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The current investigation focuses on the effect of different concentrations of green coffee bean powder (GCBp) on the physicochemical, microbiological, and sensory characteristics of whole wheat bread (WWB). C1 bread formulation (containing 1% GCBp) exhibited the highest loaf volume, suggesting optimal fermentation. Moisture analysis revealed minor alterations in the moisture retention attributes of the bread formulations. Impedance analysis suggested that C1 exhibited the highest impedance with a high degree of material homogeneity. Swelling studies suggested similar swelling properties, except C5 (containing 5% GCBp), which showed the lowest swelling percentage. Furthermore, color and microcolor analysis revealed the highest L* and WI in C1. Conversely, higher concentrations of GCBp reduced the color attributes in other GCBp-containing formulations. FTIR study demonstrated an improved intermolecular interaction in C1 and C2 (containing 2% GCBp) among all. No significant variation in the overall textural parameters was observed in GCBp-introduced formulations, except C2, which showed an improved gumminess. Moreover, the TPC (total phenolic content) and microbial analysis revealed enhanced antioxidant and antimicrobial properties in GCBp-incorporated formulations compared to Control (C0, without GCBp). The sensory evaluation showed an enhanced appearance and aroma in C1 compared to others. In short, C1 showed better physicochemical, biological, and sensory properties than the other formulations. [ABSTRACT FROM AUTHOR]

The power conversion efficiency of perovskite solar cells can be significantly improved if recombination losses and hysteresis effects, often caused by the presence of structural and chemical defects present at grain boundaries and interfaces, can be minimized during the processing of photoactive layers. As a crucial first step to address this issue, we performed density functional theory calculations to evaluate the electronic structure of the energetically favored (110) perovskite surface in the presence of the widely reported IPb antisite defects. Our calculations indicate that the nature of trap states formed is different for the perovskite surface with exposed methylammonium (MAI) and lead iodide (PbI2) terminating groups. While, in MAI terminated surfaces, IPb antisite defects lead to shallow states close to the valence band, both deep and shallow states are created in the bandgap region in the PbI2 terminated surface. Furthermore, we determined contribution from individual atoms to the trap states and inferred that the trap states originate from the clusters of iodine atoms that are formed near the defect site. The exact nature of the defect state is strongly correlated with the atomic structure of these clusters and can be potentially tuned by controlling the processing conditions of the perovskite film. [ABSTRACT FROM AUTHOR]

The Office of combination products OCP, an agency to regulate the combination products under the US Food and Drug Administration (FDA) has released the final guidance on the combination products for its approval which is named "Principles of Premarket Pathways for Combination Drugs," which provides the FDA's current strategies on the approval of combination products into the market. The final guideline, which is comparable to the draft notification issued in February 2019, emphasizes and specifies the five particular instances in which those techniques apply. [ABSTRACT FROM AUTHOR]

Myriad applications, including sensors and supercapacitors, employ substrates decorated with patterned carbon nanotubes (CNTs) in order to leverage the significant anisotropy in their properties. In the present study, a unique continuum mechanics based model was developed to predict the alignment and migration timescales of CNTs for realistic lab-scale electrophoretic deposition (EPD), which is a popular technique to create aligned deposits of pristine and functionalized CNTs without embedded catalysts. This model was initially validated based on results from molecular dynamics simulations to check for mutual consistency. EPD is a complex process that involves electrophoretic alignment and migration of CNTs towards the substrate, displacement of solvent molecules from the surface of substrate by overcoming an energy barrier, followed by deposition. We simulated —COOH functionalized CNTs of varying length under a range of applied electric fields (1 V/nm to 5 V/nm) to understand the mechanics of electrophoretic alignment and deposition. The dynamics of alignment and deposition were related to the molecular interactions between the various constituents by calculating friction parameters. The results from the parametric study, which is limited to length scales accessible to molecular dynamics simulations, was scaled up to CNTs of micrometer-scale length by comparing the results with solutions to the continuum scale model. The results indicate that the timescale for rotational alignment of realistic CNTs is of the order of seconds and several orders of magnitudes faster compared to the timescale for migration, which is of the order of thousands of seconds for a channel of diameter of 100 μm. [ABSTRACT FROM AUTHOR]

The molecular interactions between solvent and nanoparticles during photoactive layer formation in organic photovoltaic (OPV) cells influence the morphology of the photoactive layer and hence determine the power conversion efficiency. Prediction of optimal synthesis parameters in OPVs, such as choice of solvent, processing temperature, and nanoparticle concentration, requires fundamental understanding of the mechanisms that govern the agglomeration of nanoparticles in solvents. In this study, we used molecular dynamics simulations to simulate a commonly used organic nanoparticle, [6,6]-phenyl-C61-butyric acid methyl ester (PCBM), in various solvents to correlate solvent-nanoparticle interactions with the size of the agglomerate structure of PCBM. We analyzed the effects of concentration of PCBM and operating temperature on the molecular rearrangement and agglomeration of PCBM in three solvents: (i) toluene, (ii) indane, and (iii) toluene-indane mixture. We evaluated the agglomeration behavior of PCBM by determining sizes of the largest clusters of PCBM and the corresponding size distributions. To obtain further insight into the agglomerate structure of PCBMs, we evaluated radial distribution functions (RDFs) and coordination numbers of the various moieties of PCBMs with respect to solvent atoms as well as with respect to that of other PCBMs. Our simulations demonstrate that PCBMs form larger clusters in toluene while they are relatively dispersed in indane, which indicates the greater solubility of PCBM in indane than in toluene. In toluene-indane mixture, PCBMs are clustered to a greater extent than in indane and less than that in toluene. To correlate agglomerate size to nanoparticle-solvent interactions, we also evaluated the potential of mean force (PMF) of the fullerene moiety of PCBM in toluene and indane. Our results also show that the cluster size of PCBM molecules increases with the increase of concentration of PCBM and the processing temperature. To correlate the PCBM agglomeration with the dynamics of solvents, we evaluated the rotational correlation functions of the solvents. Our results illustrate that toluene relaxes faster than indane in the simulated systems and relaxation time of solvent molecules decreases with the decrease of concentration of PCBM and increase of processing temperature. Results presented in this study provide fundamental insight that can help to choose favorable solvents for processing PCBMs in OPV applications. [ABSTRACT FROM AUTHOR]

Glycine is an amino acid that has several applications in the pharmaceutical industry. Hence, growth of α-glycine crystals through solution crystallization is an important process. To gain a fundamental understanding of the seeded growth of α-glycine from aqueous solution, the (110) face of α-glycine crystal in contact with a solution of glycine in water has been simulated with molecular dynamics. The temporal change in the location of the interface of the α-glycine crystal seed has been characterized by detecting a density gradient. It is found that the α-glycine crystal dissolves with time at a progressively decreasing rate. Diffusion coefficients of glycine adjacent to (110) face of α-glycine crystal have been calculated at various temperatures (280, 285, 290, 295, and 300 K) and concentrations (3.6, 4.5, and 6.0 mol/l) and compared to that in the bulk solution. In order to gain a fundamental insight into the nature of variation in such properties at the interface and the bulk, the formation of hydrogen bonds at various temperatures and concentrations has been investigated. It is found that the nature of interaction between various atoms of glycine molecules, as characterized by radial distribution functions, can provide interesting insight into the formation of hydrogen bonds that in turn affect the diffusion coefficients at the interface. [ABSTRACT FROM AUTHOR]

We simulate unsteady nanoscale thermal transport at a solid-fluid interface by placing cooler liquid-vapor Ar mixtures adjacent to warmer Fe walls. The equilibration of the system towards a uniform overall temperature is investigated using nonequilibrium molecular dynamics simulations from which the heat flux is also determined explicitly. The Ar–Fe intermolecular interactions induce the migration of fluid atoms into quasicrystalline interfacial layers adjacent to the walls, creating vacancies at the migration sites. This induces temperature discontinuities between the solidlike interfaces and their neighboring fluid molecules. The interfacial temperature difference and thus the heat flux decrease as the system equilibrates over time. The averaged interfacial thermal resistance Rk,av decreases as the imposed wall temperature Tw is increased, as Rk,av∝Tw-4.8. The simulated temperature evolution deviates from an analytical continuum solution due to the overall system heterogeneity. [ABSTRACT FROM AUTHOR]

AbstractIn epidemiological cohort studies, the relative risk is a key measure to gauge the connection between two treatments or exposures. It quantifies the proportional change in the risk of disease due to the application of a specific treatment. However, the conventional methods for calculating relative risk, available in widely-used software, might yield inaccurate results when applied to correlated binary data from studies conducted over time or in clusters. Recently, various techniques have been proposed to estimate the risk ratio for correlated binary data. However, some methods exhibit a tradeoff between maintaining accurate coverage probability (CP) and ensuring an appropriate interval width or location. This paper introduces a new approach to confidently estimating the risk ratio using a hybrid method. This hybrid method combines two distinct confidence intervals (CIs) derived from single risk rates to establish a unified confidence interval for their ratio. Furthermore, we present a methodology to construct a confidence interval for the risk ratio, which builds upon established methods for correlated binary data. This extension incorporates principles such as the design effect and adequate sample sizes commonly used in representative sample surveys. An extensive simulation study is conducted to evaluate the effectiveness of these proposed methods. The performance of the methods is thoroughly examined in various scenarios. Additionally, the practicality of the proposed methods is showcased through three real-life examples. These examples involve comparing the side effects of low-dose tricyclic antidepressants with a placebo, assessing the efficacy of a treatment group in a teratological experiment, and evaluating the efficiency of active drugs in curing infections during clinical trials. [ABSTRACT FROM AUTHOR]