A general growth is being seen in the use of renewable energy resources, and photovoltaic cells are becoming increasingly popular for converting green renewable solar energy into electricity. Since the voltage produced by photovoltaic cells is DC, an inverter is required to connect them to the grid with or without transformers. Transformerless inverters are often used for their low cost and low power loss, and light weight. However, these inverters suffer from leakage current in the system, a challenge that needs to be addressed. In this paper, a topology with two alternative connection models is presented to stabilize the common mode voltage and reduce the leakage current. The output voltage characteristic of the proposed inverter is five-level, which reduces the harmonic distortion in the output current compared to the two- and three-level inverters. The operation modes and output of the proposed topology are described and analyzed. The structures of the proposed inverter are simulated in MATLAB/Simulink and are compared with some well-known structures. Results show that the proposed structure with both connection models effectively reduces leakage current and improves grid current THD.
A study on the principal parametric stimulation of rotating microbeams strengthened by means of graphene platelet is presented. The microbeam is exposed to a temperature gradient. On the basis of the assumptions of the hypothesis of the Timoshenko for beams alongside the modified couple stress hypothesis the nonlinear motion equations are achieved. It is supposed that the rotating speed of the microbeam varies harmonically about a mean quantity. The frequency of the harmonic term of the rotating velocity is presumed to be almost two times an axial or a transversal natural frequency. In such situation, the principal parametric agitation is stimulated. Assuming a proportional damping, a least square scheme is employed to define the Rayleigh’s coefficients. The impacts of the rotating speed, the weight fraction as well as the scattering pattern of the graphene platelets, and the damping coefficient on the presented results are examined. The results illuminate that as a consequence of the addition of the damping coefficient, the critical incitement amplitude constant increases more for reinforced microbeams rather than not-reinforced microbeams. Moreover, by means of enlarging the weight fraction of the graphene platelets, the critical incitement amplitude constant develops more for a rotating X microbeam rather than an O microbeam. Additionally, at moderate to high magnitudes of the damping coefficient, the instability area border aligned with the fundamental axial mode is impressed by the graphene platelet scattering pattern although it is invariant for small values of the damping coefficient. Moreover, by the development of the temperature the instability area border aligned with the fundamental transversal mode gets broader, while the critical incitement amplitude coefficient decreases; the both more for on O scattering pattern for the graphene platelet. Furthermore, the instability region boundary is more influenced by the graphene platelet weight fraction, while the critical incitement amplitude coefficient is more impressed by the damping coefficient design value.
This research studies the nonlinear buckling of two-dimensional functionally graded (2D-FG) nanotubes with porosity based on the Zhang-Fu theory of tubes, Timoshenko beam theory, and the nonlocal gradient strain theory (NSGT) as well as Von-Karmen nonlinear theory. In this paper, the formulation of the problem for various boundary conditions is generated according to the energy method. Then, the results are extracted by incorporating the generalized differential quadrature method (GDQM) coupled with the iteration method. The accuracy of the results is proven through comparative studies, and finally, the impact of different parameters, which influence the buckling of the nanotube, is investigated.
Electrorheological (ER) is a type of material that can change its state from liquid to solid by being under an electrical field, bringing much attention from researchers. So, in this article, the vibration of a three-layered disk made of an ER core and two graphene nanoplatelets reinforced composite (GPLRC) face sheets is carried out. The shear strain and stress of ER layer were obtained in the pre- and post-yield state. First- and third-order shear deformation theories (FSDT and TSDT) are utilized to model the face sheets and core of the structure. By using HDQM – hyperbolic differential quadrature method – the results are acquired. By employing other published studies, the validation investigation is carried out. Lastly, the influence of such parameters as graphene nanoplatelets (GPLs) distribution, foundation parameters, open-angle of the disk, the thickness of different layers, inner in addition to the outer radius of the disk, and GPLs’ weight fraction on the vibrational behavior of the system is investigated.
This study explores the current-voltage characterization of tungsten disulfide Nano-Flakes (WS2 NFs) Field-Effect-Transistor (FET) under various temperatures with a simple back-gate device structure. Due to the non-toxic nature of inorganic perovskite CsGeBr3 (CGB), this material is applied to fabricate a CGB/WS2 FET by drop-casting of lead-free perovskite CGB on the WS2 NFs FET. The characterization of fabricated two FET devices has been performed under the illumination of a laser source (at a wavelength of ∼532 nm) with three different temperatures (298°, 313°, and 333° K). The output and transfer characteristics of CsGeBr3/WS2 NFs FET illustrate that CGB is very effective in boosting the photocurrent and performance of the FET. For each two FET devices, increasing the temperature led to a decrease in drain-source current (Ids), whereas the rate of Ids reduction in CGB/WS2 NFs FET is roughly two times less than WS2 NFs FET. The results demonstrate that the conductivity and Ids of the CGB/WS2 NFs FET have been doubled compared to the bare WS2-NFs FET. Most importantly, the CGB/WS2 NFs FET shows higher external quantum efficiency, photo-responsivity, and detectivity in comparison with the WS2 NFs FET. The superior photo-sensing properties of the CGB/WS2 NFs FET are very promising to extend the two-dimensional optoelectronic devices with excellent performance.
In this study, the tribological properties of Al–15Mg2Si (AC), Al–15Mg2Si–3TiB2–TiAl3 (C31), and Al–15Mg2Si–5TiB2–4TiAl3 (C54) in-situ composites were evaluated. In the as-cast state, the optimal results were obtained for the C31 sample, where the wear rate and the average coefficient of friction (ACOF) under the load of 60 N decreased by ∼54% and ∼27% compared to those obtained for the AC sample, respectively. Morphological modification of primary and eutectic Mg2Si particles and increasing the volume fractions of TiB2 particles were characterized as key factors for improving wear resistance of C31 sample. On the other hand, the presence of needle-like TiAl3 particles resulted in severe delamination and separation of tribolayer and increased mass loss of C54 sample. Alternatively, the fragmentation and redistribution of eutectic/primary Mg2Si and TiB2/TiAl3 particles during elevated-temperature deofrmation, the reduction of casting defect by thermomechanical processing effects, as well as intense grain refinement by dynamic recrystallization (DRX) improved the mechanical properties of hot-extruded samples and led to a notable enhancement in the load bearing behavior and stability of the formed tribolayer even under high loads. Therefore, the wear mechanism changed from the combination of severe delamination, adhesive, and three-body abrasive wear in the as-cast composites to mild abrasive wear in the hybrid composites subjected to hot deformation by the extrusion process. Consequently, in the optimal condition and under load of 60 N, the wear rate decreased from 29.6 to less than 10 mg/km and ACOF decreased by about 24% in hot-extruded C54 sample compared to the AC sample.
Clustering and routing processes in underwater wireless sensor networks (UWSNs) are challenging tasks in the underwater environment due to the multiplicity of sensor nodes, transmission bandwidth, and limited energy resources. In order to address the shortcomings mentioned above, this paper proposes a novel hybrid Chimp Optimization and Hunger Games Search (ChOA-HGS) algorithms for clustering and multi-hop routing optimization in UWSNs. In this approach, first, the ChOA is used to choose cluster heads and efficiently structure clusters. Then, the HGS-based routing procedure is used to determine the network’s best pathways. The proposed approach combines the advantages of clustering and routing, resulting in optimal network lifetime and energy efficiency. The proposed ChOA-HGS is validated using a variety of measures after it is simulated using three different scenarios. In order to evaluate the performance of the ChOA-HGS, results are compared to PSO, MPSO, IPSO-GWO, TEEN, and LEACH. The results show that the ChOA-HGS outperformed other benchmarks in terms of lifetime and energy consumption.
This study focuses on late Campanian–early Thanetian calcareous nannofossils and foraminifera assemblages from the Gurpi and Pabdeh formations in the Fars province (SW Iran). To conduct biostratigraphic studies, the upper part of the Gurpi Formation and the lower part of the Pabdeh Formation were studied in Morgah stratigraphic section in Fars province. In this section, the upper part of the Gurpi Formation with 63 m thickness is mainly composed of gray argillaceous limestones and shale. Also, the base of the Pabdeh Formation includes 7 m of purple shales and argillaceous limestones. The upper boundary of the Gurpi Formation is also discontinuously associated with purple shales at the base of the Pabdeh Formation. In the biostratigraphic studies of the upper part of the Gurpi Formation, while identifying 29 species belonging to 20 genera of calcareous nannofossils, five biozones were identified. In addition, in biostratigraphic studies of the lower part of Pabdeh Formation, while identifying six species belonging to five genera of calcareous nannofossils, one biozone was identified. Based on the identified biozones, the transition of Gurpi Formation to the Pabdeh Formation in the studied section of Late Maastrichtian–Thanetian was determined. Also, based on a study based on planktonic foraminifera, four biozones were identified in the transition deposits of the Gurpi Formation to Pabdeh Formation. Biostratigraphic studies eventually led to a correlation between the two fossil groups.
Tungsten disulfide (WS2) nanoflakes are synthesized by thermal chemical vapor deposition on a Si/SiO2 substrate. Subsequently, WS2 is anchored by Au nanostructures to form Au/WS2 Schottky-type nano/hetero-junctions (Au/WS2 NHs), in various gold molar ratios of 1% and 10%, using DC magnetron sputtering. The crystalline structure, surface morphology and optical properties of the samples are investigated by X-ray diffraction, field emission scanning electron microscopy, UV–visible and Raman spectroscopy, respectively. UV–visible spectra reveal the reduction of absorption rate in terms of Au abundance. According to Raman spectra, there is a notable red shifting for A1g and E¹2g peaks and the elevation of A1g to E¹2g intensity ratio after Au anchoring. In addition, the Z-scan technique measures the corresponding nonlinear thermo-optical properties indicating a change over from self-focusing to self-defocusing modes in favor of Au/WS2 nanoflakes.
This paper proposes a variant of the Gray Wolf Optimizer (GWO) called the Cross-Dimensional Coordination Gray Wolf Optimizer (CDCGWO), which utilizes a novel learning technique in which all prior best knowledge is gained by candid solutions (wolves) is used to update the best solution (prey positions). This method maintains the wolf's diversity, preventing premature convergence in multimodal optimization tasks. In addition, CDCGWO provides a unique constraint management approach for real-world constrained engineering optimization problems. The CDCGWO's performance on fifteen widely used multimodal numerical test functions, ten complex IEEE CEC06-2019 suit tests, a randomly generated landscape, and twelve constrained real-world optimization problems in a variety of engineering fields, including industrial chemical producer, power system, process design, and synthesis, mechanical design, power-electronic, and livestock feed ration was evaluated. For all 25 numerical functions and 12 engineering problems, the CDCGWO beats all benchmarks and sixteen out of eighteen state-of-the-art algorithms by an average rank of Friedman test of higher than 78 percent, while exceeding jDE100 and DISHchain1e+12 by 21% and 39%, respectively. For all numerical functions and engineering problems, the Bonferroni-Dunn and Holm's tests indicated that CDCGWO is statistically superior to all benchmark and state-of-the-art algorithms, while its performance is statistically equivalent to jDE100 and DISHchain1e+12. The proposed CDCGWO might be utilized to solve challenges involving multimodal search spaces. In addition, compared to rival benchmarks, CDCGWO is suitable for a broader range of engineering applications.
Research in second language teacher education (SLTE) is critical for making short- and long-term policies and decisions about SLTE programs, materials, methods, etc. Therefore, it is essential to know the “what,” “how,” and “where” of SLTE research. Hence, the purpose of this synchronic study was to investigate research topics (what) and the research methodologies (how) of SLTE papers published in international and Iranian journals (where) between 2014 and 2020. To that end, we investigated a corpus, including 100 articles, consisting of 50 SLTE papers published in seven international journals and 50 SLTE papers published in seven Iranian journals. Results indicated that while there were significant differences in using qualitative and quantitative research methodologies by SLTE papers published in international and Iranian journals, there were no significant differences in using mixed methods in those journals. Moreover, results showed that the most frequent SLTE topics addressed in the papers published in international and Iranian journals were teacher professional development, teacher psychology, teacher identity, teacher cognition, teacher belief, teacher knowledge, practitioner research, teacher education design, sociocultural theory, teacher practice, and teacher and culture. However, there were no significant differences in SLTE topics addressed in the SLTE papers published in international and Iranian journals.
Contamination of soils and groundwater resources has become one of the most serious global environmental problems in recent years. The use of natural and inexpensive adsorbents such as zeolite is one of the appropriate methods to prevent the spread of contaminants and increase the adsorption capacity of the soil. Therefore, in the present study, zeolite is used as an option to improve the soil environmental condition. In this research, the behavior of the mixture of sand with 15% kaolinite clay is investigated at first, in both conditions of non-contaminated and contaminated with lead nitrate. Due to the limited adsorption capacity of the sand containing kaolinite, different percentages of zeolite adsorbent (as 5, 10, and 15 percent of soil weight) were added to this mixture to investigate the adsorption capacity and changes in strength parameters of the soil and adsorbent mixture. These parameters were also compared between zeolite and bentonite adsorbents. According to the results of the atomic adsorption test, zeolite has a favorable effect on increasing the adsorption capacity of heavy metals in soils such that by adding 5% zeolite, the amount of lead adsorption capacity increases by about 70%. Followed by investigating the static behavior and adsorption capacity of different compounds of soil containing adsorbent and without adsorbent, the dynamic behavior of these compounds in both conditions of non-contaminated and contaminated with lead nitrate was studied. The results show that in both contaminated and uncontaminated conditions, the initial shear modulus decreases with increasing zeolite content adsorbent. Also, dynamic behavior shows that in the combination of soil with both types of adsorbents, by increasing the concentration of heavy metal, the cycles corresponding to Ru decreases.
Pedestrians are the most vulnerable road users in traffic accidents. This study aims to analyze the effective factors in choosing the type of crossing by pedestrians. The required data were collected through interviews based on PBS questionnaire and video images of crossing pedestrians in Qazvin city. The observed variables such as individual characteristics, crossing choices, traffic volume and the role of latent variables of pedestrian behaviors are considered on crossing choices. Latent behavioral variables were identified through exploratory factor analysis and were divided into positive and negative habits. In addition, structural equation model, traditional binary logit, and hybrid discrete choice model were used in this paper. The results show that men are less likely to use a pedestrian overpass than women. In addition, young people in the range of 18-30 and 30-45 are more eager to use overpass than older ones. Further, negative behavioral habits such as distraction and inattention, error, and violation resulted in choosing a riskier alternative compared to level crossing. Further, positive behavioral habits such as daily walking had a positive effect on choosing safer crossing alternative (pedestrian overpass). The findings are useful in developing policy measures to build safe and efficient facilities.
Artificial intelligence (AI) techniques have been considered effective technologies in diagnosing and breaking the transmission chain of COVID-19 disease. Recent research uses the deep convolution neural network (DCNN) as the discoverer or classifier of COVID-19 X-ray images. The most challenging part of neural networks is the subject of their training. Descent-based (GDB) algorithms have long been used to train fullymconnected layer (FCL) at DCNN. Despite the ability of GDBs to run and converge quickly in some applications, their disadvantage is the manual adjustment of many parameters. Therefore, it is not easy to parallelize them with graphics processing units (GPUs). Therefore, in this paper, the whale optimization algorithm (WOA) evolved by a fuzzy system called FuzzyWOA is proposed for DCNN training. With accurate and appropriate tuning of WOA’s control parameters, the fuzzy system defines the boundary between the exploration and extraction phases in the search space. It causes the development and upgrade of WOA. To evaluate the performance and capability of the proposed DCNN-FuzzyWOA model, a publicly available database called COVID-Xray-5k is used. DCNN-PSO, DCNN-GA, and LeNet-5 benchmark models are used for fair comparisons. Comparative parameters include accuracy, processing time, standard deviation (STD), curves of ROC and precision-recall, and F1-Score. The results showed that the FuzzyWOA training algorithm with 20 epochs was able to achieve 100% accuracy, at a processing time of 880.44 s with an F1-Score equal to 100%. Structurally, the i-6c-2s-12c-2s model achieved better results than the i-8c-2s-16c-2s model. However, the results of using FuzzyWOA for both models have been very encouraging compared to particle swarm optimization, genetic algorithm, and LeNet-5 methods.
The unique therapeutic and biological characteristics of spirooxindole have led to the presentation of numerous reactions for the synthesis of spirooxindoles through 1,3-Dipolar cycloaddition of highly reactive isatin-derived azomethine ylides with activated olefins as the main tool for the formation of spirocyclic oxindoles during the last 4 years. Therefore, there is a need to highlight the recent developments in this area, along with the representative synthetic methods and relevant reaction mechanisms from 2018 to 2021. The representative synthetic methodologies were listed in four sections based on the procedure to form the azomethine ylide species including isatins and amino acids, isatin-derived α-(trifluoromethyl)imine, isatins and benzylamines, and from isatin-derived cyclic imine 1,3-dipoles. Graphical abstract
Transit signal priority (TSP) at signalized intersections is one of the important strategies to change the traffic signal schedule according to the priority of public transit. In this research, a TSP management strategy at signalized intersections using the dedicated short-range communication (DSRC) technology system and the Aimsun simulation model was evaluated as an effective method to decrease the delay of bus rapid transit (BRT) at intersections. The BRT line in this study was the Tehran-pars Intersection-Azadi Square in Tehran metropolis, Iran. This method was implemented in the morning and evening peak hours in a section of this line between Valiasr Intersection and Enghelab Square, with five intersections and three stations. The results showed that the application of this method reduced the measures of the effectiveness of delay, stop time, speed, and travel time for the morning peak hours by 18.82, 42.18, 3.81, and 3.67%, and for the evening peak hours by 22.16, 47.93, 3.91, and 3.97%, respectively. Moreover, a comparison was made between the models by examining the calibrated model of Tehran and the non-calibrated model with default parameters to determine the extent to which the management strategy of prioritizing public transport at signalized intersections can be related to drivers' behavior. The results showed that in the non-calibrated network, all outputs were in better condition. Moreover, significant improvements were obtained most of the time by prioritizing, indicating that the need for culturalization is more important in the Tehran metropolis.
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