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Face annotation plays a crucial role in the field of computer vision. Its purpose is to accurately label the faces that appear in an image. The effectiveness of face annotation relies heavily on the representation of facial features, such as color, texture, and shape. Deep texture features, in particular, play a significant role in face annotation systems. It is worth noting that different individuals can possess similar texture features, which can impact the performance of annotation. Therefore, this study addresses the enduring complexity of face similarity by introducing an innovative approach called the Deep Learning-based Texture Feature (DLTF) through the utilization of the efficient deep learning model known as the Residual Network (ResNet). Despite the variations in poses, lighting, expressions, and occlusions that can greatly alter faces, ResNet’s deep architecture and feature retention capabilities make it resilient to these changes, ensuring consistent and accurate annotations under diverse conditions. Experimental results obtained from the IMFDB, LFW, and Yahoo datasets demonstrate that the proposed DLTF is the most effective description of deep texture features, leading to improved face naming performance. Furthermore, the proposed DLTF enhances the efficiency of the face-naming task by effectively addressing real-life challenges.

Mantispids are small brown bugs about 1.5 cm in length. Mantispid eggs are produced in large quantities, with about 1000 eggs per spawning, and are tiny and densely packed. Traditionally, mantispid eggs are counted manually. However, counting such a large quantity of eggs is difficult. To provide accurate data for researchers, we detail methods to accurately detect and count the number of mantispid eggs using image processing. The following methods were used to count the mantispid eggs: background estimation, morphological image processing, background subtraction, stretching, image thresholding, gray-level transformation, labeling and counting. The results of automated counting were compared with the results of manual counting. The segmentation results were verified, and the accuracy of the mantispid egg counts was determined to be 100%. This provides a useful resource for mantispid egg counting. The automatic counting system cannot only count mantispid eggs, it can also be used to count other similar insect eggs.

This paper introduces a novel approach for contour-based shape matching named as Constructive Relaxation Matching (CRM). Relaxation Matching (RM) introduced by Rosenfeld et al. is one of the standard method for quasi-optimally solving the local correspondences of the template and input images. RM relies on an energy-minimizing nature of the dynamical system to update the label assignment to the input objects. In image matching relying on a particular modeling method, apparently similar images can be judged as being quite distant, according to the nature of the modeling process and its outcome. In the proposed CRM, the modeling stage of a novel input image contour, conventionally done in the same procedure used for modeling the templates, will be included in the procedure of iterative relaxation matching. The model of the input will be dynamically constructed during relaxation, by unifying the pairs of objects having similar template label assignment probabilities. After describing the CRM procedures, the method is applied to simple shape matching problems demonstrating the ability to adaptively model the input image during relaxation. It is shown that the proposed CRM improves the object-label correspondence for evaluation of the image similarities in the following stages of shape matching applications.

Exosomes are lipid bilayer vesicles released by cells and serve as natural carriers for cell–cell communication. Exosomes provide a promising approach to the diagnosis and treatment of diseases and are considered as an alternative to cell therapy. However, one main restriction in their clinical application is that the current understanding of these vesicles, especially their in vivo behaviors and distributions, remains inadequate. Here, we reviewed the current and emerging methods for in vivo imaging and tracking of exosomes, including fluorescence imaging, bioluminescence imaging, nuclear imaging, X-ray imaging, magnetic resonance imaging, photoacoustic imaging, and multimodal imaging. In vivo imaging and tracking of exosomes by these methods can help researchers further understand their uptake mechanism, biodistribution, migration, function, and therapeutic performance. The pioneering studies in this field can elucidate many unknown exosomal behaviors at different levels. We discussed the advantages and limitations of each labeling and imaging strategy. The advances in labeling and in vivo imaging will expand our understanding of exosomes and promote their clinical application. We finally provide a perspective and discuss several important issues that need to be explored in future research. This review highlights the values of efficient, sensitive, and biocompatible exosome labeling and imaging techniques in disease theranostics.

The power graph is a special type undirected simple graph of a finite group G which has the group elements as its vertex set and two distinct vertices $x,y\in G$ are adjacent if one is non-negative integral power of other. Vertex labeling of graph $\mathrm{\Gamma }$ is a process of assigning integers to all its vertices subject to certain conditions. In simple words, vertex (edge) labeling is a function of all vertices (edges) to set of labels. Frequently, integers are used in labeling of vertices and edges. A graph $G$ is said to be divisor graph if all vertices of graph can be labeled with positive integers such that any two distinct vertices $x,y\in G$ are adjacent if and only if either $x|y$ or $y|x$. In this research paper, we prove that every power graph of finite group is always a divisor graph, but converse is not true.

Demonstrating that a cell therapy can directly contribute to functional recovery of a diseased organ is made difficult by experimental methods that are liable to introduce false-positive data. In this chapter we analyze the methods used to prove that a transplanted cell has grafted into the target organ and highlight the potentials for producing misleading results. Furthermore, we discuss the advantages and pitfalls of supporting graft data by quantifying improvement of organ function. We conclude that a multi-tiered experimental approach is required to thoroughly dispel the notion that engraftment and functional improvement are artefactual. Because of the relative immaturity of the field of lung cell therapy, we draw many of our examples from tissues with related challenges, such as cardiomyocyte cell therapy.

Exosomes are lipid bilayer vesicles released by cells and serve as natural carriers for cell–cell communication. Exosomes provide a promising approach to the diagnosis and treatment of diseases and are considered as an alternative to cell therapy. However, one main restriction in their clinical application is that the current understanding of these vesicles, especially their in vivo behaviors and distributions, remains inadequate. Here, we reviewed the current and emerging methods for in vivo imaging and tracking of exosomes, including fluorescence imaging, bioluminescence imaging, nuclear imaging, X-ray imaging, magnetic resonance imaging, photoacoustic imaging, and multimodal imaging. In vivo imaging and tracking of exosomes by these methods can help researchers further understand their uptake mechanism, biodistribution, migration, function, and therapeutic performance. The pioneering studies in this field can elucidate many unknown exosomal behaviors at different levels. We discussed the advantages and limitations of each labeling and imaging strategy. The advances in labeling and in vivo imaging will expand our understanding of exosomes and promote their clinical application. We finally provide a perspective and discuss several important issues that need to be explored in future research. This review highlights the values of efficient, sensitive, and biocompatible exosome labeling and imaging techniques in disease theranostics.

The chapter examines the scope and significance of the National Organic Program (NOP) recently introduced in the United States and systematically analyzes the effects of the new national organic standards on the markets for organic, conventional and genetically modified food products (GMPs). The effect of the NOP on consumer purchasing decisions and welfare is examined under the current no labeling of GMPs regime. A model of vertical product differentiation is developed to capture heterogeneous consumer preferences regarding interventions in the production process. Analytical results show that, as long as the NOP does not impose significant costs in the organic food supply chain, the introduction of the new organic standards can increase the market share of the organic sector and can enhance aggregate consumer welfare. Overall, the market and welfare effects of the NOP depend on the distribution of consumer preferences and the level of aversion to interventions in the production process, the production share of GMPs, the effect of the NOP on the price of the organic product and the relative costs of producing organic, conventional and GM products.

In vivo evaluation of drug properties becomes a crucial in the drug development. Near infrared techniques contributed considerably to the development of protein polypeptide drugs by performing non-invasive in vivo real time measurements on experimental subjects. In this study, a NIR monitoring system comprised of NIR spectroscopy and imaging system for in vivo real time monitoring of the dynamic of protein polypeptide drugs on mouse models was designed. Insulin acted as polypeptide drug model was covalently labeled with NIR fluorescence probe cypate (Ex = 780nm, Em = 830nm). The labeling route was optimized with different factors to obtain the maximum labeling efficiency, which was evaluated by RP-HPLC. The labeling result show that the labeling efficiency was approximated to 95%. Pharmacodynamics study showed that insulin labeled with cypate did not affect its function of hypoglycemic. The half-time of insulin — cypate complex at arteria cruralis blood was 17min, and the dynamic distribution in mouse model indicated that the labeled insulin firstly accumulated in liver and clearance from the enteron system. The NIR monitoring system combined with NIR probe showed a promising way for in vivo monitoring the dynamics of protein polypeptide drugs in small animals.

Basic shape features of objects in a binary image are very important for image analysis and pattern recognition. In conventional algorithms, for basic shape feature computation, a labeled image generated by a connected-component labeling processing is usually necessary. This paper proposes a fast two-scan algorithm for calculating shape features of objects in a binary image without the use of a labeled image. Experiments demonstrated that the proposed algorithm is much more efficient than conventional algorithms for calculating basic shape features of objects in a binary image.

Mantispids are small brown bugs about 1.5 cm in length. Mantispid eggs are produced in large quantities, with about 1000 eggs per spawning, and are tiny and densely packed. Traditionally, mantispid eggs are counted manually. However, counting such a large quantity of eggs is difficult. To provide accurate data for researchers, we detail methods to accurately detect and count the number of mantispid eggs using image processing. The following methods were used to count the mantispid eggs: background estimation, morphological image processing, background subtraction, stretching, image thresholding, gray-level transformation, labeling and counting. The results of automated counting were compared with the results of manual counting. The segmentation results were verified, and the accuracy of the mantispid egg counts was determined to be 100%. This provides a useful resource for mantispid egg counting. The automatic counting system cannot only count mantispid eggs, it can also be used to count other similar insect eggs.