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Cancer hospitals could provide all required services for cancer patients and decrease the time-wasting of cancer-curing procedures and patients suffering from long travels between healthcare centers. This paper proposes a new fuzzy coefficient of determination of the fuzzy regression model to project the cancer patients' population and a fuzzy equity index based on the degree of possessing healthcare infrastructures. Besides, a new multi-objective mixed-integer linear mathematical model is proposed to establish a cancer hospitals network under cost, efficiency, and equity considerations. A fuzzy membership grade-based approach is employed to solve the proposed model in the case study of Iran using the CPLEX solver. The model-solving outputs provide a cancer hospital's location and cancer patients' allocation plan for Iran in 2040. Results of sensitivity analysis showed that the total cost, and equity function are considerably dependent on the cancer bed consumption rate. Finally, some managerial insights and future works are provided. [ABSTRACT FROM AUTHOR]

Uncertainty analysis is an inevitable attribute of location-allocation problems due to unforecastable parameter changes. Although the simultaneous variation of parameters is more realistic than their instinct variation, the simultaneous sensitivity analysis (SSA) of mixed-integer mathematical models’ outputs upon simultaneous changes of parameters’ value has taken no attention. In the metamodeling process using machine learning tools like regression models and artificial neural networks, several combinations of input values are used for metamodel creation. This paper employs this feature of metamodeling to propose an approach for global sensitivity analysis of mixed-integer mathematical models. The proposed approach is applied in analyzing a newly developed multi-period mixed integer mathematical model for cancer hospitals’ location-allocation problem in a case study. The comparison of results using SSA based on using Regression metamodel (RMM) and traditional one-factor-at-a-time (OFAT) methods showed different ranks of parameters. In addition to more adaptation of SSA to simultaneous changes of parameters in the real world, the created machine learning tools aim to forecast the corresponding outputs approximately when the mixed-integer mathematical model is infeasible or long-run upon some combinations of input parameters’ value. Finally, some applicable managerial insights and recommendations for future works are provided. [ABSTRACT FROM AUTHOR]

Freeform nanostructures have the potential to support complex resonances and their interactions, which are crucial for achieving desired spectral responses. However, the design optimization of such structures is nontrivial and computationally intensive. Furthermore, the current "black box" design approaches for freeform nanostructures often neglect the underlying physics. Here, a hybrid data‐efficient neural optimizer for resonant nanostructures by combining a reinforcement learning algorithm and Powell's local optimization technique is presented. As a case study, silicon nanostructures with a highly‐saturated red color are designed and experimentally demonstrated. Specifically, color coordinates of (0.677, 0.304) in the International Commission on Illumination (CIE) chromaticity diagram – close to the ideal Schrödinger's red, with polarization independence, high reflectance (>85%), and a large viewing angle (i.e., up to ± 25°) is achieved. The remarkable performance is attributed to underlying generalized multipolar interferences within each nanostructure rather than the collective array effects. Based on that, pixel size down to ≈400 nm, corresponding to a printing resolution of 65000 pixels per inch is demonstrated. Moreover, the proposed design model requires only ≈300 iterations to effectively search a thirteen‐dimensional (13D) design space – an order of magnitude more efficient than the previously reported approaches. The work significantly extends the free‐form optical design toolbox for high‐performance flat‐optical components and metadevices. [ABSTRACT FROM AUTHOR]

Despite their diverse applications, experimental studies on multi-phase flow with phase change in fractured porous media are rare in the literature. In this study, water condensation of vapor in a fractured sandstone is investigated by means of 3D rapid in situ neutron tomography (30 s per tomogram). A water vapor and air mixture is injected at a constant rate, and the accumulation of condensed water is characterized through neutron tomography. Both phase-contrast and absorption-contrast X-ray tomography are jointly used to study the microstructure of the sandstone and measure the morphology of the splitting crack. The interplay between the pore matrix and fissure on the spatiotemporal distribution of water is studied through a combination of these techniques. The condensed water accumulates at the inlet boundary and gradually diffuses into the sample. Once the extracted crack is correctly aligned with with the neutron tomographies (registered), a propensity is seen for water to accumulate in small crack openings close to the cracks and migrate into the porous matrix predominantly due to the capillary effect. When enough liquid water condenses beyond a critical content, the air pressure in the crack transfers it into the porous matrix. This results in higher water content away from the crack. The water front propagates both along and transversely to the crack at a linear rate, albeit at different velocities. The final water distribution is found to be the result of two competing processes: condensation, occurring predominantly in the crack, and diffusion toward the matrix due to the capillary effect, as well as the pressure acting on the bottom of the sample and the crack walls. [ABSTRACT FROM AUTHOR]

The development of high‐efficiency compact non‐mechanical beam tuning devices has attracted a lot of attention for light detection and ranging, augmented reality display, and chip‐to‐chip communication. Owing to the fast wavefront manipulation in an ultra‐thin dimension, metasurfaces have been regarded as potential substitutes for traditional tunable optical components toward further miniaturization and low power consumption. However, most beam tuning metasurfaces currently are polarization‐sensitive and designed to work in reflection mode, which limit their applications in integrated optical systems for full‐range steering. In this paper, a transmission mode polarization‐insensitive beam switching metasurface based on nonvolatile phase‐change material Ge2Sb2Te5 is proposed and experimentally demonstrated at the telecommunication wavelength. The high transmission efficiency with a large switching angle of up to 75° is achievable for potentially full‐range beam steering applications. As a proof of concept, the transmitted beam with a switching angle of 15° and directivity of 82.4% is demonstrated. In addition, by controlling the phase transition in the intermediate states, the metasurface can be used as a tunable beam splitter to control the ratio of the beam power between two predesigned transmission angles. The demonstrated phase‐change metasurfaces pave the way for achieving high‐efficiency dynamic beam steering for various important applications. [ABSTRACT FROM AUTHOR]

Miscible viscous fingering instability in a rectangular flow cell with engraved porous matrix was examined through experimental measurements and finger patterns were discussed in details to find out how fingers were generated or coalesced. Effects of injection rate, viscosity contrast, and gravitational field on instabilities were investigated based on Péclet number (Pe), viscosity ratio (VR), and Rayleigh number (Ra). Image processing techniques were performed to measure quantitative parameters including breakthrough time, sweep efficiency, fractal dimension, and perimeter of the interface. It was revealed that as the Péclet number and viscosity ratio increase, more complex fingers were produced and less sweep efficiency was reported. In this respect, when gravitational field was exerted by rotating the cell, new instability known as Rayleigh–Taylor amplified the former fingers. [ABSTRACT FROM AUTHOR]

The inherent thinness of two-dimensional 2D materials limits their efficiency of light-matter interactions and the high loss of noble metal plasmonic nanostructures limits their applicability. Thus, a combination of 2D materials and plasmonics is highly attractive. This review describes the progress in the field of 2D plasmonics, which encompasses 2D plasmonic materials and hybrid plasmonic-2D materials structures. Novel plasmonic 2D materials, plasmon-exciton interaction within 2D materials and applications comprising sensors, photodetectors and, metasurfaces are discussed. [ABSTRACT FROM AUTHOR]

In this paper, a novel microelectro-mechanical system (MEMS) U-shaped afloat is designed and used instead of a simple slot to activate and deactivate the band notch characteristic of an ultra wideband (UWB) monopole antenna at the WLAN band (5.15-5.825 GHz) without extra DC bias lines. The novelty of this work is design of MEMS afloat that can stay in down state permanently. When the dc actuation voltage, about 20 volts, is applied to the microstrip center line, the ?/2 long U-shaped afloat moves down and creates a slot (resonating element) in its vacant place. Whereas no voltage is applied, the afloat remains in the up position and serves as a part of the antenna, which eliminates the resonance. The proposed design for MEMS afloat has least negative effect on gain, reflection coefficient, and pattern of the antenna. The gain of the antenna is about 3.2 dBi over the entire UWB frequency band (3.1-10.6 GHz), while it decreases sharply over 7 dB at the rejection band. More-over, the time-domain characteristics of the antenna is investigated, which shows 1 ns delay over the UWB frequency band for 20 cm. Due to a novel afloat design, the addition of the resonance element does not affect on the radiation performance, reflection coefficient, gain, and group delay of the antenna outside of notched band frequencies. [ABSTRACT FROM AUTHOR]

In this paper, reduced temperature combustion has been investigated at high load condition of a direct injection Diesel engine. A 3-D computational fluid dynamics model for flow field, spray, air-fuel mixture formation, combustion, and emissions formation processes have been used to carry out the computations. The combined effect of exhaust gas recirculation temperature and exhaust gas recirculation rate was analyzed to choose with consideration of engine performance. Then, the influence of different injection rates and split injection was explored at a reduced temperature combustion condition by the use of exhaust gas recirculation. The results represent sensitiveness of various injection schemes on the combustion process and emission formation at reduced temperature condition in direct injection Diesel engines. [ABSTRACT FROM AUTHOR]

This paper is presented in order to elucidate some numerical investigations re-lated to a partially premixed gasoline fuelled engine by means of three dimen-sional computational fluid dynamics code. Comparing with the diesel fuel, gaso-line has lower soot emission because of its higher ignition delay. The application of double injection strategy reduces the maximum heat release rate and leads to the reduction of NOx emission. For validation of the model, the results for the mean in-cylinder pressure, heat release rate, NOx and soot emissions are com-pared with the corresponding experimental data and show good levels of agree-ment. The effects of injection characteristics such as, injection duration, spray angle, nozzle hole diameter, injected fuel temperature and exhaust gas recircula-tion rate on combustion process and emission formation are investigated yielding the determination of the optimal point thereafter. The results indicated that opti-mization of injection characteristics leads to simultaneous reduction of NOx and soot emissions with negligible change in indicated mean effective pressure. [ABSTRACT FROM AUTHOR]

Using hydrogen as an alternative fuel in spark-ignition engines has great potential for reducing exhaust emissions. Hydrogen engines have CO2 - and HC-free combustion and lean operation, offering lower nitrogen oxide (NOx) emission. In this paper, a numerical study of a direct injection spark-ignition (DISI) hydrogen-fueled engine was conducted via 3-dimensional computational fluid dynamics (CFD) methods and results were compared with experimental data, showing good agreement. Injection timing, initial charge temperature, and initial charge pressure were selected as effective and controllable parameters of emissions and performance characteristics. Results showed that mixture homogeneity was more affected by injection timing, and advancing the injection timing led to improved engine performance with a slight increase in NOx emissions. Increasing the initial pressure and decreasing the initial temperature led to better engine performance and reduced NOx emissions in the DISI hydrogen-fueled engine. [ABSTRACT FROM AUTHOR]

Parametric studies of a heavy duty direct injection (DI) gasoline fueled compression ignition (CI) engine combustion are presented. Gasoline because of its higher ignition delay has much lower soot emission in comparison with diesel fuel. Using double injection strategy reduces the maximum heat release rate that leads to nitrogen oxides (NOx) emission reduction. A three dimensional computational fluid dynamics (CFD) code was employed and compared with experimental data. The model results show a good agreement with experimental data. The effect of injection characteristics such as, injection duration, main SOI timing, and nozzle hole size investigated on combustion and emissions. [ABSTRACT FROM AUTHOR]