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Background: Supply chain management (SCM) plays a fundamental role in the progress and success of organizations and has continuously evolved to better adapt to today’s complex business environments. Consequently, the issue of supplier evaluation and selection (SES), which is one of the most critical decisions in SCM, has gained special significance and has been examined from various perspectives. The concept of green and resilient (gresilient) SCM has emerged in response to recent concerns about environmentally friendly production and operations, as well as organizations’ ability to cope with crises and disasters. In the rapidly growing construction industry, applying gresilient principles can ensure green operations and help overcome future challenges. Methods: This study focuses on gresilient SES in a real-world construction case study, proposing a streamlined FUCOM (S-FUCOM) approach. The proposed method streamlines traditional FUCOM processes to solve decision-making problems in deterministic and uncertain environments. Several numerical examples are provided to illustrate its applicability. Results: the case study results identify air emissions, environmental management systems, and restorative capacity as the most critical gresilient SES criteria. Conclusions: The third supplier emerged as the top performer based on decision-making indicators. Finally, a sensitivity analysis was conducted across 20 scenarios, demonstrating that S-FUCOM is robust and provides stable results.

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We reviewed the reported imaging findings of myocarditis in the literature following COVID-19 vaccination on cardiac imaging by a literature search in online databases, including Scopus, Medline (PubMed), Web of Science, Embase (Elsevier), and Google Scholar. In total, 532 cases of myocarditis after COVID-19 vaccination were reported (462, 86.8% men and 70, 13.2% women, age range 12 to 80) with the following distribution: Pfizer-BioNTech: 367 (69%), Moderna: 137 (25.8%), AstraZeneca: 12 (2.3%), Janssen/Johnson & Johnson: 6 (1.1%), COVAXIN: 1 (0.1%), and unknown mRNA vaccine: 9 (1.7%). The distribution of patients receiving vaccine dosage was investigated. On cardiac MR Imaging, late intravenous gadolinium enhancement (LGE) was observed mainly in the epicardial/subepicardial segments (90.8%, 318 of 350 enhancing segments), with the dominance of inferolateral segment and inferior walls. Pericardial effusion was reported in 13.1% of cases. The vast majority of patients (94%, 500 of 532) were discharged from the hospital except for 4 (0.7%) cases. Post-COVID-19 myocarditis was most commonly reported in symptomatic men after the second or third dose, with CMRI findings including LGE in 90.8% of inferior and inferolateral epicardial/subepicardial segments. Most cases were self-limited.

The transfer matrix approach is used to study the optical characteristics of thermal radiation in a one-dimensional photonic crystal (1DPC) with metamaterial. In this method, every layer within the multilayer structure is associated with its specific transfer matrix. Subsequently, it links the incident beam to the next layer from the previous layer. The proposed structure is composed of three types of materials, namely InSb, ZrO2, and Teflon, and one type of epsilon-negative (ENG) metamaterial and is organized in accordance with the laws of sequencing. The semiconductor InSb has the capability to adjust bandgaps by utilizing its thermally responsive permittivity, allowing for tunability with temperature changes, while the metamaterial modifies the bandgaps according to its negative permittivity. Using quasi-periodic shows that, in contrast to employing absolute periodic arrangements, it produces more diverse results in modifying the structure’s band-gaps. Using a new sequence arrangement mixed-quasi-periodic (MQP) structure, which is a combination of two quasi periodic structures, provides more freedom of action for modifying the properties of the medium than periodic arrangements do. The ability to control thermal radiation is crucial in a range of optical applications since it is frequently unpolarized and incoherent in both space and time. These configurations allow for the suppression and emission of thermal radiation in a certain frequency range due to their fundamental nature as photonic band-gaps (PBGs). So, we are able to control the thermal radiation by changing the structure arrangement. Here, the We use an indirect method based on the second Kirchoff law for thermal radiation to investigate the emittance of black bodies based on a well-known transfer matrix technique. We can measure the transmission and reflection coefficients with associated transmittance and reflectance, T and R, respectively. Here, the effects of several parameters, including the input beam’s angle, polarization, and period on tailoring the thermal radiation spectrum of the proposed structure, are studied. The results show that in some frequency bands, thermal radiation exceeded the black body limit. There were also good results in terms of complete stop bands for both TE and TM polarization at different incident angles and frequencies. This study produces encouraging results for the creation of Terahertz (THz) filters and selective thermal emitters. The tunability of our media is a crucial factor that influences the efficiency and function of our desired photonic outcome. Therefore, exploiting MQP sequences or arrangements is a promising strategy, as it allows us to rearrange our media more flexibly than quasi-periodic sequences and thus achieve our optimal result.

With a rising emphasis on public safety and quality of life, there is an urgent need to ensure optimal air quality, both indoors and outdoors. Detecting toxic gaseous compounds plays a pivotal role in shaping our sustainable future. This review aims to elucidate the advancements in smart wearable (nano)sensors for monitoring harmful gaseous pollutants, such as ammonia (NH3), nitric oxide (NO), nitrous oxide (N2O), nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), hydrogen sulfide (H2S), sulfur dioxide (SO2), ozone (O3), hydrocarbons (CxHy), and hydrogen fluoride (HF). Differentiating this review from its predecessors, we shed light on the challenges faced in enhancing sensor performance and offer a deep dive into the evolution of sensing materials, wearable substrates, electrodes, and types of sensors. Noteworthy materials for robust detection systems encompass 2D nanostructures, carbon nanomaterials, conducting polymers, nanohybrids, and metal oxide semiconductors. A dedicated section dissects the significance of circuit integration, miniaturization, real-time sensing, repeatability, reusability, power efficiency, gas-sensitive material deposition, selectivity, sensitivity, stability, and response/recovery time, pinpointing gaps in the current knowledge and offering avenues for further research. To conclude, we provide insights and suggestions for the prospective trajectory of smart wearable nanosensors in addressing the extant challenges.

The production of photovoltaic modules is increasing to reduce greenhouse gas emissions. However, this results in a significant amount of waste at the end of their lifespan. Therefore, recycling these solar panels is important for environmental and economic reasons. However, collecting and separating crystalline silicon, cadmium telluride, and copper–indium–gallium–selenide panels can be challenging, especially in underdeveloped countries. The innovation in this work is the development of a process to recycle all solar panel waste. The dissolution of all metals through the leaching process is studied as the main step of the flowchart. In the first step of leaching, 98% of silver can be recovered by 0.5 M nitric acid. Then, the second and third step involves the use of glycine for base metal dissolution, followed by the leaching of valuable metals with hydrochloric acid. The effect of parameters such as the initial pH, acid concentration, solid/liquid ratio, and hydrogen peroxide concentration is studied. The results show that up to 100% of Cu, Pb, Sn, Zn, Cd, In, Ga, and Se can be recovered under optimal conditions. The optimal conditions for the dissolution of Cu, Zn, and Cd were a glycine concentration of 0.5 M, a temperature of 25 °C, a solid/liquid ratio of 10 gr/L, and 1% of hydrogen peroxide. The optimized glycine concentration for the leaching of lead and tin was 1.5 M. Indium and gallium were recovered at 100% by the use of 5 M hydrochloric acid, S/L ratio = 10 gr/L, and T = 45 °C. Separation of selenium and tellurium occurred using 0.5 M HCl at a temperature of 60 °C. Additionally, for the first time, a general outlook for the recycling of various end-of-life solar panels is suggested.

Liver cancer is a significant contributor to the cancer burden, and its incidence rates have recently increased in almost all countries. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and is the second leading cause of cancer-related deaths worldwide. Because of the late diagnosis and lack of efficient therapeutic modality for advanced stages of HCC, the death rate continues to increase by ~2–3% per year. Circulating tumor cells (CTCs) are promising tools for early diagnosis, precise prognosis, and follow-up of therapeutic responses. They can be considered to be an innovative biomarker for the early detection of tumors and targeted molecular therapy. In this review, we briefly discuss the novel materials and technologies applied for the practical isolation and detection of CTCs in HCC. Also, the clinical value of CTC detection in HCC is highlighted.

Laser-directed energy deposition (LDED) is a promising technology for coating, repairing, and building near-net-shape 3D structures. However, the processing of copper alloys, specifically, has presented a significant challenge due to their low laser absorptivity at the 1060 nm laser wavelength and high thermal conductivity. This study undertook a methodical examination by employing a 2 kW disk laser, operating at a wavelength of 1064 nm, and a coaxial nozzle head to comprehensively examine the processability of the highly conductive CuCrZr alloy for expanding the range of materials that can be successfully processed using LDED. The investigation focuses not only on optimizing the input process parameters that are the laser power, scanning speed, powder feed rate, and overlap ratio, but also on planning the toolpath trajectory, as these factors were found to exert a substantial influence on processability, geometrical accuracy, and the occurrence of defects such as lack of fusion. The optimal toolpath trajectory discovered involved implementing a zigzag strategy combined with a 90° rotation of the scanning direction. Additionally, a start point rotation was considered between each layer to even out the deposition of the layers. Moreover, a contour with a radial path at the corners was introduced to enhance the overall trajectory. Based on the hierarchal experimental study, the appropriate ranges for the key process parameters that leads to 99.99% relative density have been identified. They were found to be from 1100 up to 2000 W for the laser power (P), and from 0.003 up to 0.016 g/mm for the amount of powder that is fed to the melt pool distance (F/V). Regarding the influence of process parameters on the microstructure of the samples with equal deposition height, it was observed that varying combinations of process parameters within the optimal processing window resulted in variations in grain size ranging from 105 to 215 µm.

A novel reconfigurable Microwave Photonics (MWP) mixer is presented in this paper, which can be configured to work as a frequency hopper, ASK modulator and phase shifter. This mixer is based on a cascaded Mach–Zehnder Modulator (MZM) structure. A general nonlinear analytical model for the structure is presented. This model is platform free, which means it can be applied to several MWP and integrated MWP platforms. Based on the analytical model, the performance of the structure and output results, such as the optical and electrical spectrum of the structure, are derived in mathematical closed-form expressions. The results of the presented analytical model are compared and evaluated with the results obtained from the simulation to prove the correctness of the analytical model. The presented structure has a simple form, which can be fabricated at a low cost. In addition, according to the obtained results from the analytical model, there is no need to change the arrangement of the structure to operate in any of the mentioned configurations, and the desired function is achievable only by changing the bias voltage of the modulators at the desired frequency.

The longest (s,t)-path problem on supergrid graphs is known to be NP-complete. However, the complexity of this problem on supergrid graphs with or without holes is still unknown.In the past, we presented linear-time algorithms for solving the longest (s,t)-path problem on L-shaped and C-shaped supergrid graphs, which form subclasses of supergrid graphs without holes. In this paper, we will determine the complexity of the longest (s,t)-path problem on O-shaped supergrid graphs, which form a subclass of supergrid graphs with holes. These graphs are rectangular supergrid graphs with rectangular holes. It is worth noting that O-shaped supergrid graphs contain L-shaped and C-shaped supergrid graphs as subgraphs, but there is no inclusion relationship between them. We will propose a linear-time algorithm to solve the longest (s,t)-path problem on O-shaped supergrid graphs. The longest (s,t)-paths of O-shaped supergrid graphs have applications in calculating the minimum trace when printing hollow objects using computer embroidery machines and 3D printers.

Modern technologies have changed human life and created a generation of customers who have different needs compared to the past. Considering Industry 4.0 and its drivers, the implementation of digital banking (DB) has faced various challenges that are caused by emerging trends. Both Industry 4.0 and DB are contemporary concepts, and decision-makers are often faced with uncertainties in their decisions regarding the implementation of DB and its indicators. For this purpose, a novel multi-criteria group decision-making approach has been developed utilizing the best–worst method (BWM) and α-cut analysis as well as trapezoidal fuzzy numbers (TFNs). By reviewing the literature and using experts’ opinions, the DB implementation criteria are determined, and considering an uncertain environment, the criteria are prioritized using the proposed method. Then, the available DB models and alternatives are examined based on the decision criteria and the importance of each criterion. This research contributes to the existing literature by identifying and prioritizing the criteria necessary for the successful implementation of DB, taking into account emerging trends and technological advances driven by Industry 4.0. Subsequently, the study prioritizes the prevalent models of DB based on these criteria. This study proposes a decision-support framework for dealing with ambiguity, lack of information, insufficient knowledge, and uncertainty in decision-making. The framework uses TFNs to account for imprecision and doubt in decision-makers’ preferences. Additionally, the study presents a fuzzy multi-criteria group decision-making approach that enables a group of experts to arrive at more reliable results. The proposed approach can help improve the quality of decision-making in complex and uncertain situations. The results of this research show that human resources, rules and regulations, and customer satisfaction are the most important criteria for implementing DB. In addition, the open, blockchain, and social banking models are the crucial models that significantly cover the implementation criteria for DB.

Anhydrous ferrous (II) oxalate (AFO) outperforms its hydrated form when used as an anode material in Li-ion batteries (LIBs). With the increasing interest in Na-ion batteries (NIBs) in mind, we examine the potential of AFO as the anode in NIBs through first principles calculations involving both periodic and non-periodic structures. Our analysis based on periodic (non-periodic) modeling scheme shows that the AFO anode generates a low reaction potential of 1.22 V (1.45 V) in the NIBs, and 1.34 V (1.24 V) in the LIBs, which is much lower than the potential of NIBs with mixed oxalates. The conversion mechanism in the underlying electrochemical process involves the reduction of Fe2+ with the addition of Na or Li. Such conversion electrodes can achieve high capacities through the Fe2+ valence states of iron.

The sustainable Supplier Evaluation and Selection and Order Allocation (SSOA) problem has received significant attention in supply chain management due to its potential to enhance a company’s performance, improve customer satisfaction, and reduce costs. In this study, an integrated methodology is proposed to address the SSOA problem. The methodology combines multiple techniques to handle the uncertainties associated with supplier evaluation, including a new ranking method based on the concept of Radius of Gyration (ROG) for interval type-2 fuzzy sets. The methodology also incorporates both subjective weights obtained using the Simple Multi-Attribute Rating Technique (SMART) and expert preferences, and objective weights calculated using the Method based on the Removal Effects of Criteria (MEREC) method to determine the weights of evaluation criteria. Some criteria for sustainable development are used to evaluate supplier performance, resulting in type-2 fuzzy sets, which are evaluated using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The ROG-based ranking method is employed to calculate the relative scores of suppliers. Finally, a multi-objective decision-making (MODM) mathematical model is presented to identify suitable suppliers and allocate their order quantities. The methodology is demonstrated in a sustainable SSOA problem and is shown to be efficient and effective, as the ROG-based ranking method allows for more accurate supplier performance evaluation, and the use of the criteria highlights the importance of sustainability in supplier selection and order allocation. The methodology’s practicality is further supported by the analysis conducted in this study, which demonstrates the methodology’s ability to handle the uncertainties associated with supplier evaluation and selection. The proposed methodology offers a comprehensive approach to the SSOA problem that can effectively handle the uncertainties in supplier evaluation and selection and promote sustainable practices in supply chain management.

The attractions and capabilities of geomorphosites are among the unique assets of each country, and their identification, classification, and planning have great importance for the development of tourism. The purpose of this research was to identify, quantitatively analyse, and classify landforms treated as geosites and landscapes of Yazd Province, using the Pralong method. The present study is a descriptive analytical research based on library studies and field surveys. After determining the study area using satellite imagery, six geomorphosites were selected. Using the Pralong method, six geomorphosites were evaluated: Chak Chak, Mountain Eagle, Siahkooh, Shirkooh, Qanat, and Barfkhane Tezerjan. In this method, using the extraction of collected data from the questionnaires completed by 41 geotourism experts in the first stage, the four grades that were evaluated in terms of potential capability of geomorphosites include the appearance aesthetic, scientific, historical-cultural, and socio-economic variables, and in the next step, two variables of productivity value and quality of productivity were evaluated. The results of evaluations showed that the geomorphosites Chak Chak and Barfkhane Tezerjan had the highest score (0.62) and are the best geomorphosites for converting to geotourism and ecotourism applications, and they have high potential for attracting tourists. The second place was dedicated to the Shirkooh geomorphosite, which is considerable in terms of the average tourism grade. The best average productivity value belonged to the Chak Chak geomorphosite with 0.52, and the last one was Mountain Eagle with 0.32. All six attractions in this study had a medium grade in the qualitative scale index, meaning that they have good potential in geotouristic and ecotouristic points of view and could be improved by regional planning. Therefore, the results of this study can be used by local managers and planners to develop and promote geotourism and ecotourism.

Long non-coding RNAs (lncRNAs) are known to be important regulators in different cellular processes and are implicated in various human diseases. Recently, lncRNA PNKY has been found to be involved in pluripotency and differentiation of embryonic and postnatal neural stem cells (NSCs); however, its expression and function in cancer cells is still unclear. In the present study, we observed the expression of PNKY in various cancer tissues, including brain, breast, colorectal, and prostate cancers. In particular, we demonstrated that lncRNA PNKY was significantly upregulated in breast tumors, especially high-grade tumors. Knock down experiments indicated that the suppression of PNKY in breast cancer cells could restrict their proliferation by promoting apoptosis, senescence, and cell cycle disruption. Moreover, the results demonstrated that PNKY may play a crucial role in the cell migration of breast cancer cells. We further found that PNKY may trigger EMT in breast cancer cells by upregulating miR-150 and restricting the expression of Zeb1 and Snail. This study is the first to provide new evidence on the expression and biological function of PNKY in cancer cells and its potential contribution to tumor growth and metastasis.

Today, most of the issues and challenges faced by managers and decision makers are complex and multifaceted. More clearly, due to the developments of technologies, emerging trends in various industries, competitive markets, and rapid and transformative changes in the business environment, managers and decision makers have faced an uncertain environments and issues that cannot be resolved definitively. The use of multi-criteria decision-making (MCDM) methods as a practical and decision-supporting tool allows managers to examine decision-making issues in various organizations and industries based on various criteria, alternatives, and objectives and make decisions with greater reliability. The use of fuzzy techniques and concepts in MCDM methods and their mathematical relationships makes it possible to consider complexities and uncertainties in decisions related to various issues and it can lead to better and more realistic decisions. In this paper, the simplified best-worst method (SBWM), which is one of the methods based on pairwise comparisons, has been developed using triangular fuzzy numbers (TFNs) to propose a fuzzy extension of SBWM (F-SBWM). Triangular fuzzy numbers in different symmetric and asymmetric forms have widely been used in MCDM approaches and pairwise comparisons. It is noteworthy that symmetric numbers are used when we are using equal division of the domain due to an increased ambiguity and lack of information. The proposed approach as a simplified fuzzy MCDM method helps managers and decision makers in various industries to solve decision-making problems under uncertainty without the need for complex calculations, specialized skills, and software packages. To check the feasibility and applicability of the proposed approach, two numerical examples and a computational experiment with real data are presented, and the results are analyzed and discussed. Furthermore, to check the robustness of the results obtained from the proposed approach, sensitivity analysis and comparison of methods have been performed.

The majority of monogenic liver diseases are autosomal recessive disorders, with few being sex-related or co-dominant. Although orthotopic liver transplantation (LT) is currently the sole therapeutic option for end-stage patients, such an invasive surgical approach is severely restricted by the lack of donors and post-transplant complications, mainly associated with life-long immunosuppressive regimens. Therefore, the last decade has witnessed efforts for innovative cellular or gene-based therapeutic strategies. Gene therapy is a promising approach for treatment of many hereditary disorders, such as monogenic inborn errors. The liver is an organ characterized by unique features, making it an attractive target for in vivo and ex vivo gene transfer. The current genetic approaches for hereditary liver diseases are mediated by viral or non-viral vectors, with promising results generated by gene-editing tools, such as CRISPR-Cas9 technology. Despite massive progress in experimental gene-correction technologies, limitations in validated approaches for monogenic liver disorders have encouraged researchers to refine promising gene therapy protocols. Herein, we highlighted the most common monogenetic liver disorders, followed by proposed genetic engineering approaches, offered as promising therapeutic modalities.

With the introduction of the working principle of coupled resonators, the coupled bulk acoustic wave (BAW) Micro-Electro-Mechanical System (MEMS) resonators have been attracting much attention. In this paper, coupled BAW MEMS resonators are discussed, including the coupling theory, the actuation and sensing theory, the transduction mechanism, and the applications. BAW MEMS resonators normally exhibit two types of vibration modes: lateral (in-plane) modes and flexural (out-of-plane) modes. Compared to flexural modes, lateral modes exhibit a higher stiffness with a higher operating frequency, resulting in a lower internal loss. Also, the lateral mode has a higher Q factor, as the fluid damping imposes less influence on the in-plane motion. The coupled BAW MEMS resonators in these two vibration modes are investigated in this work and their applications for sensing, timing, and frequency reference are also presented.

Faults in distribution networks occur unpredictably, causing a threat to public safety and resulting in power outages. Automated, efficient, and precise detection of faulty sections could be a major element in immediately restoring networks and avoiding further financial losses. Distributed generations (DGs) are used in smart distribution networks and have varied current levels and internal impedances. However, fault characteristics are completely unknown because of their stochastic nature. Therefore, in these circumstances, locating the fault might be difficult. However, as technology advances, micro-phasor measurement units (micro-PMU) are becoming more extensively employed in smart distribution networks, and might be a useful tool for reducing protection uncertainties. In this paper, a new machine learning-based fault location method is proposed for use regardless of fault characteristics and DG performance using recorded data of micro-PMUs during a fault. This method only uses the recorded voltage at the sub-station and DGs. The frequency component of the voltage signals is selected as a feature vector. The neighborhood component feature selection (NCFS) algorithm is utilized to extract more informative features and lower the feature vector dimension. A support vector machine (SVM) classifier is then applied to the decreased dimension training data. The simulations of various fault types are performed on the 11-node IEEE standard feeder equipped with three DGs. Results reveal that the accuracy of the proposed fault section identification algorithm is notable.

We discuss the applicability of the naturally occurring compound Ferrous Oxalate Dihydrate (FOD) (FeC2O4·2H2O) as an anode material in Li-ion batteries. Using first-principles modeling, we evaluate the electrochemical activity of FOD and demonstrate how its structural water content affects the intercalation reaction and contributes to its performance. We show that both Li0 and Li+ intercalation in FOD yields similar results. Our analysis indicates that fully dehydrated ferrous oxalate is a more promising anodic material with higher electrochemical stability: it carries 20% higher theoretical Li storage capacity and a lower voltage (0.68 V at the PBE/cc-pVDZ level), compared to its hydrated (2.29 V) or partially hydrated (1.43 V) counterparts.

We discuss the characteristic factors that determine the electrochemical potentials in a metal-organic framework used as cathode for Li-ion batteries via density functional theory-based simulations. Our focus is on MIL-101(Fe) cathode material. Our study gives insight into the role of local atomic environment and structural deformations in generating electrochemical potential.

The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria.

Feeble cellular responses induced by T cell-based vaccines are a major challenge for the development of an effective vaccine against Hepatitis C virus (HCV) infection. To address this challenge, the potential of N-terminal fragment of gp96 heat shock protein (rNT (gp96) as an adjuvant was evaluated and compared to that of the CpG (as a recognized Th1-type adjuvant) in the formulation of HCV core/NS3 antigens in three immunization strategies of protein/protein, DNA/DNA, and DNA/protein. Immunized mice were evaluated for elicited immune responses in week 3 (W3) and 11 post-immunizations. Our results demonstrated that the protein (subunit) vaccine formulated with rNT (gp96) in protein/protein strategy (core/NS3 + gp96) was significantly more efficient than CpG oligodeoxynucleotides (CpG ODN) formulation and all other immunization strategies in the induction of Th1-type cytokines. This group of mice (core/NS3 + gp96) also elicited a high level of anti-Core-NS3 total immunoglobulin G (IgG) with dominant IgG2a isotype at W3. Thus, the co-administration of recombinant NT (gp96) protein with rHCV proteins might be a promising approach in the formulation of HCV subunit vaccine candidates for induction of high levels of Th1 cytokines and humoral responses.

Production from mature oil reservoirs can be optimized by using the surfactant flooding technique. This can be achieved by reducing oil and water interfacial tension (IFT) and modifying wettability to hydrophilic conditions. In this study, a novel green non-ionic surfactant (dodecanoyl-glucosamine surfactant) was synthesized and used to modify the wettability of carbonate reservoirs to hydrophilic conditions as well as to decrease the IFT of hydrophobic oil–water systems. The synthesized non-ionic surfactant was characterized by Fourier transform infrared spectroscopy (FTIR) and chemical shift nuclear magnetic resonance (HNMR) analyses. Further pH, turbidity, density, and conductivity were investigated to measure the critical micelle concentration (CMC) of surfactant solutions. The result shows that this surfactant alters wettability from 148.93° to 65.54° and IFT from 30 to 14 dynes/cm. Core-flooding results have shown that oil recovery was increased from 40% (by water flooding) to 59% (by surfactant flooding). In addition, it is identified that this novel non-ionic surfactant can be used in CO2 storage applications due to its ability to alter the hydrophobicity into hydrophilicity of the reservoir rocks.

The world’s energy demand is steadily increasing where it has now become difficult for conventional hydrocarbon reservoir to meet levels of demand. Therefore, oil and gas companies are seeking novel ways to exploit and unlock the potential of unconventional resources. These resources include tight gas reservoirs, tight sandstone oil, oil and gas shales reservoirs, and high pressure high temperature (HPHT) wells. Drilling of HPHT wells and shale reservoirs has become more widespread in the global petroleum and natural gas industry. There is a current need to extend robust techniques beyond costly drilling and completion jobs, with the potential for exponential expansion. Drilling fluids and their additives are being customized in order to cater for HPHT well drilling issues. Certain conventional additives, e.g., filtrate loss additives, viscosifier additives, shale inhibitor, and shale stabilizer additives are not suitable in the HPHT environment, where they are consequently inappropriate for shale drilling. A better understanding of the selection of drilling fluids and additives for hydrocarbon water-sensitive reservoirs within HPHT environments can be achieved by identifying the challenges in conventional drilling fluids technology and their replacement with eco-friendly, cheaper, and multi-functional valuable products. In this regard, several laboratory-scale literatures have reported that nanomaterial has improved the properties of drilling fluids in the HPHT environment. This review critically evaluates nanomaterial utilization for improvement of rheological properties, filtrate loss, viscosity, and clay- and shale-inhibition at increasing temperature and pressures during the exploitation of hydrocarbons. The performance and potential of nanomaterials, which influence the nature of drilling fluid and its multi-benefits, is rarely reviewed in technical literature of water-based drilling fluid systems. Moreover, this review presented case studies of two HPHT fields and one HPHT basin, and compared their drilling fluid program for optimum selection of drilling fluid in HPHT environment.

Recently, Tahmasebi and Eskandarzadeh introduced a new extended cumulative entropy (ECE). In this paper, we present results on shift-dependent measure of ECE and its dynamic past version. These results contain stochastic order, upper and lower bounds, the symmetry property and some relationships with other reliability functions. We also discuss some properties of conditional weighted ECE under some assumptions. Finally, we propose a nonparametric estimator of this new measure and study its practical results in blind image quality assessment.

Redox mediators could be used to improve the efficiency of microbial fuel cells (MFCs) by enhancing electron transfer rates and decreasing charge transfer resistance at electrodes. However, many artificial redox mediators are expensive and/or toxic. In this study, laccase enzyme was employed as a biocathode of MFCs in the presence of two natural redox mediators (syringaldehyde (Syr) and acetosyringone (As)), and for comparison, a commonly-used artificial mediator 2,2′-azinobis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) was used to investigate their influence on azo dye decolorization and power production. The redox properties of the mediator-laccase systems were studied by cyclic voltammetry. The presence of ABTS and As increased power density from 54.7 ± 3.5 mW m−2 (control) to 77.2 ± 4.2 mW m−2 and 62.5 ± 3.7 mW m−2 respectively. The power decreased to 23.2 ± 2.1 mW m−2 for laccase with Syr. The cathodic decolorization of Acid orange 7 (AO7) by laccase indicated a 12⁻16% increase in decolorization efficiency with addition of mediators; and the Laccase-Acetosyringone system was the fastest, with 94% of original dye (100 mgL−1) decolorized within 24 h. Electrochemical analysis to determine the redox properties of the mediators revealed that syringaldehyde did not produce any redox peaks, inferring that it was oxidized by laccase to other products, making it unavailable as a mediator, while acetosyringone and ABTS revealed two redox couples demonstrating the redox mediator properties of these compounds. Thus, acetosyringone served as an efficient natural redox mediator for laccase, aiding in increasing the rate of dye decolorization and power production in MFCs. Taken together, the results suggest that natural laccase redox mediators could have the potential to improve dye decolorization and power density in microbial fuel cells.

Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers’ preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information.

This paper develops a framework to obtain the flow stress of nickel-based superalloys as a function of γ-γ’ morphology. The yield strength is a major factor in the design of these alloys. This work provides additional effects of γ’ morphology in the design scope that has been adopted for the model developed by authors. In general, the two-phase γ-γ’ morphology in nickel-based superalloys can be divided into three variables including γ’ shape, γ’ volume fraction and γ’ size in the sub-grain microstructure. In order to obtain the flow stress, non-Schmid crystal plasticity constitutive models at two length scales are employed and bridged through a homogenized multi-scale framework. The multi-scale framework includes two sub-grain and homogenized grain scales. For the sub-grain scale, a size-dependent, dislocation-density-based finite element model (FEM) of the representative volume element (RVE) with explicit depiction of the γ-γ’ morphology is developed as a building block for the homogenization. For the next scale, an activation-energy-based crystal plasticity model is developed for the homogenized single crystal of Ni-based superalloys. The constitutive models address the thermo-mechanical behavior of nickel-based superalloys for a large temperature range and include orientation dependencies and tension-compression asymmetry. This homogenized model is used to obtain the morphology dependence on the flow stress in nickel-based superalloys and can significantly expedite crystal plasticity FE simulations in polycrystalline microstructures, as well as higher scale FE models in order to cast and design superalloys.

In a straightforward and fast protocol, a mixture of 1,3-dimethylimidazolium fluoride ([DMIM]F) and 1-butylimidazolium tetrafluoroborate ([Hbim]BF4) efficiently catalyzed the reaction of epoxides with ketene silyl acetals (KSA) to give various γ-lactones under metal-free conditions. Diverse kinds of the desired γ-lactones were directly prepared with high regioselectivities and yields in a simple one-pot procedure using [DMIM]F as Si–O bond activator and [Hbim]BF4 as solvent and acidic ionic liquid catalyst. The ionic liquid mixture was recovered and reused three times and no loss in its activity was observed.

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High specific surface is a significant characteristic in zinc coatings that can be highly applicable in batteries and catalysts. Conventional methods to create foams are not cost-efficient, nor could they make a high specific surface. Electroplating has been developed that can produce a very high specific surface foam. On the other hand, conductive ink can create an affordable conductive surface with a high specific surface, so the study on using conductive ink, which has a cost-efficient nature, was necessary to create a conductive surface. This work has investigated the effect of crucial parameters, such as graphite size, coating time and bath composition, on the current efficiency and SEM microstructure. As a result, a 3 µm graphite size was found to be appropriate. Coated zinc escalates linearly with current efficiency for up to 5 h, and then it decreases. Although the zinc concentration increases up to 0.12 mol/L in the electrolyte, making a slight increase in loading, the current efficiency was almost unchanged. However, if it increases more, the loading and current efficiency significantly rise so that the loading grows up to 16 times and the current density increases up to 86%. Additionally, the morphology changes from dendritic to compact plates, sphere and semi-sphere, subsequently.

Supergrid graphs are derived by computing stitch paths for computerized embroidery machines. In the past, we have studied the Hamiltonian-related properties of supergrid graphs and their subclasses of graphs. In this paper, we propose a generalized graph class for supergrid graphs called extended supergrid graphs. Extended supergrid graphs include grid graphs, supergrid graphs, diagonal supergrid graphs, and triangular supergrid graphs as subclasses of graphs. In this paper, we study the problems of domination and independent domination on extended supergrid graphs. A dominating set of a graph is the subset of vertices on it, such that every vertex of the graph is in this set or adjacent to at least a vertex of this set. If any two vertices in a dominating set are not adjacent, this is called an independent dominating set. Domination and independent domination problems find a dominating set and an independent dominating set with the least number of vertices on a graph, respectively. The domination and independent domination set problems on grid graphs are known to be NP-complete, meaning that these two problems on extended supergrid graphs are also NP-complete. However, the complexities of these two problems in other subclasses of graphs remain unknown. In this paper, we first prove that these two problems on diagonal supergrid graphs are NP-complete, then, by a simple extension, we prove that these two problems on supergrid graphs and triangular supergrid graphs are also NP-complete. In addition, these two problems on rectangular supergrid graphs are known to be linearly solvable; however, the complexities of these two problems on rectangular triangular-supergrid graphs remain unknown. This paper provides tight upper bounds on the sizes of the minimum dominating and independent dominating sets for rectangular triangular-supergrid graphs.

In recent years, high demands for Se and Te in the solar panels and semiconductors industry have encouraged its extraction from primary and secondary sources. However, the two elements’ similar chemical and physical properties make pure element production, Se or Te, arduous. This work is aimed to investigate the significant factors of Se and/or Te recovery in the copper cementation process using the response surface methodology. The test was carried out in two series, for Te and Se, so that H2SO4, CuSO4, Te(or Se) concentration, and temperature are the factors of experimentation. According to response surface methodology (RSM) results for both test series (i. e. Se and Te), 50 g/L H2SO4, 15 g/L Cu, and 35 °C, 3000 mg/L Se (or 750 mg/L Te) was specified for higher Se recovery (97%), and the lowest Te extraction (2%) as an optimum condition, so that could make a suitable separation process. Hence, the cementation test was conducted in the simultaneous presence of Se and Te, so the separation index became 5291. Moreover, the cementation test was carried out in the pregnant leach solution of copper anode slime, and the separation factor was measured to be 606. On the other hand, the thermodynamic evaluation and XRD patterns of the process’s sediments confirm that Se is precipitated as Cu2Se and Cu1.8Se, whereas no Te components are detected in the sediments.

In the present study, a rapid, practical, selective and sensitive method was proposed for simultaneous determination of dopamine (DA) and uric acid (UA). Kinetic profiles of analytes were recorded and transformed by different mother wavelets. The contribution of ascorbic acid was neglected using mean centering of data before transformation. The concentrations range were 1.0–60.0 μmol L−1 and 7–40.0 μmol L−1, with detection limit of 0.06 and 0.30 μmol L−1 for uric acid and dopamine, respectively. The results of sym8 and db4 mother wavelets showed that proposed method creates a most selective and sensitive determination without using initial separation steps. The obtained results by CWT-sym8 and CWT-db4 were compared with partial least squares (PLS) results. The simultaneous quantitation of DA and UA with the proposed method was successfully applied in different urine and serum samples.

Reduction-oxidation (redox) reactions that transfer conduction electrons from the anode to the cathode are the fundamental processes responsible for generating power in Li-ion batteries. Electronic and microstructural features of the cathode material are controlled by the nature of the redox orbitals and how they respond to Li intercalation. Thus, redox orbitals play a key role in performance of the battery and its degradation with cycling. We unravel spectroscopic descriptors that can be used to gain an atomic-scale handle on the redox mechanisms underlying Li-ion batteries. Our focus is on X-ray Compton Scattering and Positron Annihilation spectroscopies and the related computational approaches for the purpose of identifying orbitals involved in electrochemical transformations in the cathode. This review provides insight into the workings of lithium-ion batteries and opens a pathway for rational design of next-generation battery materials.

Distributed Bragg Reflectors are optical structures capable of manipulating light behaviour, which are formed by stacking layers of thin-film materials. The inverse design of such structures is desirable, but not straightforward using conventional numerical methods. This study explores the application of Deep Learning to the design of a six-layer system, through the implementation of a Tandem Neural Network. The challenge is split into three sections: the generation of training data using the Transfer Matrix method, the design of a Simulation Neural Network (SNN) which maps structural geometry to spectral output, and finally an Inverse Design Neural Network (IDNN) which predicts the geometry required to produce target spectra. The latter enables the designer to develop custom multilayer systems with desired reflection properties. The SNN achieved an average accuracy of 97% across the dataset, with the IDNN achieving 94%. By using this inverse design method, custom-made reflectors can be manufactured in milliseconds, significantly reducing the cost of generating photonic devices and thin-film optics.

A graph is called Hamiltonian connected if it contains a Hamiltonian path between any two distinct vertices. In the past, we proved the Hamiltonian path and cycle problems for general supergrid graphs to be NP-complete. However, they are still open for solid supergrid graphs. In this paper, first we will verify the Hamiltonian cycle property of C-shaped supergrid graphs, which are a special case of solid supergrid graphs. Next, we show that C-shaped supergrid graphs are Hamiltonian connected except in a few conditions. For these excluding conditions of Hamiltonian connectivity, we compute their longest paths. Then, we design a linear-time algorithm to solve the longest path problem in these graphs. The Hamiltonian connectivity of C-shaped supergrid graphs can be applied to compute the optimal stitching trace of computer embroidery machines, and construct the minimum printing trace of 3D printers with a C-like component being printed.

Recurrence in hepatocellular carcinoma (HCC) after conventional treatments is a crucial challenge. Despite the promising progress in advanced targeted therapies, HCC is the fourth leading cause of cancer death worldwide. Radionuclide therapy can potentially be a practical targeted approach to address this concern. Rhenium-188 (188Re) is a β-emitting radionuclide used in the clinic to induce apoptosis and inhibit cell proliferation. Although adherent cell cultures are efficient and reliable, appropriate cell-cell and cell-extracellular matrix (ECM) contact is still lacking. Thus, we herein aimed to assess 188Re as a potential therapeutic component for HCC in 2D and 3D models. The death rate in treated Huh7 and HepG2 lines was significantly higher than in untreated control groups using viability assay. After treatment with 188ReO4, Annexin/PI data indicated considerable apoptosis induction in HepG2 cells after 48 h but not Huh7 cells. Quantitative RT-PCR and western blotting data also showed increased apoptosis in response to 188ReO4 treatment. In Huh7 cells, exposure to an effective dose of 188ReO4 led to cell cycle arrest in the G2 phase. Moreover, colony formation assay confirmed post-exposure growth suppression in Huh7 and HepG2 cells. Then, the immunostaining displayed proliferation inhibition in the 188ReO4-treated cells on 3D scaffolds of liver ECM. The PI3-AKT signaling pathway was activated in 3D culture but not in 2D culture. In nude mice, Huh7 cells treated with an effective dose of 188ReO4 lost their tumor formation ability compared to the control group. These findings suggest that 188ReO4 can be a potential new therapeutic agent against HCC through induction of apoptosis and cell cycle arrest and inhibition of tumor formation. This approach can be effectively combined with antibodies and peptides for more selective and personalized therapy.

Gold nanoparticles (GNPs) have been recently applied for various diagnostic and therapeutic purposes. The unique properties of these nanoparticles (NPs), such as relative ease of synthesis in various sizes, shapes and charges, stability, high drug-loading capacity and relative availability for modification accompanied by non-cytotoxicity and biocompatibility, make them an ideal field of research in bio-nanotechnology. Moreover, their potential to alleviate various inflammatory factors, nitrite species, and reactive oxygen production and the capacity to deliver therapeutic agents has attracted attention for further studies in inflammatory and autoimmune disorders. Furthermore, the characteristics of GNPs and surface modification can modulate their toxicity, biodistribution, biocompatibility, and effects. This review discusses in vitro and in vivo effects of GNPs and their functionalized forms in managing various autoimmune disorders (Ads) such as rheumatoid arthritis, type 1 diabetes, and multiple sclerosis.

Companies have been trying continuously to reduce their logistics costs in the current competitive markets. Warehouses are important components of the logistics systems and they must be managed effectively and efficiently to reduce the production cost as well as maintain customer satisfaction. Order-picking is the core of warehouse operations and an order-picking system (OPS) is essential to meet customer needs and orders. Failure to perform the OPS process properly results in high costs and customer dissatisfaction. This research aims to investigate the state of the art in the adoption of OPS and provide a broad systemic analysis on main operating strategies such as simultaneous consideration of order assignment, batching, sequencing, tardiness, and routing need. This study reviews 92 articles, classifies combinations of tactical and operational OPS problems, and provides guidelines on how warehouse managers can benefit from combining planning problems, in order to design efficient OPS and improve customer service. Combining multiple order-picking planning problems results in substantial efficiency benefits, which are required to face new market developments.

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.

Climate is changing and mitigation of the corresponding impacts requires assessment of vulnerability and adaptation building. This issue is particularly important in Middle East and North Africa (MENA), which is recognized as one of the most water scarce regions of the world and vulnerable to climate change. Therefore, the objective of this study was an assessment of the different sectors’ vulnerability as well as the overall vulnerability of the MENA countries to climate change. The Notre Dame-Global Adaptation Index (ND-GAIN) was used to investigate climate change vulnerability. Cluster analysis revealed the very high, high, medium and low levels of vulnerability for the MENA countries by distinguishing their extent of exposure, sensitivity and adaptive capacity. Further results indicated that the MENA countries have an acceptable status of infrastructure and habitat, tolerable health and ecosystem statuses, and inappropriate water and food conditions. Water shortage is also a serious problem in this region, to the extent that it is often assumed that water shortage is the root cause of all other types of vulnerability in MENA. However, the obtained results do not support this assumption. These findings provide insight about the adaptation challenges that should be faced and the choices that should be made in response to climate change, in MENA.

The ubiquitous persistence of plastic waste in diverse forms and different environmental matrices is one of the main challenges that modern societies are facing at present. The exponential utilization and recalcitrance of synthetic plastics, including polyethylene terephthalate (PET), results in their extensive accumulation, which is a significant threat to the ecosystem. The growing amount of plastic waste ending up in landfills and oceans is alarming due to its possible adverse effects on biota. Thus, there is an urgent need to mitigate plastic waste to tackle the environmental crisis of plastic pollution. With regards to PET, there is a plethora of literature on the transportation route, ingestion, environmental fate, amount, and the adverse ecological and human health effects. Several studies have described the deployment of various microbial enzymes with much focus on bacterial-enzyme mediated removal and remediation of PET. However, there is a lack of consolidated studies on the exploitation of fungal enzymes for PET degradation. Herein, an effort has been made to cover this literature gap by spotlighting the fungi and their unique enzymes, e.g., esterases, lipases, and cutinases. These fungal enzymes have emerged as candidates for the development of biocatalytic PET degradation processes. The first half of this review is focused on fungal biocatalysts involved in the degradation of PET. The latter half explains three main aspects: (1) catalytic mechanism of PET hydrolysis in the presence of cutinases as a model fungal enzyme, (2) limitations hindering enzymatic PET biodegradation, and (3) strategies for enhancement of enzymatic PET biodegradation.

In this paper, we use ideas from fractional calculus to study the rheological response of soft materials under steady-shearing flow conditions. The linear viscoelastic properties of many multi-scale complex fluids exhibit a power-law behavior that spans over many orders of magnitude in time or frequency, and we can accurately describe this linear viscoelastic rheology using fractional constitutive models. By measuring the non-linear response during large step strain deformations, we also demonstrate that this class of soft materials often follows a time-strain separability principle, which enables us to characterize their nonlinear response through an experimentally determined damping function. To model the nonlinear response of these materials, we incorporate the damping function with the integral formulation of a fractional viscoelastic constitutive model and develop an analytical framework that enables the calculation of material properties such as the rate-dependent shear viscosity measured in steady-state shearing flows. We focus on a general subclass of fractional constitutive equations, known as the Fractional Maxwell Model, and consider several different analytical forms for the damping function. Through analytical and computational evaluations of the shear viscosity, we show that for sufficiently strong damping functions, for example, an exponential decay of fluid memory with strain, the observed shear-thinning behavior follows a power-law response with exponents that are set by the power-law indices of the linear fractional model. For weak damping functions, however, the power-law index of the high shear rate viscosity is set by the terminal behavior of the damping function itself at large strains. In the limit of a very weak damping function, the theoretical formulation predicts an unbounded growth of the shear stress with time and a continuously growing transient viscosity function that does not converge to a meaningful steady-state value. By determining the leading terms in our analytical solution for the viscosity at both low and high shear rates, we construct an approximate analytic expression for the rate-dependent viscosity. An error analysis shows that, for each of the damping functions considered, this closed-form expression is accurate over a wide range of shear rates.

The rapid growth of CO2 emissions in the atmosphere has attracted great attention due to the influence of the greenhouse effect. Aerogels’ application for capturing CO2 is quite promising owing to their numerous advantages, such as high porosity (~95%); these are predominantly mesoporous (20–50 nm) materials with very high surface area (>800 m2∙g−1). To increase the CO2 level of aerogels’ uptake capacity and selectivity, active materials have been investigated, such as potassium carbonate, K2CO3, amines, and ionic-liquid amino-acid moieties loaded onto the surface of aerogels. The flexibility of the composition and surface chemistry of aerogels can be modified intentionally—indeed, manipulated—for CO2 capture. Up to now, most research has focused mainly on the synthesis of amine-modified silica aerogels and the evaluation of their CO2-sorption properties. However, there is no comprehensive study focusing on the effect of different types of aerogels and modification groups on the adsorption of CO2. In this review, we present, in broad terms, the use of different precursors, as well as modification of synthesis parameters. The present review aims to consider which kind of precursors and modification groups can serve as potentially attractive molecular-design characteristics in promising materials for capturing CO2.

Vaccination is of paramount importance to global health. With the advent of the more recent pandemics, the urgency to expand the range has become even more evident. However, the potential limited availability and affordability of vaccines to resource low- and middle-income countries has created a need for solutions that will ensure cost-effective vaccine production methods for these countries. Pichia pastoris (P. pastoris) (also known as Komagataella phaffii) is one of the most promising candidates for expression of heterologous proteins in vaccines development. It combines the speed and ease of highly efficient prokaryotic platforms with some key capabilities of mammalian systems, potentially reducing manufacturing costs. This review will examine the latest developments in P. pastoris from cell engineering and design to industrial production systems with focus on vaccine development and with reference to specific key case studies.

Inflammasomes are important intracellular multiprotein signaling complexes that modulate the activation of caspase-1 and induce levels of the proinflammatory cytokines interleukin-1β (IL-1β) and IL-18 in response to pathogenic microorganisms and molecules that originated from host proteins. Inflammasomes play contradictory roles in the development of inflammation-induced cancers. Based on several findings, inflammasomes can initiate and promote carcinogenesis. On the contrary, inflammasomes also exhibit anticancer effects by triggering pyroptosis and immunoregulatory functions. Herein, we review extant studies delving into different functions of inflammasomes in colorectal cancer development.

Antibodies of the IgG4 isotype are strongly associated with allergic disease but have several properties such as not precipitating with allergens, not activating complement and poor binding to Fcγ receptors that argue against a pro-inflammatory role. In keeping with that, IgG4 antibodies are a striking feature of the response to immunotherapy. In two naturally occurring situations IgG4 antibodies are common with low or absent IgE antibodies. The first example is children raised in a house with a cat and the second is eosinophilic esophagitis (EoE). In many population-based cohorts, the ownership of a cat in early childhood is associated with a decreased prevalence of a cat allergy at age 10. The second example (i.e., EoE) is a novel form of food allergy that is not mediated by IgE and is related to consuming cow’s milk or wheat. In EoE, patients have IgG4 to milk proteins in high > 10 µg/mL or very high > 100 µg/mL titers. Enigmatically these patients are found to have deposits of IgG4 in the wall of their inflamed esophagus. The factors that have given rise to EoE remain unclear; however, changes in food processing over the past 50 years, particularly ultra-heat treatment and the high pressure homogenization of milk, represent a logical hypothesis.

Lead composites have been used as anodes in the electrowinning process to produce metals such as copper and zinc. Manufacturing stable lead anodes with appropriate mechanical and chemical properties is required to improve the performance of the electrowinning process. In this study, an accumulative roll bonding (ARB) method was used to fabricate a Co/Pb nanocomposite. Utilizing the ARB method can help us to achieve a uniform structure with enhanced mechanical properties via severe plastic deformation. The results showed that suitable tensile properties were obtained in Pb–0.5%Co–10pass samples. The tensile strength and strain of these samples were 2.51 times higher and 83.7% lower than that of as-cast pure Pb. They also showed creep resistance and hardness up to 1.8 and 2.5 times more than that of as-cast pure Pb. The ARB technique uniformly distributed Co particles in the Pb matrix. The enhanced strength of Pb samples was observed in the composite including grain sizes of less than 50 nm as a result of hindering the recovery phenomenon. The particle size of the Co distributed in the Pb matrix was 353 ± 259 nm. Compared to conventional methods, the ARB process improved the mechanical properties of Co/Pb composites and can open a new horizon to fabricating this composite in metal industries.