Iran University of Science and Technology

A magnetic xanthan hydrogel/silk fibroin nanobiocomposite (XG hydrogel/SF/Fe3O4) was designed, fabricated, and characterized using analyzing methods such as FT-IR, EDX, FE-SEM, XRD, TGA, and VSM to evaluate the exact structure of product nanobiocomposite. The FE-SEM images reveal the presence of spherical shapes exhibiting a narrow size range and homogeneous distribution, measuring between 30 and 35 nm in diameter. The VSM analysis demonstrates the superparamagnetic properties of the XG hydrogel/SF/Fe3O4 nanobiocomposite, exhibiting a magnetic saturation of 54 emu/g at room temperature. The biological response of the nanobiocomposite scaffolds was assessed through cell viability and red blood cell hemolytic assays. MCF10A cells were exposed to a concentration of 1.75 mg/mL of the nanobiocomposite, and after 2 and 3 days, the cell viability was found to be 96.95 % and 97.02 %, respectively. The hemolytic effect was nearly 0 % even at higher concentrations (2 mg/mL). Furthermore, the magnetic nanobiocomposite showed excellent potential for hyperthermia applications, with a maximum specific absorption rate of 7 W/g for 1 mg/mL of the sample under a magnetic field in different frequencies (100, 200, 300, and 400 MHz) and 5 to 20 min time intervals.

Nowadays, orthopedic fixation devices are used in treating spine diseases, but osteoporosis is the most common challenge for lumbar interbody fusion with pedicle screws. In the elderly population of the world, osteoporosis has become a common disease, which is a concern for spine surgeons because most of the patients who need lumbar interbody fusion are older people with osteoporosis. In this study, a finite element spine model of a healthy 15-year-old teenager was built. The finite element model of the lumbar spine from the L2 to L4 vertebra was acquired from the computed tomography scan data. The 3D spine model entailed three lumbar vertebrae and two intervertebral discs and the implant system comprises 4 pedicle screws with the precise geometry of threads and two types of titanium and polyetheretherketone (PEEK) connecting rod. The loading and boundary conditions were exerted on the L2-L4 lumbar model. Considering the applied loads and bending moment on the model, stress distribution was appraised on intervertebral discs and the whole model with implant systems for titanium and PEEK rods fixation systems. To repute degeneracy, bones were categorized into four groups, i.e., weak bone, normal bone, strong bone, and very strong bone. The developed FE model was subjected to various axial compressive loads (270 and 510 N), and a pure moment of 10 Nm was applied for flexion, extension, lateral bending, and twist movements at the upside surface of the L2 vertebra, whereas the lower surface of the L4 vertebra settled fixed. 'Abaqus CAE 6.14-1' software was utilized to simulate the model with different fixed systems. A comparative study between different fixation systems showed that stress distribution values with the PEEK-based fixation system decreased over time with increasing osteoporosis. Likewise, lower equivalent stress values were recorded with the PEEK-based fixation system, especially in the whole model for cases with poor bone quality. In addition, both spine implant systems authorize to reduce the throughout loading stress in the entire spine models. It was derived that the PEEK-based spinal implant system significantly reduces the load on the whole model and also appears as a better option in reducing stress and load sharing for cases with poor bone quality compared to the titanium spinal implant system.

This paper adopts a highly effective numerical approach for approximating non-linear stochastic Volterra integral equations (NLSVIEs) based on the operational matrices of the Walsh function and the collocation method. The method transforms the integral equation into a system of algebraic equations, which allows for the derivation of an approximate solution. Error analysis is performed, confirming the effectiveness of the proposed method, which results in a linear order of convergence. Numerical examples are provided to illustrate the precision and effectiveness of the proposed method.

This research delves into investigating ion transport behavior within nanochannels, enhanced through modification with a negatively charged polyelectrolyte layer (PEL), aimed at achieving superior control. The study examines two types of electric fields� direct current and alternating current with square, sinusoidal, triangular, and sawtooth waveforms�to understand their impact on ion transport. Furthermore, the study compares symmetric (cylin-drical) and asymmetric (conical) nanochannel geometries to assess the influence of overlapping electrical double layers (EDLs) in generating specific electrokinetic behaviors such as ionic current rectification (ICR) and ion selectivity. The research employs the finite element method to solve the coupled Poisson−Nernst−Planck and Navier− Stokes equations under unsteady-state conditions. By considering factors such as electrolyte concentration, soft layer charge density, and electric field type, the study evaluates ion transport performance in charged nanochannels, investigating effects on concentration polarization, electroosmotic flow (EOF), ion current, rectification, and ion selectivity. Notably, the study accounts for ion partitioning between the PEL and electrolyte to simulate real conditions. Findings reveal that conical nanochannels, due to improved EDL overlap, significantly enhance ion transport and related characteristics compared to cylindrical ones. For instance, under η ε = η D = 0.8, η μ = 2, C 0 = 20 mM, and N PEL /N A = 80 mol m −3 conditions, the average EOF for conical and cylindrical geometries is 0.1 and 0.008 m/s, respectively. Additionally, the study explores ion selectivity and rectification based on the electric field type, unveiling the potential of nanochannels as ion gates or diodes. In cylindrical nanochannels, the ICR remains at unity, with lower ion selectivity across waveforms compared to conical channels. Furthermore, rectification and ion selectivity trends are identified as R f,square > R f,DC > R f,triangular > R f,sinusoidal > R f,sawtooth and S sawtooth > S sinusoidal > S triangular > S DC > S square for conical nanochannels. Our study of ion transport control in nanochannels, guided by tailored electric fields and unique geometries, offers versatile applications in the field of Analytical Chemistry. This includes enhanced sample separation, controlled drug delivery, optimized pharmaceutical analysis, and the development of advanced biosensing technologies for precise chemical analysis and detection. These applications highlight the diverse analytical contributions of our methodology, providing innovative solutions to challenges in chemical analysis and biosensing.

In this study, an adaptive fuzzy extended state observer (AFESO) for single-input–single-output nonlinear affine systems in the presence of external disturbances and output constraints is proposed. In this regard, an extended state observer (ESO) was employed to estimate the unmeasured states and external disturbances simultaneously. To improve the estimation accuracy, the observer gains were adjusted using an adaptation law. To obtain a more comprehensive mathematical analysis and an accurate model for the ESO and to increase the degree of freedom, a Takagi–Sugeno fuzzy system was employed. The proposed AFESO relaxes the limitations of the ESO and improves the system performance as compared with the classical methods in the presence of time-varying disturbances. Next, a command-filtered backstepping controller is designed based on the barrier Lyapunov function method, which guarantees fast convergence of the tracking error as well as satisfying the output constraints of the system. The stability analysis showed that both the estimation error of the AFESO and the tracking error of the controller are bounded, and the tracking error converges to a small neighborhood of the origin. A simulating example of a flexible-joint manipulator shows the effectiveness of the proposed method as compared with the recently proposed method in the literature.

Inattention of economic policymakers to default risk and making inappropriate decisions related to this risk in the banking system and financial institutions can have many economic, political and social consequences. In this research, it has been tried to calculate the default risk of companies listed in the capital market of Iran. To achieve this goal, two structural models of Merton and Geske, two machine learning models of Random Forest and Gradient Boosted Decision Tree, as well as financial information of companies listed in the Iranian capital market during the years 2016 to 2021 have been used. Another goal of this research is to measure the predictive power of the four models presented in the calculation of default risk. The results obtained from the calculation of the default rate of the investigated companies show that 50 companies listed in the Iranian capital market (46 different companies) have defaulted during the 5-year research period and are subject to the Bankruptcy Article of the Iranian Trade Law. Also, the results obtained from the ROC curves for the predictive power of the presented models show that the structural models of Merton and Geske have almost equal power, but the predictive power of the Random Forest model is a little more than the Gradient Boosted Decision Tree model.

Recently, microservices have become a commonly-used architectural pattern for building cloud-native applications. Cloud computing provides flexibility for service providers, allowing them to remove or add resources depending on the workload of their web applications. If the resources allocated to the service are not aligned with its requirements, instances of failure or delayed response will increase, resulting in customer dissatisfaction. This problem has become a significant challenge in microservices-based applications, because thousands of microservices in the system may have complex interactions. Auto-scaling is a feature of cloud computing that enables resource scalability on demand, thus allowing service providers to deliver resources to their applications without human intervention under a dynamic workload to minimize resource cost and latency while maintaining the quality of service requirements. In this research, we aimed to establish a computational model for analyzing the workload of all microservices. To this end, the overall workload entering the system was considered, and the relationships and function calls between microservices were taken into account, because in a large-scale application with thousands of microservices, accurately monitoring all microservices and gathering precise performance metrics are usually difficult. Then, we developed a multi-criteria decision-making method to select the candidate microservices for scaling. We have tested the proposed approach with three datasets. The results of the conducted experiments show that the detection of input load toward microservices is performed with an average accuracy of about 99% which is a notable result. Furthermore, the proposed approach has demonstrated a substantial enhancement in resource utilization, achieving an average improvement of 40.74%, 20.28%, and 28.85% across three distinct datasets in comparison to existing methods. This is achieved by a notable reduction in the number of scaling operations, reducing the count by 54.40%, 55.52%, and 69.82%, respectively. Consequently, this optimization translates into a decrease in required resources, leading to cost reductions of 1.64%, 1.89%, and 1.67% respectively.

In this research work, a magnetic nanobiocomposite is designed and presented based on the extraction of flaxseed mucilage hydrogel, silk fibroin (SF), and Fe3O4 magnetic nanoparticles (Fe3O4 MNPs). The physiochemical features of magnetic flaxseed mucilage hydrogel/SF nanobiocomposite are evaluated by FT-IR, EDX, FE-SEM, TEM, XRD, VSM, and TG technical analyses. In addition to chemical characterization, given its natural-based composition, the in-vitro cytotoxicity and hemolysis assays are studied and the results are considerable. Following the use of highest concentration of magnetic flaxseed mucilage hydrogel/SF nanobiocomposite (1.75 mg/mL) and the cell viability percentage of two different cell lines including normal HEK293T cells (95.73%, 96.19%) and breast cancer BT549 cells (87.32%, 86.9%) in 2 and 3 days, it can be inferred that this magnetic nanobiocomposite is biocompatible with HEK293T cells and can inhibit the growth of BT549 cell lines. Besides, observing less than 5% of hemolytic effect can confirm its hemocompatibility. Furthermore, the high specific absorption rate value (107.8 W/g) at 200 kHz is generated by a determined concentration of this nanobiocomposite (1 mg/mL). According to these biological assays, this magnetic responsive cytocompatible composite can be contemplated as a high-potent substrate for further biomedical applications like magnetic hyperthermia treatment and tissue engineering.

Among all technologies applied in three-dimensional printing (3DP), fused deposition modeling (FDM) is the most developing one because it is capable of producing parts with geometrically complex figures. Despite its wide applications, there are some drawbacks to its extension, for instance, weak mechanical characteristics and low dimensional accuracy. In this paper, the influence of four FDM process parameters (layer height, printing speed, infill density, and the number of top and bottom layers) on four criteria (impact strength, dimensional accuracy, consumed raw material, and production time) of polylactic acid (PLA) parts is studied. Unlike previous research, this research not only optimizes the properties of produced parts but also minimizes production costs. First, each criterion is analyzed singly; then, in an investigation, all criteria are combined and optimized simultaneously. In other words, a comprehensive decision is made considering both products' qualities and the production costs. The applied methodology for multi-criterion decision-making in this research is also usable in other fields of industry. With the help of this methodology, the best selection of process parameters' levels is attainable. According to the results, layer height = 0.3 mm, number of top and bottom layers = 2, infill density = 60% and print speed = 45.28 mm/s are the best choice while considering all four criteria. Layer height is found the most effective parameter. An increase in layer height leads to a stronger part with a shorter production time but a heavier one with less dimensional accuracy.

Porous samples have been of great interest in orthopedic implants owing to their significance to facilitate the osteogenesis process and reduction of sheath stresses. The goal of this research is to synthesize Ti6Al4V-Cenosphere porous composite samples using the spark plasma sintering (SPS) method as well as to investigate their mechanical properties and biocompatibility. Accordingly, the synthesis of the samples was performed under relative densification conditions for 5 min at 850 °C at an applied pressure of 5 MPa and a heating rate of 100 °C/min. The phases formed, the morphology of powders, porosity, distribution of pores, fractography, the density of samples, and mechanical properties of samples, were investigated by Archimedes’ method, XRD, scanning electron microscopy (SEM), hardness measurement, and bending tests, respectively. The results revealed that by an increase in the volume percentage of the cenosphere (Cen.) space holder, the density of the samples decreased whereas their open and closed porosity content increased. The morphology of the pores formed in the structure was spherical with a uniform distribution. Moreover, the modulus of elasticity of the samples decreased significantly, and the properties were close to those of the bone in the samples containing a cenosphere content of > 30 vol.%.

Integration of planar circuits been considered a credible technique for low-cost mass production of microwave and millimeter-wave circuits and systems. For the first time, in this research a dual-post band-pass filter is designed and simulated in a three-layer substrate integrated gap groove waveguide (SIGGW) for 5G millimeter-wave frequency band applications. The filter includes 12 posts (6×2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$6 \times 2$$\end{document}). Also, the structure facilitates to use resonant posts and so we can design the posts to add a transmission zero in lower rejection band. The design theory algorithm and its limitations are investigated based on the circuit model of filter. The results shows that FBW of 5% and a lower band transmission zero for the proposed 12 posts filter. Also, the results are verified by simulation using CST. According to the results, the proposed filter is a good option for Ka-band applications and can be used as the building block for suppressing the LO leakage that is commonly used for up-converting the 5G signal to Ka band.

Metal–organic frameworks (MOFs) and MXenes have demonstrated immense potential for biomedical applications, offering a plethora of advantages. MXenes, in particular, exhibit robust mechanical strength, hydrophilicity, large surface areas, significant light absorption potential, and tunable surface terminations, among other remarkable characteristics. Meanwhile, MOFs possess high porosity and large surface area, making them ideal for protecting active biomolecules and serving as carriers for drug delivery, hence their extensive study in the field of biomedicine. However, akin to other (nano)materials, concerns regarding their environmental implications persist. The number of studies investigating the toxicity and biocompatibility of MXenes and MOFs is growing, albeit further systematic research is needed to thoroughly understand their biosafety issues and biological effects prior to clinical trials. The synthesis of MXenes often involves the use of strong acids and high temperatures, which, if not properly managed, can have adverse effects on the environment. Efforts should be made to minimize the release of harmful byproducts and ensure proper waste management during the production process. In addition, it is crucial to assess the potential release of MXenes into the environment during their use in biomedical applications. For the biomedical applications of MOFs, several challenges exist. These include high fabrication costs, poor selectivity, low capacity, the quest for stable and water-resistant MOFs, as well as difficulties in recycling/regeneration and maintaining chemical/thermal/mechanical stability. Thus, careful consideration of the biosafety issues associated with their fabrication and utilization is vital. In addition to the synthesis and manufacturing processes, the ultimate utilization and fate of MOFs and MXenes in biomedical applications must be taken into account. While numerous reviews have been published regarding the biomedical applications of MOFs and MXenes, this perspective aims to shed light on the key environmental implications and biosafety issues, urging researchers to conduct further research in this field. Thus, the crucial aspects of the environmental implications and biosafety of MOFs and MXenes in biomedicine are thoroughly discussed, focusing on the main challenges and outlining future directions.

Chronic kidney disease (CKD) is a major global health concern with increasing prevalence and associated complications. Metabolic syndrome (MetS) has been linked to CKD, but the evidence remains inconsistent. We conducted a systematic review and meta-analysis to investigate the association between MetS and kidney dysfunction. We conducted a comprehensive search of databases until December 2022 for cohort studies assessing the association between MetS and incident kidney dysfunction. Meta-analysis was performed using fixed and random effects models. Subgroup analyses were conducted to explore heterogeneity. Publication bias was assessed using Egger’s and Begg’s tests. A total of 24 eligible studies, involving 6,573,911 participants, were included in this meta-analysis. MetS was significantly associated with an increased risk of developing CKD (OR, 1.42; 95% CI, 1.28, 1.57), albuminuria or proteinuria (OR, 1.43; 95% CI, 1.10, 1.86), and rapid decline in kidney function (OR, 1.25; 95% CI, 1.07, 1.47). Subgroup analyses showed a stronger association as the number of MetS components increased. However, gender-specific subgroups demonstrated varying associations. Metabolic syndrome is a significant risk factor for kidney dysfunction, requiring close renal monitoring. Lifestyle changes and targeted interventions may help reduce CKD burden. Further research is needed to understand the connection fully and assess intervention efficacy.

The oxygen content of the copper powders significantly affects the properties of copper, particularly its morphology and electric conductivity. Moreover, the oxygen content depends on the chosen synthesis method and variation of the process parameters. In this study, a sustainable oxygen-free copper powder electrolysis method was exploited to synthesize the copper powder by using wastes as initial materials. The anode and cathode copper scrap plates were used as raw materials. To accomplish this, the effect of the variation of the process parameters including current density, concentration of sulfuric acid, and copper ions was studied. Heat treatment was carried out at 600 °C for 90 min under H2 atmosphere for deoxidization. Additionally, the effect of the mechanical reduction through carbon bed on deoxidization (carbothermic reduction) was evaluated prior to the heat treatment under a hydrogen atmosphere. The oxygen content of achieved powders was measured by using the ONH analysis method based on the ASTM E 2575 standard method. The minimum measured oxygen content was found to be 179 ppm in the optimized condition of 0.3 A.cm−2, 140 g.l−1 of concentration of acid sulfuric, and 5 g.l−1 concentration of copper ions. This low oxygen content is attributed to the spherical and flake-shaped morphology of obtained copper powders. The size, morphology, and crystallization of the obtained copper powders were evaluated by scanning electron microscopy (SEM) and EDS. Results revealed that with the variation of the process parameters, the size of the powders was changed between 4.03 and 11.18 µm.

In view of the great importance of dynamical behavior prediction of nanostructures in contact with fluid and their vast range of applications in biomedical engineering, aerospace, etc., in this research, the free vibration of a Nanoscale Euler-Bernoulli rotating beam coupled with incompressible viscous fluid is studied. Small-scale effects are applied by using nonlocal elasticity theory. Using the Navier-Stokes relation, the interaction forces between the fluid and nanobeam are obtained. Governing differential equations have been solved by Galerkin method and the system vibrations frequency response has been obtained for clamped-free boundary condition. Based on the results of this research, nonlocal elasticity has a different effect on different vibration modes. The frequency of the nanobeam coupled with the fluid quickly increases when applying this theory, and the presence of fluid reduces the natural frequencies.