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Drilling muds play an important role in drilling and production operations so that the degree of success in such operations is determined by the proper design of these fluids. To optimize drilling operations and avoid excessive expenditure, it is essential to prepare a drilling mud that is both cheap and efficient. Fluid additives are typically used in drilling systems to improve these fluids' capabilities in terms of hole cleaning capacity, filtration control, viscosity, yield point, heat transfer, etc. However, environmental concerns, cost of production, and availability are always considered challenging factors. This study introduces an eco-friendly herbal fiber in powder and regular forms as a potential alternative to other chemical additives. To do so, Alyssum homolocarpum seed mucilage was added with different concentrations to the water-based drilling muds, and its rheological behavior, filtration control, and the induced formation damage were examined and the optimum concentration was introduced. The results of this study revealed the advantages of the drilling muds formulated with Alyssum in terms of filtration control, rheology, formation damage, and greenness.

This paper explores the time-delay nonlinear Susceptible–Infected–Recovered (SIR) model describing the credit risk contagion. This model describes the propagation of the financial crisis in the network of markets interacting with each other. First, we study the exponential stability of the time-delay SIR model and find sufficient conditions to achieve it. Thereafter, based on the feedback from a group of markets, the suitable fixed-time control law is developed under which all the participants of the network become healthy. The conditions presented in both sections are based on Linear Matrix inequality. Finally, the simulations for the presented theoretic results are presented.

In this study, the microstructural evolution, mechanical properties and biocorrosion performance of a Mg–Zn–Ca–Mn alloy were investigated under different conditions of heat treatment, extrusion, one pass and two passes of half equal channel angular pressing (HECAP) process. The results showed significant grain refinement of the homogenized alloy after two passes of HECAP process from 345 µm to 2 µm. Field emission scanning electron microscopy (FESEM) revealed the presence of finer Mg6Zn3Ca2 phase as well as α-Mn phase after HECAP process. The results also showed that mechanical characteristics such as yield strength, ultimate tensile strength and elongation of the HECAPed samples improved by ∼208%, ∼144% and ∼100% compared to the homogenized one, respectively. Crystallographic texture analysis indicated that most of the grains at the surface were reoriented parallel to the (0001) basal plane after HECAP process. Electrochemical corrosion tests and immersion results indicated that the sample with two passes of HEACP had the highest biocorrosion resistance confirming that the basal planes had the lowest corrosion rate compared to the non-basal ones. The mechanical behavior and bio-corrosion evaluation demonstrated that the HECAPed Mg–Zn–Ca–Mn alloy has great potential for biomedical applications and a mechanism was proposed to explain the interrelations between the thermomechanical processing and bio-corrosion behavior.

Multisource inverters (MSIs) as a new approach for the integration of the energy and the power sources in electric vehicle applications have gained considerable attraction. Such structures offer the active control of the dc sources without using any dc/dc converters or magnetic elements, which reduces the weight, and the volume of the power electronics interface between the sources and the load. Moreover, high power density and improved efficiency due to the elimination of the magnetics are the other significant features of an MSI. This article proposes a novel three-phase MSI for integration and active control of a high-voltage dc source and a low-voltage dc source. The proposed MSI structure employs a smaller number of semiconductor devices at the current path in various operating modes in comparison to the previously published counterparts, which results in an improved efficiency operation. Performance of the proposed MSI using a modified space vector modulation technique for all possible operating modes is verified through simulations and experiments on a laboratory prototype

Hot machining as one of the clean production techniques is used to improve the machinability of hard-to-cut materials. In this technique, an external heat source is used to soften the workpiece material and improves its machinability and sustainability by reducing the machining forces and eliminating cutting fluid application. In the present work, the conventional and hot turning of precipitation-hardened AISI630 stainless steel was evaluated in both numerical and experimental methods. Turning experiments were carried out using PVD-(Ti, Al)N/(Al, Cr)2O3-coated carbide tools, and the flank wear was measured by using scanning electron microscopy (SEM). Numerical analysis was carried out by finite elements method (FEM) to calculate the cutting tool temperature, cutting force values, and cutting force fluctuation. The numerical results showed that the hot turning not only decreases the cutting force but also decreases the amplitude of cutting force fluctuations up to 47%. The experimental results showed that hot turning at 300 °C reduces the tool’s flank wear and machined surface roughness up to 33% and 23%, respectively. Therefore, hot machining could be one of the realistic alternatives that can rise the machining processes on a sustainable level.

The space vector modulation (SVM) scheme is popularly implemented in multilevel converters. However, in flying capacitor-based (FC-based) multilevel converters, it becomes extremely challenging to implement due to the redundancy in phase voltage levels. The intrinsic property of line voltage redundancy of SVM in addition to the phase voltage redundancy of FC-based converters results in considerably increased computational complexity and storage requirements. In fact, one of the most important concerns about FC-based converters is the voltage control of the FCs. This article proposes a generalized decoupled SVM scheme for the FC-based multilevel converters, including the classic flying capacitor multicell (FCM) converters, which is less computationally complex. For balancing the FC voltages, an overall priority index is employed to determine the switching state with the best balancing characteristics. The proposed decoupled SVM scheme along with the capacitor voltage balancing scheme can be implemented intuitively and simply for all FC-based multilevel converters. The simulation results of a five-level FCM converter show the effectiveness of the proposed method in the regulation of FC voltages. Moreover, the proposed voltage balancing method is robust to static load and transient conditions. Also, experimental results demonstrate the effectiveness of the proposed method.

Despite the high utilization of commercial pure titanium in various applications, its performance in the modern engineering industry has created a new challenge due to its low mechanical properties and poor machinability compared to its alloying conditions. In this paper, equal channel angular pressing (ECAP) as a well-known severe plastic deformation approach was applied to the commercial pure (CP) titanium at the elevated temperature up to six passes. Although the initial sample mainly contains high-angle grain boundaries (HAGBs), some low-angle grain boundaries (LAGBs) are introduced by imposing four ECAP passes and the fraction of LAGBs is considerably increased up to 55 pct. By applying for additional ECAP passes and imposing more plastic strains, more amount of them is transformed into the HAGBs, exceeding 56 pct. It was found that the yield strength and hardness of the six-pass ECAPed sample reached 314 MPa and 249 Hv, indicating 96 and 51 pct increments as compared to the as-received condition, respectively, due to the considerable grain refinement after the process. However, the capability of processed titanium for further deformation was strictly restricted. The obtained moderate ductility of the sample after the processing was related to the decrease in the size and depth of the generated dimples in the fractured surface. The machining results showed that improvement of strength using the grain refinement led to a considerable reduction of originated cutting forces due to the reduction of friction coefficient and decrease in the tool wear rate. The mentioned two factors, as well as the discontinuous short chips, eventually result in a better surface finish of the ECAP-processed CP titanium.

Providing safe tap water has been a global concern. Water scarcity, the ever-increasing water demand, temporal variation of water consumption, aging urban water infrastructure and anthropogenic pressure on the water resources are the greatest challenges in effective water supply. In the present article, the waters exploited to be introduced in a water distribution system (i.e. input water) and tap waters are collected for determination of metal(loid)s, ions and physicochemical parameters. Seasonal variation is observed in the chemistry of the input waters. Further, the annual total dissolved solids (TDS) of the tap waters range from 200 to 1000 mg l-1 which stresses the importance of interconnections between urban water reservoirs for mixing different water types and adjusting water quality. It is complicated in populated cities like Naples with an old water distribution network, which also challenges setting up hydraulic and water quality models. The preliminary data visualization indicates the different chemical characteristics of some samples that are supposed to receive water from the same source. This might explain the difficulties in understanding the network layout in Naples. Thus, the compositional nature of chemical data was considered in hierarchical cluster analysis (HCA) to seasonally study water transfer between urban water reservoirs and define the source of tap water in each city area. The proposed method can preliminarily divide the pipe network into unique clusters and provide an overview of the relationships between different components when representative models cannot be set up due to limited information about network characteristics. Hence, advanced water distribution simulation and management is encouraged. This journal is

In this study, the energy, exergy and yield is calculated for two cultivars of quinoa (Sajama and Titicaca) production. The result shows that the energy consumption, exergy consumption, energy efficiency, and exergy efficiency for producing quinoa are calculated to be 10,932.34 MJ/ton, 14,6940 MJ/ton, 141.32% and 15.9% in Sajama cultivar and 6,442.42 MJ/ton, 98,243.6 MJ/ton, 215.3% and 20.6% in Titicaca cultivar, respectively. The grain yield of Titicaca cultivar is higher, although its growth duration is less as compared to Sajama cultivar. The combined application of bio-fertilizer with chemical fertilizers give the highest growth duration, grain yield, 1000-seed weight, biological yield and harvest index, when compared with the sole application of fertilizer and no fertilizer. Nitrogen fertilizer consumes the highest amount of total energy inputs followed by irrigation water and diesel fuel for quinoa production. About 97.5% of total input exergy consumed in quinoa production is water irrigation. Thus, it is clear that decrease in the use of irrigation water decreases the environmental impact and increases sustainability and vice versa. In pursuit of sustainable agriculture goals, Titicaca cultivar could be introduced as advanced cultivar in saline and drought stressed fields as a crop with high potential yield and nutritional value.

The significant global trend towards solar energy has led to the development of studies on the fabrication of high-performance solar cells. Accurate modeling and parameter identification of solar cells is of paramount importance. So far, several models have been proposed for the solar cell, including single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM). Each model has a number of unknown parameters and several methods have been presented in the literature to find their optimal values. In this paper, an efficient optimization algorithm, namely Whippy Harris Hawks Optimization (WHHO), is proposed to estimate the model parameters of solar systems. The proposed WHHO is an enhanced version of the HHO algorithm and has the advantages of high convergence speed, global search capability, and high robustness over the original method. To evaluate the efficiency of the proposed WHHO algorithm, it is utilized to identify the parameters of various models of solar cells, and photovoltaic (PV) module. The results are compared with those obtained from a number of other recently presented optimization methods, which shows the superiority of the proposed algorithm. Furthermore, the effectiveness of WHHO algorithm in the practical application has been assessed for the parameter estimation of three commonly-used commercial modules under different irradiance and temperature conditions, which yield variations in the parameters of the PV model. The results obtained from various experimental setups confirm the high performance and robustness of the proposed algorithm.

A single-layered slot antenna system working at 5.8 GHz Industrial, Scientific and Medical (ISM) band is proposed for in-band full duplex (IBFD) operation applications without the use of a coupler. First, high isolation is achieved by strong separation of even- and odd-mode feeds. The microstrip-coupled coplanar waveguide (CPW) is used at Port 1 (TX port) to excite a stepped-slot antenna in the CPW odd mode. On the opposite side, a microstrip T-junction power divider is employed at Port 2 (RX port) to feed two offset-fed stepped-slot antennas in even mode. Second, isolation is further improved by 30 dB by using a lumped capacitor at the termination of the CPW. The measured isolation between the two ports is about 50 dB across the bandwidth. The measured −10 dB bandwidth of Port 1 is 0.49 GHz (8.5%), while that of Port 2 is 1.06 GHz (18.3%). The gains of TX and RX antennas are 5.4 and 5.8 dBi at 5.8 GHz. The proposed antenna can also be deployed as a dual-polarized antenna. Mathematical analysis and equivalent transmission line circuit models are provided to give physical insight into the working principals of the antenna with validation from ANSYS HFSS simulation.

Background: Discovering new chemotherapy drugs and techniques with the least side effects is one of the most important and challenging issues in recent years worldwide. Chlorambucil is an anticancer drug that is still commonly used as a primary treatment in treating some cancers, but it can cause side effects. Objective: In this study, we decided to use chitosan as a carrier for enhance the uptake of chlorambucil and reduce the toxicity of this drug. Methods: After producing this nanoconjugate compound and analysing its structure by FTIR, DLS and AFM analysis, we investigated the therapeutic and biological effects of this nanoconjugate compound on the MCF-7 cell line (breast cancer). Results: The results of the MTT assay showed that this nanoconjugate compound not only retained its anticancer effect against chlorambucil but also showed less abnormal toxicity. In addition, in vitro cellular uptake by flow cytometry indicated the better uptake final product into the MCF-7 cells. The detection of apoptosis induced cell death was confirmed by RT-PCR. Conclusion: This study has created a prospective pathway for targeting cancer cells using chitosan.

Recently, a hybrid average-value/detailed modeling technique has been presented for efficient electromagnetic transient (EMT) simulation of power systems containing ac–dc line-commutated rectifiers (LCRs). In this letter, the hybrid modeling methodology is extended to consider asymmetrical operation of LCRs due to internal faults of switches. The hybrid model permits large time-steps as opposed to conventional switching models that require precise handling of switching events and respectively small time-steps. The extended hybrid model is also demonstrated to possess numerical advantages over the existing state-of-the-art average-value models (AVMs) of faulty LCRs while providing more accurate results.

AZ80 magnesium alloy reinforced by hybrid carbonaceous phase (GNPs + CNTs) is fabricated using semi-solid casting (rheocast) followed by hot extrusion (430 °C) processes through cost efficiency. This study presents the efficiency of GNPs + CNTs reinforcement in the enhancement of mechanical properties of AZ80 matrix composite with the insight of texture and microstructure evaluations. Pre-dispersed GNPs + CNTs as a network structure reinforcement provides the fairly homogeneous dispersion of GNPs + CNTs into the AZ80 matrix. Related to AZ80 alloy, the composite with only 0.1 wt% GNPs + CNTs illustrate 112%, 148%, and 277% enhancement in yield strength, fracture strain, and toughness up to 231 MPa, 10.9%, and 3156%, respectively. It reveals an extraordinary efficiency of strengthening and toughening of 1400 and 3469, respectively.

Background Ceftriaxone is one of the most common types of antibiotics used to treat most deadly bacterial infections. One way to alleviate the side effects of medication is to reduce drug consumption by changing the ordinary drug forms into nanostructured forms. In this study, a nanostructured lipid carrier (NLC) containing hydrophilic ceftriaxone sodium drug is developed, and its effect on eliminating gram-negative bacteria Escherichia coli death is investigated. Methods Double emulsion solvent evaporation method is applied to prepare NLC. Mathematical modeling based on the solubility study is performed to select the best materials for NLC preparation. Haftyzer-Van Krevelen and Hoy’s models are employed for this purpose. Drug release from optimized NLC is examined under in vitro environment. Then, the efficacy of the optimized sample on eliminating gram-negative bacteria Escherichia coli is investigated. Results Mathematical modeling reveals that both methods are capable of predicting drug encapsulation efficiency trends by chaining solid and liquid lipids. However, Haftyzer-Van Krevelen’s method can precisely predict the particle size trend by changing the surfactant types in water and oily phases of emulsions. The optimal sample has a mean particle size of 86 nm and drug entrapment efficiency of 83%. Also, a controlled drug release in prepared nanostructures over time is observed under in-vitro media. The results regarding the effectiveness of optimized NLC in killing Escherichia coli bacteria suggests that by cutting drug dosage of the nanostructured form in half, an effect comparable to that of free drug can be observed at longer times. Conclusion Results confirm that NLC structure is an appropriate alternative for the delivery of ceftriaxone drug with a controlled release behavior.

Using solid-state power amplifiers for next generation of weather radars becomes feasible by pulse compression techniques. In this study a 1.5 kW solid-state power amplifier (transmitter) for C-band weather radars is designed and fabricated by GaN high electron mobility transistor (HEMT) technology. An experimental setup based on heterodyne receiver with 16-bit digitiser is developed to investigate the behavior of the power amplifier under different cooling methods and back-off points. Several measurements with shaped LFM pulse show an approximately identical pulse to pulse (P2P) stability for 3 dB compression, P1dB and 2 dB back-off points while the best sidelobe level (SLL) is achieved for 2 dB back-off point. To study the effect of different cooling techniques on P2P stability and time SLL, two power amplifiers with the same transistors but different cooling methods are examined. Measurement results for 100 µs pulse duration indicate that the power amplifier with liquid cooling method shows 56 dBm output power with 0.1 dB droop while the forced-air cooling one shows 55.5dBm output power with 0.3 dB droop. While the liquid cooling technique shows 3 dB improvement in the overall P2P stability, its time SLL is deteriorated. To the authors' knowledge, this is the first experimental study on the time SLL under different back-off points and cooling techniques.

Some input-output classifier data envelopment analysis (DEA) models in multiplier and envelopment forms were developed to designate the status of flexible measures, playing either input or output roles. These models ignore the role of non-Archimedean epsilon in the input-output classification process. We show that these epsilon-free models may ignore some flexible measures in the performance evaluation process and hence the status of such flexible measure(s) can be randomly and inappropriately identified. To fill this gap, we develop a pair of epsilon-based multiplier and envelopment classifier models. We also develop an approach to find a suitable epsilon value for our developed classifier models. A case study of the supplier selection problem in the Iranian Space Research Center (ISRC) is provided to illustrate the potential application of our new epsilon-based approach.

This study compared 3 commonly used quenching agents for dechlorinating samples prior to disinfection byproduct (DBP) analysis under typical drinking water sampling conditions for a representative suite of chlorination byproducts. Ascorbic acid and sodium sulfite quenched the residual free chlorine to below detection within 5 seconds. Ammonium chloride did not quench the chlorine to below detection with up to a 70% molar excess, which agrees with published ammonium chloride-chlorine chemistry. With respect to the DBPs, ascorbic acid worked well for the trihalomethanes and haloacetic acids, except for dibromoiodomethane, which exhibited 2.6–28% error when using ascorbic acid compared to non-quenched control samples. Sodium sulfite also worked well for the trihalomethanes (and performed similarly to ascorbic acid for dibromoiodomethane) and was the best performing quenching agent for MX and the inorganic DBPs, but contributed to the decay of several emerging DBPs, including several halonitromethanes and haloacetamides. Ammonium chloride led to considerable errors for many DBPs, including 27–31% errors in chloroform concentrations after 24 hours of storage. This work shows that ascorbic acid is suitable for many of the organic DBPs analyzed by gas chromatography-electron capture detection and that sodium sulfite may be used for simultaneous chlorite, chlorate, and bromate analysis. HIGHLIGHTS Low ascorbic acid and sodium sulfite doses quenched chlorine within 5 seconds.; Ascorbic acid had minimal effect on most of the organochlorine byproducts tested.; Sodium sulfite was the best-performing quenching agent for the inorganic byproducts.; Ammonium chloride led to errors for chloroform and several nitrogenous byproducts.

Handling complexity in conceptual ship design processes requires a thorough understanding of complexity aspects in general. More than 100 scientific papers on the subject published since 1962 are, therefore, reviewed and discussed in this paper. The paper expands the understanding of complexity theory by reviewing the literature in the engineering domain. Different definitions of complexity, characteristics of complex systems, aspects of complexity in design, complexity sources, and its drivers are explored and discussed in detail. Furthermore, the findings are arranged into relevant complexity factors in ship design. Related complexity factors in ship design, are also discussed by use of examples from everyday ship design practices. This study is a theoretical elaboration to shed light on the current practice and future research direction in handling complexity in conceptual ship design processes to improve competitiveness.

The presence of the eutectic phase (delta ferrite + M23C6) in martensitic stainless steels brings significant deterioration of the in-service mechanical properties of the critical components such as turbine shaft made of these alloys. In the present study, thermodynamic and kinetics of eutectic phase formation during solidification and the reheating stages before forging of a large size X38CrMo16 martensitic stainless steel ingot are investigated. Material characterization and microstructural evolution were characterized in three different zones of a large size ingot. It was observed that the forging temperature and the solidification rate were the two most effective parameters influencing the volume fraction of the eutectic phase and its morphology. Optical and electron microscopy observations along with Energy Dispersion Spectroscopy (EDS) and Electron Backscatter Diffraction (EBSD) measurements were used in the investigation. The results showed that the eutectic phase precipitated primarily at the grain boundaries. Furthermore, a clear evolution on the morphology and volume fraction of the eutectic phase including thin film-like and skeleton-like carbides was found from the outer surface to the center of the ingot along the radial direction. EDS analysis revealed the substantial presence of chromium, molybdenum, and carbon within the M23C6 along the grain boundaries. Phase transformation and the precipitation phase sequences were analyzed as a function of temperature and composition of eutectic transformation using the Thermo-Calc software and the predictions were validated with experimental findings.

This paper presents a highly sensitive phase-variation sensor for dielectric constant measurements based on a capacitively-loaded periodic slow-wave transmission line. Such line is implemented in microstrip technology, and the loading capacitors are formed by closely spaced rectangular patches. The sensing area of the device is delimited by the region occupied by the capacitive patches, where the material under test (MUT) must be located. The presence of the MUT modifies the coupling capacitance between adjacent patches, thereby producing a variation in the electrical length, or phase of the transmission line, which is the output variable. A detailed analysis of the equivalent circuit model of the unit cell, useful for design purposes, is carried out in the paper. Based on such analysis, a prototype device sensor is designed and fabricated. It is demonstrated in the paper that the sensitivity of the proposed sensor is by far superior to the one achieved in an ordinary meandered line with similar sensing area. Thus, the proposed slow-wave structure constitutes a good alternative to meandered lines for the implementation of phase-variation sensors with simultaneously high sensitivity and compact size.

A new sub-1V and low power multiphase voltage-controlled oscillator (QVCO) with current-reused structure is proposed. The proposed core oscillator consists of two N-metal oxide semiconductor (NMOS) and P-metal oxide semiconductor (PMOS) transistors and an additional NMOS-only cross-coupled pair that enhances the effective negative transconductance and facilities the start-up condition at sub-1V supply voltages in modern nm CMOS technologies. In the proposed coupling scheme, the gate of cross-coupled transistors is used for coupling in an ‘in-phase−anti-phase’ manner. Parallel capacitors to the drain-source of transistors have been used for further enhancement of effective transconductance and thus lower power consumption; though the increase of parallel capacitors reduces the tuning range, indicating a trade-off in the proposed QVCO. The proposed quadrature oscillator is designed and simulated in a standard 0.18 μm RF-CMOS technology. The results of the simulation show that the QVCO has a 9% tuning range from 5.35 GHz to 5.88 GHz, and the phase noise is −119.6 dBc/Hz at 1-MHz offset from the 5.7 GHz carrier while consumes only 1.4 mW from a 0.85-V supply voltage; yielding an excellent figure-of-merit (FOM) of −193.3 dBc that is amongst the best FOMs. Several Monte Carlo and PVT analyses verify the robust performance of the QVCO.

Porosity parameters are one of the structural properties of the extracellular microenvironment that have been shown to have a great impact on the cellular phenotype and various biological activities such as diffusion of fluid, initial protein adsorption, permeability, cell penetration and migration, ECM deposition, angiogenesis, and rate and pattern of new tissue formation. The heterogeneity of the study protocols and research methodologies do not allow reliable meta-analysis for definite findings. As such, despite the huge available literature, no generally accepted consensus is defined for the porosity requirements of specific tissue engineering applications. However, based on the biomimetic approach, the biological substitutes should replicate the 3D local microenvironment of the recipient site with matching porosity parameters to best support local cells during tissue regeneration. Ideally, the porosity of biomaterials should mimic the porosity of the substituting natural tissue and match the clinical requirements. Careful analysis of the impact of architectures (i.e., porosity) on biophysical, biochemical, and biological behaviors will support designing smart biomaterials with customized architectural and functional properties that are patient and defect site-specific.

Groundwater level observations due to the lack of synoptic water-level measurements are often available with irregular time intervals. The results lead to an inaccurate understanding of the parameters affecting groundwater level changes and their time delays. This paper presents a simple and low-cost approach to interpolate the irregular, periodic intervals of recorded groundwater level data for the Najafabad aquifer located in central Iran. Forty-six monitoring wells with an average of 20 years of data were used for this study. Piecewise cubic Hermite interpolating polynomial (PCHIP), cubic spline, linear, and nearest neighbor are the selected interpolation methods. Cross-validation with leave-one-out technique was also applied to evaluate the accuracy of the methods under three conditions, including low, average, and high groundwater level decline. The analysis proved that (1) PCHIP interpolation showed a high performance in all of the groundwater level decline conditions (0.22

In the recent years, unmanned aerial vehicles (UAVs) because of their ability to be used as aerial base stations for collecting data from IoT devices have attracted substantial interest in Internet of Things (IoT) systems. In this paper, a novel method has been proposed to increase the quality of the uplink IoT communications and to decrease the transmission power of IoT devices. For this purpose, to compute the UAVs’ trajectory, association of device-to-UAV and IoT transmission power, a novel objective function has been defined to optimize the link quality and energy consumption in the considered UAV-based IoT system. Then, for optimizing this objective function, a novel constrained version of gravitational search algorithm is proposed, which is an NP-hard problem. In this algorithm, to handle the constraints, a multiple constraint ranking method is used. Moreover, to calculate the value of the parameter of this method, a fuzzy logic controller is used to control the exploitation and exploration abilities and improve the performance of this algorithm. To evaluate the performance of the proposed method, simulations have been performed and the results were compared with those of the other methods. the experimental results show that an increase in system throughput and a decrease in the energy consumption of the considered UAV-based IoT system can be achieved simultaneously using the proposed optimization algorithm.

Microwave broadband dielectric spectroscopy (MBDS) is generally recognized as an experimental method to characterize different materials (solids and liquids) according to their dielectric properties [1]. The dielectric properties of many materials over the RF/microwave frequency range are uniquely defined. As a result, using the MBDS technique, the complex relative permittivity of a material under test (MUT) is extracted as a function of frequency. Due to its nondestructive and real-time nature, MBDS is promising for a variety of applications, such as chemical/biological sensing, oil exploration and processing, food and drug quality control, disease diagnosis, and biothreat detection [2]-[5].

This research has investigated the simulation of sustainable water resources management to assess the impact of socio-economic development on water, food and energy resources security in Khuzestan Province in Iran. To achieve this goal, after simulation of the water-food-energy system dynamics model, taking into account results of the sensitivity analysis, development of water resources sustainability policy-making was elaborated in the form of four strategies of water demand, water supply, food resource and energy demand management, as well as combined policies. The simulation results of the proposed solutions were selected to be a combination of the strategies of water demand and food resources management as the best policies. Hence, 16% increase in irrigation efficiency, 10% improvement in cultivation patterns, 6% reduction in agricultural products losses, 5% decrease in food demand due to food losses, and 5% annual increase in the performance of agriculture are selected as sustainable water resources management policies.

The current study was performed for the optimisation of the biodiesel production from E. fetida earthworms oil using the transesterification method. Rice husk was sulphonated by sulphuric acid and ...

This paper aims to find the possible relationships between winter precipitation (December, January, February; DJF) in Iran with three oceanic sources through the correlation wavelet analysis by applying the continuous wavelet transform (CWT), the cross–wavelet transform (XWT), and the wavelet transform coherence (WTC). The sources in the North Atlantic Ocean (30°W-70°W, 10°N-30°N), the South Pacific Ocean (80°W-120°W, 20°S-40°S) and the Indian Ocean (50°E-100°E, 10°S-40°S) were selected using Pearson correlation coefficient (PCC > 0.5) that can represent the possible relationships between Iran’s winter precipitations with the oceanic sea surface temperature (SST) anomaly. The monthly gridded precipitation and SST data with a 2.5° × 2.5° resolution were evaluated from 1984 to 2019 to achieve this goal. The XWT results of precipitation and SST anomaly showed that the 8–16 months period is the most effective and predominant period between the South Pacific Ocean and 81% of all the precipitation zones. WTC results for the North Atlantic Ocean and 72% of all the precipitation zones showed periods of 4–8 (36%) and 16–32 (36%) months as the dominant duration. Despite the proximity of the Indian Ocean to the precipitation zones, there is no significant causal relationship between them, based on the XWT results. However, due to Madden–Julian oscillation (MJO), the 4–8 months period (45%) was seen between the Indian Ocean and some precipitation zones, based on WTC results.

Several synthetic and natural scaffolds have been developed for bone tissue engineering (BTE). This study was designed to fabricate and characterize a composite scaffold based on poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV)/polycaprolactone (PCL) polymers containing 5 % Hydroxyapatite (HA) nano-particles (HA5) for regeneration of bone critical size defect in a rat animal model. In the first step of this study, the PHBV/PCL (30 and 70 wt.%, respectively) with and without HA nanoparticle scaffolds were fabricated by Dual-Leaching Technique and then evaluated for FTIR spectroscopy, SEM, degradation rate, cell binding and proliferation. In the second step, the scaffolds were applied for cell differentiation and animal study. Human osteoblast-like Saos-2 cell line was seeded onto the scaffolds and Alkaline Phosphatase (ALP) activity was assayed on 7 days and 14 post-culture. The capacity of scaffolds to promote the bone regeneration genes was also investigated using quantitative RT-PCR. The critical size defects were made on the dorsal part of the rat’s calvarium and were filled with PCL70PHBV30 and PCL70PHBV30HA5 scaffolds and were then evaluated histologically and histomorphometrically. The higher mean percentage of new bone formation, bone cells and osteon, as well as lower fibrous connective tissue, was detected in the PCL70PHBV30HA5 group than that of the other groups. In conclusion, the HA nanoparticles at 5 % concentration have been well distributed in the PCL70PHBV30 scaffold that could accelerate bone regeneration.

Removal of lead from aqueous solutions was studied using nanocomposite absorbent of bentonite/-alumina. The novel absorbent was characterized using XRD, FT-IR and SEM-EDX. Absorption process optimization using response surface methodology (RSM) and experimental design was performed with central composite design technique. The effects of Pb(II) initial concentration, adsorbent dosage, and composite percentage on Pb(II) removal percentage and adsorption capacity were examined. The adsorption capacity of 166.559 mg/g and removal % of 82.9887 with desirability equal to 0.763 were obtained for optimal initial concentration of 200 mg•l-1, adsorbent dosage of 0.5 mg•l-1, and composite percentage of 7.08 % determined using RSM design. The equilibrium adsorption data were investigated by Langmuir, Freundlich and Dubinin-Radushkevich isotherm models. It was found that Freundlich isotherm model fits better compared with other models.

Owing to the high toxicity and large-scale use of pesticides, it is imperative to develop selective, sensitive, portable, and convenient sensors for rapid monitoring of pesticide. Therefore, the electrochemical detection platform offers a promising analytical approach since it is easy to operate, economical, efficient, and user-friendly. Meanwhile, with advances in functional nanomaterials and aptamer selection technologies, numerous sensitivity-enhancement techniques alongside a widespread range of smart nanomaterials have been merged to construct novel aptamer probes to use in the biosensing field. Hence, this study intends to highlight recent development and promising applications on the functional nanomaterials with aptamers for pesticides detection based on electrochemical strategies. We also reviewed the current novel aptamer-functionalized microdevices for the portability of pesticides sensors. Furthermore, the major challenges and future prospects in this field are also discussed to provide ideas for further research.

This study was carried out to determine whether the changes in dust concentration (DC) in Iran were attributed to changes in aridity index (AI) from 1990 to 2018. Long-term precipitation and potent...

Low thermal efficiency is one of the main problems in using solar collectors in different fields. In the present study, the effect of using phase change materials (PCM) inside the Flat plate collector (FPC) on the thermal performance and overall drying efficiency of FPC was investigated. Four PCM positions were considered inside of the collector, and the results compared with the collector without PCM. Experimental results implied that specific energy consumption for drying tomato slices is between 11.12 and 9.01 MJ/kg. The drying time of the slices using the collector with PCM at the end section was decreased about 21.87%. Based on the position of PCM, the thermal efficiency of FPC increased by about 5.02%-10.13%. The overall efficiency varied from 21.92% to 25.72% for different PCM positions. CFD simulation of the system was performed by Ansys 2015, and it showed that the thermal performance of the collector could be predicted with good accuracy (R2 > 0.9432). Moreover, the result of evolutionary polynomial regression models applied for each PCM position. It confirmed that outlet temperature and thermal efficiency of collector predicted with acceptable accuracy (R2 > 0.98). Due to the use of PCM at the end section of the collector, a homogeneous drying process, normal temperature, and short drying time resulted. The quality of tomato slices dried by the solar dryer was higher than other positions.

In existing physical layer security (PLS) and key generation protocols, major assumptions, including channel reciprocity, localization, and synchronization between the legitimate parties, are often considered. However, these assumptions are arguable in practice leading to major barriers in building systems based on PLS protocols. To overcome these barriers, we proposed, designed, and implemented a novel embedded architecture for distributed Internet-of-Things (IoT) networks that utilize a master–slave full-duplex communication to exchange a random secret key. In the proposed architecture, an IoT node generates a phase-modulated random key/data and transmits it to a master node in the presence of an eavesdropper, referred to as Eve. The master node, simultaneously, broadcasts a high-power signal using an omnidirectional antenna, which is received as a jammer signal or interference by Eve. This results in a high bit error rate (BER) making the data undetectable by Eve. The two legitimate nodes communicate in a full-duplex fashion and, consequently, subtract their transmitted signals from the received signal (self-interference cancellation). Our proposed protocol does not require any knowledge of the node locations. In particular, we show, using theoretical and measurement results, that our proposed approach provides significantly better security measures, in terms of the BER at Eve’s location, compared to a conventional method based on directional beamforming antennas. Also, it is proved that in our novel system, the possible eavesdropping region, BER < 10−1, is always smaller than the reliable communication region, BER < 10−3.

In this research, a number of paired three-dimensional Atmosphere-Ocean General Circulation Models (AOGCM) from CMIP (Climate Model Inter Comparison Project) 5 group with the base period of 1989–2005 have been evaluated and the output of these models was micro-scaled and calibrated by LARS-WG software. The appropriate model was selected to simulate temperature and rainfall data under the emission scenarios of RCP (Representative Concentration Pathway) 2.6, RCP4.5 and RCP8.5 for the future period of 2020–2050, and then to model the groundwater level of the region, GMS software for both stable and transient states for one water year was calibrated and then was validated by observation data. The results in the future periods showed an increase of 1–1.5 degrees in temperature and an increase in rainfall in the early months of the year to late spring season and a decrease in rainfall in autumn season. Generally, the RCP4.5 scenario showed slightly more annual rainfall increase over the next 30 years compared to the base period than the other two scenarios. The time series investigation of the average of groundwater level shows that the implementation of RCP 2.6, RCP 4.5 and RCP 8.5 scenarios respectively leads to an average monthly increase of 4.2, 4.3 and 4.6 cm of the groundwater level. HIGHLIGHTS Using the models and scenarios of the fifth IPCC report in Varamin and Tehran plains to study the trend of climate change.; Using a step-by-step approach to investigate the effect of climate change on groundwater level in the Varamin plain.; A view of the future of the Varamin plain aquifer under different climate change scenarios for groundwater resources management.

This composition presents a multi-phase-lags thermos-elasticity model for the thermos-elastic wave propagation reaction of a composite hollow circular cylinder with the interface layer LEMV/CFRP (L...

High pressure die casting (HPDC) Mg alloy has a hetero-structure in which the microstructures gradually coarsen from the casting surface to the interior, leading to the different elastic–plastic (E-P) transitional behaviors among the layers. In this paper, we quantitively determined the diverse E-P transitions among the HPDC layers and related them to the microstructural evolution. To investigate independently the E-P transitional behavior of the layer, the surface, middle, and central layers were deliberately sliced in sequence from the casting surface to the interior of the HPDC Mg-4Al-5.7RE (in wt.%) component. The onset and the end of E-P transition in each layer were quantitively determined by cyclic tensile test and Kocks-Mecking analysis, respectively. It was found that the plastic deformation for all layers occurred in the first unloading loop near zero strain, indicating the start of the E-P transition. With increasing strain, the E-P transition ended first in the middle layer at 0.0081 strain due to the lowest fraction of the second phases and ended last at the small-grained surface layer at 0.0090 strain. Excluding the twinning-dependent anelastic strain, the E-P transitions ended in advance at the strains of 0.0059 and 0.0062 in the middle and surface layer, respectively. A combination of cyclic tensile test and Kocks-Mecking analysis provided a method to quantitively determine the diverse E-P transitions among the HPDC layers resulted from the hetero-structure regarding grains, the second phases, and twins.

Renewable energy sources (RES) are an inevitable environmental option in near future. These sources compete with conventional power generation, where good wind and solar resources are available. Hy...

The ASTM D6424 standard is used for general aviation piston engine knock detection and is tested for unleaded fuel candidates. Issues are discussed regarding the identification of knocking cycles, filtering frequency bands, and the effects of down-sampling for this knock detection technique. The knock tests were performed on the Continental TSIO-520-VB engine at 12,000 ft for take-off and cruise conditions using three different fuels, the standard leaded 100LL avgas and two unleaded fuel candidates. The ASTM D6424 knock detection method has its own particular disadvantages, which are detailed and compared to other knock detection methods including the third derivative of pressure signal and discrete wavelet transform. Updates to the standard include a minimum sampling rate of 0.2 CAD. Additionally, the current standard does not contain recommendations for filtering the cylinder pressure which results in over detection of knocking cycles with the two new aviation fuel candidates tested. Recommendations are provided regarding the pressure signal processing prior to ASTM D6424 knock-characterization.

In this article, critical angular velocity, critical velocity of fluid flow and vibration control analysis of a rotating multi-hybrid nanocomposite reinforced (MHCR) cylindrical microshell covered with a piezoelectric layer as sensor and actuator (PLSA) are presented. The current non-classical model is capable of capturing the size dependency in the microshells using only one material length scale parameter; moreover, the mathematical formulation of microshells based on the classical model can be recovered from the present model by neglecting the material length scale parameter. This structure is under conveying viscous fluid, and the related force is calculated by the modified formulation of Navier–Stokes. In addition, the current structure rotates around its axial direction. The Coriolis and centrifugal effects due to the rotation are considered. For semi-numerical method, the strains and stresses can be determined through via the first-order shear deformable theory (FSDT). For accessing to various mass densities, thermal expansion as well as Poisson ratio, the rule of mixture is applied, although a modified Halpin–Tsai theory is used for obtaining the module of elasticity. The external voltage is applied to the sensor layer, while a Proportional-Derivative (PD) controller has been utilized for controlling output of sensors. The boundary conditions are derived through governing equations of the MHCR cylindrical microshell using energy method known as Hamilton’s principle and finally are solved using generalized differential quadrature method (GDQM). The outcomes show that the angular velocity, velocity of fluid flow, external force, PD controller, external voltage and MHC’s weight fraction have a considerable impact on the amplitude, and vibration behavior of a spinning MHCR cylindrical shell conveying fluid flow.

While multi-joint continuum robots are highly dexterous and flexible, designing an optimal robot can be challenging due to its kinematics involving curvatures. Hence, the current work presents a computational method developed to find optimal designs of continuum robots, given reachability constraints. First, we leverage both forward and inverse kinematic computations to perform reachability analysis in an efficient yet accurate manner. While implementing inverse kinematics, we also integrate torque minimization at joints such that robot configurations with the minimum actuator torque required to reach a given workspace could be found. Lastly, we apply an estimation of distribution algorithm (EDA) to find optimal robot dimensions while considering reachability, where the objective function could be the total length of the robot or the actuator torque required to operate the robot. Through three application problems, we show that the EDA is superior to a genetic algorithm (GA) in finding better solutions within a given number of iterations, as the objective values of the best solutions found by the EDA are 4–15% lower than those found by the GA.

Disaster management, search and rescue missions, and health monitoring are examples of critical applications that require object localization with high precision and sometimes in a timely manner. In the absence of the global positioning system (GPS), the radio received signal strength index (RSSI) can be used for localization purposes due to its simplicity and cost-effectiveness. However, due to the low accuracy of RSSI, unmanned aerial vehicles (UAVs) or drones may be used as an efficient solution for improved localization accuracy due to their agility and higher probability of line-of-sight (LoS). Hence, in this context, we propose a novel framework based on reinforcement learning (RL) to enable a UAV (agent) to autonomously find its trajectory that results in improving the localization accuracy of multiple objects in shortest time and path length, fewer signal-strength measurements (waypoints), and/or lower UAV energy consumption. In particular, we first control the agent through initial scan trajectory on the whole region to 1) know the number of nodes and estimate their initial locations, and 2) train the agent online during operation. Then, the agent forms its trajectory by using RL to choose the next waypoints in order to minimize the average location errors of all objects. Our framework includes detailed UAV to ground channel characteristics with an empirical path loss and log-normal shadowing model, and also with an elaborate energy consumption model. We investigate and compare the localization precision of our approach with existing methods from the literature by varying the UAV's trajectory length, energy, number of waypoints, and time. Furthermore, we study the impact of the UAV's velocity, altitude, hovering time, communication range, number of maximum RSSI measurements, and number of objects. The results show the superiority of our method over the state-of-art and demonstrates its fast reduction of the localization error.

The configuration of a crack with respect to the multi-material fiber reinforced composite joint determines the order of singularity of the stress solutions reproduced around the crack-tip. These solutions for different configurations of crack are obtained for carbon nano-tube (CNT) reinforced CFRP composite using an innovative finite element asymptotic analysis. Micro-cracks aligned with CNTs covered by interphase material in the reinforced polymer matrix (PMNC) may impinge upon the PMNC-Carbon fiber interface; and this investigation demonstrates that the CNT reinforcement increases the power of the stress field at the area surrounded by the crack-tip. Various CNT alignments have been considered with due concern on symmetric and anti-symmetric deviation of nanotubes on either side of the crack. The effect of notches is considered as well. Finally, the consistent singular mode shapes proposed are applies to efficiently increase the accuracy of the fracture analysis solutions for this category of orthotropic composite materials using a novel extended finite element (XFEM) approach named Direct-XFEM. Direct-XFEM reproduces the stress intensity factors (SIFs) directly, at a few additional degrees of freedom included in the local crack-tip area. The results indicate a notable improvement in contrast with the ordinary XFEM in the absence of the singular shape functions.

Drug resistance is a great challenge in cancer therapy using chemotherapeutic agents. Administration of these drugs with siRNA is an efficacious strategy in this battle. Here, the present study tried to incorporate siRNA and paclitaxel (PTX) simultaneously into a novel nanocarrier. The selectivity of carrier to target cancer tissues was optimized through conjugation of folic acid (FA) and glucose (Glu) onto its surface. The structure of nanocarrier was formed from ternary magnetic copolymers based on FeCo-polyethyleneimine (FeCo-PEI) nanoparticles and polylactic acid-polyethylene glycol (PLA-PEG) gene delivery system. Biocompatibility of FeCo-PEI-PLA-PEG-FA(NPsA), FeCo-PEI-PLA-PEG-Glu (NPsB) and FeCo-PEI-PLA-PEG-FA/Glu (NPsAB) nanoparticles and also influence of PTX-loaded nanoparticles on in vitro cytotoxicity were examined using MTT assay. Besides, siRNA-FAM internalization was investigated by fluorescence microscopy. The results showed the blank nanoparticles were significantly less cytotoxic at various concentrations. Meanwhile, siRNA-FAM/PTX encapsulated nanoparticles exhibited significant anticancer activity against MCF-7 and BT-474 cell lines. NPsAB/siRNA/PTX nanoparticles showed greater effects on MCF-7 and BT-474 cells viability than NPsA/siRNA/PTX and NPsB/siRNA/PTX. Also, they induced significantly higher anticancer effects on cancer cells compared with NPsA/siRNA/PTX and NPsB/siRNA/PTX due to their multi-targeted properties using FA and Glu. We concluded that NPsAB nanoparticles have a great potential for co-delivery of both drugs and genes for use in gene therapy and chemotherapy., Graphical abstract Image 1, Highlights • A series of novel nanoparticles which composed of either glucose and/or folic acid conjugated FeCo@SiO2-SS-PEI-PLA-PEG copolymers were successfully synthesized and loaded with siRNA and PTX simultaneously. • The prepared nanoparticles had diameter in range of 100–150 nm, and released the drugs in sustainable manner. • The simultaneous PTX and siRNA loaded nanocarrier showed significant toxicity on MCF-7 cells and also their significant transfection efficiency in these cells was demonstrated through increased uptake of siRNA-FAM via fluorescence microscopy imaging.

Concerns about environmental degradation and fossil fuel depletion have led to the advent of energy-aware manufacturing and material handling processes in factories and warehouses. However, as the transition to eco-friendly material handling by electric material handling vehicles (EMV) is progressing, the use of electric forklifts (EFs) remains a challenge, as these EMVs are recognized only as energy consumers. In this paper, we develop an integrated dynamic algorithm for solving the EF routing problem with battery charging constraints in which EFs’ picking or put-away routes, EFs’ battery charging schedules, and the number of EFs operated are simultaneously determined while considering electricity consumption in a warehouse. Time series of electricity-usage penalty estimated by predicted energy consumption in a warehouse facility and equipment level play key roles in establishing EF battery charging schedules. Dynamic models for the arrival processes in material handling and EF battery charging jobs in multiple EF queues are developed and implemented as core engines in the proposed dynamic control algorithm. Operational performance and energy performance of the proposed dynamic algorithm are examined using real energy and operational parameters of the Toyota 9BRU23/16.5 reach truck and compared to those of the metaheuristic approach, called adaptive large neighborhood search. Experimental results of large-size instances with uniformly distributed job locations show that an average 5.6% better performance is achieved by the proposed dynamic algorithm. An additional experiment with the proposed approach and clustered job locations results in 8.9% lower energy-related costs and 1.2% shorter EF travel distances, demonstrating the competitiveness of the proposed energy-aware EF operations strategy for warehouse administration.

The purpose of present investigation is to study propagation of flexural wave in porous metal foam beams resting on Winkler–Pasternak foundation based upon refined higher-order shear deformable bea...

In this paper, the linear eigen buckling and vibration analysis of various composite laminated structures such as flat plates, curved panels and cylindrical shell are investigated individually. The method of analysis is the semi-analytical finite strip approach which is based on the full-energy methods. The first-order Lagrange and the third-order Hermitian shape functions are utilized for the transverse and longitudinal directions, respectively, to estimate in-plane and out-of-plane displacements. By using layer-wise theory, thick structures can be modeled with good agreement with finite element methods as presented in this work. In addition, multiple nodes are considered along the thickness of structure, so displacement can be estimated more precisely in comparison with classic and first-order models as compared with other references.

While steer-by-wire (SBW) systems benefit from improved performance and comfort, they require a large number of sensors impacting whole system reliability. In order to address this challenge fault tolerance property against sensor faults has to be improved. Application of redundancy for the sensors is the best solution proposed so far. This paper proposes a novel solution of analytical redundancy based on various position estimation methods for both electrical motor and steering wheel position sensors. Three different estimation techniques including extended programmable cascaded low-pass filter (EPCLPF), stator flux linkage estimator using stator currents, as well as stator flux linkage estimator using stator voltages are proposed for this purpose. The faulty sensors are recognized using a voting technique in which a comparison between the sensors’ outputs with the estimated values is made. In this way, the SBW system reliability is highly improved with no additional cost and space. Simulation and experimental results are presented to confirm the presented fault tolerant SBW system capabilities.

Finding the most suitable co-author is one of the most important ways to conduct effective research in scientific fields. Data science has contributed to achieving this possibility significantly. The present study aims at designing a mathematical model of co-author recommender system in bioinformatics using graph mining techniques and big data applications. The present study employed an applied-developmental research method and a mixed-methods research design. The research population consisted of all scientific products in bioinformatics in the PubMed database. To achieve the research objectives, the most appropriate effective features in choosing a co-author were selected, prioritized, and weighted by experts. Then, they were weighted using graph mining techniques and big data applications. Finally, the mathematical co-author recommender system model in bioinformatics was presented. Data analysis instruments included Expert Choice, Excel, Spark, Scala and Python programming languages in a big data server. The research was conducted in four steps: (1) identifying and prioritizing the criteria effective in choosing a co-author using AHP; (2) determining the correlation degree of articles based on the criteria obtained from step 1 using algorithms and big data applications; (3) developing a mathematical co-author recommender system model; and (4) evaluating the developed mathematical model. Findings showed that the journal titles and citations criteria have the highest weight while the abstract has the lowest weight in the mathematical co-author recommender system model. The accuracy of the proposed model was 72.26. It was concluded that using content-based features and expert opinions have high potentials in recommending the most appropriate co-authors. It is expected that the proposed co-author recommender system model can provide appropriate recommendations for choosing co-authors on various fields in different contexts of scientific information. The most important innovation of this model is the use of a combination of expert opinions and systemic weights, which can accelerate the finding of co-authors and consequently saving time and achieving a greater quality of scientific products.