Development of a pH-responsive imprinted polymer for diclofenac and study of its binding properties in organic and aqueous media

Three different molecularly imprinted polymers (MIPs) for drug delivery of diclofenac in gastrointestinal tract were synthesized employing bulk polymerization method and their binding and release properties were studied in different pH values. Methacrylic acid (MAA), methacrylamide (MAAM) and 4-vinyl pyridine (4VP) were tested as functional monomers and ethylene glycole dimethacrylate (EDMA) was used as a cross-linker monomer in polymeric feed. Binding properties and imprinting factor (IF) of MIPs were studied in comparison with their non-imprinted ones (Blank) in organic and aqueous media. Diclofenac release in aqueous solvents at pH values of 1.5, 6.0 and 8.0, simulating gastrointestinal fluids, were also studied. The results indicated the specific binding of diclofenac to imprinted polymers. Duo to the stronger non-specific bounds in aqueous solutions, IF values decreased in water compared to acetonitrile as an organic medium. Our results proved that all polymers represented pH-responsive diclofenac delivery at above conditions. The data showed that imprinted polymer, prepared by MAA had superior properties, in comparison with other polymers, for minimum release (14%) of drug in gastric acid and maximum release (90%) in basic condition. The results indicated that diclofenac imprinted polymer could be used as a pH-responsive matrix in preparation of a new drug delivery system for diclofenac.     

Qualitative and quantitative analysis of natural light in the dome of San Lorenzo,Turin

The Church of San Lorenzo in Turin, which was designed by the Theatine architect Guarino Guarini in the 17^th century, is among the most famous Christian Baroque architectural masterpieces. Guarini was given freedom to plan and design this church, which can be considered his most innovative and influential work. The most significant feature of this building is its dome, which is magnificent and slightly different from what is expected from a Baroque church. The dome of San Lorenzo has been the subject of considerable research due to its perforated surface that allows daylight to penetrate into the interior space. However, this dome has been mostly described through mere observation in a poetic and mystical manner. Although a subjective analysis is vital in understanding this architectural piece, a systematic and objective analysis that includes numerical data is required to understand fully the illumination by natural light present in this work of architecture. This paper presents a method based on high-dynamic-range-imaging luminance analysis that employs a quantitative luminous measurement technique to analyze the daylight behaviorin San Lorenzo. The first section of this paper investigates the subjective experience in the dome hall, and the last two sections objectively show the dome functions and the manner through which the design of Guarini creates various light values in different parts of the dome. Such a design is responsible for the unique experience in the dome hall.     

Effect of Titanium Addition on As Cast Structure and Macrosegregation of High‐Carbon High‐Chromium Steel

In casting heavy ingots of high‐chromium high‐carbon cold work steels, macrosegregation develops in the center of the ingot, causing difficulties during subsequent hot working. Heat transfer and solidification of an industrial scale high‐carbon high‐chromium steel ingot was simulated and thereafter a laboratory scale representative ingot was designed to model the solidification of the industrial scale ingot. Titanium in the range of 0.3–1% was added to the high‐chromium high‐carbon (12%Cr–2%C) steel during melting process. Microstructures, macrosegregation and phase formations were studied using optical microscopy, scanning electron microscopy, energy dispersive X‐ray spectrometry, wave dispersive X‐ray spectrometry, optical emission spectroscopy, and X‐ray diffraction. Addition of 0.3% titanium was sufficient to diminish the macrosegregation; however it did not have a significant effect on the grain size. Addition of 0.7 and 1% titanium had a substantial effect on grain size in the longitudinal direction and refined the primary carbides structure. The formation of small TiC carbides that precipitated before solidification of liquid iron acted as nuclei for primary pro‐eutectic austenite grains.     

Ranking of design scenarios of TMD for seismically excited structures using TOPSIS

In this paper, design scenarios of a tuned mass damper (TMD) for seismically excited structures are ranked. Accordingly, 10 design scenarios in two cases, namely unconstrained and constrained for the maximum TMD, are considered in this study. A free search of the TMD parameters is performed using a particle swarm optimization (PSO) algorithm for optimum tuning of TMD parameters. Furthermore, nine criteria are adopted with respect to functional, operational, and economic views. A technique for order performance by similarity to ideal solution (TOPSIS) is utilized for ranking the adopted design scenarios of TMD. Numerical studies are conducted on a 10-story building equipped with TMD. Simulation results indicate that the minimization of the maximum story displacement is the optimum design scenario of TMD for the seismic-excited structure in the unconstrained case for the maximum TMD stroke. Furthermore, H₂ of the displacement vector of the structure exhibited optimum ranking among the adopted design scenarios in the constrained case for the maximum TMD stroke. The findings of this study can be useful and important in the optimum design of TMD parameters with respect to functional, operational, and economic perspectives.     

VAD Based on Kernel Smoothed Function of EGARCH Models

An algorithm for a voice activity detector (VAD) is proposed. It is based on the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) filter for generalized hyperbolic (GH), Gaussian random variables, adaptive threshold values and autocorrelation coefficients. EGARCH models are a new variation of GARCH models used especially in economic time series. A speech signal is assumed to have a GH because GH has heavier tails than the Gaussian distribution (GD) covering other heavy tailed distributions like hyperbolic, skewed $t$ , variance gamma (VG), inverse Gaussian (NIG), Cauchy, Student’s $t$ and Laplace distributions. The distribution of noise signal is assumed to be uncorrelated (white noise), but in general, that is not necessary. In the proposed method, heteroscedasticity is modeled by EGARCH. A kernel smoothed function of conditional variances and autocorrelations generate the soft detection vector. Finally, hard detection is the result of comparing the soft detection vector with an adaptive threshold value. The simulation results show that the proposed VAD is able to operate down to $-5$  dB.     

Remineralization effects of self-assembling peptide P11-4 associated with three materials on early enamel carious lesions: An in vitro study

The aim of this study was to assess the remineralization of enamel caries lesions using the self-assembling peptide P₁₁-4 associated with different materials. Artificial early enamel lesions were prepared on 154 primary teeth. The samples were randomly divided into eight groups: (1) control, (2) P₁₁-4, (3) fluoridate toothpaste (FT), (4) P₁₁-4 + FT, (5) casein phosphopeptide–amorphous calcium phosphate (CPP–ACP), (6) P₁₁-4 + CPP–ACP, (7) fluoridate bioactive glass toothpaste (BT), and (8) P₁₁-4 + BT. The surface enamel microhardness (EMH) and energy-dispersive X-ray spectroscopy (EDS) of the teeth were then measured at the baseline, after demineralization, and after 28 days of remineralization. The enamel surfaces were assessed by field emission scanning electron microscopy (FESEM) and atomic force microscopy (AFM). The data were analyzed with one-way analysis of variance (ANOVA) (p < .05). EMH after demineralization was significantly lower than the baseline value (p < .001). The interventions led to an enhanced percentage of EMH recovery (%REMH), which was higher in Groups 6 and 7. There was no significant difference between Groups 3 and 4. Groups 1 and 2 had the lowest %REMH. The mean calcium/phosphate weight percentage ratio of P₁₁-4 was significantly lower than the others (p < .001). The FESEM and AFM images revealed mineral deposition on the eroded enamel and reductions in surface roughness in Groups 5 and 7.     

Does Density Aggravate the COVID-19 Pandemic?

Abstract

Problem, research strategy, and findings: The impact of density on emerging highly contagious infectious diseases has rarely been studied. In theory, dense areas lead to more face-to-face interaction among residents, which makes them potential hotspots for the rapid spread of pandemics. On the other hand, dense areas may have better access to health care facilities and greater implementation of social distancing policies and practices. The current COVID-19 pandemic is a perfect case study to investigate these relationships. Our study uses structural equation modeling to account for both direct and indirect impacts of density on the COVID-19 infection and mortality rates for 913?U.S. metropolitan counties, controlling for key confounding factors. We find metropolitan population to be one of the most significant predictors of infection rates; larger metropolitan areas have higher infection and higher mortality rates. We also find that after controlling for metropolitan population, county density is not significantly related to the infection rate, possibly due to more adherence to social distancing guidelines. However, counties with higher densities have significantly lower virus-related mortality rates than do counties with lower densities, possibly due to superior health care systems.

Takeaway for practice: These findings suggest that connectivity matters more than density in the spread of the COVID-19 pandemic. Large metropolitan areas with a higher number of counties tightly linked together through economic, social, and commuting relationships are the most vulnerable to the pandemic outbreaks. They are more likely to exchange tourists and businesspeople within themselves and with other parts, thus increasing the risk of cross-border infections. Our study concludes with a key recommendation that planners continue to advocate dense development for a host of reasons, including lower death rates due to infectious diseases like COVID-19.     

Liquefaction assessment using microtremor measurement,conventional method and artificial neural network (Case study: Babol,Iran)

Recent researchers have discovered microtremor applications for evaluating the liquefaction potential. Microtremor measurement is a fast, applicable and cost-effective method with extensive applications. In the present research the liquefaction potential has been reviewed by utilization of microtremor measurement results in Babol city. For this purpose microtremor measurements were performed at 60 measurement stations and the data were analyzed by suing Nakmaura’s method. By using the fundamental frequency and amplification factor, the value of vulnerability index (K _g ) was calculated and the liquefaction potential has been evaluated. To control the accuracy of this method, its output has been compared with the results of Seed and Idriss [1] method in 30 excavated boreholes within the study area. Also, the results obtained by the artificial neural network (ANN) were compared with microtremor measurement. Regarding the results of these three methods, it was concluded that the threshold value of liquefaction potential is K _g = 5. On the basis of the analysis performed in this research it is concluded that microtremors have the capability of assessing the liquefaction potential with desirable accuracy.