Values Of Parameters Research Articles

A Multifactor Combination Optimization Design Based on Orthogonality for a Two-Degree-of-Freedom Floating Machine Gun Vibration System

This paper introduces a novel type of floating machine gun that can be simplified as a self-balancing two-degree-of-freedom mechanical system with distinct vibration characteristics. The model accounts for intricate motion patterns and encompasses numerous potential influencing factors. Multifactor combination optimization of the system represents a pressing engineering challenge. After establishing a simulation model for the machine gun and validating it experimentally, seven factors were chosen as optimization variables. The maximum recoil displacement of the inner receiver (MRD) and the firing rate were chosen to be indicators. Orthogonal combinations and variance analyses were used, and the effects of multiple factors were analyzed using SPSS software; these processes led to a determination of the optimal combination. The results indicated that the piston cylinder pressure, the bi-directional buffer spring energy storage, and the inner receiver mass significantly affected the MRD. Furthermore, the automaton mass and the reset spring energy storage were found to substantially affect the firing rate. Careful analysis of the variance results facilitated the determination of the optimal combination of parameter values. Remarkably, the optimal combination chosen resulted in an MRD reduction of approximately 20.2% and a firing rate increase of approximately 26.6%.

Intrinsically low lattice thermal conductivity and thermoelectric performance of 2D Cu2Te

In this study, we employed density functional theory to investigate the structural, mechanical, dynamical, electronic, and thermal transport properties of 2D Cu2Te in the hexagonal P6/mm structure. Our results demonstrate that this structure is both mechanically and dynamically stable, and has a direct band gap, indicating its potential as a semiconductor. The high Grüneisen parameter value of 2D Cu2Te resulted in a lower lattice thermal conductivity compared to its bulk counterpart due to increased phonon scattering in the 2D structure. Furthermore, we observed that the Seebeck coefficient in 2D Cu2Te is higher in the p-type region, while the electrical conductivity is higher in the n-type region at lower temperatures. Two different approaches were used to calculate the lattice thermal conductivity, and it was found that the thermal conductivity decreases with dimension reduction in Cu2Te. Additionally, ultralow thermal conductivity was observed. Moreover, the lattice thermal conductivity plays a dominant role in the thermoelectric performance. The maximum ZT value for 2D Cu2Te was obtained as 1.28 at 700 K. Overall, our results suggest that 2D Cu2Te is a potential new candidate for high thermoelectric performance.

Simulation Study on the Influence of Chimney Structure on the Efficiency of Gravity Heat Pipes for Controlling Spontaneous Combustion in Coal Waste Rock Piles

ABSTRACT Heat pipe is an efficient heat transfer element. Using heat pipes to control spontaneous combustion of coal gangue piles is a simple and effective method. However, the heat conducted by the heat pipe is usually directly released into the atmosphere, causing waste of resources. In order to utilize this part of the heat, this paper studied the method of enhancing the heat dissipation of the heat pipe. Based on the chimney effect, a chimney that utilizes the heat conducted by the heat pipe to enhance its heat dissipation efficiency was designed. The effects of five different parameters, including the distance between the chimney and the ground, the length of the chimney expansion section, the radius of the chimney inlet, the distance between the heat pipe and the inner wall of the chimney, and the height of the chimney, on the enhancement of heat dissipation of the chimney effect by the heat pipe were mainly studied. A large number of numerical simulation studies were carried out for chimneys with different structural sizes. The results show that all of the above five parameters have certain effects on the enhancement of heat dissipation of the chimney by the heat pipe, and each parameter has an optimal value to achieve the best enhancement effect of the chimney on the heat dissipation of the heat pipe. The response surface analysis was used to optimize the parameter values. The final designed chimney can increase the heat dissipation efficiency of the heat pipe by three times, providing a new direction for heat dissipation of heat pipes and the utilization of waste energy.

Numerical simulation on the MHD time-dependent Williamson nanofluid flow with cross diffusion and heat generation/absorption over a stretching plate

This novel study unfolds the heat and mass transfer investigation of Williamson nanofluid (WNF) through a porous medium past a stretching plate, along with considering heat generation/absorption. Nanoparticles hold significant significance in thermal engineering, industrial operations, and biomedical advancements, contributing to enhanced heat transfer, cooling mechanisms, thermal extrusion processes, and applications in cancer treatment, particularly in addressing brain tumors. The coupled ordinary differential equations (ODEs) are gained from governing partial differential equations (PDEs) by applying sufficient transformations. Then the ODEs of a nonlinear nature, along with boundary conditions, are solved through bvp4c, a built-in MATLAB program. A good agreement has been found in comparing the present study with already published papers. Numerical values for skin friction, mass transfer, and heat transfer are shown through a table against involved physical parameters, especially for both injection [Formula: see text] and suction [Formula: see text] cases, by varying the values of unsteadiness parameter A and Weissenberg number [Formula: see text]. The effects of the physical parameters on velocity, temperature, and mass profile are graphically depicted and illustrated minutely. It is noted that both the magnetic and Williamson parameters cause the thickness of the boundary layer to be reduced. It can be deduced from these findings that the rate of heat transfer over the surface of the plate decreases as the unsteadiness parameter increases. Furthermore, it is observed that an increase in the parameters of thermophoresis and Brownian motion leads to a higher temperature of the nanofluid.

SPATIAL PREDICTION OF RECEIVED SIGNAL STRENGTH FOR CELLULAR COMMUNICATION USING SUPPORT VECTOR MACHINE AND K-NEAREST NEIGHBOURS REGRESSION

Abstract. Signal strength maps are of great importance for cellular system providers in network planning and operation. Accurate prediction of signal strength is important for solving problems such as link quality. In this study, Received Signal Strength (RSS) prediction model is proposed for the 900 MHz band in the Van Yüzüncü Yıl University campus environment by using machine learning regression methods such as K- Nearest Neıghbours (KNN) and Support Vector Regression (SVR) together with Geographic Information Systems. For the training of this model, signal strength values taken from the RF Spectrum Analyser at different locations and distances were used. In addition, spatial data sets such as the digital elevation model, location of base stations and measurement stations, building heights and location, and land use/cover were used in the model. The effect of these data sets on RSS power is included in the model. The model aims to predict RSS accurately, visualize the estimated signal strength, and analyze the signal field strength coverage. Different kernels from the SVR model such as Polynomial, , and Sigmoid were tested. To increase the success of the model, appropriate parameter values were selected and configured according to SVR and KNN methods. For 900 MHz, the performances of SVR and KNN models were compared and the results of the models were verified using root mean squares (RMSE). Among the measured data, the lowest prediction is found in KNN Manhattan. According to the results of the simulation was observed that the SVR model created with spatial data performs better for Signal Strength. Finally, the lowest RMSE value (1.71 dB) was obtained from the Sigmoid kernel in the best signal strength estimation SVR model. The SVR model is recommended for Campus Area signal strength estimation.

Creation of a Simulated Sequence of Dynamic Susceptibility Contrast—Magnetic Resonance Imaging Brain Scans as a Tool to Verify the Quality of Methods for Diagnosing Diseases Affecting Brain Tissue Perfusion

DSC-MRI examination is one of the best methods of diagnosis for brain diseases. For this purpose, the so-called perfusion parameters are defined, of which the most used are CBF, CBV, and MTT. There are many approaches to determining these parameters, but regardless of the approach, there is a problem with the quality assessment of methods. To solve this problem, this article proposes virtual DSC-MRI brain examination, which consists of two steps. The first step is to create curves that are typical for DSC-MRI studies and characteristic of different brain regions, i.e., the gray and white matter, and blood vessels. Using perfusion descriptors, the curves are classified into three sets, which give us the model curves for each of the three regions. The curves corresponding to the perfusion of different regions of the brain in a suitable arrangement (consistent with human anatomy) form a model of the DSC-MRI examination. In the created model, one knows in advance the values of the complex perfusion parameters, as well as basic perfusion descriptors. The shown model study can be disturbed in a controlled manner—not only by adding noise, but also by determining the location of disturbances that are characteristic of specific brain diseases.

Optimizing chemotherapy treatment outcomes using metaheuristic optimization algorithms: A case study.

This study explores the dynamics of a mathematical model, utilizing ordinary differential equations (ODE), to depict the interplay between cancer cells and effector cells under chemotherapy. The stability of the equilibrium points in the model is analysed using the Jacobian matrix and eigenvalues. Additionally, bifurcation analysis is conducted to determine the optimal values for the control parameters. To evaluate the performance of the model and control strategies, benchmarking simulations are performed using the PlatEMO platform. The Pure Multi-objective Optimal Control Problem (PMOCP) and the Hybrid Multi-objective Optimal Control Problem (HMOCP) are two different forms of optimal control problems that are solved using revolutionary metaheuristic optimisation algorithms. The utilization of the Hypervolume (HV) performance indicator allows for the comparison of various metaheuristic optimization algorithms in their efficacy for solving the PMOCP and HMOCP. Results indicate that the MOPSO algorithm excels in solving the HMOCP, with M-MOPSO outperforming for PMOCP in HV analysis. Despite not directly addressing immediate clinical concerns, these findings indicates that the stability shifts at critical thresholds may impact treatment efficacy.

High-precision 1′ × 1′ bathymetric model of Philippine Sea inversed from marine gravity anomalies

Abstract. The Philippine Sea, located at the edge of the northwestern Pacific Ocean, possesses complex seabed topography. Developing a high-precision bathymetric model for this region is of paramount importance, as it provides fundamental geoinformation essential for Earth observation and marine scientific research, including plate motion, ocean circulation, and hydrological characteristics. The gravity–geologic method (GGM), based on marine gravity anomalies, serves as an effective bathymetric prediction technique. To further strengthen the prediction accuracy of conventional GGM, we introduce the improved GGM (IGGM). The IGGM considers the effects of regional seafloor topography by employing weighted averaging to more accurately estimate the short-wavelength gravity component, along with refining the subsequent modeling of long-wavelength gravity component. In this paper, we focus on seafloor topography modeling in the Philippine Sea based on the IGGM, combining shipborne bathymetric data with the Scripps Institution of Oceanography (SIO) V32.1 gravity anomaly. To reduce computational complexity, the optimal parameter values required for IGGM are first calculated before the overall regional calculation, and then, based on the terrain characteristics and distribution of sounding data, we selected four representative local sea areas as the research objects to construct the corresponding bathymetric models using GGM and IGGM. The analysis indicates that the precision of the IGGM models in four regions is improved to varying degrees, and the optimal calculation radius is 2′. Based on the above finding, a high-precision 1′×1′ bathymetric model of the Philippine Sea (5–35° N, 120–150° E), known as the BAT_PS model, is constructed using IGGM. Results demonstrate that the BAT_PS model exhibits a higher overall precision compared to the General Bathymetric Chart of the Oceans (GEBCO), topo_25.1, and DTU18 models at single-beam shipborne bathymetric points.

Exploring Cooperative Mechanisms in the Chinese Agricultural Value Chain: A Game Model Analysis Based on Leading Enterprises and Small Farmers

In the context of agricultural modernization in China, this paper examines the micro-level perspective of agricultural value chains. Drawing from three primary models of agricultural value chain cooperation—namely, “leading enterprises + small farmers”, “leading enterprises + cooperatives + small farmers”, and “corporate integration”—it establishes four game models: the decentralized decision-making game model, the two revenue-sharing game models, and the centralized decision-making game model. It systematically analyzes the cooperation mechanisms between leading enterprises and small farmers in upstream production links of the agricultural value chain, aiming to improve the cooperation strategy between leading enterprises and small farmers, elevate the status of small farmers in the agricultural value chain, promote increased income for farmers, and strengthen the agricultural value chain. The research findings are as follows: Firstly, the traditional contract of “leading enterprise + smallholder farmers” is incomplete, which makes it difficult to avoid opportunism and moral hazard that may arise between the two parties. By comparing multiple parameter values, it is found that this model is at a lower level of agricultural value chain development. Secondly, the model of “leading enterprise + cooperative + smallholder farmers” improves the tightness and stability of cooperation between leading enterprises and smallholder farmers. This model explains to some extent the operability of smallholder farmers sharing the value of the agricultural value chain. Compared with various parameter values, this model is at a medium level between other models. Finally, the “corporate integration” model is a fully vertical integration model. Compared with various parameter values, this model is at an advanced stage of agricultural value chain development. Therefore, agricultural value chains will ultimately develop toward the direction of corporate integration. This study has positive practical significance for enhancing the status and claim rights of small farmers, promoting increased income for farmers, enhancing the consistency of values between leading enterprises and small farmers, strengthening the stability of the agricultural value chain, and ultimately achieving common prosperity and agricultural modernization in China.

Thermophoretic particle deposition in a nanofluid flow across a disc with non-fourier heat flux: An investigation using tangent hyperbolic model

Non-Newtonian nanofluids are attracting the attention of researchers and academics due to the high heat transmission rates that they possess. To improve thermal devices and exchangers, the researchers come up with innovative and expense-effective methods. One of the advanced technological approaches that can be utilized to enhance the thermal performance of devices is the utilization of nanofluids. This non- Newtonian nanofluid possesses the advanced properties of increasing heat transfer and destroying harmful bacteria. For this purpose, the present theoretical work is to explore the heat and thermophoretic particle deposition analysis on the tangent hyperbolic nanofluid flow over the rotating porous disk with presence of non-Fourier heat flux model and nanoparticle aggregation effect. Darcy-Forchheimer fluid model is adopted to develop the fluid flow system. Furthermore, the nanofluid’s viscosity and thermal conductivity are expressed through advanced modeling, employing the modified Krieger-Dougherty model for viscosity and the Maxwell-Bruggeman model for thermal conductivity. The nanoparticles and base fluid involved in this context are Molybdenum disulfide ( Mo S 2 ) and Water/carboxyl-methyl cellulose (CMC) respectively. The mathematical representation of the fluid flow and energy propagation involves a system of coupled partial differential equations (PDEs). The system of partial differential equations (PDEs) is transformed into non-dimensional ordinary differential equations (ODEs), which are then solved both analytically and numerically using the Homotopy Analysis Method(HAM) and Runge-Kutta-Fehlberg (RKF) method along with shooting technique. Exploring the graphical representation reveals a comprehensive analysis of key factors influencing velocity, temperature, and concentration. Through innovative visualization, these parameters take center stage, providing insights into their intricate interplay and dynamic relationships. The heat transfer rate is enhanced 0.24% and 1.4% by rising the values of thermal relaxation parameter and Weissenberg number. Also, the mass transfer rate is accelerated 0.8% and 0.14% due to enhancing the values of thermophoretic coefficient and thermophoresis parameter.

Compactons in Higher-Order Nesterenko's-Type Equations

Abstract A model describing propagation of waves in a prestressed granular media is considered. The model, having the form of evolutionary partial differential equation (PDE), is obtained from the system of ordinary differential equations (ODEs) describing dynamics of a chain of prestressed granules by means of formal asymptotic expansion. It is shown in our previous papers that in the lowest asymptotic approximation, in which both nonlinear effects and the presence of media structure are taken into account, the model equation possesses traveling wave (TW) solutions with compact support (compactons) manifesting soliton properties. In this paper, we study a higher-order evolutionary PDE obtained by taking into account previously discarded terms of the asymptotic expansion, as well as another PDE (called analogue), differing from the original one in the values of parameters and having compacton solutions expressed in analytical form. Numerical and analytical studies of both the higher-order model and its analogue allow to conclude that both models have compacton solutions exhibiting some properties of “true” solitons. This, in turn, testifies the stability of the previously used model with respect to the inclusion of the discarded terms of the asymptotic expansion.

Projecting COVID-19 intensive care admissions for policy advice, the Netherlands, February 2020 to January 2021.

BackgroundModel projections of coronavirus disease 2019 (COVID-19) incidence help policymakers about decisions to implement or lift control measures. During the pandemic, policymakers in the Netherlands were informed on a weekly basis with short-term projections of COVID-19 intensive care unit (ICU) admissions.AimWe aimed at developing a model on ICU admissions and updating a procedure for informing policymakers.MethodThe projections were produced using an age-structured transmission model. A consistent, incremental update procedure integrating all new surveillance and hospital data was conducted weekly. First, up-to-date estimates for most parameter values were obtained through re-analysis of all data sources. Then, estimates were made for changes in the age-specific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a changepoint analysis guided by Akaike's Information Criterion.ResultsThe model and update procedure allowed us to make weekly projections. Most 3-week prediction intervals were accurate in covering the later observed numbers of ICU admissions. When projections were too high in March and August 2020 or too low in November 2020, the estimated effectiveness of the policy changes was adequately adapted in the changepoint analysis based on the natural accumulation of incoming data.ConclusionThe model incorporates basic epidemiological principles and most model parameters were estimated per data source. Therefore, it had potential to be adapted to a more complex epidemiological situation with the rise of new variants and the start of vaccination.

Optimization of surface roughness in milling of EN 24 steel with WC-Coated inserts using response surface methodology: analysis using surface integrity microstructural characterizations

Introduction: Among alloys of medium-carbon and high-strength steel, EN 24 steel is characterised by its nickel-chromium-molybdenum composition. EN 24 steel is highly suitable for application in heavy-duty projects due to its notable resilience to damage, especially when exposed to low temperatures. With the objective of minimising surface irregularities, this research endeavours to enhance the milling process of EN 24 steel by employing coated tungsten carbide (WC) tool inserts.Methods: Feed rate, cutting speed, depth of cut, and cutting fluid are all crucial process factors in the experimental investigation. Four distinct levels are applied to each factor. The research utilises the Design of Experiments (DOE)-based Central Composite Design of Response Surface Methodology. To predict output parameters, mathematical models are developed utilising analysis of variance (ANOVA) for optimisation purposes.Results and discussions: Through the utilisation of multi-objective optimisation, the optimal combination for tungsten carbide inserts was determined, which provided surface irregularities of 0.301 µm. Cutting speed (CS) of 149.507 m/min, feed rate (FR) of 340.27 mm/min, depth of cut (DOC) of 0.599 mm, and cutting fluid (CF) of 12.50 L/min are the optimal parameters. The surface morphologies of the machined workpiece at particular parameter values can be discerned through scanning electron microscope (SEM) analysis, yielding significant insights. The optimal parameters that have been identified provide practical recommendations for improving the milling method of EN 24 steel when tungsten carbide inserts are utilised. Understanding the milling process in its entirety is facilitated by SEM analysis of surface morphologies and microstructures under particular cutting conditions. The morphology and surface irregularities of the machined workpiece are evaluated using profilometry, which provides additional insight into surface integrity. The discourse investigates the potential applications and implications of the results, as well as suggests directions for further study concerning the enhancement of milling processes for similar steel alloys.

Monte Carlo Investigation of Dielectric Characteristics in Silicene–Germanene Nanosystem with Junction Connection

In this study, Monte Carlo investigation delves into the dielectric features of silicene–germanene nanosystem with junction connection. We emphasized the profound influence of physical parameters, coupling between Si–Si and Ge–Ge atoms and temperature, on these dielectric features. Our results highlight the pivotal role of the coupling parameter between Ge atoms in influencing blocking temperatures, underlining the significance of high values for spin and coupling parameters for achieving a high blocking temperature and delaying transitions. Furthermore, our analysis of electric hysteresis loops demonstrates their sensitivity to parameter variations, which can offer valuable insights for nanoelectronics and materials science applications.

Constitutive Modeling of Mouse Arteries Suggests Changes in Directional Coupling and Extracellular Matrix Remodeling That Depend on Artery Type, Age, Sex, and Elastin Amounts.

Arterial stiffening occurs during natural aging, is associated with an increased risk of adverse cardiovascular events, and can follow different timelines in males and females. One mechanism of arterial stiffening includes remodeling of the extracellular matrix (ECM), which alters the wall material properties. We used elastin haploinsufficient (Eln+/-) and wildtype (Eln+/+) mice to investigate how material properties of two different arteries (ascending aorta and carotid artery) change with age, sex, and ECM composition. We used a constitutive model by Dong and Sun that is based on the Holzapfel-Gasser-Ogden (HGO) type, but does not require a discrete number of fibrous ECM families and allows varied deformation coupling. We find that the amount of deformation coupling for the best fit model depends on the artery type. We also find that remodeling to maintain homeostatic (i.e., young, wildtype) values of biomechanical parameters with age, sex, and ECM composition depends on the artery type, with ascending aorta being more adaptable than carotid artery. Fitted material constants indicate sex-dependent remodeling that may be important for determining the time course of arterial stiffening in males and females. We correlated fitted material constants with ECM composition measured by biochemical (ascending aorta) or histological (carotid artery) methods. We show significant correlations between ECM composition and material parameters for the mean values for each group, with biochemical measurements correlating more strongly than histological measurements. Understanding how arterial stiffening depends on age, sex, ECM composition, and artery type may help design effective, personalized clinical treatment strategies.

Numerical simulation for radiative hybrid nanofluid (TiO2+Fe3O4∕H2O) flow due to a non-uniform stretching sheet with variable permeability

Variable permeability plays a crucial role in various manufacturing and technical applications such as fixed-bed catalytic reactors, heat exchangers, and dying, among others. The primary focus of this paper is to investigate the impacts of variable permeability on hybrid nanofluid (HNF) flow due to nonlinear sheet stretching with thermal heat flux. The HNF is made up of a mixer of [Formula: see text] and [Formula: see text] nanoparticles and water serving as the base fluid. Using efficient similarity transformations, the flow-governing equations are converted into a set of ordinary differential equations, and the resulting system is computationally solved by using the MATLAB program (bvp4c). The impact of various physical variables on the fluid velocity and heat transfer characteristics is analyzed via graphs. It is found that as the permeability parameter rises, the velocity of the HNF diminishes while the temperature amplifies. The drag force coefficient declines with an intensification of the volume fraction of the [Formula: see text] nanoparticles. The HNF [Formula: see text] exhibits 0.45–0.75% increase in heat transfer rate when compared to a nanofluid [Formula: see text] for different values of heat source parameter. The current investigation is compared to the existing literature, revealing a good level of agreement.

Water disinfection using hydrogen peroxide with fixed bed hematite catalyst - kinetic and activity studies.

A lab-scale reactor with a fixed-bed hematite catalyst for the effective decomposition of H2O2 and bacteria inactivation was designed. The bactericidal effect is the largest at a low initial bacterial count of 2·103CFU/L, which is typical for natural surface waters. When using a 5mM H2O2 solution and a residence time of 104min, the reduction in the number of E. coli bacteria is about 3.5-log. At a higher initial bacterial count of 1-2·104CFU/L, a 5mM H2O2 solution reduces the bacteria number by about 4-log. The H2O2 decomposition follows the log-linear kinetics of a first-order reaction while the bacterial inactivation does not. The kinetics of bacterial inactivation was described using the Weibull model in the modified form: log10(N0/N) =b · tn. The values of the non-linearity parameter n were found to be lower than 1, indicating that bacterial inactivation slows down over time. With increasing initial H2O2 concentration, the rate parameter b increases while the non-linearity parameter n decreases. With increasing temperature, both parameters increase. The stability of the catalyst has been proved by XRD, FTIR, SEM, and ICP-OES. The concentration of iron leaching into water during disinfection is much lower than the limit declared by WHO for iron in drinking water. The results show that technical-grade hematite is a promising Fenton-like catalyst for water disinfection. The fixed-bed reactor can be the basis of the mobile installations for water purification in emergencies.

Cost-effectiveness analysis of minimally invasive surgical treatments for benign prostatic hyperplasia: implications for Japan’s public healthcare system

Aims Benign prostatic hyperplasia (BPH) represents a significant public health issue in Japan. This study evaluated the lifetime cost-effectiveness of water vapor energy therapy (WAVE) versus prostatic urethral lift (PUL) for men with moderate-to-severe BPH from a public healthcare payer’s perspective in Japan. Materials and methods A decision analytic model compared WAVE to PUL among males in Japan. Clinical effectiveness and adverse event (AE) inputs were obtained from a systematic literature review. Resource utilization and cost inputs were derived from the Medical Data Vision database and medical service fee national data in Japan. Experts reviewed and validated model input parameters. One-way and probabilistic sensitivity analyses were conducted to determine how changes in the values of uncertain parameters affect the model results. Results Throughout patients’ lifetimes, WAVE was associated with higher quality-adjusted life years (0.920 vs. 0.911 year 1; 15.564 vs. 15.388 lifetime) and lower total costs (¥734,134 vs. ¥888,110 year 1; ¥961,595 vs. ¥1,429,458 lifetime) compared to PUL, indicating that WAVE is a more effective and less costly (i.e. dominant) treatment strategy across all time horizons. Lifetime cost-savings for the Japanese healthcare system per patient treated with WAVE instead of PUL were ¥467,863. The 32.7% cost difference between WAVE and PUL was predominantly driven by lower WAVE surgical retreatment rates (4.9% vs. 19.2% for WAVE vs PUL, respectively, at 5 years) and AE rates (hematuria 11.8% vs. 25.7%, dysuria 16.9% vs. 34.3%, pelvic pain 2.9% vs. 17.9%, and urinary incontinence 0.4% vs. 1.3% for WAVE vs PUL, respectively, at 3 months). Model findings were robust to changes in parameter input values. Limitations The model represents a simplification of complex factors involved in resource allocation decision-making. Conclusions Driven by lower retreatment and AE rates, WAVE was a cost-effective and cost-saving treatment for moderate-to-severe BPH in Japan compared to PUL, providing better outcomes at lower costs to the healthcare system.

Efficiency of the non-maximally entangled quantum Otto engine

We generalized the maximally entangled Hamiltonian of the isotropic Heisenberg XX model with two spin-1/2 particles to the case of non-maximal entanglement parametrized by the degree of non-maximality 0 < n < 1. The thermal concurrence as the function of the degree of non-maximality in the entanglement at different values of the exchange parameter is calculated. We analyzed the efficiency of the quantum Otto engine for different scenarios of exchange parameter regimes and the degree of maximal entanglement between the spin states. We showed that it is possible to run the quantum Otto engine using non-maximally entangled states and achieve higher efficiencies by controlling the exchange parameter value with respect to a critical value J c and this feature also depends on the degree of non-maximal entanglement n ≠ 1. This result may be useful for harnessing the non-maximal entanglement in quantum heat engine for optimizing the operation of quantum devices interacting with heat bath or environment.

CPV System Optical Performance Evaluation by Means of Direct Experimental Measurement Procedure

The optics is the component that most affects the concentrating photovoltaic (CPV) system performance, depending above all on the concentration factor and optical efficiency. Hence, a basic aspect is the concentrated solar flux measure on the receiving area, the evaluation of which is principally realized by indirect measurement methods. First, a literature review on indirect and direct methods used for the evaluation of concentrated solar flux and optical parameters is presented in this paper. The experimental measurement procedure, which is able to evaluate the optical parameters and concentrated solar flux in CPV systems, is also presented. The main steps of this procedure are represented by experimental system setup, sensor selection for concentrated solar flux estimation, identification of all the factors affecting optical performances, and development of an experimental campaign and output analysis. In particular, the optical characterization results of a CPV system are obtained by means of in-depth experimental analysis using Triple-Junction (TJ) solar cells with areas of 5.5 × 5.5 mm2 and 10 × 10 mm2. Three different setups have been analyzed related to primary and secondary optics composition. The main aim of this paper is the determination of a direct measuring technique, rarely adopted in literature in comparison to the established techniques, that is able to evaluate experimentally the optical parameter values and that can be standardized for other CPV systems. In particular, equations that link the optical concentration factor (C) and efficiency (ηopt) with focal distance (h) represent the fundamental results. They can be used for similar point-focus configurations presenting the same TJ cell size and ranges of C, ηopt and h. Finally, the experimental results of the direct method are compared with those of an indirect method adopting the same CPV system and operational conditions.