One-dimensional shape memory polymer fibers (SMPFs) have obvious advantages in mechanical properties, dispersion properties and weavability. In this work, a method for fabricating semi-crystallization ethylene-vinyl acetate copolymer (EVA) fiber with two-way shape memory effect by melt spinning and ultraviolet (UV) curing was developed. Here, the effect of crosslink density on its performance was systematically analyzed by gel fraction measurement, tensile tests, DSC and TMA analysis. The results showed that the crosslink density and shape memory properties of EVA fiber could be facilely adjusted by controlling UV curing time. The resulting EVA fiber with cylindrical structure had a diameter of 247.13 ± 10.07 μm, and its mechanical strength and elongation at break were 64.46 MPa and 114.33%, respectively. The critical impact of the crosslink density and applied constant stress on the two-way shape memory effect were analyzed. Moreover, the single EVA fiber could lift more than 143 times its own weight and achieve 9% reversible actuation strain. The reversible actuation capability was significantly enhanced by a simple winding design of the single EVA fiber, which provided great potential applications in smart textiles, flexible actuators and artificial muscles.

This study aimed to assess the ecotoxicological effects of the interaction of fullerene (C₆₀) and benzo[a]pyrene (B[a]P) on the marine mussel, Mytilus galloprovincialis. The uptake of nC₆₀, B[a]P and mixtures of nC₆₀ and B[a]P into tissues was confirmed by GC-MS, LC-HRMS and ICP-MS. Biomarkers of DNA damage as well as proteomics analysis were applied to unravel the toxic effect of B[a]P and C₆₀. Antagonistic responses were observed at the genotoxic and proteomic level. Differentially expressed proteins (DEPs) were only identified in the B[a]P single exposure and the B[a]P mixture exposure groups containing 1 mg/L of C₆₀, the majority of which were down-regulated (~52%). No DEPs were identified at any of the concentrations of nC₆₀ (p < 0.05, 1% FDR). Using DEPs identified at a threshold of (p < 0.05; B[a]P and B[a]P mixture with nC₆₀), gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated that these proteins were enriched with a broad spectrum of biological processes and pathways, including those broadly associated with protein processing, cellular processes and environmental information processing. Among those significantly enriched pathways, the ribosome was consistently the top enriched term irrespective of treatment or concentration and plays an important role as the site of biological protein synthesis and translation. Our results demonstrate the complex multi-modal response to environmental stressors in M. galloprovincialis.

This review describes how resonance in amides is greatly affected upon substitution at nitrogen by two electronegative atoms. Nitrogen becomes strongly pyramidal and resonance stabilisation, evaluated computationally, can be reduced to as little as 50% that of N,N-dimethylacetamide. However, this occurs without significant twisting about the amide bond, which is borne out both experimentally and theoretically. In certain configurations, reduced resonance and pronounced anomeric effects between heteroatom substituents are instrumental in driving the HERON (Heteroatom Rearrangement On Nitrogen)^† reaction, in which the more electronegative atom migrates from nitrogen to the carbonyl carbon in concert with heterolysis of the amide bond, to generate acyl derivatives and heteroatom-substituted nitrenes. In other cases the anomeric effect facilitates S­_N1 and S_N2 reactivity at the amide nitrogen.

DR2B and DR2C extracts, from peel of commercially and physiologically ripe eggplants, were studied for the antioxidative cytoprotective properties and anti-HSV-1 activity, in line with the evidence that several antioxidants can impair viral replication by maintaining reducing conditions into the host cells. The antioxidative cytoprotective effects against tBOOH-induced damage was assessed in Caco2 cells, while the antiviral activity was studied in Vero cells; phenolic and anthocyanin fingerprint was characterized by integrated phytochemical methods. Results highlighted different compositions of the extracts, with chlorogenic acid and delphinidin-3-rutinoside as the major constituents; other peculiar phytochemicals were also identified. DR2C resulted able to partly counteract the tBOOH-induced cytotoxicity, with a remarkable lowering of lactate metabolism under both normoxia and hypoxia. DR2B and DR2C reduced ROS production, possessed scavenging and chelating properties. Interestingly, DR2C increased intracellular GSH levels. Furthermore, DR2C inhibited the HSV-1 replication when added for 24 h after viral adsorption, as also confirmed by the reduction of many viral proteins expression. Since DR2C was able to reduce NOX4 expression during HSV-1 infection, its antiviral activity may be correlated to its antioxidant properties. Although further studies are needed to better characterize DR2C activity, the results suggest this extract as a promising new anti-HSV-1 agent.

Borneol and menthol were two terpenes wildly used as penetrate enhancer in transdermal drug delivery. To explore their penetration enhancement effect towards hydrophilic drug, 5-FU was selected as model drug. A method combined vitro permeation studies and coarse grain molecular dynamics was used to investigate their penetration enhancement effect towards 5-FU. As a result, although both borneol and menthol showed a penetration enhancement effect towards 5-FU, they differed a lot in the penetration enhancement mechanism, which was also thought to account for their different penetration enhancement effect. As for menthol, SC bilayer disrupting effect seemed to be its main mechanism. While for borneol, its mechanism seemed to be more complicated. Except for disrupting the SC bilayer, it could also increase the permeation of 5-FU by enhancing the diffusion rate of 5-FU or inducing the formation of transient pore. All of this enable us a molecular understanding of borneol and menthol’s penetration enhancement effect towards hydrophilic drug, which might provide some guidance in the latter research and application.

Restoration experience is a positive response against the ever-increasing problem of stress. It is recovery of attentional capacity, clearing random thoughts and feelings of relaxation and calmness. Although there is a body of research on investigating the impact of open green space characteristics on psycho- logical restoration through attention restoration theory and supportive environment theory, there is little knowledge on how the interaction among these characteristics could promote restorative outcomes. To address this problem, using Perceived Sensory Dimension (PSD) for open green space qualities and Perceived Restorativeness (PR) as the property of restorative environment, this study assessed the extent to which the PSD and PR impact on restoration experience. Using 444 screened surveys, a Partial Least Square Structural Equation Model (PLS-SEM) was developed and the validity and reliability of it, was demonstrated. Extensive analysis of the results showed how environmental qualities can promote restoration experience using a sample of university students. These results provide information for landscape architecture and planning researchers to promote the development of open spaces as a resource of psychological restoration and stress relief.

Deploying onshore wind energy as a cornerstone of future global energy systems challenges societies and decision-makers worldwide. Expanding wind energy should contribute to a more sustainable electricity generation without harnessing humans and their environment. Opponents often highlight the negative environmental impacts of wind energy to impede its expansion. This study reviews 152 studies to synthesize, summarize, and discuss critically the current knowledge, research gaps, and mitigation strategies on the environmental impacts of onshore wind energy. The investigated effects comprise impacts on the abiotic and biotic environment, with birds and bats in particular, noise and visual impacts. Effects are discussed in the context of social acceptance, other energy technologies, and wind energy expansion in forests. The review illustrates that many effects are highly case-specific and must be more generalizable. Studies are biased regarding the research focus and areas, needing more standardized research methods and long-term measurements. Most studies focus on the direct mortality of birds and bats at wind farms and are concentrated in Europe and North America. Knowledge gaps persist for many impact categories, and the efficacy of mitigation strategies has yet to be proven. More targeted, unbiased research is required that allows for an objective evaluation of the environmental impacts of wind energy and strategies to mitigate them. Impacts, such as those on biodiversity, need to be addressed in the context of other anthropogenic influences and the benefits of wind energy. This forms the basis for a socially acceptable, efficient, and sustainable expansion of wind energy.

The sustainable development of an area is highly dependable on reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for the active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller's performance is evaluated in MATLAB environment and simulation results show the proposed scheme's superiority under different operating conditions.

Vertical-axis wind turbines (VAWTs) are receiving more and more attention as they involve simple design, cope better with turbulence and are insensitive to wind direction which has a huge impact on the cost since the yaw mechanism is not needed. However, VAWTs still suffer from low conversion efficiency. As a results tremendous efforts are exerted to improve its efficiency which mainly focus on two methods regardless of whether the study is a CFD simulation or a field test or lab test experiment. An active approach which involves the modification of the rotor itself such as the blade design, angle, trailing and leading edges, inner blades, chord thickness, contra-rotating rotor, etc. While the second approach involves passive techniques where the flow is directed to optimally face the downwind rotor by mounting a guiding vane such as a diffuser or other shapes at the upwind position of the rotor. Among all techniques undertaken, the CRWT rotor technique seems to be the most effective with an output even comparable to that of Horizontal Axis Wind Turbines (HAWT), while the Savonius rotor received more attention compared to other designs of VAWTs. Apart from technological issues, it was also suggested that geographical issues such as proper site siting of the wind turbine rotor at a particular location where a uniform flow could be guaranteed is of paramount importance to ensure an effective conversion capacity of wind turbines.

In the full load operating range, wind turbines typically use pitch control to maintain rotor speed and output power at their rated values to guarantee the whole system’s safety. Blade pitch actuators are subject to physical limitations and safety requirements, which imposes strict constraints on pitch angle’s amplitude and rate of change. These constraints will bring windup problem to the integral part of the pitch controller. It leads to deterioration of the pitch control system’s performance or even the instability problem, especially for large-scale turbines operating in extreme uncertain wind conditions or suffering from cyber attacks. This paper designs an anti-windup robust pitch angle control strategy to deal with pitch rate constraint issue to enhance the security of control system. First, to facilitate controller design, a filtered tracking error technique is employed to transform the nonaffine form into an affine one. Subsequently, a feedback robust controller based on UDE is developed to handle the model’s uncertainty and external disturbances. To address the issue of integral saturation in the pitch system and guarantee its safety, an elliptical bounded constraint is integrated into the designed UDE strategy. This bounded UDE controller can improve the stability of power generation quality, reduces the mechanical loads on components and enhance the whole system’s safety. Finally, the effectiveness of the proposed scheme is verified on the Wind Turbine Blockset platform in Matlab/Simulink. It can achieve better performance than the traditional method.

Long span cable-stayed bridge is the main bridge type with a span of more than 400 meters. It is generally designed as a double tower long-span structure with good spanning capacity and economic performance. Wind resistance safety performance is the main index to control the long-span cable-stayed bridge structure. During the operation of long-span cable-stayed bridge structure, because the service life of the cable is far less than the design life of the structure, the wind resistance performance of the structure will inevitably deteriorate significantly, which will seriously affect the structural service performance of symmetric cable-stayed bridge. Based on symmetric reliability theory, this paper takes flutter and static wind stability of long-span cable-stayed bridge structure as the main design control index, uses positive reliability theory to calculate the reliability index of symmetric cable-stayed bridge structure, uses inverse reliability theory to calculate the safety factor of symmetric cable-stayed bridge structure, and evaluates the wind resistant time-varying performance of long-span cable-stayed bridge structure by comprehensively considering the reliability index and safety factor. Taking a practical project of a long-span cable-stayed bridge as a specific case, the wind resistant time-varying reliability of the bridge during its operation for more than 30 years is analyzed, and the parameter sensitivity is analyzed. The results show that the wind resistance performance of the cable-stayed bridge structure is obviously affected by the cable, and the degradation of the cable performance will have an important impact on the wind resistance time-varying performance of the structure, especially the critical wind speed of the structure has obvious time-varying characteristics. The safety factor and reliability index can objectively evaluate the wind resistance time-varying performance of the long-span cable-stayed bridge structure.

Wind power is one of the most important sources of renewable energy available today. A large part of the wind energy cost is due to the cost of maintaining wind power equipment. When a wind turbine component fails to function, it might need to be replaced under the less than ideal circumstances. This is known as corrective maintenance. To minimize unnecessary costs, a more active maintenance policy based on the life expectancy of the key components is preferred. Optimal scheduling of preventive maintenance activities requires advanced mathematical modeling. In this paper, an optimal preventive maintenance algorithm is designed using the renewal-reward theorem. In the multi-component setting, our approach involves a new idea of virtual maintenance which allows us to treat each replacement event as a renewal event even if some components are not replaced by new ones. The proposed optimization algorithm is applied to a four-component model of a wind turbine and the optimal maintenance plans are computed for various initial conditions. The modeling results showed clearly the benefit of PM planning compared to pure CM strategy (about 30% lower maintenance cost).

Yaw misalignment can make a wake steer, which is an effective method to increase the power of wind farms, but it also increases the fatigue load of the turbines. In this paper, the method of combining yaw misalignment and pitch control (CYMP) is proposed to investigate the potential to mitigate wake interference, the wind velocity distribution and turbulence distribution in the wake, as well as the power and load changes of the wind turbine are studied, focusing on power in-crement and fatigue damage reduction. Although some studies have found that the method of CYMP are beneficial to increase power generation and reduce fatigue loads, there are no papers that have made a detailed analysis of the effects of wake turbulence, wind speed distribution, power, especially fatigue damage under this control. Simulation tool FAST.Farm is used to model and analyze wind farms, obtain the variation details of wake and provide simulation data for calculating power and fatigue load. The pitch control brings bias to the CYMP optimization results was neglected, the case studies show that the method of CYMP can reduce the fatigue load by 10.29% and increase the total power by 1.7% compared with only wake steering. The Model Predictive Control collaborative method based on CYMP is proposed, which can increase power by more than 2% and reduce thrust by more than 4% under 10m/s turbulent wind.

As one of the fastest-growing new energy sources, wind power technology has attracted widespread attention from all over the world. In order to improve the quality of wind power generation, wind speed prediction is an indispensable task. In this paper, an error correction based Variational Mode Decomposition and Broad Learning System (VMD-BLS) hybrid model is proposed for wind speed prediction. First, the wind speed is decomposed into multiple components by the VMD algorithm, and then an ARMA model is established for each component to find the optimal number of sequence divisions. Second, the BLS model is used to predict each component, and the prediction results are summed to obtain the wind speed forecast value. However, in some traditional methods, there is always time lag, which will reduce the forecast accuracy. To deal with this, a novel error correction technique is developed by utilizing BLS. Through verification experiment with actual data, it proves that the proposed method can reduce the phenomenon of prediction lag, and can achieve higher prediction accuracy than traditional approaches, which shows our method’s effectiveness in practice.

This work investigates how to balance the electricity supply and demand in a carbon-neutral northern Europe. Applying a cost-minimizing electricity system model including options to invest in eleven different flexibility measures, cost-efficient combinations of strategies to manage varia-tions are identified. The results of the model are post-processed using a novel method to map the net load before and after flexibility measures are applied to reveal the contribution of each flexi-bility measure. The net load is mapped in the space spanned by the amplitude, duration, and number of occur-rences. The mapping shows that, depending on cost structure, flexibility measures contribute to reduce the net load in three different ways; 1) by reducing variations of long duration but low amplitude, 2) by reducing variations of high amplitude but short duration and low occurrence or 3) by reducing variations of high amplitude, short duration and high occurrence. It is found that cost-efficient variation management is achieved by combining wind and solar power and by combining strategies (1-3) to manage variations. The cost-efficient combination of strategies de-pends on electricity system context where electricity trade, flexible hydrogen and heat production (1) manage the majority of variations in regions with good conditions for wind power while sta-tionary batteries (3) are the main contributors in regions with good conditions for solar power.

In this review, the potential of an emerging field of interdisciplinary climate research, that is the Coastal Boulder Deposits (CBDs) as natural archives for intense storms, is explored with particular reference to the Mediterranean region. First, the identification of the pertinent scientific articles was performed by using Web of Science (WoS) engine. Thus, the selected studies have been analysed to feature CBDs produced and/or activated during the last half century. Then, the meteorological events responsible to the literature reported cases were analysed in some details using the web archives of the Globo-Bolam-Moloch model cascade. The study of synoptical and local characteristics of the storms involved in the documented cases of boulder production/activation proved useful to assess the suitability of selected sites as geomorphological storm proxies. It is argued that a close and fruitful collaboration involving several scientific disciplines is required to develop this climate research field.

Integrating large-scale wind energy in modern power systems is demanding more efficient mathematical models to properly address classical assumptions in power system problems. In particular, there are two main assumptions in power system problems with wind integration that have not been adequately studied yet; First, non-linear AC power flow equations have been linearized in most of the literature. Such simplifications can lead to inaccurate power flow calculations that may result in other technical issues. Second, wind power uncertainties are inevitable and have been mostly modelled using the traditional uncertainty modelling approaches, that may not be suitable for large-scale wind power integration. In this paper, we address both challenges: we present a tight second-order conic relaxation (SOCR) for optimal power flow (OPF) problem, and simultaneously, implement the new effective budget of uncertainty approach for uncertainty modelling that determines the maximum wind power admissibility first and then addresses the uncertainty in the model. To the best of our knowledge, this is the first study that proposes an effective robust second-order conic programming (ERSOCP) model that simultaneously addresses the issues of power flow linearization and wind power uncertainty with the new paradigm on the budget of uncertainty approach. Our numerical results show the merit of the proposed model against traditional linearized power flow equations as well as traditional uncertainty modelling approaches.

Motivated for improving the efficiency and reliability of wind turbine energy conversion, this paper presents an advanced control design that enhances the power regulation efficiency and re-liability. The constrained behaviour of the wind turbine is taken into account, by using the barrier Lyapunov function in the analysis of the Lyapunov direct method. This, consequently, guarantees that the generated power remains within the desired bounds to satisfy the grid power demand. Moreover, a Nussbaum-type function is utilized in the control scheme, to cope with the unpre-dictable wind speed. This eliminates the need for accurate wind speed measurement or estimation. Furthermore, via properly designed adaptive laws, a robust actuator fault-tolerant capability is integrated into the scheme, handling the model uncertainty. Numerical simulations are performed on a high-fidelity wind turbine benchmark model, under different fault scenarios, to verify the effectiveness of the developed design. Also, a Monte-Carlo analysis is exploited for the evaluation of the reliability and robustness characteristics against the model-reality mismatch, measurement errors and disturbance effects.

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

The recent advancements in the field of communication have led data sharing to become an integral part of today's smart cities with the evolution of concepts such as the internet of vehicles (IoV) paradigm. As a part of IoV, Electric Vehicles (EVs) have recently gained momentum as authorities have started expanding their Low Emission Zones (LEZ) in an effort to build green cities with low carbon footprints. Energy is one of the key requirements of EVs not only to support the smooth and sustainable operation of EV itself but to also ensure connectivity between the vehicles and infrastructure with controlling devices like sensors and actuators installed within an EV. In this context, renewable energy sources (such as wind energy) dramatically play their parts in the automobile sector towards designing the energy harvesting electric vehicles (EH-EV) to pare the energy reliance on the national grid. In this article, a novel approach is presented to achieve electric generation due to vehicle mobility to support the communication primitives in electric vehicles which enables plenty of IoV use cases in the presence of surplus energy at hand. A small-scale wind turbine is designed to harness wind power for converting it into mechanical power. This power is then fed to the onboard DC generator to produce electrical energy. Furthermore, the acquired power is processed through a regulation circuitry to consequently achieve the desired power supply for the end load, i.e. the batteries installed. The suitable orientation for efficient power generation is proposed on ANSYS-based aerodynamics analysis. The voltages induced by DC generator at No-Load condition are 35V while at Full-Load 25V are generated at rated current of 6.9A, along with the generation of power at around 100W (at constant voltage) at the rated speed of 90 mph for nominal battery charging. Moreover, the acquired data can be monitored via an android application interface by using a Bluetooth module.

Reassessment of the fatigue life for wind turbines structural components is typically performed using deterministic methods with the same partial safety factors as used for the original design. However, in relation to life extension, the conditions are generally different from the assumptions used for calibration of partial safety factors; and using a deterministic assessment method with these partial safety factors might not lead to optimal decisions. In this paper, the deterministic assessment method is compared to probabilistic and risk-based approaches, and the economic feasibility is assessed for a case wind farm. Using the models also used for calibration of partial safety factors in IEC61400-1 ed. 4 it is found that the probabilistic assessment generally leads to longer additional fatigue life than the deterministic assessment method. The longer duration of the extended life can make life extension feasible in more situations. The risk-based model is applied to include the risk of failure directly in the economic feasibility assessment and it is found that the reliability can be much lower than the target for new turbines, without compromising the economic feasibility.

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator and the Monte–Carlo tools represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

Increasingly, there is a focus on utilising renewable energy resources in a bid to fulfil increasing energy requirements and mitigate the climate change impacts of fossil fuels. While most renewable resources are free, the technology used to usefully convert such resources is not and there is an increasing focus on improving the conversion economy and efficiency. To this end, advanced control technologies can have a significant impact and is already a relatively mature technology for wind turbines. Though hydroelectric plants can use simple regulation systems, significant benefits have been shown to accrue from the appropriate use of the same control methods designed for wind turbine plants. This represents the key point of the paper. In fact, to date, the application communities connected with wind and hydraulic energies have had little communication, resulting in little cross fertilisation of control ideas and experience, particularly from the more mature wind area to hydrodynamic systems. Therefore, this paper examines the models and the application of control technology across both domains, both from a comparative and contrasting point of view, with the aim of identifying commonalities in models and control objectives, as well as potential solutions. Key comparative reference points include the articulation of the exployed models, specification of control objectives, development of high--fidelity simulators, and development of solution concepts. Not least, in terms of realistic system requirements are the set of physical and constraints under which such renewable energy systems must operate, and the need to provide reliable and robust control solutions, which respect the often remote and relatively inaccessible location of many onshore and offshore deployments.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

This study aims to develop low-cost, eco-friendly and circular economy-compliant composite materials by creating three types of magnetorheological suspensions (MRSs) utilizing lard, carbonyl iron (CI) microparticles, and varying quantities of gelatin particles (GP). These MRSs serve as dielectric materials in cylindrical cells used to fabricate electric capacitors. The equivalent electrical capacitance (C) of these capacitors is measured under different magnetic flux densities (B≤160 mT) superimposed on a medium-frequency electric field (f = 1 kHz) over a period of 120 seconds. The results indicate that at high values of B, by increasing the GP content to 20 vol.% decreases the capacitance C up to about one order of magnitude compared to MRS without GP. From the measured data, the average values of capacitance Cm are derived, enabling the calculation of relative dielectric permittivities (ϵr′) and the dynamic viscosities (η) of the MRSs. It is demonstrated that ϵr′ and η can be adjusted by modifying the MRS composition and fine-tuned through the magnetic flux density B. A theoretical model based on the theory of dipolar approximations is used to show that ϵr′, η and the magnetodielectric effect can be coarsely adjusted through the composition of MRSs and finely adjusted through the values B of the magnetic flux density. The ability to fine-tune these properties highlights the versatility of these materials, making them suitable for applications in various industries, including electronics, automotive and aerospace.

Limited knowledge is available about the association between autistic spectrum disorder (ASD) and precocious puberty. Our study examined the association between the two medical conditions, and the effect modification by sex and neuropsychiatric comorbidities in a nationwide population. To compare the risk of precocious puberty between ASD and non-ASD cases, we conducted Cox regression analysis, using ASD as exposure and time-to-precocious puberty as outcome. We adjusted for sex, attention-deficit/hyperactivity disorder (ADHD), tics disorder, obsessive–compulsive disorder (OCD), anxiety disorder, intellectual disability, and epilepsy. We performed a moderation analysis to examine the potential moderating effects by sex or comorbidities. Patients with ASD were prone to have precocious puberty, with an adjusted hazard ratio (aHR) of 1.80 (95% CI: 1.61-2.01). For the effect modification, sex, specifically females, moderated the association between ASD and precocious puberty, with relative excess risk due to interaction (RERI) 7.35 (95% CI 4.90-9.80). No significant effect modification was found for any of the comorbidities within the scope of additive effect modification. We found that patients with ASD were prone to precocious puberty, regardless of sex or comorbid neuropsychiatric disorders. Girls with ASD are at particularly higher risk to develop precocious puberty.

During the high-speed flight of a vehicle in the atmosphere, surface friction with the air generates aerodynamic heating. The aerodynamic heating phenomenon can create extremely high temperatures near the surface. These high temperatures impact material properties and the structure of the aircraft, so thermal deformation measurement is essential in aerospace engineering. This paper revisits high-temperature deformation measurement using the digital image correlation (DIC) technique under high-intensity blackbody radiation with a precise speckle pattern fabrication and a heat haze reduction method. The effect of speckle pattern on the DIC measurement has been thoroughly studied at room temperature, but high-temperature measurement studies have not reported such effects so far. We found that the commonly used methods to reduce the heat haze effect could produce incorrect results. Hence, we propose a new method to mitigate heat haze effects. An infrared radiation heater was employed to make an experimental setup that could heat a specimen up to 950 ℃. First, we mitigated image saturation using a short-wavelength bandpass filter with blue light illumination, a standard procedure for high-temperature DIC deformation measurement. Second, we studied how to determine the proper size of the speckle pattern under a high-temperature environment. Third, we devised a reduction method for the heat haze effect. As proof of the effectiveness of our developed experimental method, we successfully measured the deformation of stainless steel 304 specimens from 25 ℃ to 800 ℃. The results confirmed that this method can be applied to the research and development of thermal protection systems in the aerospace field.

Inverse gas chromatography at infinite dilution was used to determine the surface thermodynamic properties of silica particles and PMMA adsorbed on silica, and more particularly, to quantify the London dispersive energy γsd, the Lewis acid γs+ and base γs- polar surface energies of PMMA/silica composites as a function of the temperature and the recovery fraction θ of PMMA. The polar acid–base surface energy γsAB and the total surface energy of the different composites were then deduced as a function of the temperature. In this paper, the Hamieh thermal model was used to quantify the surface thermodynamic energy of poly methyl methacrylate (PMMA) adsorbed on silica particles at different recovery fractions. A comparison of the new results was carried out with those obtained by applying other molecular models of the surface areas of organic molecules adsorbed on the different solid substrates. An important deviation of these molecular models from the thermal model was proved. The determination of γsd, γs+, γs-, and γsAB of PMMA in both bulk and adsorbed phases showed an important non-linearity variation of these surface parameters as a function of the temperature. The presence of maxima in the curves of γsd(T) highlighted the second order transition temperatures in PMMA showing beta-relaxation, glass transition and liquid-liquid temperatures. These three transition temperatures depended on the adsorption rate of PMMA on silica. The proposed method gave a new relation between the recovery fraction of PMMA and its London dispersive energy showing an important effect of the temperature on the surface energy parameters of adsorption of PMMA on silica. A universal equation relating γsd(T,θ) of the systems PMMA/silica to the recovery fraction and the temperature was proposed.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

In recent years the number of available chemical pesticides has been significantly reduced and there have been an urgent need for discovery of alternative to chemical pesticides products, as among others the natural zeolites (zeolitic rocks). We determined the mineralogical and chemical composition of a specific and continuous layers of zeolitic rock sample (ZeotP) from Petrota, Ev-ros, Greece and evaluated its oviposition deterrent effect for the olive fruit fly Bactrocera oleae (Diptera: Terphritidae). The tested natural zeolite contained 70 wt. % Clinoptilolite, 18 wt. % Amorphous material, 7 wt. % Feldspars, 4 wt. % Cristobalite and 1 wt. % Quartz. We tested the oviposition deterrent effect of ZeotP mixed or not with an emulsifier adjuvant NU-FILM-P® in water and applied on the surface of olive fruits. The ZeotP oviposition deterrent effect for the ol-ive fly was very high under a series of tested temperatures (17°C, 20°C, 25°C and 30°C) and RHs (23%, 33%, 55%, 75%, 94%). In addition, the ZeotP residual deterrent effect after equable water spraying was high and similar to the respective effect of a pyrethroid insecticide (Decis®). Our results may contribute to an effective control of the olive fruit fly using an alternative to chemical pesticides natural zeolite (zeolitic rocks) product.

Olive trees have a unique reproductive pattern marked by biennial fruiting. This study delves into the repercussions of alternate fruit bearing on the water relations of olive trees and the associated ecophysiological mechanisms. The experiment spanned two consecutive years: the "ON" year, characterized by a high crop load, and the "OFF" year, marked by minimal fruit production. Key ecophysiological parameters, including sap flow, stomatal conductance, and photosynthetic rate, were monitored in both years. Pre-dawn water potential was measured using continuous stem psychrometers and the pressure chamber technique. Biochemically, non-structural carbohydrate concentrations (starch, sucrose, and mannitol) and the carbon-stable isotope ratio (δ13C) in olive leaves were examined. Results unveiled heightened leaf gas exchange during the "ON" year, leading to increased water consumption and photosynthetic rates. This escalated water usage during the "ON" year significantly reduced leaf water potential. Sucrose and starch concentrations were notably elevated in the "ON" year, with no significant impact on mannitol concentration. Regarding the carbon stable isotope ratio, leaves from the "OFF" year exhibited significantly higher δ13C abundance, indicative of heightened resistance to the CO2 pathway from the atmosphere to carboxylation sites compared to the "ON" year plants.

In the last ten years, plasma waste treatment has gained increasing prominence as a technology in response to growing challenges in waste disposal and the recognition of opportunities for generating valuable by-products. The efficiency and outcomes of this process are intricately linked to the characteristics of the plasma involved, such as plasma enthalpy and heat flux. We employed an experimental radio frequency inductively coupled plasma (RF-ICP) torch operating at atmospheric pressure to generate plasma. Utilizing optical emission spectroscopy (OES), we measured plasma parameters, specifically the effective electron temperature (Teff) and plasma density (ne), while varying argon gas flow rates and RF powers. Our investigations revealed that both flow rate and RF power exert significant control over plasma parameters, and we observed an unusual phenomenon within this range of discharge pressures. Consequently, both the plasma's enthalpy and the heat flux it generates are influenced by variations in both flow rate and RF power.

Malignant melanoma is one of the most aggressive and resistant tumor types which is often accompanied by poor prognosis when spread to nearby or distant tissues. Even though an increasing number of second-line therapies are available for cancer patients, the 5-year survival rate of melanoma patients with regional and distant metastases is still rather low. Therefore, there is an urgent need to develop new, highly efficient treatments. Melanocortin-1-receptor (MC1R) is a cell surface receptor for α-MSH. It is responsible for melanogenesis and is shown to be overexpressed on the surface of cancer cells in a subset of melanoma patients. Here, we designed and synthesized α-MSH analogs and conjugated them to daunomycin through oxime linkage. Using our peptide-drug conjugates (Dau-α-MSHs), we performed comparative in vitro and in vivo evaluations to reveal their suitability for tumor targeting. Firstly, the expression level of MC1R was determined in various melanoma cell lines via RT-qPCR. Then, we examined the antiproliferative effect of our Dau-α-MSHs, moreover we determined the cellular uptake profile and intracellular localization of Dau-α-MSHs. The most efficient Dau-α-MSHs were investigated in vivo using a murine xenograft melanoma model. We found that various cell lines show differential expression on the mRNA levels. We also showed that healthy primary cells have lower expression of MC1R compared to tumor cell lines. Moreover, the concentration-dependent cellular uptake profile of Dau-α-MSHs was detected and the compounds exhibited a great antiproliferative effect on melanoma cell lines. We also provided evidence that our novel Dau-α-MSHs can inhibit tumor expansion significantly and are suitable for targeted tumor therapy.

The phenomenon of interference is a characteristic of all waves. This paper reviews the interference of classical waves and of matter waves in quantum mechanics. In quantum mechanics, there are two interference mechanisms between identical particles. One is that the de Broglie wavelengths of two interference waves are the same, which is called the equal wavelength interference mechanism. The other is that the wavelengths of interference waves can also be different, in which case there should be an exchange term in additional to the direction term in the wave function. There is a fixed phase difference between the two terms, which causes interference. This is called exchange effect interference mechanism. We propose an experiment, which is simpler to what has been done, to show the exchange effect interference. There is a special case where two interference waves can satisfy both the two mechanisms. We propose an experiment to discriminate that in this case which mechanism plays a role on earth.

BACKGROUND AND OBJECTIVES. Rod-Cone Dystrophies (RCDs) are genetically determined retinal dystrophies, resulting in nyctalopia, visual field progressive reduction and visual acuity decay in the late stages. Retinitis Pigmentosa (RP) is the most described type. All modes of transmission can be identified in RP, with the autosomal dominant form (ADRP) accounting for about 20% of cases. To date, over 30 genes have been related to ADRP, with RP1 gene estimated to be involved in 5-10% of cases. In a cohort of patients affected by RCD and sharing the same geographic origin from Palermo province in Western Sicily, we identified a prevalent causative variant in the RP1 gene (NM_006269.2; c.2219C>G, p.Ser740*). Objective of our study was to analyse clinical and molecular data of this population and define the entity and the meaning of this finding. MATERIALS AND METHODS. Eighty-four patients with a diagnosis of RCD or RP underwent deep phenotyping, pedigree definition and molecular characterization, mostly by Next Generation Sequencing (NGS). All potentially pathogenic variants have been confirmed through direct sequencing and familial segregation. Statistical evaluation of resulting data has been performed. RESULTS. In 28 probands we identified a pathogenic variant (p.Ser740*) in the RP1 gene that resulted significantly prevalent. Some patients, after careful interviewing, were found to share the same pedigree; we ultimately defined 20 family groups with no traceable consanguinity. CONCLUSIONS. The high prevalence of the p.Ser740* variant in RP patients from Western Sicily unveils the presence of a founder effect, which has implications for the molecular diagnosis of RCD in patients coming from this Italian region. This variant can be primarily searched in RP affected subjects displaying compatible mode of transmission and phenotype, with an advantage in terms of costs and analysis time. Moreover, given its high prevalence, RP1 p.Ser740* variant could represent a potential candidate for the development of therapeutic strategies based on gene editing or translational read-through therapy for suppression of nonsense variants.

Ever since oil was discovered in the Persian Gulf Region in the 1920s, the oil and gas industries have been dominant in the area. These countries are responsible for generating approximately 35 percent of the world's natural gas and 25 percent of its crude oil, making them the largest crude oil producers globally. The release of carbon dioxide (CO2) into the atmosphere is directly linked to the use of fossil fuels. CO2 accounts for 58.8 percent of all greenhouse gas emissions caused by human activities and has a detrimental impact on urban residents through the urban heat island effect. A significant portion of these emissions can be attributed to residential buildings. Some nations exacerbate the problem by relying excessively on fossil fuels. Oil-rich countries provide energy subsidies to the public in order to lower energy costs for their citizens. However, this policy can have negative consequences, including wasteful energy usage in countries like Iran.

This experimental study examined the application effect of polycaprolactone (PCL), an organic resin material with excellent elasticity and ductility, on improving the mechanical performance of cellulose nanocrystal (CNC) cement composites. To analyze the effect, a test specimen containing CNC and PCL mixed, containing only CNC, and a control (plain) specimen containing nothing were compared. PCL was compared according to its shape, and in the case of Granules, which is the basic shape, interfacial adhesion with cement was not achieved, so a DCM solution was used to dissolve and use the Granules form. As a method for bonding PCL to the CNC surface, the CNC surface was modified using 3-aminopropyltriethoxysilane (APTES), and surface silylation was confirmed through Fourier transform infrared spectroscopy(FT-IR) analysis. To evaluate the dispersibility according to the application of PCL to the modified CNC, particle size analysis (PSA) and zeta potential analysis were performed according to the PCL mixing amount (0.1, 0.3, 0.5, and 1 vol.% compared with those of CNC) and size distribution. Through the zeta potential value, the highest dispersion stability was shown at 1 vol.%. The cohesive force of CNC was low and the dispersion stability was high according to the application of PCL. According to the results of the dispersion stability evaluation, the degree of hydration of the dissolved PCL 1 vol.%, CNC-only specimens, and plain specimens were analyzed. Hydration products increased by increasing the degree of hydration in the unhydrated area. However, the incorporation of PCL showed a low degree of hydration, and the analysis of strength characteristics also showed a decrease of approximately 27% compared with that of plain specimens. This was because the bonding with SiO2 was not smooth owing to the solvent, thus affecting internal hydration. To investigate the effect of the PCL shape, the compressive and flexural strength characteristics were compared using PCL powder as an additional parameter. The compressive and flexural strength values were improved by approximately 54% and 26%, respectively, compared with those of the plain specimen. Scanning electron microscopy (SEM) analysis determined that the filler effect that made the micropore structure denser, affected the mechanical performance improvement.

We present evidence of the anchoring bias and disposition effect (DE) in investor trading decisions across different asset markets (stable and volatile assets) and market scenarios (stable and volatile markets), as well as how these biases affect investors' portfolio performance. The study employs a quasi-experimental design, allowing subjects to engage in interactive trading with four securities, two with potential negative returns and two with potential positive returns, within a simulated asset market. Our findings reveal the presence of the disposition effect and anchoring bias among individual investors in India. Second, market scenarios or volatility can influence the investors’ behavioral biases. The disposition effect was more prominent in volatile markets and the total market, while the anchoring bias was significant in stable and total markets. Additionally, investors exhibiting the disposition effect exhibit lower portfolio performance, while those demonstrating anchoring bias perform relatively better. The study's findings can help individual investors understand their behavioral biases, avoid them in future trading decisions, and improve portfolio performance. Financial institutions and regulatory agencies could identify investment products and supportive investor interactions towards better market trade decisions.

Glycerol has found its applications as a heat-transfer fluid in heat exchangers, and as a compo-nent of functional solutions in biosensor analysis. Flowing non-aqueous fluids are known to be able to induce electromagnetic fields due to triboelectric effect. These triboelectrically generated electromagnetic fields can affect biological macromolecules. Horseradish peroxidase (HRP) is widely employed as a convenient model object for studying how external electric, magnetic, and electromagnetic fields affect enzymes. Herein, we have studied whether the flow of glycerol in a ground-shielded cylindrical coil affects the HRP enzyme incubated at a 2 cm distance near the coil’s side. Atomic force microscopy (AFM) has been employed in order to study the effect of glycerol flow on HRP at the nanoscale. Increased aggregation of HRP on mica has been observed after the incubation of the enzyme near the coil. Moreover, the enzymatic activity of HRP has also been affected. The results reported can find their application in biotechnology, food technology and life sciences application, considering the development of triboelectric generators, en-zyme-based biosensors and bioreactors with surface-immobilized enzymes. Our data can also be of interest for scientists studying triboelectric phenomena.

The aim of this work is a comprehensive study of the effect of variable atomic composition and structural-phase state of (CoFeZr)x(MgF2)100-x nanocomposites (NCs) on their nonlinear electronic and magnetic/magneto-optical properties. Micrometer-thick nanocomposites layers on the glass substrates were obtained by ion-beam sputtering of a composite target in the argon atmosphere in a wide range of compositions x=9-51at.% The value of the resistive percolation threshold xper=34 at.%, determined from the concentration dependences of the electrical resistance of NCs, coincides with the beginning of nucleation of metallic nanocrystals CoFeZr in MgF2 dielectric matrix. The absolute value of maximum magnetoresistance of NCs is 2.4 % in a magnetic field of 5.5 kOe at x=25 at.%, up to the percolation threshold. Two maxima appear in the concentration dependences of magneto-optical transversal Kerr effect, one of which at x = 34 at.% corresponds to the formation of CoFeZr alloy nanocrystals of a hexagonal structure, and the second one at x=45 at.% corresponds to the phase transition of nanocrystals from a hexagonal to a cubic body-centered structure. The magnetic percolation threshold in (CoFeZr)x(MgF2)100-x system at xfm=34 at.% with the appearance of a hysteresis loop and a coercive force of Hc≈ 8 Oe, coincides with the resistive percolation threshold xper=34 at.%. Concentration dependence of the coercive force showed that at low contents of metallic alloy x<30 at.% NCs are superparamagnetic (Hc=0). With an increase of the alloy content, in the region of magnetic and resistive percolation thresholds NCs exhibit a magnetically soft ferromagnetic character and do not change it far beyond the percolation threshold with the maximum value of the coercive force Hc< 30 Oe. Decrease in magnetic order and soft ferromagnetic are influenced by the diamagnetic phase FeF2 that we discovered at the interface of magnetic nanocrystals CoFeZr with a dielectric matrix MgF2 by the Mössbauer spectroscopy.

Technology-enabled maintenance via sensors and the internet of things (IoT) technologies is seen as the “new maintenance strategy”. The aim is to use these technologies to focus on unnecessary breakdowns and increase levels of asset availability where the existing of a dedicated team to maintain or data on asset condition is limited, useless or full of noise. This paper presents the integration of various sensing nodes within an automated laser cutting machine for monitoring of critical components’ conditions. The integrated system provides a centralised platform for data collection from various sensors and provides early failure detection mechanism based on specified set points with alert mechanisms utilising a custom dashboard for data visualisation. The research highlights the required stages for the identification of the appropriate components and sensory devices for the development of efficient monitoring environment.

As a rapidly growing coastal megacity, Shanghai is continuously threatened with land subsidence issues since 1920s. Land subsidence was controlled in 1960s, however in 1990s, unconscious and dangerous urban underground space (UUS) exploration and tunneling development are causing further land subsidence. It is imperative to study previous relations towards future adaptive and resilient scenario modelling and planning. There are multiple cause-effect factors determined in the urban built environment of Shanghai megacity. This paper presents the current evidence based on the relations of the multifactor of the spectrum. Methods consist of understanding the cause-effect relations and spatiotemporal from the crucial period of 1960-2020. Data are collected secondarily from multiple open sourced databases. The results determine Shanghai are highly influenced by the UUS development induced-subsidence, tunneling leakage and weak spatial modelling. Spatiotemporal pattern has shown a mixed positive-negative impact: population, land subsidence is growing in parallel distribution (positive) with tunneling leakage, construction of tunneling, metro system, UUS development, building price, reconstruction area, GDP growth, land price, arable land decrease and further tunnel settlement in Urban City Centre, Pudong New Area, Minhang, Baoshan and Songjiang districts. These results are useful for further adaptive and resilient scenario modelling and spatial planning.

Manipulation of radiation pattern control is challenging, especially at low frequencies. In this paper, we demonstrate that acoustic metamaterials as an effective array of quadrupoles can remarkably improve the directionality of acoustic radiation at low frequencies, compared with previous metamaterials as monopole and dipole structures. The directivity of the acoustic radiation can be adjusted by changing the characteristic parameter and the symmetry of the structure, which provide a flexible method of adjustable radiation di-rections. The directionality can be further improved by constructing linear array of structure. Our work opens an approach of acoustic radiation control via quadrupolar metamaterials.

In magneto-photoluminescence (magneto-PL) spectra of quasi-two dimensional islands (quantum dots) having seven electrons and Wigner-Seitz radius rs~1.5, we revealed a suppression of magnetic field (B) dispersion, paramagnetic shifts and jumps of the energy of the emission components for filling factors &gt;1 (B&lt;10 T). Additionally, we observed B-hysteresis of the jumps and a dependence of all these anomalous features on rs. Using a theoretical description of the magneto-PL spectra and an analysis of the electronic structure of these dots based on the single-particle Fock-Darwin spectrum and many-particle configuration-interaction calculations, we show that these observations can be described by the rs-dependent formation of the anyon (magneto-electron) composites (ACs) involving single-particle states having non-zero angular momentum and that the anyon states observed involve Majorana modes (MMs), including zero-B modes having equal number of vortexes and anti-vortexes, which can be considered as Majorana anyons. We show that the paramagnetic shift corresponds to a destruction of the equilibrium self-formed ~5/2 AC by the external magnetic field and that the jumps and their hysteresis can be described in terms of Majorana qubit states controlled by B and rs. Our results show a critical role of quantum confinement in the formation of magneto-electrons and implies the liquid-crystal nature of fractional quantum Hall effect states, Majorana anyon origin of the states having even , i.e., composite fermions, which provide new opportunities for topological quantum computing.

Background: Although, negative repercussions of inadequate health service use on the health outcomes has been presumably exacerbated by COVID-19, the impact of the pandemic measures has been not evaluated properly yet. Objective: Our study aimed to quantify the COVID-19 pandemic measures’ effect on the general practitioner (GP) visit, specialist care, hospitalization and cost-related prescription nonredemption (CRPNR) among adults in Hungary, and to identify the social strata susceptible to the pandemic effect. Methods: This community-based cross-sectional study based on nationally representative data of 6,611 (Nprepandemic=5,603 and Npandemic=1,008) subjects aged 18 years and above. Data were obtained from the European Health Interview Survey 2019 (EHIS) and International Social Survey Program 2021 (ISSP) for prepandemic and pandemic, respectively. Multivariable logistic regression models were applied to determine the sociodemographic and clinical factors influencing the health care use by odds ratios (OR) along with the corresponding 95% confidence intervals (CI). To identify the social strata susceptible to pandemic effect, the interaction of the time of data collection with level of education, marital status, and ethnicity, was also tested. Results: While, the CRPNR did not changed, the frequency of GP visit, specialist care and hospitalization rate were remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic in Hungary. Roma proved to be not specifically affected by the pandemic in any studied respect. The pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (ORhigh-school vs primary-education =0.434; 95% CI 0.243-0.776, ORhigh-school vs primary-education =0.598; 95% CI 0.364-0.985), and among widows (ORwidowed vs married =2.284; 95% CI 1.043-4.998, ORwidowed vs married=1.915; 95% CI 1.157-3.168) on the frequency of GP visit and specialist visit; and the prepandemic CRPNR inequality by level of education was increased (ORhigh-school vs primary-education =0.236; 95% CI 0.075-0.743). Conclusion: Primary educated and widowed did not follow the general trend, and their prepandemic limited health care use was not reduced further during pandemic, resulting in an inequality reduction. The vulnerability of primary educated to CRPNR was the only gap widened in the pandemic period. This shows that although the management of pandemic health care use restrictions was implemented by increasing the social inequality in Hungary, the prevention of inequity in drug availability for primary educated individuals could require more support.

The anisotropy in the CMBR detected by the COBE satellite has sprouted the research and theories of the void that got created, after being washed away by a parallel universe after its collision. This details of the roadmap to the parallel universe, that are previously been entangled, but now, separated, with the concept of 2-time dimensions as a time curve of containing the closed curves embedded on the surface area, thereby time running backward in orientation in the parallel universe, along with the perspective of eternal inflation and divided subspaces giving birth to twin universes are provided here. This time curve being responsible for creating an exponentiality of time frames, growing in layers, giving us the perception of the confabulations being an indication of the previously connected worlds.

The high-power Asymmetric half-bridge Converter (AHBC) LED constant current driver controlled by digital current mode is a fourth-order system. Static operating point, parasitic resistance, load characteristics, sampling effect, modulation mode and loop delay will have great influence on its dynamic performance. In this paper, the small-signal pulse transfer function of the driver is established by the discrete-time modeling method for the two operating points corresponding to the three modulation modes of the trailing edge, leading edge and double edge. And, the effects of parasitic parameters, delay effect, sampling effect and load effect are fully considered in modeling. For a large number of complex exponential matrix operations, the first order Taylor formula is used for approximate calculation after the coefficient matrix is obtained by substituting the data. Then, Matlab software is used to compare and analyze the discrete-time model and the discrete-average model. The results show that the proposed discrete-time model can more accurately characterize the resonant peak and high-frequency dynamic characteristics, and is very suitable for the design of high frequency digital controller.

Here we calculate the deflection angle of photon by Casimir wormhole in weak limit approximation. First we calculate Gaussian optical curvature with the help of optical spacetime geometry and so we use the Gauss-Bonnet theorem on Gaussian optical metric and find deflection angle of photon by Casimir wormhole. Moreover, we calculate the photon's deflection angle in the presence of plasma medium and we also see the graphical nature of deflection angle in both cases. After calculating the deflection angle of Casimir wormhole. Now, we move towards the shadow of Casimir wormhole. After the observations of Event Horizon Telescope, the study of shadow become very important so that we plot the shapes of shadow of Casimir wormhole, and we calculate the photon geodesic around the Casimir wormhole.

We introduce a total energy and environmental evaluation method in the manufacturing industry. The method gives us a series of descriptive indexes to assess the overall environmental effect level on materials, energy, wastes and products in the life cycle process. Meanwhile, the method uses partial indexes, environmental effect factors, and correction offsets into the quantitative model to analyze the learning process and rebound effect on the energy and environment at each procedure. In this work, we choose S-shaped learning curves to describe how to decrease energy consumption and improve the technical learning by doing for recent 30 years. Also, we draw the different rebound effect curves of the total energy-environmental evaluation with technical learning method, which use the annual industrial production growth rate to show that it's significant to estimate its effect on technology changes. The ideas about the interaction of energy and production environment from material flows to energy consumption, direct us to build an example to estimate quantitatively the results with different condition factors, and realize the process improvement and develop new products.

The thermal stabilizers, lubricant, and plasticizers are three crucial additives for processing poly (vinyl chloride) (PVC). In this study, a new mannitol stearate ester-based aluminum alkoxides (MSE-Al) was designed and synthesized as a novel additive for PVC. The thermal stability and processing performance of PVC stabilized by MSE-Al were evaluated by Congo red test, conductivity measurement, thermal aging test, ultravioletevisible (UV-vis) spectroscopy test, and torque rheometer test. Results showed that the addition of MSE-Al can not only markedly improve the long-term thermal stability of PVC, but also greatly accelerate the plasticizing and decrease the balance torque which demonstrated that MSE-Al possesses the lubricating property. Thus, MSE-Al was demonstrated to be able to provide tri-functional additive roles, e.g., thermal stabilizer, plasticizer, and lubricant. The test results for the thermal stability of PVC indicated that the initial whiteness of PVC stabilized with MSE-Al was not good enough, thus the synergistic effect of MSE-Al with zinc stearates (ZnSt₂) on the thermal stability of PVC was also investigated. The results showed that there exhibited an appreciable synergistic effect between MSE-Al and ZnSt₂. The thermal stabilization mechanism and synergism effect of MSE-Al with ZnSt₂ were then discussed.

The high demand for liquefied natural gas (LNG) requires more LNG carriers (LNGCs) to be in operation. During transportation, there is a high risk due to the required extremely low temperatures and the explosive nature of LNG cargo. Moreover, when there is a lack of experience in operating old LNGCs, there is a serious concern regarding operational accidents. A systematic maintenance strategy, especially for LNG cargo containment systems, is crucial for maintaining safe LNG transportation at sea. The purpose of this study is to develop preventive LNG cargo containment system maintenance models by using LNGC dock specifications from LNGCs of various ages. The dock specifications from a conventional LNGC repairing dock were analyzed using natural language processing techniques in order to develop preventive maintenance models of the LNG cargo containment system. From these results, and by considering the ship’s age, it was found that for young LNGCs the priority for repair should focus on checking routine consumable spare parts by tank inspections, whereas for older LNGCs the focus should be on tank condition maintenance rather than on other facilities. These results are expected to be useful in the development of a maintenance strategy of preventive LNG cargo containment systems in maritime LNG transportation.

The purpose of the present study is to explore the linkage between Hazardous Road Locations-based crash counts and a variety of geometric characteristics, roadway characteristics, traffic flow characteristics and spatial features in the region of Sousse, Tunisia. For this purpose, collision data was collected from at 52 hazardous road sections including 1397 crash records for a 11-year monitoring period from January 1, 2004 to December 31, 2014 obtained from National Observatory for Information, Training, Documentation and Studies on Road Safety in Tunisia (NOITDRS). The matrix of Pearson correlation was used in order to avoid inclusion of both variables, which were highly correlated. Both the Random Effects Negative Binomial model and the Negative Binomial model were estimated. To evaluate the models, the Random Effect Negative Binomial model improves the goodness-of-fit compared to the Negative Binomial model. Average Daily Traffic volume, Curved alignment, Presence of public lighting, Visibility, Number of lane, Presence of vertical/horizontal sign, Presence of rural segment, Presence of drainage system, Roadway surface condition, Presence of paved shoulder and presence of major road were found as significant variables influencing accident occurrences. Overall, the current research contributes to the literature from empirical, modeling methodological standpoints since it was the first study conducted in Tunisia to use crash prediction models for hazardous road locations, and that portrays Tunisian reality. The research findings present advantageous insights on hazardous road locations in the region of Sousse, Tunisia and present useful planning tools for public authorities in Tunisia.

Carbon nanotubes have been attracting considerable interest among material scientists, physicists, chemists and engineers for almost 30 years. Owing to their high aspect ratio, coupled with remarkable mechanical, electronic and thermal properties, carbon nanotubes have found application in diverse fields. In this review, we will cover the work on carbon nanotubes used for sensing applications. In particular, we will see examples where carbon nanotubes act as main players in devices sensing biomolecules, gas, light or pressure changes. Furthermore, we will discuss how to improve the performance of carbon nanotube-based sensors after proper modification.

The Western ‘discovery’ of Japanese cinema in the 1950s prompted scholars to articulate essentialist visions understanding its singularities as a result of its isolation from the rest of the World and its close links to local aesthetic and philosophical traditions. Recent approaches however, have evidenced the limitations of this paradigm of ‘national cinema’. Higson (1989) opened a critical discussion on the existing consumption, text andproduction-based approaches to this concept. This article draws on Higson´s contribution and calls into question traditional theorising of Japanese film as a national cinema. Contradictions are illustrated by assessing the other side of the ‘discovery’ of Japanese cinema: certain gendaigeki works that succeeded at the domestic box office while jidaigeki burst into European film festivals. The Taiyōzoku and subsequent Mukokuseki Action created a new postwar iconography by adapting codes of representation from Hollywood youth and western films. This article does not attempt to deny the uniqueness of this film culture, but rather seeks to highlight the need to reformulate the paradigm of national cinema in the Japanese case, and illustrate the sense in which it was created from outside, failing to recognise its reach transnational intertextuality.

The aim of this document is to provide practical guidance on the choice of target difference used in the sample size calculation of a randomised controlled trial (RCT). Guidance is provided with a definitive trial, one that seeks to provide a useful answer, in mind and not those of a more exploratory nature. The term “target difference” is taken throughout to refer to the difference that is used in the sample size calculation (the one that the study formally “targets”). Please see the glossary for definitions and clarification with regards other relevant concepts. In order to address the specification of the target difference, it is appropriate, and to some degree necessary, to touch on related statistical aspects of conducting a sample size calculation. Generally the discussion of other aspects and more technical details is kept to a minimum, with more technical aspects covered in the appendices and referencing of relevant sources provided for further reading.The main body of this guidance assumes a standard RCT design is used; formally, this can be described as a two-arm parallel-group superiority trial. Most RCTs test for superiority of the interventions, that is, whether or not one of the interventions is superior to the other (See Box 1 for a formal definition of superiority, and of the two most common alternative approaches). Some common alternative trial designs are considered in Appendix 3. Additionally, it is assumed in the main body of the text that the conventional (Neyman-Pearson) approach to the sample size calculation of an RCT is being used. Other approaches (Bayesian, precision and value of information) are briefly considered in Appendix 2 with reference to the specification of the target difference.

There are dozens of approved, investigational and experimental antiviral agents. Many of these agents cause serious side effects, which can be revealed only after drug administration. Identification of the side effects prior to drug administration is challenging. Here we describe an ex vivo approach for studying immuno- and neuro-modulatory properties of antiviral agents, which could be associated with potential side effects of these therapeutics. The approach combines drug toxicity/efficacy tests and transcriptomics, which is followed by cytokine and metabolite profiling. We demonstrated the utility of this approach with several examples of antiviral agents. We also showed that the approach can utilize different immune stimuli and cell types. It can also include other omics techniques, such as genomics and epigenomics, to allow identification of individual markers associated with adverse reactions to antivirals with immuno- and neuro-modulatory properties.

In daily living environments, an individual’s state influences spatial perception. The current study, based on Attention Restoration Theory, aimed to explore differences in the health utility of nature according to individual differences in spatial perception. Cognitive mapping and the Perceived Restorativeness Scale (PRS) were used to assess spatial perception ranges and the restorative effect of the environment. Two spatial perceptual groups were defined: one describing only the internal area of a green space, and another illustrating the external area of this green space on a larger scale. The former had higher overall PRS, Being Away, Fascination, and Compatibility scores. The latter had higher scores only on the Coherence subscale. These results illustrate that frequency of nature visits and time spent traveling to do so differently influence the two groups’ attentional restoration, which has great implications for landscape planning in highly stressful urban environments.

Alzheimer’s disease (AD) is an age-related neurodegenerative disease and is clinically characterized by cognitive impairment, memory loss, and personality disorder. Oligomers of amyloid beta-peptides (Aβ) and enhanced oxidative stress in senile plaques are prevalent pathologic hallmarks of AD. In this study, we detected the behavioral performance of Lycium ruthenicum Murray anthocyanin (LRA) -treated rats using the Morris water maze test and then investigated the effect of LRA on oxidative damage, neuronal apoptosis, and inflammatory response induced by Aβ1–42. Our results showed that LRA treatment markedly ameliorated the behavioral performance of Aβ1–42-induced rats and reduced the level of malondialdehyde, formation of protein carbonyl, and 8-hydroxy-2’-deoxygua-nosine. Furthermore, LRA also inhibited activated astrocytes and neuroinflammation via suppression of glial fibrillary acidic protein and tumor necrosis factor-alpha in the hippocampus of Aβ1–42-treated rat brain. These data suggest that LRA could be a potential anti-oxidant and anti-neuroinflammatory agent for the treatment of AD.

Mesoscale eddies wield a significant influence on primary productivity in marine ecosystems by regulating nutrient availability, vertical mixing, and phytoplankton growth dynamics. In this study, we tracked and analyzed the effects of mesoscale eddies on net primary productivity (NPP) across the Bay of Bengal (BoB) using remote sensing data. Dividing the Bay into six zones based on mesoscale eddy frequency and distribution, our analysis identified 1880 anticyclonic eddies and 1972 cyclonic eddies during January 2010–March 2020 monitoring period. Cyclonic eddies predominantly occurred in the western part of the bay - along the east coast of the Indian Peninsula; while anticyclonic eddies were also observed, albeit in lesser proportions. Among eddies lasting one-week, anticyclonic eddies comprised approximately 48.81%, while cyclonic eddies constituted approximately 51.19% of the total. Analysis of the NPP distribution across the months revealed intriguing patterns. Mean values of NPP fluctuated throughout the year, with the highest value observed in August (748.51 mg C/m2/day) and the lowest in May (519.26 mg C/m2/day). The findings indicate a complex relationship between eddy distribution and NPP, with Zones 1 and 2 exhibiting a higher occurrence of cyclonic eddies, correlating with greater NPP and its variability. Conversely, Zones 3 and 5 display increased eddy activity despite fewer cyclonic eddies and lower NPP levels. Zone 6 shows reduced eddy activity and NPP, while Zone 4 presents moderate eddy activity alongside lower NPP. In contrast, Zones 3 to 5 exhibit lower NPP levels despite exhibiting heightened eddy activity. This study contributes valuable insights into the dynamics of ocean circulation and the impacts of eddies on NPP, which can inform fisheries management strategies, advances climate resilience measures, expands scientific knowledge, and guides policies related to conservation and sustainable resource utilization.

The terrain of Changbai Mountain has great influence on the distribution of atmospheric flows and the occurrence and development of precipitation. This study quantitatively analyzes the regional characteristic of topographic perturbations and the relationship between terrain, wind and precipitation in Changbai Mountain region, by using a spectral analysis of the two-dimensional discrete cosine transform. Three domains with relatively heavy summer precipitation are selected as the study region. The results indicate that the overall terrain of Changbai Mountain region exhibits anisotropic characteristics. The terrain spectra of domain B are less than those of domain A and C across the whole wavelength (λ) bands, indicating that the large-scale topographic perturbations of domain B are relatively weak. The largest topographic spectral peak of domain C shows the most pronounced undulation of terrain among the three domains. The dominant wavelengths of terrain height variance for domain A and C, both close to the respective maximum wavelengths, indicate more prominent large-scale topographic perturbations. For domain A, the variation of the precipitation spectra is consistent with that of the wind spectra at the wavelength bands of λ < 390 km, showing a high correlation between wind field and the occurrence of rainfall. The inverse relationship at larger wavelengths indicates that multiple factors contribute to the occurrence of rainfall. For domain B, there is consistency in the fluctuations of terrain spectra, precipitation spectra, and wind spectra at the wavelength bands of λ < 278.3 km, implying that the smaller-scale terrain has an important effect on the occurrence of summer precipitation. For domain C, the variations of terrain spectra, precipitation spectra, and wind spectra are almost consistent across the whole wavelength bands, indicating that the large-scale terrain and minor terrain both play a crucial role in atmospheric uplift and the occurrence and development of summer rainfall.

To address the problems of wind abandonment in the regional integrated energy system (RIES), which occurs when cogeneration unit operates in a heat-determined electricity operation mode, and the low efficiency of the energy storage system in a low-temperature environment, we propose an optimal scheduling method for RIES based on fine energy storage and wind power dissipation. First, a fine energy storage model is established on the source side and the conditional value at risk(CvaR) theory is used to quantify the uncertainty of wind power; then a combined heat and power demand response mechanism is introduced on the load side to reduce the peak-to-valley difference between heat and power loads, and to promote the consumption of wind power. Finally, with the objective of minimizing the total cost of RIES optimal dispatch, the example is solved on the MATLAB platform. The simulation results show that compared with the traditional model, the proposed model is not only more adaptable to the low-temperature environment, but also can effectively improve the system economy and wind power consumption.

Cable-supported façades represent a novel approach in the design and technology of double skin façades (DSF). This type of systems not only offer flexibility in terms of exterior finishes, but also regulates the access of solar radiation, thereby transforming the appearance of the building in response to varying daylight conditions. However, the structural performance of these façades under wind, impact and seismic loads remains an active area of research. The study is a groundbreaking work that experimentally evaluates the wind and seismic behaviour of these type of façades. The methodology used for the evaluation of flexible masonry facades includes laboratory tests analysing the individual capacity of the connections and materials of the system under standardized and non-standardized procedures. A full-scale experimental sub-assembly specimen of a representative module of the façade is also subjected to uniformly distributed pressures of wind load tests as well as hard body and soft body impact tests. The setup considered the border conditions, tension loads, and actual materials. Furthermore, the earthquake assessment includes tests of full-scale specimens subjected to these demands. Research findings allowed the refinement and redesign of the system's components granting the validation of the DSF used as a case study.

This paper defines the two main causes of global warming in the UK and seeks to cut climate change using green hydrogen made from renewable electricity sources. Combustion vehicles powered by fossil gasoline and diesel emit a third of UK climate-warming CO2 while buildings heated by natural gas provide a quarter. First, current UK grid problems are defined: Electricity grid, gas grid and petroleum grid. Then experiments on the private energy community of Keele University allow electrolysis demonstrations producing green hydrogen for buildings and vehicle refueling. Next, the model supply chain is planned and tested. Finally, experiments and calculations are outlined, analyzing the optimum system design criteria proposed. We conclude that economic green hydrogen can displace diesel and gasoline in vehicle transport, while also displacing natural gas for combined heat and power in buildings. In addition, the prospect in 2023 is that profits can now be made all along the green hydrogen supply chain, such that new businesses involved in clean communities can beat the National Grid monopoly and other large dominant fossil grid companies.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

As wind turbine power requirements have evolved from the order of kilowatts (kW) to the order of several megawatts (MW), wind turbine components have been subjected to more demanding and critical operating conditions. The wind turbine must cope with higher wind loads due to larger blade sizes, which are also time-varying and ultimately higher power levels. One of the challenges in the manufacture of high-power wind turbines lies in the gearbox and consists of achieving ever greater power density without compromising efficiency, i.e., greater load capacity with lower weight (and production cost) and reduced power losses. In this paper we will analyze the influence that certain design parameters have on the size and weight of the gearbox components and therefore of the gearbox itself. For this purpose, the theoretical model of the gearbox will be planned and the influence of calculation parameters on the gearbox design will be analyzed. The influence of material, modulus and tooth width on the size and weight of the gearbox will be observed. Critical stresses are also calculated. The goal is to prepare the theoretical basis for an optimization process that will result in a gearbox as compact as possible without compromising the service life of the components.

Several coastal barriers experienced significant erosion and change in shape throughout the Mediterranean coasts over the past decades, and the issue has become of increasing concern for scientists and policymakers. With reference to a case study and by meteorological and geomorphological investigations, this note aims to infer recent shoreline dynamics and define coastal phenomena shaping the beach-dune barrier of Cesine Lagoon (South Italy), to finally point out the weather-driven processes. A challenge for this research was to obtain significant results from publicly available sources and simple and inexpensive methods. The retreat of the dune toe, the accretion of washover fans, and the formation of gravel beaches have been related to the analyzed wind-wave conditions. Net longshore transport was found in accordance with the direction of the more intense winds. The role of extreme events in the shaping of coastal landforms is yet to be established even if they greatly increase the vulnerability to flooding of the study area. The results achieved so far are starting points for further data collection and analysis in the perspective of assessing the impact of climate changes on the lagoon barrier.

The fundamental challenge for the structural design of complicated shapes and lightweight structures such as Tensile Membrane Structures (TMS) is a reliable estimation of lateral loading such as wind load. Wind pressure coefficients can’t be correctly calculated by standards for a large range of intricate forms of structures. Computational Fluid Dynamics (CFD), a strong computational technique for evaluating wind pressure distribution on complicated geometry, can be used to determine wind-related parameters. The average wind related-distributions for the tensile membrane surface are validated with a few contributions from prior studies, which are important to validate with benchmarks in experimental wind tunnel experiments. For the double-curved surface, the results show good agreement between experimental tests and CFD simulations. In this study, CFD simulation was used to calculate the mean surface pressure coefficient (Cp) for generic shapes and tensile membrane forms using the steady Reynolds-Averaged Navier-Stokes (RANS) technique. Wind force coefficients and the effect of wind directions are also explored across a wide range of classical and tensile forms. The purpose of the current research is to look at the effect of wind assault angle on the Cp distribution for tensile membrane structures and general shapes.

Climate change impacts and adaptations is subject to ongoing issues that attract the attention of many researchers. Insight into the wind power potential in an area and its probable variation due to climate change impacts can provide useful information for energy policymakers and strategists for sustainable development and management of the energy. In this study, spatial variation of wind power density at the turbine hub-height and its variability under future climatic scenarios are taken under consideration. An ANFIS based post-processing technique was employed to match the power outputs of the regional climate model with those obtained from the reference data. The near-surface wind data obtained from a regional climate model are employed to investigate climate change impacts on the wind power resources in the Caspian Sea. Subsequent to converting near-surface wind speed to turbine hub-height speed and computation of wind power density, the results have been investigated to reveal mean annual power, seasonal, and monthly variability for a 20-year period in the present (1981-2000) and in the future (2081-2100). The results of this study revealed that climate change does not affect the wind climate over the study area, remarkably. However, a small decrease was projected for future simulation revealing a slightly decrease in mean annual wind power in the future compared to historical simulations. Moreover, the results demonstrated strong variation in wind power in terms of temporal and spatial distribution when winter and summer have the highest values of power. The findings of this study indicated that the middle and northern parts of the Caspian Sea are placed with the highest values of wind power. However, the results of the post-processing technique using adaptive neuro-fuzzy inference system (ANFIS) model showed that the real potential of the wind power in the area is lower than those of projected from the regional climate model.

The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, data--driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods, such as fuzzy and adaptive self--tuning controllers, were already verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. The working conditions of these systems will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.

In this paper, an offshore airborne wind energy (AWE) farm consisting of three non-reversing pumping mode AWE systems is modelled and simulated. The AWE systems employ permanent magnet synchronous generators (PMSG). A direct interconnection technique is developed and implemented for AWE systems. This method is a new approach invented for interconnecting offshore wind turbines with the least number of required offshore-based power electronic converters. The direct interconnection technique can be beneficial in improving the economy and reliability of marine airborne wind energy systems. The performance and interactions of the directly interconnected generators inside the energy farm internal power grid are investigated. The results of the study conducted in this paper, show the directly interconnected AWE systems can exhibit a poor load balance and significant reactive power exchange which must be addressed. Power control strategies for controlling the active and reactive power of the AWE farm are designed, implemented, and promising results are discussed in this paper.

The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, self--tuning control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods were already verified on wind turbine systems, and important advantages may thus derive from the appropriate implementation of the same control schemes for hydroelectric plants. This represents the key point of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. In fact, it seems that investigations related with both wind and hydraulic energies present a reduced number of common aspects, thus leading to little exchange and share of possible common points. This consideration is particularly valid with reference to the more established wind area when compared to hydroelectric systems. In this way, this work recalls the models of wind turbine and hydroelectric system, and investigates the application of different control solutions. The scope is to analyse common points in the control objectives and the achievable results from the application of different solutions. Another important point of this investigation regards the analysis of the exploited benchmark models, their control objectives, and the development of the control solutions. The working conditions of these energy conversion systems will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.

This paper generalizes the actuator disc theory to the application of crosswind kite power systems. For simplicity, it is assumed that the kite sweeps an annulus in the air, perpendicular to the wind direction (i.e. straight downwind configuration with tether parallel to the wind). It is further assumed that the wind flow has a uniform distribution. Expressions for power harvested by the kite is obtained, where the effect of the kite on slowing down the wind (i.e. the induction factor) is taken into account. It is shown that although the induction factor may be small for a crosswind kite (of the order of a few percentage points), neglecting it in calculations may result in noticeable overestimation of the amount of power harvestable by a crosswind kite system.

The fault diagnosis of wind farms has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of a wind park benchmark model, and it considers viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, noise, uncertainty and disturbances. In particular, the proposed data-driven solutions rely on fuzzy models and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive with exogenous input models, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind farm installation. The achieved performances are also compared with those of a model-based approach relying on nonlinear differential geometry tools. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine Operation and Maintenance (O&amp;M). Incorporating machine learning in developing condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Base Density for the Support Vector Machine (BDSVM) and the evolutionary Fourier spectra of vibrations. This method allows smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the BDSVM to timely determine the magnitude, frequency, and place of the failure occurring in wind turbine drive.

In China's mountainous coastal terrain, the storm badly damaged low-rise buildings. At present, it is not clear how the relative position of buildings and mountains affects the surface of a low-rise building’s fluctuating coefficient. The study compared these results with the wind pressure distribution without the surrounding environment. The primary objective of this study is to examine the fluctuating coefficient variation rule based on the spacing between hillsides and buildings under 0° wind angle. Additionally, the study analyzes the fluctuating wind pressure coefficient across wind angles between 0°~90°. The distribution of wind pressure in different common hillside landforms was examined through a wind tunnel experiment, which also compared with the distribution in an open environment. The study examined the fluctuating coefficient as the distance between the building and the hillside changed, specifically for wind blowing at a 0° angle. Next, an analysis is conducted on the changing pattern of the fluctuating coefficient for low-rise buildings ranging from a wind angle of 0° to 90°. Simultaneously, the investigation examined the power spectrum and wind pressure’s probability distribution, while considering the proximity of the building to an adjacent hill. The findings indicated that the changing wind pressure factor on the surface of the structure differed based on the relative location of the hillside and the building. The roof's wind pressure coefficient fluctuated and gradually increased until it reached its peak, unaffected by the surroundings. The low-frequency energy decreased in windward eaves, while the high-frequency energy progressively rose as the distance between the hillside and the building increased. The wind pressure on the leeward side exhibited Gaussian characteristics in its probability distribution.

Abstract: The internationally accepted goals of eliminating climate gas emissions implies substantial investments in renewable energy (RE) facilities. This will inevitably lead to major impacts on landscapes. Landscape concerns linked to RE facilities are already leading to controversies in many local communities. In this article, we focus on the question of landscape democracy related to the establishment of RE facilities. Based on recommendations from the European Landscape Convention, an analytical framework is presented identifying three main dimensions of landscape democracy, followed by an overview of arrangements, procedures and methods that are or may be used to encourage democracy. The procedures and methods are analysed based on examples from Denmark and Norway. This is followed by an analysis of decision levels with a special focus on the principle of subsidiarity. Finally, recommendations are presented to strengthen landscape democracy in relation to the installation of RE-facilities.

We live in the world that is completely entangled on energy and thus, Humankind can no longer do without it, power. With electricity being the main form of energy today, this has increased the complexity of our life today. In Uganda, electricity generation is mainly through hydropower which put the country in the bottleneck of over dependence on one source of energy. Yet, there are many energy systems out there that country can diversify its electricity generation. Therefore, the need to understand, the level of development and utilization of various energy systems has been the underlying question for this present study. Comprehensive literature survey was conducted from the electronic databases including ScienceDirect, Wiley, Sage, Scopus, Taylor & Francis, and Google Scholar. The publications in form of reports, conference papers, working papers, discussion papers, journal articles, book sections and textbooks were considered in this study. In total, 11 energy systems including human and animal energy, solid biomass (firewood), hydropower, wind, geothermal, solar, nuclear, peat, coal, petroleum, and non-solid biomass (methanol, hydrogen, ethanol, biodiesel, and biogas) are described. The current and the future development and utilization of these energy systems has been described. The challenges with their development and utilization were elaborated and the solution the challenges were presented. The hydropower with River Nile being the main river for large hydropower plant construction is the dominance energy system in Uganda. Nuclear energy will be the salvation for the country’s electric energy supply in the near future. Therefore, Uganda needs to bet big on nuclear energy.

A preliminary study of a wind turbine design is carried out using a wind tunnel to obtain its aerodynamic characteristics. Utilization of data from the study to develop large-scale wind turbines requires further study. This paper aims to discuss the use of wind turbine data obtained from the wind tunnel measurements to estimate the characteristics of wind turbines that have field size. The torque of two small-scale turbines was measured inside the wind tunnel. The first small-scale turbine has a radius of 0.14 m and the second small turbine has a radius of 0.19 m. Torque measurement results from both turbines were analyzed using Buckingham π theorem to obtain a correlation between torsion and diameter variations. The obtained correlation equation is used to estimate the field measurement of turbine power with a radius of 1.2 m. The resulting correlation equation can be used to estimate the power generated by the turbine by the size of the field well in the operating area of the tip speed ratio of the turbine design.

Cancer-specific monoclonal antibodies (CasMabs) that recognize cancer-specific antigens with in vivo antitumor efficacy are innovative therapeutic strategies for minimizing the adverse effects. We previously established a cancer-specific anti-human epidermal growth factor receptor 2 (HER2)monoclonal antibody (mAb), H₂Mab-250/H₂CasMab-2. In flow cytometry and immunohistochemistry, H₂Mab-250 reacted with HER2-positive breast cancer cells but did not show the reactivity to normal epithelial cells. In contrast, a clinically approved anti-HER2 mAb, trastuzumab, strongly recognizes both breast cancer and normal epithelial cells in flow cytometry. The human IgG₁ version of H₂Mab-250 (H₂Mab-250-hG₁) possesses compatible in vivo antitumor effects against breast cancer xenografts with trastuzumab despite the lower affinity and effector activation than trastuzumab in vitro. This study compared the antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cellular cytotoxicity (CDC) between H₂Mab-250-hG₁ and trastuzumab. Both H₂Mab-250-hG₁ and trastuzumab showed ADCC activity against CHO/HER2 and breast cancer cell lines (BT-474 and SK-BR-3) in the presence of human natural killer cells. Some tendency was observed that trastuzumab showed a more significant ADCC effect compared to H₂Mab-250-hG₁. Importantly, H₂Mab-250-hG₁ exhibited superior CDC activity in these cells compared to trastuzumab. Similar results were obtained in mouse IgG_2a types of both H₂Mab-250 and trastuzumab. These results suggest the different contributions of ADCC and CDC activities to the antitumor effects of H₂Mab-250-hG₁ and trastuzumab and indicate the future direction for the clinical development of H₂Mab-250-hG₁ against HER2-positive tumors.

In mountain-gorge areas, the rock creep is the critical process for high rock slopes failure. During long-term rock creep, slopes might encounter earthquakes and form further creep after earthquakes. This complex mechanical response process can easily lead to the slope failure. Based on a high rock slope in the Nujiang River Basin, this paper analyzes deformation characteristics and dynamic response characteristics by using FLAC3D software, considering combined effects of multiple earthquakes and long-term creep. Results show that when the amplitude increases, the shear strength of the slope decreases and the risk of instability increases under combined actions of creep and earthquakes. Earthquakes promote the development of creep and induce the accumulation of damage on the slope surface and in the slope. The delayed effect becomes more pronounced as the slope height increases. We need to consider deformation differences of the slope further. The ground motion response on the slope surface is stronger than those in the slope, with the peak occurring at the top of the slope. Earthquakes have a greater impact on the middle and top of the slope surface, where cumulative damage and crack development begin. Reinforcement should be considered in these two places. Vertical earthquake has a great effect on the dynamic response. The phenomenon of slope resonance leads to a larger MPGA in the vertical direction than in the horizontal direction. Nonlinear and damping characteristics of the slope and the frequency of seismic waves cause the MPGA to decrease with the increase of amplitudes. This study could promote the development of high rock slope failure mechanism and provide references for the prevention of landslides in the Nujiang River Basin.

This study investigates the potential of a hybrid nanofluid composed of MoS2 and ZnO nanoparticles dispersed in engine oil, aiming to enhance the properties of lubricant's chemical reaction with the Soret effect on stretching sheet under the influence of applied magnetic field. With the growing demand for efficient lubrication systems in various industrial applications, including automotive engines, the development of novel nanofluid-based lubricants presents a promising avenue for improving engine performance and longevity. However, the synergistic effects of hybrid nanoparticles in engine oil remain relatively unexplored. This research addresses this gap by examining the thermal conductivity, viscosity, and wear resistance of the hybrid nanofluid, shedding light on its potential as an advanced lubrication solution. By analyzing the dispersion stability and interaction mechanisms between nanoparticles and base oil, valuable insights are gained into the fundamental aspects governing the entertainment of hybrid nano lubricants. Overall, the objectives of studying hybrid nano lubricant MoS2+ZnO with engine oil aim to advance the development of more efficient and durable lubrication solutions for automotive engines, contributing to improved reliability, fuel efficiency, and environmental sustainability. Governing non-linear partial differential equations are simplified as ordinary differential equations by utilizing similarity variables. MATLAB Bvp4c technique is used to solve the obtained linear ODE equations. The outputs are presented through graphs and tables for various state variables. The comparative survey in all the graphs is presented for the nanofluid (MoS2/Engine oil) with the hybrid nanofluid (MoS2+ZnO/Engine oil). These graphs show the effect of various parameters M, Q, β, Pr, Ec, Sc, Sr, Kp, Kr and (hybrid nano lubricant parameter). The velocity profile diminished against the values of M, Kp, and β. Temperature profile rising with Ec and Q. reciprocally goes down to Pr. The concentration profile incremented with the value of Sr and decremented with the value of Sc, and Kr. With the increasing value of both f′ (η) and θ(η) increases. But in θ(η) hybrid nanofluid slows down with the higher value of .

Knowledge-intensive business services (KIBS) are professional services that create new added value by creating, accumulating, and disseminating new knowledge. When it comes to conducting business involving new technology, KIBS play the roles of innovator, user, and producer of new technology that has led to technological innovation. This study aimed to determine the role of KIBS as a tool for innovation in a country’s economic system. Specifically, the degree and role of their impact on the Korean economy were analyzed and compared for the entire KIBS sector, T-KIBS (a new technology-based professional service), P-KIBS (a traditional professional service), and every subsector. For this purpose, the demand-inducement model, supply inducement model, and interlinkage effects method were applied using the 2019 input-output table published in 2022. The analysis showed that the indirect production inducement effect of the entire KIBS industry on other industries was 0.800 KRW, the indirect added value inducement effect was 0.330 KRW, and the supply disruption effect was 1.144 KRW. For T-KIBS, the indirect production inducement effect was 0.687 KRW, the indirect added value inducement effect was 0.272 KRW, and the supply disruption effect was 0.730 KRW. For P-KIBS, the indirect production inducement effect was 1.472 KRW, the indirect added value inducement effect was 0.646 KRW, and the supply disruption effect was 2.657 KRW. Finally, regarding the economic ripple effect of the KIBS subsector, legal and management support services and advertisements corresponding to P-KIBS showed higher figures than the T-KIBS subsectors in all sectors, including production inducement, the added value inducement effect, and the supply disruption effect. These results revealed that in the South Korean economic system, KIBS contribute to production and value addition across all industrial sectors. It is apparent that the absence of supply significantly disrupts other industries. Furthermore, production inducement effects are evenly distributed among all the KIBS subsectors in the secondary and tertiary sectors, while the value-added effects have a greater impact on the tertiary sector. In terms of the supply shortage effects, the secondary sector experiences a more significant impact. This underscores the crucial role of KIBS in sustaining and enhancing overall economic activity in South Korea. This study is significant in that it not only investigated KIBS as an industry group using the advantages provided by industry linkage analysis but also examined and compared detailed subsectors, thereby elaborately evaluating the influence relationship between KIBS and other industries. Therefore, the results presented in this study are expected to be useful for fostering the KIBS industrial sector and establishing economic innovation policies using KIBS.

Support effect is an important issue in heterogeneous catalysis while the explicit role of a catalytic support is often unclear for catalytic reactions. A systematic density functional theory computational study is reported in this paper to elucidate the effect of a model boron nitride (BN) support on the first N-H bond activation step of NH3 on Run (n =1, 2, 3) metal clusters. Geometry optimizations and energy calculations were carried out using density functional theory (DFT) calculation for intermediates and transition state from the starting materials undergoing the N-H activation process. The primary findings are summarized as follows. The involvement of the model BN support does not significantly alter the equilibrium structure of intermediates and transition state in the most favorable pathway (MFP). Moreover, the involvement of BN support decreases the free energy of activation, ΔG≠, thus improving the reaction rate constant. This improvement is more obvious at high temperatures like 673 K than low temperatures like 298 K. The BN support effect leading to the ΔG≠ decrease is most significant for the single Ru atom case among all three cases studied. Finally, the involvement of model BN may change the spin transition behavior of the reaction system during the N-H bond activation process. All these findings provide a deeper insight into the support effect on the N-H bond activation of NH3 for supported Ru catalyst in particular and for supported transition metal catalysts in general.

A bridged 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivative (PN-DOPO) in combination with aluminum phosphates coated sepiolite (Sep@AlPO4) was used to improve the flame retardancy, thermal stability and mechanical properties of poly (ethylene oxide) (PEO)/poly (butylene adipate-co-terephthalate) (PBAT) blends. The synergistic effects of PN-DOPO and Sep@AlPO4 on the fire resistance, thermal decomposition behavior and mechanical properties of PEO/PBAT composites were investigated systematically. The results indicated that 5 wt % Sep@AlPO4 combined with 10 wt% PN-DOPO into PEO/PBAT achieved a V-1 rating in UL-94 test and the LOI value increased to 23.7%, meanwhile, the peak-heat release rate (p-HRR), av-HRR and total heat release (THR) values of PEO/PBAT/PN10%/Sep5% composites decreased by 35.6%, 11.0% and 23.0% compared with those of PEO/PBAT, respectively. The thermogravimetric analysis (TGA) results confirmed that PN-DOPO/Sep@AlPO4 could enhance the initial thermal stability and char yield of PEO/PBAT matrix, and TGA/Fourier transform infrared spectrometry (TGA-FTIR) results revealed that the composites exhibited the absorption peaks of phosphorous-containing groups and an increase in gas-phase volatiles during the thermal decomposition process. The digital photographs and morphological structures of char residues demonstrated that PN-DOPO and Sep@AlPO4 mixtures benefited to the formation of a more continuous and dense carbon layer on the composites surface during combustion. Rheological behavior revealed that a higher storage modulus, loss modulus and complex viscosity of PEO/PBAT/PN-DOPO/Sep@AlPO4 composites could also promote the cross-linking structure during burning. Furthermore, the PEO/PBAT/PN-DOPO/Sep@AlPO4 composites exhibited excellent mechanical properties in terms of elongation at break and flexural performance than the PEO/PBAT system. All the results demonstrated that PEO/PBAT system modified by the combination of PN-DOPO and Sep@AlPO4 not only exhibited excellent synergistic effect on the flame retardance, but also had good improvement on thermal stability and mechanical properties, indicating the potential application in areas requiring fire safety.

This study aimed to elucidate the antibacterial efficacy and unique chemical compositions generated from plasma-activated water (PAW) when utilized a novel vaginal cleansing device. We conducted an analysis of antibacterial activity against probiotics and several chemical compositions including ions under various operational parameters of PAW, including electrical power (12 and 24 V), treatment duration (1, 10, and 20 min), and stay duration (immediate, 30 and 60 min). Our findings revealed that as treatment duration increased, hypochlorous acid (HOCl), Ca2+, and Mg2+ concentrations increased and Cl−concentrations decreased. Higher electrical power and longer treatment duration resulted in increased HOCl levels, which acts to prevent the growth of general microorganisms. Notably, PAW exhibited no antibacterial effects against a type of probiotic, Lactobacillus reuteri that produces lactic acid for vaginal health. This result demonstrated the ability of the vaginal cleaning device to generate ions, primarily HOCl and some cations (Ca2+ and Mg2+), thereby providing vaginal mucosa protecting and cleansing effects with the vaginal environment.

One of the key pathogenetic links of type 2 diabetes mellitus (T2DM) is the formation of insulin resistance (IR). Besides a wide selection of synthetic antidiabetic drugs, various plant-origin extracts are also available to support the treatment of T2DM. This study aimed to investigate and gain knowledge of the chemical composition and potential IR correction effect of American cranberry (Vaccinium macrocarpon Aiton) leaf extracts and formulate novel 3D-printed oral dosage forms for such extracts. The bioactivity and IR of L-arginine-loaded cranberry leaf extracts were studied in vivo in rats. The cranberry leaf extracts consisted of quinic, 3-caffeoylquinic (chlorogenic), p-coumaroylquinic acids, quercetin 3-O-galactoside, quercetin-3-O-glucoside, quercetin-3-xyloside, quercetin-3-O-arabino-pyranoside, quercetin-3-O-arabinofuranoside, quercetin 3-O-rhamnoside and quercetin-O-p-coumaroyl-hexoside-2 identified by HPLC. In-vivo studies with rats showed that the oral administration of the cranberry leaf extracts had a positive effect on insulin sensitivity coefficients under ITT test, and affected HOMA-IR levels and liver lipid content with experimental IR. A novel 3D-printed immediate-release dosage form was developed for the oral administration of cranberry leaf extracts using polyethylene oxide (PEO) as a carrier gel in a semi-solid extrusion (SSE) 3D printing. In conclusion, American cranberry leaf extracts loaded with L-arginine could find uses in preventing health issues associated with IR.

Maxwell equations governing electromagnetic effects are being shown to be equivalent to the compressible inviscid Navier-Stokes equations applicable in fluid dynamics and representing conservation of mass and linear momentum. The latter applies subject to a generalized Beltrami condition to be satisfied by the magnetic field. This equivalence indicates that the compressible inviscid Navier-Stokes equations are Lorentz invariant as they derive directly from the Lorentz invariant Maxwell equations subject to the same Beltrami condition. In addition, the derivation results provide support for the claim that electromagnetic potentials have physical significance as demonstrated by Aharonov-Bohm effect, and are not only a convenient mathematical formulation.

Cu-Sn shape-memory microwires were fabricated by a glass-coated melt spinning method. Effects of Sn content on the microstructure and mechanical property of microwires were investigated. The phase transforms from martensite to austenite with Sn content increasing from 14.0 atomic percent (at.%) to 16.5 at.%, and highly ordered intermetallic phase, δ, formed with higher Sn content. The fracture stress, σf, and the critical stress for martensitic transformation, σMs, increases with Sn content increasing. The mechanical property as well as superelasticity were improved greatly by high cooling rate of the glass-coated melt spinning method.

(1) Background: The emergence of antibiotic-resistant bacteria is a growing concern in the field of medicine. This has led to the need for alternative treatments for bacterial infections. (2) Methods: The present study aimed to investigate the synergistic effect of a water-based extract of S. fru-tescens and penicillin G on the growth of E. faecalis. (3) Results: The study found that the combina-tion of the plant extract and penicillin G had a synergistic effect on the inhibition of bacterial growth, with a significantly larger inhibition zone observed compared to penicillin G alone. The MIC and MBC tests also demonstrated that the combination of the plant extract and penicillin G was more effective against E. faecalis than penicillin G alone, with a dilution of 1 in 4 yielding 100% inhibition of growth. (4) Conclusion: Although the specific mechanism of action was not dis-cussed in the study, the results suggest that the combination of the plant extract and penicillin G may offer a promising alternative treatment for antibiotic-resistant infections. Further research is needed to determine the active compounds in the plant extract and to investigate the synergistic effect of the combination on other strains of bacteria.

We employed the Riemannian Face Manifold (RFM) as an alternative approach to the conventional linear Euclidean space for explaining the atypicality bias in face likeliness judgments. The RFM posits that the mental representation of faces is better captured as a manifold of stable states, accounting for the nonlinearity in the physical properties of faces. To examine the relationship between physical and psychological distance of morph and typical/atypical faces, we manipulated the parameter k and incorporated a weight function in the Riemannian metric. Our results indicate that the psychological distance between the morph and typical face was longer than that between the morph and atypical face, consistent with prior research on the atypicality bias in perceptual similarity. The RFM approach provides mathematical support and is a powerful tool for studying face perception and recognition, offering potential implications for explaining the other-race effect. Future research can utilize the RFM to investigate individual differences in face recognition abilities and expertise, and how they impact psychological distance and face processing.

Accurate measurement of low-level thoron gas and high-accuracy calibration of thoron measurement devices are essential for assessing and preventing thoron radiological risks. This study aimed to develop a thoron gas measurement technique using an airflow-through scintillation cell for both low-level measurement and high-accuracy calibration. To achieve this, a compartment model was developed to estimate the influence of progeny deposition and accumulation on the wall of the scintillation cell to prevent overestimation of thoron. A self-developed scintillation cell was utilized to implement and validate this technique. The lower detection limit and measurement uncertainty were then evaluated to assess the feasibility of the technique for low-level measurement and high-accuracy calibration. The results showed that the compartment model effectively addressed the influence of the progeny deposition. The measurement technique achieved a lower detection limit below 100 Bq m-3 even with the coexistence of 100 Bq m-3 of radon and attained a measurement uncertainty (k = 2) below 10% when the concentration of thoron exceeded 1,000 Bq m-3. In summary, this study developed a reliable and practical thoron gas measurement technique using an airflow-through scintillation cell with consideration for progeny deposition, and is expected to contribute to the assessment and prevention of thoron radiological risk.

In this age of global warming, academics and policymakers are increasingly concerned about firm environmental sustainability success. Therefore, this study aims to investigate whether Environmental, Social and Governance (ESG) performance impacts sustainability performance through the mediating effect of firm innovation. To this end, Structural Equation Modeling (SEM) was deployed to analyze data collected from the employees of manufacturing industries in an emerging economy like Bangladesh. The results revealed that ESG performance significantly enhances the innovation and sustainability performance of manufacturing industries, indicating that the higher the ESG performance of a firm, the greater its innovation and sustainability performance. Furthermore, the results confirmed that firm innovation performance fully mediates the relationship between ESG initiatives and sustainability performance. The findings of this study provide policymakers and industry authorities with valuable insight into the role of ESG and innovation performance in improving sustainability performance. Specifically, the study sheds knowledge on how firm ESG initiatives and innovation performance impact sustainability performance in the manufacturing sector of an emerging economy like Bangladesh.

In the development of the safety-critical systems, it is important to perform Failure Modes and Effects Analysis (FMEA) process to identify potential failures. However, traditional FMEA activities tend to be considered difficult and time-consuming tasks. To compensate for the difficulty of the FMEA task, various types of tools are used to increase the quality and the effectiveness of the FMEA reports. This paper explains an Automatic FMEA tool which integrates the Model-based Design (MBD), FMEA, and Simulated Fault Injection techniques in a single environment. The Automatic FMEA tool has the following advantages compared to the existing FMEA analysis tool. First, the Automatic FMEA tool automatically generates FMEA reports compared to the traditional spreadsheet-based FMEA tools. Second, the Automatic FMEA tool analyzes the causality between the failure modes and the failure effects by performing model-based fault injection simulation. In order to demonstrate the applicability of the Automatic FMEA, we used the electronic fuel injection system (EFI) Simulink model. The results of the Automatic FMEA were compared to that of the legacy FMEA.

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions like context familiarity influences affective feelings and is linked to cardiac-brain interactions. Hence to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that cardiac-brain interaction is dependent on familiarity such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.

The combination of organic matter, iron oxide, and clay minerals is of great significance for the adsorption of copper ions (Cu). The purpose of this study is to explore the characteristics of Cu adsorption and laws governing Cu complexation to organic–inorganic, organic–clay mineral, and iron-oxide–clay mineral complexes in the sediments in the estuary of plateau fault and sinking lake——Dianchi Lake. In this study, Cu adsorption tests were performed on the three complexes, in order to study the kinetic behavior of adsorption, Langmuir and Freundlich isotherm models were used. The samples before and after adsorption were characterized via scanning electron microscope (SEM), Fourier infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Our results show that, the Freundlich isotherm models model was able to describe adsorbent behavior in comparison to the Langmuir models. During the Cu adsorption process, the iron-oxide–clay mineral complex is able to adsorb Cu, via coordination exchange, through the –OH contained therein. Organic-matter–clay mineral complexes bonded to the surfaces of clay minerals by replacing the hydroxyl groups with functional groups (carboxyl groups or phenolic hydroxyl groups) contained in the organic matter. Organic–inorganic composites then adsorbed Cu through the coordination exchange of –OH in the polar functional groups of alcohols, phenols, and carboxylic acids. The adsorption capacity of Cu in these three sediment complexes was observed to have the following order: organic–inorganic complex &gt; organic-matter–clay mineral complex &gt; iron-oxide–clay mineral complex. The semi-quantitative analysis results of Fourier Infrared Spectroscopy show that the organic matter (changes in the peak area of functional groups such as carboxyl groups) in the organic-inorganic composite material has an important effect on the amount of copper ions adsorbed by clay minerals.

Understanding of the decisive role of the interaction mechanism and kinetics in the combustion processes is highly relevant for the elaboration of optimal conditions for obtaining Mo-Cu composite powders. From this perspective, the efficient delivery of the reduction mechanism of copper and molybdenum oxides with combined Mg + C reducing agents at high heating rates is crucial to develop a valuable approach for the combustion synthesis of Mo-Cu composite powders. Herein, we shed light on the mechanism of the reactions in all the studied binary, ternary and quaternary systems contemporaneously demonstrating the effect of the heating rate on the conversion degree. The combination of two highly exothermic and speedy reactions (MoO3+3Mg and CuO+Mg vs MoO3+CuO+4Mg) led to a slow interaction with weak self-heating (dysynergistic effect) due to a change in the reaction mechanism. On the other hand, it has been shown that during the simultaneous utilization of the Mg and C reducing agents, the process begins exclusively with carbothermic reduction, and at relatively high temperatures it continues with magnesiothermic one. The effective activation energy values of the magnesiothermic stages of the studied reactions were determined by Kissinger isoconversional method.

Keywords: underground engineering; numerical simulation; excavation length effect, major principal stress; displacement; damage initiation; CPU time

Pd-Pt catalysts supported on carbon preheated to 1600°C have been reinvestigated in CHFCl2 hydrodechlorination. An additionally adopted catalyst oxidation at 350-400°C produced an order of magnitude increase in the catalytic activity of Pd/C. This increase is not caused by changes in metal dispersion or possible decontamination of the Pd surface from superficial carbon, but rather by unlocking the active surface, originally inaccessible in metal particles tightly packed in the pores of carbon. Burning carbon from the pore walls attached to the metal changes the pore structure, providing easier access for the reactants to the entire palladium surface. As upon calcination the performance of the rest of the Pd-Pt/C catalysts changes less than for Pd/C, the relation between the turnover frequency and alloy composition does not confirm the Pd-Pt synergy invoked in our previous work. The use of even higher-preheated carbon (1800°C), completely free of micropores, results in a Pd/C catalyst that does not need to be oxidized to achieve high activity and excellent selectivity up to CH2F2 (>90%).

Neonatal palliative care (NPC) is an integrated and holistic approach that is an integral part of the contemporary neonatal treatment delivery paradigm. It is the highest fulfillment of the notion of beneficence (doing or creating 'good') that has otherwise been neglected/underestimated by the focus of modern medicine on technology and instrumental treatments by its commitment to alleviating patient pain and quality of life. For decades, the Double-Effect Doctrine (DDE) has been used to consider and address a range of ethically questionable circumstances, often at the end of life, including euthanasia, termination of pregnancy to save maternal life, and morally justified warfare. The theory has continued to be mired in controversy as ethicists, legal scholars, theologians, and philosophers discuss the abstract concepts of moral reasoning, purpose, foresight, and other underlying moral theories. In this paper, the moral theory of DDE is discussed in its clinical application to the ethical decision-making process in neonatal palliative and end-of-life treatment, specifically 1) the administration of opioids as required for symptom control and 2) the use of palliative sedation for intractable symptom care.

Soil CO2 efflux (FCO2) plays a dominant role in the terrestrial carbon (C) cycle but interpreting constraints on local observations is impeded by challenges in disentangling belowground CO2 sources. Trees contribute most C to forest soils, so linking aboveground properties to FCO2 could open new avenues to study plant-soil feedbacks and facilitate scaling; furthermore, FCO2 responds dynamically to meteorological conditions, complicating predictions of total FCO2 and forest C balance. We tested for proximity effects of individual Acer saccharum Marsh. trees on FCO2, comparing FCO2 within 1 m of mature stems to background fluxes before and after an intense rainfall event. Wetting significantly increased background FCO2 (6.4±0.3 vs. 8.6±0.6 s.e. μmol CO2 m-2s-1), with a much larger enhancement near tree stems (6.3±0.3 vs. 10.8±0.4 μmol CO2 m-2s-1). FCO2 varied significantly among individual trees and post-rain values increased with tree diameter (with a slope of 0.058 μmol CO2 m-2s-1 cm-1). Post-wetting amplification of FCO2 (the ‘Birch effect’) in root zones often results from the improved mobility of labile carbohydrates and further metabolization of recalcitrant organic matter, which may both occur at higher densities near larger trees. Our results indicate that plant-soil feedbacks change through tree ontogeny and provide evidence for a novel link between whole-system carbon fluxes and forest structure.