Deep ocular tumor classification model using cuckoo search algorithm and Caputo fractional gradient descent.

While digital ocular fundus images are commonly used for diagnosing ocular tumors, interpreting these images poses challenges due to their complexity and the subtle features specific to tumors. Automated detection of ocular tumors is crucial for timely diagnosis and effective treatment. This study investigates a robust deep learning system designed for classifying ocular tumors.

Enhancing Medical Image Classification with an Advanced Feature Selection Algorithm: A Novel Approach to Improving the Cuckoo Search Algorithm by Incorporating Caputo Fractional Order.

Glaucoma is a chronic eye condition that seriously impairs vision and requires early diagnosis and treatment. Automated detection techniques are essential for obtaining a timely diagnosis. In this paper, we propose a novel method for feature selection that integrates the cuckoo search algorithm with Caputo fractional order (CFO-CS) to enhance the performance of glaucoma classification.

A YOLOX-Based Deep Instance Segmentation Neural Network for Cardiac Anatomical Structures in Fetal Ultrasound Images.

Echocardiography is an essential procedure for the prenatal examination of the fetus for congenital heart disease (CHD). Accurate segmentation of key anatomical structures in a four-chamber view is an essential step in measuring fetal growth parameters and diagnosing CHD. Currently, most obstetricians perform segmentation tasks manually, but the pixel-level operation is labor-intensive and requires extensive anatomical knowledge and clinical experience.

MobileUNet-FPN: A Semantic Segmentation Model for Fetal Ultrasound Four-Chamber Segmentation in Edge Computing Environments.

The apical four-chamber (A4C) view in fetal echocardiography is a prenatal examination widely used for the early diagnosis of congenital heart disease (CHD). Accurate segmentation of A4C key anatomical structures is the basis for automatic measurement of growth parameters and necessary disease diagnosis. However, due to the ultrasound imaging arising from artefacts and scattered noise, the variability of anatomical structures in different gestational weeks, and the discontinuity of anatomical structure boundaries, accurately segmenting the fetal heart organ in the A4C view is a very challenging task.

KL-MOB: automated COVID-19 recognition using a novel approach based on image enhancement and a modified MobileNet CNN.

The emergence of the novel coronavirus pneumonia (COVID-19) pandemic at the end of 2019 led to worldwide chaos. However, the world breathed a sigh of relief when a few countries announced the development of a vaccine and gradually began to distribute it. Nevertheless, the emergence of another wave of this pandemic returned us to the starting point.

Transfer Learning to Detect COVID-19 Automatically from X-Ray Images Using Convolutional Neural Networks.

The novel coronavirus disease 2019 (COVID-19) is a contagious disease that has caused thousands of deaths and infected millions worldwide. Thus, various technologies that allow for the fast detection of COVID-19 infections with high accuracy can offer healthcare professionals much-needed help. This study is aimed at evaluating the effectiveness of the state-of-the-art pretrained Convolutional Neural Networks (CNNs) on the automatic diagnosis of COVID-19 from chest X-rays (CXRs).

CacheTrack-YOLO: Real-Time Detection and Tracking for Thyroid Nodules and Surrounding Tissues in Ultrasound Videos.

To accurately detect and track the thyroid nodules in a video is a crucial step in the thyroid screening for identification of benign and malignant nodules in computer-aided diagnosis (CAD) systems. Most existing methods just perform excellent on static frames selected manually from ultrasound videos. However, manual acquisition is labor-intensive work.

Solving Many-Objective Optimization Problems by a Pareto-Based Evolutionary Algorithm With Preprocessing and a Penalty Mechanism.

It is known that the Pareto-based approach is not well suited for optimization problems with a large number of objectives, even though it is a class of mainstream methods in multiobjective optimization. Typically, a Pareto-based algorithm comprises two parts: 1) a Pareto dominance-based criterion and 2) a diversity estimator. The former guides the selection toward the optimal front, while the latter promotes the diversity of the population.

Helical Folding Competing with Unfolded Aggregation in Phenylene Ethynylene Foldamers.

The folding and aggregation behavior of a pair of oligo(phenylene ethynylene) (OPE) foldamers are investigated by means of UV/Vis absorption and circular dichroism spectroscopy. With identical OPE backbones, two foldamers, 1 with alkyl side groups and 2 with triethylene glycol side chains, manifest similar helical conformations in solutions in n-hexane and methanol, respectively. However, disparate and competing folding and aggregation processes are observed in alternative solvents.

Triangular-shaped molecular random tiling and molecular rotation in two-dimensional glassy networks.

Macrocycle-1 molecules can self-assemble into glassy state networks via van der Waals force and form many triangular nanopores in networks. The nanopores can be expressed by triangular tilings, which lead to a particularly rich range of arrangements. Moreover an interesting molecular rotation phenomenon was observed in the glassy networks.

Detection of object-based manipulation by the statistical features of object contour.

Object-based manipulations, such as adding or removing objects for digital video, are usually malicious forgery operations. Compared with the conventional double MPEG compression or frame-based tampering, it makes more sense to detect these object-based manipulations because they might directly affect our understanding towards the video content. In this paper, a passive video forensics scheme is proposed for object-based forgery operations.

Helical folding of conjugated oligo(phenyleneethynylene): chain-length dependence, solvent effects, and intermolecular assembly.

As a representative folding system that features a conjugated backbone, a series of monodispersed (o-phenyleneethynylene)-alt-(p-phenyleneethynylene) (PE) oligomers of varied chain length and different side chains were studied. Molecules with the same backbone but different side-chain structures were shown to exhibit similar helical conformations in respectively suitable solvents. Specifically, oligomers with dodecyloxy side chains folded into the helical structure in apolar aliphatic solvents, whereas an analogous oligomer with tri(ethylene glycol) (Tg) side chains adopted the same conformation in polar solvents.

A foldamer at the liquid/graphite interface: the effect of interfacial interactions, solvent, concentration, and temperature.

The unfolding process and self-assembly of a foldable oligomer (foldamer 1) at the liquid/graphite interface were investigated by scanning tunnelling microscopy. At the level of molecular conformation, we identified several molecular conformations (A(z), B, C, D, E) that represent intermediate states during unfolding, which may help to elucidate the unfolding process at the liquid/graphite interface. Adsorption at the interface traps the intermediate states of the unfolding process, and STM has proved to be a powerful technique for investigating folding and unfolding of a foldamer at the molecular level, which are not accessible by other methods.

A photoswitch based on self-assembled single microwire of a phenyleneethynylene macrocycle.

Crystalline microwires of a phenyleneethynylene (PE) macrocycle self-assembled from solution exhibited superior photoconductive properties. Photoswitches fabricated with single wires afforded nA-scale photocurrents with on/off ratios of ca. 10(3).

Folding a conjugated chain: oligo(o-phenyleneethynylene-alt-p-phenyleneethynylene).

An oligo( o-phenyleneethynylene- alt- p-phenyleneethynylene) was synthesized to create a conjugated molecule capable of adopting a helical secondary structure. A special feature of such a folded molecule is that the effective directions of energy/charge transport via covalent conjugation and through pi-pi stacking are converged to be along the helix axis. The transition from random conformations to the helix, driven by solvophobic and aromatic stacking interactions, was controlled by solvent properties.

Oligo(p-phenyleneethynylene)s with hydrogen-bonded coplanar conformation.

A series of monodispersed oligo( p-phenyleneethynylene)s were synthesized bearing intramolecular hydrogen bonds between side chains of adjacent phenylene units in the backbone. Thus, all repeating units of the molecules are constrained in a coplanar orientation. Such planarized conformation is considered favorable for single-molecule conductance.