Grounded on the resource-based view, this study aims to examine the mediating role of product launch quality as a deployment mechanism in the association between market orientation and new product performance. Conducting an on-site survey of Iranian manufacturing industries, this study applies covariance-based structural equation modeling to test research hypotheses and verify the proposed theoretical model. The empirical findings indicate market orientation is a critical knowledge-based resource enhancing firms’ product launch quality, and right decisions concerning the product launch elevate new product performance. The results also reveal while market orientation significantly impacts new product performance, product launch quality is a crucial deployment mechanism for leveraging market orientation as it fully mediates impacts of market orientation on new product performance. The current static characterization of the resource-based view signifies strategic resources have potential value, but unleashing this potential requires incorporation of deployment mechanisms in the resource-performance link. Besides, considering this insufficient view, prior studies have revealed mixed and inconsistent results. Accordingly, through examining product launch quality as a deployment mechanism for leveraging market orientation on new product performance, not only does this study address inconsistent findings, but it noticeably contributes to the resource-based view by casting light on the mechanism through which market orientation as a strategic knowledge-based resource leads to superior new product performance.
The entorhinal cortex (EC) plays a pivotal role in epileptogenesis and seizures. EC expresses high density of serotonergic receptors, especially 5-HT 3 receptors. Cognitive impairment is common among people with epilepsy. The present study investigated the role of 5-HT 3 receptor on the severity of seizures and learning and memory impairment by electrical kindling of amygdala in rats. The amygdala kindling was conducted in a chronic kindling manner in male Wistar rats. In fully kindled animals, ramosetron (as a potent and selective 5-HT 3 receptor antagonist) was microinjected unilaterally (ad doses of 1, 10 or 100 µg/0.5 µl) into the EC 5 min before the novel object recognition (NOR) and Y-maze tests or kindling stimulations. Applying ramosetron at the concentration of 100 μg/0.5 µl (but not at 1 and 10 µg/0.5 µl) reduced afterdischarge (AD) duration and increased stage 4 latency in the kindled rats. Moreover, the obtained data from the NOR test showed that treatment by ramosetron (10 and 100 µg/0.5 µl) increased the discrimination index in the fully kindled animals. Microinjection of ramosetron (10 and 100 µg/0.5 µl) in fully kindled animals reversed the kindling induced changes in the percentage of spontaneous alternation in Y-maze task. The findings demonstrated an anticonvulsant role for a selective 5-HT 3 receptor antagonist microinjected into the EC, therefore, suggesting an excitatory role for the EC 5-HT 3 receptors in the amygdala kindling model of epilepsy. This anticonvulsive effect was accompanied with a restoring effect on cognitive behavior in NOR and Y-maze tests.
SARS-CoV-2 (COVID-19) is the causative organism for a pandemic disease with a high rate of infectivity and mortality. In this study, we aimed to assess the affinity between several available small molecule and proteins, including Abl kinase inhibitors, Janus kinase inhibitor, dipeptidyl peptidase 4 inhibitors, RNA-dependent RNA polymerase inhibitors, and Papain-like protease inhibitors, using binding simulation, to test whether they may be effective in inhibiting COVID-19 infection through several mechanisms. The efficiency of inhibitors was evaluated based on docking scores using AutoDock Vina software. Strong ligand–protein interactions were predicted among some of these drugs, that included: Imatinib, Remdesivir, and Telaprevir, and this may render these compounds promising candidates. Some candidate drugs might be efficient in disease control as potential inhibitors or lead compounds against the SARS-CoV-2. It is also worth highlighting the powerful immunomodulatory role of other drugs, such as Abivertinib that inhibits pro-inflammatory cytokine production associated with cytokine release syndrome (CRS) and the progression of COVID-19 infection. The potential role of other Abl kinase inhibitors, including Imatinib in reducing SARS-CoV and MERS-CoV viral titers, immune regulatory function and the development of acute respiratory distress syndrome (ARDS), indicate that this drug may be useful for COVID-19, as the SARS-CoV-2 genome is similar to SARS-CoV.
In this paper, we discuss the problem of estimating the unknown parameters of the Gompertz distribution and the acceleration factor under constant-stress partially accelerated life test model. Based on adaptive Type II progressive hybrid censored samples, the maximum likelihood estimates of the model parameters and acceleration factor are derived. From Bayesian aspect, the Bayes estimates of the unknown parameters are obtained using the Gibbs sampler together with Metropolis-Hastings (GMH) algorithm. Based on the interval estimation viewpoint, the asymptotic, Bayesian credible and bootstrap confidence intervals for model parameters and acceleration factor are also constructed. In order to investigate the impact of estimation procedures and methodologies adopted, a simulation study is performed. Finally, a real life example contains the persistence of the virus-containing micro droplets is analyzed to illustrate the application of the partially accelerated life test model. It is observed that the GMH algorithm is superior for estimating the parameters of partially accelerated life test model after comparison. The results of real example analysis show that the proposed model can be applied to the engineering problem and the considered methods are suitable for the modeling of the virus-containing micro droplets lifetime data under two co-current air flow velocities.
Background Phycocyanin is an important protein in cyanobacteria that has many medical and therapeutic properties. The aim of the present study was to compare the antibacterial properties of phycocyanin and its SNPs and to evaluate their effects on rat blood cells and liver enzymes. Results The UV absorption in phycocyanin was 620 nm but in phycocyanin nanoparticles was 420 nm. For fluorometry, the maximum emission peak of phycocyanin was 660 nm and that of phycocyanin-AgNO3 nanoparticles was 580 nm. PC-AgNp showed greater antibacterial effects than phycocyanin. In animal studies, it was found that the platelet count in both groups was higher than the control group. Red blood cells and white blood cells had changes. AST and ALT levels increased in both phycocyanin and nanoparticle groups and ALK levels decreased in both groups compared to the control group. Conclusions Examination of antibacterial activity showed that PC-AgNp showed more antibacterial effects than PC. Also, in the study of the effect of PC and NP-PC, accumulation of PC and C-Np in mice also altered blood cells and liver enzymes in rats.
Phytase is the commercial enzyme for bioconversion of phytate substrate to digestible phosphate ions. Recently silver nanoclusters (AgNCs) have received great attention as the optical transducer nanoparticles in biosensors structure. The novel detection platform was developed to detect the phytase enzyme activity and phosphate ions based on fluorescence quenching of AgNCs. The AgNCs were synthesized through gelatin supported reaction and characterized by TEM, FTIR and XRD analysis. The hydrolytic effect of phytase enzyme and subsequent phosphate release led to suppression of AgNCs fluorescence. The linear range was observed for enzyme in the range of 0.5–5 U/mL with the detection limit of 0.2 U/mL. Also, the same fluorescence quenching effect was observed in the presence of phosphate ion in the linear range of 1 to 16 µM with a detection limit of 0.5 µM. The proposed mechanism showed effectiveness of detection strategy for detection of phytase enzyme and phosphate ion.
Hydrogen sulfide (H2S) was identified as a novel signaling molecule that plays roles in plant growth and responses to abiotic stresses. However, information regarding its role in cadmium (Cd) detoxification and possible beneficial effects against oxidative damage in garlic plants is lacking. In this study, garlic (Allium sativum) seedlings were grown hydroponically at 0, 10⁻⁴, 10⁻³ and 10⁻² M of cadmium chloride (CdCl2) and 0, 200 µM concentrations of sodium hydrosulfide (NaHS). Cadmium stress caused growth inhibition and biomass reduction, which was related to high accumulation of cadmium in roots and shoots, depletion of chlorophyll contents, decrease of photosynthetic parameters and imbalanced in essential elements. These changes were accompanied by increasing activities of superoxide dismutase and ascorbate peroxidase enzymes while catalase enzyme activity decreased. The treatment with H2S ameliorator reduced Cd accumulation in seedling and improved photosynthetic rate of plants. This conclusion was supported by the increase of superoxide dismutase and ascorbate peroxidase activities as well as the balanced to mineral element uptake. Based on the results, it can be concluded that exogenous H2S has a positive effect on reducing Cd oxidative damages by adjusting antioxidant enzyme system and balances in nutrient element uptake, thus proposing H2S as a candidate for managing toxicity of cadmium in garlic plants.
The purpose of this study was to see how green synthesized zinc nanostructure (Zn NS) applied to the leaves of Zataria multiflora Boiss. affected the plant’s essential oil constituents, antioxidant activity, phenolic compounds, total phenolic, flavonoid, carotenoid, chlorophyll and anthocyanin contents. A completely randomized block design was used in this experiment. The zinc chelate (Zn-EDTA) was compared to foliar application of Zn NS fertilizer at three dosages (0, 100, and 300 mgL⁻¹). There was no significant difference on Zn content between Zn NS fertilizer with pomace extract at 100 and 300 mg L⁻¹ concentrations. In contrast to Zn-EDTA and control plants, fertilization with Zn nano-fertilizer at 300 mgL⁻¹ resulted in substantial essential oil production and major constituent of linalool. As shown in the findings, various sources of zinc fertilizer considerably increased oxygenated monoterpenes content. Other analyzed phytochemical attributes changed significantly with Zn nano-fertilizer, with the maximum level of evaluated phytochemical parameters observed at a dosage of 300 mgL⁻¹ when compared to the untreated reference. Furthermore, we discovered a favorable relationship between phytochemical characteristics. According to the findings of this study, green synthesized Zn NS has a substantial impact on all biochemical parameters. It may be inferred that Zn NS must be applied to the leaves of Z. multiflora to improve quality and quantity.
In this study, ferrate nanoparticles are prepared by solution plasma process and are employed for degradation of different dyes including Bromothymol blue, Cresol Red, Methylene blue, Methyl orange, Methyl Red, Methyl violet and Blue 203. TEM image indicates that particle size of synthesized nano-ferrate is lower than 50 nm. The effects of nanoparticle dosage, pH and temperature on dye degradation are examined. The degradation efficiency indicates that ferrate is capable for oxidation of dyes with high efficiency in very low reaction time. Moreover, removal efficiency of dyes increases more than 96 % by enhancing ferrate dosage especially with multiple addition of ferrate in very low dosage. The optimum temperature for oxidation is 25° and effective pH range is 6–8. The reaction kinetic of dye oxidation with ferrate is second order reaction and the calculated overall reaction rate constants indicate higher values for methyl orange and blue 203. The oxidation efficiency indicates no considerable variation in the presence of anions SO4²⁻, Cl⁻, and HCO3⁻ and monovalent cations K⁺ and Na⁺, while divalent and trivalent cations (Mg²⁺, Ca²⁺, Cu²⁺ and Fe³⁺) and humic acid inhibit dyes oxidation. In addition, real water systems including tap and river water without pH control are applied and the results show that removal efficiencies for most of dyes change very low. Mineralization efficiency of dyes measured by total organic carbon are about 50 % indicates that dyes are not degraded to CO2 completely. In addition, liquid chromatography equipped with mass spectrometry analysis after oxidation proves the TOC removal data.
Semi-variance is a similar measure to variance, but it only considers values that are below the expected value. As important roles of semi-variance in finance, this paper proposes the concept of semi-variance for uncertain random variables. Also, a computational approach for semi-variance is provided via inverse uncertainty distribution. As an application in finance, portfolio selection problems of uncertain random returns are solved by minimizing semi-variance in mean-semi variance models. For better illustration, mean-semi variance model is compared with mean-variance one. Finally, for better understanding, some tables, figures and outputs are provided.
Metal-organic frameworks (MOFs) are a promising class of porous nanomaterials in the field of environmental remediation. Ni-MOF and Fe-MOF were chosen for their advantages such as structural robustness and ease of synthesis route. The structure of prepared MOFs was characterized using FE-SEM, XRD, FTIR, and N2 adsorption-desorption. The efficiency of MOFs to remove organic model contaminants (anionic Alizarin Red S (ARS) and cationic malachite green (MG) and inorganic fluoride was studied. Fe-MOF and Ni-MOF adsorbed 67, 88, 6% and 32, 5, and 9% of fluoride, ARS, and MG, respectively. Further study on ARS adsorption by Fe-MOF showed that the removal efficiency was high in a wide range of pH from 3 to 9. Moreover, dye removal was directly increased by adsorbent mass (0.1–0.75 g/L) and decreased by ARS concentration (25–100 mg/L). The pseudo-first-order kinetic model and Langmuir isotherm model with a qmax of 176.68 mg/g described the experimental data well. The separation factor, KL, was in the range of 0–1, which means the adsorption process was favorable. In conclusion, Fe-MOF showed remarkable adsorption of organic and inorganic model contaminants.
The current work investigates the effect of oil to kerosene ratio, space velocity, temperature, demulsifier dosage, and wash water ratio on the performance of demulsification of water-in-heavy crude oil emulsions. For this purpose, an electrostatic desalting pilot plant has been utilized to carry out the experiments. Performance has been evaluated by determining the water removal efficiency (WRE) and the salt removal efficiency (SRE) based on operating parameters. Besides, the central composite design based on the response surface methodology was applied to design the experiments, model and optimize the water and salt removal processes. Moreover, the analysis of variance has been used to evaluate the significance of developed models, as well as operating parameters. It was observed that the proposed models for the WRE and SRE were found to be highly significant and presented the p-values < 0.0001. In addition, R² and adjusted-R² values were 94.78 and 92.01% for the WRE model, and 97.90 and 95.80% for the SRE model, which also emphasizes the high accuracy of both models. The obtained results demonstrated that the oil to kerosene ratio had the greatest impact on WRE as well as SRE compared to other studied parameters. The results show that the addition of the optimum value of 25 vol% kerosene to the emulsion could increase the maximum WRE and SRE by about 17.4, and 8.1%, respectively. At the same time, adding this volume of kerosene to the oil, in addition to such an increase in WRE and SRE, simultaneously reduced the optimum required demulsifier dosage and wash water ratio from 48 to 27 ppm and 8.5 to 5.5 vol%, respectively. Furthermore, the added kerosene also could increase oil space velocity from 0.5 to 0.7 1/h. The results of numerical optimization indicate that the optimal conditions to maximize the water and salt removal efficiencies were as follows: 75:25 (v/v), 0.7 1/h, 125 °C, 27 ppm, and 5.5 vol%, for oil to kerosene ratio, space velocity, temperature, demulsifier dosage, and wash water ratio, respectively. The maximum efficiency of water and salt removal from heavy crude oil under optimal values were achieved 92.89 and 98.73%.
In the present paper, we investigate the Moore–Penrose inverse and characteristic matrix of unbounded WCT operators on the Hilbert space L2(μ). In addition, we obtain some applications of the Moore–Penrose inverse of unbounded operators on the Hilbert space H to variational regularization problem. Moreover, some examples are provided to illustrate the applications of our results in linear equations and specially Fredholm integral equations.
A new approach for performance enhancement of dye sensitized solar cells (DSSC) is presented in this paper using a combination of co-sensitization method and Förster resonance energy transfer (FRET) from natural pigments to synthetic pigment. Although co-sensitization is the most common method for spectral extension of DSSCs, the loading of pigment on the semiconductor is restricted in this method. To overcome this problem, here, the TiO2 was sensitized directly by an organic synthetic pigment that has suitable anchor groups, while the natural pigments were used as energy-donors without the need for direct bonding to the TiO2. The natural pigments were selected in such a way that satisfies the FRET requirements. Three natural pigments were inexpensively extracted from plants to prepare a broad absorption spectrum. This issue was evaluated by UV–Visible analyses. It was found that the natural pigments can be more useful in the spectral expansion if applied in the FRET process as energy-donors due to their weaker anchoring groups compared to synthetic pigment. The anchoring groups of the extracted pigments were evaluated by FT-IR analysis. Also, the FRET occurrence between the natural pigments with the synthetic pigment was examined by photoluminescence spectroscopy. The results indicated a proper spectral overlap and emission quenching between these pigments. Finally, the opto-electrical performances of the DSSCs fabricated by the proposed method were investigated by J-V characteristics, electrochemical Impedance spectroscopy (EIS), and induced photon conversion efficiency (IPCE) compared with conventional co-sensitization methods (cocktail and sequential methods). The efficiencies obtained for these two conventional methods were 1.8% and 2.2%, respectively, while an efficiency of 2.9%. was provided by the proposed approach.
Many efforts have been done to develop new catalysts for organic reactions. In this study, preparation and characterization of palladium immobilized on modified magnetic Fe3O4 nanocatalyst (Fe3O4@SiO2@DPA-Pd) have been reported; dipicolylamine (DPA) groups are used as linkers to fix palladium nanoparticles on silica-coated Fe3O4 nanoparticles without agglomeration. The structure of the nanocatalyst was investigated using scanning electron microscopy, X-ray powder diffraction, Fourier-transform infrared spectroscopy, energy-dispersive X-ray spectroscopy, Brunauer–Emmett–Teller (BET) and thermogravimetry analysis. The data showed that the nanoparticles have spherical morphology with an average size of about 40 nm and 49.16 m²/g BET surface area. The inductively coupled plasma analysis confirmed that the Pd²⁺ had been successfully loaded on the Fe3O4@SiO2@DPA support with a high amount of 1.03 mmol g⁻¹. The synthesized nanocatalyst was considered for synthesis of biaryls by the Suzuki–Miyaura coupling reaction in water/ethanol as the solvent system and in the absence of toxic phosphine ligand. The reaction conditions were mild, and coupling reaction yields were excellent (68–95%). The synthesis is compatible with the environment. The nanocatalyst can be easily recycled from the reaction mixture using an external magnet and was used at least five times without significant loss of catalytic activity.
The synthesis of MIL-53 samples and encapsulation process of phosphomolybdic acid were implemented using ultrasound at ambient temperature and atmospheric pressure. Analysis of the results showed that H3PMo salts have strong electrostatic interactions with the iron (III) lattice, which plays an important role in reducing leaching from the compound. Characterization of newly synthesized nanocomposite was carried out using various techniques such as XRD, FT-IR, SEM, EDS, BET, ICP and NH3-TPD. The catalytic activity of the prepared nanocomposites, PMA@MIL-53(Fe), was tested through the esterification reaction of oleic acid with methanol under ultrasonic irradiation. Biodiesel production process using certain molar ratio of oleic acid/methanol, PMA@MIL-53(Fe) as catalyst (50–200 mg) containing different amounts of PMA (0–40%), at different reaction times (5–25 min) and ambient temperature under ultrasound conditions was optimized using CCD tab of Design Expert software. The results indicated that the synthesized composites show excellent catalytic activity. Graphical abstract
Quantile regression estimates conditional quantiles and has found extensive applications in real-life statistical procedures. This study assessed a new for nonlinear quantile regression modeling in cases where response variables are reported by triangular fuzzy numbers and predictors are exact data. For this purpose, the notion of the conditional quantile of a fuzzy random variable giving exact values and its empirical estimation were introduced. Then, a fuzzy empirical kernel-based quantile regression method was developed using a hybrid algorithm to evaluate the unknown bandwidth and quantile level. For this purpose, a sign distance measure was introduced for triangular fuzzy numbers. The proposed sign distance measure was also compared with a well-known sign distance frequently used in fuzzy environments. The proposed method was also compared with other fuzzy regular quantile regression models as well as some common fuzzy linear/nonlinear regression models in terms of popular goodness-of-fit measures. A simulation study was also conducted to evaluate the performance of the proposed method. Two applied examples were investigated using the proposed method, as well. Simulations and the applied examples indicated the better fit of the proposed fuzzy empirical quantile regression model with the data set as compared with the existing fuzzy quantile regression models and other fuzzy regression methods.
Digital Shoreline Analysis System (DSAS) is the most frequently used coastal engineering system for shoreline change quantification. Factors like human and system errors, wrong perception of the shoreline changes, and non-exact data sources may cause errors in the measured data. Detection and modification of such data can increase the accuracy of results. At present, the DSAS tool lacks this capability, so this research aimed to present a new module for DSAS to detect uncertain data in shoreline change rate measurements. The module’s basis for detecting uncertain data is to use statistical methods: adjusted boxplot, Grubbs’ test, standard deviation tests, median test, modified Z-score test, and voting method. The module’s performance was evaluated based on a data set obtained through Qeshm Island shoreline change quantification in Iran. The details of these methods, the prepared module, the case study, and the shoreline change measurement statistical methods were discussed in this study. The results showed the acceptable output of this module in detecting uncertain data.
One of the most famous equations that are widely used in various branches of physics, mathematics, financial markets, etc. is the Langevin equation. In this work, we investigate the existence of the solution for two generalized fractional hybrid Langevin equations under different boundary conditions. For this purpose, the problem of the existence of a solution will become the problem of finding a fixed point for an operator defined in the Banach space. To achieve the result, one of the recent fixed point techniques, namely the $ \alpha $-$ \psi $-contraction technique, will be used. We provide sufficient conditions to use this type of contraction in our main theorems. In the calculations of the auxiliary lemmas that we present, the Mittag-Leffler function plays a fundamental role. The fractional derivative operators used are of the Caputo type. Two examples are provided to demonstrate the validity of the obtained theorems. Also, some figures and a table are presented to illustrate the results.
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