The Industrial Internet is the key for Industry 4.0, and network control in the industrial internet usually requires high reliability and low latency. The industrial internet ubiquitously connects all relevant Internet of things (IoT) sensing and actuating devices, allowing for monitoring and control of multiple industrial systems. Unfortunately, guaranteeing very low end-to-end wait times is particularly challenging because the transmissions must be articulated in time. In the industrial internet, there usually coexist multiple streams. The amount of data for controlling business flows is small, while other business flows  typically transmit large amounts of data across the network. These data flows are mainly processed in traditional switches using a queue-based "store-and-forward" mode for data exchange, consuming much bandwidth and filling up the network buffers. This causes delays in the control flow. In our research, we propose an Software Defined Networking (SDN) framework to reduce such delays and ensure real-time delivery of mixed service flows. The scheduling policy is performed through the northbound Application Programming Interface (API) of the SDN controller so that the dynamic network topology can be satisfied. We use the concept of edge and intermediate switches, where each switch port sends data at a specific time to avoid queuing intermediate switches. We also introduce an improved Langerian relaxation algorithm to select the best path to ensure low latency. Finally, the path rules are deployed to the switches in flow tables through the SDN controller. Our mathematical analysis and simulation evaluation demonstrates that the proposed scheme is more efficient. The original standard Ethernet IEEE802.32 satisfies the bandwidth requirements while maintaining scalability and cost-effectiveness but is not suitable for applications with low latency requirements. In the Industrial Internet, physical processes are controlled by several distributed sensors, actuators, and controllers. Smart Factory is a product of the Industrial Internet, and Cyber-Physical System (CPS) is the key to building SmartFactory.With the emergence of industrial IoT, an increasing number of intelligent devices and infrastructures have formed intelligent systems, as shown in Fig. Cyber-Physical Systems (CPS) depend on a computer network that sends sensor data and actuator instructions to the controller. In general, such CPSs are sensitive systems where network delays and jittering can affect the performance of control of the CPS. When two continuous packets are lost, machines on the production floor may malfunction. For example, Daystar, the third-generation industrial robot developed by Lenovo in 2021, is a CPS system. Daystar industrial robots have been able to work for the manufacture of aircraft, helping workers perform remote painting jobs with precision. First, the robot performs an aspatial scan of the entire workshop for perception. The data is built and rendered in real-time in 3D on an edge-side virtual machine and moved to the designated paint booth through containerized Simultaneous Localization And Mapping (SLAM) technology, navigation, and positioning. The robot’s binocular stereo camera captures the workpiece and surroundings of the operator table in real-time to the edge server. However, this collaborative human–machine interaction is now a bottleneck in the development of industrial robots, as it is necessary to ensure real-time binocular stereoscopic video data return from the robot side, with the camera view following the user’s perspective in real-time, combined with augmented reality technology enabling users to immerse themselves in the dynamic remote environment in real-time. It is also essential to ensure that the robot control algorithm is responsive and robust, this allows the robot in the remote domain to reproduce the action commands from the user with very low latency by taking advantage of the rapidity of transmitting control commands, allowing the robot to operate precisely in the remote environment. But current network speeds are not up to the real-time, low-latency response needed for collaborative robots.In the field of industrial manufacturing, network interconnection is the foundation. Due to the complexity of industrial communication and automation, improving the delay performance of the network is essential for the future development of industrial communication and automation control. Scheduling algorithms are a crucial part of the network. Efficient scheduling algorithms are closely related to timely and reliable data transmission. The smart factory makes the transmission of mixed data streams a reality. The birth of Software Defined Networking (SDN) provides new ideas for scheduling data flows in multiple data streams. SDN is more suitable for centralized management and control than traditional networks. OpenFlow protocol implements the notion of network programmability, and network state, data flow, and control information can be transmitted in real-time through the standard interface of this protocol; this makes it possible to deploy SDN networks into industrial Internet environments.Let us enumerate the main contents of this article. (1) This paper introduces the scheduling problem (NP-hard) in the Industrial Internet and introduces an Integer Linear Programming (ILP) model to calculate routing and transmission scheduling to select an optimal path. (2) This paper introduces an improved Lagrangian relaxation algorithm that converges faster than the traditional routing algorithm. The improved algorithm not only ensures the real-time performance of the network but also reduces other cost overheads of the network, such as bandwidth, jitter, and link utilization. In summary, the proposed algorithm overcomes the technical barriers in the field of low network latency, and it is important for the development of network deterministic delay technology.The remainder of this paper is enumerated as follows. In “3, which uses the traditional Shortest Path (SP) algorithm to find the shortest path and then finds the subsequent shortest paths based on the initial shortest path. KSP is a static scheduling algorithm; although it performs well in sparse network topologies, the number of traversed paths needs to be increased in dense topologies to achieve optimality. The traditional optimal shortest path algorithm is often unusable due to its high computational effort and is unsuitable for real-time operation. A novel stream scheduling generation model is proposed by Zaiyu Pang et al.4 The model is designed with two algorithms to suit different application scenarios: the offline algorithm has better schedulability, while the online algorithm consumes less time and has slightly reduced schedulability. Many heuristic search strategies have been proposed to improve the computational efficiency of shortest path search. Misra et al.5 proposed a polynomial-time heuristic algorithm, but it only considered the maximum throughput under the bandwidth constraint and ignored the delay and packet loss rate. We found a heuristic algorithm based on Particle Swarm Optimization (PSO) to solve the scheduling problem in Xue et al.6. Nevertheless, the results obtained are not entirely accurate due to the rapid convergence rate, which can lead to an optimal local solution. Even the results do not reflect the actual performance of the PSO. For large-scale scheduling, Pozo et al.7 proposed a segmentation method that decomposes the scheduling problem into smaller problems that can be solved independently. While maintaining the quality of the schedule reduces the running time of the scheduler and allows scheduling larger networks in a shorter period. The work in8 relaxes the scheduling rules, divides the Satisfiability Modulo Theories (SMT) problem into multiple Optimization Mode Theory (OMT) problems, and reduces the solver runtime to an acceptable level to eliminate scheduling conflicts. The scheduling is an NP-hard problem. To solve the NP-hard problem, some researchers used the traditional Lagrange relaxation algorithm9 to transform the relaxation function into a new heuristic function. After analyzing and discussing Lagrange multipliers, we propose multipliers different from the traditional Lagrange relaxation algorithm in this paper.This paper focuses only on the low-latency problem of scheduling mixed service flows in the industrial Internet. Many scholars have investigated the scheduling of flows. Berclaz et al. proposed the well-known K Shortest Paths (KSP) algorithm10 and TT-Ethernet11. GengLiang et al.12 used a fieldbus scheduling table to construct an algorithm that minimizes communication jitter. We can assume that the propagation delay, processing delay, and transmission delay in the network are deterministic. The propagation delay, processing delay, and transmission delay in the network are deterministic13. Therefore, Niklas Reusch et al.14 propose a novel and more flexible window-based scheduling algorithm using a time-aware shaper (TAS) that guarantees bounded delays by integrating worst-case delay analysis. These networks architectures limit the non-deterministic queuing delay. For this purpose, Nayak et al.15 used a Software Defined Network (SDN) architecture and received a series of predefined time-triggered flows. They first proposed an Integer Linear Programming (ILP) formulation to address the problem of combining routing and time-triggered flows. Subsequently, the same authors proposed an increasing flow scheduling and routing algorithm in their paper16. This algorithm dynamically adds or removes flows by scheduling them one at a time. The authors propose the concept of a basic period, which is then divided into multiple time slots, each of which is large enough to traverse the entire network with Maximum Transmission Unit (MTU)-sized packets. And this results in too large a time slot being reserved for each stream, resulting in a large amount of wasted bandwidth. The network topology is large enough to introduce time delays with time-triggered flows traversing the entire network. Traditional switches mainly use queue-based "store-and-forward" mode for data exchange processing, where mixed service flows are scheduled in the switch’s "input queue" to different forwarding queues according to priority and then forwarded to the output queue. Inspired by Nayak’s scheduling of time slots for flows to avoid network queuing, we propose an SDN network framework to minimize the possibility of queuing. As shown in Fig. 17 who proposed TracForetime-LSH to perform short-term traffic flow prediction using traffic data detected from sensors.We design a low-latency routing algorithm for messaging between intermediate switch links and also for port data flow prediction to minimize queuing in the intermediate switches. This algorithm effectively eliminates packet loss due to queue overflow while maximizing the number of flows in the network and reducing the end-to-end delay of each flow.To guarantee low latency in the Industrial Internet, the network is traditionally organized by a dedicated Fieldbus network. For this purpose, several real-time Ethernet networks have been proposed, such as ProfiNET18. The SDN controller has the topology and global view of the switch, which helps realize the network control logic . The data plane of our network architecture consists of switches and end systems  that support the OpenFlow protocol. The edge SDN switches set priority queues. Based on time sensitivity and latency requirements, the controller divides each flow into specific time slots by the information collected from the flow. The edge switch transmits data to the intermediate switch according to the time slot. The SDN controller calculates the route for the streams from the intermediate switch, selects the best path, and sends down the flow table.Our network model is based on the software-defined networking (SDN) framework, as shown in Fig. 11. Therefore, the processing delay can also be regarded as a deterministic delay. For constant traffic, usually, the transmission delay in the network is bounded and definite. When data packets from multiple input ports are transmitted on one output port simultaneously, queuing occurs in the switch. If no two input ports compete for one output port, the source host will only initiate transmission when the traffic passes through a specific path on the network. This situation can be eliminated. Our proposed scheduling algorithm uses the controller’s global information about the network topology and the use of the southbound interface to collect information about various types of flows to define the appropriate transmission scheduling and routing. For example, in the topology shown in Fig. The focus of this paper is on routing and scheduling mixed service flows. Our goal is to realize deterministic network behavior and reduce latency in the network and jitter to support real-time communication. Network delays include four kinds of delays, propagation delay, processing delay, transmission delay, and queuing delay. The propagation latency is bounded, which is deterministic and very short, usually in nanosecond units. The processing delay of a commercial Ethernet switch is in the range of less than or equal to microseconds and is approximately constant for a given matched tupleWe proposed the following mathematical model for the network. In this approach, the scheduler can route flows to any other available path. The inputs are the topology of the network and the start and end positions of a series of flows that need to be scheduled. The variables are the flows that need to be scheduled. The goal of optimization is to maximize the number of flows to be scheduled and to minimize the end-to-end delay of the network.We propose a directed network topology diagram The topology of network,Characteristics of a series of streams to be scheduled The model requires the following inputs:We use decision variables to represent the mapping between flows and network links.The decision variable is as shown below:We formulate the objective function to maximize the number of schedulable flows while guaranteeing low latency. Therefore, we define the following:We assume a path i of the flow, which starts from the source host and ends at the destination host. The source host can only have one outbound link without an inbound link, and the destination host is the opposite. For other nodes on the path, the number of inbound links equals the number of outbound links.To avoid conflicts between different streams on the same link, no more than one stream is allowed on any one link.To ensure end-to-end deterministic latency, the total latency of each flow over all links cannot exceed the specified latency.19 can reduce the problem to an unconstrained linear programming problem. Some studies have found that heuristic algorithms about Lagrangian Relaxation techniques are attractive20. The basic idea is first to construct a weight and then use the Dijkstra algorithm to find the shortest path. By evaluating a large number of Lagrangian relaxation algorithms for solving delay-constrained problems, we found that the algorithms based on Lagrangian relaxation have low time complexity and a higher probability of achieving feasible or optimal solutions. However, the prime values of Lagrangian multipliers are critical to LR because they may make it difficult for LR to reach the dual optimum or cause a longer time to converge. The computation time of the Lagrangian relaxation method is a serious challenge when the problem size is large. The efficiency of the Lagrangian multiplier update determines the number of subproblems be solved. Traditionally, the Lagrange multipliers are updated using a subgradient-based approach. However, deriving the mathematical formula in the algorithm is very complicated. In the subgradient method, if the step size of the update iteration is not selected properly, it will often increase the number of iterations of the algorithm. The methods for updating the Lagrangian multipliers are finite, and the traditional Lagrangian relaxation algorithm may get caught in locally optimal solutions. BinSahaq et al.21 proposed a delay-constrained least-cost Quality of Service (QoS) routing approach to finding the optimal Lagrangian multipliers using the Lagrange Relaxation-based Aggregated Cost (LARAC) algorithm. This method operates in polynomial time and produces a theoretical lower bound. Its average path cost is smaller, but it runs slower. They only consider the routing computation task and do not address how to collect information about the network state and available network resources. For this reason, we propose an improved Lagrangian relaxation method that uses a particle swarm algorithm (PSO) to update the Lagrangian multipliers. The reason for using PSO is that it is simple and easy to implement22 and does not increase the complexity of the original algorithm. And this is faster, more accurate, and easier to converge than the sub-gradient method. Kamboj et al. have also proposed an algorithm to solve the Unit Commitment Problem (UCP) in the power industry23. However, unlike their approach, our proposed algorithm updates only one Lagrangian multiplier. Our algorithm is more concise and efficient in solving the scheduling problem.Many heuristic algorithms can be used when solving integer programming model problems. However, they are complex to implement and depend on the appropriate selection of parameter variance factors. Moreover, complex algorithms consume controller resources. The Lagrangian Relaxation algorithm (LR)We improve the Lagrangian relaxation algorithm with a particle swarm (PSO-LR):We use the Lagrangian relaxation algorithm to solve the problem described above. The original model is shown below.In the LR method, Lagrange multipliers are used to form the penalty terms. After introducing the Lagrangian relaxation operator, the above model can be rewritten as:The Lagrangian dyadic model can be expressed as follows.To maximize the Lagrangian function, the adjustment of the Lagrangian multiplier must be carefully performed. Most researchers have used the subgradient method to accomplish this task. However, the subgradient method tends to increase the number of iterations. Thus, we use the particle swarm optimization technique to tune the Lagrangian operator  in this article, the PSO algorithm is well adapted and simple in practical applications and enhances the performance of the Lagrangian relaxation method. The following is the algorithm flow.Step 1: Initialize the total number of particles Each particle is randomly generated in the allowed range.Step 2: Initialize other parameters we needed, such as population size, inertia weights, particle acceleration constants, compression factors, pairwise gaps, etc.Step 3: Use Step 4: Compare the value of each individual with its pbest. We denoted the best evaluation value in the pbest as gbest.Step 5: Alter the membership velocity Step 6: Update each λ position.Step 7: If each evaluation value brings better results than the previous pbest, set the latter to pbest. If the pbest is better than gbest, set the value to gbest.Step 8: We use the idea of dynamic programming to minimize the Lagrangian function for.Step 9: Use to Step 10: Use Step 11: The difference between the original problem and the pairwise problem (pairwise gap ε) is used as the termination criterion. The pairwise gap can be calculated by the following equation.Step 12: If the number of iterations reaches the maximum value, or the dual gap is less than the established threshold, go to step 13, if not, then go to step 3.Step 13: The individual generating the latest information has the shortest delay on each link while scheduling the most streams.The general flow of the algorithm can be described in Fig. The algorithm pseudocode is as follows.The advantage of using particle swarms to update the Lagrangian multiplier is that the PSO algorithm replaces the subgradient method for calculating the Lagrangian multiplier λ, simplifying the theoretical analysis and solution process. It is noteworthy that the presented algorithm has several feasible solutions superior to the original Lagrangian relaxation algorithm. In updating the Lagrangian multiplier λ using PSO, there are many other particles in addition to the optimal one. This provides more alternative models for solving multipath routing problems.Because of the limitations of the conditions, we configured the switch using Open vSwitch (OVS) and used Ryu as our SDN controller for the convenience of the experiment. We simulated PLCs, signal generators, and actuators with a host computer. We evaluated the algorithm performance using Mininet, an open source platform that uses virtualization on Linux to simulate real-world SDN. Mininet is capable of simulating various types of network components. For instance: computers, switches (layer 2), routers (layer 3), links, and other network elements. For each experiment, we use Mininet to generate topology randomly. The packets from the real-time stream are queued into separate queues in each edge switch. If the flow from a host exceeds the maximum rate set by each queue, we use ingress rules to limit traffic before it enters the switch.Netperf is used to create UDP traffic between the source and destination nodes for the stream Fi. Once we have configured the flow rules and queues, the controller assigns a time slot to each flow based on the information collected about the flow. It is sent to the edge switch by downlinking the flow table. The path rules for the streams are sent to the intermediate switch by flow table.To evaluate the effectiveness of the mixed flow , all nonreal-time streams use separate queues and are served in First In-First Out (FIFO). Since many commercial switches support up to 8 queues per port, in our experiments, we limited the number of real-time streams to 7. We experimented with a single port where each of the seven real-time streams used a separate queue, while the remaining eighth queue was used for non-real-time streams. Our stream rules segregate the two types of streams.Scheduling input:We take as input the network topology, flow information , and the maximum time slot window.Scheduling output:Stream sends time per node, arrival time per node in the path the stream travels, time of opening and closing of time slots at each switch egress port, end-to-end delay per stream.Our program and algorithms are programmed in the Ubuntu environment using Python, and the program is deployed to the SDN controller. And the data processing results are processed using MATLAB. For convenience; all links are communicated at 1 Gbit/s.We evaluate the average end-to-end delay for all flows in each test case, as well as the worst-case end-to-end delay, which is the maximum end-to-end delay in this test case, and the link utilization. We compare the proposed algorithm with the original Lagrangian relaxation algorithm, as well as with Dijkstra's algorithm, which is commonly used for traditional routing.To evaluate the performance of our proposed algorithm, we compared it with the Lagrangian relaxation algorithm (LR), Dijkstra's algorithm.The average delay indicates the time needed to transmit data from the source node to the target node. Figure Throughput indicates the amount of data successfully received by the destination in the required time. Figure Figure Figure This paper proposes the SDN scheduling framework and the improved Lagrangian relaxation algorithm. The proposed framework can reduce traffic queuing, ensure low delay in traffic transmission, and avoid data retransmission or packet loss due to conflicts in the transmission path of a certain number of scaled flows. Compared with traditional scheduling algorithms, our proposed algorithm can decrease the end-to-end delay by nearly 20% while transmitting more data streams under the condition of consistent network topology. Hybrid flow scheduling in networks is an NP-hard problem that has attracted much attention in the past few years. Here we modify the Lagrangian relaxation algorithm to satisfy the deterministic latency of the transmission network, which embeds the particle swarm optimization algorithm to obtain better performance. This study may have some possible limitations: (1) This study is mainly based on the same network domain. In the real scenario, traffic may be transmitted between different subnets. Scheduling flows between different network domains using SDN is the next topic we will investigate. (2) The experiments in this study are based on computer simulation so that the interference present in the real scenario is ignored. Due to the limited experimental environment, we can extend our work by deploying SDN networks to natural industrial Internet environments. Transport networks can profit from SDN innovations to support and deliver services of high quality.Supplementary Information.


Diabetes is one of the most prevalent diseases in the world, which is a metabolic disorder characterized by high blood sugar. Diabetes complications are leading to Diabetic Retinopathy (DR). The early stages of DR may have either no sign or cause minor vision problems, but later stages of the disease can lead to blindness. DR diagnosis is an exceedingly difficult task because of changes in the retina during the disease stages. An automatic DR early detection method can save a patient's vision and can also support the ophthalmologists in DR screening. This paper develops a model for the diagnostics of DR. Initially, we extract and fuse the ophthalmoscopic features from the retina images based on textural gray-level features like co-occurrence, run-length matrix, as well as the coefficients of the Ridgelet Transform. Based on the retina features, the Sequential Minimal Optimization (SMO) classification is used to classify diabetic retinopathy. For performance analysis, the openly accessible retinal image datasets are used, and the findings of the experiments demonstrate the quality and efficacy of the proposed method . The World Health Organization (WHO) assesses that 347 million people currently suffer from diabetes and that in 2030 this disease will be the seventh leading reason for death in the world . Over thThere are usually two types of DR, such as Proliferative DR (PDR) and Non-Proliferative DR (NPDR). As new blood vessels develop on the surface of the retina, PDR has the elements of neovascularization and vitreous fluid hemorrhage and can bleed. But there are no signs in NPDR and it can only are identified by the retinal image . The funThe typical retina image does not display any signs of DR characteristics, including retinal lesions, while blood vessels are clear without any leakage. In the case of mild NPDR, the micro-aneurysms are observed. During the moderate NPDR, there are microaneurysms, hemorrhages, damaged exudates, and blood vessels that can expand and distort. One of the signs will recognize severe NPDR: blockage of certain blood vessels in retinas, development of new blood vessels. The PDR damaged retina has the consequences of forming new blood vessels, which are neovascularization of an abnormal nature. It is developed at the back of the eye; as a result, the vision is blurry; it can burst or bleed .Many automatic DR detection techniques  were proThe principal cause of mortality for people living with diabetes is cardiovascular disease (CVD). While diabetes was previously considered a risk similar to CVD, the variability of this risk is gradually being recognized, with recent guidance available explicitly targeting diabetic patients providing risk evaluation . The incRetinal fundus images were often used to detect retinal diseases. Diabetic retinopathy disorders are observed by image processing algorithms. For the identification of hard exudates, cotton dots, hemorrhage, and microaneurysm lesions that arise in the initial stages of the disease, an algorithm focused on retinal image processing techniques and a decision support system was built in A method of identification for the five intensity stages of diabetic retinopathy has been developed in The work in Any retinopathy diagnostics model must measure the weights that give the patient's eye intensity level. The primary difficulty of this analysis is the exact judgment of thresholds for each functional level. Weighted Fuzzy C-means algorithm was used to define target level thresholds. The model should help determine the right degree of seriousness in diabetic retinopathy photos. The Deep Learning algorithms are effective in evaluating the properties of blood pressure, fluid loss, exudates, hemorrhages, and micro-aneurysms as well as other structural features of biomedical images . FeatureThis paper aims at the detection of DR determined from retinal fundus images. The contribution of this paper is as follows. At first, the ophthalmoscopic characteristics are derived from the photographs of the retina, as well as extracting local binary sequence, gray-level co-occurrence vector, run length, and adding certain morphological operations.The novelty of our proposed method is the use of the SMO classification algorithm, which has not been done before for DR recognition.The remainder of this paper is structured as follows. The “Materials and methods” section described the datasets used and the methodology applied. The “Results” section evaluates the results of the proposed methods. The “Conclusion” section summarizes the paper.This section explicitly details the processing of the diabetic retinopathy through the fusion of features from gray level co-occurrence matrix (GLCM) and gray level run length matrix (GLRLM) and Continuous Ridgelet Transform (CRT). Specific problems regarding feature extraction approaches are examined, and the proposed scheme is refined.The data image collection used for this analysis consists of photographs previously identified as normal (without DR) images and abnormal (DR) images with different stages like mild, moderate, and severe. Two openly accessible datasets such as DIARETDB1  and KAGGThe other retina data is extracted from Kaggle, which are retina scan images at APTOS 2019 Blindness Detection dataset. These images have a size of 224 This section explains the overall general workflow shown in , and alsMicroaneurysms and dot hemorrhages occur on the fundus as small lesions that characterize the ballooning of capillaries in which the vessel wall is weakened by the lack of pericyte protection and/or glial attachment. Hemorrhages and fluid release from microaneurysms contribute to intermittent edema which may leave heavy deposits of lipoproteins (“exudates”) in the retinal neuropile before reabsorbed .The GLCM defines the texture relationship between pixels by executing an action in the images based on the second-order statistics. For this operation, normally two pixels are used. The GLCM calculates the frequency defined by the variations of these pixel intensity values, which reflects the pixel-pair occurrence creation . The GLCAssign GLCM is expected to keep the probability of co-occurrence of any two intensities, rather than the count. And the GLCM values are translated to show probabilities. To that effect, to determine estimates, the number of times a given mixture of intensities occurs is determined by the overall number of potential results. A GLCM is converted into approximate probabilities as follows:here y values .The GLCM features used in this work are: autocorrelation, correlation, cluster shade, cluster prominence, contrast, difference entropy, dissimilarity, difference variance, energy, entropy, homogeneity, information measure of correlation, maximum probability, inverse difference, sum of average, sum of entropy, sum of squares variance, and sum of variance.GLRLM is a model representing texture that finds out the spatial plane characteristics of each pixel using high-order statistics. In GLRLM, statistics involved are the number of gray level value pairs and their length of runs in a region of interest (ROI). A gray level run is a group of pixels with the same value of the gray level, spread in the ROI in consecutive and collinear directions. The number of pixels is the length of gray level run in that particular set. Therefore, such a set is defined by a gray level value and the length of a gray level running mutually. GLRLM is a type of two-dimensional histogram in the structure of a matrix that records all the different combinations of gray level values and gray level.The gray level values and runs are conventionally indicated as row and column keys, respectively, of the matrix, thus the Suppose The idea of the latter is to display linear features image to point using Radon transform and the subsequent use of wavelet transformations. The result of this operation is an effective representation of two-dimensional functions with piecewise smooth areas separated by linear plots. The main difference between ridge functions and wavelet functions are that ridgelets are two-dimensional inseparable functions and determine not only the parameters of scale and shift but also their orientation in space . The CRTwhere here, In images, CRT can be calculated via Radon transform (RT). RT of a two-dimensional object where The Ridglet transform scheme is shown in Calculation of direct two-dimensional transformation Fourier (FFT2D).The application of forward Fourier transform from the rectangular grid of coordinates to the polar grid using the interpolation operation coefficients of the Fourier transform.The use of the inverse one-dimensional transform Fourier (IFFT1D) to each line of the obtained polar Noah grid. The result of this operation is the Radon transform coefficients.Application to the plane of the Radon transform of the one-dimensional wavelet transform (WT1D) along with a variable that determines the angle of the line produces the ridgelet coefficients.This section explains the proposed methodology for diabetic retinopathy detection. Preprocessing is the initial step of the image processing techniques. It is used to enhance the image quality which gives clear visualization. The preprocessing consists of image conversion, filtering, morphological operation, and segmentation. The retina images provided by ophthalmologists in the public repositories are shown in color format. The retina image is divided into the following channels in the image conversion step: Red, Green, and Blue . The greImage filtering is used to denoising the image. It is the method of eliminating noise from the retina images. Laplacian filter is used for image denoising. The Laplacian of an image shows regions with an accelerated change in intensity and is an example of a second-order or second type of enhancement derivatives. The discovery of the fine details of an image is especially good. A Laplacian operator can improve any function that has a sharp discontinuity. The Laplacian Morphological processing of images is a range of non-linear operations associated with the structure or morphology of features in an image. This technique investigates an image called a structuring feature with a specific outline or blueprint. The structuring factor is located in the picture at all possible positions and is contrasted with the respective pixel neighborhood . A morphTexture in feature extraction is the key characteristic of an image. Numerous methods for texture analysis are introduced in various fields of study. We use a fusion of textural GLCM and GLRLM features and Ridgelet Transform features.This is the last stage of the recognition process in diabetic retinopathy disease. After extraction of features, the retina fundus image is classified as normal, or DR. SMO  is a straightforward algorithm that uses only two Lagrange multipliers at each iteration to move the chunking process to the nearest possible expression. It determines the optimal value for these multipliers and updates the SVM until it fixes the whole QP problem. The benefit of SMO is that the optimization sub-problem can be solved analytically with two Lagrange multipliers.Detection of the diagnostic induced disease has its limits. When a device is prepared for a classification task, the issues are different. It would be able to work automatically by providing the system with proper classification instructions, which will have better classification performance. This study uses the SMO algorithm for classifying the DR.The performance analysis of the proposed system is explained in this section. The DR detection is implemented using MATLAB 2019b . This work is evaluated based on Sensitivity, Specificity, Accuracy and F-score computed as follows:Here TP is a count of true positive class , TN is the count of true negative class (DR). FP is the count of false-positive . FN is the count of false-negative class .The feature extraction time of the two data set is shown in We compare our results with the results of other authors, which used a wide variety of techniques from handicraft feature extraction and heuristic optimization methods to deep learning networks, achieved on the same datasets. The comparison is presented in On the DIARETDB1 dataset,  used conOur results demonstrate the competitiveness of our method with the state-of-the-art. On the DIARETDB1 dataset, our method achieved very good sensitivity, while considering the accuracy, only the methods of , and Al have achThe proposed method for the detection of diabetic retinopathy using the Ridgelet Transform and the Sequential Minimal Optimization (SMO) presents an alternative to recent works based on convolutional networks and deep learning. The achieved results are competitive with the state-of-the-art results while the common pitfalls of deep learning methods such as the need for very large datasets for training deep network models as well as the underfitting and overfitting problems are avoided. Moreover, the results provided by artificial intelligence methods are not explainable. As a result, any black box diagnostics systems are not accepted by a professional ophthalmologist in the real world, regardless of their fine results.The method presented in this article adopts a traditional approach. However, our approach is different from other works based on feature creation and classification. The proposed method also has some limitations as using all textural and Ridgelet features may include irrelevant features for the task of DR recognition, which can incur larger computation time, and sometimes even reduce the recognition accuracy. These limitations could be overcome by further fine-tuning the parameters of SMO technique.The integration of the extracted features using texture analysis methods (GLCM and GLRLM) and Ridgelet Transform features suggests an automated approach for classifying Diabetic Retinopathy (DR). The extracted features using the suggested approach are used for the process of classification using the SMO classifier to identify DR. The results show that the proposed method is competitive with other state-of-the-art methods on the DIARETDB1 and KAGGLE datasets . The obtained results show that image processing techniques combined with optimization methods can still be competitive to convolutional network and deep learning based approaches.10.7717/peerj-cs.456/supp-1Supplemental Information 1Code of implemented method (in MATLAB).Click here for additional data file.10.7717/peerj-cs.456/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj-cs.456/supp-3Supplemental Information 3Click here for additional data file.


The patch clamp technique underwent continual advancement and developed numerous variants in cardiac electrophysiology since its introduction in the late 1970s. In the beginning, the capability of the technique was limited to recording one single current from one cell stimulated with a rectangular command pulse. Since that time, the technique has been extended to record multiple currents under various command pulses including action potential. The current review summarizes the development of the patch clamp technique in cardiac electrophysiology with special focus on the potential applications in integrative physiology. Cardiac action potential (AP) is shaped by numerous ionic currents flowing in and out of the cell through the sarcolemma. The ultimate goal in cellular cardiac electrophysiology is to characterize the dynamics of individual ionic currents and understand how the interplay of these currents will draw the profile of the AP in different experimental conditions. There are two conceptually different methods to determine the profile of a given ionic current during AP. To accomplish this goal in the traditional way, we have to determine the magnitude of each discrete current from moment to moment during the AP. This step is followed by the reconstruction of the AP from the interplay of the individual actors. The traditional way employs rectangular command pulses mapping the channel kinetic parameters and the voltage dependence of the parameters. Based on this information, the profile of the current can be reconstructed during the AP with the help of computer simulation. The other approach, termed the AP clamp method, uses prerecorded AP command and measures the current profile directly during the AP in question. Current experimental methods allow the researcher to record multiple currents under the same AP. The goal of this article is to review the evolution of the voltage clamp method in a classical way employing rectangular command pulse to the sequential the AP voltage clamp technique. We aimed to compare the benefits and disadvantages of the methodical variations of these techniques with special emphasis on the integrative approach.The voltage clamp technique was developed by Kenneth Cole and George Marmont in 1947 to study giant axon electrophysiology . Silvio The primary research goal when using rectangular command voltage is to characterize the behavior of ion channels and understand how the changing membrane voltage modulates their function. The function of ion channels is determined by the conformation of the pore-forming protein. The transition between functional states  is governed by membrane potential changes. Using a series of rectangular command voltages  the kinetic properties  of a given channel can be mapped. Hypothetically, having all the channel parameters determined, the magnitude of the current can be predicted during any voltage change with an appropriate mathematical model . There iThe great quote “Measure what is measurable, and make measurable what is not so” attributed sometimes to Galileo Galilei, at other times to the French scholars Antoine-Augustin Cournot and Thomas-Henri Martin, could be a first-rate motto for this technique. This experimental method uses a “reverse approach” in order to determine the current profile directly during AP. To achieve this, a four-step protocol is employed. First, an AP is recorded from the cell in physiological ionic milieu under the current clamp mode. Second, the recorded AP is fed back to the amplifier as command voltage in the voltage clamp mode, and the compensation current is recorded. Under these circumstances, the compensation current will be a flat line with some minor artifacts before the upstroke caused by the exogenous stimuli in the previous step. In an ideal measurement, the compensation current will be zero because the cell membrane does not require any exogenous current from the amplifier to produce its own AP  results from changing the current magnitude during the AP. For a long time, nobody attempted to apply a second or third channel inhibitor upon the cell after the development of the effect of the first drug. The first report using multiple channel inhibitors in a sequential manner to record multiple currents in the same cell was published in 2011. The new method, named as “sequential dissection technique,” added only one innovative idea to the regular AP clamp method: multiple channel inhibitors were applied cumulatively, and the compensation current, recorded after the development of the effect of a channel inhibitor, was used as a reference current for the next compensation current . HypotheSeveral variations of the AP clamp technique are used in various labs these days. These variants employ different modifications in order to circumvent technical limitations or extend certain capacities of the method. Discussing all possible modifications within one single article would be an overambitious aim leading to the loss of the focus of our article; therefore, we restricted ourselves to outline the main variants only.SelfAP clamp) (bis(β-aminoethyl ether)-N,N,N’,N’-tetraacetic acid (EGTA) is added to the internal solution to buffer calcium in voltage clamp experiments. Buffering cytosolic calcium eliminates the contraction of the cell, increasing the lifetime of the seal. Using “physiological” internal solutions without calcium buffer leave the cell’s calcium cycling intact, and the cell will develop regular contractions during the experiment.Individual cells display distinctive APs with some degree of cell-to-cell variations. The selection of the AP influences the current profiles obtained in the experiments. Using the cell’s own AP is an obvious choice resulting in a decent, flat reference current in the first phase of experiments. This method is referred to as the self-AP clamp technique (P clamp) . The essP clamp) . AnotherUsing canonical  AP can prevent the error introduced by the cell-to-cell fluctuation and offers reduced variability for the recorded current . An undeKs or IKr, are recorded in the cardiac cells, it is practical to set the amplifier gain high in order to increase the resolution and record fine details of the current profile. Unfortunately, increasing the gain reduces the maximum output current of the amplifier. Therefore, high gain increases the chance to lose voltage control during the upstroke of the AP where sodium current may exceed 100 nA. The consequences are serious because the membrane voltage is uncertain until the control is not regained. There are two equally poor options here. If the amplifier gain is kept high, the resolution is maintained, but the clamp would be lost at the beginning of the AP. If the gain is set low, the voltage control is maintained, but the resolution of the recorded current is poor. The solution could make use of modified AP with a short, depolarizing voltage step  prior to the upstroke. This depolarizing step can inactivate the voltage-activated sodium channels allowing the amplifier to maintain voltage control during the whole AP , like Iwhole AP . Custom-whole AP .2+ modulation of ionic currents during AP in the cardiac myocyte  is obtained from a current clamped cell (Cell 2) or mathematical model . Then, t myocyte . First, ad libitum. During the data processing, any current can be determined by the subtraction of the compensation current recorded under the effect of its blocker from the previously recorded compensation current. Hypothetically (if the viability of the cell is appropriate), it is possible to record each current of the membrane during the AP. Kr. The reason for this distinction is that the selectivity of pharmacological inhibitors is sometimes debated. This further developed version of the self-AP technique allows the recording of multiple ion currents from the same cell . Before The quality requirements are exceptionally high to successfully perform onion-peeling experiments. Robust cells with stable membrane potential and AP are vital. Cell isolation is basically the same as in other single cell methods, but the storage media should mimic the physiological milieu. If any media with non-physiological ionic composition are used during the cell isolation, the exposition time should be minimized. The pH and osmolarity of the solution must be tightly controlled, and using membrane-permeable buffers is known to increase the robustness of the cells. The pipette solution used in these experiments should mimic the intracellular ionic milieu of the cell. Pipette resistance and noise should be kept low. Since the pipette solution contains no exogenous calcium buffer, each AP evokes contraction of the cell; hence, the seal must be sufficiently stable to survive hundreds of contractions during the experiment. The instrumentation  used in these experiments are basically the same as for any voltage clamp setup used for recording small (<1 nA) currents. A good external square wave/pulse generator is very useful in these experiments. Although most electrophysiology software offers the option of stimulating the cell with a rectangular pulse in current-clamp mode, adjustment of stimulation parameters is complicated. Old-fashioned external square pulse generators usually have control knobs that allow the experimenter to adjust any parameters without interrupting the actual experimental protocol.post hoc adjustment/optimization is often needed during the model construction. The AP clamp technique determines the current profile directly during the AP without later adjustment of the obtained data.Cardiac arrhythmias are the primary cause of death in the developed world. Pathological conditions that serve as a substrate for arrhythmias are consequences of complex changes in ion channels/transporters and calcium handling molecule function. The dysfunction of these systems leads to alteration of one or more membrane currents causing abnormal AP generation with resultant arrhythmias. To understand how altered membrane currents with the deformed AP cause pathological rhythm generation, one needs to understand the interaction of the individual ion currents during the AP. The traditional approach to achieve this goal was combining voltage clamp experiments with mathematical modeling. Choosing this method inherently assumes that it is possible to determine the sufficient number of parameters with the required accuracy with rectangular command voltages for each ion current to successfully reconstruct the AP with computer model. Since the parameters of the individual currents are obtained in different experiments, Ca,L, IKs, and ICl in guinea pig ventricular cells (K1 in ferret cardiac myocytes (Each ionic current has a characteristic profile/trajectory during AP termed as fingerprint. The AP clamp technique is suitable for economic screening of new drugs with unknown target(s). After having all ion currents mapped, the suspected drug-sensitive current can be identified in a single AP clamp experiment . Analyziar cells  and the myocytes  were claCa,L of epicardial and endocardial cells were compared with the traditional  voltage clamp technique, the voltage dependence, activation, and inactivation kinetics of the currents were found not statistically different. Interestingly, when the profile of ICa,L was determined as nisoldipine-sensitive current with the AP clamp technique, marked differences were observed between epicardial and endocardial cells  were analyzed and compared. Analysis results showed that some cells had large current density for all four currents recorded, while others had small ones. The values span a wide range; for example, the ratio of the largest and smallest nisoldipine-sensitive current was higher than 10. The difference could not result from the cell size because all current magnitudes were normalized to cell capacitance. Data showed that cells exhibiting large inward currents also had large potassium currents. The statistical analysis revealed linear correlation between the inward going charge carried by Ca2+ and the outward moving charge carried by the sum of potassium currents during the AP. Interestingly, the AP parameters  showed no correlation with the current magnitudes or the moving charge. These data provide the first observations to demonstrate that either large or small currents can generate similar APs as long as the inward going and outward going currents counterbalance each other in the cell. The possibility to measure multiple currents from the same cell has revealed hitherto unknown and unexpected characteristics of the ionic currents in myocardial cells. First, within a single cell, large outward current/charge movement is matched with large inward current/charge movement and vice versa; hence, the magnitudes of the depolarizing and repolarizing currents seem to be coordinated in such a way as to produce canonical AP, as seen in healthy guinea pig ventricular myocytes in this study. Second, there exists large variation in the current/charge movements between cells. These two findings suggest a more pluralistic view of cardiac cells. The magnitude of ionic currents can vary widely between cells, but the relative strength of the depolarizing and repolarizing currents is somehow constrained within a cell to produce similar APs. Variation and coordination of ionic currents in cardiac myocytes should have a significant impact on the AP and play important roles in arrhythmias.The onion-peeling technique allows to correlate AP parameters with membrane currents. In an earlier study, our team studied the membrane currents during the AP in guinea pig ventricular myocytes . Four cuKr and IK1 are the two chief repolarizing currents in the ventricular myocyte; the contribution of IKs to repolarization is minor. β-adrenergic stimulation is known to facilitate these currents in different extent. IKs is reported to be very sensitive to β-adrenergic stimulation; the sensitivity of the other two currents is less. In all previous studies, however, each potassium current was recorded from different cells and using different voltage clamp protocols. Thus, it remains unknown how β-adrenergic stimulation coordinately regulates these current in the same cell during AP. Previous experiments could not answer the question how β-stimulation changes the relative contribution of each potassium current to the repolarization reserve. Such knowledge is essential for designing antiarrhythmic strategies involving potassium channel blockers. Using the onion-peeling method, it became possible to measure and analyze the proportion of different potassium currents in the same cell during the AP in control condition and following β-stimulation  counterbalance each other during the ventricular AP. That is, robust linear correlation was found between the peak amplitude and the total moving charge of these two currents under various conditions. The correlation was present in young and old control animals and in a heart failure model as well. The correlation between these two currents was demonstrated after prolongation of the AP with anemone toxin II too. Additionally, the authors reported a strong correlation between the length of the AP and the current parameters . These correlations should be considered when building in silico AP models. Recently, The onion-peeling technique was used to explore the coordination between inward and outward currents in a recently published work by This review summarizes the development of the voltage clamp technique from the traditional version that applies rectangular command to the onion-peeling method. These new techniques widen the opportunities for exploring the function of individual ion channels as well as the coordination of membrane currents during AP. The onion-peeling technique is exceptionally suited for studying the interplay among the currents; thus, it has a unique potential in integrative physiology. It was developed for cardiac myocytes but can be adapted to the skeletal muscle or smooth muscle cells, neurons, and any excitable cell type where ionic currents and AP control cell function.BH, NS, CD, ZK, PN, YC-I, and LI contributed to conception and design of the work, literature search, and review of the text. TB contributed to conception and design of the work, literature search, drafting, writing, and figure design and drawing. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In this work, the optical properties of asymmetric nanoshells with different geometries are comprehensively investigated in the quasi-static regime by applying the dipolar model and effective medium theory. The plasmonic behaviors of these nanostructures are explained by the plasmon hybridization model. Asymmetric hybrid nanoshells, composed of off-center core or nanorod core surrounded by a spherical metallic shell layer possess highly geometrically tunable optical resonances in the near-infrared regime. The plasmon modes of this nanostructures arise from the hybridization of the cavity and solid plasmon modes at the inner and outer surfaces of the shell. The results reveal that the symmetry breaking drastically affects the strength of hybridization between plasmon modes, which ultimately affects the absorption spectrum by altering the number of resonance modes, their wavelengths and absorption efficiencies. Therefore, offsetting the spherical core as well as changing the internal geometry of the nanoparticle to nanorod not only shift the resonance frequencies but can also strongly modify the relative magnitudes of the absorption efficiencies. Furthermore, higher order multipolar plasmon modes can appear in the spectrum of asymmetric nanoshell, especially in nanoegg configuration. The results also indicate that the strength of hybridization strongly depends on the metal of shell, material of core and the filling factor. Using Au-Ag alloy as a material of the shell can provide red-shifted narrow resonance peak in the near-infrared regime by combining the specific features of gold and silver. Moreover, inserting a high permittivity core in a nanoshell corresponds to a red-shift, while a core with small dielectric constant results in a blue-shift of spectrum. We envision that this research offers a novel perspective and provides a practical guideline in the fabrication of efficient tunable absorbers in the nanoscale regime. LSPR represents the collective oscillation of conduction electrons at the interface between a metal NP and its dielectric surrounding excited by an incident electromagnetic field. These resonances can be easily observed as pronounced peaks in the optical spectrum occur at specific frequencies and can be tuned by changing the NP’s size, geometry, material and the surrounding medium. Depending on the NP size, scattering or absorption of incident light would be the main process. The large NPs scatter the electromagnetic wave, while the dominant process for NPs less than 6 and they are proper candidates for applications such as photothermal therapy (PTT), where the incident light is absorbed within the biological windows (700–1400 nm)8. In this technique, although the local temperature of tumor tissue reaches 42–47 9. In designing efficient nanostructure for PTT applications, one must consider both tuning the plasmon energies to the wavelength of the biological window and optimizing the NP for the largest possible light absorption cross-section.Currently, there is a great interest in the development of plasmonic nanoparticles (NPs) due to their fascinating optical properties, which arise from their localized surface plasmon resonances (LSPR), in a variety of fields ranging from physics to medicine12. These bi-functional NPs with an extra degree of freedom in LSPR provide high stability, low reactivity and surface modification by combining different chemical and physical properties of the core and shell parts16.To achieve new advances, more complex geometries which provide a high degree of tunability made by combining different materials and shapes are desired. Among numerous candidates, the most widely-used nanoshells composed of a spherical core surrounded by a concentric metallic shell (i.e. core–shells NPs) show much wider spectral tunability with energies being controlled by the interaction between the individual plasmon mode supported by the inner and outer surfaces (i.e. the cavity and solid plasmon modes)19. As a result, the higher order plasmon modes are excited and become visible in the optical spectrum of NP21. One can break the symmetry is giving the core an offset. For such “nanoeggs”, symmetry breaking is obtained by a displacement of the dielectric core with respect to the metallic shell23. The position of LSPRs as well as the number of higher order multipolar plasmon modes depend quite sensitively on core offset, so varying this parameter provides the tuning mechanism for this nanostructure.Compare to symmetric nanoshells, asymmetric ones can also provide further tunability due to a drastic change in the coupling of solid and cavity plasmon modes. When the symmetry of NP is broken, the selection rules are relaxed, so that the interactions between both different and same angular momentum numbers are allowed24, which can be characterized by its aspect ratio (AR), defined as the ratio between its major to minor radii. The electrons of nanorod can oscillate along the length and width of NP, hence, the optical spectrum of nanorod exhibits two distinct LSPRs corresponding to each individual electrons oscillation. Since the position of plasmon resonances is highly sensitive to the aspect ratio of the nanorod, high tunability of LSPR can be obtained by changing AR26. Besides nanoegg as a conventional tunable asymmetric NP capable of supporting multiple LSPRs, a new hybrid nanostructure that combines the optical properties of both nanoshell and nanorod, provides far greater structural tunability than either a nanorod or a nanoshell. Despite the intensity of efforts and publications, to the best of our knowledge, quantitative analysis of the asymmetric NPs, which simultaneously consider the effects of all important parameters, remains challenging.Another highly anisotropic tunable nanostructure is the nanorodIn this work, the optical properties of asymmetric nanoshells are comprehensively investigated by applying the dipolar model and effective medium theory. In addition, the hybridization method is employed to analyze related features to the absorption spectrum. Here, the effect of symmetry breaking on the optical response of nanoshell is explored from two points of view; the former is giving the core an offset, while the latter is induced by inserting a nanorod as a core of the nanoshell. The results indicate that LSPR frequency is significantly influenced by symmetry-breaking and it can be tuned either by varying nanorod aspect ratio or core offset. Moreover, to achieve an optimum absorption spectrum, three different metals  are considered as a material of the shell. Eventually, the effect of other critical factors including core aspect ratio and orientation of nanorod, core offset of nanoegg, dielectric function of the core, and filling factor are thoroughly analyzed. The rest of the paper is organized as follows: in “33.A key feature that characterizes the optical spectrum of hybrid nanostructures is the interactions between different plasmon modes at different surfaces of plasmonic metal. Even the simplest possible symmetry breaking can alter these interactions and give rise to modified, and altogether new, plasmonic features. Here, two types of symmetry breaking in nanoshells are considered. One is the core offsetting which means that the spherical core is displaced and the nanoshell has a non-concentric core; the other is changing core geometry which is generated by replacing the spherical core with a nanorod. It is worth mentioning that these nanostructures are proposed based on the recent nanofabrication techniquesa) and major (b) radii of spheroid and radius of the outer spherical shell The discussion initiates with the modal properties of the tunable asymmetric nanostructures capable of supporting multiple LSPRs. It is common to consider a nanorod as a spheroid in simulations. The spheroid is an ellipsoid with two equal axes that can look like either a stretched (prolate) or a flattened (oblate) sphere. Since the polarizability of nanorod sensitively depends on the orientation of nanorod with respect to the polarization of incident light, two distinct geometries are considered for this structure. The nanorod is treated as a prolate and oblate, when the polarization of light is parallel with its length or width, respectively. Figure mentclass2pt{minimmentclass2pt{minimmentclass2pt{minimmentclass2pt{minimd. If 34.In the first instance, the optical response of metallic NP depends on its characteristic size 35:To obtain the static dipole polarizability of nanoegg 37To find the static polarizability of spheroidal core in the nanoshell, the effective medium theory (EMT) can be employed. According to this analytical method, the hybrid nanostructure in a homogeneous medium is replaced by a single nanoparticle with an effective dielectric function. Using this theory, first the effective dielectric function for the entire nanostructure is derived, then a relation between the polarizability and the dielectric function through the Clausius–Mossotti relation is obtained38.The important parameters in the geometry of an ellipsoid are its depolarization factors. The three depolarization factors for any ellipsoid satisfy  by Eqs.  and 11)\document39:Once the effective dielectric function of NP is known, the dipole  by Eqs.  and 14)\document43:A is a dimensionless parameter for matching theoretical and empirical data, 44:From Eqs. , 9) and and9) an45. The dielectric constant of the core and host medium can be mentioned as other important parameters. Here, the core is made of silica and nanoshell is embedded in the aqueous environment. In the wavelength range of 300–1400 nm, the refractive index of Since, gold and silver in NP form exhibit the most interesting selective absorption in the visible and near-infrared regime, here, the optical properties of nanoshells in which the metallic shells are one of these two materials or their combination in the form of alloy, is investigated. The related data to the dielectric function of gold and silver are presented in Table 1f is the filling factor, defined as the ratio of the core to nanoparticle volumes) are identical for all structures. A spherical nanoshell with outer radius of 25 nm and filling factor of a, b) are  and , respectively. For all structures presented in this part, the metal and dielectric of choice are gold and silica, respectively. It is found that the scattering efficiencies are smaller than the absorption ones and most part of the incident light is absorbed by these small nanoshells. Therefore, only absorption spectra are presented in the next figures.Here, the optical response of nanoshell with different geometries including core-shell (CS), nanoegg (NE), core with prolate shape (PS) and core with oblate shape (OS), are investigated. For a reasonable comparison between different geometries of NP, the radius of the shell and filling factor  and the higher energy antibonding mode (ABM). The strength of hybridization between plasmon modes is controlled by the thickness of the metallic shell. The coupling between incident light and BM is strong due to a large net electric dipole moment of bonding mode,whereas there is a weak interaction between the optical field of light and ABM with an electric quadrupolar nature50.As one can see, two distinct plasmon resonance peaks can be observed in the spectra of CS, PS and OS; while the spectrum of NE exhibits three LSPR peaks.To understand this plasmonic behavior, the plasmon hybridization of solid and cavity plasmon modes can be applied to this geometry. According to the hybridization model, metallic nanoshell supports plasmon modes at the inner and outer surfaces of the shell which can interact with each other due to the finite thickness of the shellAs it can be seen from Fig. 51. This charge accumulation is influenced by the NP shape. Depends on the polarization of the incident light, charge separation on the surface of spheroidal NP is in two direction. Since the incident radiation is linearly polarized in the x-direction, the longitudinal and transverse plasmon modes are excited in the prolate and oblate, respectively. For more accurate discussion about charge accumulation, the surface charge density at the metal-dielectric interfaces of nanoshell, should be considered53. Surface charge density is calculated by applying Gauss’s law at the inner and outer surfaces of nanoshell21. Figure 55. When the electric field is transverse to the long axis of the spheroid  with different metallic shells  embedded in the water were calculated. Note that the dielectric function of alloy 58. Therefore, the resonance frequency and full width at half maximum (FWHM) of the LSPR can be modified as63. Since 64. Obviously, the amplitude of the absorption spectrum is roughly determined by absorption coefficient, n is extinction coefficient and refractive index, respectively. The detail of the Au fraction effect on BM LSPR wavelength, FWHM and absorption efficiency is presented in Fig. The results in Fig. 65. Here, only the bonding modes are analyzed because they are the most intense plasmonic modes in the optical spectra we are interested in; antibonding modes are not observable in the selected spectra (500–1000 nm).It is apparent that both the LSPR peak position and intensity of absorption spectra are significantly influenced by the dielectric properties of the core materials. Using magnetic core in nanoshell offers the unique advantage of a combination of magnetic and plasmonic properties. The most commonly used magnetic NPs in biological application are iron oxides, which have several different compositions, such as magnetite entclass1pt{minima67. Filling a lower dielectric medium in the core regions reverses the situation. In other words, a core with a high permittivity corresponds to a red-shift, whereas a core with small dielectric constant results in a blue-shift of LSPR. Compared to 68. Therefore, when the imaginary component of permittivity is not negligible, the intensity of the LSPR peak is weakened; the larger is the imaginary refractive index, the larger is intensity drop of the LSPR peak. It should be noted for 69.The results reveal that a difference in the values of the core dielectric constants leads to the shift of LSPR peak due to a modification of cavity plasmon mode which results in the change of the extent of the plasmon coupling. When the core region is filled by a higher dielectric medium, the effective dielectric constant of the core will be increased and results in a greater polarization of the dielectric medium. As a consequence, the accumulated charges in the resonance zone will attenuate and therefore, the restoring force can be reduced. This corresponds to the lower resonant frequency . This is why resonance peaks experience red-shiftedf) on the tunability of the resonance peak as well as the absorption efficiency is investigated by changing the core dimension while the total size of the nanoshell remains constant. For a complete comparison, the absorption spectra of metal-coated silica and hematite NPs embedded in water for CS, NE, PS and OS configurations are calculated and shown in Fig. f are increased from 0.31 to 0.77.The impact of the filling factor (f) is increased. Since these two modes exhibit opposite trends in the peak position displacement, it is concluded that well-separated LSPRs can be obtained at higher f. This trend is observed in the spectra of both f due to a relatively strong symmetry breaking in these structures. Moreover, the absorption efficiency of BM mode initially increases, reaches its maximum and then decreases. In addition, for MM resonance peak in NE configuration, the considerable red-shift alongside absorption reduction is observed in the spectrum by increasing the value of f.For all configurations, the results clearly indicate that the resonance peak at a longer wavelength shows a considerable red-shift, whereas the resonance peak at a short wavelength exhibits a slight blue-shift when the ratio between the core and NP volumes  in the quasi-static regime by applying the dipolar model and effective medium theory has been presented. The plasmon hybridization model is employed to explain the plasmonic behavior of these nanostructures. According to hybridization theory, the interaction of solid and cavity plasmon modes at the inner and outer surfaces of nanoshell results in the splitting of the plasmon resonances into a lower energy bonding mode (BM) and a higher energy antibonding mode (ABM). Additionally, the higher order plasmon modes can be excited and appear in the absorption spectrum due to the relaxation of selection rules of plasmon interactions. The strength of this coupling is remarkably altered either by changing the geometry of the core to prolate or oblate or by offsetting the spherical core. In comparison with CS, the considerable red-shift alongside absorption reduction is observed in the BM mode of PS and OS, while the shift of ABM modes is slight. For the case of nanorod as the core, the results indicate that the coupling between plasmon modes of OS is stronger and the energy gap between BM and ABM is larger. The absorption spectrum of OS shifts toward the higher wavelengths at the near-infrared regime. Moreover, the ABM mode of OS is also enhanced due to its large electric dipole moment. On the other side, although the red-shift of PS is not as large as OS, LSPR is much narrower than the one for OS. For NE, besides BM and ABM, another resonance mode (MM) emerges in the spectrum as a result of coupling between the cavity and plasmon modes with different angular momenta. In addition, the bonding mode of NE is also red-shifted and its absorption is decreased, compared to CS. Furthermore, the absorption spectrum of asymmetric nanoshell can be further tuned over the wider spectral region either by changing the aspect ratio of nanorod or core offset of nanoegg. Based on findings, a larger aspect ratio correlates with a larger shift in the spectrum. Similarly, a larger core offset leads to a larger red-shift of the spectrum.It is also found that the optical response of nanoshell significantly depends on the material of the shell. In contrary with the silver-coated nanoshell which provides narrow LSPR at shorter wavelengths with high absorption efficiency, the more broaden LSPR with less absorption of gold-coated NP occurs at longer wavelengths. Combining gold and silver as the shell material is a good method to merge the advantages of both gold and silver in single NP. In addition, the absorption spectrum is tuned over the wide spectral range by changing the percentage of gold or silver in the alloy. When Au content in the alloy increases, the spectrum gets red-shifted and absorption efficiency is reduced. The same trend is observed in the spectra of all geometries; CS, NE, PS and OS.One of the effective parameters to modify the hybridization is the dielectric function of the core since it determines the cavity plasmon mode energy. Therefore, changing the material of the core leads to a change in the optical response of nanoshell. Inserting a high permittivity core in the nanoshell corresponds to a red-shift, while a core with small dielectric constant results in a blue-shift of bonding mode. On the other side, using a magnetic core (magnetite and hematite) with a complex dielectric function in the metallic nanoshell can unite the plasmonic and magnetic properties in a single NP. The larger red-shift is observed in the spectra of magnetite and hematite due to their large real refractive indices. At the same time, the absorption intensities of LSPR of magnetic NPs are remarkably lower than one of the silica-core nanoshell due to the decrease in the strength of hybridization between solid and cavity plasmon modes as a result of dampening the cavity plasmon modes by their imaginary part of dielectric functions.Finally, it is observed that there is a significant red-shift in the resonance peaks at longer wavelengths as the filling factor increases, while the resonance peaks at short wavelengths exhibit a slight blue-shift. This trend is observed in the absorption spectra of all reported NPs. These findings open a new route to optimize the synthesis of hybrid nanostructures in various applications as far as absorption is concerned.