Optical Photographs Research Articles

Prevalence and associations of parapapillary scleral ridges: the Beijing Eye Study

PurposeTo explore the prevalence and associated factors of parapapillary scleral ridges (PSRs).MethodsOut of the cohort of the population-based Beijing Eye Study (n=3468 participants), the study included all eyes with an...

Synergistic improvement of the compression-after-impact performance of composite laminates by multi-scale CNF/Z-pin reinforcement

This paper investigated the effects of carbon nanofibers (CNF), Z-pin, and multi-scale CNF/Z-pin on the compression-after-impact (CAI) properties and damage morphology of laminates after 10 J, 30 J, and 50 J impact. The deformation and strain field variations of the laminate during the CAI process were clearly characterized by 3D-Digital Image Correlation (DIC). The process from local buckling to the global failure of the laminate was clearly revealed. The mechanical response results showed that the CAI strength of unreinforced, CNF, Z-pin and CNF/Z-pin-reinforced laminates increased in order after impact with the same energy. After 50 J impact, the CAI strength of CNF, Z-pin and CNF/Z-pin-reinforced laminates was increased by 18.6 %, 28.7 % and 36.4 %, respectively, compared to unreinforced laminates. By constructing a simulation model to analyze damage and mechanical response, the model's effectiveness was verified. Additionally, the damage morphology, damage mechanism, and synergistic toughening mechanism between CNF and Z-pin in CAI specimens were revealed from optical photographs and scanning electron microscopy (SEM).

Synergistically improving the edge-on impact damage resistance of composite laminates using multi-scale CNF/Z-pin toughening

Edge-on impact damage of composite structures has drawn significant attention from the engineering and academic communities because of the much more notorious damage caused than that by out-of-plane impacts. However, research focusing on improving the edge-on impact resistance of these structures has been limited. This paper proposed a synergistic toughening approach involving multi-scale carbon nanofiber (CNF) and Z-pin to improve the composite laminates' edge-on impact damage resistance. Through analysis of mechanical response, C-scan, optical and Scanning electron microscopy (SEM) photographs of unreinforced, CNF-reinforced, Z-pin-reinforced and CNF/Z-pin-reinforced laminates, the failure mechanisms of the four types of laminates and the synergistic toughening mechanism of CNF/Z-pin were revealed. The results show that the synergistic toughening of CNF/Z-pin could weaken the negative effects caused by Z-pin implantation and that CNF has the potential to increase the damage initiation energy threshold of the laminate. Furthermore, the toughening effect of Z-pin was significantly greater than that of CNF in damage propagation. Specifically, at 50 J impact energy, the damage area of CNF/Z-pin, Z-pin and CNF-reinforced laminates was reduced by 50.5 %, 39.8 %, and 8.3 %, respectively, compared to unreinforced laminates.

GENETIC FACTORS AND CHARACTERISTICS ON SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHY ARE ASSOCIATED WITH CHOROIDAL THICKNESS IN ABCA4 -RELATED RETINOPATHY.

To investigate the possible correlation factors of choroidal thickness in ABCA4 -related retinopathy. A total of 66 patients were included in the cohort. It is a retrospective, cross-sectional laboratory investigation. The patients were tested using whole-exon sequencing and ophthalmic examinations, including slit-lamp examinations, best-corrected visual acuity, spectral-domain optical coherence tomography, fundus photograph, and fundus autofluorescence. Besides demographic characteristics (age, onset age, duration), we selected genetic factors and ocular characteristics on spectral-domain optical coherence tomography as the candidates related to choroidal thickness. Mutation type (inframe mutation or premature termination codon), epiretinal membrane, retinal pigment epithelium- Bruch membrane integrity, and macular curvature changes were identified as related factors to choroidal thickness in ABCA4 -related retinopathy after the adjustment of Logistic LASSO regression. Mutation type, epiretinal membrane, retinal pigment epithelium-Bruch membrane integrity, and macular curvature changes are related factors to choroidal thinning. These findings could provide us a further understanding for the pathological process and clinical features of ABCA4 mutation.

Enhancing the outline sharpness of crosslinked printed cotton fabrics using ethylene glycol diglycidyl ether

AbstractIn the current study, to obtain environmentally friendly printed cotton fabrics with a clear contour edge, ethylene glycol diglycidyl ether (EGDE) as a crosslinking agent and guar gum as a thickener were used with natural madder dye. The solid content of the thickener was assessed to determine the optimal viscosity of the printing paste. Scanning electron microscopy images and colour depth (K/S) values were used to analyse the surface morphology and printing properties. The pattern outline of the printed cotton fabric was assessed with an optical microscope. Also, the overall fastness properties of the printed fabrics were evaluated. The results showed that when the solid content of guar gum was 2.5%, the viscosity of the printing paste was close to 10 000 mPa.s, which was suitable for printing cotton fabrics. Scanning electron microscopy analysis showed that most of the printing paste was removed during the washing process, and did not affect the microstructure of the cotton fabric. Compared with direct printed cotton fabrics, the K/S values of mordant and crosslinked printed cotton fabrics increased by 3.12 and 4.01, respectively. In the optical microscopy photographs, the mordant and crosslinked printed cotton fabrics displayed a clear outline sharpness of the printed pattern, and excellent printed products were obtained. The colour fastness to washing, rubbing and light of the crosslinked printed cotton fabric were significantly improved, reaching levels of 4‐5.

Predicting visual acuity with machine learning in treated ocular trauma patients.

To predict best-corrected visual acuity (BCVA) by machine learning in patients with ocular trauma who were treated for at least 6mo. The internal dataset consisted of 850 patients with 1589 eyes and an average age of 44.29y. The initial visual acuity was 0.99 logMAR. The test dataset consisted of 60 patients with 100 eyes collected while the model was optimized. Four different machine-learning algorithms (Extreme Gradient Boosting, support vector regression, Bayesian ridge, and random forest regressor) were used to predict BCVA, and four algorithms (Extreme Gradient Boosting, support vector machine, logistic regression, and random forest classifier) were used to classify BCVA in patients with ocular trauma after treatment for 6mo or longer. Clinical features were obtained from outpatient records, and ocular parameters were extracted from optical coherence tomography images and fundus photographs. These features were put into different machine-learning models, and the obtained predicted values were compared with the actual BCVA values. The best-performing model and the best variable selected were further evaluated in the test dataset. There was a significant correlation between the predicted and actual values [all Pearson correlation coefficient (PCC)>0.6]. Considering only the data from the traumatic group (group A) into account, the lowest mean absolute error (MAE) and root mean square error (RMSE) were 0.30 and 0.40 logMAR, respectively. In the traumatic and healthy groups (group B), the lowest MAE and RMSE were 0.20 and 0.33 logMAR, respectively. The sensitivity was always higher than the specificity in group A, in contrast to the results in group B. The classification accuracy and precision were above 0.80 in both groups. The MAE, RMSE, and PCC of the test dataset were 0.20, 0.29, and 0.96, respectively. The sensitivity, precision, specificity, and accuracy of the test dataset were 0.83, 0.92, 0.95, and 0.90, respectively. Predicting BCVA using machine-learning models in patients with treated ocular trauma is accurate and helpful in the identification of visual dysfunction.

Self-supervised anomaly detection, staging and segmentation for retinal images.

Unsupervised anomaly detection (UAD) is to detect anomalies through learning the distribution of normal data without labels and therefore has a wide application in medical images by alleviating the burden of collecting annotated medical data. Current UAD methods mostly learn the normal data by the reconstruction of the original input, but often lack the consideration of any prior information that has semantic meanings. In this paper, we first propose a universal unsupervised anomaly detection framework SSL-AnoVAE, which utilizes a self-supervised learning (SSL) module for providing more fine-grained semantics depending on the to-be detected anomalies in the retinal images. We also explore the relationship between the data transformation adopted in the SSL module and the quality of anomaly detection for retinal images. Moreover, to take full advantage of the proposed SSL-AnoVAE and apply towards clinical usages for computer-aided diagnosis of retinal-related diseases, we further propose to stage and segment the anomalies in retinal images detected by SSL-AnoVAE in an unsupervised manner. Experimental results demonstrate the effectiveness of our proposed method for unsupervised anomaly detection, staging and segmentation on both retinal optical coherence tomography images and color fundus photograph images.

Strong, Ultrastretchable Hydrogel‐Based Multilayered Soft Actuator Composites Enhancing Biologically Inspired Pumping Systems

Adv. Eng. Mater 2021, 23, 2100121 10.1002/adem.202100121 After publication there are a few corrections that haven't been carried: Abstract Section: The HEAP-sandwiched layer embracing hydrogel-based ionotronics presents 2205% ultimate strain and sustains compressive stress of 632 kPa. Adding second affiliation for Dr. A. Jusufi: ETH Center for Learning Systems Max-Planck-Ring 4, 72076 Tübingen, Germany Figure 1 caption: b) (I)_(II) Multilayered soft actuator composite with ionogel sandwiched with actuation physics. (III) Composite planar membrane's optical photograph with carbon grease electrode (black) that connects with the copper tape for electroactuation. (IV) Scanning electron microscopy (SEM) of freeze-dried ionogel demonstrating porous surface. Page 5 right column: … 100th, 500th, and the 1000th cycle, respectively. Correction Figure 4(a) caption: 10 kV, 12kV, 14kV, 16kV, 18kV The correct version of Figure 4: Page 7 left column: adding Figure 6 b): Potential applications of the HEAP-based biologically informed pumping systems include cardiovascular and renal assistive devices, and testing of compatibility via animal models (Figure 6 (a,b)). We apologize for any inconvenience caused.

The future application of artificial intelligence and telemedicine in the retina: A perspective.

The development of artificial intelligence (AI) and deep learning provided precise image recognition and classification in the medical field. Ophthalmology is an exceptional department to translate AI applications since noninvasive imaging is routinely used for the diagnosis and monitoring. In recent years, AI-based image interpretation of optical coherence tomography and fundus photograph in retinal diseases has been extended to diabetic retinopathy, age-related macular degeneration, and retinopathy of prematurity. The rapid development of portable ocular monitoring devices coupled with AI-informed interpretations allows possible home monitoring or remote monitoring of retinal diseases and patients to gain autonomy and responsibility for their conditions. This review discusses the current research and application of AI, telemedicine, and home monitoring devices on retinal disease. Furthermore, we propose a future model of how AI and digital technology could be implemented in retinal diseases.

Critical role of water in fused silica glass by silica nanopowder sintering: Nanoparticle dispersion

Thermoplastic nanocomposite preparation using a silica nanopowder/polyethylene glycol (PEG) / polyvinyl butyral (PVB) system followed by heat-treatment sintering to obtain fused silica glass has high precision, scalable manufacturing processes, and short processing time. However, conventional solvents are toxic and harmful to the environment, and for this reason, the ethanol/water solvent system was proposed in this study. In this study, the effect of water content on the dispersion effect of nano-silica suspensions was investigated through particle size and zeta potential tests and FTIR spectra analysis; in addition, the study proposes a dispersion theory based on the solvation layer of the ethanol/water competitive adsorption and viscosity effect. Finally, optical photographs and SEM characterization showed that the obtained fused silica glass was transparent and had no seam defects, and the XRD and hydroxyl group tests showed that the glass had a low hydroxyl group content of only 2.55 ppm.

To study the association of dyslipidemia with macular edema and hard exudates in diabetic maculopathy in an industrial hospital in Chhattisgarh

To study the affect of LDL cholestrol, HDL cholestrol and triglycerides with diabetic maculopathy in type 2 diabetic patients.An informed written consent was obtained in every case.A 5ml blood sample was withdrawn. All the patients detailed history, general physical examination and ocular examination including visual acuity, intraocular pressure by applanation tonometry, slit lamp examination and fundus examination by biomicroscopy were done. Optical coherence tomography and fundus photograph were also taken.Patients who were having diabetic retinopathy had higher values of LDL and total cholestrol as compared to those who were not having diabetic retinopathy.Patients who were having diabetic retinopathy changes had non-significant differences in the level of HDL and triglycerides as compared to those who were not having diabetic retinopathy changes.Patients with changes of diabetic retinopathy had significantly higher values of foveal thickness as compared to those without changes of diabetic retinopathy. Foveal thickness had correlation with total cholesterol levels.

Clinical Features of Post Fever Retinitis and Visual Outcomes with Oral Corticosteroids: A Retrospective Study

Introduction: Post Fever Retinitis (PFR) is an infectious or parainfectious uveitis presenting with visual impairment after a fever episode. The condition can cause potential visual impairment in these patients. There is no national guideline for treatment of PFR. Hence, there is a need to study the clinical features and visual outcomes with the use of corticosteroid therapy. Aim: To describe the clinical features of patients presenting with PFR and visual outcome with the oral corticosteroid therapy. Materials and Methods: This retrospective study conducted in the Outpatient Department (OPD) of Ophthalmology at SDM College of Medical Sciences and Hospital, Dharwad, Karnataka, India. The duration of the study was 35 months, from January 2019 to December 2021. A total of 23 eyes of 13 patients treated with oral corticosteroids were included. Data collected included patients’ demographic details including name, age, sex, hospital identification number, duration of vision loss, detailed ophthalmic examination findings, including visual acuity testing with Snellen’s chart, slit lamp examination findings and fundus examination findings including detailed fundus drawings, Optical Coherence Tomogram (OCT) and fundus photographs. Visual Acuity (VA) at the time of presentation and after steroid therapy were recorded. Data was entered in microsoft excel spreadsheet and descriptive analysis was done. Results: Age of the study participants ranged from 15 years to 52 years with an average of 29.6 years. A total of 23 eyes of 13 patients were included in the present study. At the time of presentation, two eyes had visual acuity better than 6/12 on Snellen’s chart. Five eyes had mild vision impairment, five eyes had moderate vision impairment and eleven eyes had vision <3/60, according to the visual impairment classification of World Health Organisation (WHO). Macular oedema was the other most common finding seen in 12 (52.17%) eyes. All the patients showed beginning of resolution of retinitis by 2-3 weeks after starting oral corticosteroids. A total of 23 eyes, 8 (34.7%) eyes recovered vision >6/12, out of which 6 eyes (26.08%) recovered with 6/6 vision. Conclusion: PFR affects predominantly young immunocompetent individuals. Treatment outcomes with oral steroids is found to be satisfactory

Axenfeld-Rieger syndrome: a novel histopathologic finding associated with corneal abnormalities

BackgroundAxenfeld-Rieger syndrome (ARS) is a rare kind of anterior segment dysgenesis (ASD). The most common ocular features of ARS are posterior embryotoxon and iris hypoplasia, while some patients may manifest as corneal opacity and edema. However, the current understanding of how ARS affects the cornea is still incomplete. This study reports a novel histopathological finding of ARS, complicating corneal abnormalities, including congenital corneal opacity and irreversible endothelial decompensation.MethodsThis retrospective study included 6 eyes of 3 ARS patients, 5 of which underwent keratoplasty for irreversible endothelial decompensation from May 2016 to January 2019. No eye had a history of surgery. We reviewed the data of epidemiology, clinical manifestations and histopathologic examinations.ResultsFive eyes developed irreversible endothelial decompensation, among which 4 were born with corneal opacity. One eye exhibited transparent cornea but showed a continuous loss of endothelial cells in the absence of surgery and elevated intraocular pressure thereafter. Anterior segment optical coherence tomography photographs showed that anterior synechia existed in the area with corneal opacities, where we found the interlayer splitting of the Descemet membrane inserted by hypoplastic iris and a basement membrane-like structure under a light microscope.ConclusionAnterior synechia might be associated with corneal abnormalities in ARS patients. The novel histopathologic finding revealed the internal relation between anterior segment dysgenesis and would help explore the inner mechanism of corneal abnormalities in ARS.

Stab-Resistant Performance of the Well-Engineered Soft Body Armor Materials Using Shear Thickening Fluid.

Stab-resistant body armor can effectively prevent sharp instruments from attacking the protected parts and reduce the threat to human bodies. Shear thickening fluid (STF) is a kind of smart material with variable viscosity and its viscosity can change significantly with external stimuli. The soft and adaptive characteristics of STF provide a new idea for improving the performance of stab-proof materials. In this work, three kinds of soft anti-stabbing materials were designed and prepared with aramid, poly–p–phenylene benzodioxazole (PBO), and carbon fiber fabrics impregnated with STF. Quasi-static puncture tests and dynamic impact tests were conducted to compare the performance of different anti-stabbing structures. The results showed that the peak piercing force of the STF-treated fabrics in the puncture testing was greatly increased than that of neat samples. Against the D2 knife, the maximum impact load of STF/PBO fiber fabric was increased from 55.8 N to 72.9 N, increasing by 30.6%. Against the D3 spike, the maximum impact load of STF/aramid fabric was increased from 128.9 N to 254.7 N, increasing by 197.6%. The mechanical properties of fibers were important factors for the resistance to knives, and the fabric structure was the key point to bear the spike. Optical photographs of fabric fractures and scanning electron microscope analysis indicated that the STF effectively limited the slip of the fiber bundle when the tool penetrated the fabric, which played a positive role in maintaining the tightness and integrity of the fabric structure.

N -Heterocycles Extended π-Conjugation Enables Ultrahigh Capacity, Long-Lived, and Fast-Charging Organic Cathodes for Aqueous Zinc Batteries

<i>N</i> -Heterocycles Extended π-Conjugation Enables Ultrahigh Capacity, Long-Lived, and Fast-Charging Organic Cathodes for Aqueous Zinc Batteries

Cost-Effectiveness of Screening for Open Angle Glaucoma Compared With Opportunistic Case Finding.

The manuscript evaluates cost-effectiveness of glaucoma screening with imaging devices and telemedicine based on a screening campaign performed in Spain. The screening strategy implemented in our analysis was cost-effective compared with opportunistic case finding. Open angle glaucoma is an asymptomatic ocular disease that represents one of the first causes of blindness. Diagnosis is currently made by opportunistic case finding, usually by community optometrists or general ophthalmologists. The aim of this study was to assess the cost-effectiveness of a screening strategy based on optical coherence tomography and fundus photographs in glaucoma detection. A cost-effectiveness analysis was carried out to compare 2 alternative strategies: opportunistic finding versus screening. A Markov tree model was carried out with 10 health states according to disease progression. Quality-adjusted life years (QALYs) were used as a measure of effectiveness. We included short-term and long-term direct health costs and a discount rate of 3%. We performed a probabilistic sensitivity analysis and several 1-way sensitivity analyses. The cohort in the screening program entailed an increase in 0.097 QALYs and additional costs of €1187 versus opportunistic finding, with an incremental cost-effectiveness ratio of about €12.214/QALY. The 1-way sensitivity analysis showed that inputs related to age and screening program (cost and detection rate) were those most strongly influencing the results of the analysis. Probabilistic sensitivity analyses showed that the model was robust to significant changes in the main variables of the analysis. The screening strategy implemented in our analysis was cost-effective compared with opportunistic finding in patients with glaucoma in this Spanish setting.

Verification of Marine Oil Spills Using Aerial Images Based on Deep Learning Methods

The article solves the problem of verifying oil spills on the water surfaces of rivers, seas and oceans using optical aerial photographs, which are obtained from cameras of unmanned aerial vehicles, based on deep learning methods. The specificity of this problem is the presence of areas visually similar to oil spills on water surfaces caused by blooms of specific algae, substances that do not cause environmental damage (for example, palm oil), or glare when shooting (so-called look-alikes). Many studies in this area are based on the analysis of synthetic aperture radars (SAR) images, which do not provide accurate classification and segmentation. Follow-up verification contributes to reducing environmental and property damage, and oil spill size monitoring is used to make further response decisions. A new approach to the verification of optical images as a binary classification problem based on the Siamese network is proposed, when a fragment of the original image is repeatedly compared with representative examples from the class of marine oil slicks. The Siamese network is based on the lightweight VGG16 network. When the threshold value of the output function is exceeded, a decision is made about the presence of an oil spill. To train the networks, we collected and labeled our own dataset from open Internet resources. A significant problem is an imbalance of classes in the dataset, which required the use of augmentation methods based not only on geometric and color manipulations, but also on the application of a Generative Adversarial Network (GAN). Experiments have shown that the classification accuracy of oil spills and look-alikes on the test set reaches values of 0.91 and 0.834, respectively. Further, an additional problem of accurate semantic segmentation of an oil spill is solved using convolutional neural networks (CNN) of the encoder-decoder type. Three deep network architectures U-Net, SegNet, and Poly-YOLOv3 have been explored for segmentation. The Poly-YOLOv3 network demonstrated the best results, reaching an accuracy of 0.97 and an average image processing time of 385 s with the Google Colab web service. A database was also designed to store both original and verified images with problem areas.

Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks.

Cracked tooth syndrome is a commonly encountered disease in dentistry, which is often accompanied by dramatic painful responses from occlusion and temperature stimulation. Current clinical diagnostic trials include traditional methods (such as occlusion test, probing, cold stimulation, etc.) and X-rays based medical imaging (periapical radiography (PR), cone-beam computed tomography (CBCT), etc.). However, these methods are strongly dependent on the experience of the clinicians, and some inconspicuous cracks are also extremely easy to be overlooked by visual observation, which will definitely affect the subsequent treatments. Inspired by the achievements of applying deep convolutional neural networks (CNNs) in crack detection in engineering, this article proposes an image-based crack detection method using a deep CNN classifier in combination with a sliding window algorithm. A CNN model is designed by modifying the size of the input layer and adding a fully connected layer with 2 units based on the ResNet50, and then, the proposed CNN is trained and validated with a self-prepared cracked tooth dataset including 20,000 images. By comparing validation accuracy under seven different learning rates, 10−5 is chosen as the best learning rate for the following testing process. The trained CNN is tested on 100 images with 1920 × 1080-pixel resolutions, which achieves an average accuracy of 90.39%. The results show that the proposed method can effectively detect cracks in images under various conditions (stained, overexplosion, images affected by other diseases). The proposed method in this article provides doctors with a more intelligent diagnostic solution, and it is not only suitable for optical photographs but also for automated diagnosis of other medical imaging images.

Brightly luminescent green-emitting halide perovskite light emitting diode by employing the whole single crystal

Halide Perovskite light emitting diodes (LEDs) have attracted enormous attention due to their remarkable optoelectronic properties, facile bandgap tunability and low-cost. Here, we successfully synthesized the centimeter-sized pure non-emissive Cs4PbBr6, hybrid green-emitting Cs4PbBr6@CsPbBr3 (H-Cs4PbBr6) and ligand-induced H-Cs4PbBr6 single crystals (SCs) via the precision-temperature-gradient crystallization method. The detailed formation process of H-Cs4PbBr6 was detected by a real-time optical photograph and ultraviolet lamp during different growth stages ranged from colorless transparent to bright green. Notably, the H-Cs4PbBr6 SC shows the behavior of excellent luminous properties (PLQY = 92 %) owing to the higher exciton binding energy, which is estimated to be ∼439.8 meV. The unusual intense green photoluminescence mechanism is evidenced by the various measurements, which can be attributed to the embedded CsPbBr3 nanocrystals. Interestingly, the excellent long-term stabilities of as-prepared H-Cs4PbBr6 SC against heat, and environment oxygen/moisture degradation are reported, which maintains high fluorescence brightness for 3 years in air, and then for more than 4 days under 80 °C and 80 % relative humidity without additional encapsulation. A larger activation energy of 461.1 meV exhibits the better thermal stability. Furthermore, an adjustment of the PL emission of H-Cs4PbBr6 SCs is first achieved with the addition of ligands. Ultrapure green LED fabricated with the whole large Cs4PbBr6 SC exhibits wonderful performance with luminous efficiency of 20.50 lm·W−1, excellent color purity of ∼90.7 % and external quantum efficiency of 5.43 %, which demonstrate the immense potential and great prospect of H-Cs4PbBr6 perovskite composites to replace conventional phosphors in lighting devices.

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September Online Cover: Characterization of lotus seed development; fresh weight, dry weight, and moisture content of developing seeds; optical microscope photographs of iodized slices of mature seed and rhizome; and Venn diagrams of differentially expressed genes, from “Differential expression involved in starch synthesis pathway genes reveal various starch characteristics of seed and rhizome in lotus (Nelumbo Nucifera)” by Fenglin Zhu, Han Sun, Jia Wang, Xingwen Zheng, Tao Wang, Ying Diao, and Zhongli Hu. p. 4250–4263.