Anterior lamellar recession, blepharoplasty, and supratarsal fixation for cicatricial upper eyelid entropion without lagophthalmos

PurposeTo assess the results of anterior lamellar recession, blepharoplasty, and supratarsal fixation procedure in patients with upper eyelid cicatricial entropion without lagophthalmos.MethodsIn a prospective interventional case series, 52 eyelids (32 patients) were included (April 2009-December 2010). Excluded were patients with previous eyelid surgeries, lagophthalmos, and <12 months of follow-up. Using a microscope, after recessing anterior lamella 3-4 mm above the eyelid margin, it was fixed with 4-5 interrupted 6-0 vicryl sutures. Excess anterior lamella was then excised (blepharoplasty), supratarsal fixation sutures (6-0 vicryl) were put and the skin was closed with 6-0 nylon sutures. Success and failure defined based upon eyelash-globe touch on the last follow-up visit (at least 12 months), respectively.ResultsThere were 21 females (65.6) and 11 males (34.4) with a mean age of 69.7 years (SD=6.9) and mean follow-up of 21.06 months (SD=8.26). Success was observed in 39 (75) and failure in 13 (25). Mean time of failure was 4.5 months (SD=3). Although re-treatment with radio-frequency electrolysis (eight eyelids) and re-anterior lamellar recession (two eyelids) resulted in success in 12 eyelids with failure, two patients (three eyelids) declined further procedure. Except for thickened eyelid margin, no complications were observed.ConclusionAnterior lamellar recession, blepharoplasty, and supratarsal fixation procedure is an effective and safe technique for the treatment of the upper eyelid cicatricial entropion without lagophthalmos. © 2016 Macmillan Publishers Limited All rights reserved

Exploring Model Complexity in Machine Learned Potentials for Simulated Properties

Machine learning (ML) enables the development of interatomic potentials that promise the accuracy of first principles methods while retaining the low cost and parallel efficiency of empirical potentials. While ML potentials traditionally use atom-centered descriptors as inputs, different models such as linear regression and neural networks can map these descriptors to atomic energies and forces. This begs the question: what is the improvement in accuracy due to model complexity irrespective of choice of descriptors? We curate three datasets to investigate this question in terms of ab initio energy and force errors: (1) solid and liquid silicon, (2) gallium nitride, and (3) the superionic conductor LGPS. We further investigate how these errors affect simulated properties with these models and verify if the improvement in fitting errors corresponds to measurable improvement in property prediction. Since linear and nonlinear regression models have different advantages and disadvantages, the results presented herein help researchers choose models for their particular application. By assessing different models, we observe correlations between fitting quantity (e.g. atomic force) error and simulated property error with respect to ab initio values. Such observations can be repeated by other researchers to determine the level of accuracy, and hence model complexity, needed for their particular systems of interest

Correlated Terahertz phonon-ion interactions dominate ion conduction in solid electrolyte Li0.5La0.5TiO3

Ionic conduction in solids that exceeds 0.01 S/cm is predicted to involve collective phonon-ion interactions in the crystal lattice. Here, we use theory and experiment to measure the contribution of possible collective phonon-ion modes to Li+ migration in Li0.5La0.5TiO3. The ab initio calculations reveal that only a few phonon modes, mostly TiO6 rocking modes below 6 Terahertz, provide over 40% of the energy required for the Li+ hop in Li0.5La0.5TiO3. Laser-driving the TiO6 rocking modes decreases the measured impedance ten-fold compared to exciting acoustic and optical phonons at similar energy densities. The decreased impedance persists on thermalization timescales. These findings provide new insights on phonon-coupled ion migration mechanisms, material design rules, and the potential for metastable states for opto-ionic materials

Review on superglue eye injuries è¶ å¼ºå��è�¶ç�¼é�¨æ��伤ç��ç �究è¿�å±�

The purpose of this study is to run a review on possible superglue injuries to the eye. In this review, previous papers regarding the harmful impacts of superglue were systematically studied. Superglue eye injuries have been common during the three last decades and most of them were accidental and preventable by introducing safety issues and although it may be toxic for the tissues, it is not associated with long term morbidity. This paper addresses the management of superglue injuries and shows the importance of the prevention of ocular superglue injuries. Copyright 2020 by the IJO Press

Topography-guided vs wavefront-optimized surface ablation for myopia using the wavelight platform: A contralateral eye study

PURPOSE: To compare treatments with wavefrontoptimized and topography-guided ablations. METHODS: This prospective, randomized, contralateral study comprised 40 eyes (20 patients) with low to moderate myopia with or without astigmatism that underwent topography-guided photorefractive keratectomy (PRK) (ALLEGRO Topolyzer, Alcon Laboratories Inc) in one eye and wavefront-optimized PRK (ALLEGRETTO WAVE software version 2.020 default treatment, Alcon Laboratories Inc) in the fellow eye. Visual acuity, refractive error, contrast sensitivity, and Orbscan (Bausch & Lomb) 3- and 5-mm corneal irregularities were measured preoperatively and 3 and 6 months postoperatively. The results were compared between the two eyes. RESULTS: In both groups, preoperative corrected distance visual acuity (CDVA) (0.03-0.09 logMAR for topography-guided and 0.01±0.06 logMAR for wavefront-optimized P=.1), 3-month postoperative uncorrected distance visual acuity (UDVA) (-0.01±0.03 logMAR for topography-guided and -0.01±0.03 logMAR for wavefront-optimized P=.4), and 6-month postoperative UDVA (0.01±0.03 logMAR for topography-guided and 0.0±0.01 logMAR for wavefront-optimized P=.3) were the same. All wavefront-optimized and 18 (90%) topography-guided eyes had UDVA of 20/20 or better. No signifi cant differences were noted between groups in pre- and postoperative spherical and cylindrical refractive errors or corneal irregularity and contrast sensitivity measurements. Six months postoperatively, contrast sensitivity values at 3, 6, 12, and 18 cycles/degree were 5.7±0.7, 6.0±1.5, 6.1±1.3, and 5.5±1.5, respectively, in the topography-guided group, and 6.2±0.6, 6.4±1.2, 6.4±1.1, and 5.8±1.3, respectively, in the wavefront-optimized group (P=.3, P=.5, P=.4, and P=.6, respectively). CONCLUSIONS: Using the WaveLight excimer laser platform for PRK, CDVA and contrast sensitivity outcomes were statistically similar between the wavefront-optimized and topography-guided ablations in eyes with low to moderate myopia with and without astigmatism. Copyright © SLACK Incorporated

Exploring model complexity in machine learned potentials for simulated properties

Abstract Machine learning (ML) enables the development of interatomic potentials with the accuracy of first principles methods while retaining the speed and parallel efficiency of empirical potentials. While ML potentials traditionally use atom-centered descriptors as inputs, different models such as linear regression and neural networks map descriptors to atomic energies and forces. This begs the question: what is the improvement in accuracy due to model complexity irrespective of descriptors? We curate three datasets to investigate this question in terms of ab initio energy and force errors: (1) solid and liquid silicon, (2) gallium nitride, and (3) the superionic conductor Li $$_{10}$$ 10 Ge(PS $$_{6}$$ 6 ) $$_{2}$$ 2 (LGPS). We further investigate how these errors affect simulated properties and verify if the improvement in fitting errors corresponds to measurable improvement in property prediction. By assessing different models, we observe correlations between fitting quantity (e.g. atomic force) error and simulated property error with respect to ab initio values. Graphical abstrac

Lamellar Ionenes with Highly Dissociative, Anionic Channels Provide Lower Barriers for Cation Transport

Solid polymer electrolytes have the potential to enable safer and more energy-dense batteries; however, a deeper understanding of their ion conduction mechanisms, and how they can be optimized by molecular design, is needed to realize this goal. Here, we investigate the impact of anion dissociation energy on ion conduction in solid polymer electrolytes via a novel class of ionenes prepared using acyclic diene metathesis (ADMET) polymerization of highly dissociative, liquid crystalline fluorinated aryl sulfonimide-tagged (“FAST”) anion monomers. These ionenes with various cations (Li+, Na+, K+, and Cs+) form well-ordered lamellae that are thermally stable up to 180 °C and feature domain spacings that correlate with cation size, providing channels lined with dissociative FAST anions. Electrochemical impedance spectroscopy (EIS) and differential scanning calorimetry (DSC) experiments, along with nudged elastic band (NEB) calculations, suggest that cation motion in these materials operates via an ion-hopping mechanism. The activation energy for Li+ conduction is 59 kJ/mol, which is among the lowest for systems that are proposed to operate via an ion conduction mechanism that is decoupled from polymer segmental motion. Moreover, the addition of a cation-coordinating solvent to these materials led to a >1000-fold increase in ionic conductivity without detectable disruption of the lamellar structure, suggesting selective solvation of the lamellar ion channels. This work demonstrates that molecular design can facilitate controlled formation of dissociative anionic channels that translate to significant enhancements in ion conduction in solid polymer electrolytes