Optical Pictures Research Articles

Automated Identification of Retinal Disorders by Deep Learning with Optical Coherence Tomography Pictures

A crucial problem in computer-aided diagnosis (CAD) for medical applications is the classification of retinal disorders. This paper addresses the 4-class classification problem in optical coherence tomography image analysis (OCT) to automatically identify choroidal neovascularization (CNV), diabetic macular edema (DME), DRUSEN, and NORMAL. Retinal OCT pictures were identified by the proposed classification approach using a set of four classification model instances, each based on an upgraded residual neural network (ResNet50).At the patient level, the experiment employs a 10-fold cross-validation process that is founded on the growth of the OCT retinal picture collection. According to the study's findings, multiple ResNet50 concatenation is a helpful method when the availability of pictures used in medicine is scarce. In order to better understand the decision-making process, we also ran a bottleneck test and a qualitative assessment of the model predictions.

Improving Haze Detection Using Deep Learning-Based Optimal Contrast Limited Adaptive Histogram Equalization

When gathering optical satellite pictures, light reflected from the surface due to water vapor, snow, fog, haze, and more tiny particles in the environment is generally seen as a gap in the propagation process. Haze has a greater number of suspended particles like aerosols and water droplets. These particles have absorption effects and scattering in the light. Although haze translucency grants a chance for image restoration, a well-organized and broadly relevant haze removal procedure for holding several hazes is quite an extensive provocation. To address this issue, this paper proposed an Optimal Contrast Limited Adaptive Histogram Equalization (OCLAHE) to capture further intricate features and patterns connected to haze, enabling more accurate haze detection and removal. The deeper network can learn complicated descriptions and recognize between hazy and nonhazy regions with higher precision. The proposed method is validated in I-Haze and O-Haze datasets, and its performance is quantified by various performance metrics such as MSE, SSIM, PSNR, WPSNR, and Running time. The experimental consequences demonstrate that the developed model performs better than other techniques and attains an MSE from both datasets as 0.0054 and 0.0051. Overall, the proposed model amends the accuracy and reliability of haze detection in images.

A lightweight object detection framework for underwater imagery with joint image restoration and color transformation

Traditional underwater detectors struggle to match the demands of visual observation and icon detection because of the underwater optical pictures' color distortion, uneven illumination, and excessive noise levels. In this paper, a lightweight deep-water object detection network is proposed, which consists of three key components, namely image restoration, color transformation, and object detection. First, we propose a lightweight attention module for the problems of color distortion and uneven illumination in underwater images. This module pays more attention to the areas with a greater influence of underwater color when dealing with different types of poor-quality images. Second, to reduce the computational complexity of object detection, we propose a color conversion module based on the laplacian pyramid decomposition. This module incorporates multi-scale features to effectively address the loss of details in the brightest or darkest regions. Finally, we propose a multi-scale dense residual object detection network. The network applies a multi-scale kernel to an improved residual module to realize the extraction and fusion of feature information of multiple receptive fields. Furthermore, to deal with the problem of underwater small-sample object detection, we propose a mutually exclusive loss function. The mutual exclusion loss promotes the update of network parameters so that the classes with different characteristics of samples generated by the network are mutually exclusive. We ran tests on the Pycharm platform to show that the suggested lightweight joint underwater object identification algorithm outperformed the most sophisticated ones. The proposed system was put to the test in an intricate underwater setting, achieving 92.56 percent accuracy and 19.2 frames per second.

Extraction, Characterization, and Evaluation of Lepidium sativum Linn. Mucilage as a Mucoadhesive Polymer.

Being biocompatible, less toxic, cheap, easily available, and environmentally friendly, there is an increased trust in natural polymers in the drug delivery system. Mucilages, among the natural polymers, are the primary metabolites of plants that have been widely utilized in pharmaceutical manufacturing for different purposes, and mucoadhesive is one among them. The present study was designed to investigate the use of LSM as a mucoadhesive polymer using ibuprofen as a model drug. The mucilage was extracted following an aqueous extraction method and its percentage yield was found to be 13.2% w/w. Besides, three microsphere formulations of ibuprofen were prepared using synthetic polymer hydroxyl propyl methyl cellulose (HPMC) K100M and the LSM in polymer to drug ratios of 1 : 1, 1 : 5, and 3 : 5 by applying ionotropic gelation followed by solvent evaporation methods. The microspheres were evaluated for various micromeritic properties and all the formulations exhibited free-flowing properties. Optical microscopic pictures of almost all the microspheres except F3 and F6 (which had more or less spherical shapes) were found to have irregular and discrete shapes. Besides, the surfaces of all the formulations were rough in texture. The drug entrapment efficiency of the microspheres was found to be between 52.08% ± 0.80 and 87.97% ± 0.72. The in-vitrowash-off test evidenced that almost 50 percent (especially F3) of the microspheres were able to adhere up to 18 h and showed remarkable bioadhesion properties. The in-vitro drug release profile indicated that all the formulations were able to prolong their drug release up to 12 h with a non-fickian release mechanism, except for F4, which followed a fickian release. Therefore, based on the findings of this study, LSM can be used as a potential alternative mucoadhesive excipient for sustained release formulations.

Ionic liquids: a new generation of efficient polyvinyl chloride thermal stabilizers

AbstractPolyvinyl chloride (PVC), is one of the main synthetic materials used widely in many applications of our life aspects today. Though, the practical usage of it was always affected by some destructive factors like UV-light and heat. The optical and surface characteristics of pure and modified PVC thin films were compared throughout a temperature range of 25–55 °C. It was found that the intensity of the amine group in modified PVC varied with temperature. Surface morphology properties studied by AFM results; the ionic liquid was proven to comparably increases the stability of PVC surface while the roughness was less than pure PVC with increasing temperature. Optical microscope pictures, manifest PVC as drops at 55 °C, while, in modified PVC at the same temperature, the PVC surface was noticeably more stable. Finally, the energy gap of PVC pure and modified PVC thin films are studied. At 55 °C, the modified PVC's energy gap value increased from 3.64 eV at ambient temperature to 4.28 eV. This makes it more isolated when compared to pure PVC, which has an energy gap of 3.04 eV at ambient temperature and 3.1 eV at 55 °C and is a semiconductor.

Investigation of the Effect of Filling Ratio on Mechanical Properties of Pumice Filled Epoxy-Based Composites.

This study attempted to fill epoxy, a widely used industrial material, with pumice, a cheap volcanic rock, in order to form a composite material. The objective was to evaluate the worth of the pumice and improve the mechanical properties of the epoxy. Composite samples with no filler, 10%, 20%, or 30% filler were produced. An ultrasonic mixer during manufacture made sure the powder was dispersed properly, and vacuuming stopped air pockets from accumulating in the composite. The mechanical characteristics of the composites were evaluated by compression testing, and the post-production distribution of the powder was observed using optical microscope pictures. Finally, XRF analysis was used to establish the composition of the pumice powder. The outcomes demonstrated that adding filler greatly enhanced the maximum stress and unit strain values of the composites.

Development of natural attractants to control the Mediterranean fruit fly Ceratitis capitata (Tephritidae) in Gafsa oasis, Tunisia

A natural attractant for Ceratitis capitata developed by microencapsulation by coacervation complex with gelatin and gum arabic of the essential oil of Ruta graveolens was evaluated. Essential oil composition was analyzed by Gas Chromatography Mass Spectrometry (GC/MS). Microencapsulation efficacy was evaluated by determination of the encapsulation yield (%), encapsulation efficiency (%), optical microscopy, Fourier transform infrared spectroscopy (FTIR) and release kinetics (%). Repellent/attractant and contact toxicity tests of crude and encapsulated Ruta graveolens oil were assessed under laboratory and field conditions. GC-MS analysis indicated that 2-nonanone (36.31%) and 2-undecanone (35.92%) were the dominant compounds. Encapsulation yield was 77.06% and encapsulation efficiency was 73.33%. Optical microscopy pictures revealed spherical form particles. Results exhibited the attractant potential of crude oil (class III: moderately attractant) and that encapsulated oil accomplished better attractant performance (class IV: attractant). The encapsulated oil was also toxic to Medfly adults. Results further showed that both Ceratrap® and oil capsules were attractant under field conditions. This work supports the practice of encapsulated essential oil as natural attractant for Medfly management.

Polypyrrole Modified Carbon Nanotube/Polyimide Electrode Materials for Supercapacitors and Lithium-ion Batteries

Lithium-ion batteries have evolved and transcended in recent years to power every device across the spectrum, from watches to electrical vehicles and beyond. However, the lithium-ion battery requires the use of heavy and expensive transition metal oxides that have limited life cycles. Conductive polymer nanocomposites have been shown to possess good electrochemical and thermomechanical properties and are considered to be effective alternatives to transition metal oxides. The fabrication and properties of polyimide matrix-single wall carbon nanotube, SWCNT composite electrode materials, modified by the electrodeposition of polypyrrole, PPy was successfully carried out. The doping of PPy with p-Toluene sulfonic acid, T resulted in a dramatic transformation of the morphology and specific capacitance of the electrode material. Electrochemical impedance spectroscopy, EIS, cyclic voltammetry, CV, and galvanic charge–discharge tests were used to measure the electrode’s specific capacitance and specific capacity. Maximum specific capacitance values of up to 84.88 F/g and 127.13 F/g were obtained by CV and charge–discharge tests, respectively. A capacitance retention of over 80% was obtained after over 500 cycles of testing. The insertion of doped PPy into the electrode material by electrochemical polymerization was shown to positively correlate to the improved electrochemical performance of the nanocomposite. An increase in the porosity of about 34.68% over the non-doped polypyrrole was obtained from EIS measurement and supported by the optical microscope pictures. Increasing the process parameters, such as pyrrole, Py concentration and the amount of dopants, lead to a dramatic increase in the specific capacitance and capacity of the composite electrodes.

Preliminary observation of Marmolada glacier collapse of July 2022 with space-based cameras

ABSTRACT On 3 July 2022, a section of the Marmolada glacier (Marmolada Group, Fassa Dolomites, Southern Limestone Alps) collapsed, causing an ice avalanche resulting in the death of 11 alpinists. Before the event, there were no clear signs of any potential collapse, and no warning notices were broadcasted; due to the velocity of the avalanche, no escape was possible for the involved persons. In this work, a preliminary analysis of the Marmolada glacier collapse is performed with four optical channels space imaging provided by Planet Labs, with resolution of 3 m per pixel. Pre- and post-event satellite observations are employed to assess the areas involved in the event: multispectral images can be compared to identify the collapse area and the debris conoid. A first estimation suggests a collapse area of about 4800 m2 and a collapse volume of about 96,000 m3. In addition, historical data from the Planet Labs optical pictures database can be employed to compare the status of the detached glacier and the evolution of the crevasses on its surface.

Investigation of Flexure Strength of Aluminum Composites Reinforced with Iron Fibers

Flexure strength of Aluminum composite reinforced with iron fiber has been investigated.Atomization procsses method were used to prepare sheet of aluminum reinforced with iron fiber with direction (0-90°) and (0-45°) to cognition fiber direction effect on flecture strength values.The results shows that the values of maximum bending stress, yield stress and young modulus of aluminum reiforced with iron fibers direction (0-90) higher than for the aluminum reinforced with fibers direction (0-45). The optical microscopy and photographic pictures shown the fracture surface of the tested specimens and fibers segmented and supported the rising in the flecture strength values of the aluminum composites(0-90).

Magnetoresponsive Functionalized Nanocomposite Aggregation Kinetics and Chain Formation at the Targeted Site during Magnetic Targeting

Drug therapy for vascular disease has been promoted to inhibit angiogenesis in atherosclerotic plaques and prevent restenosis following surgical intervention. This paper investigates the arterial depositions and distribution of PEG-functionalized magnetic nanocomposite clusters (PEG_MNCs) following local delivery in a stented artery model in a uniform magnetic field produced by a regionally positioned external permanent magnet; also, the PEG_MNCs aggregation or chain formation in and around the implanted stent. The central concept is to employ one external permanent magnet system, which produces enough magnetic field to magnetize and guide the magnetic nanoclusters in the stented artery region. At room temperature (25 °C), optical microscopy of the suspension model’s aggregation process was carried out in the external magnetic field. According to the optical microscopy pictures, the PEG_MNC particles form long linear aggregates due to dipolar magnetic interactions when there is an external magnetic field. During magnetic particle targeting, 20 mL of the model suspensions are injected (at a constant flow rate of 39.6 mL/min for the period of 30 s) by the syringe pump in the mean flow (flow velocity is Um = 0.25 m/s, corresponding to the Reynolds number of Re = 232) into the stented artery model. The PEG_MNC clusters are attracted by the magnetic forces (generated by the permanent external magnet) and captured around the stent struts and the bottom artery wall before and inside the implanted stent. The colloidal interaction among the MNC clusters was investigated by calculating the electrostatic repulsion, van der Waals and magnetic dipole-dipole energies. The current work offers essential details about PEG_MNCs aggregation and chain structure development in the presence of an external magnetic field and the process underlying this structure formation.

Cover Image, Volume 139, Issue 33

This image, taken and designed by Zahra Ayar, is a combination of SEM, fluorescent, and optical pictures of a porous alginate hydrogel that is modified using Schwann cell- and fibroblast-derived ECM. The study focused on the efficacy of cell-derived ECM modification of the differentiation potency of alginate hydrogel. This modified hydrogel provides an efficient microenvironment for differentiation of adipose-derived stem cells towards neuron-like cells. DOI: 10.1002/app.52501

Diagnosis Retinal Disease by using Deep Learning Models

Deep learning approaches have shown to be useful in assisting physicians in making decisions about cancer, heart disease, degenerative brain disorders, and eye disease. In this work, a deep learning model was proposed for the diagnosis of retinal diseases utilizing optical coherence tomography X-ray pictures (OCT) to identify four states of retina disease. The proposed model consists of three different convolutional neural network (CNN) models to be used in this approach and compare the results of each one with others. The models were named respectively as 1FE1C, 2FE2C, and 3FE3C according to the design complexity. The concept uses deep CNN to learn a feature hierarchy from pixels to layers of classification retinal diseases. On the test set, the classifier accuracy is 65.60 % for a (1FE1C) Model, 86.81% for (2FE2C) Model, 96.00% for (3FE3C) Model, and 88.62% for (VGG16) Pre-Train Model. The third model (3FE3C) achieves the best accuracy, although the VGG16 model comes close. Also, this model improves the results of previous works and paves the way for the use of state-of-the-art technology of neural network in retinal disease diagnoses. The suggested strategy may have a bearing on the development of a tool for automatically identifying retinal disease.

Self-healing epoxidized natural rubber with ionic/coordination crosslinks

Self-healing polymers with strong mechanical robustness and superior self-healing ability are of interest in coatings, electronics, structural components, etc. However, it is difficult to realize these properties simultaneously, owing to the mutually exclusive requirements: the mechanical robustness of materials needs strong bonds to form robust network, but a strong bond leads to weak self-healing capability. In this work, we report the rational design of epoxidized natural rubber (ENR) incorporating with ionic and coordination supramolecular hybrid bond network, in which these two kinds of bonds possess identical cross-linking point yet contrasting bond strength. The optical microscope pictures and the temperature-dependent infrared spectra analysis show that ionic bonds rapidly shorten the spatial distance of the ENR chains located on both sides of the ionic bond to assemble into a stable network with lower energy state owing to its short temporal timescale for reconstruction, and simultaneously promote the reconstruction of coordination bond as a result of their sharing the same cross-linking point. The cooperative collaboration of these two bonds lead to a tensile stress of 1.33 MPa, a strain of 600%, and a healing efficiency of 92% after healing for 3 h at ambient temperature. This novel self-healing material is promising for various applications, especially when the component is difficult to disassemble or with limited enviroment conditions.

Контроль течений на поверхности прибрежных морских акваторий дистанционными методами

Object and purpose of research. The compare analysis carried out on the vorticies structure optical satellite pictures observation of the sea surface and the velocities field obtained by the ground HF Doppler radar. The purpose of this research is estimation of the possibility on fast monitoring feasibility assessment for the changes in littoral waters dynamics through joint application of satellite surveillance, radar probing of sea currents, wind data and numerical simulation of water circulation in the area under investigation. Materials and methods. The Sea surface observation data obtained by the satellites Sentinel 1 and 2 and by the coastal Doppler HF radar Sea Sonde in the South-east Black Sea area are analyzing. The additional data on the satellite observation of this area and on the wind condition is used from LANCE processing system [9, 10] and reanalysis NCEP/NCAR [11, 12]. The comparative analysis is carried out on the large vertical structures (LVS) establishing in the research coastal area. The numerical modeling of the water mass circulation in this area is carried out by the software package COHERENS (Belgian Institute of Natural Science) to investigate the role of the wind conditions at LVS appearance in the research area. Main results. The LVS in the vicinity of Sea coast line could be generated, as satellites observations demonstrated, by the vortices arrived along the coast line from the east-south direction in accordance with the Black Sea general circulation flow. Such vortices could be induced by the bottom roughness, rivers discharges and another local sources. Another LVS source could be connected with the wind impact in some affordable direction as demonstrated by the numerical modeling of the coastal water circulation. The continuous currents measurements at the Sea surface by Doppler HF coastal Radar supply the valuable data for further details on the space –time variation of LVS parameters and operational forecast of the hydrology regime in the aquatic areas. The operative numerical modelling of the wind impact to the surface currents structures formation provides the efficient estimation of the local large vorticity structure appearance in the research area. Conclusion. Satellite radar and optical observation provide the large scale control on the Sea surface dynamics conditions, but that is limited by relatively long interval between satellite tracks over the region of interest and do not acquire optical data at the cloud cover. The additional data could be operative obtain from the open internet resource in satellite optical, radar and meteorological data (LANCE, NCEP/NCAR), to get the more details development of the Sea surface dynamics. Sub-satellite Sea currents measurements by HF Doppler radar are useful for the reliable interpretation of satellite pictures and for the proper forecast of the aquatic area dynamics. Operative numerical modelling of the Sea coastal water circulation in accordance with variable meteo data combining with dynamic processes remote measurements could be efficient for the forecast of the environment parameters variation due the water mass transfer. In general the presented results demonstrates the combined application possibilities of the satellite observations, coastal Doppler radar measurements, internet data and operative numerical modelling for operational oceanographic and ecological monitoring of Sea coastal areas with heavy pollution load.

Role of Cyclic Thermal Shocks on the Physical and Mechanical Responses of White Marble

Marble is a common rock used in many buildings for structural or ornamental purposes and is widely distributed in underground engineering projects. The rocks are exposed to high temperatures when a tunnel fire occurs, and they will be rapidly cooled during the rescue process, which has a great impact on the rock performance and the underground engineering stability. Therefore, the role of cyclic thermal shocks on the physical and mechanical properties of marble specimens was systematically investigated. Different cyclic thermal shock treatments (T = 25, 200, 400, 600, 800 °C; N = 1, 3, 5, 7, 9) were applied to marble specimens and the changes in mass, volume, density and P-wave velocity were recorded in turn. Then, the thermal conductivity, optical microscopy and uniaxial compression tests were carried out. The results showed that both the cyclic thermal shock numbers (N) and the temperature level (T) weaken the rock properties. When the temperature of a thermal shock exceeds 600 °C, the mass loss coefficient and porosity of the marble will increase significantly. The most noticeable change in P-wave velocity occurs between 200 and 400 °C, with a 52.98% attenuation. After three thermal shocks, the cyclic thermal shock numbers have little influence on the uniaxial compressive strength and Young’s modulus of marble specimens. Shear failure is the principal failure mode in marble specimens that have experienced severe thermal damage (high N or T). The optical microscopic pictures are beneficial for illustrating the thermal cracking mechanism of marble specimens after cyclic thermal shocks.

PLA-Cu reinforced composite filament: preparation and flexural property printed at different machining conditions

Fused Deposition Modeling (FDM) is commonly used to construct complicated design, especially for medical applications. In the present work, 12 rate weight percentage of copper powder with a molecule size of 30–50 µm is used in the Poly Lactic Acid (PLA) matrix as a fortification to form a composite fiber. For the variable working conditions, the samples are printed to ASTM D-790. In FDM, layer height, bed temperature, and nozzle temperature are taken as variable parameters to measure the bending property. The Scanning Electron Microscope (SEM) and 3-dimensional optical pictures examine the flexural quality, crack mechanics, and impact of various printed conditions for three-point flexural tests. A layer thickness of 0.14 mm was recorded for the maximum flexural quality of 68.6 MPa. The fracture mechanism is considered as identical under any machining conditions. Layer height predominantly determines the material’s flexural property and the uniform dispersion of the copper molecule over the crack surface which is confirmed by surface topography. Also, the non-parametric Bayesian Additive Regression Trees (BART) model is created to benefit from the earlier use of this inferential structure to measure vulnerability and information alignment.

Virtual reality and distraction cards to reduce pain during intramuscular benzathine penicillin injection procedure in adults: A randomized controlled trial.

The aim of this study was to determine the effect of using three-dimensional videos with virtual reality glasses and distraction cards including optical illusion pictures on patients' pain and satisfaction levels during intramuscular benzathine penicillin injection. A randomized controlled trial. The study population consisted of 91 patients who were prescribed intramuscular benzathine penicillin medication. The participants were stratified by gender and assigned to three groups (control, virtual reality and distraction cards groups). The visual analogue scale was used to assess pain and patient satisfaction. A one-way analysis of variance and Dunnett's post hoc tests were used to compare the pain and satisfaction levels by group. The mean pain was 6.67 (2.17) in the control group, 4.4 (2.71) in the distraction cards group and 4.93 (3.07) in the virtual reality group and the difference was statistically significant (F=5.84, p˂.01). The average of the satisfaction levels in the groups was 3.57 (2.23) in the control group, 7.13 (2.86) in the distraction cards group and 8.07 (2.55) in the virtual reality group. The difference between the satisfaction levels was statistically significant (F=25.77, p˂.01). The three-dimensional videos with virtual reality glasses and distraction cards including optical illusion pictures were effective in reducing pain associated with intramuscular benzathine penicillin injection and increasing patient satisfaction. The results of this study will contribute to evidence-based nursing practices for the pain associated with intramuscular benzathine penicillin injection. NCT04420559.

Study of Human Motion Recognition Algorithm Based on Multichannel 3D Convolutional Neural Network

Aiming at the problem that it is difficult to balance the speed and accuracy of human behaviour recognition, this paper proposes a method of motion recognition based on random projection. Firstly, the optical flow picture and Red, Green, Blue (RGB) picture obtained by the Lucas‐Kanade algorithm are used. Secondly, the data of optical flow pictures and RGB pictures are compressed based on a random projection matrix of compressed sensing, which effectively reduces power consumption. At the same time, based on random projection compression data, it can effectively find the optimal linear representation to reconstruct training samples and test samples. Thirdly, a multichannel 3D convolutional neural network is proposed, and the multiple information extracted by the network is fused to form an output recognizer. Experimental results show that the algorithm in this paper significantly improves the recognition rate of multicategory actions and effectively reduces the computational complexity and running time of the recognition algorithm.

A study of gross and histological structure of thymus gland in fetuses and adolescent

The thymus is the lymphoid organ of greatest importance. It is a structurally separated lobules through the tissue of the connective septa. That lobule has a cortex and a medulla in it. Many studies of this organ related to the histology of early fetuses are focused on animals. The present study focuses on certain features relating to the histogenesis of the thymus and adolescent fetuses. In the present study, 50 normal human stillborn/aborted fetuses and one is 15 years thymus gland in adolescent was studied from 18 to 35 weeks were examined. The acquired fetuses were set in formalin of 10 per cent. They have been exposed to dissection after correct fixation. The specimens acquired had been processed through a well-known paraffin block making process. Sections were taken with haematoxylin & eosin, and painted. The stained sections had been tested using 40x and 100x optical magnifications and pictures taken under light microscopy. Compared to its CRL, the gland's dimension has changed. Compared to gestational age, the mass of the gland and fetuses was. It has been demonstrated capsule, septae, cortex, medulla, blood vessel, lymphocytes, reticular epithelial cells, adipose cells, and the corpuscle of Hassall.Thymus gland involution, pondered in its anatomy and histology, will serve as a basis for becoming conscious of pathological conditions. Within the first 18 weeks of gestation, all structural changes viz. cortico-medullary differentiation, lobulation, and maturity of the hassall's corpuscles happened.