Album: Two Editorials

Abstract

There is good reason to be curious about modern creative photography in England. There has been very little .... Robert M. Doty, Infinity     

Recent Developments in Drug Delivery to Prolong Allograft Survival in Lung Transplant Patients

Since the discovery of cyclosporine in 1971, calcineurin inhibitors have played a critical role in the therapeutic suppression of the immune response. Patients receiving solid organ transplants rely heavily on these medications to prevent the acute and chronic rejection of allografted tissue. These therapies can prove difficult because of potential toxicity, heightened risk of invasive infection, and erratic oral bioavailability, requiring frequent blood samples for monitoring of systemic levels. Added challenges are presented in immunosuppression of lung transplant patients owing to the increased susceptibility to invasive infection and extensive immune mechanisms inherent in lung tissue. With the introduction of tacrolimus, a more potent calcineurin inhibitor, clinical outcomes of transplants have continued to improve; however, little improvement has been noted in lung transplantation. While very effective upon arrival at the site of action, tacrolimus and cyclosporine present a variety of formulation challenges such as poor solubility, potential systemic toxicity, and extensive first pass metabolism. Initial attempts to improve solubility in both oral and intravenous formulations have resulted in variable drug absorption and increased systemic toxicity, respectfully, creating a need for formulation improvement. Through alternative routes of delivery and novel formulation techniques, researchers have addressed these issues and, in some cases, demonstrated improved clinical outcomes. Through enhanced solubilization, reduction in absorption variability, and more effective drug targeting with reduced systemic levels, improvements in outcomes and overall patient survival in lung and other solid organ transplantation can be expected.     

Microstructure and elastic tensile behavior of polyethylene terephthalate-exfoliated graphene nanocomposites

Polyethylene terephthalate-exfoliated graphene nanocomposites were prepared by injection molding. Nanocomposites with graphene platelets of 2, 5, 10, and 15% weight fractions were molded and tested for mechanical characterization. Transmission electron microscopy imaging along with X-ray diffraction show that the graphene platelets remained intact and were dispersed into the matrix. An exponential increase in the Young’s modulus of the nanocomposites was observed, but with current limits on exfoliation they do not yet reach the potential suggested by idealized predictions.     

Conjugate-order systems for signal processing: stability, causality, boundedness, compactness

The fundamental system theory is presented for a class of real systems whose derivative order is complex. It is demonstrated that these so-called conjugate-order systems have a scale-invariance property in both the time and frequency domains, which makes them useful for describing certain phenomena in continuous media. The conditions for which these systems are guaranteed to be causal and stable are reviewed. The compactness properties of their Hankel operators, which allow them to admit finite-order approximations, are also discussed. A procedure is developed for choosing appropriate transfer-function parameter values to design a stable conjugate-order system whose frequency response meets given bandwidth, resonance, and ripple specifications.     

Photoactive Earth‐Abundant Iron Pyrite Catalysts for Electrocatalytic Nitrogen Reduction Reaction

The generation of ammonia, hydrogen production, and nitrogen purification are considered as energy intensive processes accompanied with large amounts of CO₂ emission. An electrochemical method assisted by photoenergy is widely utilized for the chemical energy conversion. In this work, earth‐abundant iron pyrite (FeS₂) nanocrystals grown on carbon fiber paper (FeS₂/CFP) are found to be an electrochemical and photoactive catalyst for nitrogen reduction reaction under ambient temperature and pressure. The electrochemical results reveal that FeS₂/CFP achieves a high Faradaic efficiency (FE) of ≈14.14% and NH₃ yield rate of ≈0.096 µg min^?1 at ?0.6 V versus RHE electrode in 0.25 m LiClO₄. During the electrochemical catalytic reaction, the crystal structure of FeS₂/CFP remains in the cubic pyrite phase, as analyzed by in situ X‐ray diffraction measurements. With near‐infrared laser irradiation (808 nm), the NH₃ yield rate of the FeS₂/CFP catalyst can be slightly improved to 0.1 µg min^?1 with high FE of 14.57%. Furthermore, density functional theory calculations demonstrate that the N₂ molecule has strong chemical adsorption energy on the iron atom of FeS₂. Overall, iron pyrite‐based materials have proven to be a potential electrocatalyst with photoactive behavior for ammonia production in practical applications.     

Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

Effect of iron alloying in evolution of nanostructure and microstructural stability in nickel

Nanocrystalline materials show many interesting properties such as high strength and hardness due to nanosized grains and high density of interfaces. In this context, the present work reports the effect of Fe (iron) addition in Ni (nickel) on nanostructure retention during the annealing of Ni-Fe alloy (with 0, 18.5, 28.5 and 43 wt% Fe) at 450 °C for 16 h. Furthermore, effect of annealing on the deformation mechanism was investigated. The integral breadth method revealed the decrease in grain size with increase in wt% Fe in Ni. The strain rate sensitivity exponent which is a signature of operating deformation mechanism showed a higher value (0.10803) in case of Ni-18.5 wt% Fe during nanoindentation. However, Ni-0 wt% Fe, Ni-28.5 wt% Fe and Ni-43 wt% Fe were characterized by a relatively low strain rate sensitivity exponent (between 0.02069 and 0.10803). Results indicated the presence of Hall-Petch relationship up to 18.5 wt% Fe and inverse Hall-Petch relationship above 18.5 wt% Fe.     

Symmetry building Monte Carlo-based crystal structure prediction

Methods are presented that allow for the automatic increase and preservation of symmetry during global optimization of crystal structures. This systematic building of symmetry allows for its incorporation into structure prediction simulations even when the space group information is not known a priori. It is shown that simulations that build and maintain symmetry converge much more rapidly to ground state crystal structures than when symmetry is ignored, allowing for the treatment of unit cells much larger than would otherwise be possible, especially when beginning from the P1 space group.