Low vision devices for age-related macular degeneration: a systematic review.

PURPOSE: Age-related macular degeneration (AMD) is a degenerative condition impacting central vision. Evaluating the effectiveness of low vision devices provides empirical evidence on how devices can rehabilitate and overcome deficits caused by AMD. This evidence could help to facilitate discussion on necessary future improvements to vision enhancement technology. METHODS: A systematic review of the literature was conducted on low vision device use in AMD populations. Relevant peer-reviewed research articles from six databases were screened. RESULTS: The findings of thirty-five studies revealed a significant positive impact of low vision devices leading to improvements in visual acuity, reading performance, facial recognition, and more. While the studies were found to have moderate risks of bias, a GRADE assessment of the evidence suggested the certainty of the evidence was low-moderate. DISCUSSION: Simple hand-held low vision devices (e.g., magnifiers) appear to currently have greater preferential support than newer visual enhancement technology (e.g., head mounted devices). Financial, comfort or usability reasons may influence preferences more than performance-based findings. However, there is a lack of studies examining newer technologies in AMD populations, which future research should address. Moreover, given the presence of bias across the studies and limited controlled experiments, confidence in the results may be low. CONCLUSIONS: Most studies indicated that low vision devices have positive impacts on reading and visual performance. But, even though they are reported to be a valuable asset to AMD populations, more rigorous research is required to draw conclusive evidence. IMPLICATIONS FOR REHABILITATIONLow vision devices can improve patient outcomes (e.g., vision, reading ability) for age-related macular degeneration populations.A multidisciplinary combination of low vision devices and rehabilitative services (i.e., eccentric viewing training, counselling, education) may enhance quality of life.

Protonation-Induced Microphase Separation in Thin Films of a Polyelectrolyte-Hydrophilic Diblock Copolymer.

Block copolymers composed of poly(oligo ethylene glycol methyl ether methacrylate) and poly(2-vinylpyridine) are disordered in the neat state but can be induced to order by protonation of the P2VP block, demonstrating a tunable and responsive method for triggering assembly in thin films. Comparison of protonation with the addition of salts shows that microphase separation is due to selective protonation of the P2VP block. Increasing acid incorporation and increasing 2-vinylpyridine content for P2VP minority copolymers both promote increasingly phase-separated morphologies, consistent with protonation increasing the effective strength of segregation between the two blocks. The self-assembled nanostructures formed after casting from acidic solutions may be tuned based on the amount and type of acid incorporation as well as the annealing treatment applied after casting, where both aqueous and polar organic solvents are shown to be effective. Therefore, POEGMA-b-P2VP is a novel ion-containing block copolymer whose morphologies can be facilely tuned during casting and processing by controlling its exposure to acid.

Simultaneous modeling and optimization of nonlinear simulated moving bed chromatography by the prediction-correction method.

This work demonstrates a systematic prediction-correction (PC) method for simultaneously modeling and optimizing nonlinear simulated moving bed (SMB) chromatography. The PC method uses model-based optimization, SMB startup data, isotherm model selection, and parameter estimation to iteratively refine model parameters and find optimal operating conditions in a matter of hours to ensure high purity constraints and achieve optimal productivity. The PC algorithm proceeds until the SMB process is optimized without manual tuning. In case studies, it is shown that a nonlinear isotherm model and parameter values are determined reliably using SMB startup data. In one case study, a nonlinear SMB system is optimized after only two changes of operating conditions following the PC algorithm. The refined isotherm models are validated by frontal analysis and perturbation analysis.