Deterministic simulations using the SWAN model were conducted along a stretch of the Tietê-Paraná waterway in the Ilha Solteira dam reservoir, São Paulo, Brazil, to assess the water waves generated by winds. Simultaneously employs a probabilistic metamodeling approach (PCE) and Sobol indices, to quantify uncertainty of the five involved physical parameters (wind velocity and direction, bottom friction (JONSWAP), whitecapping and depth-induced breaking index). In the deterministic part, Janssen’s formulation yielded the most successful and accurate estimations of wave heights. Probabilistic analysis underscored the importance of wind data and the whitecapping parameter in model calibration, with a significant influence of wind speed indicated by Sobol indices. The results not only refined the model calibration process, but also allowed the creation of contour maps for wave height and period that offer practical pre-project applications. This work advances understanding of wind wave hydrodynamics deterministically and probabilistically, with good concordance and performance indices compared to field data, despite being scarce.

A joint analysis of solar wind, geomagnetic field, and earthquake catalog data showed that before the catastrophic M7.8 and M7.5 Kahramanmaras earthquake sequence on February 6, 2023, the closed strong magnetic storm occurred on November 7, 2022, SYM/H=-117 nT. Storm started at 08:04 UT. At this time, the high latitudinal part of Turkey's longitudinal region of future epicenters was located under the polar cusp, where the solar wind plasma would directly access the Earth's environment. The time delay between storm onset and earthquake occurrence was ~91 days. We analyzed all seven strong (M7+) earthquakes from 1967 to 2020 to verify the initial findings. A similar pattern has been revealed for all events. The time delay between magnetic storm onset and earthquake occurrence varies from some days to some months. To continue these investigations, a retrospective analysis of seismic and other geophysical parameters just after preceded geomagnetic storms in the epicenter areas is desirable.

Estimating parameters for multiple datasets can be time consuming, especially when the number of datasets is large. One solution is to sample from multiple datasets simultaneously using Bayesian methods such as adaptive multiple importance sampling (AMIS). Here we use the AMIS approach to fit a von Misses distribution to multiple datasets for wind trajectories derived from a Lagrangian Particle Dispersion Model driven from a 3D meteorological data. The primary objective is to characterise the uncertainties in wind trajectories in a form that can be used as inputs for predictive models of wind-dispersed insect pests and pathogens of agricultural crops for use in evaluating risk and in planning mitigation actions. Our results show that AMIS can significantly improve the efficiency of parameter inference for multiple datasets.

This study uses a wind turbine case study to showcase an architecture for implementing a distributed digital twin in which all important aspects of a predictive maintenance solution in a DT use a fog computing paradigm, and the typical predictive maintenance DT is improved to offer better asset utilization and management through real time condition monitoring, predictive analytics, and health management of selected components of Wind turbines in a wind farm.. Digital twin (DT) is a technology that sits at the intersection of Internet of Things, Cloud Computing and Software Engineering to provide a suitable tool for replicating physical objects in the digital space. This can facilitate the implementation of asset management in manufacturing systems through predictive maintenance solutions leveraged by Machine Learning (ML). With DTs, a solution architecture can easily use data and software to implement asset management solutions such as Condition Monitoring and Predictive Maintenance using acquired sensor data from physical objects and computing capabilities in the digital space. While DT offers a good solution, it is an emerging technology that could be improved with better standards, architectural framework, and implementation methodologies. Researchers in both academia and industry have showcased DT implementations with different levels of success. However, DTs remain limited in standards and architectures that offer efficient predictive maintenance solutions with real time sensor data, and intelligent DT capabilities. An appropriate feedback mechanism is also needed to improve asset management operations.

To address global warming, there is a worldwide effort to establish carbon-neutral energy plans. Given the characteristics of renewable energy generation, a diverse 'Energy Mix' consisting of various energy sources such as wind and solar power is crucial. In particular, the wind power is expected to continue expanding globally due to its sustainable nature. Furthermore, the expan-sion of offshore wind farm is making essential and a rapidly growing industry sector to be achieving carbon neutrality with limited land for construction. To facilitate the construction and operation of offshore wind farms, specialized vessels with dynamic positioning (DP) systems are essential such as Wind Turbine Installation Vessels (WTIVs) and Service Operating Vessels (SOVs). The purpose of this study is to predict and analyze the scale and structural changes in the fleet capacity of DP vessel, which is essential for offshore wind power construction as the offshore wind power industry develops using System Dynamics (SD) modeling. Specifically, this study aims to construct a demand forecasting model for DP vessel used in offshore wind farm con-struction based on SD methodology. The study aims to identify influencing factors by analyzing dynamic changes in system configurations over time and establishing causal relationships based on feedback structures. Instead of traditional time series analysis methods, causal relation-ship-based simulations were conducted for quantitative analysis. The results provide insights into the changes in the DP vessel market structure due to the emergence of the new industry and highlight areas that require improvement throughout the industry.

This paper provides a review of the aerodynamic behavior of horizontal axis wind turbines operating in hazardous environmental conditions. Over the past decade, renewable energy use has accelerated due to global warming, depleting fossil fuel reserves, and stricter environmental regulations. Among renewable options, solar and wind energy have shown economic viability and global growth. Horizontal axis wind turbines offer promising solutions for sustainable energy demand. Since wind turbines operate in an open environment, their efficiency depends on environmental conditions. Hazard environmental conditions, such as icing, rainfall, hailstorm, dust or sand, insects’ collisions, increased humidity and sea spray, result in degraded aerodynamic performance. The outcome of the most studies is that lift is degraded and at the same time drag is increased when wind turbines operate under these conditions. The objective of this review is to improve our comprehension of the crucial aspects to take into account when designing wind turbine blades, and it offers suggestions for future research paths. It serves as a valuable resource that can inspire researchers who are dedicated to enhancing the aerodynamic performance of horizontal axis wind turbines.

A significant electromotive force is induced in the rotor circuit of a doubly fed induction generator (DFIG) due to its high vulnerability to grid faults. Therefore, the system performance must be increased with appropriate control actions that can successfully offset such abnormalities in order to provide consistent and stable operations during grid disturbances. In this regard, this paper presents a solution based on a combination of an energy storage-based crowbar and a rotor-side crowbar that makes the effective transient current and voltage suppression for wind-driven DFIG possible. The core of the solution is its ability to restrict the transient rotor and stator overcurrents and DC-link overvoltages within their prescribed limits, aiming to protect the DFIG and power converters, and consequently, improve the system’ ability to ride-through faults. Further, the capacity of an energy storage device for transient suppression is estimated. Finally, simulation results show that the proposed approach is effective in achieving transient control objectives precisely and maintaining a stable grid connection during the faults.

This paper investigates the problem of cooperative standoff tracking using multiple fixed-wing unmanned aerial vehicles (UAVs) with control input constraints. In order to achieve accurate target tracking in the presence of unknown background wind and target motion, a coordinated standoff target tracking algorithm is proposed. The objective of the research is to steer multiple UAVs to fly a circular orbit around a moving target with prescribed intervehicle angular spacing. To achieve this goal, two control laws are proposed, including relative range regulation and space phase separation. On one hand, a heading rate control law based on Lyapunov guidance vector field is proposed. The convergence analysis show that the UAVs can asymptotically converge to a desired circular orbit around the target, regardless of their initial position and heading. Through rigorous theoretical proof, it is concluded that the command signal of the proposed heading rate controller will not violate the boundary constraint on heading rate. On the other hand, a temporal phase is introduced to represent the phase separation and avoid discontinuity of the wrapped space phase angle. On this basis, a speed controller is developed to achieve equal phase separation. The proposed airspeed controller met the requirement of airspeed constraint. In addition, to improve the robustness of the aircraft during target tracking, an estimator is developed to estimate the composition velocity of the unknown wind and target motion. The proposed estimator uses the offset vector between the UAV’s actual flight path and the desired orbit which is defined by Lyapunov guidance vector field to estimate the composition velocity. The stability of the estimator is proved. Simulations are conducted under different scenarios to demonstrate the effectiveness of the proposed cooperative standoff target tracking algorithm. The simulation results of indicate that, the temporal-phase-based speed controller can achieve fast convergence speed and small phase separation error. Additionally, the composition velocity estimator exhibits fast response speed and high estimation accuracy.

This study aims to focus on using the Volterra series and machine learning for forecasting random and chaotic wind speed regimes, since the calm weather is mostly noticed at the local site, making the dataset selection difficult. A novel method is proposed to predict Volterra kernels up to the third order, using a forward-back propagation neural network with 12-month measurements at Fujairah site (UAE). Both daily and monthly wind speed data sets are investigated for forecasting. The three dominant hourly and daily kernels are extracted for each day and each month. Predicted future Volterra kernels are estimated from past values using both statistical analysis and individual neuro networks for each of the Volterra kernel coefficients. Due to the random nature of wind speed at the local site, a two-layer with 4 neurons per layer neuro network is used to locate the most variable and intense speed during 8-hours in the day. Forecasted wind speed is determined with errors arising from different sources such as the utilization of only 3rd-order Volterra kernels and the difficulty of machine training of the employed shallow network. Nevertheless, this work depicts a useful algorithm to forecast chaotic and random wind speed regimes. Computational time is a trade of the complexity of Volterra mathematical analysis.

Wave buoy measurements were carried out near the north-eastern Black Sea coast at the natural reserve Utrish in 2020-2021. In total, about 11 months of data records were collected during two stages of the experiment at 600 and 1500 meters offshore and depths of 18 and 42 meters. The measured waves propagate almost exclusively from the seaward directions. Generally, the waves do not follow the local wind directions, thus, implying a mixed sea state. Nevertheless, dimensionless wave heights and periods appears to be quite close to the previously established empirical laws for the wind-driven seas. The results of the wave turbulence theory are applied for estimates of spectral energy fluxes and their correspondence to the energy flux from the turbulent wind pulsations. These estimates are consistent with today's understanding of wind-wave interaction. It is shown that the main fraction of the wind energy flux goes to the direct Kolmogorov-Zakharov cascade to high wave frequencies and then to dissipation in small scales. Less than 1% of the wind energy flux is directed to low frequency band (the so-called inverse Kolmogorov-Zakharov cascade), thus, providing wave energy growth.

The common dandelion uses a bundle of drag-enhancing bristles (the pappus) that enables seed dispersal over formidable distances; however, the scaling laws of aerodynamic drag underpinning pappus-mediated flight remains unresolved. In this paper, we study the aerodynamic shape of dandelion, derive the scaling law of resistance, determine the Vogel exponent. In particular, we find that the total drag coefficient is proportional to the -2/3 power of the dandelion pappus Reynolds number, and obtain the terminal velocity of the dandelion seed under gravitation field.

Rising sensitivity of the loads with respect to power quality has grown-up the consideration of power system study and power quality enhancement systems. The fluctuation of voltage outside the normal working range due to faults may lead to unsuitable interruption of wind turbines. This thesis present 1.5MW grid connected Adama Ⅰ Wind Farm in Ethiopia with the objectives to capture the optimal power from the wind and ensure voltage source for sensitive load. This paper deals with the effective voltage sag mitigation and Harmonic distortion effectively met IEEE 519-1992 standard under all Phase to ground fault compensation by using Dynamic Voltage Restorer (DVR), to regulate the terminal voltage of the wind farm and safe operation of sensitive load. The DVR utilizes a feed forward control-based algorithm to generate PWM. The simulation results are going to be carried out by MATLAB-Simulink to verify the operation and effectiveness of DVR during balanced voltage sag and swell conditions.

Large structures such as wind turbines are subject to environmental factors and varying operational loads which may result in structural damage, making components of these large structures prone to performance and mechanical degradation. The use of high-definition optical vision sensors in digital image correlation (DIC) allow for the application of a non-destructive image registration technique in which it measures finite three-dimensional deformations on surfaces through correlations of a unique pattern or set of unique localized patterns. However, the physical placement of an artificial marker such as a unique speckled pattern on the surface of the structure is time-consuming and often impractical for large structures. Therefore, we propose a novel auto-mated methodology that searches and segments salient and unique regions of an image as well as for all subsequent images to assist in performing efficient displacement measurements for vibrational study and structural health monitoring purposes. Our algorithm is validated on a con-trolled set of images, as well as on a small structure and large real-world wind turbine, which suggests the algorithm’s efficacy without the use of artificial markers for large structural health monitoring.

The North Sea Offshore Grid concept has been envisioned as a promising alternative to: 1) ease the integration of offshore wind and onshore energy systems, and 2) increase the cross-border capacity between the North Sea region countries at low cost. In this paper we explore the techno-economic benefits of the North Sea Offshore Grid using two case studies: a power-based offshore grid, where only investments in power assets are allowed (i.e. offshore wind, HVDC/HVAC interconnectors); and a power-and-hydrogen offshore grid, where investments in offshore hydrogen assets are also permitted (i.e. offshore electrolysers, new hydrogen pipelines and retrofitted natural gas pipelines). We compare these scenario results with a business as usual scenario, in which offshore wind is connected radially to the shore and no offshore grid is deployed. All scenarios are run with the IESA-NS model, without any specific technology ban and under open optimization. This paper also presents a novel methodology, combining Geographic Information Systems and Energy System Models, to cluster offshore spatial data and define meaningful offshore regions and offshore hub locations. This novel methodology is applied to the North Sea region to define nine offshore clusters taking into account offshore spatial claims, and identifying suitable areas for single-use and multi-use of space for renewable energy purposes. The scenario results show that the deployment of an offshore grid provides relevant cost savings, ranging from 1% to 4.1% of relative cost decrease (2.3 bn € to 8.7 bn €) in the power-based, and ranging from 2.8% to 7% of relative cost decrease (6 bn € to 14.9 bn €) in the power-and-hydrogen based. In the most extreme scenario (H2) an offshore grid permits to integrate 283 GW of HVDC connected offshore wind and 196 GW of HVDC meshed interconnectors. Even in the most conservative scenario (P1) the offshore grid integrates 59 GW of HVDC connected offshore wind capacity and 92 GW of HVDC meshed interconnectors. When allowed, the deployment of offshore electrolysis is considerable, ranging from 61 GW to 96 GW, with capacity factors of around 30%. Finally, we also find that, when imported hydrogen is available at 2 €/kg (including production and transport costs), large investments in an offshore grid are not optimal anymore. In contrast, at import costs over 4 €/kg imported hydrogen is not competitive.

Doubly Fed Induction Generator (DFIG) has a stator winding directly coupled with grid. Whereas, rotor winding is connected via a fault-prone back to back power converters. DFIG is known to be vulnerable to the grid faults. In early times, when a fault occurred, these generators were required to disconnect from the grid to secure the generator and power converters. However, due to the increased penetration of wind turbines into the power system, grid operators demanded that the wind turbines remain connected to the grid, as disconnecting them would further disrupt the grid. When a fault at the grid terminal occur, a high stator current is induced which further result in high rotor current. This current will trigger the DC-link voltage to rise. This high currents and DC-link voltage will cause harm to the converters. Thus, in this paper work, the crowbar protection system is employed for protecting the converters against excess energy. Furthermore, the analysis of DFIG is rendered by integrating the crowbar protection with the Battery Energy Storage System (BESS) for a much effective outcome in enhancing machine to drive the fault. MATLAB-Simulink software is used for modeling and simulation. All system parameters are obtained from ADAMA-II Wind Farm.

The Haar wavelet decomposition technique is used to detect the planetary magnetosphere boundaries and discontinuities. We use the magnetometer data from the CASSINI and MESSENGER spacecraft to identify the abrupt changes in the magnetic field when the spacecraft crossed the magnetospheric bow shocks and magnetopauses of Saturn and Mercury, respectively. The results confirm that the Haar transform can efficiently identify the planetary magnetosphere boundaries characterized by the abrupt magnetic field changes. It is suggested that this technique can be applied to detect the planetary boundaries as well as the discontinuities such as the shock waves in the interplanetary space.

Air pollution is responsible for any adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the present work is to study the behavior of two bio-climatic indexes and statistical characteristics of the air quality index for Sofia city - the capital of Bulgaria for the period 2008 - 2014. The study is based on WRF-CMAQ model system simula-tions with a spatial resolution of 1 kilometer. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indi-ces, respectively, for hot and cold weather. Results: It was found that half of the heat and cold index categories are present in the simulations. Their distribution has some spatial features. All air quality categories are present in the domain, with dominance only of the O3 and PM10. Conclu-sions: It was found that Sofia is not so hot and air polluted place, but in some situations, people have to have some concerns when intend to be outdoors for a prolonged time.

The present study aims to develop a risk-based approach to find optimal solutions for life extension management for offshore wind farms based on Markowitz’s modern portfolio theory, adapted from finance. The developed risk-based approach assumes that the offshore wind turbines (OWT) can be considered as cash-producing tangible assets providing positive return from the initial investment (capital) with a given risk attaining the targeted (expected) return. In this regard, the present study performs a techno-economic life extension analysis within the scope of the multi-objective optimisation problem. The first objective is to maximise the return from the overall wind assets, while the latter aims to minimise the risk associated with obtaining the return. In formulating the multi-dimensional optimisation problem, the life-extension assessment considers the results of a detailed structural integrity analysis, free-cash-flow analysis, and probability of project failure, local and global economic constraints. Further, the risk is identified as the variance from the expected mean of return on investment. The risk-return diagram is utilised to classify the OWTs of different classes using an unsupervised machine learning algorithm. The optimal portfolios for the various required rate of return are recommended for different stages of life extension.

There is an accelerating requirement for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry was open for an optimization. Therefore, this study’s first objective was to identify the aerodynamic performance of such curvy twin sails. Simultaneously, a secondary objective was to estimate the effect of the sail’s spacing and shapes. A viscous Navier-Stokes flow solver is used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results have shown that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail is an important parameter. The spacing is 0.035L, 0.07L, and 0.14L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21L, 0.28L, and 0.35L. Significantly, the spacing 0.28L shows the maximum high pressure at the lower area and the small low pressure area at leading edges, so the highest lift is generated.

Spaceborne altimeters are an important data source for obtaining global sea surface wind speeds (U10). Although many altimeter U10 algorithms have been proposed and they perform well, there is still room for improvement. In this study, the data from ten altimeters were collocated with buoys to investigate the error of the altimeter U10 retrievals. The U10 residuals were found to be significantly dependent on many oceanic and atmospheric parameters. Because these oceanic and atmospheric parameters are inter-correlated, an asymptotic strategy was used to isolate the impact of different parameters and establish a neural-network-based correction model of altimeter U10. The results indicated that significant wave heights and mean wave periods are effective in correcting U10 retrievals, probably due to the tilting modulation of long-waves on the sea surface. After the wave correction, the root-mean-square error of the retrieved U10 was reduced from 1.42 m/s to 1.24 m/s and the impacts of thermodynamic parameters, such as sea surface (air) temperate, became negligible. The U10 residuals after correction showed that the atmospheric instability can lead to errors on extrapolated buoy U10. The buoy measurements with large air-sea temperature differences need to be excluded in the Cal/Val of remotely sensed U10.

The aim of work is to derive an explicit expression for a function of vertical mixing induced by wind-waves. To this end, in the Navier-Stokes equations, a current is decomposed into four constituents: the mean flow, the wave-orbital motion, the wave-induced turbulent and the background turbulent currents. This decomposition allows separating the wave-induced Reynolds stress, Rw, from the background one, Rb. To make a statistical closure for Rw, the Prandtl approach for the background turbulent fluctuations is used that results in an implicit expression for the wave-induced vertical mixing function, Bv. Expression for Bv is specified based on the author’s results for the eddy viscosity found earlier in the frame of the three-layer concept for a wavy air–sea interface, used for modelling wind-drift currents [1]. Finally, the explicit parameterization for Bv(a, u*, z) is found as a linear function in both the wave amplitude at depth z, a(z), and the friction velocity in the air, u*. The linear dependence of function Bv(a) on the wave amplitude provides the enhanced vertical mixing induced by wind–waves in comparison with function Bv(a) having the cubic dependence found in [2], as far as the wind-wave amplitude a(z) decays exponentially with depth.

The underground complicated testing environment and the fan operation instability cause large random errors and outliers of the wind speed signals. The outliers and large random errors result in distortion of mine wind speed monitoring, which possesses safety hazards in mine ventilation system. Application of Kalman filter in velocity monitoring can improve the accuracy of velocity measurement and eliminate the outliers. Adaptive Kalman Filter was built by automatically adjusting process noise covariance and measurement noise covariance depending on the differences between measured and expected speed signals. We analyzed the fluctuation of airflow flow using data of wind speed flow and distribution characteristics of the tunnel obtained by the Laser Doppler Velocimetry system (LDV) studies. A state-space model was built based on the tunnel airflow fluctuations and wind speed signal distribution. The adaptive Kalman Filter was calculated according to the actual measurement data and the Expectation Maximization (EM) algorithm. The adaptive Kalman filter was used to shield fluid pulsation while preserving system-induced fluctuations. Using the Kalman filter to treat offline wind speed signal acquired by LDV, the reliability of Kalman filter wind speed state model and the characteristics of adaptive Kalman Filter were investigated. Results showed that the adaptive Kalman filter effectively eliminated the outliers and reduced the root-mean-squares error (RMSE), and the adaptive Kalman filter had better performance than the traditional Kalman filter in eliminating outliers and reducing RMSE. Field experiments in online wind speed monitoring were conducted using the optimized adaptive Kalman Filter. Results showed that adaptive Kalman filter treatment could monitor the wind speed with smaller RMSE compared with LVD monitor. The study data demonstrated that the adaptive Kalman filter is reliable and suitable for online signal processing of mine wind speed monitor.

Considering the need to reduce greenhouse gas emissions, onshore wind energy is certain to play a major role in future energy systems. This topic has received significant attention from the research community, producing many estimations of Europe's onshore wind potential for capacity and generation. Despite this focus, previous estimates have relied on distribution assumptions and simulation schemes that summarily under predict both the amount of available future wind capacity as well as its performance. Foremost in this regard is the common use of contemporary, or at least near-future, turbine designs which are not fitting for a far-future context. To fulfill this role, an improved, transparent, and fully reproducible work flow is presented for determining European onshore wind potential. Within a scenario of turbine cost and design in 2050, 13.5 TWof capacity is found to be available, allowing for 34.4 PWh of generation. By sorting the explicitly-placed potential generation locations by their expected generation cost, national relations between turbine cost and performance versus a desired capacity are exposed. In this way, it is shown that all countries possess some potential for onshore wind energy generation below 4 €_ct kWh^-1. and, furthermore, that it is unlikely for these costs to exceed 6 €_ct kWh^-1.

Typhoon Durian forming over the Western North Pacific Ocean and entering into the South China Sea (SCS), caused extreme and widespread damages in 2006. In this research, sensitivity analyses on different physical parameterization schemes of the Weather Research and Forecasting Atmospheric Model (WRF-ATM) have been utilized to study typhoon Durian. Model accuracy and performance testing were investigated with different initial conditions during the tropical cyclone simulation in the SCS. The initial and boundary conditions (IBCs) for all experiments were derived from the European Centre for Medium Range Weather Forecasts (ECMWF), Re-Analysis Interim (ERAI), and the National Centers for Environmental Prediction (NCEP) with Final (FNL) analysis data compiled through the WRF-ATM model. The sensitivity analysis results indicated a major improvement for the cumulus scheme by using the Grell-Devenyi scheme along with the PBL scheme of Yonsei University, mixed-phase microphysics scheme of the WRF Single Moment 5-class and IBCs for ECMWF-ERAI of TC simulation under the context of Wind-Pressure Relationships. This predicted better track and intensity comparing with these of the Joint Typhoon Warning Center. The results revealed that the TC track and intensity were well simulated by the WSM5-GD combination for the WRF-ATM model with an intensity error of 1.69 hPa for minimum surface level pressure, maximum wind speed of 1.83 knots and average track error of 25 km in 72 hours. The simulations showed that the potential track and intensity error decreased with the delayed IBCs, suggesting that the model simulation is more dependable when the coast is approached by the TC.

This study analyses the short-run hydro generation scheduling for the wind power differences from the contracted schedule. The approach for construction of the joint short-run marginal cost curve for the hydro-wind coordinated generation is proposed and applied on the real example. This joint short-run marginal cost (SRMC) curve is important for its participation in the energy markets and for economic feasibility assessment of such coordination. The approach credibly describes the short-run marginal costs which this coordination bears in “real life”. The approach is based on the duality framework of a convex programming and as a novelty combines the shadow price of risk mitigation capability and the water shadow price. The proposed approach is formulated as a stochastic linear program and tested on the case of the Vinodol hydropower system and the wind farm Vrataruša in Croatia. The result of the case study is a family of 24 joint short-run marginal cost curves.

A three-dimensional, unstructured grid, hydrodynamic and suspended-sediment transport model (i.e., SELFE-SED) was developed to simulate temporal and spatial variations of suspended sediment and was applied to the subtropical subalpine Tsuei-Feng Lake (TFL) of Taiwan. The model was validated with measured water level and suspended‑sediment concentration in 2009, 2010, and 2011. The overall model simulation results are in quantitative agreement with the observational data. The validated model was then applied to explore the most important parameter that affects the suspended-sediment concentration and to investigate the effect of wind stress on the mean current and suspended‑sediment distribution in this shallow lake. Modeling results of sensitivity analysis reveal that the settling velocity is a crucial parameter and erosion rate is less important in the suspended-sediment transport model. Remarkable lake circulation was found based on the strength of wind speed and wind direction. Strong wind would result in higher mean current in the top layer and suspended-sediment distribution in the top and bottom layers. This study demonstrated that the wind stress played a significant influence on mean circulation and suspended-sediment transport in a shallow lake.

Optimizing the NACA0015 airfoil which is widely applied in small-scale vertical axis wind turbine to make it has a better aerodynamic performance. In the optimization process, using CST parameterization method to perturb the airfoil geometry, the thickness and camber of the airfoil are selected as the constraint, and the value of the maximum tangential force coefficient is chosen as the objective function, the genetic algorithm based on non-dominated sorting (NSGA-II)is selected as an optimization method, calculates the aerodynamic performance of the airfoil by applying the approach of combining XFOIL program and Viterna-Corrigan post-stall mode ,and establishes the optimizing process by the optimization software modefrontier for NACA0015 airfoil’s muti-point optimization, validate the airfoil’s performance with CFD finally. The result illustrates that, by comparing with the NACA0015 airfoil, the optimized airfoil’s lift to drag ratio is improved over a wide range of attack angles, the stall performance is more gentle. The maximum lift coefficient, the maximum lift-drag ratio and the maximum tangential force coefficient are increased by 7.5%,9 and 8.87%, respectively. The optimized airfoil has a wide variable condition performance, more suitable for the operating conditions of a vertical axis wind turbine. Finally, predict the rotor efficiency with optimized airfoil and NACA0015 airfoil for different tip speed ratios and different solidities with multiple streamtube model, the result shows the rotor with optimized airfoil has a higher efficiency.

I propose a new strategy to suppress human cancer completely with two entirely new drug compounds exploiting cancer's Warburg effect characterized by a defective mitochondrial aerobic respiration, substituted for by cytosolic aerobic fermentation/glycolysis of D-(+)-glucose into L-(+)-lactic acid. The two essentially new drugs compound 1 [P(op)T(est)162] and compound 3 (PT167) represent new highly symmetric, four-bladed propeller-shaped polyammonium cations. The in vitro antineoplastic highly efficacious drug compound 3 represents a covalent combination of compound 1 and compound 2 (PT166). The intermediate drug compound 2 is an entirely new colchic(in)oid derivative synthesized from colchicine. Compound 2's structure was determined by X-ray crystallography. Compound 1 and compound 3 were active in vitro versus 60 human cancer cell lines of the National Cancer Institute (NCI) Developmental Therapeutics Program (DTP) 60-cancer cell testing. Compound 1 and compound 3 both not only stop the growth of cancer cells to ±0% (cancerostatic effect), but completely kill nearly all 60 cancer cells to a level of almost −100% (tumoricidal effect). Compound 1 and compound 3 induce mitochondrial apoptosis (under cytochrome c release) in all cancer cells tested by (re)activating (in most cancers impaired) p53 function which results in a decrease of cancer's dysregulated cyclin D1 and an induction of the cell cycle-halting cyclin-dependent kinase inhibitor p21^Waf1/p21^Cip1.

In this paper, using the two integers that describe the stationary 2-dimensional wave and the charge quantization along with the balance between the Lorentz force and electrical force, we succeed in deriving the fractional quantum Hall effect and the integer quantum Hall effect; we find that the latter exists as a special case of the former. Moreover, using the derived expression describing the fractional quantum Hall effect, a relationship between the plateau in the resistivity of the sample and the applied magnetic field is obtained. The findings of this model agree well with experimental measurements. Because the two integers that describe the stationary 2-dimensional wave and the charge quantization along with the force balance have concrete physical meanings in this work, we could provide a clear picture of the origin of both the integer quantum Hall effect and the fractional quantum Hall effect.

The plant productivity-richness relationship (PPR) is one of the most debated and important issues in ecology. There have been distinct stages in the research of this issue, including the discovery of the different PPR shapes, respective tests of influencing processes, and integrative research with vegetation investigation, manipulation experiments, and theoretical analysis. The debate largely focuses on what the dominant shapes and underlying mechanisms are. Recent integrative research works following analyses of respective processes affecting PPR have found that the humped, asymptotic, positive, negative, and irregular shapes of PPR are linked to each other. One shape of PPR may change into another. The balance between positive and negative processes determines the different shapes of PPR. Plant diversity has a globally positive effect on plant productivity.

The conversion of native habitats into anthropogenic ones compromises the original composition and configuration of the landscapes, influencing ecological dynamics and affecting biodiversity. Increasingly, landscape ecology has shown that these effects can only be understood if accessed at adequate spatial scales, as the scale which landscape structure is evaluated influences species responses. Here, we investigated how three variables of landscape composition (proportion of forest, coffee crop and pasture) and two of configuration (number of fragments and mean nearest neighbor distance) interfere in the richness and composition of medium and large-sized mammals considering a multiscale approach. We recorded medium and large-sized mammal species in 13 landscapes with predominantly matrices of coffee and pasture in Minas Gerais, Brazil. Then, we built distance-based linear models to identify the scale of effect of each landscape variable for both response variables considering eight scales (from 250 m to 2000 m). Finally, we verified the influence of the landscape on the richness and composition of mammals, considering the landscape variables in their respective scales of effect. We found 67% of the probable species occurring in the region. The scales of effect varied among landscape variables probably due to the different variables affect different aspects of organisms' ecological requirements. The proportion of pasture in the landscape explained the variation in species richness, while the proportion of forest explained the variation in species composition. In addition, the proportion of pasture in the landscape had a positive influence on species richness, indicating that this matrix may favor the presence of generalist species of habitat and/or this result is due to the higher concentration of species in the fragments immersed in this matrix. These results suggest that considering different responses to biodiversity is important to understand different aspects of the landscape's influence on biodiversity. In addition, the composition of the landscape is fundamental for the perpetuation of species and, therefore, both forest cover and types of matrices in the landscape must be considered to improve species conservation strategies. Finally, generalizing a spatial scale can lead to misinterpretations about the influence of the landscape on biodiversity.

Silver ion (Ag+) are recognized for their potent antibacterial properties; however, their utilization in food preservation is restricted by factors such as inadequate stability, a transient antibacterial impact, and the potential for human absorption. Hydrogel-based antibacterial agents are capable of exerting their antibacterial effects by establishing appropriate microenvironments, which facilitate the efficient delivery of antimicrobial molecules to the contaminated regions of food. In previous studies, we observed that chitosan (CS) and silver nitrate (AgNO3) were able to reduce Ag+ to silver nanoparticles (AgNPs) with enhanced antibacterial properties. This not only significantly extended the stability of the antibacterial agent but also demonstrated exceptional inhibitory capabilities against pathogenic bacteria, including common grape contaminants such as P. expansum, A. niger, and B. cinerea. Utilizing ultrasound-induced complexation technology, this study has successfully synthesized a chitosan-silver (CS-AgNPs) hydrogel. The efficacy of this hydrogel against the pathogenic fungus responsible for jujube black spot disease has been thoroughly investigated. The morphology structures of CS-AgNPs hydrogels were characterized by TEM, FTIR and UV-vis. The results indicated that AgNPs ranging from 80 to 110 nm were uniformly dispersed within the gel matrix and remained stable for extended periods at room temperature. In vitro antibacterial assays and fractional inhibitory concentration index (FICI) studies revealed that the pronounced antibacterial efficacy of the CS-AgNPs hydrogel was primarily attributed to the additive antibacterial effect of CS and AgNPs. These insights underscore the significant potential of CS-AgNPs hydrogels in combating fungal diseases of jujube, offering innovative strategies and materials for the management of agricultural pathogens.

Lactoperoxidase (LP) is an important enzyme of the salivary and mammary glands. It has been proven to increase the shelf life of raw milk by inhibiting the growth of bacteria, especially Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, and Pseudomonas spp. The aim of this work was to verify the use of LP to extend the shelf life of meat products. In vitro experiments showed inhibitory effects against selected bacteria (Listeria innocua (ATCC 33090), Staphylococcus saprophyticus (CP054440.1), and Pseudomonas fluorescens (ATCC 13525) due to prolongation of the lag phase of growth curves. A lower increase in viable counts (P < 0.05) was also found by testing the pork cubes surface treated with LP solution (5%) + L. innocua and stored for 7 days at 15 °C. LP has also been studied at concentrations of 0.25 and 0.50% in meat products (pork ham and pâté) during refrigerated storage (4 °C for 28 days). Lower viable counts were observed throughout the storage experiment, especially for 0.50% LP (P < 0.05). Meat products containing LP also showed lower levels of oxidation (MAD) (P < 0.05). According to these results, LP could extend the shelf life of a wider range of products.

For concrete structures exposed to offshore areas, chloride ion erosion is one of the main factors affecting the durability. It is crucial to evaluate chloride ion permeability resistance of concrete structures. In this article, a finite element simulation of the chloride ion diffusion process in concrete is conducted. A mass diffusion finite element model based on random aggregate approach is established to investigate the influence of aggregate, interface transition zone, and micro-cracks on chloride ion diffusion coefficients in concrete. The results show that the mass diffusion finite element analysis based on the exponential function model and power function model can effectively simulate the chloride ion diffusion process in concrete. In addition, the data reveal that coarse aggregate is the most important factor affecting chloride ion diffusivity in concrete. However, the interface transition zone significantly accelerates chloride ion diffusion in concrete. Moreover, this acceleration effect exceeds the barrier effect of aggregate.

Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

In all mammals, the circulating pool of MLT is synthesized in the pineal gland, during the night darkness hours. Its main function is that of synchronizing the organism in the photoperiod. In contrast, extra-pineal MLT is synthesized in peripheral organs, does not follow any circadian rhythm nor circulates and plays a detoxifying and cytoprotective action. Circulating MLT may stimulate both innate and acquired immune responses by its circadian action and by activating high affinity receptors on immunocompetent cells. Extra-pineal MLT may have anti-oxidant and anti-inflammatory effects dampening the innate immune response. These two seemingly divergent roles may be considered as two faces of the same coin. In fact, the integration of both circulating and extra-pineal MLT functions might generate a balanced and effective immune response against microbial pathogens. The studies described in this review investigated the effect of exogenous MLT in various models of infectious diseases using extremely different doses and treatment schedules. None of them evaluated the possibility to integrate the non-circadian anti-inflammatory effect with the circadian immunoenhancing action of MLT. As a consequence, in spite that most studies agree that MLT has a beneficial effect against infections, it seems difficult to draw any definite conclusion about its possible therapeutic use.

Through a brief analysis of the basic principle of relativity, it is found that there is a contradiction in principle between general relativity and special relativity in solving the specific problem of the clock moving around the earth, and one of them must be wrong. Through comparative analysis of five physical phenomena and experiments, it is proved that there are serious problems in the space concept of relativity theory and classical physic. At the same time, the different concept of absolute airspace is further expounded and demonstrated, and the related space-time physical phenomena and experiments are perfectly explained by this concept. According to this idea, a new time transformation relation is deduced and its correctness is demonstrated. It is proved that the principle of special relativity and special relativity are wrong, and a series of physical laws and physical explanations generated by special relativity may also be wrong, and a series of amendments or new interpretations need to be made.

Cancer, a globally prevalent and often deadly disease, holds promise for improved treatment through the integration of innovative medical technologies and interdisciplinary collaborations. Despite advancements, current cancer therapies lack a specific focus on addressing recurrence and targeting cancer stem cells (CSCs), known contributors to relapse. In this study, we utilized three types of cancer cells and generated three types of CSCs derived from them to conduct proteomic analysis and identified shared cell surface biomarkers as potential targets for a comprehensive treatment strategy. The selected biomarkers underwent evaluation through shRNA treatment, revealing contrasting functions in cancer and CSCs. Knocking down the identified protein showed promising results in regulating epithelial-mesenchymal transition (EMT) and stemness via the ERK signaling pathway. This led to a reduction in resistance to anticancer agents, ultimately enhancing the overall anticancer effects. Additionally, the biomarker's significance in clinical patient outcomes was confirmed using bioinformatics. Our study suggests a novel cancer treatment strategy that addresses existing limitations in current anticancer therapies.

Diarrhea-related mortality remains an important public health concern, particularly in developing countries, and has become difficult to treat because of antibacterial resistance. The development of synergistic antimicrobial agents appears to be a promising alternative treatment against diar-rheal infections. In this study, the combined effect of tetracycline together with either nitroxoline, sanguinarine, or zinc pyrithione (representing various classes of alkaloid-related compounds) was evaluated in vitro against selected diarrheagenic bacteria (Enterococcus faecalis, Escherichia coli, Listeria monocytogenes, Shigella flexneri, Vibrio parahaemolyticus, and Yersinia enterocolitica). The chequerboard method in 96-well microtiter plates was used to determine the sum of the fractional inhibitory concentration indices (FICIs). Three independent experiments were performed per combination, each in triplicate. It was observed that the combinations of tetracycline with either nitroxoline, sanguinarine, or zinc pyrithione produced synergistic effects against most of the pathogenic bacteria tested, with FICI values ranging from 0.086 to 0.5. Tetracycline-nitroxoline combinations produced the greatest synergistic action against S. flexneri at a FICI value of 0.086. Combinations of the agents tested in this study can thus be used for the development of new anti-diarrheal medications. However, studies focusing on their in vivo anti-diarrheal activity and safety are required before any consideration for utilization in human medicine.

A thermal system in very deep Lake Tazawa (maximum depth, 423 m) was investigated by estimating the heat budget. In the heat budget estimate, the net heat input at lake surface and the heat input by river inflow and groundwater inflow were considered. Then, the heat loss by snowfall onto lake surface was taken into account. Meanwhile, lake water temperature was monitored at 0.2 m to the bottom by mooring temperature loggers for more than two years. The heat storage change of the lake from the loggers was calibrated by frequent vertical measurements of water temperature at every 0.1 m pitch by a profiler with high accuracy (± 0.01 °C). The heat storage change (W/m2) obtained by the temperature loggers reasonably accords to that from the heat budget estimate. In the heat budget, the net heat input at lake surface dominates the heat storage change, but the significant heat loss by river inflow sporadically occurred, which is caused by the relatively large discharge from a reservoir in the upper region. How deep the vertical water circulation in the lake occurs in winter was judged by the differences between water temperatures at 0.2 m depth and bottom and between vertical profiles of dissolved oxygen over winter. It is strongly suggested that the whole water circulation does not occur every winter, if any, very weak.

The increasing residential space differentiation is an important practical problem for Chinese cities. The different choice of living space for urban residents is a concrete reflection of social class divide, which reflects the differences in the choices and demands of different social groups for urban housing. Taking Wuhan, an important city in central China, as an example, this research divides the residential space based on the social resource structure, and analyzes and compares the spatial differentiation and influencing factors of different residential areas and houses with different prices in Wuhan by spatial differentiation indicators and geographic detector. The results show clear differences in resource structure among residential areas, and there are few high-quality residential areas with a concentrated distribution. The spatial differentiation levels of different residential areas are distinct, and the pursuit of high-quality and scarce resources is the key to the residential space differentiation of most large cities in China. In addition, residential space differentiation can lead to inter-generational problems such as housing wealth inequality, resource deprivation and solidified class identity. Exploring the mechanisms and social effect of residential space differentiation in most large cities in China can provide some reference for China's urban space planning and real estate market regulation in the new era.

Heptanuclear {GdIII7} (complex 1) and tetradecanuclear {GdIII14} (complex 2) have been synthesized using a Rhodamine 6G ligand HL (Rhodamine 6G salicylaldehyde hydrazone) and characterized. Complex 1 has a rare disc-shaped structure, where the central Gd ion was connected to the peripheral six GdIII ions via CH3O-/μ3-OH- bridges. Complex 2 has an unexpected three-layer double sandwich structure with a rare μ6-O2- ion in the center of the cluster. Magnetic studies revealed that complex 1 exhibits a magnetic entropy change of 17.4 J kg−1 K−1 at 3 K and 5 T. On the other hand, complex 2 shows a higher magnetic entropy change of 22.3 J kg−1 K−1 at 2 K and 5 T.

German chamomile galenic preparations are used to treat mild skin diseases, inflammation and spasms, and they have also reported to have anxiolytic and sedative effects. The medicinal use of chamomile is well-known in ethnomedicine. Since chamomile has shown to have some adverse effects, there is a need to develop new formulations, such as dry extracts, for the present herb. The aims of this study were (1) to develop a novel method for preparing essential oils and dry extracts from German chamomile flowers, (2) to reveal the phytochemical composition of such extracts, and (3) to verify the analgesic and soporific activity of extracts in vivo with a rodent animal model. Furthermore, our study aims to gain knowledge of the ethnomedical status of chamomile in the past and presence. Essential oils and dry extracts were successfully prepared from the tincture and aqueous extracts obtained after hydrodistillation and from a tincture powder. Total 22 phenolic compounds (7 hydroxycinnamic acids, 13 flavonoids and 2 phenolic acids), were found in the dry extracts by using UPLC-MS/MS. Total 9 main terpenoids were identified in the chamomile oil, and these terpenoids represent the chemotype rich in bisabolol oxides A and B. In the highest yield, the ratio of phenolic compounds and extract was in the range of 1:14-1:16 and triple extraction was performed. In in-vivo studies with mice and rats, the extracts showed analgesic activity and improvements in sleep. The highest sedative effect in rodents was found with the extract prepared by using a 70% aqueous ethanol solution for extraction. The administration of such extract at the dose of 50 mg/kg significantly prolonged the sleeping time in rats.

There is a major problem with the rising occurrence of highly virulent and multiply-resistant strains, including methicillin-resistant Staphylococcus aureus (MRSA), because of their difficult treatment. This study aimed to evaluate the antibacterial and antibiofilm effect of new enterocins (Ent) against potential pathogenic MRSA strains isolated from rabbits. Staphylococci (n =110) were identified with PCR and screened for methicillin/oxacillin/cefoxitin resistance (MR) using the disk diffusion method and the PBP2' Latex Agglutination Test Kit. Enzyme production, hemolysis, DNase activity, slime production, and biofilm formation were tested in MRSA strains. The susceptibility of MRSA to eight partially-purified enterocins (Ent) produced by E. faecium and E. durans strains was checked using agar spot tests. The antibiofilm activity of Ents was tested using a quantitative plate assay. Out of 14 MRSA, PBP testing confirmed MR in 8 strains. The majority of MRSA showed DNase activity and β-hemolysis. Slime production and moderate biofilm formation were observed in all strains. MRSA were susceptible to tested Ents (100–12800 AU/mL; except Ent4231). The antibiofilm effect of Ents (except Ent4231) was noted in the high range (64.9-97.0%). These results indicate that enterocins offer a promising option for the prevention and treatment of bacterial infections caused by biofilm-forming MRSA.

As an outstanding information carrier, skyrmion is increasingly widely used in devices based on complex geometries. To achieve the skyrmion-based spintronic devices, a reasonable and feasible nanotrack is essential. In this paper, we conducted a study on the current-driven skyrmion movement in a circular-ring-shaped nanotrack. Our results suggest that the asymmetry of the inside and outside boundary of the circular ring changed the stable position of the skyrmion, causing it to move like the skyrmion Hall effect when driven by currents. Moreover, the asymmetric boundaries have advantages in enhancing or weakening the skyrmion Hall effect. Additionally, we also compared the skyrmion Hall effect from the asymmetric boundary of circular ring nanotracks with that from inhomogeneous DMI. It is found that the skyrmion Hall effect caused by the circular ring is significantly greater than that caused by the inhomogeneous DMI. These results contribute to our understanding of the skyrmion dynamics in confined geometries and offer an alternative method for controlling the skyrmion Hall effect of skyrmion-based devices.

The direct measurements of the magnetocaloric effect were performed in Heusler Ni44.4Mn36.2Sn14.9Cu4.5 alloy at cryogenic temperatures in magnetic fields up to 10 T. The maximum value of the inverse magnetocaloric effect in a field of 10 T was observed ∆Tad = –2.7 K in the vicinity of the 1st order magnetostructural phase transition at T0 = 117 K. The ab initio and Monte Carlo calculations were performed to discuss the effect Cu doping into Ni-Mn-Sn compound on the ground state structural and magnetic properties. It is shown that with increasing Cu content the martensitic transition temperature decreases and the Curie temperature of austenite slightly increases. In general, calculated transition temperatures, magnetization values are correlated well with the experimental ones.

High production cost is one of the major factors that limit the market growth of polyhydroxyalkanoates (PHAs) as a biopolymer. Improving PHA synthesis performance and utilizing low grade feedstock are two logical strategies for reducing the cost. As an oleaginous yeast, Y. lipolytica has a high carbon flux through acetyl-CoA (main PHB precursor) which makes it a desired cell factory for PHB biosynthesis. Two different metabolic pathways introduced into Y. lipolytica PO1f in this study for enhancing PHB biosynthesis, along with glucose and acetate as co-substrates. Results showed that NBC pathway led to more than 11% PHB accumulation, while there was non-detectable PHB accumulations using ABC pathway. Further modifications were done using peroxisomal compartmentalization and gene-dose overexpression. Final strain showed up to 41% PHB of CDW with a growth rate of 0.227 h-1. Low growth rate was observed using acetate or glucose as sole carbon and energy source. The co-substrate strategy showed compensatory effect on overcoming inhibitory and toxic effects of both substrates at high concentrations. Cultivating the engineered strain in optimal co-substrate condition predicted by RSM led to 83.4 g/L biomass concentration and 31.7 g/L PHB.

Higher concentrations of greenhouse gases resulting from anthropogenic actions associated with energy generation are one of the causes of climate change. In view of this, several efforts have been undertaken in the search for more sustainable alternatives, and photovoltaic (PV) technology has stood out among the different possibilities. However, PV generation is highly sensitive to future climate variability, which is a source of uncertainty that can complicate energy planning and compromise the viability of systems. This theme has received attention from the academic community, but some challenges to map and identify relevant literature have been encountered. Therefore, this study was conducted to analyze and identify relevant aspects of international scientific production on the impacts of climate change on the potential of photovoltaic production, CC-PVP, through bibliometric techniques. For this, 3900 articles from the Web of Science and Scopus databases, published between 1960 and 2021, were retrieved and analyzed through a bibliometric approach, using the SciMAT tool. Among the results obtained, it is worth pointing out that the CC-PVP research field (i) has moderate maturity, (ii) is concentrated in the areas of energy, fuels and technology, as well as environmental sciences and meteorology, (iii) has the most studied themes currently related to energy and the forecasting of photovoltaic energy production and electric energy consumption in the world, especially when considering climate change, and (iv) is more researched by Chinese, North Americans and Australians.

Four strains of green microalgae (Scenedesmus acutus, Scenedesmus vacuolatus, Chlorella sorokiniana and Chlamydomonas reinhardtii) were compared for growth and pigment composition under photoautotrophic or heterotrophic conditions. Batch growth experiments were performed in multicultivators with online monitoring of optical density. For photoautotrophic growth, light-limited (CO2-sufficient) growth was analysed under different light intensities during exponential and deceleration growth phases. The specific growth rate, mesured during exponential phase, and the maximal biomass productivity, measured during deceleration phase, were not related to each other when different light intensities and different species were considered. This indicates species-dependent photoacclimation effects during cultivation time, which was confirmed by light-dependent changes in pigment contents and compositions when exponential and deceleration phases were compared. Except for C. reinhardtii, that does not grow on glucose, heterotrophic growth was promoted to similar extents by acetate or by glucose, however these two substrates led to different pigment compositions. Weak light increased pigment contents during heterotrophy in the four species, but was efficient in promoting growth only in S. acutus. C. sorokiniana and S. vacuolatus exhibited the best potential for heterotrophic biomass productivities both on glucose and acetate, with carotenoid (lutein) content being the highest in the former.

Amidst China's new economic normal, the real economy faces various domestic and global challenges. Technological innovation, with its capital intensity and uncertain returns, is crucial to rejuvenate emerging industries and revamp the industrial structure. Meanwhile, financial agglomeration plays a dual role: directly fostering real economic development and indirectly affecting it through technological innovation. This study analyzes data from 30 mainland Chinese provinces and cities between 2011 and 2018, utilizing fuzzy matter-element analysis and location entropy method. Relying on a spatial econometric model, we explore the impact of technological innovation and financial clustering on real economic growth, including spatial ripple effects. The conclusions are derived from Chinese evidence and offer valuable insights into the evolving innovation and financial dynamics within the participating nations.

ABSTRACT The present study aimed to investigate the presence of asymmetric stochastic volatility and leverage effects within the Nasdaq-100 index. This index is widely regarded as an important indicator for investors. We focused on the nine leading stocks within the index, which are highly popular and hold significant weight in the investment world. These stocks are Netflix, PayPal, Google, Intel, Microsoft, Amazon, Tesla, Apple, and Meta. The study covered the period between 03/01/2017 and 30/01/2023, and we employed the Eviews and WinBUGS applications to conduct the analysis. We began by calculating the logarithmic difference to obtain the return series. We then performed a sample test with 100,000 iterations, excluding the first 10,000 samples to eliminate the initial bias of the coefficients. This left us with 90,000 samples for analysis. Using the results of the asymmetric stochastic volatility model, we evaluated both the Nasdaq-100 index as a whole and the volatility persistence, predictability, and correlation levels of individual stocks. This allowed us to evaluate the ability of individual stocks to represent the characteristics of the Nasdaq-100 index. Our findings revealed a dense clustering of volatility, both for the Nasdaq-100 index and the nine individual stocks. We observed that this volatility is continuous but has a predictable impact on variability. Moreover, with the exception of Intel, all the stocks in the model exhibited both leverage effects and the presence of asymmetric relationships, as did the Nasdaq-100 index as a whole. Overall, our results show that the characteristics of stocks in the model are similar to the volatility characteristic of the Nasdaq-100 index and have the ability to represent it.

Accurate forecast of tail water level (TWL) is of great importance for the safe and economic operation and management of hydropower stations. The predictive performance is significantly influenced by the backwater effect of downstream hydropower stations and tributaries, but the explicit quantification method of the backwater effect is lacked. In this study, a deep learning model based forecasting framework for TWL predictions is established and applied to forecast TWL of Xiangjiaba (XJB) hydropower stations, which is influenced by the backwater effect of downstream tributaries including Hengjiang River (HJR) and Minjiang River (MJR). Firstly, the lag time of the backwater effect of HJR and MJR is analyzed based on the permutation importance. The results demonstrate that the lag time of backwater effect on the TWL of XJB is 5-7 hours for the HJR and 1-2 hours for the MJR. Then, the runoff thresholds of the HJR and MJR for impacting the TWL of the XJB station are obtained by scenario comparison, and the results show that the thresholds of HJR and MJR are 700 m3/s and 7000 m3/s respectively. Finally, the deep learning methods based TWL forecasting model is established based on the lag time and threshold analysis. The model is used to forecast the TWL in future 48 hours. The results show that the forecasting model has a good predictive performance with 98.22% of absolute errors less than 20 cm. The mean absolute error over the validation dataset is 5.27 cm and the maximum absolute error is 63.35 cm.

To determine the impacts of metabolizable energy levels on the performance indices of geese and to forecast the ideal range of dietary metabolizable energy levels, this study was carried out. Literature on the effects of dietary metabolized energy level on the performance of geese was searched from CNKI, Wanfang, VIP, PubMed, Web of Science, and ScienceDirect databases from January 1, 2000, to December 31, 2022. A dose-response meta-analysis was performed by STATA (14.0), data were calculated by the robust error meta-regression model (REMR), and nonlinear dose-effect curves were plotted by the restricted cubic spline method (RCS). 29 papers were chosen from the 1,475 literatures that fit the criteria and were included in the dose-response meta-analysis. There were 6,079 geese included in the sample. The following production performance indices included average daily gain (ADG), average daily feed intake (ADFI), feed-to-gain ratio (F/G), dressed percentage, percentage of half-eviscerated yield, percentage of eviscerated yield, percentage of breast muscle, percentage of leg muscle and percentage of abdominal fat. The Egger test assessed publication bias, while sensitivity analysis was used to examine the heterogeneity. The verified results are consistent and reliable. The results indicated that for each group, the optimal dietary metabolizable energy level was about 13 to 13.5MJ/kg for medium-sized geese aged 0 to 4 weeks, 12 to 13MJ/kg for medium-sized geese aged above 5 weeks, 12.5 to 13MJ/kg for small-sized geese aged 0 to 4 weeks, and 13 to 13.5MJ/kg for mall-sized geese over 5 weeks of age. Future research should be conducted on related diets of large-sized geese, small-sized geese, and higher metabolizable energy levels.

Adverse events associated with opioid use in palliative care have been extensively studied. However, predicting the occurrence of adverse events based on the specific opioid used remains unclear. This study aimed to comprehensively analyze the adverse events caused by µ receptor stimulation of opioids approved in Japan and investigate the tendencies of adverse event occur-rence among different opioids.We utilized the FDA Adverse Event Reporting System (FAERS) database to extract reported adverse events of opioids approved in Japan. Cluster analysis was performed on reporting odds ratios (RORs) of adverse event names among opioids to visualize relationships between opioids and adverse events, facilitating a comparative study of their clas-sifications.We calculated the RORs of adverse events for the target opioids. Based on these RORs, we performed a cluster analysis, which resulted in the classification of 11 target opioids into five distinct groups. we were able to comprehensively compare and examine the relationships between opioids and adverse events. This analysis helps in understanding and managing the risks and benefits of each drug in palliative care settings. By analyzing relationships between opioids and adverse events, clinicians can make informed decisions about opioid selection, dosage, and monitoring to maximize patient safety and comfort.

Cropland abandonment is a widespread phenomenon with an increasing trend around the world, including China. Cropland abandonment is the result of a multi-scale and multi-factor nested structure, in order to comprehensively identify the individual and background effects, the study explores the causes of the differences in farmland abandonment levels at two levels: farm household and village, based on a hierarchical linear model. The results show that: (1) 83.63% of the differences in farm abandonment rates are differences in farm households while 16.37% are differences in their villages; (2) whether head of household is healthier, per capita cropland area, ratio of transferred farmland, possession of large-scale agricultural production machinery or livestock for agricultural production, ratio of agricultural income, and whether there are village cadres have a significant negative impact on abandonment rates at the farm household level; while at the village level, commuting distance, whether it is a suburb of a large or medium-sized city, topography of the village is plain or not, and ratio of the number of people in agricultural production in the village have a significant positive impact on abandonment rates, while whether it has experienced land expropriation has a significant positive effect on the abandonment rate; (3) commuting distance weakens the negative correlation between the ratio of transferred cropland and the ratio of agricultural income and the abandonment rate; whether it is a suburb of a large or medium-sized city strengthens the negative correlation between whether it owns large-scale agricultural production machinery or livestock and the abandonment rate; whether the topography of the village is plain weakens the negative correlation between the possession of large agricultural production machinery or livestock for agricultural production and the agricultural income ratio and the abandonment rate; ratio of the number of people in agricultural production in the village weakens the negative correlation between the ratio of transferred cropland and abandonment rate; and whether the village has experienced land expropriation strengthens the negative correlation between the ratio of agricultural income and abandonment rate.

Environmentally friendly lead-free K1-xNaxNbO3 (KNN) ceramics possess electromechanical properties comparable to lead-based ferroelectric materials, but cannot meet the needs of device miniaturization, and the corresponding thin films lack of theoretical and experimental studies. To this end, we developed the nonlinear phenomenological theory for ferroelectric materials to study the effects of non-equiaxed misfit strain on the phase structure, electromechanical properties and electrical response of K0.5Na0.5NbO3 epitaxial films and constructed the in-plane misfit strain (u1-u2) phase diagrams. The results show that K0.5Na0.5NbO3 epitaxial film under non-equiaxed in-plane strain can exhibit abundant phase structures, including orthorhombic a1c, a2c and a1a2 phases, tetragonal a1, a2 and c phases, and monoclinic r12 phases. Moreover, in the vicinity of a2c-r12, a1c-c and a1a2-a2 phase boundaries, K0.5Na0.5NbO3 epitaxial films exhibit excellent dielectric constant ε11, while at a2c -r12 and a1c-c phase boundaries large piezoelectric coefficient d15 is observed. It was also found that high permittivity ε33 and piezoelectric coefficients d33 exist near the a2c - a2, r12- a1a2 and a1c-a1 phase boundaries due to the existence of polymorphic phase boundaries (PPB) in the KNN system, which makes it easy to polarize near the phase boundaries, and the polarizability changes suddenly, leading to electromechanical enhancement. In addition, the results show that the K0.5Na0.5NbO3 thin films possess a large electrocaloric response at the phase boundary at the r12-a1a2 and a1c-a1 phase boundaries. And the maximum adiabatic temperature change ∆T is about 3.62 K when the electric field change is 30 MV/m at room temperature, which is significantly enhanced compared with equiaxed strain. This study provides theoretical guidance for obtaining K1-xNaxNbO3 epitaxial thin films with excellent properties.

The effect of cooling rate on the magnetorheological response was investigated for magnetic hydrogels consisting of carrageenan and carbonyl iron particles with a concentration of 50 wt.%. For magnetic gels prepared by natural cooling, the storage moduli at 0 and 50 mT were 3.7×104 Pa and 5.6×104 Pa, respectively, and the change in the modulus was 1.9×104 Pa. For magnetic gels prepared by rapid cooling, the storage moduli at 0 and 50 mT were 1.2×104 Pa and 1.8×104 Pa, respectively, and the change in the modulus was 6.2×103 Pa, which was 3.1 times higher than that for the magnetic gel of rapid cooling. The critical strains, where G‘=G“ on the strain dependence of the storage modulus, for magnetic gels of natural cooling and rapid cooling were 0.023 and 0.034, respectively, indicating that the magnetic gel of rapid cooling has a hard structure compared to that of natural cooling. Oppositely to this, the change in the storage modulus at 500 mT for the magnetic gel of rapid cooling was 1.6×105 Pa, which was 2.5 times higher than that of natural cooling. SEM images revealed that many small aggregations of carrageenan network were found in the magnetic gel of natural cooling and continuous phases of carrageenan network with large sizes were found in the magnetic gel of rapid cooling. It was revealed that, magnetic particles in the magnetic gel of rapid cooling can move and form a chain structure at high magnetic fields by breaking the restriction from the continuous phases of carrageenan.

Skin cancer is a condition characterized by the abnormal growth of skin cells, primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Different types of skin cancer include melanoma, basal cell carcinoma, and squamous cell carcinoma. Despite the advancements in targeted therapies, there is still a need for a safer, highly efficient approach to preventing and treating cutaneous malignancies. Spices have a rich history dating back thousands of years and are renowned for their ability to enhance the flavor, taste, and color of food. Derived from various plant parts like seeds, fruits, bark, roots, or flowers, spices are important culinary ingredients. However, their value extends beyond the culinary realm. Some spices contain bioactive compounds, including phenolic compounds, which are known for their significant biological effects. These compounds have attracted attention in scientific research due to their potential health benefits, including their possible role in disease prevention and treatment, such as cancer. This review focuses on examining the potential of spice-derived phenolic compounds as preventive or therapeutic agents for managing skin cancers. By compiling and analyzing the available knowledge, this review aims to provide insights that can guide future research in identifying new anticancer phytochemicals and uncovering additional mechanisms for combating skin cancer.

Trichinella spiralis (T. spiralis), a nematode parasite, is the major cause of Trichinellosis, a zoonotic disease. A key role of MAPR in the reproductive system is to maintain pregnancy. Previous studies found antihormone (P4 and RU486) drug design and vaccine therapy of recombinant protein (rTs-MAPRC2) to control T. spiralis infection. The current study investigates the inhibitory effects of different ratios of antibody against Ts-MAPRC2 on the development of muscle larvae (ML) and newborn larvae (NBL). First, we performed indirect immunofluorescence assays (IIFA) and examined the effects of rTs-MAPRC2-Ab on ML and NBL in vitro as well as in vivo. After-ward, siRNA-Ts-MAPRC2 was transfected into T. spiralis muscle larvae. Following that, Ts-MAPRC2 protein was detected by Western Blotting and mRNA levels were determined by qPCR. Also, we assessed whether siRNA-treated NBLs were infective by analyzing muscle larvae burden (MLs). Our Result showed rTs-MAPRC2-Ab greatly inhibited the activity of the Ts-MAPRC2 gene in ML and NBL of T. spiralis. rTs-MAPRC2-Ab reduced larval infectivity and survival in the host in a dose-dependent manner (1:50, 1:200, 1:800 dilutions). Further, siR-NA-Ts-MAPRC2 effectively silenced the Ts-MAPRC2 gene in muscle larvae (ML) by in vitro, as well as in new-born larvae (NBL) of T. spiralis by in vivo. In addition, siRNA-Ts-MAPRC2 (siR-NA180, siRNA419, siRNA559) reduced host larval survival and infectivity significantly. The effect of siRNA on larval development, survival, and infectivity was significantly reduced when the Ts-MAPRC2 gene was knocked down. This study, therefore, suggests that Ts-MAPRC2 might be a novel molecular target that might be useful in the development of vaccines against T. spiralis infection.

In order to effectively utilize red mud, an aluminum industrial waste, the stabilized soil material was developed using nano-SiO2 synergistically modified red mud, and the strength characteristics of the stabilized soil were analyzed to clarify the feasibility of such stabilized soil serves as a road base material. Through different combination schemes, the effects of different nano-SiO2 and cement contents on the strength of the stabilized materials were explored. The test results show that: in the synergistic modification of nano-SiO2 and cement, nano-SiO2 can significantly improve the early unconfined compressive strength of red mud-based stabilized soil; in the synergistic modification of nano-SiO2, gypsum and cement, the 7-d unconfined compressive strength of red mud-based stabilized soil is greater than 2 MPa, which meets the strength requirements of road base materials and shows the superiority of synergism. The nominal stress-strain curves are divided into five stages: compressed and compacted stage, elastic deformation stage, plastic deformation stage, damage deformation stage and residual deformation stage. The macroscopic compressive damage pattern of the specimens shows that the modified red mud-based stabilized soil mostly exhibits brittle damage.

Air pollution is an important factor affecting human health and daily life. Chinese government is making vigorous efforts to control air pollution. The upgrading of industrial structure is a problem-solving tool in environment and economic growth cases. This paper aims to explore the relationships among environmental regulation, the upgrading of industrial structure and air pollution. The PVAR (Panel Vector Auto Regression) model and moderation effect model has been used to conduct empirical analysis based on panel data of 30 provinces in China from 2004 to 2020. The results of analysis indicate (1) the environmental regulation can significantly reduce the air pollution, but the deterioration of air quality could not effectively influence environmental regulations. (2) The upgrading of industrial structure can weaken the air pollution and air pollution hinders the upgrading of industrial structure. (3) With the improvement of environmental regulation, the industrial structure is constantly upgraded, but the upgrading of the industrial structure has a negative effect on the improvement of environmental regulation. (4) The upgrading of industrial structure can positively moderate the influence of environmental regulation on air pollution.

This study, based on the AISAS model, explores the impact of the interaction effect between visual and auditory signals on consumer purchase behavior. Using experimental methods, 120 participants were randomly assigned to four different visual and auditory signal combinations, and their purchase intentions and actual purchase behavior were measured. The results show that the interaction effect between visual and auditory signals has a significant impact on both purchase intentions and actual purchase behavior, and there is a significant positive relationship. Specifically, when visual and auditory signals are mutually consistent, consumers have the highest purchase intentions and actual purchase behavior; when both visual and auditory signals are absent, consumers have the lowest purchase intentions and actual purchase behavior; when either the visual or auditory signal is missing, consumers' purchase intentions and actual purchase behavior are in between the two extremes. This study provides a new perspective for understanding consumers' decision-making processes in multi-sensory environments and offers valuable insights for the development of marketing strategies.

Germanium is an essential microelement, and its deficiency can result in numerous diseases, particularly oncogenic conditions. Consequently, water-soluble germanium compounds, including inorganic and coordination compounds, have attracted significant attention due to their biological activity. The review analyzes the primary research from the last decade related to the anticancer activity of germanium compounds. Furthermore, the review clarifies their actual toxicity, identifies errors and misconceptions that have contributed to the discrediting of their biological activity, and suggests a putative mechanism of germanium-mediated protection from oxidative stress. Finally, the review provides clarifications on the discovery history of water-soluble organic germanium compounds, which was distorted and hushed up for a long time.

Recycling of metallurgical solid waste has intriguing increasing attention for fabricating cementitious materials, due to its low-carbon emission, cost-effectiveness, and environmental conservation. Herein, the effects of silica fume (SF) on the microstructure and mechanical properties of alkali-activated slag/FA (fly ash) pastes subjected to elevated temperatures (150, 500, 850, and 1200℃) are investigated, to clarify the fact that whether or not the SF generates positive roles in mechanical properties of slag/FA geopolymers. The results show that the replacement with 10 wt% SF (silica fume) promotes the increasing pore volume with a diameter of 0.2~3 μm at room temperature, leading to an increase in the compressive or flexural strength, “right shifts” of endothermic peak and the initial-final temperature of mass loss, presenting a denser and compact fracture surface. Meanwhile, the mineral phase of gehlenite and labradorite emerges after exposure above 850℃ from the XRD results. Furthermore, the bloating effect of the incorporated SF occurs due to the formation of a liquid phase altogether with the amorphous silicates after exposure to 1200℃, leading to a greater deformation and enhancement of restructuring involved in the [SiO4]4− and [AlO4]5−. It explores an effective recycling approach for fabricating paste binders using metallurgical solid wastes.

A variant of the von Neumann-Wigner Interpretation is proposed. Problems arising from the quantum Zeno effect are addressed as we have described previously. We do, however, offer some new, and perhaps unexpected observations. We are accustomed to thinking of wave function collapse as occurring consequent to laboratory measurements. We speculate that, whatever physical correlate of consciousness exists within the brain, it is quantum mechanical in the sense that a brain, left to itself, would eventually decohere into a state no longer compatible with its conscious functioning. Wave function collapse returns it to a state compatible with consciousness. Indeed, this may be its important reason for occurring. A universe without it simply could not play host to conscious brains. The fact that it also prevents us from encountering "absurd" situations in the laboratory is merely a fortunate dividend. Whenever a quantum measurement is made the universe's future history splits into a number of possibilities. This number may be very large or infinite. And we believe consciousness plays a vital role in this happening. A "conscious" universe where quantum measurements are being made allows for an enormous number of equally acceptable world-histories. An "unconscious" one, always evolving in a unitary fashion, allows for only one. If we assume that the decision as to which worldhistory is the real one (i.e. this one) is made at random we see that the universe is overwhelmingly more likely to be "conscious" than not.

Prostate Cancer (PCa) is still ranked as the first cancer in male population and evidences have suggested an alteration of glycemic and lipidic metabolism that are related to its progression and prognosis. Aim of the study is to investigate associations between enzymes’ expression, especially involved in the lipidic pathway, and PCa aggressiveness. We retrospectively analyzed data from 390 patients with PCa or benign prostatic hyperplasia (BPH) at the Department of Urology, University of Catania. Immunohistochemical slides were evaluated for the expression of proteins related to glucose and lipidic metabolism. A total of 286 were affected by PCa while 104 by BPH. We demonstrated that ATP-lyase (odds ratio [OR]: 1.71; p<0.01), fatty acide sinthase (OR: 4.82; p<0.01), carnitine palmitoyl transferase-1a (OR: 2.27; p<0.05) were associated with androgen receptor (AR) expression. We found that steaoryl Co-A desaturase expression in PCa patients with total cholesterol ≥ 200 mg/dl was independently associated with ISUP ≥4 (OR: 4.22; p=0.049). We found that CPT-1a+ was associated with biochemical recurrence (hazard ratio: 1.94; p=0.03]). Our results support the evidences that the manipulation of lipidic metabolism could serve in the future to contrast PCa progression.

Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigated the relationship between the symbiotic units, environments, models, and effects of the integration of medical and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects for on this integration. Results: The path coefficient of symbiotic unit on the symbiosis model was 0.46 (p<.001), the path coefficient of symbiotic environment on symbiosis model was 0.52 (p<.001). The path coefficient of the symbiotic unit and environment was 0.91 (p<.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that Health policy-makers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical and disease prevention in public hospitals.

The results of the study of the influence of the size of cylindrical samples of A5N aluminum on the time and rate of their cooling are presented. According to experimental data, the temperature dependence of the heat transfer coefficient for pure metals is calculated. It revealed that the process of cooling of the aluminium and its alloys has a relaxation behavior. It has found that the main mechanisms of natural air cooling are convection heat transfer and radiation. The characteristic cooling time due to radiation is less than due to convection. The contribution of thermal radiation is noticeable at high temperatures. It was found that the characteristic times of cooling due to radiation and convection increase with increase in volume to area ratio of the sample.

To mitigate lithium dissolution and polysulfide shuttle effect phenomena in high energy lithium sulfur batteries (LISBs), a conductive, flexible, and easily modified polymer composite layer was applied on the anode. The polymer composite layer includes polyaniline and functionalized graphite. The electrochemical behavior of LISBs was studied by galvanostatic charge/discharge tests from 1.7 to 2.8 V up to 90 cycles and via COMSOL Multiphysics simulation software. No apparent overcharge occurred during the charge state, which suggests that the shuttle effect of polysulfides was effectively prevented. The COMSOL Multiphysics simulation provides a venue for optimal prediction of the ideal concentration and properties of the polymer composite layer to be used in the LISBs. The testing and simulation results determined that the polymer composite layer diminished the amount of lithium polysulfide species and decreased the amount of dissolved lithium ions in the LISBs. In addition, the charge/discharge rate of up to 2.0 C with a cycle life of 90 cycles was achieved. The knowledge acquired in this study was important not only for the design of efficient new electrode materials, but also for understanding the effect of the polymer composite layer on the electrochemical cycle stability.

A highly sensitive strain sensor based on tunable cascaded Fabry-Perot interferometers (FPIs) is proposed and experimentally demonstrated. Cascaded FPIs consist of a sensing FPI and a reference FPI which effectively generate the Vernier Effect (VE). The sensing FPI comprises a hollow core fiber (HCF) segment sandwiched between single-mode fibers (SMFs), and the reference FPI consists of a tunable air reflector, which is constituted by a computer programable fiber holding block to adjust the desired cavity length. Simulation results predict the dispersion characteristics of modes carried by HCF. The sensor’s parameters are designed corresponding to a narrow bandwidth range, i.e., 1530 nm to 1610 nm. Experimental results demonstrate that the proposed sensor exhibits optimum strain sensitivity of 23.9 pm/με in the range of 0 to 3000 με which is 13.73 times higher than the single sensing FPI strain sensitivity of 1.74 pm/με. The strain sensitivity of the sensor can be further enhanced by extending the source bandwidth. The proposed sensor exhibits ultra-low temperature sensitivity of 0.49 pm/°C in the wider temperature range of 25 °C to 135 °C, providing good isolation for eliminating cross-talk between strain and temperature. The sensor is very robust, cost-effective, easy to manufacture, repeatable, and shows a highly linear and stable response in the wider range of axial strain. Based on the sensor’s performance, it may suit plenty of practical applications in the real sensing world

Saturated lights appear brighter than white lights of the same luminance. This phenomenon is known as the Helmholtz-Kohlrausch (H-K) effect and can be estimated by modeling achromatic luminance and saturation to total brightness. These models have been shown to differ between women and men and are more variable in women. The variation in brightness models among women may be due to hormonal changes across the menstrual cycle. To test this, total brightness and achromatic luminance were measured across blue, green, yellow-green, yellow, and red hues. These data were measured along with salivary hormone levels for nine cycling women at points representing the menstrual, peri-ovulation, and luteal phases. These data were also collected for seven oral contraceptive (OC) users. There were no main effects of OC use nor menstrual cycle phase on B/L ratios, but ratios were higher for the red stimulus in cycling women than OC users. Red B/L ratios were also higher for cycling women than OC users during the luteal phase. Estrogen, progesterone, and their interaction predicted 18% of the variation in brightness for cycling women. These models could not be fit for OC users, and estrogen only accounted for 5% of brightness variance with progesterone terms omitted. These findings and potential mechanisms are discussed in the context of previous results.

A paradigm shift away from null hypothesis significance testing seems in progress. Based on simulations, we illustrate some of the underlying motivations. First, P-values vary strongly from study to study, hence dichotomous inference using significance thresholds is usually unjustified. Second, statistically significant results have overestimated effect sizes, a bias declining with increasing statistical power. Third, statistically non-significant results have underestimated effect sizes, and this bias gets stronger with higher statistical power. Fourth, the tested statistical hypotheses usually lack biological justification and are often uninformative. Despite these problems, a screen of 48 papers from the 2020 volume of the Journal of Evolutionary Biology exemplifies that significance testing is still used almost universally in evolutionary biology. All screened studies tested default null hypotheses of zero effect with the default significance threshold of p = 0.05, none presented a pre-specified alternative hypothesis, pre-study power calculation, and the probability of ‘false negatives’(beta error). The results sections of the papers presented 49 significance tests on average (median 23, range 0–390). Of 41 studies that contained verbal descriptions of a ‘statistically non-significant’ result, 26 (63%) falsely claimed the absence of an effect. We conclude that studies in ecology and evolutionary biology are mostly exploratory and descriptive. We should thus shift from claiming to ‘test’ specific hypotheses statistically to describing and discussing many hypotheses (possible true effect sizes) that are most compatible with our data, given our statistical model. We already have the means for doing so, because we routinely present compatibility (‘confidence’) intervals covering these hypotheses.

(1) Background: Health Care-Associated Infections (HAIs)are a significant public health problem worldwide favoring multidrug-resistant (MDR) microorganisms. The SARS-CoV-2 infection had a negative association with the increase in antimicrobial resistance, and the ESKAPE group had the most significant impact on HAIs. The study aimed to evaluate the bactericidal effect of high concentration O3 gas on some reference and ESKAPE bacteria. (2) Material and Methods: Four standard strains and four clinical or environmental MDR strains were exposed to high ozone doses at different concentrations and times. Bacterial inactivation (growth and cultivability) was investigated using colony counts and resazurin as a metabolic indicator. Scanning electron microscopy (SEM) was performed. (3) Results: The culture exposure to a high level of O3 inhibited the growth of all bacterial strains tested with a statistically significant reduction in colony count compared to the control group. The cell viability of S. aureus (MRSA) (99,6%) and P. aeruginosa (XDR) (29,2%) was reduced considerably, and SEM showed damage on bacteria after O3 treatment (4) Conclusion: High doses of ozone were able to interfere in the growth of all strains studied, evidencing that ozone-based decontamination approaches may represent the future of hospital cleaning methods.

In the past years, our knowledge of coastal environments has been enriched by remotely sensed data. However, to successfully extract information from a combination of different sensors systems, it should be understood how these interact with the common coastal environment. In this research we co-analyze two sensor systems: Terrestrial Laser Scanning (TLS) and satellite based Synthetic Aperture Radar (SAR). TLS shows large potential for examining coastal processes thanks to the possibility to retrieve repeated, accurate and dense topographic information in a rapid and non-invasive manner. However, TLS presents some limits due to its high economic costs and limited field of view. SAR systems are among the most used active remote sensor system for Earth Observation. Despite their relatively low resolution, SAR systems provide the ability to monitor and map coastal areas with complete, repeated and frequent coverage, penetrating through clouds and providing all weather monitoring. Moreover, Sentinel-1 SAR images are freely available. The availability of a permanently installed TLS system (PLS, Permanent Laser Scanner) allows us, to extensively compare Sentinel-1 SAR data and topographic laser scans during different conditions on a sandy beach. PLS data are compared with simultaneous Sentinel-1 SAR images in order to investigate the combined use of PLS and SAR in coastal environments. The purpose of this comparison is the investigation of a possible relation between PLS and SAR data: knowing their relation, SAR dataset could be correlated to beaches characteristics. Meteorological and surface roughness have also been taken into consideration in the evaluation of the correlation between PLS and SAR data. The permanently installed laser scanner for the present study is located in Noordwijk (the Netherlands). A generally positive but low correlation exists between the two variables. When considering weather phenomena, their correlation increases and shows a dependence on wind directions and speed. The correlation with the surface roughness, evaluated in terms of root-mean squared height, also depends on specific wind speed and directions.

Synthetic cannabinoids are a series of synthetic substances that mimic the effects of natural cannabinoids and produce a much stronger toxicity than natural cannabinoids, which have become the most abused family of new psychoactive substances. A solid-phase extractive-liquid chromatography-triple quadrupole/linear ion trap mass spectrometry method was developed to determine 11 synthetic cannabinoids in rat urine. The factors affecting recovery were optimized, and Oasis HLB was selected to extract synthetic cannabinoids simultaneously. The results showed that the linear correlation coefficients of the synthetic cannabinoids ranged from 0.993 to 0.999, and the limit of quantitation ranged from 0.01 to 0.1 ng/mL, and the spiked recoveries ranged from 69.90% to 118.39%. This method has the advantages of good purification ability, simple operation, and good reproducibility, and can be used for the high sensitivity analysis of various synthetic cannabinoids in urine.

Positive education is seen as a transformative methodological approach capable of improving the act of teaching and learning and, above all, essential for the development of students' personal skills and competences. However, few studies have been carried out on this subject in the field of lifelong and adult education. This study works with a sample of 399 people over 16 years of age and students of the Universidad Popular de Dos Hermanas in order to show the relationship between the Pygmalion effect and learned helplessness in the process of acquiring knowledge in adulthood. In this way, three tools were used: a questionnaire that showed teachers' perceptions of students' qualities and behaviour and two that provided information on self-concept, self-esteem, personal and social skills and other variables directly related to emotional intelligence and positive education. It shows how exposure to negative operational conditioning factors influences the psychosocial and socio-educational development of students in every possible way, while on the other hand, it indicates the importance of positive education to compensate for this phenomenology by improving the development and growth of those who study and participate in non-formal education. Likewise, the factorial interrelation of both positive and negative conditioning factors and their incidence on learning is shown; the importance of neutralising the negative components and strengthening the positive reinforcement and the role played by the community and education professionals as catalysts and behavioural modulators at any stage of learning and age group for the achievement of the objectives of the student and of education itself in a broad sense

Staphylococcus aureus can develop resistance by mutation, tranfection or biofilm formation. Resistance was induced in S. aureus by growth in sub-inhibitory concentrations of ciprofloxacin for 30 days. The ability of the antimicrobials to disrupt biofilms was determined using crystal violet and live/dead staining. Effects on the cell membranes of biofilm cells was evaluated by measuring release of dyes and ATP and nucleic acids. S. aureus did not develop resistance to the AMPs but resistance increased to ciprofloxacin by 128 times after 30 passages. Only peptides reduced biofilms of ciprofloxacin resistant cells. The antibiofilm effect of melimine with ciprofloxacin was more (27%) than with melimine alone at 1X MIC (p < 0.001). Similarly, at 1X MIC the combination of Mel4 and ciprofloxacin produced more (48%) biofilm disruption than Mel4 alone (p < 0.001). Combinations of either of the peptides with ciprofloxacin at 2X MIC released  66 nM ATP, more than either peptide alone (p  0.005). At 2X MIC, only melimine in combination with ciprofloxacin released DNA/RNA which was 3 times more than released by melimine alone (p = 0.043). These results suggest the potential use of melimine and Mel4 with conventional antibiotics for the treatments of S. aureus biofilms.

We report that ethanol, used together with water, plays a crucial role in tuning the structures of a zirconium-based Metal-Organic Framework, the 12-connected MOF-801, and the possible mechanisms of this modulating effect. By employing the cosolvent system of ethanol and water just under room temperature without the presence of a monotopic carboxylic acid as the modulator, MOF-801 in various morphologies of different sizes can be synthesized. The linear correlation between the ethanol/water ratio and the crystal sizes is also demonstrated. The growth mechanism is mainly explained by ethanol’s binding with the metal ion clusters and the Marangoni Flow Effect. Ethanol competes with the linker molecules in coordinating with the Zr metal clusters, a role similar to that of the modulators. The Marangoni Flow Effect, which dominates at a certain solvent ratio, further promotes the 1-D alignment of the MOF-801 crystals.

Abstract:Global ship demolition is mostly concentrated in south Asian countries, namely Bangladesh, India, Pakistan and China, since 1990’s, having competitive advantage for their high natural tide, and low environmental and social costs. Due to high social and environmental externalities, stakeholders increase monitoring of the externalities and continue to prescribe improvement towards sustainability, which put pressures on profitability and competitiveness. As a consequence, also seen in the past, a leakage effect may emerge, leading to shift of this activity to a region, with relatively less monitored and less stricter on social and environmental impacts. Unfortunately, the leakage effect is never predicted in shipbreaking in order to understand the level of push compatible in the given socio-economic contexts. In this study, we have attempted to predict the future ship demolition landscape, applying machine learning technique to 34,531 in-service vessels worldwide, larger than 500 gross tonnage (GT), which is run against a learning model based on 3500 demolished vessels from 2014. This study shows that redistribution may occur among the top recycling nations: India may emerge out to be a dominant player in shipbreaking, surpassing Bangladesh by a margin of two-fold, while Pakistan and China are in decreasing trend. In addition, the leakage effect is observed, in that Vietnam is predicted to be the fourth largest ship demolition country, while China and Pakistan recede from the third and fourth place to 6th and 8th. Turkey is predicted to advance from fifth position to third position by vessel count but stays same in term of total GT dismantled. Although it is not clear if any leakage is to be observed in the near future, this study may be a model for future predictive analytics and help stakeholders take evidence-based business decisions.

Thermal shape memory polymers (SMPs) find increasing applications in biology and medicine due to their promising potential for improved biocompatibility. In such applications, the inevitable penetration of small molecules from the ambient fluid into the polymer influences the shape recovery process and often leads to a reduction of the temperature, at which shape recovery takes place. We show here via molecular dynamics simulations that the size of additive molecules plays a key role for this process. While the effect of concentration on the recovery rate is monotonic in the investigated range, a non-monotonic dependence on the size of additive molecules emerges at temperatures close to the glass transition. This work thus identifies the additives’ size to be a qualitatively novel parameter for switching the recovery process in polymer-based shape memory materials.

Currently, the use of sustainable chemistry as an ecological alternative for the generation of products or processes, free of polluting substance has assumed a preponderant role. The aim of this work is propose a bioinspired, facile, at low cost, non-toxic and environmentally friendly alternative to obtaining magnetic nanoparticles whit a majority phase of magnetite (Fe₃O₄). Is important to empathize that the synthesis was based on the chemical reduction through the Cnicus Benedictus extract, whose use as reducing agent has not been reported in the synthesis of iron oxides nanoparticles. In addition, the Cnicus Benedictus is abundant endemic plant in Mexico, with several medicinal properties and a large number of natural antioxidants. The obtained nanoparticles exhibited significant magnetic and antibacterial properties and an enhanced photocatalytic activity. The crystallite size of the Fe₃O₄ nanoparticles (Fe₃O₄ NP’s) was calculated by Williamson-Hall method. The photocatalytic properties of the Fe₃O₄ NP´s were studied by kinetics absorptions models in the Congo red (CR) degradation. Finally the antibacterial effect of the Fe3O4 NP´s were evaluated mediated the Kirby-Bauer method against E. coli and S. aureus bacteria. This route offers a green alternative to obtain Fe3O4 NP´s with remarkable magnetic, photocatalytic and antibacterial properties.

Ethnopharmacological relevance: Novel coronavirus disease (COVID-19) outbroke in Wuhan has imposed a huge influence onto the society in term of the public heath and economy. However, so far, no effective drugs or vaccines have been developed. Whereas, the Traditional Chinese Medicine (TCM) has been considered as a promising supplementary treatment for the disease owing to its clinically proven performance on many diseases even like severe acute respiratory syndrome (SARS). Meanwhile, many side-effect (SE) reports suggest the SE of the TCM prescriptions cannot be ignored in curing the COVID-19, especially because COVID-19 always simultaneously leads to dramatic degradation of the patients’ physical condition. How to evaluate the TCM regarding to their latent SE is a urgent challenge. Aim of the study: In this study, we use an ontology-based side-effect prediction framework (OSPF) developed in our previous work and Artificial Neural Network (ANN)-based deep learning to evaluate the TCM prescriptions that are officially recommended in China for novel coronavirus (COVID-19). Materials and methods: Firstly, we adopted the OSPF developed in our previous work, where an ontology-based model separate all the ingredients in a TCM prescription into two categories: hot and cold. Then, we established a database by converting each TCM prescription into a vector containing the ingredient dosage and the according hot/cold attribution as well as the safe/unsafe label. And, we trained the ANN model using this database, after which a safety indicator (SI), as the complementary percentage of side-effect (SE) possibility, is then given for each TCM prescription. According to the proposed SI from high to low, we re-organize the recommended prescription list. Secondly, by using this method, we also evaluate the safety indicators of some other famous TCM prescriptions that are not in the recommended list but are used traditionally to cure flu-like diseases for extending the potential treatments. Results: Based on the SI generated in the ANN model, FTS, PMSP, and SF are the safest ones in recommended list, which all own a more-than-0.8 SI. Whereas, JHQG, LHQW, SFJD, XBJ, and SHL are the prescriptions that are most likely unsafe, where the indicators are all below 0.2. In the extra list, the indicators of XC, XQRS, CC, and CHBX are all above 0.8, and at the meantime, XZXS, SJ, QW, and KBD’s indicators are all below 0.2. Conclusions: In total, there are seven TCM prescriptions which own the indicators more than 0.8, suggesting these prescriptions should be considered firstly in curing COVID-19, if suitable. We believe this work will provide a reasonable suggestion for the society to choose proper TCM as the supplementary treatment for COVID-19. Besides, this work also introduces a pilot and enlightening method for creating a more reasonable recommendation list of TCM to other diseases.

The measurement range of a conventional current sensor is narrow because it is used with signals relative to the rated values of the measurement range from a voltage-type device. Consequently, multiple current sensors must be used in accordance with the measurement range. To address this problem, this paper proposes a new current sensor with a clamp-shaped part for low current measurement and a simple straight structure for high current measurement. The output signals of the proposed current sensor are amplified with a Hall element using the magnetic force of a rectangular air gap inside the clamp. To verify the characteristics of the proposed current sensor, a current was applied to an external load, and the value determined by the current sensor noted. Then, electromagnetic field analysis was performed through current sensor modeling and the results obtained compared to the actual sensor results. The proposed sensor had a 1% linearity in the output signals and exhibited dynamic characteristics over a wide current range.

One ambitious objective of Integrated Computational Materials Engineering (ICME) is to shorten the materials development cycle by using computational materials simulation techniques at different length scales. In this regard, the most important aspects are the prediction of the microstructural evolution during material processing and the understanding of the contributions of microstructural features to the mechanical response of the materials. One possible solution to such a challenge is to apply the Phase Field (PF) method because it can predict the microstructural evolution under the influence of different internal or external stimuli, including deformation. To accomplish this, it is necessary to take into account plasticity or, specifically, non-homogeneous plastic deformation, which is particularly important for investigating the size effects in materials emerging at the micron length scale. In this work, we present quasi-2D simulations of plastic deformation in a face centred cubic system in a finite strain formulation. Our model consists of dislocation-based strain gradient crystal plasticity implemented into a PF code. We apply this model to study the influence of grain size on the mechanical behavior of polycrystals, which includes dislocation storage and annihilation. Furthermore, the initial state of the material before deformation is also considered. The results show that a dislocation-based strain gradient crystal plasticity model can capture the Hall-Petch effect in many aspects. The model reproduced the correct functional dependence of the flow stress of the polycrystal on grain size without assigning any special properties to the grain boundaries. However, the predicted Hall-Petch coefficients are significantly smaller than those found typically in experiments. In any case, we found a good qualitative agreement between our findings and experimental results.

Random copolymers made of both (PIM-polyimide) and (6FDA-durene-PI) were prepared for the first time by a facile one-step polycondensation reaction. By combining the highly porous and contorted structure of PIM (polymers with intrinsic microporosity) and high thermomechanical properties of PI (polyimide), the membranes obtained from these random copolymers [(PIM-PI)x-(6FDA-durene-PI)y] showed high CO₂ permeability (> 1047 Barrer) with moderate CO₂/N₂ (> 16.5) and CO₂/CH₄ (> 18) selectivity, together with excellent thermal and mechanical properties. The membranes prepared from three different compositions of two comonomers (1:4, 1:6 and 1:10 of x:y), all showed similar morphological and physical properties, and gas separation performance, indicating ease of synthesis and practicability for large-scale production. The gas separation performance of these membranes at various pressure ranges (100–1500 torr) was also investigated.

The reinforcement of concrete by using polyolefin fibres may be considered in structural design to meet the requirements of the applicable code rules. In order to achieve a reliable use of such a composite material, use of full-scale real structures is needed. The conversion of lab testing data into real practice properties is challenging and significantly influenced by various aspects, among which the size effect is a key one. Given that the available literature does not report coinciding conclusions about such an effect on quasi-brittle materials reinforced with fibres, further research is justified. Therefore, this work studies the behaviour of notched beams with three proportional sizes by using self-compacting polyolefin reinforced concrete with a fibre volume fraction of 1.1%. Flexural testing was carried out according to the standard EN-14651, with the results revealing the existence of the size effect. In addition, a reduction of the residual strength identified in the larger specimens was observed in fracture surfaces with equal fibre content.

The notion of the three-phase (line) tension remains one of the most disputable notions in the surface science. A very broad range of its values has been reported. Experts even do not agree on the sign of the line tension. The polymer-chain-like model of the three-phase (triple) line enables the rough estimation of the entropic input into the value of the line tension, estimated as Γ_en≅(k_B T)/d_m ≅〖10〗^(-11) N, where d_m is the diameter of the liquid molecule. The introducing of the polymer-chain-like model of the triple line is justified by the “water string” model of the liquid state, predicting strong orientation effects for liquid molecules located in the vicinity of hydrophobic moieties. The estimated value of the entropic input into the line tension is close to experimental findings, reported by various groups.

A variable annuity is a popular life insurance product that comes with financial guarantees. Using Monte Carlo simulation to value a large variable annuity portfolio is extremely time-consuming. Metamodeling approaches have been proposed in the literature to speed up the valuation process. In metamodeling, a metamodel is first fitted to a small number of variable annuity contracts and then used to predict the values of all other contracts. However, metamodels that have been investigated in the literature are sophisticated predictive models. In this paper, we investigate the use of linear regression models with interaction effects for the valuation of large variable annuity portfolios. Our numerical results show that linear regression models with interactions are able to produce accurate predictions and can be useful additions to the toolbox of metamodels that insurance companies can use to speed up the valuation of large VA portfolios.

The object of this study was to discover an alternative therapeutic agent with fewer side effects against acne vulgaris, which is one of the most common skin diseases. Acne vulgaris often associates with acne-related bacteria such as <i>Propionibacterium acnes</i>, <i>Staphylococcus epidermidis</i>, <i>Staphylococcus aureus</i> and <i>Pseudomonas aeruginosa</i>, some of which exhibit a resistant against commercial antibiotics used in the treatment of acne vulgaris (tetracycline, erythromycin, and lincomycin). In the current study, we evaluated <i>in vitro</i> antibacterial activity of chitosan-phytochemical conjugates against acne-related bacteria. Three of chitosan-phytochemical conjugates used in this study showed stronger antibacterial activity than that of chitosan (unmodified control). Chitosan-caffeic acid conjugate (CCA) exhibited the highest antibacterial activity against acne-related bacteria with minimum inhibitory concentration values of 8 μg/mL to 256 μg/mL. In addition, the MICs of antibiotics against antibiotic resistant <i>P. acnes</i> and <i>P. aeruginosa</i> strains were dramatically reduced in the combination with CCA, suggesting that CCA would restore the antibacterial activity of the antibiotics. The analysis of fractional inhibitory concentration indices clearly revealed a synergistic antibacterial effect between CCA and the antibiotics. Thus, the median ∑FIC values against the antibiotic resistant bacterial strains were ranged from 0.375 to 0.533 in the combination mode of CCA and antibiotics.

The intention of this paper is to elucidate new types of heat engines with extraordinary efficiency, more specifically to eventually focus on the author’s research into a temporary magnetic remanence device. First we extend the definition of heat engines through a diagrammatic classification scheme and note a paradoxical non-coincidence between the Carnot, Kelvin-Planck and other forms of the 2nd Law, between sectors of the diagram. It is then seen, between the diagram sectors, how super-efficient heat engines are able to reduce the degrees of freedom resulting from change in chemical potential, over mere generation of heat; until in the right sector of the diagram, the conventional wisdom for the need of two reservoirs is refuted. A brief survey of the Maxwell Demon problem finds no problem with information theoretic constructs. Our ongoing experimental enquiry into a temporary magnetic remanence cycle using standard kinetic theory, thermodynamics and electrodynamics is presented – yet a contradiction results with the 2nd law placing it in the right sector of the classification diagram.

As the largest energy consumer and carbon emitter, China has made substantial efforts to improve energy efficiency for decrease energy consumption, while the energy rebound effect determines its effectiveness. The embodied energy consumption of construction projects accounted for nearly one-sixth of the total economy's energy consumption in China. This paper is based on the logical relationship among capital input, technological progress, economic growth, and energy consumption, adapting an alternative estimation model to estimate the energy rebound effect for the construction industry in China for the first time. Empirical results in our paper reveal that the energy rebound effect for the construction industry in China is about 59.5% for the period of 1990–2014. The results indicate that the energy rebound effect does exist in China’s construction industry and it presented a fluctuating declining trend. This implies that half of the energy savings by technological progress is achieved. In addition, China’s government should implement proper energy pricing reforms and energy taxes to promote the sustainable development of China’s construction industry.

China is striving to leverage the power of science and technology to green its agriculture while increasing grain productivity. In this context, this study presents the green growth rate of agriculture from the DEA-based Green Total Factor Productivity (GTFP) indicator, together with the growth rate of grain yields, and applies it to the case of Jiangsu, a major grain-producing province with a well-developed economy. It is found that Jiangsu's agriculture has generally performed well in the implementation of the two major national strategies of green development and grain security, especially in the northern Jiangsu, which is a major grain-producing area. In contrast, the phased fluctuations of green growth in agriculture in Southern Jiangsu are more pronounced, with even negative green growth occurring during the green agriculture movement. Much of the volatility in agricultural green growth at the provincial, subregional, municipal level comes from the effects of the movement of the green technology frontier led by best practitioners. Accordingly, the possibility of improving the weak state of the catch-up effect on green growth is explored from the perspective of the Chinese government-led agricultural science and innovation system; it also traces the green agricultural initiatives in the main grain-marketing areas that have failed to deliver the expected green growth, and recommends a review of such policies and refinement of the GTFP Index tool for assessing sustainable green growth.

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.

In this paper, the feasibility and potential assessment (PA) of wind power in six different areas MehalMeda, Eneware, DebreBerhan, AlemKetema, GundoMekel, and Majet are investigated. The data is collected from the National Metrological Agency (NMA) in Addis Ababa and from the districts of the case study areas and analyzed using MATLAB and HOMER software. Using the data collected at 10 meter height, wind direction using a wind rose, the wind frequency distribution, and wind turbine characteristics have been analyzed. Moreover, to obtain a more realistic wind potential study, the wind speed at a 10 meter height is extrapolated to a height of 50 meter in order to determine wind speed, wind power density, and wind energy density. The average wind speed of the zone at 10m and 50m heights are 1.58 m/s and 1.99 m/s, 3.06 m/s and 3.85 m/s, 4.75 m/s and 5.98 m/s, 2.29 m/s and 2.88 m/s, 1.01 m/s and 1.27 m/s and 4.07 and 5.12m/s at Alemketema, Debreberhan, Eneware, Gundemeskel, Majete and Mehalmeda respectively. The extrapolated result shows that the maximum wind speed and power densities at a height of 50 meter for Eneware, MehalMeda and Debre Berhan are 10.4 m/s, 689 W/m2, 8.9m/s, 429 W/m2 and 6.3m/s, 152.2 W/m2 respectively. The energy densities at a height of 50 meter for AlemKetema, DebreBerhan, Eneware, GundoMekel, Majete, and MehalMeda are 181.06 kWh/m2*yr , 1332.83 kWh/ m2*yr, 6078.91 kWh/ m2*yr, 857.76 kWh/ m2*yr, 58.78 kWh/ m2*yr, and 3939.42 kWh/ m2*yr respectively. As per the international standard for wind power and wind speed classification, considering the extrapolated height, Eneware, MehalMeda, and DebreBerhan have feasible wind potential for both small-scale and large-scale wind farm implementation, whereas Majete, AlemKetema, and GundoMeskel of the North Shewa Zone in the Amhara region have poor wind potential.

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen enriched compressed natu-ral gas (HCNG). It is also injected into the natural gas pipeline network to realize the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load peak and trough period is adjusted, and large-scale consumption of renewa-ble energy and the reduction of carbon emissions are realized. First of all, a fine model of hydro-gen production and hydrogen use equipment is established to analyze the impact of adding hy-drogen mixing on the economy and low-carbon of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utiliza-tion rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment opera-tion cost, carbon emission cost, wind curtailment cost and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natu-ral gas was established. The model was linearized and solved by using MATLAB and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.

Previous studies have demonstrated that cold pools play a pivotal role in the initiation and organization of convection, yet their influence on the evolution of GFs remains inadequately understood. A destructive wind event associated with a rearward gust front (RGF, 8 grade gale appeared after passing GF) and a prior gust front (PGF, 10 grade gale appeared before passing GF) over the north coast of China on 10 June 2016 was analyzed. Using multiple observation data as well as the four-dimensional Variational Doppler Radar Data Assimilation System (VDRAS), we found that the intensity of the GFs increased with increasing cold pool strength, depth and propagation speed. Two schematic models were proposed to explain the discrepancy between GFs and associated cold pools. The depth and intensity of the cold pool in RGF are found to be relatively shallower and weaker, leading to a correspondingly reduced strength in both outflow and convergence. In contrast, the enhanced vertical shear and boundary northeaster inflow of PGF generate intensified and more organized downdrafts, resulting in a deeper cold pool, robust outflow, and convergence. These findings offer novel insights into the diversity of GFs and associated cold pools.

A new layout optimization method for offshore wind farms is proposed to minimize power deficits due to wake effect. The main engine of the algorithm is a gradient-descent method, in which an analogy is established between power deficit and repulsive electrostatic potential energy. To achieve a maximum dispersion in the initial solution, throughout the optimization process, new turbines are included in the centre of the concession area, and quickly expand outward looking for areas with less potential, in turn pushing the previous ones. When the optimization process ends, to avoid local maximums, it enters into a process of suppression of the set of locations that cause the greatest potential (power deficit). Then, a potential map of the entire area is created and a greedy algorithm includes new turbines to complete the layout with the final number of turbines. To speed up the search process and the creation of the potential map, two simplifications have been validated and added: the spatial distribution of velocities has been converted into its equivalent with point symmetry; and, for turbines affected by multiple wakes, the power deficit has been calculated by using a linear aggregation of powers, instead of the usual linear (or quadratic) aggregation of speeds. Owing to this type of aggregation, the process is accelerated in a factor of 90.

A Savonius wind turbine is one of the simplest vertical-axis turbines. Several researchers have been attracted to it because of its simple structure, low noise, appropriate torque, and independence from wind direction. SR3345 and SR5050 blade profiles will be investigated for their effects on the performance of Savonius wind turbines. First, the fabricated wind turbine is placed in front of an open circuit wind tunnel with a velocity of 6 m/s. Furthermore, governing relationships are used to calculate power and torque coefficients as well as tip speed. In this study, the power and torque coefficients of the turbine are compared with the two profiles considered based on overlap ratios between 0 and 0.3. Despite its increased stability, the central shaft reduced the power coefficient of the turbine. For blade SR3345, the best performance occurs at tip speed ratios of less than 1, while for blade SR5050, the best performance occurs at higher tip speed ratios. Both blades SR3345 and SR5050 achieve the highest power coefficients at overlap ratios of 0 and 0.18 when a central shaft is present.

This research paper presents a comprehensive study on the optimal planning and design of hybrid renewable energy systems for microgrid (MG) applications at Oakland University. The HOMER Pro platform analyzes the technical economic and environmental aspects of integrating renewable energy technologies. The research also focuses on the importance of addressing unmet load in the MG system design to ensure the university's electricity demand is always met. By optimizing the integration of various renewable energy technologies, such as solar photovoltaic (PV), energy storage system (ESS), combined heat and power (CHP), and wind turbine energy (WT), the study aims to fulfill the energy requirements while reducing reliance on traditional grid sources and achieving significant reductions in greenhouse gas emissions. The proposed MG configurations are designed to be scalable and flexible, accommodating future expansions, load demands changes, and technological advancements without costly modifications or disruptions. By conducting a comprehensive analysis of technical, economic, environmental factors, and addressing unmet load, this research contributes to the advancement of renewable energy integration within MG systems. It offers a complete guide for Oakland University and other institutions to effectively plan, design and implement hybrid renewable energy solutions, fostering a greener and more resilient campus environment. The findings demonstrate the potential for cost-effective and sustainable energy solutions, providing valuable guidance for Oakland University in its search of energy resilience and environmental surveillance which has a total peak load of 9.958MW. The HOMER simulation results indicate that utilizing all renewable resources, the estimated net present cost (NPC) is a minimum of 30M$, with a levelized energy cost (LCOE) of 0.00274$/kWh. In addition, the minimum desired load will be unmeted on some days of September.

The accurate of model attitude angel plays an important role on the aerodynamic test results in the wind tunnel test. The original method applies the spherical coordinate system transformation to obtain attitude angel calculation. The model attitude angel is obtained by coordinate transformation and spherical surface mapping applying the nominal attitude angel (the balance attitude angel in the wind tunnel coordinate system) indicated by the mechanism. First, the coordinate transformation of this method is not only complex but also difficult to establish the transformed relationship between the space coordinate systems especially after many steps of coordinate transformation, moreover it cannot realize the iterative calculation of the interference relationship between attitude angels; Second, during the calculate process to solve the problem the arc is approximately used to replace the straight line, the angel for the tangent value, and the inverse trigonometric function is applied. Therefore, in the calculation of attitude angel, the process is complex and inaccurate, which can be solved approximately when calculating small attack angel. However, with the advancing development of modern aerodynamic unsteady research, the aircraft tends to develop high or super large attack angel and unsteady research field. According to engineering practice and vector theory, the concept of vector angel coordinate system is proposed for the first time, and the vector angel coordinate system of attitude angel is established. With the iterative correction calculation and avoiding the problem of approximate and inverse trigonometric function solution, the model attitude calculation process is carried out in detail, which validates that the calculation accuracy and accuracy of model attitude angels are improved. Based on engineering and theoretical methods, a vector angel coordinate system is established for the first time, which gives the transformation and angel definition relations between different flight attitude coordinate systems, that can accurately calculate the attitude angel of the corresponding coordinate system and determine its direction, especially in the channel coupling calculation, the calculation of the attitude angel between the coordinate systems is only related to the angel, and has nothing to do with the change order s of the coordinate system, which simplifies the calculation process.