Drug delivery for tumor theranostics involves the extensive use of the enhanced permeability and retention (EPR) effect. Previously, various types of nanomedicines have been demonstrated to accumulate in solid tumors via the EPR effect. However, EPR is a highly variable phenomenon because of tumor heterogeneity, resulting in low drug delivery efficacy in clinical trials. Because ultrasonication using micro/nanobubbles as contrast agents can disrupt blood vessels and enhance the specific delivery of drugs, it is an effective approach to improve the EPR effect for the passive targeting of tumors. In this review, the basic thermal effect, acoustic streaming, and cavitation mechanisms of ultrasound, which are characteristics that can be utilized to enhance the EPR effect, are briefly introduced. Second, micro/nanobubble-enhanced ultrasound imaging is discussed to understand the validity and variability of the EPR effect. Third, because the tumor microenvironment is complicated owing to elevated interstitial fluid pressure and the deregulated extracellular matrix components, which may be unfavorable for the EPR effect, few new trends in smart bubble drug delivery systems, which may improve the accuracy of EPR-mediated passive drug targeting, are summarized. Finally, the challenging and major concerns that should be considered in the next generation of micro/nanobubble-contrast-enhanced ultrasound theranostics for EPR-mediated passive drug targeting are also discussed. Solid tumors exhibit a special microenvironment featuring tortuous vascularity, angiogenesis, and hypoxia However, numerous parameters  prevent the successful application of EPR-based theranostics in clinical applications because of tumor heterogeneity In recent years, various nanomaterials based on the EPR effect have been used because the sizes of these nanomaterials can be modulated according to the pore sizes in tumor blood vessels. Because different types of tumors have different sized gaps in the endothelial cells, a suitable nanoparticle size must be selected according to the type of tumor. Furthermore, the interception by biological barriers when nanomaterials enter the circulation system also needs to be considered. Particularly, nanoparticles should not be destroyed by the reticuloendothelial system (increased particle size) while maintaining the ability to penetrate the tumor (reduced particle size) In view of these challenges, to best leverage the EPR effect in nanomedicine delivery, various diagnostic and therapeutic strategies have been developed Figure . To moniTo enhance the efficacy of delivery, three approaches based on the EPR effect have been developed. The first approach involves exerting physical exogenous factors light , 43 to p2 is generally referred to as high-intensity ultrasound, while that with an intensity between 0.5 and 1 W/cm2 is usually considered to be low-intensity ultrasound. In clinical ultrasound imaging, the output levels of the ultrasound equipment can be quantified using the mechanical index (MI) defined by the U.S. Food and Drug Administration (FDA). MI is expressed as the ratio of in situ peak negative pressure (PnP) to the square root of the center frequency (Fc), as shown in Equation (1):Acoustic transducers are used to generate transverse or longitudinal waves with frequencies greater than 20 kHz. Medical ultrasound is characterized by a broad frequency range of 0.1-50 MHz and peak negative pressures of 0.01-10 MPa. It can be classified into focused and unfocused ultrasound depending on the radiation distribution of transducers. It can also be characterized into continuous and pulsed ultrasound depending on the waveform and with parameters such as pulse length and pulse repetition frequency. When used in biomedical applications, the acoustic densitometry of ultrasound can be expressed in the following manner. Sonic intensity can be defined as the time-averaged rate of sonic energy-flow through unit area In general, the maximum output levels of diagnostic devices are limited to an MI of 1.9, which is the maximum allowed value for clinical imaging applications without microbubbles When ultrasonic energy is applied for the diagnosis and treatment of tumors, acoustic waves can be used to enhance the EPR in two ways: drug release and bioeffects. During drug release, ultrasound can stimulate the carrier to release its cargo and increase the distribution concentration of drugs in the tumor. The efficiency of drug release is controlled by acoustic parameters such as ultrasound frequency, power density, and pulse duration 2 can promote the platelet penetration of gold nanoparticles (GNPs). The results indicated that ultrasound can enhance membrane permeability, which has been proved using scanning electron microscopy (SEM) and transmission electron microscopy (TEM).For bioeffects, the use of acoustic energy with EPR mainly focuses on the enhancement of cell membrane permeability 2) is known to be non-thermal, and this may be regarded as the boundary between mechanical and thermal effects.Besides, acoustic waves interact with drug carriers, body tissues, and cell membranes via a combination of thermal and mechanical effects The mechanical effects of ultrasound and MNB-assisted ultrasound on EPR are based on both acoustic radiation forces and mechanical bioeffects.Because of the momentum exchange between the object and the sound field, an acoustic wave can move suspended micro-objects by exerting a force known as the acoustic radiation force (ARF) via the ''primary''  sound field is called the primary Bjerknes force and can be expressed as Equation (2). Assuming that the microcapsules are spherical and placed in an ideal plane ultrasonic wave, the force acts to propel the capsules in the direction of acoustic propagation as per the following equation:The various forces that act on an air bubble in a sound field are often referred to as Bjerknes forces P is the mean energy density of the incident wave, Yp is a dimensionless factor known as the radiation force function that depends on the scattering and absorption properties of the capsule, and r is the radius of the capsule.where The force between two bubbles that is caused by the ''secondary'' sound fields emitted by other bubbles is known as the secondary Bjerknes force V1 and V2 describe the volume of the first and second bubbles, respectively, and er denotes the radial unit vector. The mutual interaction forces between two small coupled gas bubbles (R0<10 μm) in a strong low-frequency acoustic field  have been investigated in a previous study 3-106 than that expected from linear approximations.where < > denotes the time average, ρ is the density of the liquid, d is the distance between the first bubble and the second one, The EPR effect would be considerably increased if the agent was initially concentrated in a particular region, and if the velocity of the agent passing the potential binding site was decreased. Dayton et al. in vitro low-frequency sonophoresis Acoustic streaming is defined as the radiation force from reflectors and scatterers in an ultrasonic field that can cause local particle displacements and fluid currents. The movement of localized fluid currents in the direction of the propagating ultrasound radiation forces that are induced by sound waves is termed bulk streaming. Microstreaming involves localized eddies or currents that are generated next to cavitating bodies. The differences between bulk streaming and microstreaming are shown in Figure With the same acoustic-pressure amplitude, the maximum streaming velocity of ultrasound contrast agent (UCA) microbubbles is achieved under the action of resonance frequency. The velocity fields of the streaming sonicated UCA microbubbles were measured using particle image velocimetry (PIV) in a blood vessel model Gas-filled bubbles show different oscillation performances when acoustic parameters such as the pulse length, amplitude, and frequency are varied. The stable cavitation (SC) of UCAs is usually accomplished at low sound pressures (<0.1 MPa). When exposed to sufficiently large acoustic rarefactional pressure amplitudes, UCAs undergo a violent collapse known as inertial cavitation (IC) The difference between SC and IC is due to the different degrees of bubble deformation under ultrasonic irradiation. Many models have been developed to describe the deformations that can occur on the surface of a coated bubble because of oscillation. Marmottant et al. For US-induced SC or IC of MNBs, MNBs are either excited, causing them to oscillate and mechanically massage the vascular wall, or are destroyed, generating micro-jets. These mechanical effects can lead to the creation of pores in the cell membrane. The opening of the inter-endothelial junctions contributes to an enhancement in the vessel permeability and improves the extravasation of co-administered drugs MNB-mediated sonoporation occurs because of the physical perturbation of cellular structures The enhanced efficiency can be evaluated through the accurate measurement of the spatial and temporal scales of these pores. Some methods are available to measure these pores. SEM and atomic force microscopy (AFM) have both been employed to obtain information about pores When a blood vessel is located near the focal spot, a part of the acoustic energy is absorbed and converted to thermal energy. Tissues may have different sensitivities to ultrasound-induced damage. This sensitivity to the effects of ultrasound-induced heating has primarily been studied by Stanley et al. Ultrasound energy can be absorbed and transformed into thermal energy in tissues as the acoustic waves propagate through the tissue and generate friction Estimating the efficiency of the temperature rise caused by radiation of ultrasound is critical. When the distance between the surface of the blood vessel and the focal point is 2.5 mm, the temperature at the focal point was saturated after approximately 50 s of radiation, and the maximum cooling caused by the blood flow was approximately 0.5 °C when the supply of radiation was ceased MNBs comprise a gaseous core encapsulated in a shell of biocompatible materials such as lipids or proteins, typically ranging from 0.1 to 10 μm in diameter. When exposed to ultrasound, MNBs can contract and expand, which may result in backscattering of the ultrasound, cavitation, or even bursting of the shell. Because of these acoustic behaviors, MNBs have been extensively used as UCAs and have shown increasing potential for drug delivery. Under low-intensity ultrasound irradiation, MNBs can be used as contrast agents in ultrasound imaging for EPR evaluation. Through high-intensity ultrasound-mediated cavitation, EPR mediated therapy can be improved with enhanced drug delivery.The materials of the encapsulated gas and shell together determine the physicochemical properties of a bubble. The transport properties of the encapsulated core gas mainly affect the stability of the bubbles. Air and bioinert heavy gases such as sulfur hexafluoride or perfluorocarbons are often used in commercial UCAs found in clinics. One approach to increase the stability of UCAs is to use insoluble gases. For example, perfluorocarbons have a higher resistance to water permeation than to air  via shell modification and bubble aggregation. Research has shown that NBs are more stable and exhibit a longer circulation time than MBs via the EPR effect. Compared with MBs, NBs can penetrate the sites where tumor vascular leakage takes place via EPR and can accumulate in the tumor. The gaps between the endothelial cells in tumors, therefore, allow passive targeting with NBs. Fluorescent dye-labeled NBs have been found in the intracellular spaces of tumor cells In vivo studies have confirmed the ability of NBs to passively target tumor tissues via the EPR effect The performance of MNBs primarily depends on the physicochemical properties of the shell material. Proteins, polymers, and lipids are mainly used as shell materials for bubbles. The echogenicity of MBs and NBs is significantly different because of the size difference. MBs possess good echogenicity and have been widely used for ultrasound imaging. A reduction in the size reduces the acoustic response of the bubble The mechanical effects that ultrasound-mediated MNBs have on the EPR are associated with the process of cavitation, which is mainly due to the oscillation of gas-filled bubbles in an acoustic field. MNBs have different responses to external stimulation based on the features of the applied ultrasound, as shown in Section 2 in the review. Under diagnostic frequency and low sound pressure (<0.1 MPa), bubbles expand and contract with a small amplitude, and the generated energy is low enough to form an SC. This regular oscillation can echo the ultrasonic wave utilized by ultrasound imaging. The SC can create a circulating flow of fluid around the bubble, which is known as microstreaming. Under higher sound pressures (>0.1 MPa), the oscillation of the bubble becomes nonlinear and the expanded diameter is much larger, causing the microbubbles to oscillate drastically. When the sound pressure exceeds a certain threshold, the bubbles instantaneously collapse to release strong jets, shock waves, and shear force (IC). Both SC and IC lead to the creation of pores in the cell membrane and the opening of interendothelial junctions, thus enhancing vessel permeability and improving the extravasation of co-administered drugs via MNBs changes the vascular and cell membrane permeability of a tumor. Both SC and IC can cause mechanical disturbance to the vessel walls and cell membranes in cancer tissue, thus improving the EPR effects in the tumor. The application of ultrasound to vessels containing MNBs can change the permeability of the blood vessel wall, resulting in the extravasation of drugs into the interstitial space. The change in the permeability of the capillaries depends on various factors, including shell composition, bubble size, the ratio of capillary diameter to bubble diameter, and ultrasound parameters. In addition to changing the permeability of the blood-vessel wall, the cavitation of MNBs can enhance the permeability of a cell membrane. The collapse of a bubble and the associated production of a jet can instantly break adjacent cell membranes. Small holes are produced within a cell membrane, resulting in either repairable or non-repairable sonoporation. With different ultrasound parameters, short-lived pores are produced within the cell membrane and exogenous materials can thus be transported into the cytoplasm. The collapse of MNBs can also cause cell death in the tumor tissue, which further alleviates solid stress and can reduce the barriers to deeper penetration. Studies have shown that cavitation effects can alter vascular and cell membrane permeability through three different mechanisms: (1) During the regular mechanical disturbance of the oscillating bubbles undergoing SC, the cell membrane potential is changed to promote endocytic uptake Inducing cavitation 3O4 nanoparticles ruptured and released the nanoparticles into the cells under exposure to ultrasound. The results showed that cells internalized the Fe3O4 nanoparticles released by the MBs most efficiently at 1 MHz and 0.25 MPa. The pores in the cell membrane can be simultaneously repaired by the lysosomal membrane associated protein (LAMP-1). When the sound pressure exceeded 0.25 MPa, the severe nonlinear oscillation of the microbubbles may have caused permanent damage to the cells. It has been found that high-intensity focused ultrasound combined with microbubbles can open the blood-brain barrier (BBB), which provides a means for treating brain tumors. Pulsed US causes less negative biological interactions with healthy cells and tissues not intended for treatment Cavitation is directly affected by various factors, such as ultrasound frequency, intensity, and the length of US pulses, which in turn influence the EPR in the biological tissues or cells. Low-frequency ultrasound (20-100 kHz) can penetrate the tissues deeper than high-frequency ultrasound (1-3 MHz). Transdermal transport and cell penetration are enhanced as the US frequency decreases In addition to cavitation, MNBs can also generate other biological effects, such as thermal effects, under the guidance of high-intensity ultrasonic energy. These biological effects work together to temporarily enhance the permeability of biological tissues and blood vessels, allowing the active substances carried in the MNBs to enter the tumor tissue more easily through the EPR effect, which is the theoretical basis of ultrasound-assisted MNB-enhanced EPR.The high heterogeneity of EPR among individual patients is considered a major barrier to the clinical application of nanomedicines. In preclinical validation, drug delivery systems generally work very well, with significant improvements in both target site accumulation and therapeutic efficacy. Clinically, however, the efficacy of passive tumor-targeted nanomedicines is compromised because of the large inter- and intra-individual variability in EPR. Significant increases in tolerability but hardly any increases in efficacy have been seen in clinical therapy Ultrasound contrast imaging is a simple, non-invasive imaging modality used to evaluate vascular conditions. However, tumors are characterized by tortuous vascularity, angiogenesis, and hypoxia. To address these problems, different strategies for MNB-enhanced ultrasound imaging based on EPR have been developed. One important factor to be considered in ultrasound imaging is the accumulation of MNBs in tumor tissue. As mentioned above, NBs of an appropriate size can penetrate the leakage sites of tumor vascular tissue. EPR-mediated passive targeting can result in the accumulation of NBs in the tumor. However, the enhancement of ultrasound imaging by nanobubbles is reduced relative to microbubbles Although MBs cannot pass through blood vessels and enter tumor tissue, efforts can be made to allow them to accumulate around the blood vessels of the tumor. Angiogenesis is a remarkable characteristic in the tumor microenvironment. Endothelial cells and receptors associated with angiogenesis are readily accessible for targeting with MBs. The conjugation of ligands onto the surface of MBs has already been proven successful for MB accumulation in tumors for imaging purposes. It has been reported that a better ultrasound signal was detected from MBs in angiogenic areas after the conjugation of arginylglycylaspartic acid (RGD) peptides onto the MB surfaces via the inflow of MBs using US Another important factor in contrast ultrasound imaging for EPR characterization is to identify the correlation between the imaging parameters of tumor blood vessels and drug accumulation in tumors. A US-based assessment of tumor vascularization can potentially be used to predict the efficiency of passive tumor targeting. EPR assessment based on ultrasound imaging is simple, general, and easily transformed for clinical use. In an exemplary preclinical study MNBs can act as carriers for therapeutic payload delivery. Therapeutic payloads including therapeutic gas, targeting ligands, drug molecules, and nanoparticles can be loaded into the bubble.The delivery of drugs used for chemotherapy suffers from many problems including severe side effects and the resistance of tumor cells  via the enhanced EPR effect. NPs are often loaded into the shell of MNBs and delivered to tumor cells in a process controlled by ultrasound. A typical example is the delivery of superparamagnetic iron oxide (SPIO) NPs through MNBs. Different types of bubble related carriers including magnetic microbubbles in situ microbubble generation. Combined with US, SPIO NPs were locally released at the tumor and taken up by the tumor cells though EPR effects. These bubble-based magnetic carriers offer an attractive possibility for clinical MR imaging, hyperthermia, and the magnetically targeted release of therapeutic agents for cancer.Nanoparticles (NPs) such as gold and superparamagnetic iron oxide NPs are widely used in tumor diagnosis and treatment. The delivery of these NPs at the tumor-specific site is a challenging task. Small nanoparticles (<5 nm) can be rapidly removed from vessels by renal clearance or uptake by the liver, whereas large particles (>200 nm) are removed by the spleen or the reticuloendothelial system (RES) 2), nitric oxide (NO), hydrogen sulfide, and carbon monoxide have important physiological roles or can elicit biological responses. Therefore, they have significant therapeutic potential 2 nanobubbles for spontaneous oxygenation in response to the tumor microenvironment 2 level can be significantly increased by the O2 released from O2 nanobubbles that have been passively accumulated within the tumor because of the EPR effect. NO plays a critical role in vascular physiology and cancer biology. At low concentrations, NO promotes tumor cell growth by stimulating angiogenesis, while at high concentrations, NO is cytotoxic and may be a useful chemotherapeutic agent Gaseous molecules including oxygen  with phase-change ability, which undergo a liquid-gas phase transition under LIFU irradiation The “small to large” strategy is mainly used in EPR targeting to overcome the contradiction between particle size and the sound intensity of the contrast agent. Nanobubbles exhibit The "big to small" strategy is mainly used to help microbubbles bypass the EPR effect and release drugs at the tumor site. Micro-sized bubbles are good angiographic contrast agents and drug carriers, but they cannot penetrate blood vessels to reach the tissues. If MBs can somehow be made smaller to become nanobubbles after reaching the tumor blood vessels and completing the imaging function, they could spread across the vascular barrier and into the tumor tissue to be used for further tissue imaging and drug release. Huynh et al. reported a method used for the conversion of microbubbles to nanoparticles using low-frequency ultrasound, as shown in Figure Therefore, through the delicate design of the bubble structure and the appropriate introduction of external triggers, a new size-controllable theranostic agent with ultrasound enhancement effect and tissue penetration ability can be constructed to evaluate and enhance the EPR effect.in-situ generation of bubbles in a solid tumor. These types of stimuli are usually endogenous and are closely related to changes in the tumor microenvironment. Agents that are responsive to such stimuli are encapsulated in nanocarriers, which accumulate at the tumor site through the EPR effect. Stimuli are then applied, thus triggering the generation of gas free bubbles at the tumor tissue. The advantages of this in situ generation strategy are as follows: (1) The bubbles generated in situ at the tumor site do not need to be transported through blood. They can, therefore, avoid various biological barriers in the human body and can also bypass the requirement for EPR in changing the bubble size. (2) The generation of bubbles enhances the ultrasound imaging effect at the tumor site, which is conducive to diagnosis. If the generated gas can also be used for treatment, targeting, diagnosis, and treatment can be integrated.Different types of stimuli have been reported to trigger the 2O2 is an ROS and a diagnostic marker in the development of certain diseases. Studies have found that Prussian blue nanoparticles have a catalase-like function in neutral environments, catalyzing H2O2 to produce oxygen For example, the production of reactive oxygen species (ROS) is much higher in cancer tissues than in normal tissues. HIn the above studies, the aggregation of bubbles and release of drugs in the target region were mainly dependent on various exogenous and endogenous stimuli and were not caused by specific active targeting. EPR and the (over-) expression of angiogenesis-related surface receptors are key features of tumor blood vessels. As a consequence, EPR-mediated passive and ligand-based active targeting have attracted considerable attention. Kunjachan et al. visualized and quantified passive and active tumor targeting using RGD- and NGR-modified polymeric nanomedicines Rapid and efficient early binding of MNBs to the blood vessels of the tumor occurred through vascular targeting, but passive targeting was significantly more efficient over time. These results indicate that a combination of passive and active targeting is required for effective tumor imaging and therapy. Based on the above ideas, a multi-gradient targeting strategy has emerged. Multi-gradient targeting strategies refer to the further coupling of specific targeting factors on MNBs to combine active targeting with EPR-mediated passive targeting. When such MNBs are intravenously injected into the body, they become actively enriched in the tumor blood vessels under the action of specific targeting ligands, contributing to clearer ultrasound imaging. Following the application of an ultrasound field or various other internal and external sources of stimulation, the structure and/or the size of the MNBs changes. On the one hand, this change triggers various biological effects, which affect the permeability of the tumor blood vessels and enhance the EPR effect. On the other hand, the drug is released, forming a high drug concentration gradient in the microcirculation of the tumor tissue, efficiently allowing the drug to enter the tumor tissue for treatment by virtue of the EPR effect.2β1, α5β1, α6β1, and αbβ3, and the glycoproteins, GPIb-IX-V and GPV, which can naturally target injured vasculature Several classes of ligands have been conjugated onto the surface of UCAs to achieve better targeting of tumor cells, including peptides, aptamers, and affibody molecules. These targeting ligands allow the UCAs to remain at a size at which the EPR effects can be exploited Active targeting can be performed by modifying bubble shells using a range of targeting ligands; such bubbles can therefore be applied in different types of cancer. There are several strategies that allow the binding of ligands to the bubble shell. First, avidin or streptavidin is commonly used for non-covalent attachment of biotinylated ligands onto the shell materials in situ around the tumor rupture and the nanoscale SPIOs with associated RGD-l-TRAIL molecules can travel through the blood vessels and enter the tumor tissue because of the tumor ligand induced integrin αvβ3-receptor-mediated endocytosis. At this stage, the tumor tissue can also be imaged using MRI. With the accumulation of RGD-l-TRAIL and SPIOs in the tumor tissue and cells, tumor apoptosis induced by TRAIL molecules can also be observed during this process; therefore, this process involves nanoscale targeting and diagnosis. The multi-gradient targeting drug delivery system has a reasonable structure, an adjustable drug dosage, and a clear target. It is a typical example of applying a multi-gradient targeting strategy for in vivo diagnosis and treatment.Multi-gradient targeting can be applied to both microscale and nanoscale bubbles. Nanoscale bubbles modified with targeting ligands are good carriers. Li et al. reported that the soft biodegradable glycine/PEG/RGD-modified poly (methacrylic acid) nanobubbles can be applied as intelligent theranostic vehicles for drug delivery In addition to the ultrasound field, external factors including light, magnetic fields, radiation, and microwaves affect EPR. Internal factors such as pH, high concentrations of active oxygen, and various special cytokines are provided by the special pathological environment of the lesion. The mechanism by which each factor affects the EPR is different. Combining multiple energy fields can exert the combined effects of all of the different mechanisms to obtain an optimized and enhanced EPR effect.Local heating of the tumor site tends to increase the accumulation of nanomedicine, resulting in more effective intratumoral drug delivery. Hyperthermia enhances the increase in nano drug delivery within tumors because of the increased blood flow to the tumor caused by vasodilation. This increased vascular permeability is due to the increased intercellular space between endothelial cells 2O2 and gluconic acid. The magnetic nanoparticles in the microcapsule shell then move under the action of the external magnetic field to generate gaps in the membrane, and the internally loaded L-arginine further reacts with the H2O2 to form NO. Therefore, it is apparent that through the dual response of the microcapsule structure to glucose and magnetic fields, high concentrations of glucose can be reduced and the generated NO gas can enhance the ultrasound imaging and the EPR effect, thus treating the disease. In addition to responding to external magnetic fields, the SPIO in the system also functions for MRI imaging. This system can be used as a multifunctional carrier platform for the effective regulation of blood glucose.The strategy of combining internal and external stimuli is also beneficial. Yang et al. Liu Yang et al. There are also multifunctional carrier systems with sophisticated designs that combine lasers, heat, radiation, and other external and ultrasonic fields to improve the permeability of tumor blood vessels and tissues and deliver drugs effectively.The ideal process for tumor diagnosis and treatment based on the EPR effect is shown in Figure in situ generation" strategy to generate bubbles in situ using the specific microenvironment of the tumor to create ultrasound contrast with which to evaluate the EPR.Around the process of tumor diagnosis and treatment and applying the four strategies mentioned, the potential of MNBs can be described in detail, as seen below in Figure Second, for patients with low EPR levels, MNBs can be combined with internal biochemical triggers and external energy fields to enhance the EPR effect using various strategies, as shown in Figure In addition, while enhancing the EPR effect, various energy fields can mediate the gradual disintegration of the structure of MNBs, releasing the various active substances the MNBs carry, including drugs, other nanoparticles, and therapeutic gases. These active substances are enriched in tumor tissues by the enhanced EPR effect and lead to further therapeutic or real-time imaging functions.In the complex and variable micro-environment of a living organism, the key to effective treatment is drug components reaching a lesion efficiently and exerting continuous therapeutic effect. The nano carrier targeted drug delivery system, based on EPR, is one way to effectively improve the anticancer effect of drugs. In recent decades, various forms of multifunctional carrier materials such as liposomes, MNBs, micelles, nanoemulsions, magnetic nanoparticles, polymer nanoparticles, and dendrimers have been designed and developed to improve the aggregation and permeability of the drug at the tumor site. In this review, we focused on the effects of ultrasound and MNBs on EPR, discussed in detail the potential mechanisms by which their respective roles and synergies affect EPR, and illustrated new strategies that have been developed to enhance EPR. Although these new strategies do show promise, further research is needed in this area to demonstrate effective drug delivery and therapeutic effects. In this study, we discuss the advantages of MNB-assisted ultrasound to enhance the EPR effect, the current problems, and any possible countermeasures.in situ generation”, “multi-gradient targeting”, and “multi-field association” strategies, which can further improve the penetration ability and delivery efficiency of drugs at the tumor site.MNBs are distinctly distinguished from other carrier materials in that they have multiple forms of response to the ultrasound field, and the rich biological effects of these responses have a potential role in both EPR imaging and enhancement processes. Under ultrasound energy mediation, the MNB theranostic carrier can affect the EPR in combination with various favorable conditions. First, ultrasound and MNBs can both affect the EPR. The ultrasonic streaming and hyperthermia effect from the ultrasound itself can improve the ability of a drug to diffuse into a tissue, promote the extravasation of drugs, and enhance the permeability of blood vessels. MNBs can also be used as drug carriers with certain EPR effects using various strategies such as structural design, size control, and modification of the membrane shell. Second, ultrasound can be used to further assist MNBs, which are imaged by low-intensity ultrasound energy to evaluate EPR. MNBs can also rupture under high-intensity ultrasound energy and produce biological effects such as cavitation, which leads to the more efficient transport of a drug into the tumor tissue through the vascular endothelial cells. Through sophisticated design, the internal and external source energy fields can be combined, making full use of “adjustable size modulation”, “The size of the MNBs is still a barrier to the EPR effect. The efficacy of a diagnostic and therapeutic agent through the EPR effect is size-dependent. Related research has shown that liposomes with a hydrodynamic particle size between 100 and 200 nm showed a 4-fold higher accumulation in tumors than liposomes with a particle size of less than 50 nm and above 300 nm Multi-modal imaging, in which targeting factors are coupled with the response to various energy fields and other functions, makes the structure of MNBs complex, thus increasing the difficulty in constructing carriers. Therefore, it is necessary to further study and optimize the preparation method of MNBs theranostics carriers, improve the fineness, controllability, and repeatability, and finally to achieve standardization. It is also necessary to further study the effects of MNB carrier structures on their function, such as the material from which membrane shells are built, size, drug-loading mode, and the effects of target type on imaging and targeting. In addition, in the complex and variable microenvironment of the body, it is very challenging to simultaneously achieve a targeted system with high diagnostic sensitivity, high specificity, and good therapeutic effect. The more complex a structure is, the more risk there is, so it is difficult to anticipate the realization of a function and to achieve clinical transformation, especially when using relatively large targeting systems (hundred nanometers and above) such as MNBs. The sensitivity of different biological tissues to ultrasound is quite different, so the applied ultrasound parameters will need to be changed accordingly. The ultrasound parameters used to stimulate the MNBs would also need to be adjusted for use with the different kinds of bubbles.in vivo experiments are needed to clarify the toxicity, distribution, and pharmacokinetics of a carrier within the body and to provide abundant evidence for clinical application. It is foreseeable that with the continuous development of biomedical nanotechnology based on ultrasound and MNBs, more innovative and more powerful theranostics carriers will be designed and developed to further promote tumor-targeted therapy.More One of the important principles of drug delivery system development is safety. The safety issues for micro/nano-bubble-assisted ultrasound to enhance EPR effects, such as micro/nano-bubble toxicity


Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community.The pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partitioning data structure minimizes CPU workload, enabling the introduction of new features that further enhance user experience. Through the use of highly optimized data structures and algorithms, Reactome has boosted the performance and usability of the new pathway diagram viewer, providing a robust, scalable and easy-to-integrate solution to pathway visualization. As graph-based visualization of complex data is a frequent challenge in bioinformatics, many of the individual strategies presented here are applicable to a wide range of web-based bioinformatics resources.https://reactome.org. The diagram viewer is part of the Reactome pathway browser (https://reactome.org/PathwayBrowser/) and also available as a stand-alone widget at: https://reactome.org/dev/diagram/. The source code is freely available at: https://github.com/reactome-pwp/diagram.Reactome is available online at: Bioinformatics online. It provides bioinformatics tools for visualization, interpretation and analysis of biomolecular data to support basic research, genome analysis, modelling, systems biology and education.Reactome  had trouble using the diagram search functionality, (ii) found the diagrams too crowded/complex, especially in zoomed-out views and (iii) often lost diagram context while navigating through the event hierarchy due to the diagram’s flashing and abrupt changes of location, instead of an animated transition to the target position. Other comments highlighted the fact that the zoom was not progressive, but instead users could only zoom in predefined steps.http://www.nngroup.com/articles/powers-of-10-time-scales-in-ux).Aiming to address these challenges and enhance the overall user experience, a new version of the Pathway Diagram Viewer was implemented. The new version (version 3) was also focused on faster data loading, diagram rendering and element seeking. This decision was made based on the fact that users retain the feeling of being in control when an interaction between them and the computer takes no more than one second (Improvements targeted different levels and included: (i) restructuring of the data format used to send the data from the server to the client, (ii) using a graph data structure to store the pathway content on the client side, (iii) boosting the client content load strategy, (iv) implementing a multi-layer canvas approach, (v) utilising a space partitioning data structure to store the elements to be rendered and (vi) employing the delegate design pattern to control the flow of information based on the level of zoom. This section delves deeper into each aspect to describe them in finer grain.https://www.w3.org/TR/REC-xml) for diagram data storage with JavaScript Object Notation (JSON) (http://www.json.org). JSON is less verbose than XML and thus has a smaller footprint. More important, JSON’s natural mapping to JavaScript objects is faster and uses fewer resources than its XML counterpart  format . As soon as the layout data is available, the viewer processes it and renders the diagram on the canvas. Once the graph content is ready, the latter is processed and linked to the diagram layout to be used for interactive navigation, search and future analysis overlay purposes. Following this render-first approach, the new version of the diagram viewer primes the display of the layout while it retrieves the graph behind the scenes. This strategy boosts the user experience by reducing both the true and perceived loading time.The introduction of separate layout and graph files was accompanied by the adoption of a render-first loading strategy in the client . The cliAdopting a similar strategy that prioritizes the loading of that bit of information necessary to render something useful on the screen and, thus, engage the user, can prove particularly useful to any visualization application that requires excessive loading time. People can define a duration only when there is a clear start time and a clear end time . As a reWhile browsing pathways, users often go back and forth among several pathways of interest, causing the viewer to load and show the same diagram several times in a relatively short period of time. A pathway diagram that has been loaded is very likely to be revisited shortly after visits to other pathways. In computer science, this is known as locality of reference , being aThe new version of the diagram viewer responds to common user actions, such as hovering over an element with the mouse and selecting an entity in the diagram, by highlighting the hovered element and marking the selected entity, respectively. Aiming to provide a richer user experience and visually reinforce user actions, the diagram viewer draws a halo around the elements (reactions and participating entities) related to the selection. In addition, when the user selects an entity that is repeated in the same diagram, the viewer marks all instances of that entity as selected and draws halos around all elements related to them.www.ibm.com/developerworks/library/wa-canvashtml5layering) was adopted to reduce the processing and redrawing overhead inherent to a single canvas update. Each of the stacked canvases in To improve the visual feedback and optimize the diagram rendering process, the new version of the viewer implements a set of advanced techniques developed and used by the gaming industry. In particular, the multi-layer canvas approach  .Here, we employed a QuadTree, a tree data structure used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions . The QuaFor the new diagram viewer, the QuadTree was extended to work not only with points but also with shapes that occupy diagram areas. The aim was to use it in order to narrow down the number of elements to be drawn depending on whether they are in the part of the diagram visible in the client viewport. This allows a fast, selective redraw limited to visible regions of the diagram, again improving interactivity of the diagram viewer.Hence, the usage of this data structure could prove particularly useful for other resources featuring interactive visualizations that contain a lot of elements where the requirements include one or more of the following features: (i) determining the element hovered over by the mouse pointer, (ii) determining the selected element upon user’s click or tab action, (iii) smooth animated view transitions or (iv) progressive zoom.In order to tackle users’ requests for less cluttered pathway diagrams, but at the same time preserve access to all information stored in Reactome knowledgebase, the new viewer enables the user to control the flow of visualized information through the level of zoom. This practically means that depending on the zoom level, the viewer enriches or abstracts layers of information. Thus, each diagram entity is rendered in a slightly different way according to the level of zoom, progressively revealing more details as the user zooms in. For instance, as illustrated in This strategy also improves rendering time when many elements are in the viewport because fewer details are drawn. Other simplifications are to avoiding rounded corners, only showing reaction backbones without central decorators, or removing node attachments or stoichiometry. As users zoom in to specific areas, the number of elements in the viewport falls and more detail is added.The adoption of this strategy could prove particularly useful for other resources featuring complex visualizations as it allows controlling the granularity of information displayed for a given object and level of zoom. Usability-wise, this enables resources to show different views of the same element based on the zoom, determining the optimal level of detail and type of information to be displayed in each case.The new pathway diagram viewer combines the set of strategies and data structures described above to improve performance and to include new features that aim to address the shortcomings of the previous version highlighted by the usability testing sessions. The updated diagram storage format combined with the improved ‘Render-first’ loading strategy resulted in faster loading of diagrams. Additionally, faster rendering was accomplished via the combined use of (i) a QuadTree that efficiently filters down the elements to be drawn based on the visible area, (ii) rendering delegates that declutter the view by regulating the level of detail to be drawn depending on the number of visible elements and (iii) a multi-layer html5 canvas strategy that optimizes rendering by updating only the layers that require redrawing. Optimized rendering enabled the introduction of animation and smooth transitions that, in turn, help users to maintain diagram context while navigating through pathways. The use of an underlying graph structure provided the basis for improving the built-in search feature, by including all the participating molecules of the pathway whether or not they are visible in the diagram.Updating the underlying storage format had a positive impact on the performance of the new version of the pathway diagram viewer. To assess this performance boost, we compared the resulting file sizes for both the previous (XML) and the new data format (JSON), as well as the respective times required by the client to process them. This included the time required to populate the model in the client with the diagram data once they were retrieved from the server.To measure the improvement in performance, a series of experiments were conducted and the results are presented graphically in The update in the storage format combined with the new render-first loading strategy contributed to reducing the overall diagram loading time, as it is perceived by the user. This includes the time required until the diagram is loaded and fully rendered by the client. A striking feature of the comparison of perceived loading times  is that As illustrated in We have conducted a usability testing session centered on the improvements described here . Users ahttps://reactome.org/dev/diagram/.The new diagram viewer was developed in a way that can be both extended or easily integrated as it is in third party applications. Currently, Reactome offers two options for integrating this pathway diagram viewer in other web applications; either using the GWT implementation or the JavaScript wrapper. More details and examples on how to reuse this as a widget can be found at Through the use of highly optimized data structures and algorithms, Reactome has improved the pathway diagram viewer in terms of performance and usability. The new version of the diagram viewer provides a robust, scalable solution to pathway visualization that is easily integrated into third party applications.National Institutes of Health BD2K grant (U54 GM114833); National Human Genome Research Institute at the National Institutes of Health (U41 HG003751); European Bioinformatics Institute (EMBL-EBI); Open Targets ; Medicine by Design (University of Toronto). Funding for open access charge: National Institutes of Health (U54 GM114833). The funding bodies had no role in the design or conclusions of the study.Conflict of Interest: none declared.Supplementary DataClick here for additional data file.


Preliminaries convolutional neural network (CNN) applications have recently emerged in structural health monitoring (SHM) systems focusing mostly on vibration analysis. However, the SHM literature shows clearly that there is a lack of application regarding the combination of PZT-(lead zirconate titanate) based method and CNN. Likewise, applications using CNN along with the electromechanical impedance (EMI) technique applied to SHM systems are rare. To encourage this combination, an innovative SHM solution through the combination of the EMI-PZT and CNN is presented here. To accomplish this, the EMI signature is split into several parts followed by computing the Euclidean distances among them to form a RGB  frame. As a result, we introduce a dataset formed from the EMI-PZT signals of 720 frames, encompassing a total of four types of structural conditions for each PZT. In a case study, the CNN-based method was experimentally evaluated using three PZTs glued onto an aluminum plate. The results reveal an effective pattern classification; yielding a 100% hit rate which outperforms other SHM approaches. Furthermore, the method needs only a small dataset for training the CNN, providing several advantages for industrial applications. One of the most important and promising applications for structural health monitoring (SHM) systems is the aeronautics industry. Global aviation is growing rapidly promising even increased prospects for growth in the future. As discussed in  the worlIn SHM, physical or mathematical models are very useful for dynamic structural analysis, however, most of the real applications present some type of nonlinearity originated from geometric features, type of material, or boundary conditions, which leads to complex and expensive models. Owing to that, many authors have avoided working on structural modeling making use of techniques which allow the damage identification directly from the structural responses obtained from sensors signals. On this subject, the Electromechanical Impedance (EMI) technique plays an important role within the NDE methods. The EMI technique uses low-cost, small, and lightweight piezoelectric (PZT-lead zirconate titanate) transducer glued onto the structure . This teMore recently, the convolutional neural network (CNN) has exploded in popularity and real-world applications. The CNN simply provides a new class of NN which uses the concept of deep learning. CNN is one of the most recent major breakthroughs in the area of computer vision, speech recognition, biomedical systems, and natural language processing ,29. UnliRecently a single CNN application emerged in the SHM field focusing on video processing . ThereinWe developed a novel method suitable for mechanical data analysis. A method that takes advantage of the combination of the EMI-PZT-based method along with CNN.A way of converting PZT response based on the EMI technique to a RGB frame constitutes a novel approach;Frames were computed through a wide range of frequency instead of choosing only the best range in which the EMI presents higher sensitivity. This issue provides an important advantage because that task is very difficult;An unpublished frame dataset encompassing a total of four types of structural conditions for each PZT is introduced;An enhanced method which requires only a small dataset for training the CNN without using GPU. Furthermore, only three epochs are needed to yield 100% of hit rate.Unlike existing studies, the major contribution of this work consists of a novel strategy for damage detection via the combination of the EMI-PZT-based technique and the CNN algorithm. The developed methodology was experimentally tested based on the EMI technique. The validation of the methodology was carried out in an aluminum plate which contains three attached PZT patches. The damage scenarios were simulated by gluing a small metallic nut at three different positions. The results, therefore, showed that it can identify various structural conditions with accuracy, reliability, and efficiency. In summary, the main contributions of this paper are:The remainder of the paper is organized as follows. Firstly, the main theoretical fundamentals are addressed. Secondly, the developed method, highlighting the combination of the EMI-PZT along and the CNN algorithm, is presented. Next, the results followed by a comparison with other SHM approaches are presented. Finally, the paper concludes by highlighting remarks on the developed approach.Structural health monitoring (SHM) systems have become a crucial element in maintenance and inspection activities in the industry, with special emphasis on aeronautical engineering, aerospace, civil, maritime and other related fields. Owing to the high level of safety required, the aeronautical industry has demanded high investments in order to guarantee an adequate operating condition in aircrafts. According to , SHM sysSHM systems are characterized by their ability to detect, locate, quantify, and estimate the life of the structure according to the occurred damage . HoweverConsidering the use of the EMI technique, piezoelectric materials play important roles due to these materials can be used as passive and/or active elements. These materials cover a large range of frequency (from a few Hz up to GHz). Low-frequency applications are covered mainly by the polycrystalline materials . In turn, crystals and thin films are the most used in high-frequency applications . PZT cerX (with amplitude VP and angular frequency (ω)) will produce a current I with amplitude IP and phase Ψ. The electrical impedance of the PZT (ZE(ω)) is given as follows [a(ω) and Z(ω) represent the mechanical impedances for the transducer and monitored structure, respectively. In Equation (1), From a practical point of view of applying the EMI technique in SHM systems, the PZT transducers are glued into the monitored structure by high stiffness adhesive glue based on cyanoacrylate or an epoxy resin. From that, a coupling is established between the structure and the transducer PZT enabling to monitor variations of the mechanical impedance of the structure by measuring the electrical impedance of the PZT . Hence,  follows :(1)ZE(ω)ferences ,47,48,49The convolutional neural network (CNN) is a deep linear network inspired by the functioning of the visual cortex of mammals. Its first version was proposed by  and was The fundamental difference between an “ordinary” neural network and a CNN consists of the fact that CNN uses the convolution operation instead of the multiplication of the array of neurons in at least one of its layers . In the There are three important distinctive features on CNN compared to other Neural Network (NN): shared weights, spatial/temporal subsampling, and local receptor fields . The shaThe third distinctive feature is the existence of local receptor fields. In the classical NN, each input value of each layer is completely connected to the input values of the previous layer (fully connected). Hence, the NN needs to perform several multiplications to find the connected neuron activation, requiring a great computational power mainly for images that have many connected neurons. On contrary, as in natural images, the adjacent pixels tend to be more strongly correlated than the distant pixels, the CNN is architected for that each filter learns on only one subregion of the data received from the previous layer . This alIn summary, CNN networks are composed of convolution layers, which involve the convolution process and the pooling process, in addition to using the concept of local receiver fields to optimize the image processing; layer normalization, which involves the dropout process and other processes used to improve network performance; and the fully connected layer responsible for sorting. The In order to obtain the structural response signals, we developed a method based on the EMI technique. EMI requires that the structure is excited through a PZT at low amplitude considering over a wide frequency range to produce a forced excitation of the structure . Each PZSubsequently, a chirp signal sweeping from 20 kHz to 110 kHz with amplitude of 3 V was used to excite the set PZT/structure. Although many authors consider that the real part of EMI in a frequency range from 20 kHz up to 40 kHz constitutes the best set in terms of damage sensibility , the The acquisition system (DAQ) was developed in LabVIEW software and used here to excite and obtain the structure responses . This syNext, three damage cases were separately simulated by gluing (using 3M Scotch-Weld Epoxy Adhesives DP460 Off-White) a metallic nut of about 10 g (diameter of 12 mm and height of 7 mm) at three different positions in the structure , being oStep 1: The matrix containing the raw EMI data, sampled by the LabVIEW acquisition software, is read;Step 2: As the proposed method uses only the real part of the EMI, those samples are retrieved from the matrix into an array;Step 3: The EMI signatures (baseline and unknown conditions) are divided into equal parts ;Step 4: Those parts are used to compute Euclidian distances and generate a new array;Step 5: That new array is transformed into a square matrix;Step 6: Those obtained values (inside the array) are normalized by the maximum mean;Step 7: Using the colormap function (MATLAB), the normalized matrix is mapped to a colored matrix (RGB);Step 8: The generated image is then saved as a JPEG image. The image will be used as an input to the CNN preprocessing block .As stated earlier, the SHM literature shows clearly that there is not a combination of PZT-based methods and CNN due to the difficulty in obtaining images/videos from the PZT responses. As a consequence, there is a lack of using CNN along with the EMI technique applied to monitor structures. To overcome that, this paper introduces an innovative way of forming frames from PZT-EMI signatures, as explored in detail next. The RGB frame formation process is composed of eight steps, as follows :Step 1: Next, the most important steps are further detailed from a practical point of view. Firstly, the real parts of the EMI are divided into several parts as illustrated in ®, Euclidean Distances (ED) were computed from the EMI parts, as follows (Step 4):Using MATLABIt is important to highlight that the principal diagonal of the ED-matrix is zero because the method computes EDs for the same part of the signals there. This matrix is formed for each PZT-EMI signature and this will be used to form a frame. In this paper, the baseline signature is always used in the first part of the ED-matrices. Each element of ED-matrix was transformed into a RGB  scale in order to form a RGB frame with three dimensions . This procedure was easily run in the developed MATLAB software (Step 7). As observed in As aforementioned, the CNN forms a new class of neural networks (NN) which uses the concept of deep learning ,56,57,58In order to evaluate structural conditions, this approach proposes a framework for the CNN as shown in A brief explanation of the most significant characteristics of the CNN architecture shown in In order to evaluate the developed methodology, this section presents the results obtained considering the experimental set up described above. Firstly, structural response signals were obtained from the various structural conditions and positions of damage on the structure, through PZTs using the above-mentioned acquisition system. Sample signals are presented in Secondly, the obtained structural response signals were divided, in ten parts for each signal, as shown in The frame showed in Thirdly, the CNN block is fed to the aforementioned dataset . Both trConsidering that one CNN is designed for each PZT sensor and the training and testing phases have been carried out, the CNN successfully converged after running three epochs. As stated earlier, the developed method successfully converged after running 3 epochs. This issue is further investigated in In order to evaluate the performance of the developed method, Training and testing times are stated next. As aforementioned, the training time is directly related to the number of epochs. Hence, As observed in The feasibility of the above approach is validated based on EMI-measurement datasets. The method results in an accuracy rate of 100% for all tested scenarios. Therefore, the main advantages of the developed method can be summarized into four points.Firstly, a new way of converting PZT response to RGB frames along with the CNN-based method represents a new approach to structural health monitoring. Based on the results, the method has direct implications in terms of diminishing the percentage of false alarms whilst the damage detection is being performed.Secondly, the major achievement in applying the method is the ability to classify structural damage with higher accuracy compared with the state-of-the-art approaches ,24,27. TThirdly, it is important to quote that this method, proves to be more reliable to detect both internal and non-visual damage compared with a method based on only video/image processing . FurtherFourthly, the developed method forms frames through a wide range of frequency instead of choosing only the best range in which the EMI presents higher sensitivity. This issue comprises an important advantage because that task is very difficult as pointed out in .Despite the advantages, improvements of the developed method still need to be investigated. The major problem with the current approach is the time consumption issue. As presented in It is important to remark that SHM techniques based on PZT transducers are highly influenced by environmental conditions, noise ,36,63 anTo date, we can only guarantee the capabilities of the method for damage detection and size/type estimation in terms of a rather large size as defined here. Smaller damage sizes will form future investigations. However, the simulated damage represents an only negligible increment of structural mass when compared to the total mass of the structure, which is compatible with real damage. Furthermore, future research will be undertaken to evaluate the accuracy of the developed method for randomly initiated defects and to establish the outcomes from having two or more areas of damage at the same time. Another interesting point to be addressed is the evaluation of different type, position, and size of damage ,67,68.This paper has introduced an exploration of the suitability of a CNN-based method applied to monitor structural damage in aluminum structures. Accordingly, we developed a method which takes advantage of the combination of the EMI-PZT-based method and CNN. This methodology presents a new approach for SHM. Additionally to the fact of that CNN-based method was developed here for the first time, this approach consists of a reliable and innovative way of converting PZT response based on the EMI technique to the RGB frame.Based on the results, the CNN-based method shows significant enhancement in terms of the overall success rate whilst the structural damage detection is carried out. As a result, a hit rate of 100% was obtained running only three epochs, which outperforms current approaches. Furthermore, the method runs only a small dataset for training the CNN without using any type of dedicated GPU. To conclude, the method identified the damage scenarios with higher accuracy, therefore, rendering this approach in a promising and useful contribution in the SHM area.Future work will focus on the evaluation of the sensitivity of the developed methodology to identify the progression of the structural damage in structures made of composite materials. Those materials present a higher damping coefficient compared with aluminum, demanding a more accurate method such as shown throughout the paper. Future goals, motivated by the outcomes presented in this paper, will focus on features other than the success rate for measuring the classifier efficiency such as the Kappa coefficient. Further research will be undertaken in evaluation the CNN configuration such as: image size, training dataset size, and the number of kernels to optimize the required time consumption.


Quality of service (QoS)-aware data gathering in static-channel based underwater wireless sensor networks (UWSNs) is severely limited due to location and time-dependent acoustic channel communication characteristics. This paper proposes a novel cross-layer QoS-aware multichannel routing protocol called QoSRP for the internet of UWSNs-based time-critical marine monitoring applications. The proposed QoSRP scheme considers the unique characteristics of the acoustic communication in highly dynamic network topology during gathering and relaying events data towards the sink. The proposed QoSRP scheme during the time-critical events data-gathering process employs three basic mechanisms, namely underwater channel detection (UWCD), underwater channel assignment (UWCA) and underwater packets forwarding (UWPF). The UWCD mechanism finds the vacant channels with a high probability of detection and low probability of missed detection and false alarms. The UWCA scheme assigns high data rates channels to acoustic sensor nodes (ASNs) with longer idle probability in a robust manner. Lastly, the UWPF mechanism during conveying information avoids congestion, data path loops and balances the data traffic load in UWSNs. The QoSRP scheme is validated through extensive simulations conducted by NS2 and AquaSim 2.0 in underwater environments (UWEs). The simulation results reveal that the QoSRP protocol performs better compared to existing routing schemes in UWSNs. The ocean covers more than 70% of the Earth’s surface and it is vital for human life. It helps in driving weather and regulating Earth’s temperature, provides primary resources for humans and serves as a medium for commerce and transport. However, more than 95% of the volume of the ocean remains unexplored and, even more alarming, is unseen by human eyes due to lack of appropriate acoustic communication technologies for data collection from the ocean. However, the internet of things (IoT) technology is expected to make possible a new era in the vast ocean exploration with the aims to connect ubiquitous devices and facilities with different types of underwater networks to provide efficient and reliable services for all kinds of applications anytime and anywhere . Thus, tThere are a few alternatives to acoustic telemetry, such as radio waves and optical communication that can be used . The radTo this end, underwater acoustic communication seems to be the best option and, therefore, underwater acoustic sensor networks (UASNs) have been attracting increasing attention from scientific and industrial communities . The ASNOn the other hand, efficient data collection using ASNs is challenging due to the various aforementioned factors in the UWSNs. Often, underwater ASNs are equipped with acoustic modems to wirelessly communicate with each other. Underwater communication links are affected due to location and time-dependent acoustic channel communication characteristics. Moreover, temporary connectivity loss can occur due to shadow zones. Therefore, the wireless link between neighboring ASNs may perform poorly or even be down at any given moment, which will increase the packet retransmissions as an attempt to deliver data packets result in more packet collisions, delay and energy consumption in UWSNs. Thus, excessive rerouting due to poor link quality consumes nodes residual energy, which can disrupt underwater monitoring and exploration missions prematurely . To addrIn the rest of the paper, In the past few years, there has been intensive research in designing routing schemes for UWSNs. In this respect, this section summarizes up to date existing studies on the developments and status of routing schemes in UWSNs. The authors in  propose To solve the issues of above-mentioned depth-based routing schemes, the work in  presentsThe protocol proposed in  exploitsThe protocol in  divides Han et al.  propose The main purpose of the aforementioned routing protocols is to provide reliable data delivery at a low cost in UWSNs. These static-channel based schemes significantly help in designing and development of advanced routing solutions for UWSNs. However, they suffer from major disadvantages. First, most of the schemes employ probabilistic values to estimate the link quality between ASNs in highly dynamic UWEs. Thus, the poor link quality due to the false estimation of the channel is facing severe reliability issues lead to excessive rerouting during monitoring time-critical events in UWSNs. The new routes finding or repairing broken links require a significant amount of control message overheads, which consumes the sensor’s energy and increases the chance of packets collision and brings latency issues in the network. On the other hand, the interference issues further increase the corrupted data packets in UWSNs. Second, during conveying packets these schemes consider shortest paths routing with excessive hop counts, which may balance the network residual energy; however, it consumes more ASNs energy and increases the probability of invalid data packets because of data path loops in UWSNs. In addition, the shortest path routing result in high routing table management cost and congestion problems because of quickly draining the residual energy frequently used by ASNs nearer to the sink. Third, most of these routing protocols are stuck in void regions and instead of finding an alternative route just discards the packets and thus subjected to packet loss in UWSNs. Fourth, the existing static-channel based routing solutions due to lack of dynamic channel adaptation cannot mitigate the inference effects in order to provide high packet delivery rates and network throughput with low latency and corrupted packets in UWSNs.We propose an underwater acoustic channel detection mechanism to find the vacant channels with a high probability of detection and low probability of missed detection and false alarms.An underwater acoustic channel assignment mechanism is proposed to assign high data rates channels to acoustic sensor nodes with longer idle probability in a robust manner.A hybrid underwater routing mechanism is proposed to convey collected data to the sink. The proposed mechanism while conveying information avoids congestion, data path loops and balances the energy consumption load of UWSNs.The performance of the QoSRP protocol against existing routing schemes is validated through extensive simulations conducted by NS2 and AquaSim 2.0 in the UWSNs.These facts motivate researchers to propose a novel cross-layer QoS-aware multichannel routing protocol called QoSRP for the internet of UWSNs to mitigate the effects of the underwater environments and improve the overall data collection in UWSNs. The entire routing problem has been modelled using mixed integer linear programming (MILP) in UWSNs. The major contributions of our proposed protocols are as follows:The later sections explain the working mechanism of our proposed routing protocol in UWSNs.The protocol design details are given in the following sections.The network model used in the design, development, simulating and testing the QoSRP scheme is illustrated in Recently, the spectrum shortage problem aggravates in an apparent manner because of increasing demands for higher data rates at low frequencies for various UWSN-based applications. The principle of dynamically exploiting the local vacant spectrum bands of the primary users during their silence periods by secondary users is among the best-proposed solutions for this problem. Therefore, the multichannel is proposed as a prominent technology to implement spectrum access for its autonomous, agility, and ability to detect the primary user’s (PU) signal. In multichannel communications, the spectrum sensing is a key element in the sense that it demonstrates how signals of the PUs are identified, sampled, and processed for detecting spectrum holes . The maiIn the MaD technique, the unctions . The useationary .Typically, these features in the signal format are introduced intentionally, which enables a receiver to exploit parameter estimation like the direction of arrival, pulse timing, or carrier phase. This detection technique can improve the sensing detection, however, it requires prior knowledge of the primary signal characteristics. In addition, the high computational complexity and significantly extensive sensing delays are the other shortcomings of this approach. The EnD is the widely used channel detection method, which does not require any previous knowledge of the In this respect, the detection threshold that precisely detects the presence of primary signals plays an important role in the multichannel acoustic sensor networks (MCASNs). The less error in computing the SNR value decreases the probability of ealed in  to identThe key aims of the objective function is to maximize the probability of detection In Equation (2), Equations Distributed cooperative spectrum sensing consists of main two types of data fusion, namely hard decision and soft decision mechanisms in the MCASNs. The soft decision mechanism due to heavily sharing test statistics faces excessive cooperation overheads compared to the hard decision mechanism, which consumes the sensor’s energy and increases the probability of channel assignment delay in MCASNs. On the other hand, the hard decision mechanism performs best when the channel state information between the Equations In the UWCD scheme, the local channel detection made by the individual The receiver This mechanism significantly reduces the cooperation overhead in terms of latency for searching an appropriate spectrum since multiple channels are sensed in a single sensing interval. Moreover, it also significantly minimizes the network implementation cost by eliminating the need for centralized intelligent devices in the UWSNs. In addition, the fusion mechanism improves the robustness of the decision-making process at the fusion node on the presence or absence of In UWSNs, the fusion center cooperating with all users does not essentially attain the optimal performance since the channel fluctuates over time and location due to the harsh nature of the UWEs. This might lead to assigning a poor-quality channel to the Constraints in (12a) state that the selected secondary users are less than the total number of secondary users involved in the sensing process for the distinct channels in a region in the network. Constraints in (12b) guarantee that the selected secondary users perform the best The local sensing and data reporting to the fusion center spend a notable amount of The g (DCoS) . In the Thus, the key aim of the specialized devices is to allocate vacant channels efficiently to ng (DWS) .The DRS allows secondary users to sense for the vacant channels in a specific region. Although, secondary users sequentially sense the specific region for available channels might raise the probability of detecting an available channel more quickly. However, the possibility of finding a poor capacity-aware channel with high interference also arises that affects the neighboring ASNs leading to low link qualities in the network. This results in packets loss, significant delay and degrades secondary users’ throughput in the network. On the contrary, the DWS allows secondary users to allow to sense the whole region for the desired channel instead of sensing the specific region. Compared to DRS, the DWS in the proposed scheme increases the chance of finding high data rates channels at low interference, sensing overheads and latency due to allowing variously known . The proIn UWSNs, the data traffic passing over an ASN differs based on its location along a data path. Generally, the ASNs closer to the sink convey more packets compared to the sensors that are far away. Therefore, data reliability is one of the main requirements for various underwater monitoring and control applications. The static channel assignment mechanisms in underwater suffer from link burstiness due to high interferences and channel variation in the network. This result in packet loss between a sender and receiver for long time intervals, resulting instability and severe communication delays in the scheme. This issue becomes more severe when routing topology varies dynamically. Thus, the SCA limits channel utilization and cannot provide data reliability in the underwater. To this end, the DCA is introduced to mitigate the impact of the interference on the link dynamics due to acoustic channel variations and channel traffic changes in the underwater. The DCA allows the channel assignment schemes to allocate channels with more accurate decisions to secondary users. The DCA provides high throughput in harsh nature dynamic underwater environments. However, it is with the expense of freshness of the data delivery and overhead due to very frequent channel assignment, typically before each transmission. The SDA approach takes the advantages of both static and dynamic channel assignments and provides better trade-off between low overheads and traffic changes with high adaptation to channel variety in the proposed scheme. In this mechanism, the channels are assigned periodically or based on events in the network. Generally, high capacity links with low interferences are allocated statically to the sensors closer to the sink that have the heaviest traffic loads in the network.The rest of the available channels are allocated for other sensors to pursue a dynamic channel assignment. The semi-dynamic mechanism due to its adaptability to links dynamics, data traffic variations, and interferences while managing the long switching latencies provides a high throughput for delay-sensitive underwater events monitoring applications. To this end, the key objective function of UWCA algorithm can be numerically indicated asIn the proposed scheme, the Constraints in (20a) show that the transmission power for each ASN cannot exceed In which Accordingly, when However, this high transmission power significantly improves the data transmission rate to a faraway distance in the network. However, it brings severe interference to neighboring sensors in the UWSNS. This interference The Constraints in (28a) and (28b) ensure that the internal This maximum utility function, i.e., On the other hand, during the time The volume of channel history data stored In the proposed scheme, a primary or the secondary user sensor may share information to its single hop neighboring sensors and sense the entire region only in a case where the desired capacity channel is currently occupied or does not have desired capacity channel information stored in the CIT. Consequently, at each iteration of the negotiation procedure, the sensor’s CIT is periodically updated in the MCASNs. In the proposed scheme, we employ First in First Out (FILO) policy to avoid the management complexity of the events data in a channel information table (CIT). Thus, a channel that is not used in a predefined time is substituted with the new one in the channel table of a primary or secondary user as shown in Thus, the designed scheme saves a notable amount of spectrum re-sensing energy by avoiding the data packet collision due to assigning a longer idle channel between the Recently, the designed packets forwarding schemes during packets forwarding prefers to select the shortest forwarder node along a routing path  state that in single-hop packet progress, the Euclidian distance Generally, the forwarders switch to sleep mode if they do not have more data to transmit to the sink. On the other hand, continue data transmission for a long time can drain relay nodes energy, particularly for those who are nearer to the sink. Moreover, in most cases these relay nodes are facing congestion issues because they are forwarding a huge amount of data coming from the rest of the network. In addition, the possibility of transmission failures cannot be ignored since the wireless links are unreliable in the harsh UWEs. In the first and last cases, if the receiver relay node did not reply to the sender in a predefined amount of time and then it sends the request again to the sender and wait for a predefined amount of time longer than the previous waiting time. The receiver node is declared as an inactive forwarder if the sender did not receive any reply from the destination node. In the second case, the congested node first set up the time and then sends a buffer overflow The packets transmission begins as soon as the acknowledgment message is received from the receiver in the network. The buffer overflow priority of the selected destination relay node is set to one in the routing table since it is ready to receive packets. Finally, the data with the new relay nodes information is delivered to the sea surface sink, which sends an The following section discusses the channels models, simulation settings and results obtained during simulation studies.In this study, we employ the widely used acoustic channel model explained in ,42,43 toThe absorption coefficient  formula  is givenussed in ,46,47 isussed in  and MERPIn this section, the results obtained from the single channel protocols with interference are compared with the multichannel protocol with the same interference rate of 15% (low), 35% (moderate) and 55% (high) in UWSNs. During simulation studies, it is noticed that the packets delivery ratio is found high in all routing protocols when the interference rate level is 15%. The interference does not heavily affect the transmissions in a single channel protocol at the beginning as the interference is not frequent enough, showing the average 87%, 90%, 92% reception rates in LRP, QERP and MERP in the first 30 s as shown in In these single-channel protocols, the node does not have enough time to recover from the high interference to retransmit and drops most of the packets. There are more packets being dropped over time and the node stops receiving packets as it does not have enough buffer space to store the incoming packet and the channel becomes congested. However, the MERP protocol data delivery performance improves as the interference rate increases since it has more time to recover compared to the QERP and LRP routing protocols. On the contrary, the overall packets delivery ratio is recorded high at around 99% in QoSRP in UWSNs. In QoSRP, the number of packets received at the sink is observed around 88% when the vacant channel’s record is found to be around 5 at each ASN in UWSNs. This low packet delivery ratio is due to the method utilizing low priority channels which cannot effectively mitigate the interference and noise effects for packets transmission in UWSNs. This level rapidly increases up to 96% when the ASNs keeps the record around 9 vacant channels in UWSNs. As soon as the packets reception rate is increasing, the ASN starts to block the channels that are facing high interference and noise issues for a predefined amount of time by assigning a low priority level in the routing table. By doing this, it ensures that the rest of the node’s listening channels are good channels. This enables the use of all other available channels without blacklisting any channel until it is sure that it is a bad channel through the negotiation process. Therefore, the QoSRP periodically orders the channel based on their priority each time before making a decision on the new channel in order to avoid the interference channel. Thus, it enhances the ability of an acoustic node to find a vacant channel in a robust manner with higher data rates at low interference, which effectively increase the network throughput in QoSRP around 96% compared to other routing protocols as shown in Consequently, each node has different listening and transmitting channels. When the node is awake, it waits for the incoming packets on its listening channel. If the node has a packet to send, it will switch to the desired capacity-aware channel based on the channel information from the neighboring table. The channel quality table is built over time at each hop helps to learn good and bad channels based on the previous history information of message exchange processes. The channel switching takes at most a few milliseconds to switch to the transmission channel. The QoSRP uses a transmission phase-lock that is based on the previous history wake up or sleep activity information of the primary users and, therefore, the transmission node knows the receiver wake up phase. The node starts transmitting just before the receiver is expected to be awake. The channel switching happens shortly before the receiver is ready to receive the packets, thus the time taken in channel switching does not affect the packet reception in the network. The node goes back to sleep once the transmission has succeeded or reached the maximum number of retransmissions. In the next iteration, the node is reset and wakes up on its listening channel. The channel reset is done in these cases: (i) the queue buffer is empty, (ii) before sending the next packet from the queue buffer, and (iii) the last packet in the queue buffer has been sent. This reset is done to avoid any delay in packet reception that could happen when the node is awake. In load-balanced routing, the workload is evenly distributed in the network, which as a result, distributes the energy consumption across the nodes. The static channel-based studies, however, do not consider the appropriate energy or the battery level as the performance metric but instead use the node’s workload value. Therefore, they perform poorly in load balancing in the network. This rate is found more in MERP and LRP compared to the QERP routing protocol. On the other hand, the QoSRP uses routing through the good neighborhood, which provides alternative routes instead of concentrating on a single good path to ensure that the workload is widely spread and no specific nodes are being used excessively.The neighborhood metric uses the information regarding the quality of the surrounding neighborhood, which are the forwarding path value and the neighborhood influence on the node in making a decision based on the priority. If the current path becomes congested or unavailable, it switches to the alternative route, which is through a node closer to the destination to improve the overall throughput and data rates in the network. Thus, the next hop neighbor that is not selected as the forwarder becomes the alternative route if the current path is unavailable. The neighborhood metrics allow a set of forwarding routes to be used to enable network load distribution, which as a result, helps to improve the network load balancing and reduces the energy consumption, and latency. All the above factors lead to low latency in QoSRP compared to QERP, MERP and LRP routing schemes as shown in The design of a QoS-aware routing protocol for time-critical events data gathering is the major concern in UWSNs. Therefore, this paper proposed a new cross-layer QoS-aware multichannel data-gathering protocol for UWSNs-based time-critical marine monitoring applications. The proposed scheme takes into account the time and location-dependent acoustic channel communication characteristics during time-critical events data gathering and relaying towards the sink. In the proposed QoSRP scheme, the UWCD mechanism successfully detects vacant channels for ASNs with a high probability of detection and low probability of missed-detection and


In this paper, improved Bernoulli filtering methods are developed to deal with the problem of joint passive detection and tracking of an underwater acoustic target with multiple arrays. Three different likelihood calculation methods based on local beamforming results are proposed for the Bernoulli filter updating. Firstly, multiple peaks, including both mainlobe and sidelobe peaks, are selected to form the direction-of-arrival (DOA) measurement set, and then the Bernoulli filter is used to extract the target track. Secondly, to make full use of the informations in the beamforming output, not only the DOAs but also their intensities, the beam powers are used as the input measurement sets of the filter, and an approach based on Pearson correlation coefficient (PCC) is developed for distinguishing between signal and noise. Lastly, a hybrid method of the former two is proposed in the case of fewer then three arrays. The tracking performances of the three methods are compared in simulations and experiment. The simulations with three distributed arrays show that, compared with the DOA-based method, the beam-based method and the hybrid method can both improve the target tracking accuracy. The processing results of the shallow water experimental data collected by two arrays show that the hybrid method can achieve a better tracking performance. In many target detection and tracking applications, detection and estimation are usually carried out separately under the Bayes framework . HypotheIn passive acoustic target surveillance applications, however, a non-cooperative target may not always radiate a signal that is observable for detection and tracking. The noisy environment increases the uncertainty of obtaining the exact target existence information from available observations. A filter that can distinguish the existence of a target by noisy observations and can be able to resume track after losing the target for a while is needed.Recently, target tracking based on random finite set (RFS) theory provides new opportunities for state-space processing which has been widely used in many tracking examples, such as video image recognition , infrareIn active radar monitoring, the measurement set of Bernoulli filter is assumed to be composed of a DOA estimation of the true target, whose error is a zero mean Gaussian variable, and several DOAs generated by clutters, which form a Poisson RFS . HoweverThe main contribution of our work is that three different likelihood calculation methods based on local beamforming results are proposed for the Bernoulli filter. Firstly, we construct a DOA measurement set from the passive beamforming results (the DOA-based method). Similar to the method used in Reference , to incrf as a generic symbol for the finite set statistics (FISST) PDF of the RFS variables, while p is denoted as a generic symbol for the traditional PDF of the vector variables. For any variable or function k, and k.Throughout this paper, we use uppercase calligraphic letters to denote the RFS variable, and ∅ denotes the emptyset. For any RFS The rest of the paper is organized as follows. The Bernoulli filter are briefly reviewed in The concept of RFS was introduced by Mahler to describe the state of a randomly present target or multiple targets . RFS-bask, and their state vectors are k is presented by an RFS on the state vector space, In the RFS-based Bayes filter, target states and sensor measurements are modeled as RFSs instead of traditional vector formulation. Suppose that k, RFS state The posterior probability density of the state variable is propagated in the predicting and updating procedure of the Bayes filter. By using the RFS state and measurement sets, we can extend the traditional Bayes filter from vector space to RFS framework. The predicting and updating process of the RFS posterior densities  follows : (1)fk|kq), whose element q asFor the case of tracking a target which may randomly be present or disappeared in a surveillance area, Bernoulli RFS can be adopted to model the target state, whose cardinality distribution is Bernoulli. Such RFS is either an empty set :k, and The kinetic characterization of the target is used in the prediction stage. This dynamic is described by the Markov transitional density qk|k−Equations  and 8)  8) complIn the next section, we present the update stage for the multi-array passive beamforming system. Different kinds of measurement sets are used, which lead to different forms of the update procedure.Using a multi-array system for joint passive detection and tracking of the underwater acoustic target, we first perform beamforming on each local array to obtain the relative DOA information of the target to the local array. Subsequently, in the Bernoulli filter, with known array locations, the tracking of the target state  is achieved using the beamforming results of all the arrays via triangulation.For the convenience of practical implementation, CBF is adopted to process the collected data. We divide the signal band of interest into multiple narrow subbands and perform narrow-band CBF on every subband, and then sum up the subband results to obtain the final beam power.S-sensor array is converted to frequency-domain snapshots on M narrow subbands. The center frequency for the mth subband is denoted by L snapshots are collected to form one data frame matrix, lth column vector in matrix r, the propagation delay difference on the array is described by the steering (or replica) vector mth frequency bin with c being the sound speed. In the shallow water environment, depth is negligible compared to the range between target and array. That is, M subbands leads to the basic broadband beamforming of the formBy fast Fourier transform (FFT), the recorded time domain signal of a given When the featured frequencies of the target are included in the summed subbands, the target DOA will be enhanced in the beam power. The estimation of DOA is then given by In some scenarios, for example, when SNR is low or the array sensor spacing does not meet half-wavelength requirement, strong noise at the sidelobes and grating lobes will degrade the performance of DOA estimation. The correct peak still exists in the beam power but is usually lower than the spurious peaks. In other words, the beam pattern corresponding to the correct azimuth is corrupted but remains in the presence of noises and interferences. For the purpose of making full use of the beamforming results, we propose two kinds of derivative measurements of N distributed arrays is deployed in the surveillance region. Every array in the system provides a measurement set at frame k. Denote the measurement set of the nth array at frame k by nth array. Suppose that a system equipped with l arrays:φk(Zk|Xk)ectively ,(11)qk|The likelihood functions In this section, we discuss the construction method of a DOA-based measurement set. In the case of low SNR, the sidelobe outputs may be higher than the mainlobe in the beam power. However, our simulations showed that, if we conserve certain number of peaks, the correct DOA information of the target has a high probability to be retained, which can thus be transferred to the subsequent filter. Therefore, for each local array, we search for  pattern .N-array system, let nth array. When the target is absent, In an When a target is present, the likelihood is given byThe update process of the DOA-based method is completed by substituting the likelihood functions in Equations  and 17)17) into nth array at time k. According to the definition of likelihood functions, In the DOA-based method, we only retain the DOA peak positions from the beamforming outputs for filtering, but the intensity information in the beam power can also be useful. Therefore, we proposed a beam-based method in this section, where the entire beam power for nth array is denoted by For a fixed array, the element positions in the array are known a priori. Thus, we have known beam pattern (in power) for a given DOA The PCC has a value between Note that negative PCCs are considered as mismatch here. Readers may be confused because negative correlations are usually considered as strong correlations in applications such as image recognition. That is, if the direction of a measured image are opposite to the original one, the PCC between them equals to −1, but they are still the same object (highly correlated). However, in our application, the PCC between the local beamforming result and the beam pattern being negative means that peaks appear at the DOA positions that should have been valleys, while false peaks appear at where they should not have been existed. This is not a match in our expectation. If the negative PCC was still considered as strong correlation, we would get wrong DOA estimation.The desired mapping rules should satisfy the requirements listed above. For this purpose, we first define a non-negative PCC  follows:ηbeam,1(nEquation –13)..ρk+(n) is a measure that is used to analyze the estimation error of the target state and target number at the same time. The OSPA distance between two RFS r is the pre-defined position error radius, outside which the estimation is regarded as target missing.Another metric used is to measure the probability of target lost in the tracking problem, called circular position error probability (CPEP), defined asGiven the target track in Results are shown in The experiment dataset used to evaluate the performance was collected in the experiment SWellEx-96 Event S5 . In thisk contains L = 11 snapshots with 5 snapshots overlapping between the adjacent frames. A total of 199 frames were processed. During the experiment, for frames 48∼54, 120∼123 and 131∼134, the deep source stopped projecting continuous wave (CW) tones and started projected chirps that are not on the processed frequency bands. Target is treated as absent during those frames for that only noise is contained in the data for processing.The recorded sound pressure is sampled at 3276.8 Hz. Data flow is transformed to frequency-domain snapshots with 8192-point FFT. The snapshots length is thus 2.5 s (0.4 Hz frequency bin widths). Similar to the simulations in the previous section, in beamforming, one single frame In the experiment data processing, the Bernoulli filter parameters are set to Only two arrays in the experiment led to wrong estimation when the correlation deviated for any of the arrays. This deviation should have been eliminated if we had one more array. Besides, for many frames, the target is in the end-fire direction of HLAs, where the performance of the beam-based method is not satisfactory. In We studied the passive joint detection and tracking problem of underwater targets using multiple arrays. The beamforming results obtained by the spatially distributed arrays were used as inputs to the Bernoulli filter to track the target presence, target position, and velocity. Three different likelihood calculation methods, the DOA-based, beam-based and hybrid methods are proposed for the Bernoulli filter. In the DOA-based Bernoulli filter, measurement sets were composed of DOA peak positions of beam power. The beam-based Bernoulli filter adopted the entire beam power as the input measurement set. The hybrid method was proposed to complement the advantages of the DOA-based and the beam-based method in the case of fewer arrays. We used a realistic underwater acoustic waveguide model to generate simulation data and evaluate the performance of the three methods. We also compared their performance using the low-frequency portion of the real data collected in the SWell-Ex96 experiment. The simulation results with three arrays showed that the proposed beam-based method and hybrid method can improve the tracking performance compared with the DOA-based filter. In the experimental data processing with two arrays, results also indicate that the proposed hybrid method has a better ability of detection, as well as a better tracking precision after convergence. It is worth noting that the RFS-based Bernoulli filter has great potential in multi-target tracking. We wish to extend the proposed methods to track multiple acoustic targets in future efforts.