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Objective: The integration of nanomaterials and herbal medicine has led to the design of new nanocomposites, which are therapeutically more effective. The purpose of this study was to prepare different zinc oxide (ZnO)-based nanoparticles (NPs) via Mentha longifolia extract based on gauze linen fibre and study its effects on wound healing. Methods: The textural properties, morphology, thermal stability, purity, spectroscopic and phase structure of nanoparticles were investigated. Subsequently, male Wistar rats were subjected to wounds in six different treatment groups: Group I: control; group II: ZnO/W prepared in water (W); group III: ZnO/M synthesised with Mentha longifolia (M) extract; group IV: ZnO/copper(II) oxide (CuO)/M nanocomposite synthesised with M extract; group IV: treated with ZnO/silver (Ag)/M nanocomposite; group V: treated with ZnO/Ag/M nanocomposite; and finally, group VI: treated with ZnO/CuO/Ag/M nanocomposite. In all groups, the wounds were treated for 21 days with prepared samples. Every seven days, after measuring the decreasing rate of the wound size, tissue samples from each group were taken for histopathological analysis. The prepared tissue sections were assessed by haematoxylin and eosin staining for the formation of the epidermis, dermis and muscular tissue, and Masson's Trichrome staining for the formation of collagen fibres. Results: The results showed that the ZnO/CuO/Ag/M nanocomposite was a significantly more effective wound healing material in comparison with other samples (pConclusion: In this study, the integration of ZnO/CuO/Ag nanocomposites with secondary metabolites of Mentha longifolia gave rise to a superior combination, which could support different phases of wound healing via the regulation of cytokines and growth factors in the course of healing.

Modeling reservoir sedimentation is particularly challenging due to the simultaneous simulation of shallow shores, tributary deltas, and deep waters. The shallow upstream parts of reservoirs, where deltaic avulsion and erosion processes occur, compete with the validity of modeling assumptions used to simulate the deposition of fine sediments in deep waters. We investigate how complex numerical models can be calibrated to accurately predict reservoir sedimentation in the presence of competing model simplifications and identify the importance of calibration parameters for prioritization in measurement campaigns. This study applies Bayesian calibration, a supervised learning technique using surrogate-assisted Bayesian inversion with a Gaussian Process Emulator to calibrate a two-dimensional (2d) hydro-morphodynamic model for simulating sedimentation processes in a reservoir in Albania. Four calibration parameters were fitted to obtain the statistically best possible simulation of bed level changes between 2016 and 2019 through two differently constraining data scenarios. One scenario included measurements from the entire upstream half of the reservoir. Another scenario only included measurements in the geospatially valid range of the numerical model. Model accuracy parameters, Bayesian model evidence, and the variability of the four calibration parameters indicate that Bayesian calibration only converges toward physically meaningful parameter combinations when the calibration nodes are in the valid range of the numerical model. The Bayesian approach also allowed for a comparison of multiple parameters and found that the dry bulk density of the deposited sediments is the most important factor for calibration.

Background and Aim: The vast applications of nanotechnology in various fields including medicine, bring about the necessity to investigate the in vivo side effects of these materials. On this basis, we investigated the potential anti-diabetic activity of nanoparticles (NPs) along with toxicological effects on liver and pancreas tissue. Materials and Methods: In this excremental research after preparation of ZnO nanoparticles and their characterization with SEM, EDX, and TEM, 30 rats were studied in 6 groups of 5 each. The groups included 1- Healthy control 2- Diabetic control 3- Diabetic - Insulin (10 U/kg) 4- Diabetic - Cranberry (150 mg/kg) 5- Diabetic-ZnO (8 mg/kg) 6- Diabetic-ZnO + extract (8 mg/kg). Diabetes was induced with alloxan monohydrate via intraperitoneal injection (170 mg/kg). Rats were treated intraperitoneal for 16 days and every four days examined for blood glucose levels, at the end of the treatment period, the liver and pancreatic tissues were analyzed by hematoxylin-eosin staining. Data were analyzed using two-way ANOVA and Tukey post hoc tests in SPSS. Results: The analysis of nanoparticles revealed the capping of organic constituents on the surface of the biological nanoparticles. The assessment of serum samples displayed a significant decrease in blood glucose levels in the group that was treated by NPs prepared by extract when compared to that of the diabetic control group (p≤0/05). The histopathological analysis did not show any damages to the studied organs. Conclusion: The results obtained in the present study revealed that the bio-synthesized nanoparticles not only significantly decreased the blood glucose level of diabetic rats but also had no toxic effects on the liver and pancreas tissues at the concentrations used in this study.

Wound healing has long been recognised as a major clinical challenge for which stablishing more effective wound therapies is necessary. The generation of metallic nanocomposites using biological compounds is emerging as a new promising strategy for this purpose. In this study, four metallic nanoparticles (NPs) with propolis extract (Ext) and one without propolis including ZnO/Ext, ZnO/Ag/Ext, ZnO/CuO/Ext, ZnO/Ag/CuO/Ext and ZnO/W were prepared by microwave method and assessed for their wound healing activity on excision experimental model of wounds in rats. The developed nanocomposites have been characterised by physico‐chemical methods such as X‐ray diffraction, scanning electron microscopy, diffuse reflectance UV–vis spectroscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis and Brunauer–Emmett–Teller analyses. The wounded animals treated with the NPs/Ext in five groups for 18 days. Every 6 days, for measuring wound closure rate, three samples of each group were examined for histopathological analysis. The prepared tissue sections were investigated by haematoxylin and Eosin stainings for the formation of epidermis, dermis and muscular and Masson's trichrome staining for the formation of collagen fibres. These findings toughly support the probability of using this new ZnO/Ag/Ext materials dressing for a wound care performance with significant effect compared to other NPs.

The present study aimed at producing ZnO nanoparticles using the leaf extract of nettle (Urtica dioica) as a medicinally valuable plant to maximize the antidiabetic property of ZnO while excluding the chemical pollution from the synthesis process. The properties of the ZnO-extract sample were uncovered by various techniques and compared to that produced without the extract (ZnO). The results of the surface, optical, and thermal studies disclosed the presence of the extract biomolecules over the ZnO-extract sample and was further confirmed by GC–MS analysis. The ZnO-extract was intraperitoneally injected to alloxan-induced diabetic rats and the effects on the serum levels of fasting blood glucose, insulin, high-density lipoprotein cholesterol, total cholesterol, and total triglyceride were assessed. The obtained results were then compared with the effects of ZnO, nettle leaf extract, and insulin on the same factors. Among all the examined treatments, the best antidiabetic performance was obtained in the rats treated by ZnO-U. dioica extract mainly owing to the great synergistic interaction between its constituents.

This manuscript aimed to determine the underlying point mutations causing Duchenne muscular dystrophy (DMD) in a heterogeneous group of Iranian patients, who are clinically suspected. Whole-exome sequencing was utilized to detect disease-causing variants in 40 MLPA-negative DMD patients. Disease-causing variants were detected in the DMD gene in 36/40 of the patients (90%), and 4/40 of them (10%) remained undiagnosed. WES analysis revealed that nonsense variant was the most common type in our study (23/36 of the cases). Besides, 12/36 of the cases had frameshift variant, and one of the patients had a likely pathogenic splice variant in the DMD gene. Carrier testing revealed that 21/40 of the mothers had the identified variant. Therefore, most variants were inherited (58.3%), while 19/40 were de novo (41. 7%). The present study has demonstrated the importance of performing WES to detect disease-causing point mutations in MLPA-negative DMD patients and to identify carrier females. Due to regulatory challenges, the clinical development of therapeutic approaches is time-consuming and may not be available to all patients shortly. Therefore, it appears that the techniques used to accurately detect disease-causing variants in carrier mothers are a more efficient solution to prevent the increased prevalence of DMD.

Background 3MC syndrome type 3 is an autosomal recessive disorder caused by mutations in the COLEC10 gene besides other genes like COLEC11 and MASP1. This disorder is characterized by facial dysmorphism, cleft lip and palate, postnatal growth deficiency, cognitive impairment, hearing loss, craniosynostosis, radioulnar synostosis, genital and vesicorenal anomalies, cardiac anomalies, caudal appendage, and umbilical hernia. Methods In the present study, whole‐exome sequencing was performed in order to identify disease causing variant in an Iranian 7‐year‐old affected girl with craniosynostosis, dolichocephaly, blepharoptosis, clinodactyly of the 5th finger, high myopia, long face, micrognathia, patent ductus arteriosus, downslanted palpebral fissures, telecanthus, and epicanthus inversus. Identified variant confirmation in the patient and segregation analysis in her family were performed using Sanger sequencing method. Results A novel homozygous frameshift deletion variant [NM_006438.5: c.128_129delCA; p.(Thr43AsnfsTer9)] was identified within the COLEC10 gene. Up to now, only three 3MC syndrome patients with mutations in the COLEC10 gene have been reported, and here, we report the fourth patient and the first homozygous frameshift variant. Conclusion Other genes and factors responsible for 3MC syndrome occurrence are remained to be discovered. We believe further investigation of the genes in the lectin complement pathway is needed to be done for the identification of other causes of this disease., Up to now, only three 3MC syndrome patients with mutations in the COLEC10 gene have been reported, and here, we report the fourth patient and the first homozygous frameshift mutation.

Dynamic voltage restorer (DVR) is a series compensation device designed to compensate for voltage-related power quality (PQ) problems. In the weak distribution systems, the Thevenin impedance of the system is high. On the other hand, the AC-AC converter-based DVR takes the required compensation energy from the grid so that its current increases and extra voltage drop on the system impedance occurs worsening the situation. This paper investigates the operation challenges of the AC-AC converter-based DVR in weak distribution systems and determines the voltage sag compensation capability of the AC-AC converter-based DVR in such a condition. The detailed analysis of the voltage sag compensation capability of the DVR in weak grid is presented and the effect of different parameters such as the grid impedance, load current, and the load power factor are considered and analyzed. The analysis given in the paper are verified by simulation studies on a single-phase 220V DVR.

Transformerless inverters have been commonly used in grid-connected photovoltaic (PV) systems due to their high power density, low weight and volume, and high efficiency. However, they also suffer from the issue of leakage current. On the other hand, the ability to inject reactive power is another challenge of transformerless grid-connected PV inverters. In order to reduce leakage current and provide reactive power injection (RPI) capability, a single-phase transformerless grid-connected asymmetric phase-legs PV inverter is presented in this paper. The proposed inverter improves the conventional hybrid phase-legs PV inverter, ensuring that the common-mode voltage (CMV) is always constant. As a result, the high-frequency CMV is avoided, and the leakage current is diminished. Also, the proposed inverter has the same performance in the grid power factor of unity and non-unity. In order to validate the operation of the proposed PV inverter, the simulation results are presented and compared with the conventional hybrid phase-legs inverter based on a 1 kW sample.

Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface reservoirs that currently contains strong conceptual uncertainty. This means, several modeling approaches describing the biogeochemical process are plausible and modelers face the uncertainty of choosing the most appropriate one. The considered models differ in the underlying hypotheses about the process structure. Once observation data become available, a rigorous Bayesian model selection accompanied by a Bayesian model justifiability analysis could be employed to choose the most appropriate model, i.e. the one that describes the underlying physical processes best in the light of the available data. However, biogeochemical modeling is computationally very demanding because it conceptualizes different phases, biomass dynamics, geochemistry, precipitation and dissolution in porous media. Therefore, the Bayesian framework cannot be based directly on the full computational models as this would require too many expensive model evaluations. To circumvent this problem, we suggest to perform both Bayesian model selection and justifiability analysis after constructing surrogates for the competing biogeochemical models. Here, we will use the arbitrary polynomial chaos expansion. Considering that surrogate representations are only approximations of the analyzed original models, we account for the approximation error in the Bayesian analysis by introducing novel correction factors for the resulting model weights. Thereby, we extend the Bayesian model justifiability analysis and assess model similarities for computationally expensive models. We demonstrate the method on a representative scenario for microbially induced calcite precipitation in a porous medium. Our extension of the justifiability analysis provides a suitable approach for the comparison of computationally demanding models and gives an insight on the necessary amount of data for a reliable model performance., Deutsche Forschungsgemeinschaft, Projekt DEAL

We present version 3 of the open-source simulator for flow and transport processes in porous media DuMu$^\text{x}$. DuMu$^\text{x}$ is based on the modular C++ framework Dune (Distributed and Unified Numerics Environment) and is developed as a research code with a focus on modularity and reusability. We describe recent efforts in improving the transparency and efficiency of the development process and community-building, as well as efforts towards quality assurance and reproducible research. In addition to a major redesign of many simulation components in order to facilitate setting up complex simulations in DuMu$^\text{x}$, version 3 introduces a more consistent abstraction of finite volume schemes. Finally, the new framework for multi-domain simulations is described, and three numerical examples demonstrate its flexibility.

The microbially induced calcite precipitation (MICP) process is a reactive transport, which consists of various important biogeochemical processes, namely precipitation, and dissolution of calcite, adhesion of the biomass on surfaces, detachment of the biomass from the biofilm as well as growth and decay of the biomass. Due to the accumulation of the biofilm and especially the calcite precipitation, the flow conditions in the subsurface can be modified and especially the porosity and permeability can be reduced, so that the existing leakages are sealed. This sealing property of MICP is of interest in different applications, such as sealing cracks in gas tanks or in a cap rock for CO2 underground storageThe process of biofilm growth in porous media using MICP can be described by many models with different complexity and assumptions. Typically, complex models require more measurement data to constrain their parameters. Therefore, there is a need to seek a balance between model complexity and efforts for acquiring field data. To do so, the modelers are interested in assessing the similarities among these models and their prediction accuracy by comparing them with field observation data. In this study, we perform a Bayesian model legitimacy analysis to investigate the similarities among different MICP models and their prediction accuracy. Moreover, this analysis provides a model ranking based on computed model weights, achieved within the framework of Bayesian model selection (BMS). This framework requires many model evaluations, which makes the analysis intractable for computationally expensive MICP models. To overcome this issue, we use surrogate models that are constructed using arbitrary polynomial chaos expansion (aPCE). To account for the approximation error, we introduce a correction factor that compensates the inaccuracies due to replacing the original models by the surrogates.

In this paper, a new non-isolated step-up DC-DC converter is proposed for solar systems. The proposed converter has simple topology, low volume, and lightweight because only one switch and one inductor is utilized. So, the control strategy will be simple. The design focuses on achieving high voltage gain and low voltage and current stress on semiconductors. Also, using the least number of elements in the structure is the other objective of this study. The proposed converter is investigated in continuous conduction mode (CCM), and the mathematical analysis has been examined in details. To confirm the theoretical concept, the proposed converter performance is examined, and the results are presented in detail.

Boosting the low voltage output of renewable sources to the utility voltage state is one of the important issues in renewable applications. The boost DC-DC converters are widely used in these systems to attain the utility voltage. The benchmarking of the converters mainly in terms of the voltage gain, efficiency, the number of active and passive components, the voltage stress on semiconductors, and simplicity is considered. In this paper, a new extendable non-isolated step-up DC-DC converter is presented. Comparing the conventional boost converter, the basic structure of the proposed converter has a high voltage gain and reduced stress on the switch. To increase the voltage gain, the basic structure of the proposed converter can be easily extended. The detailed analysis of the proposed converter in continuous current mode (CCM) is presented. To verify theoretical concepts, the simulation results are carried out using the MATLAB/SIMULINK.

In this research, a milk thistle seed extract (MTSE)-rich medium was used as a capping and reducing agent for the one-pot biosynthesis of ZnO/Ag (5 wt%) nanostructure. The sample was systematically characterized through various techniques and its strong biomolecule‒metal interface structure was supported by the results. The efficacy of the derived nanostructure (MTSE/ZnO/Ag) was evaluated in vivo on the basis of its therapeutic effects on the main complications of Type 1 diabetes (hyperglycemia, hyperlipidemia, and insulin deficiency). For this purpose, the changes in the plasma values of fasting blood glucose, total cholesterol, total triglyceride, high-density lipoprotein cholesterol, and insulin in alloxan-diabetic Wistar male rats were compared with those in healthy and untreated diabetic controls after a treatment period of 16 days. The antidiabetic results of MTSE/ZnO/Ag were compared with those obtained from pristine ZnO, MTSE, and insulin therapies. The health conditions of the rats with Type 1 diabetes were significantly enhanced after treatment with MTSE/ZnO/Ag (p 0.05), which is owing to the enhanced interface structure and participatory functions of the united compartments of MTSE/ZnO/Ag.

Green synthesis of ZnO nanoparticles (NPs) using the plants' extract and their potential application have driven a tremendous interest in recent years. This study reports a green microwave-assisted method for synthesis of ZnO NPs using Silybum marianum L. seed extract. Characteristics of the as-prepared sample was explored in terms of crystalline phase, morphology, composition, surface area, optical, and thermal properties. The particles of the biosynthesized sample (ZnO/extract) had smaller sizes than the chemically produced one (ZnO). The existence of biomolecules from Silybum marianum L seed extract linked to the ZnO/extract sample was approved by various analyses. The ZnO/extract sample was used for treating alloxan-induced diabetic rats and its efficiency was compared with ZnO, extract, and insulin treatments. For this purpose, the levels of blood glucose, insulin, total cholesterol, total triglyceride, and high-density lipoprotein were measured before and after treating with the studied treatment agents and compared with each other. Moreover, the antibacterial activities of both ZnO samples were investigated against E. coli to assess their potential antibacterial application. From the results, ZnO/extract NPs represented an outstanding performance in overcoming the diabetic disorders and good antibacterial activity against the studied bacteria.

A variety of empirical formulas to predict river bed evolution with hydro-morphodynamic river models exists. Modelers lack objective guidance of how to select the most appropriate one for a specific application. Such guidance can be provided by Bayesian model selection (BMS). Its applicability is however limited by high computational costs. To transfer it to computationally expensive river modeling tasks, we propose to combine BMS with model reduction based on arbitrary Polynomial Chaos Expansion. To account for approximation errors in the reduced models, we introduce a novel correction factor that yields a reliable model ranking even under strong computational time constraints. We demonstrate our proposed approach on a case study for a 10-km stretch of the lower Rhine river. The correction factor may shield us from misleading model ranking results. In our case, the correction factor was shown to increase the confidence in model selection.

The aim of this essay is to investigate discursive, cognitive and social aspects of manipulation in regard to the dialogues of the literary fictional character of Gandalf in the trilogy of The Lord of the Rings. Accordingly, the researcher has taken a multidisciplinary approach to an account of discursive manipulation, and focuses on the cognitive dimensions of manipulation. As a result, the researcher demonstrates meticulously how manipulation involves intensifying the power, moral superiority and the credibility of the speaker(s), while abusing the others (recipients), along with an emotional and attractive way of expression, and supplemented by reasonable facts and documents in regard to a specific issue.

Diabetic retinopathy accounts for a considerable amount of the blindness especially among the patients who are between 20 to 60 years. The early detection of this disease plays an important role in preventing vision damages and appropriate follow-up care of diabetic eye. Manual investigation of color fundus images to check morphological changes in dark and bright lesions is tedious work and very time-consuming that can be made easily with the help of computer-aided diagnosis system. Many techniques were proposed for early detection of the abnormalities in the retinal images help the ophthalmologists recognize the retinopathy earlier. This paper presents a review of various automated algorithms that have been used for the detection of diabetic retinopathy.

One of the most interesting aspects of J.R.R. Tolkien’s stories, especially The Lord of the Rings is the presentation of the multidimensional characters; therefore, the complexity of interpretations concerning their actions, motives, and aims will be manifested from the beginning of the story, until the end. Following the study of a mythic hero’s adventure, initiation, and psychological aspects, the present paper focuses on the investigation of Predestinate Call to Adventure. The researcher has benefited the theories of Joseph Campbell, presented in his renowned book The Hero with a Thousand Faces and the supplementary comments of Christopher Vogler. In fact, the researcher’s motivation for the work initiated in this regard is to improve the very few previous attempts studied by others, concerning Frodo Baggins’ role as the main and the most tragic hero of The Lord of the Rings .

The presence of the Catholic framework in J.R.R. Tolkien’s legendarium has long been the subject of debate. Various Tolkien scholars and literary critics have already written different critical interpretations to consider whether to assign The Lord of the Rings and The Silmarillion to Christian Mythology or not; numerous attempts have been made to clarify this statement. Therefore, the reasons, why it should be included in this category are many and various. There are several examples in Tolkien’s The Lord of the Rings that can be studied in relation to Christian themes and motives. Consequently, the aims of this paper are to study the possible similarities of Varda, Queen of the Stars, and Galadriel, the Lady of Light, to the Blessed Virgin Mary in Christian contexts. Moreover, to study the influence of Tolkien’s strong faith, which shaped his Catholic imagination, all through his legendarium, and subsequently leads us to observe Tolkien’s complete obedience to Catholicism, and especially, his profound devotion to the Blessed Virgin Mary.

In this paper, I examine the theoretical aspects of worldbuilding in Murasaki’s and Tolkien’s imagined worlds and accentuate the role of aesthetic landscape creation through which spatio-temporal layers are negotiated. As a starting point, I refer to Thomas Ryba’s Husserl, Fantasy and Possible Worlds (1990), where he evaluates the believability of secondary worlds via Husserlian phenomenology. To shed light on Ryba’s statement that authors must be “adept at describing the qualities of characters and the world in which they live” (232) through the lens of engagement, I contend that critically acclaimed imagined worlds such as Heian Japan in The Tale of Genji (c.1000 A.D.) and Middle-earth in The Lord of the Rings (1954-1955) demonstrate two fundamental qualities: the physical environments possess aesthetic qualities and the emotional experience of the place is integrated into the fabric of worldbuilding, generating an aura of believability.