process for hybrid power plants. In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for a more refined optimization, which allows for a more accurate selection of the capacity for specific geographical conditions. Importantly, the proposed method significantly increases the speed of computation compared to traditional numerical methods. Finally, the authors present the results of the analysis of the proposed system of equations for calculating the levelized cost of electricity (LCOE) for hybrid solar power plants. The nonlinearity of the LCOE on the main calculation parameters is shown.

Carbon Quantum Dots (CQDs) have emerged as promising nanomaterials for enhancing the performance of supercapacitors, offering unique advantages such as high surface area, excellent electrical conductivity, and tunable surface chemistry. This review provides a comprehensive overview of recent advancements in the synthesis, characterization, and integration of CQDs into supercapacitor devices. Various synthesis methods, including chemical oxidation, hydrothermal/solvothermal methods, microwave-assisted synthesis, and pyrolysis, are discussed, highlighting their impact on the structural and electrochemical properties of CQDs. Characterization techniques such as transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, and photoluminescence (PL) spectroscopy are elucidated for assessing the morphology, crystallinity, and optical properties of CQDs. The integration of CQDs into supercapacitors, including their utilization in composite electrodes, binder-free electrodes, and doping strategies, is explored to enhance specific capacitance, energy density, power density, and cycle stability of the devices. Challenges and future perspectives in the field are outlined, emphasizing the need for scalable synthesis methods, enhanced electrochemical performance, and sustainable device engineering to realize the full potential of CQD-based supercapacitors for various energy storage applications. This review aims to provide insights into the current state of research and guide future endeavors towards developing high-performance and environmentally sustainable energy storage technologies.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

This is a study on fractals existing in music. The application case is the composition DIAPHONIES of Michael Paouris. Sliding-window fractal analysis indicate areas of continuous fractality dipped in non-fractal areas of possibly deterministic and stochastic nature. Diverging cases of pronounced non-fractal areas are addressed and also areas of mixed fractality and non-fractality. Many segments exhibit persistency-P (2

The occurrence of chaotic instability of oscillations at the output of a single-stage amplifier on a powerful bipolar microwave transistor when a biharmonic signal is amplified is considered. It has been established that at a high level of the input signal at the output of the amplifier, the signal contains a significant chaotic component. Cases were experimentally studied when the frequency distance between the partial frequency components of a biharmonic signal is close to the gain band and when it is much smaller than this band. It has been established that in the first case, the chaos in oscillations is associated with the emergence of a sequence of trains of a forced oscillatory process with arbitrary initial phases and durations. In the second case, the appearance of a chaotic pedestal is associated with the chaos in the passive underexcited mode of the nonlinear circuit formed by the capacitance of the p-n junction and the input matching circuits of the amplifier stage.

Objectives: To compare the effects of high-velocity resistance training to slow-velocity re-sistance training on neuromuscular and functional parameters and to analyze the relationship between changes in walking speed and improvements in neuromuscular parameters following intervetions. Methods: 40 participants were randomly assigned to either a high-speed resistance training group (GHS, n = 18; age = 80.41 ± 10.12 years; BMI = 23.81 ± 3.45 kg/m²) or a low-speed resistance training group (GLS, n = 22; age = 82.89 ± 5.32 years; BMI = 23.81 ± 3.45 kg/m²). Before and after the interventions, gait speed (m/s) was assessed using a 10-minute walking test, and relative maximal force (Relative F max, N/kg) was evaluated during maximal voluntary isometric con-traction of the plantar flexors. From the force-time curve, early (0 – 50 ms) and late (100 – 200 ms) rates of force development (RFD) were extracted from the linear slopes (Δ force / Δ time). Results: Gait speed significantly improved in both groups (p < 0.05). However, the improvement was more pronounced in the GHS compared to the GLS (p < 0.05). Relative Fmax showed a more significant increase in the GLS than in the GHS (p < 0.05). Moreover, a significant 10% increase in early RFD in the GLS and a 20.1% increase in the GHS were observed (p < 0.05). The improvement in early RFD was greater in the GHS (p < 0.05). Additionally, late RFD improved significantly only in the GHS (+20.4%, p < 0.05). Conclusion: High-velocity resistance training appears particularly effective in improving the ability to rapidly generate force, which is essential for many daily activities re-quiring explosive movements and quick responses.

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to the plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation such as wind and solar is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that Energy Storage Systems integrated with a thermal power plant improves plant flexibility and participation in the Energy and Ancillary Services markets which improves plant financial performance. The study was funded by the U.S. Department Office of Fossil Energy FE-1 under Award Number DE-FE0031903.

In power systems there are complex transformer structures, whose accurate analysis is not possible using the techniques available today. This paper presents a systematic data driven analysis method for coupled inductors of arbitrary complexity. The method first establishes a winding matrix N mapping the windings to the limbs of the transformer. A permeance matrix P is created from the reluctance network of the magnetic core. A generalized inductance matrix L mapping currents in the transformer windings to the induced voltages is generated based on the winding (N) and permeance (P) matrices. The inductance matrix representation of a coupled inductor is then transformed to an admittance matrix, which can be integrated to the nodal analysis of the electrical circuit surrounding the coupled inductor. The method presented is validated by simulations with real transformer structures using electromagnetic transient program (EMTP/ATP).

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consist of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to LNG terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

As the aging of the world accelerates, clarifying the relationship between cultural differences and ageism is an urgent issue. Therefore, in this study, we conducted a correlation analysis between the six cultural scales of Hofstede et al. [1] and the objective and subjective ageism scales calculated from data on 35,232 people from 31 countries included in the World Values Survey Wave 6 by Inglehart et al. [2]. The results of a partial correlation analysis controlling for economic and demographic factors showed that power distance (PDI) and indulgence versus restraint (IVR) are positively and negatively correlated with ageism, respectively. This is the first study to show that these two cultural scales that previous studies have not paid much attention to are related to ageism.

An active power dispatch method for a microgrid (MG) with multi-type loads, renewable energy sources (RESs) and distributed energy storage devices (DESDs) is the focus of this paper. The MG operates in a grid-connected model, and distributed power sources contribute to the service for load demands. The outputs of multiple DESDs are controlled to optimize the active power dispatch. Our goal with optimization is to reduce the economic cost under time-of-use (TOU) price, and to adjust the excessively high or low load rate of distributed transformers (DTs) caused by the peak-valley demand and load uncertainties. To simulate a practical environment, the stochastic characteristics of multi-type loads are formulated. The transition matrix of system state is provided. Then, a finite-horizon Markov decision process (FHMDP) model is established to describe the dispatch optimization problem. A learning-based technique is adopted to search the optimal joint control policy of multiple DESDs. Finally, simulation experiments are performed to validate the effectiveness of the proposed method, and the fuzzification analysis of the method is presented.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

The use of alternative fuels and electric vehicles is an opportunity to reducing exhaust emissions. We observe that the regulations on exhaust emissions from mobile sources are becoming gradually stricter on the all the world. As is widely known, using alternative fuels instead of conventional fuels helps lower vehicle emissions. The most popular alternative fuels are hydrogen, propane, biobutanol, methanol, dimethyl ether, etc. It is very important that more than a dozen alternative fuels are under development. The article contains a comparison of the operating costs of electric cars and cars with an internal combustion engine. This work shows also the characteristic of new alternative fuels and their impacts on exhaust emissions.

This research has developed a process for producing ZnO thin film from DEZn deposited onto a PET substrate with low-pressure, high-frequency Ar + O2 plasma using a chemical vapor deposition technique. The aim is to study the film production conditions that affect electrical properties, optical properties, and thin film surfaces. This work highlights the use of plasma energy produced from a mixture of gases between Ar + O2. Plasma production is stimulated with an RF power supply to deliver high chemical energy and push ZnO atoms from the cathode inside the reactor onto the substrate through surface chemical reactions. The results showed that increasing the RF power in plasma production affected the chemical reactions on the substrate surface of film formation. The film preparation at RF power 300 W will give the thickest films. The film has a continuous columnar formation, and the surface has a granular structure. This results in the lowest electrical resistivity of 1.8 x 10-4 Ω-cm. In addition, when fabricated into a DSSC device, the device tested the PCE value and showed the highest value at 5.68%. This is due to the very rough surface nature of the ZnO film, which increases the scattering and storage of sunlight, making cells more efficient. Therefore, the benefit of this research is that it will be a highly efficient prototype of thin film production technology using a chemical process that reduces production costs and can be used in the industrial development of solar cells.

Solar photovoltaic (PV) generation suffers from multiple serious issues, for example shading effects directly affect the performance of installed PV arrays. By studying these issues, it can play a key role in improving the limitations and performance of PV panels. The study of PV arrays under partial shading conditions is mentioned in many papers as a part of other studies and as an independent phenomenon. Therefore, it is essential to improve these studies and update them with new research and study this problem in detail to know how to limit the effects of partial shading irradiance conditions on PV arrays performances, including economical aspects. This paper proposes to study the effects of different partial shading irradiance conditions for a PV array in various configurations. The analysis is proved in detail through the simulation of the proposed PV array in the Matlab/Simulink environment. The obtained results show the performances of interconnected PV arrays under different partial shading irradiance and temperature conditions, including the solar array I-V and P-V characteristics. In addition, different PV array configurations with and without bypass and blocking protection diodes improve and minimize the effect of partial shading conditions and avoid the reductions in output power.

The UK government and many international experts have pointed out that nuclear energy has an important role to play in the transition towards a decarbonized energy system since it is the only freely manageable very low-carbon energy technology with 24/7 availability to complement renewables. Besides current investments in light water reactor technologies, we need innovation for improved fuel usage and reduced waste creation, like offered by iMAGINE, for the required broad success of nuclear technologies. To allow quick progress into innovative technologies like iMAGINE and their regulation, a timely investment into urgently needed experimental infrastructure and expertise development will be required to assure the availability of capacities and capabilities. The initial steps to start the development of such a new reactor physics experimental facility to investigate molten salt fast reactor technology are discussed and a stepwise approach for the development of the experimental facility is described. The down selection to the choice for a diverse control and shutdown system is described through manipulating the reflector (control) and splitting the core (shutdown). The developed innovative core design of having the two core parts in two different rooms opens completely new opportunities and will allow to manifest the request for separated operational and experimental crews, as nowadays requested by regulators into the built environment. The proposed physical separation of safety relevant operational systems from the experimental room should on the one hand help to ease the access to the facility for visiting experimental specialists. On the other hand, the location of all safety relevant systems in a now separated access-controlled area for the operational team will limit the risk of misuse through third party access. The planned experimental programme described with the major steps: core criticality experiments, followed by experiments to determine the neutron flux, neutron spectrum, and power distribution as well as experiments to understand the effect of changes in reactivity and flux as a function of salt density, temperature and composition change.

The aim of this cross-sectional study was to assess the influence of the maturity status on speed, explosive power and change of direction (COD) in 13-year-old football players. Ninety-eight male players (age: 13.1 ± 1.0 y) were divided into late, average, and early maturation groups. Physical fitness testing included the following variables: 10 and 30-meter sprint time and maximum speed in the 20-30 m segment of the 30-meter sprint test, the T-test time, countermovement jump height and horizontal distance in the triple jump. The data showed a significant effect of maturity status on performance in three parameters: in maximum speed in the 20-30 m section (p = 0,024), however, the only significant differences were found between the early-maturation group and average-maturation group (p = 0.033); in the COD (p = 0.024), where significant differences were confirmed between the late-maturation group and the average-maturation group (p = 0.033); in the unilateral triple jump distance of the dominant and non-dominant (p = 0,007 and p = 0.001, respectively) lower limb. For both limbs, significant differences between the late-maturation group and average maturation group (p = 0.005 and p = 0.013, respectively) as well as the late-maturation group and early-maturation group (p = 0.007 and p = 0.045, respectively) were proved. These results indicate that maximal speed, COD speed and unilateral lower limb reactive strength are moderated by biological age in football players aged 13 years.

Integration of wind energy into the grid faces a great challenge regarding power quality. The International Electrotechnical Commission (IEC)~61400-21 standard defines the electrical characteristics that need to be assessed in a Wind Turbine (WT), as well as the procedure to measure the disturbances produced by the WT. One of the parameters to be assessed are voltage fluctuations or flicker. To estimate the flicker emission of a Wind Power Plant (WPP), the standard establishes that a quadratic exponent should be used in the summation of the flicker emission of each WT. This exponent was selected based on studies carried out in WPPs with type I and II WTs. Advances in wind turbines technology have reduced their flicker emission, mainly thaks to the implementation of power electronics for the partial or total management of the power injected into the grid. This work is based on measurements from a WPP with 16 type III WTs. The flicker emission of a single WT and of the WPP were calculated. Low flicker emission values at the Point of Common Coupling (PCC) of the WPP were obtained. The flicker estimation at the PCC, based on the measurement from a single WT, was analyzed using different exponents. The results show that a cubic summation performs better than the quadratic one in the estimation of the flicker emission of a WPP with type III WTs.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

Plasma electrolytic polishing (PeP) is mainly used to improve the surface quality and thus the performance of electrically conductive parts. It is usually used as an anodic process, i.e. the workpiece is negatively charged. However, the process is susceptible to high current peaks during the formation of the vapour skin especially when polishing workpieces with a large surface area. In this study, the critical influence of workpiece submerging velocity on the current peaks and the average power during the initialisation of the PeP process is investigated for a workpiece size of microreactor mould insert. Through systematic experimentation and analysis, this work provides insights into the control of the initialisation process by modulating the workpiece submerging velocity. The results clarify the relationship between submerging velocity, peak current and average power and provide a novel approach to improve process efficiency in PeP. The highest peak current and average power occur when the electrolyte splashes over the top of the workpiece and not, as expected, when the workpiece touches the electrolyte. By submerging the workpiece while the voltage is applied to the workpiece and counter electrode, the reduction in both parameters is over 80 %.

This study aimed at characterizing the composition and performing chemical speciation modelling to determine species that are abundant in the coal fly ash (CFA) and soil samples sourced from Hendrina Power station located in Mpumalanga Province. All CFA samples were alkaline in nature with pH values ranging between 8.11 ± 0.07 and 8.60 ± 0.03 with an electrical conductivity (EC) ranging between 301.70 and 1515.00 µS/cm while EC of control soil was 103.10 µS/cm. The control soil pH was found to be 6.24 ± 0.13 and total organic carbon values ranged between 2.68 and 85.82 mg/kg and some percentage organic carbon values of CFAs were found to be greater than 8%, which is above the permissible limits of hazardous waste dumping. Oxidation-reduction potential values were negative in all CFA samples and positive in soil. The speciation modelling showed that the potential for a trace metal to have hazardous effects in soil systems depends on its concentration, specific form and interactions with other constituents in CFA. The slow release of metals from CFA to soil was assessed by looking at how a given metal is distributed throughout its several possible chemical forms. The presence of divalent cations (Pb2+, Cu2+, Zn2+, etc.) in CFAs might pose a threat to soil quality. In the competition for binding sites on ferric hydroxides, dissolved metal ions faced off against other metals. Protons (H+) were seen to be in competition with Pb, Cu and Zn for the ability to bind to hydroxyl (OH-) groups and this is due to chemical precipitation and surface complexation.

Study assessed the wind potential of three sites in Chad: Koro Toro, Salal and Nedeley. Analysis of the Weibull distribution curves reveals marked seasonal variability in wind speed, concentrated around the mean. Three models of high-power wind turbines were analyzed. At Koro Toro, the Siemens Gamesa SG 14-222 DD has a capacity factor of between 0.52 and 0.682, allowing a daily flow of pumped water of between 1.4 and 6.1 million m³. The Enercon E-126 EP4 performs slightly less well. At Salal, the Siemens Gamesa has a capacity factor of between 0.4463 and 0.6605, with a water flow rate of between 0.9 and 3.7 million m³/day. The Vestas V164-10.0 MW has a higher capacity factor (0.6327 to 0.8115) but a lower water flow rate (0.5 to 1.9 million m³/day). Enercon's performance is comparable to that of Siemens Gamesa. The Nedeley study reveals favorable conditions, with seasonal variations in wind speed and capacity factor indicating good wind potential, and maximum daily water flows of between 3 and 6 million m³. Analysis of the wind roses shows interesting potential in these towns, with a dominant east-north-easterly wind at maximum frequencies of 40%. The absence of calm winds is promising, although Nedeley and Salal have a residual presence. This study shows that the sites offer good wind potential This, enabling the production of electricity and heat.

{This study investigates the coordinated behaviors and the underlying collective intelligence in biological groups, particularly those led by informed leaders. By establishing new convergence criteria based on real biological group experiments, this research introduces the concept of a volitional term and heterogeneous networks, constructing a coupled force Cucker-Smale model with informed leaders. The inclusion of the informed leader aspect distinctively characterizes the dynamics of leaders and followers, enabling a more accurate representation of biological group behavior. The paper then proposes the Flock Leadership Hierarchy Network (FLH), a model reflecting real biological interactions. By employing time slicing and rolling time windows, the study methodically analyses group behavior stages, using volatility and convergence time as metrics to examine the relationship between group consistency and interactions. Comparative experiments show the FLH network's superior performance. The Kolmogorov-Smirnov test indicates that the FLH network follows a power-law distribution, highlighting the evolutionary intelligence of biological groups. This research offers new perspectives on the evolution of biological groups, contributing to our understanding of both natural and artificial systems, such as animal migration and autonomous drone operations.

Abstract—Hydraulic switching actuators are high efficiency, fast response, and low cost solutions for hydraulic control systems. One of the challenging problems is throttling losses during valve transitions. Previously the authors proposed a zero-flowrate switching method to reduce throttling energy loss of the switching valve, where a hydraulic resonator is applied to make the flowrates through the lines approaching zero before the valves are switched off. The major challenge of this approach is fast switching valves whose transition times are less than 2 ms. In this paper, an improved zero-flowrate switching method is presented. It utilizes the capacity with independent inlet/outlet ports to regulate flowrates through the lines. Models of capacity applied in a simple line with different pressure signals are developed to explore characteristics of the capacity, based on which a complete actuation system is developed. In the complete model, resistance and inductance are optimized to achieve desired flowrate response. The improved zero-flowrate switching method reduces throttling energy losses by 99.945% compared to a hard switching system. The simulation results demonstrated that the improved zero-flowrate switching method performs as expected in the design condition. A capacity with proper volume is able to regulate flowrates through all the lines to zero, with the help of appropriate resistance and inductance. Compared to previous zero-flowrate switching method, the novel strategy allows slower switching valves applied in hydraulic actuation systems and achieves better efficiency performance. This research paves a new avenue for reducing throttling energy losses and improves system efficiency in hydraulic switching actuators, as well as most of the hydraulic switch-mode circuits.

Power quality problem is a hot area in power systems and drives that has drawn the attention of many researchers. This is because of the threat it poses on the health of electrical systems and the cost incurred on utility bills. The problem arises as a result of the need for reactive power to be supplied alongside active power in power transmission and distribution. Unfortunately, reactive power is consumed by almost all components of the system, leading to a shortage. To solve this problem, there is a need to compensate for the lost reactive power. Several researchers have proposed various approaches to mitigate this problem such as thyristor switched capacitor bank, series compensator, series reactor, series var compensator (SVC), Static Synchronous Compensator (STATCOM), synchronous condenser and others. In order to further draw attention in this area, this work investigates a number of research papers on power compensation techniques and draw up challenges from each work that can be considered for further investigation. To this end, each research paper reviewed is evaluated in terms of problem solved, technique used, and results obtained. It therefore offers ample opportunities for researchers to explore in improving power quality and power system safety.

The Power Theory of Exchange and Money (PTEM) refines the economic neoclassical two-equation model of exchange. PTEM replaces the statistical average condition of exchange, which represents the equality of supply and demand for all transactions in the market, with a more specific equation of the equality of the generalized power of the parties in relation to their objects of exchange. The purpose of the article is to show the application of PTEM for the study of various social phenomena. Along with a brief summary of the main statements of this theory, its integration into the existing corpus of theories and ideas in economics and sociology is considered. The conclusions of power theory are then applied to consider the following topics: the objective motivation of exchange by the desire to increase power, the power nature of market equilibrium, the power nature of money, the accumulation of power through profit, the creation of money as a power act, the role of the state in the creation of money, the measure of power as a possible tool for social and political research.

The correct selection of the value of p is a complex and iterative procedure that requires experience in the interpretation of the obtained interpolated maps. Inverse Distance Weighting is a method applied to the porosities of the K and L hydrocarbon reservoirs, discovered in the Neogene (Lower Pontian) subsurface sandstones in the northern Croatia (Pannonian Basin System). They represent small and large data samples. Also a standard statistical analysis of the data was made, followed by the qualitative-quantitative analysis of the maps, based on the selection of different values of the power distance exponent (p-value) for the K and L reservoirs maps. According to the qualitative analysis, for a small data set, p-value could be set on 1 or 2 giving the most optimal result, while for a large data set, a p value of 3 and 4 could be applied. By quantitative analysis, for the case of small data p=2 is recommended, resulting in a root mean square error value of 0.03458, a mean absolute error of 0.02013 and a median absolute deviation of 0.00546. Oppositely, a p-value of 3 and 4 is selected as appropriate for a large data set, with root mean square errors of 0.02435 and 0.02437, mean square errors of 0.01582 and 0.01509 and median absolute deviations 0.00896 and 0.00444. Eventually for a small data set, it is recommended to use a p-value of 2, and for a large data set, a p-value of 3 or 4.

A recently published article posited the use of polymer matrix composites (PMCs) as a replacement material for low-carbon steel (LCS) in large power transformer (LPT) tanks [1]. PMCs offer potential advantages such as weight reduction, corrosion prevention, and self-healing of the tank material which may not be achievable with traditional LCS. LCS can arrest ballistic projectiles at relatively low velocities, but at higher velocities, penetration can occur leading to a potential major transformer failure. Numerical simulations of steel projectile impacts upon LCS plates and glass and/or carbon fiber polymer composite laminates showed that with sufficient thickness both could prevent projectile penetration. This prevention was especially efficient when the plates were coated with a high strain rate sensitive material such as polyurea (PU). Our simulations show that the addition of a 3 mm coating of PU to a standard 10 mm thick LCS plate used in LPT tanks could prevent penetration of a 400 m/s steel projectile. For PMC plates, the simulations with the same projectile velocity showed three times faster deceleration with a 3 mm PU coating than without the coating. Thus, two realistic approaches to improving the ballistic protection of LPTs are presented. In addition to their other advantages, this research clearly shows that PMCs with the coating could provide significant ballistic protection for the next generation of LPT tanks.

Extremely low-frequency electromagnetic fields (ELF-EMFs) are non-ionizing radiations typically emitted by power lines, electrical wiring and electrical appliances. Epidemiological studies have repeatedly shown a positive association between ELF-EMFs and childhood leukemia. Exposures greater than 0.3-0.4 µT increase the risk by approximately 1.5-2 fold, and estimates indicate that up to 2% of childhood leukemia cases in Europe may be attributable to ELF-EMFs. However, it is considered unlikely that ELF-EMFs can cause cancer, because carcinogenesis requires the accumulation of DNA alterations and ELF-EMFs do not have enough energy to damage the DNA. Lack of biological plausibility is a barrier to accept the evidence of carcinogenicity in human studies and to take measures to protect pregnant women and children from ELF-EMFs. Recent evidence indicates that non-mutagenic agents can cause DNA alterations and increase the risk of cancer by promoting the accumulation of cell divisions in stem cells. Cell division generates DNA alterations (e.g., mutations arising during DNA replication), which occur even in the absence of DNA-damaging agents. Importantly, ELF-EMFs can trigger the division of stem cells; this effect is under development in the field of regenerative medicine. A possible mechanism by which ELF-EMFs induce the malignant transformation of hematopoietic stem cells is discussed.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.

In recent times, the increasing concern for climate control has led to the widespread application of grid-connected inverter (GIC) based renewable energy systems. In addition, the increased usage of non-linear loads and electrification of the transport sector cause ineffective grid-frequency management and the introduction of harmonics. These grid conditions affect power quality and result in uncertainty and inaccuracy in monitoring and measurement. Incorrect measurement leads to overbilling/underbilling, ineffective demand and supply forecasts for the power system, and inefficient performance analysis. To address the outlined problem, a novel three-phase frequency component extraction and power measurement method based on Digital Lock-in Amplifier (DLIA) and Digital Lock-in Amplifier Frequency-Locked Loop (DLIA-FLL) is proposed to provide accurate measurement under the conditions of harmonics and frequency offset. A combined filter with a lowpass filter and notch filter for DLIA is employed to improve computation speed. A comparative study is performed to validate the performance of the proposed power measurement method, by comparing the proposed method to the windowed interpolated fast Fourier transform (WIFFT). The ZERA COM 3003 (a commercial high-accuracy power measurement instrument) is used as the reference instrument in the experiment

Keywords: Energy harvesting, Hybrid, Medical Wearable Sensor Nodes, Health Monitoring, Power Management

In the Internet of Things (IoT) era, Mobile Edge Computing (MEC) significantly enhances the efficiency of smart devices but is limited by battery life issues. Wireless Power Transfer (WPT) addresses this issue by providing a stable energy supply. However, effectively managing overall energy consumption remains a critical and under-addressed aspect for ensuring the network’s sustainable operation and growth. In this paper, we consider a WPT-MEC network wit user cooperation to migrate the double near-far effect for the mobile node (MD) far from the base station. We formulate the problem of maximizing long-term computation rates under a power consumption constraint as a multi-stage stochastic optimization (MSSO) problem. This approach is tailored for a sustainable WPT-MEC network, considering the dynamic and varying MEC network environment, including randomness in task arrivals and fluctuating channels. We introduce a virtual queue to transform the time-average energy constraint into a queue stability problem. Using the Lyapunov optimization technique, we decouple the stochastic optimization problem into a deterministic problem for each time slot, which can be further transformed into a convex problem and solved efficiently. Our proposed algorithm works efficiently online without requiring further system information. Rigorous mathematical analysis shows that our algorithm achieves O(1/V),O(V) trade-off between computation rate and queues stability. Extensive simulation results demonstrate that our proposed algorithm outperforms baseline schemes, achieving approximately 4% enhancement while maintain the queues stability.

This paper deals with the design, simulation and implementation of shunt hybrid compensator to maintain the power quality in 3-phase distribution networks feeding different types balanced and unbalanced nonlinear loads. The configuration of the compensator consists of a selective harmonic elimination passive filter, a series connected conventional 6-pulse IGBT inverter, acting as the active filter terminated with a dc link capacitor. The theory and modelling of the compensator based on current harmonic components at the load end and their decomposition in d-q axis frame of reference are utilized in the reference current generation algorithm. Accordingly, the source current waveform is made to follow the reference current waveform using a high frequency carrier based controller. Further, this inner current control loop is supported by a slower outer voltage control loop for sustaining desirable dc link voltage. Performance of the compensator is evaluated through MATLAB simulation covering different types of loads and reduction of harmonic currents and THD at the supply side along with excellent regulation of dc link voltage are confirmed. The performance of a hybrid compensator designed and fabricated using the above principles is evaluated and corroborated with the simulation results.

While microcredits are, by the development practitioners, repeatedly hailed as a useful measure of development policy, this empirical research in Bangladesh arrives at different results: the governing and disciplinary measures are necessary to trigger the best possible repayment success. Based on interviews with the microfinance beneficiaries, loan officers, and microfinance experts in Bangladesh, I chart some of the most frequently used governing and disciplinary techniques including fictitious proximity of loan officers, their fields of visibility and surveillance processes. The “success” of credit delivery is a neoliberal stance that ensures the ceaseless debt repayment process using the intentional and planned conduct, capitalizing social capital and credit honour reputation, surveillance over business enterprises, use of equivocal language and different forms of deception. The development strategy through microfinance in Bangladesh is a development “dispositif” with a changing shift in its declared social missions.

Mobile Edge Computing (MEC) integrated with Wireless Power Transfer (WPT) is emerging as a promising solution to reduce task delays and extend the battery life of Mobile Devices (MDs). Cooperative user communication, or relay technology, enhances communication efficiency for users located far from the base station by mitigating the double near-far effect caused by distance. This is considered a key technology in Beyond 5G (B5G) and future communication systems. In this paper, we focus on maximizing the long-term energy efficiency (EE) of a user-cooperation WPT-MEC system, while taking into account the uncertain load dynamics at the edge MD and the time-varying state of the wireless channel. The joint optimization of wireless charging time fraction, MD offloading duration, helper node processing time, and transfer power decision presents significant challenges due to the coupling of data offloading among cooperative users and a volatile system environment. To address these challenges, we formulate the problem as a stochastic programming problem and propose an online control algorithm, DOUCA, to solve it. Our approach utilizes Dinkelbach’s method and Lyapunov optimization theory to decouple the sequential decision problem into a deterministic sub-problem for each time slot. For the sub-problem, we use variable substitution to convert the non-convex problem into a convex one, containing only a small number of variables, which can be efficiently solved. Furthermore, we provide a mathematical analysis of our algorithm’s performance. Extensive simulation results demonstrate the effectiveness of our proposed algorithm, as evidenced by an impressive energy efficiency improvement of over 20% compared to benchmark methods. Our algorithm also achieves a trade-off between EE and system stability.

This paper presents a new optimization algorithm to control the voltage of power system generators by the simultaneous tuning of the parameters of Automatic Voltage Regulator (AVR) and Power System Stabilizer (PSS) using a new technique called Particle Swarm Optimization with Periodic Oscillating Exponential Decay (PSO - POED). The proposed algorithm was applied to both the Single-Machine Infinite-Bus (SMIB) Power System and the 9-Bus Multi-Machine Power System. The results of the simulation show that the proposed method is efficient and guarantees an improvement in the dynamic stability and convergence rate of the simulations.

This article presents a new input device for spastic patients and others with similar symptoms. The sensor consists of a disc used to determine positions and can replace standard joysticks in medical devices such as electric-powered wheelchairs. Using a standard joystick while operating a powered wheelchair can result in dangerous situations when spastic movements occur and extremities cramp making them uncontrollable. To avoid this, a disc was developed that can be controlled with any body part. By shifting weight (x- and y-axis) the disc can tilt in any direction creating a proportional output signal and can also be pushed down in the center (z-axis) to open a menu on a screen for example. When spasms occur it is impossible for users to get stuck on the input device because the disc is flat and can be mounted within a control panel. Body parts coming into contact with the disc would merely slide across the disc without triggering unintentional actions. The sensor presented here is also adaptive and can be adjusted to fit a user’s strength and range of motion. This proposal aims to develop an input device that enables spastic patients to operate sensitive systems safely.

In this paper, a small wind power generator is proposed with a new straight shape stator and rotor. The advantages of the proposed structure are introduced through a comparison between the basic and the proposed models. By comparing the pole slot combination of the proposed generator, the combination with optimal cogging torque characteristics was selected. The electromagnetic characteristics of proposed shape are analyzed for design variables using a finite element analysis (FEA) of ANSYS Maxwell. The final model of the proposed structure is designed by considering cogging torque and the generator electromagnetic characteristics. The electromagnetic and structural simulations of the final model are performed to satisfy the required performance of generator and mechanical safety. To verify the FEA results of the final model, a prototype is manufactured, experimented, and compared with the FEA results.

The study investigates the influence of power dynamics on supply chain decision-making processes through a qualitative lens, aiming to understand how various forms of power impact interactions, relationships, and strategic outcomes within supply chains. Using semi-structured interviews with supply chain managers and executives from diverse industries, the research explores the multifaceted nature of power, identifying key sources such as economic leverage, expertise, resource control, and network centrality. Findings reveal that power dynamics significantly shape decision-making by determining negotiation outcomes, governance structures, and operational efficiencies. Economic power, often exercised by larger firms, enables them to dominate negotiations and impose favorable terms, creating pressures on smaller partners and potentially leading to conflicts. Expertise and resource control allow firms with specialized knowledge or unique inputs to influence product development and process innovation, further dictating supply chain configurations. The study differentiates between coercive and non-coercive power strategies, showing that while coercive power enforces compliance, it can erode trust and collaboration. Non-coercive power, on the other hand, promotes positive relationships through incentives and collaborative approaches, fostering trust and alignment of supply chain objectives. Governance structures imposed by dominant firms often reflect their strategic priorities but can burden less powerful partners, highlighting the need for balanced oversight. Power also plays a crucial role in risk management, resilience, sustainability, and innovation within supply chains, with digitalization introducing new dimensions of influence. The research underscores the importance of balanced and equitable power dynamics to enhance cooperation, resilience, and innovation in supply chains. These insights provide valuable implications for practitioners and scholars in developing more effective and adaptive supply chain strategies.

The steady rheological behavior of suspensions of solid particles thickened by cellulose nanocrystals is investigated. Two different types and sizes of particles are used in the preparation of suspensions, namely TG hollow spheres of Sauter mean diameter of 69 µm and Solospheres S-32 of Sauter mean diameter of 14 µm. The nanocrystal concentration varies from 0 to 3.5 wt% and the particle concentration varies from 0 to 57.2 vol%. The influence of salt (NaCl) concentration and pH on the rheology of suspensions is also investigated. The suspensions generally exhibit shear-thinning behavior. The degree of shear-thinning is stronger in suspensions of smaller size particles. The experimental viscosity data are adequately described by a power-law model. The variations of power-law parameters (consistency index and flow behavior index) under different conditions are determined and discussed in detail.

Information theoretic quantities such as entropy, entropy rate, information gain, and relative entropy are often used to understand the performance of intelligent agents in learning applications. Mean squared error has not played a role in these analyses, primarily because it is not felt to be a viable performance indicator in these scenarios. We build on a new quantity, the log ratio of entropy powers, to establish that minimum mean squared error (MMSE) estimation, prediction, and smoothing are directly connected to Mutual Information Gain or Loss in an agent learning system modeled by a Markov chain for many probability distributions of interest. Expressions for mutual information gain or loss are developed for MMSE estimation, prediction, and smoothing and an example for fixed lag smoothing is presented.

As the adoption of renewable energy sources grows, ensuring a stable power balance across various time frames has become a central challenge for modern power systems. In line with the "dual carbon" objectives and the seamless integration of renewable energy sources, harnessing the advantages of various energy storage resources and coordinating the operation of long-term and short-term storage have become pivotal directions for future energy storage deployment. To address the complexities arising from the coupling of different time scales in optimizing energy storage capacity, this paper proposes a method for energy storage planning that accounts for power imbalance risks across multiple time scales. Initially, the Seasonal and Trend decomposition using the Loess (STL) decomposition method is utilized to temporally decouple actual operational data. Subsequently, power balance computations are performed based on the obtained data at various time scales to optimize the allocation of different types of energy storage capacities and assess the associated imbalance risks. Finally, the effectiveness of the proposed approach is validated through hourly applications using real-world data from a province in China over recent years.

This paper investigates an innovative photovoltaic cell configuration, denoted as “Au/CuSCN/RbGeI3/CdTe/ZnO/TiO2/FTO", using SCAPS-1D simulation. The research focuses on optimizing device performance by analyzing key components, including ZnO as the electron transport layer (ETL), RbGeI3 as the perovskite absorber layer, CuSCN as the hole transport layer (HTL), and CdTe as the active buffer layer. A comparison is made with the standard “Au/CuSCN/CH3NH3SnI3/CdTe/ZnO/TiO2/FTO" configuration under dark and illuminated conditions. Through an in-depth investigation involving temperature effects, generation rate analysis, RbGeI3 absorber layer thickness, Nd level, and interface defect levels, an optimized design for a unit area is achieved. The proposed solar cell demonstrates outstanding performance metrics, including an open circuit voltage (Voc) of 0.94V, a short circuit current density (Jsc) of 34.52mA/cm2, a fill factor (FF) of 77.77%, and an energy conversion efficiency (η) of 25.40%. These values significantly outperform the reference models with energy conversion efficiencies of 10.11% and 21.09%. Real-world applicability is validated by implementing these optimized characteristics in a photovoltaic system for Pakistan’s geographical location using PVSyst software. The suggested solar cell achieves a remarkable performance ratio (PR) of 85.6%, surpassing the PR of the reference basic solar cell model at 83%. The findings of this research offer a promising and superior solar cell design, incorporating innovative materials and optimization techniques to achieve exceptional energy conversion efficiency and overall performance. This study’s outcomes have the potential to advance photovoltaic technology and contribute to sustainable energy solutions worldwide.

The wide circulation of conspiracy narratives and their frequent intertwining with populist rhetoric is both an element of concern and a topic of intense scientific and philosophical debate. The depth of the link between conspiracy theories and populism represents a crucial issue whose comprehension can facilitate understanding their specific nature and the factors behind their diffusion in public communication. To this end, it is necessary to cultivate an interdisciplinary approach and great critical attention, eschewing monocausal explanations. This paper addresses the question of the essentially political nature of conspiracism confronting the recent epistemological debate that, by putting the positivist paradigm aside, has sought to explore and understand the socio-cultural roots of conspiracy rhetoric, with its sceptical, antagonistic and hermetic traits. By integrating the reflections of epistemologists such as Cassam or Harris with the considerations of political scientists such as Taggart and with Schmitt's radical reflections on politics, it is perhaps possible to reintegrate the different approaches to populist conspiracism into an overall social genealogical perspective, thanks also to recent demographic elaborations. Thus, we could ascribe the spread of conspiracism to the prevalence in societies of a hyper-political discursive regime, i.e. founded on the principle of opposition, without the possibility of compromise, between different groups and interests. At the basis of such Manichaeism, it is plausible to place in the first place the growing inequalities and related social disintegration, which hinder the circulation of trust and recognition between individuals and groups, thus ending up undermining democracy at its roots, as a political system that legitimises and thus peacefully regulates conflict.

The methods of Artificial Intelligence (AI) have been used in the planning and operation of power systems for more than 40 years. In recent years, due to the development of microprocessor and data storage technologies, the effectiveness of this use has greatly increased. This paper provides a systematic overview of the application of AI including the use of Machine Learning (ML) to the power system. The potential application areas are divided into four blocks and the classification matrix has been used for clustering the AI application tasks. Furthermore, the data acquisition methods for setting the parameters of AI and ML algorithms are presented and discussed in a systematic way considering the supervised and unsupervised learning methods. Based on this, three complex application examples: wind power generation forecasting, smart grid security as-sessment (using two methods), and automatic system fault detection are presented and discussed in detail. Summary and outlook conclude the paper.

This article delves into the enduring relevance of Liberal International Relations (IR) Theory amidst persistent criticisms regarding power dynamics and its applicability in emerging states. Despite its detractors, Liberal IR Theory offers a nuanced understanding of state behavior, blending social contexts with power dynamics. It recognizes the intricacies of economic interdependence and advocates for a balanced approach in advancing democracy and human rights. While nationalism poses challenges to international institutions, their adaptability endures. Leaders, albeit constrained, retain the capacity to foster peace through visionary leadership and global cooperation. By acknowledging its limitations and fostering open dialogue, Liberal IR Theory continues to evolve, poised to contribute to a just and peaceful global order.

The basic equation for estimating the aerodynamic power captured by an Anderson Vertical Axis Wind Turbine (AVAWT) is a solution of the Navier-Stokes(N-S) equations for a baroclinic, inviscid flow. In a nutshell, the pressure difference across the AVAWT is derived from Bernoulli’s equation; an upshot of the integration of the N-S momentum equation for a baroclinic inviscid flow, Euler’s momentum equation. The resulting expression for the pressure difference across the AVAWT rotor is plotted as a function of freestream speed. Experimentally determined airstream speeds at the AVAWT inlet and outlet, coupled with corresponding freestream speeds are used in estimating the aerodynamic power captured. The aerodynamic power is subsequently used in calculating the aerodynamic power coefficient of the AVAWT. The actual power coefficient is calculated from the power generated by the AVAWT at various free stream speeds and plotted as a function of the latter. Experimental results show that, at all free stream speeds and tip speed ratios, the aerodynamic power coefficient is higher than the actual power coefficient of the AVAWT. Consequently, the power generated by the AVAWT prototype is lower than the aerodynamic power captured, given the same inflow wind condition.

In recent years, there has been an increasing interest in adopting novel sensing technologies for the continuous monitoring of structural systems. In this respect, Micro-Electro-Mechanical System (MEMS) sensors are widely used in several applications, including Structural Health Monitoring (SHM). Thanks to their significantly lower cost, ease of installation on the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through the network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analysis show that MEMS can correctly detect modal frequencies, useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

In this paper we consider type II bivariate generalized power series Poisson distribution as a compound Poisson distribution with bivariate generalized power series compounding distribution. We obtain some properties, p.m.f. and conditional distributions. In addition we also give a brief discussion about the multivariate extension of this case. Then we introduce type II bivariate generalized power series Poisson process and consider a bivariate risk model with type II bivariate generalized power series Poisson model as the counting process. For this model we derive distribution of the time to ruin and bounds for the probability of ruin. We obtain partial integro-differential equation for the ruin probabilities and express its bivariate transform through two univariate boundary transforms,where one of the initial capitals is fixed at zero.

This research paper examines a cosmological model in flat space-time via $f(R,G)$ gravity where $R$ and $G$ are respectively the Ricci scalar and Gauss-Bonnet invariant. Our model assumes that $f(R,G)$ is an exponential function of $G$ combined with a linear combination of $R$. We scrutinize the observational limitations under a power law cosmology that relies on two parameters - $H_0$, the Hubble constant, and $q$, the deceleration parameter, utilizing the 57-point $H(z)$ data, 8-point BAO data, 1048-point Pantheon data, joint data of $H(z)$ + Pantheon, and joint data of $H(z)$ + BAO + Pantheon. The outcomes for $H_0$ and $q$ are realistic within observational ranges. We have also addressed Energy Conditions, $Om(z)$ analysis and cosmographical parameters like Jerk, Lerk and Snap. Our estimate of $H_0$ is remarkably consistent with various recent Planck Collaboration studies that utilize the $\Lambda$CDM model. According to our study, the power law cosmology within the context of $f(R,G)$ gravity provides the most comprehensive explanation for the important aspects of cosmic evolution.

In this paper, a continuous power management for a decentralized DC microgrid (DCMG) is proposed to achieve voltage regulation and power balance even under system uncertainty and voltage sensor failure. The DCMG system achieves a continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under voltage sensor failure, a DC bus voltage (DCV) sensor fault detection algorithm is proposed. In this algorithm, the DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. When the power agent identifies the DCV sensor failure, it changes the operation properly according to the proposed control mode decision algorithm to maintain the stability of the DCMG system. When uncertain conditions such as the power variation of the distributed generations, sudden grid disconnection, DCV sensor failure, electricity price change, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. Simulation and experimental results under different test conditions confirm the reliability and effectiveness of the proposed control scheme.

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model integrates advanced methodologies including Improved Intrinsic Mode Function with Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Permutation Entropy(PE), Least Squares Support Vector Regression (LSSVR), Regularized Extreme Learning Machine(RELM), Multi-head Attention (MHA), and Bidirectional Gated Recurrent Unit (BiGRU). Firstly, the ICEEMDAN technique is employed to decompose the non-stationary raw wind power data into multiple relatively stable sub-modes, while concurrently utilizing PE to assess the complexity of each sub-mode. Secondly, the dataset is reconstituted into three distinct components: high-frequency, mid-frequency, and low-frequency, to alleviate data complexity. Following this, the LSSVR, RELM, and MHA-BiGRU models are individually applied to predict the high, mid,and low-frequency components, respectively. Thirdly, the parameters of the low-frequency prediction model are optimized utilizing the Dung Betele Optimizer(DBO) algorithm. Ultimately, the predicted results of each component are aggregated to derive the final prediction. Empirical findings illustrate the exceptional predictive performance of the multiscale hybrid model incorporating LSSVR, RELM,and MHA-BiGRU. In comparison to other benchmark models, the proposed model exhibits a reduction in Root Mean Square Error(RMSE) values of over 10%, conclusively affirming its superior predictive accuracy.

The solar energy can mitigate the power supply shortage in remote regions for portable irrigation systems. The accurate prediction of solar irradiance is crucial for determining the quantity of solar panels and the power capacity of photovoltaic power generation (PVPG) systems for mobile sprinkler machines. In this study, a prediction method is proposed to forecast the solar irradiance of typical irrigation areas. The impact of the meteorological parameters on the solar irradiance is studied, and four different parameter combinations are formed and considered as input to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict the solar radiation. The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. The differences between the prediction performances of models trained based on single-station data and mixed data from multiple stations are also compared. The obtained results show that the proposed model achieves the highest prediction accuracy when the maximum temperature, minimum temperature, sunshine hours ratio, relative humidity, wind speed, and extraterrestrial radiation are used as the input parameters. The prediction effectiveness is also verified based on measured data. The WOA-XGBoost model has higher prediction accuracy than the XGBoost model, with predicted values falling within acceptable ranges. The model developed using mixed data of multiple stations can be applied for forecasting solar irradiance in different regions. This study provides a foundation for the optimization of the configuration of PVPG systems for mobile sprinkler machines.

On 2013 the Villonaco wind farm (16.5 MW), the first wind farm in continental Ecuador near the city of Loja, began operations. The power generated is delivered to the National Interconnected System (SNI), which services the city. This research confronts two sets of real data, the electricity use of the urban area of Loja, and the power generated by the Villonaco Wind Farm. Electricity use follows clearly defined daily and weekly cycles, and wind power has a seasonal behaviour. The study shows that wind power integration cannot be a long-term stable power source regardless power or generation surplus. Another essential finding is that time series can be used as a statistical source to determine the need for short- (seconds) and long- (days, weeks) term energy storage. Strategies to further the energy autonomy of the urban area through the expansion of the wind farm by a factor of 2 are discussed.

One of the challenges posed by renewable energies is the stabilization of parameters related to the quality of electrical energy. This study demonstrates the existence of a relationship between input blocks of hydropower and the variation of the fundamental frequency of the electricity grid. By mapping production data provided by Spanish Electric Network with frequency measured in the laboratory, it is shown that gradients of hydropower are correlated with frequency fluctuations for certain characteristic times. Considering hourly instances of energy input, the study compares two methods for calculating hydropower gradients (linear regression and pseudo-linear regression); and two methods for calculating local frequency extremes (the "specular inertia" method and analysis by comparison with the moving average), in order to corroborate the results.

In this study, we examined the effects of the organizational power resources used by school principals on teachers' work alienation and trait anxiety levels. Then, we examined the mediating role of trait anxiety in the relationship between organizational power resources and work alienation. We used the correlational scanning model and mediation model in the research. The research sample consists of 400 teachers working in Turkish public schools. In our research, "Organizational Power Scale in Schools", "Work Alienation Scale" and "Trait Anxiety Scale" were used. As a result of the research, we found significant relationships between the variables. Accordingly, there is a positive relationship between trait anxiety and work alienation, a positive relationship between trait anxiety and coercive power and legal power, a negative relationship between trait anxiety and expert, charismatic and reward power, a positive relationship between work alienation and coercive power, and a positive relationship between work alienation and reward power. Negative relationships were observed between expertise and charismatic power. Finally, it was determined that trait anxiety had a mediating role in the relationship between the power resources used by school principals and the level of work alienation of teachers.

Cloud data centers play a vital role in modern computing infrastructure, offering scalable resources for diverse applications. However, managing costs and resources efficiently in these centers has become a crucial concern due to the exponential growth of cloud computing. User applications exhibit complex behavior, leading to fluctuations in system performance and increased power usage. To tackle these obstacles, we propose the consolidation of virtual machines (VMs) to optimize resource utilization and reduce operational costs. This paper introduces a novel algorithm, leveraging the Modified Artificial Feeding Birds Algorithm (ModAFBA), to manage cost optimally in cloud data centers by reducing power usage while meeting service level agreements (SLAs). The ModAFBA algorithm, inspired by bird foraging behavior, dynamically adjusts solutions based on environmental changes. Comprehensive experimental evaluation demonstrates the superiority of the proposed algorithm in terms of power usage, migration count, and SLA compliance. Through this research, we aim to advance cost management and resource optimization in cloud data centers, providing a valuable tool for cloud service providers to enhance infrastructure efficiency and achieve cost savings.

This article introduces new method using ANN to control SVC in order to correct the source power factor of low voltage network. Two ANN approaches are investigated to design accurate and fast power factor correction (PFC) controller. First approach uses simple ANN (SANNA). Second approach uses cascaded ANN (CANNA). ANN regression, performance and the calculated error for both approaches are investigated to select between the two approaches. CANNA is selected as a better solution and it used to build the ANN PFFC controller using database, generated by MATLAB-Simulink, for standard three low voltage levels (240V, 220V and 110V). Nine test cases are carried out to validate the performance of proposed ANN PFC controller with a network has variable loads and low power factor (0.6 approximately). In order to extend the use of the controller to other voltage levels not included in the training process of the cascaded ANN, only the SVC is resized. Another nine cases are carried out with the same loads using the same ANN controller, as it is, to test its performance with the extended voltage level range (415V, 230V and 120V). The results show accurate and fast response in all test cases.

In the context of the Korean building structure standard KDS2022, wind loads can be readily calculated in terms of the along-wind, across-wind, and torsional components, based on a single wind direction. However, this approach falls short in accurately and safely evaluating the impact of winds from various directions. Therefore, in this study, we developed a Wind Load Calculation Program (WCP) capable of predicting wind loads with relative precision during the preliminary design phase. First, wind tunnel tests were conducted to identify the essential factors necessary for calculating wind loads and the variables influencing these factors. The building shape considered was a square, and the wind force coefficients and power spectral density were measured by combining 4 ground roughness values, 11 side ratios (), 4 aspect ratios (), and wind directions ranging from 0° to 90°. Subsequently, a generalized formulation was devised to facilitate wind load calculations across diverse conditions and a method for calculating load combination coefficients, considering response correlation and load simultaneity, was presented. Finally, the wind loads obtained from the wind tunnel tests were compared with those predicted by the WCP using an actual project model.

In this paper, a novel permanent magnet-assisted synchronous reluctance machine (PMASynRM) with rare-earth PMs and ferrite magnets is proposed. The performance of PMASynRM is discussed with respected to the different magnet ratio of rare-earth PMs and ferrite magnets. Some characteristics including the flux density, output torque, cogging torque, output power, power factor, torque ripple, loss, efficiency, and demagnetization are calculated by 2-D finite element analysis (FEA). The analysis results show that the excellent performance can be obtained by using hybrid magnet of rare-earth PMs and ferrite magnets with the suitable magnet ratio, and provide some desirable cost-performance trade-off.

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to prevent malfunctions and faults in electric assets and in connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic, the supraharmonic 2kHz–150kHz range. This range is not populated by the harmonic components of the 50-60 Hz mains fundamental, but a combination of intentional emissions, switching and non-linearity by-products and various types of resonances. This paper aims to provide a detailed analysis of the impact of SH on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference to equipment and to power line communication (PLC) technology in particular. Under some shareable assumptions limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with specific focus on their accuracy.

We propose a new methodology for long-time biopotential recording based on MEMS multisensor integrated platform featuring a commercial electrostatic charge transfer sensor. That family of sensors was originally intended for presence tracking in automotive, so the existing setup has been engineered for the acquisition of electrocardiogram, electroencephalogram, electrooculogram and electromyography, designing a dedicated front-end and writing a proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in domestic environment will be discussed in detail. The excellent results candidate this technology to provide a low power, unexplored solution to biopotentials acquisition. The technology breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, they open to additional possibilities for wearable sensing and strengthen the role of MEMS technology in medical wearable applications for long time synchronous acquisition of a wide range of signals.

This research review explores the synthesis of graphene quantum dots (GQDs) from biowaste for supercapacitor applications, driven by the need for sustainable and efficient energy storage technologies. GQDs, with their unique properties like high surface area and excellent conductivity, hold promise for enhancing supercapacitor performance. Various synthesis methods, including hydrothermal/solvothermal processes, chemical exfoliation, carbonization/pyrolysis, and microwave-assisted synthesis, are discussed alongside characterization techniques to evaluate GQD properties. Biowaste-derived GQDs demonstrate significant potential by improving specific capacitance and cycling stability in supercapacitor electrodes. Challenges such as scalability and material purity are identified, with future directions focusing on enhancing energy density, cycle life, and cost-effectiveness to propel the adoption of biowaste-derived GQDs in commercial energy storage applications.

This research investigates the alignment of soft power and institutional skills in Montenegro's journey towards accession to the European Union (EU), with a particular focus on the environmental sector. An online survey targeting individuals employed in state institutions directly engaged in negotiation processes, notably the Ministry of Sustainable Development and Tourism and the Agency for Nature and Environmental Protection, was conducted. The research conducted an online survey, distributed before and after the summer recess to accommodate the transition of power following parliamentary elections, aimed at assessing the effectiveness of current personnel and identifying areas for improvement in staffing and negotiation strategies within Montenegro's environmental sector. Employing diverse methodologies, the survey's analysis delved into the demographic, social, and professional backgrounds of respondents. It explored their roles within institutions, involvement in environmental negotiations, and possession of relevant skills and expertise. Furthermore, respondents' knowledge of environmental issues, legislation, and challenges facing the country was assessed to gauge institutional capacity for environmental governance. Demographic data, including gender, age, education and regional origin, were collected to understand gender-specific attitudes and regional disparities in environmental perspectives. The sample of 84 individuals, comprising executives and employees from both institutions, provided insights into the age structure and regional diversity of personnel involved in negotiation tasks for Chapter 27. The selection of the Ministry of Sustainable Development and Tourism and the Agency for Nature and Environmental Protection reflects their pivotal roles in shaping Montenegro's environmental policies and addressing climate change challenges. This study aims to illuminate the dynamics of environmental governance within Montenegro's state administration, contributing to the country's path towards EU accession. The research findings highlight the critical need for Montenegro to prioritize strategic initiatives in personnel management, skill development, and institutional capacity-building within its environmental sector. The implications of this research extend beyond academia to inform policymaking and societal action, emphasizing the urgency for Montenegro to bolster its environmental sector capabilities, fostering both EU alignment and sustainable governance practices for the benefit of present and future generations.

Risk-based redispatch optimization is proposed as a methodology to support the Transmission System Operator (TSO) with preventive remedial actions obtained by extending the security constrained unit commitment/economic dispatch with constraints resulting from the risk assessed for the power system. Although being heuristic, the methodology is based on comprehensive dynamic security assessment as time-domain simulations are used, allowing to express the degree of all types of instabilities, e.g., caused by contingencies, in monetary terms. Therefore, the risk is assessed as the expected value of the cost incurred by the TSO. Such approach forms a new pathway to including risk in planning procedures already used by TSOs. Results obtained for the IEEE39 dynamic power system, with costs assigned to load shedding and generator tripping due to single transmission lines short-circuits, are shown as a reference case.

Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5^th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.

The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate for a long duration without the presence of a consistent power source. In this paper, we develop a batteryless, ultra-low-power Wireless Sensor Transmission Unit (WSTx) depending on the solar-energy harvester and LoRa technology. We investigate the feasibility of harvesting ambient indoor light using polycrystalline photovoltaic (PV) cells with a maximum power of 1.4mW. The study provides comprehensive power management design details and a description of the anticipated challenges. The power consumption of the developed WSTx was 21.09µW during the sleep mode and 11.1mW during the operation mode. The harvesting system can harvest energy up to 1.2mW per second, where the harvested energy can power the WSTx for six hours with a maximum power efficiency of 85.714%.

This study evaluates the viability of n-octanol as an alternative fuel in a direct-injection diesel engine, aiming to enhance sustainability and efficiency. Experiments employed varying blends of n-octanol (10%, 30%, and 50% by volume) with pure diesel, analyzing impacts on engine performance and emissions. The methodology involved testing each blend in a single-cylinder engine, measuring engine performance parameters such as brake torque and brake power under full load conditions across an engine speed range from 1400 to 2500 rpm. Comparative assessments of performance and emission characteristics at a constant engine speed of 1700 rpm were also conducted with varying loads. Results indicated that while n-octanol blends consistently improved brake thermal efficiency, they also increased brake specific fuel consumption due to the lower energy content of n-octanol. Consequently, while all n-octanol blends reduced nitrogen oxides (NOx) emissions compared to pure diesel, they also significantly decreased carbon monoxide, hydrocarbons, and smoke opacity, presenting a comprehensive reduction in harmful emissions. However, the benefits came with nuanced trade-offs: notably, higher concentrations of n-octanol (especially the 50% blend) led to a relative increase in NOx emissions as the octanol ratio increased. The study concludes that n-octanol significantly improves engine efficiency and reduces diesel dependence, but optimizing the blend ratio is crucial to balance performance improvements with comprehensive emission reductions.

Backscatter communication, which transmits information by passively reflecting radio 1 frequency (RF) signals, has become a focal point of interest due to its potential to significantly enhance 2 the energy efficiency of Wireless Power Mobile Edge Computing (WPMEC) networks and extend the 3 operational lifespan of terminal devices. However, there is little research on the integration of user 4 cooperation in WPMEC scenarios within volatile network environments. In this paper, we propose 5 a dynamic task offloading scheme for a Backscatter-assisted WPMEC system, which involves two 6 mobile devices (MDs) and a Hybrid Access Point (HAP) with user cooperation. We formulate the 7 energy efficiency (EE) maximization problem as a stochastic programming problem, considering 8 the randomness of task arrivals and time-varying wireless channels. By leveraging Dinkelbach’s 9 method and stochastic network optimization technique, we transform the problem into a series of 10 deterministic sub-problems for each time slot, and convert the non-convex sub-problem into convex 11 ones. We propose a low-complex EE maximization algorithm to solve the convex problems efficiently. 12 Extensive simulations are conducted to validate the performance of our algorithm under various 13 system parameter settings. Experiment results demonstrate that our algorithm not only outperforms 14 the benchmark algorithms by approximately 23%, but also stabilize all queues within the MEC 15 system.

This paper presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g. a laser diode is affixed to a movable axis and projects a random geometric shape on an image sensor (CMOS or CCD). The software in the downstream microcontroller identifies the geometric shape’s center, distortion and size, then calculates X, Y, and Z coordinates. These coordinates can then be processed in attached devices. The 3-axis sensor is characterized by its very high resolution, precise reproducibility and plausibility of the coordinates produced. In addition, optical processing of the signal provides a high level of safety against electromagnetic and radio frequency interference. The sensor presented here is adaptive and can be adjusted to fit a user’s range of motion (stroke and force). This recommendation aims to optimize sensor systems such as joysticks in medical devices in terms of safety, ease of use, and adaptability.

We investigate a singularly perturbed q-difference differential Cauchy problem with polynomial coefficients in complex time and space with quadratic nonlinearity. We construct local holomorphic solutions on sectors in the complex plane with respect to the perturbation parameter with values in some Banach space of formal power series in space with analytic coefficients on shrinking domains in time. Two aspects of these solutions are addressed. One feature concerns asymptotic expansions in the parameter for which a Gevrey type structure is unveiled. The other fact deals with confluence properties as q tends to 1. In particular the built up Banach valued solutions are shown to merge in norm to a fully bounded holomorphic map in all its arguments that solves a nonlinear partial differential Cauchy problem.