Potential Applications Research Articles

Two-stage HOG/SVM for license plate detection and recognition

Automatic license plate recognition (ALPR) is one of the technologies used in intelligent transport systems (ITS) to read vehicle license plates automatically. The extracted information has various potential applications, including but not limited to an electronic payment gateway, a system for paying parking fees, road surveillance, and managing traffic flow. In this paper, we propose an efficient method to detect and identify the Algerian license plate (LP). This method consists of a two-stage algorithm that combines the histogram of oriented gradients (HOG) with the support vector machine (SVM) classifier. The purpose of the first stage of HOG/SVM is the detection of the LP, while the recognition of the digits is accomplished by the second stage of HOG/SVM. As first contribution, a dataset of standard Algerian LP not available elsewhere is built (DZLP dataset), The second is a proposal of a very efficient pre-processing step for LP detection and digit recognition. Experimental results show that the proposed approach yields very high license plate and average digits recognition rates, which of 97.5% and 99.46%, respectively.

A Novel Lie Hypergraph Based Lifetime Enhancement Routing Protocol for Environmental Monitoring in Wireless Sensor Networks

Wireless sensor network (WSN) is a rapid surging technology promising many fruitful innovations for the user community. The use of WSNs for continuous monitoring of environmental factors in severe situations, such as detection of volcanoes, forest fires, floods, and so on. Despite WSN’s various potential applications, energy and deployment are two major concerns influencing the network life span. The primary requirement is to monitor node energy consumption in order to improve network performance. Many approaches are proposed in recent times for energy efficiency, this article introduces an associated hypergraph with Lie algebra of upper triangular matrices for energy efficient clustering and routing. Initially, the sensor nodes are formulated as a hypergraph, and each hyperedge is treated as a cluster, from which cluster-head (CH) selection is exploited by minimum hypergraph transversal. The routing decision is employed by constructing the upper triangular matrix (UTM), and Lie commutators of the UTM Lie algebra identifies the best relay nodes for data forwarding. The performance of the proposed work is evaluated using simulation results which shows the effectiveness of the scheme over compared protocols in terms of, number of alive nodes, energy consumption and number of packets received in BS.

Comprehensive Review on Phytoconstituents-based Nanomedicine for the Treatment of Atopic Dermatitis.

Atopic dermatitis (AD) is known as a chronic disease characterized by eczematous and pruritus skin lesions. The pathology behind atopic dermatitis etiology is loss of epidermal barrier, which prevents the production of protein filaggrin that can induce T-cell infiltration and inflammation. Treatment of AD is majorly based on limiting skin repair as well as reducing inflammation and itching. There are several remedies available for the treatment of AD, such as Janus kinase and calcineurin inhibitors, topical corticosteroids, and phosphodiesterase-4 inhibitors. The conventional formulations in the market have limited safety and efficacy. Hence, effective treatment of atopic dermatitis requires the development of novel, efficacious, reliable, and specific therapies. Recent research data have revealed that some naturally occurring medicinal plants have potential applications in the management of AD through different mechanisms. The nanotechnology-based therapeutics have gained a lot of attention in the last decade for the improvement in the activity of drugs having low absorption due to poor solubility, thus leading to lesser bioavailability. Therapies based on nanotechnology can be an effective way to overcome these obstacles. Due to their effective propensity to provide better drug diffusion and bioavailability as well as drug targeting potential at the desired site of action, these approaches may have decreased adverse drug effects, better penetration, and enhanced therapeutic efficacy. Hence, this review highlights the potential of phytoconstituents-based novel formulations for the treatment of atopic dermatitis. Furthermore, recent patents on therapeutic approaches to atopic dermatitis have also been briefly described.

Eco-friendly extraction of antibacterial compounds from enriched olive pomace: a design-of-experiments approach to sustainability.

The increasing interest in utilizing olive pomace bioactive molecules to advance functional elements and produce antioxidant and antimicrobial additives underscores the need for eco-friendly extraction and purification methods. This study aims to develop an eco-friendly extraction method to evaluate the effect of extraction parameters on the recovery of bioactive molecules from enriched olive pomace. The effects were identified based on total phenolic and flavonoid contents and antioxidant activity, employing a design of experimental methodology. The positive and the negative simultaneous effects showed that among the tested enrichments, those incorporating Nigella Sativa, dates, and coffee demonstrated superior results in terms of the measured responses. Furthermore, chromatographic analysis unveiled the existence of intriguing compounds such as hydroxytyrosol, tyrosol, and squalene in distinct proportions. Beyond this, our study delved into the structural composition of the enriched pomace through FTIR analysis, providing valuable insights into the functional groups and chemical bonds present. Concurrently, antimicrobial assays demonstrated the potent inhibitory effects of these enriched extracts against various microorganisms, underscoring their potential applications in food preservation and safety. These findings highlight enriched olive pomace as a valuable reservoir of bioactive molecules for food products since they can enhance their anti-oxidative activity and contribute to a sustainable circular economy model for olive oil industries.

Model Predictive Control of Magnetic Helical Swimmers in Two-Dimensional Plane

Magnetic micro/mini-swimmers have a great potential application in biomedical research and have gained broad attention. Recent research studies focus on the automatic control methods of magnetic micro/mini-swimmers, such as artificial intelligence methods. However, their autonomous manipulation remains a challenge since they are subject to various disturbances from the external environment and model uncertainties. The current methods employ a status observer to estimate these disturbances and uncertainties. In this paper, we apply a data-driven technique that utilizes the nonlinear approximation ability of neural networks (NNs). To be specific, a flexible structure of NNs, Broad Learning System (BLS), is employed to model the input-output mapping relationship between the direction of the rotating magnetic field and the swimming direction of the helical miniature swimmer. Then, according to the dual-variable decoupling control, a levitation controller is formulated and a path following controller is proposed based on a planar three-degree-of-freedom model of magnetic helical swimmers, which is inspired by the model of wheeled mobile robots. Simulations and experiments are conducted to quantitatively validate the proposed control method using different planar paths. The experiment results show that the mean absolute error of the path following control is about 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> of the body length which is less than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm$</tex-math> </inline-formula> . Our proposed control method provides a preliminary study to alleviate the impact of disturbances and uncertainties on the control performance of magnetic micro/mini-swimmers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is mainly motivated by the potential application of artificial intelligence methods in magnetic micro/mini-robot community, especially for the applications that reject disturbances and uncertainties. In practice, a path planner is employed to compute a pre-defined reference path that connects the start and the targeted locations. Then our control method is applied to the magnetic helical swimmer and it is guided to follow the reference path. Tackling external disturbances and model uncertainties is still challenging during the control progress. Neural network-based technique is an intuitive approach since their nonlinear modeling ability and generalization are suitable for estimating these disturbances and uncertainties. As for training the neural-network model, the training data about the angle parameters should be recorded by manual control of the helical swimmer. These angle parameters define the rotating axis of the uniform rotating magnetic field and the self-rotating axis of the magnetic helical swimmer. According to the planar motion model, the optimal controller is formulated using the feedback distance error and angle error, and the sum of the control signal and the prediction of the compensating model is used as the final control input. Our electromagnetic coil system features easy operation and configuration of cameras or other sensors. Simulations and experiments validate the performance of the neural network-based compensating method and the proposed optimal control method using magnetic micro/mini-swimmers.

Structural and optical properties of position-controlled n-ZnO nanowire arrays: Potential applications in optoelectronics

Highly position-controlled ZnO nanowire (NW) arrays and nanowire-cluster (NW–C) arrays are grown on mask-patterned gallium nitride (GaN) substrates by hydrothermal method. Electroluminescence (EL) emissions with blue-violet light at forward-bias(fb) voltage, EL emissions with yellow light at reverse-bias(rb) voltage, and EL emission at both rb voltages and rb voltages were achieved by the adjustment of the size of the heterojunction interface between wire arrays and film. The high rb current is attributed to electron tunneling transport edge effect via a narrow tunnel barrier. The obtained results highlight that the EL characteristics of ZnO NWs can be tuned and controlled through the size of the heterojunction interface between wire arrays and film. Besides, the nonplanar heterogeneous structure of ZnO NW arrays/GaN film also shown a great spectral response characteristic in the ultraviolet(UV) band, which proves that the structure of is worthy of being studied to achieve high performance UV photodetectors.

Fine-Tune the Electronic Structure of Copper Nanowire Networks by Heteroatom Doping Toward Enhanced Fenton-like Reaction

To fine-tune the configuration of electrons around metal centers is critical to enhancing the activation of peroxymonosulfate (PMS) for organic decontamination in a manner similar to the Fenton-like reaction. Herein, we systematically explored the inclusion of different heteroatoms to manipulate the electronic configuration of copper nanowire (CuNW) networks toward PMS activation. Both experimental results and theoretical simulations unveiled that doping the CuNW with boron (B) to generate CuNW-B adjusted the d orbital of CuNW, optimized the electronic density of Cu active sites and endowed a proper adsorption energy of PMS, which provided the most active oxidation capacity of the materials studied. Conversely, doping with phosphorus (P) to generate CuNW-P caused evident performance decay in terms of the activation of PMS, as strong adsorption energy hindered the effective desorption of key intermediates. Accordingly, the CuNW-B boosts the Fenton-like reaction and is nearly triple and twice as effectively at degrading bisphenol A (92.5%) as CuNW-P (36.0%) and CuNW (50.5%). Thus, it was reasonably hypothesized that electronic reconstruction played an important role in improving the Fenton-like reaction. During this process, an applied potential (AP) facilitated the catalytic process by reducing Cu2+ to Cu+, which was followed by the formation of primary active species (Cu3+). Additionally, the use of a recirculating fluid flow in the reactor provided convective mass transfer, which led to more charge transfer to the structure of electrode relative to a conventional diffusion-limited batch reactor. Moreover, tests in a variety of challenging conditions demonstrated the robustness and stability of the combined CuNW-B/PMS/AP approach. This study provides an approach to finely control the electronic structure of Cu sites and is expected to guide the design of advanced Fenton-like catalysts, which could further provide a promising technology for the treatment of actual organic wastewater in a sustainable manner.

The Role of Extracellular Vesicles in Efferocytosis.

Efferocytosis is the physiological process of phagocytic clearance of apoptotic cells by both professional phagocytic cells, such as macrophages, and non-professional phagocytic cells, such as epithelial cells. This process is crucial for maintaining tissue homeostasis in normal physiology. Any defects in efferocytosis can lead to pathological consequences and result in inflammatory diseases. Extracellular vesicles (EVs), including exosomes, microvesicles (MVs), and apoptotic vesicles (ApoVs), play a crucial role in proper efferocytosis. These EVs can significantly impact efferocytosis by affecting the polarization of macrophages and impacting calreticulin (CRT), TAM receptors, and MFG-E8. With further knowledge of these effects, new treatment strategies can be proposed for many inflammatory diseases caused by efferocytosis disorders. This review article aims to investigate the role of EVs during efferocytosis and its potential clinical applications in inflammatory diseases.

Therapeutic Potential of Piperine: A Comprehensive Review

Abstract: Piperine, an alkaloid from black pepper, has demonstrated diverse pharmacological properties and potential therapeutic applications. Piperine content varies with the pepper plant and ranges from 2 to 7.4% in black pepper. Piperine possesses remarkable biological properties, including antioxidant, anti-inflammatory, antibacterial, anticancer, neuroprotective, and hepatoprotective qualities. Its ability to affect numerous signaling pathways and biological targets implicated in disease development is responsible for these functions. Studies have shown piperine to have high antioxidant activity, which aids in reducing oxidative stress and preventing cellular damage. It has been established that its anti-inflammatory effects suppress the generation of pro-inflammatory mediators, thereby relieving inflammation-related diseases. This review emphasizes and examines piperine's medical and health-promoting benefits and proposed mechanisms of action in health promotion and illness prevention.

In Vivo Microwave-Induced Thermoacoustic Endoscopy for Colorectal Tumor Detection in Deep Tissue.

Optical endoscopy, as one of the common clinical diagnostic modalities, provides irreplaceable advantages in the diagnosis and treatment of internal organs. However, the approach is limited to the characterization of superficial tissues due to the strong optical scattering properties of tissue. In this work, a microwave-induced thermoacoustic (TA) endoscope (MTAE) was developed and evaluated. The MTAE system integrated a homemade monopole sleeve antenna (diameter = 7 mm) for providing homogenized pulsed microwave irradiation to induce a TA signal in the colorectal cavity and a side-viewing focus ultrasonic transducer (diameter = 3 mm) for detecting the TA signal in the ultrasonic spectrum to construct the image. Our MTAE, system combined microwave excitation and acoustic detection; produced images with dielectric contrast and high spatial resolution at several centimeters deep in soft tissues, overcome the current limitations of the imaging depth of optical endoscopy and mechanical wave-based imaging contrast of ultrasound endoscopy, and had the ability to extract complete features for deep location tumors that could be infiltrating and invading adjacent structures. The practical feasibility of the MTAE system was evaluated i n vivo with rabbits having colorectal tumors. The results demonstrated that colorectal tumor progression could be visualized from the changes in electromagnetic parameters of the tissue via MTAE, showing its potential clinical application.

A Time Delay Estimation Interpretation of Extended State Observer-Based Controller With Application to Structural Vibration Suppression

This paper aims to investigate the disturbance estimation mechanism of extended state observer (ESO) from a new perspective: a time-delay estimation (TDE) interpretation. By drawing the concept of input-output linearization, ESO is transformed into an equivalent TDE form in frequency domain. The establishment of this relationship can lead to an improved understanding of ESO’s principle. In addition, ESO’s parameters for disturbance estimation are given with explicitly physical meanings. Furthermore, theoretical analysis from this perspective also results in a quantitative relationship between ESO estimation performance and its two tuning parameters including control gain <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$b_0$</tex-math> </inline-formula> and bandwidth <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\omega _o$</tex-math> </inline-formula> . Theoretical results are evaluated by using an all-clamped plate structure with an inertial actuator, which is considered to be a typical benchmark for active vibration control. Extensive comparative experiments validate algorithm effectiveness. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper was focused on the ability of extended state observer (ESO) to estimate total disturbances. The controlled system is a typical benchmark for active vibration control consisting of an all-clamped plate structure with an inertial actuator. The model uncertainties and external disturbances that bothers the system is compensated by the real-time estimation of the ESO. In order to facilitate practical engineering applications, the distinct physical meanings of ESO parameters are expounded with the help of the relationship between ESO and time delay estimation (TDE) established in frequency domain. Moreover, the influence of parameters control gain <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$b_0$</tex-math> </inline-formula> and bandwidth <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\omega _o$</tex-math> </inline-formula> on ESO is qualitatively established. Therefore, the engineer can avoid fall into a trial-and-error strategy that could be laborious and time-consuming. Thus, this paper proposed a convenient way for practitioners interested in developing anti-disturbance control strategies based on ESO. The simplicity and the partial-model-based characteristics are also profitable in practice. Potential applications include robotic systems, smart structures and electrical drives. In the future, the improvements of ESO based on the proposed method to deal with the intractable disturbances should be taken in an effort.

Hybrid Wi-Fi and PLC network for efficient e-health communication in hospitals: a prototype

E-health is being adapted in modern hospitals as a significant addition to the existing healthcare services. To this end, modern hospitals urgently require a mobile, high-capacity, secure, and cost-effective communication infrastructure. In this paper, we explore potential applications of a hybrid broadband power line communication (PLC) and Wi-Fi in an indoor hospital scenario. It utilizes the existing power line cables and Wi-Fi plug-and-play devices for indoor broadband communication. Broadband power line (BPL) adaptors with Wi-Fi outputs are used to build an access network in hospitals, particularly in areas where the wireless router signal is poor. The Tenda PH10 AV1,000 AC Wi-Fi power line adapter is a set of BPL adapters that offer operational bandwidth of up to 1,000 Mbps. These adapters are based on the HomePlug AV2 protocol and can provide a data rate up to 200 Mbps on the physical layer. An experiment using the PLC Wi-Fi kit is carried out to show that a Wi-Fi and PLC hybrid network is the best candidate to provide wide range of practical applications in a hospital including, but not limited to, telemedicine, electronic medical records, early-stage disease diagnosis, health management, real-time monitoring, and remote surgeries.

Use of the Win Ratio Analysis in Critical Care Trials.

Composite outcomes are commonly used in critical care trials to estimate the treatment effect of an intervention. A significant limitation of classical analytic approaches is that they assign equal statistical importance to each component in a composite, even if these do not have the same clinical importance (i.e., in a composite of death and organ failure, death is clearly more important). The win ratio (WR) method has been proposed as an alternative for trial outcomes evaluation, as it effectively assesses events based on their clinical relevance (i.e., hierarchical order) by comparing each patient in the intervention group with their counterparts in the control group. This statistical approach is increasingly used in cardiovascular outcome trials. However, WR may be useful to unveil treatment effects also in the critical care setting, because these trials are typically moderately sized, thus limiting the statistical power to detect small differences between groups, and often rely on composite outcomes that include several components of different clinical importance. Notably, the advantages of this approach may be offset by several drawbacks (such as ignoring ties and difficulties in selecting and ranking endpoints) and challenges in appropriate clinical interpretation (i.e., establishing clinical meaningfulness of the observed effect size). In this perspective article, we present some key elements to implementing WR statistics in critical care trials, providing an overview of strengths, drawbacks, and potential applications of this method. To illustrate, we conduct a reevaluation of the HYPO-ECMO (Hypothermia during Venoarterial Extracorporeal Membrane Oxygenation) trial using the WR framework as a case example.

Temperature sensing of novel Tb3+/Ho3+/Bi3+ co-doped lead-free double perovskite Cs2AgInCl6 nanocrystals

Up to now, the research field of application of lanthanide ions doped lead-free double perovskite Cs2AgInCl6 nanocrystals (NCs) was relatively limited, even less in temperature sensing. Here, Tb3+/Ho3+/Bi3+ ions were successfully doped into Cs2AgInCl6 NCs by hot-injection. The temperature sensing performance of co-doped NCs by using the fluorescence intensity ratio (FIR) was studied through the temperature-dependent emission spectra. By analyzing the influence of ions' doping concentration on temperature sensing performance, the optimal doping concentration of co-doped Cs2AgInCl6 NCs was determined to be 7 % Tb3+, 20 % Ho3+ and 1 % Bi3+. The highest absolute and relative sensitivities reach 1.48 K−1 and 2.48 %/K, respectively. We provide a new doping scheme of lead-free double perovskite NCs which have good temperature sensing performance. This co-doped NCs have great potential application value in non-contact temperature sensing in nanoscale.

224 Artificial Intelligence-based Decision Support Predicts Requirement for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool (ASIST-TBI) Development, Validation and Simulated Prospective Deployment

INTRODUCTION: Artificial intelligence (AI) model integration into clinical workflow offers potential to optimize decision-support for transfer of acute traumatic brain injury (TBI) patients to appropriate trauma centers. METHODS: We retrospectively identified TBI patients from 2005-2021 treated at a quaternary Canadian trauma center. We employed various modeling techniques including principal component analysis, three-dimensional convolutional neural networks, and a transformer-based approach using Vision Transformer (ViT) architecture. Model training, validation, and testing was performed using head CT scans with binary ground truth labels corresponding to whether the patient received neurosurgical intervention witin 72 hours. The finalized model, termed Automated Surgical Intervention Support Tool for TBI (ASIST-TBI), was then deployed in a simulated prospective fashion on consecutive TBI patients at our center between March 2021 - September 2022. RESULTS: A dataset of 2,806 trauma patients with acute head CT scans were divided into training, validation, and testing groups; the ViT model exhibited optimal performance. There was accurate prediction of requirement for neurosurgical intervention with an area under the receiver operating curve (AUC) of 0·92, accuracy of 0·87, sensitivity of 0·87, and specificity of 0·88 on the testing cohort. In simulated 18-month prospective deployment, an additional 612 consecutive scans were used to assess the performance of ASIST-TBI. Classification accuracy remained robust with AUC of 0·89, 0·85 sensitivity, 0·84 specificity, and 0·84 accuracy. We manually reviewed false positive and false negative cases to identify reasons for misclassification. CONCLUSIONS: We developed a novel deep learning model that accurately predicts requirement for acute neurosurgical intervention using unlabeled TBI scans. ASIST-TBI has potential application to optimize state-wide triage efficiency and care pathways for brain-injured patients.

Isatin Derivatives: A Frontier in Antimicrobial Agents

Abstract: Microbial infection is one of the major concerns for human health in the modern era. Condition is further worsening due to the development of resistance by the microbe against the available drugs. This problem can be overcome by synthesizing novel antimicrobial agents. Isatin is a promising moiety possessing antimicrobial activity. A number of isatin derivatives are present in the market for the treatment of microbial infection. In this review, we have tried to summarize isatin derivatives as antimicrobials, including numerous potent isatin analogs. The reported literature related to the development and application of isatin derivatives have been collected from electronic data bases like Science Direct, Google Scholar, and PubMed by using key words like “design, synthesis and evaluation”, “isatin derivatives,” and “indoldione analogues” and related combinations. It was identified that isatin derivatives play an essential role in drug discovery and development. In recent years, isatin and its derivatives have shown promising antibacterial and antiviral properties. This review aims to provide an overview of the current research on isatin potential applications. Studies have shown that isatin derivatives can effectively fight against various types of microorganisms, such as gram-negative and gram-positive bacteria. They also exhibit lower toxicity and better efficacy than standard antimicrobial agents. Moreover, isatin-based products have the potential to address the rising issue of antimicrobial resistance. The current work attempts to review such innovations, which may lead to the creation of novel therapeutic agents. More research is required to confirm their safety and effectiveness in clinical practice.

A Stepwise Multivariate Granger Causality Method for Constructing Hierarchical Directed Brain Functional Network.

The directed brain functional network construction gives us the new insights into the relationships between brain regions from the causality point of view. The Granger causality analysis is one of the powerful methods to model the directed network. The complex brain network is also hierarchically constructed, which is particularly suited to facilitate segregated functions and the global integration of the segregated functions. Therefore, it is of great interest to explore new approach to model the hierarchical architecture of the directed network. In the present study, we proposed a new approach, namely, stepwise multivariate Granger causality (SMGC), considering both the directed and hierarchical features of brain functional network to explore the stepwise causal relationship in the network. The simulation study demonstrated that the diverse and complex hierarchical organization could be embedded in the apparently simple directed network. The proposed SMGC method could capture the multiple hierarchy of the directed network. When applying to the real functional magnetic resonance imaging (fMRI) datasets, the core triple resting-state networks in human brain showed within-network directed connections in the first-level directed network and rich and diverse between-network pathways in the second-level hierarchical network. The default mode network (DMN) had a prominent role in the resting-state acting as both the causal source and the important relay station. Further exploratory research on the adaption of directed hierarchical network in athletes suggested the enhanced bidirectional communication between the DMN and the central executive network (CEN) and the enhanced directed connections from the salience network (SN) to the CEN in the athlete group. The SMGC approach is capable of capturing the hierarchical architecture of the brain directed functional network, which refreshes the new stepwise causal relationship in the directed network. This might shed light on the potential application for exploring the altered hierarchical organization of brain directed network in neuropsychiatric disorders.

Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements

This paper addresses a bearing-only formation tracking problem in robotic networks by considering exogenous disturbances and actuator faults. In contrast to traditional position-based coordination strategies, the bearing-only coordinated movements of the unmanned vehicles only rely on the neighboring bearing information. This feature can be utilized to reduce the sensing requirements in the hardware implementation. A gradient-descent protocol is first developed to achieve the desired coordination within a prespecified settling time, where the unknown disturbances are considered in the vehicle dynamics, then the bound of formation tracking error is guaranteed by the Lyapunov approach. In case of damage to the actuators (e.g., motors) in some of the vehicles during the task, fault-tolerant analysis of the proposed controller is provided to ensure the success of the task in extreme environments. Furthermore, the proposed bearing-based method is extended to deal with general linear systems, which can be applied to a wider range of robotic platforms. Finally, numerical simulations and lab-based experiments using unmanned ground vehicles are conducted to validate the effectiveness of the proposed strategy. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The aim of this paper is to develop and design a practical bearing-only formation control approach for multi-vehicle systems. Many real-world complex tasks can be solved by multiple unmanned aerial and ground vehicles being connected by a communication network. This paper has proposed a formation tracking scheme for networked multi-vehicle systems that only relies on the relative bearing information of the neighboring vehicles. Closed-loop stability of the scheme and finite-time convergence of the tracking error have been established using the Lyapunov stability approach. The proposed method ensures the robustness and fault-tolerance of the multi-vehicle system against hardware faults or exogenous disturbances. A systematic set of guidelines on how to apply the proposed strategy in practice is also provided for the control practitioners in the form of an algorithm. In order to demonstrate the feasibility and usefulness of the proposed coordination scheme, numerical simulations and lab-based hardware experiments were conducted. Potential applications of the proposed scheme include search and rescue, security surveillance and cooperative exploration.

Numerical and experimental assessment of tilted-helical fiber orientation effects on deformation of pneumatic soft actuators

Pneumatic actuation of fiber-reinforced soft-material slender structures, and specifically inflatable cylinders, plays a key role in soft robotics, particularly for generating sought deformations in terms of, e.g. elongation, expansion, torsion, and bending. Fiber-reinforced tubes were widely investigated, in particular by considering regular helical patterns for the fibers, and multiple sets of fibers were introduced for achieving relatively richer deformations such as coiling (i.e. combined bending and torsion). However, coiling can be obtained even by introducing a single tilted-helical fiber, thus potentially simplifying actuator design and implementation. Therefore, in this study, we numerically investigated the effect of fiber orientation on the coiling behavior of tilted-helical fiber-reinforced cylindrical actuators. Specifically, we used finite element numerical simulations to determine the effect of fiber pitch and tilt angle on the curvature and twist angle of an inflated cylindrical actuator, and we assessed numerical results based on corresponding experiments. Finally, we addressed a preliminary design chart based on the inverse map linking coiling to the corresponding pitch and tilt angle. Our results take an initial step for the design of tilted-helical fiber-reinforced actuators, with potential application to a wider class of inflatable soft actuators to program a desired coiled configuration through the integration of a single tilted-helical fiber.

The 30,000 Foot View: Using Big Data to Address Complex Clinical Questions in the Most Vulnerable Older Adults

Older people of color, those who are socially isolated, veterans, and incarcerated older adults experience disparities in mental healthcare and high levels of psychiatric and physical comorbidity, including increased risk of suicide. The identification of risk factors and understanding the culture and context that impact risk are major public health challenges. Effective approaches to address these challenges are likely to involve using national databases and applying advanced methodologies to address complex clinical questions in older adults. By leveraging extensive epidemiological datasets, we can effectively pinpoint risk factors and consequences associated with mental health disorders in later stages of life. Moreover, these datasets allow us to disaggregate heterogeneous groups which are often treated as homogeneous (e.g. people of color, veterans, etc.). This disaggregation may reveal significant within group differences and provide important contextual information regarding these groups which can be used to deliver precision mental healthcare in an efficient manner and reduce the burden of mental illness in late life. In this session, we will explore innovative methodologies of utilizing national datasets to discern the cultural and contextual elements that impact the mental health and well-being of four high-risk, older adult populations. Emphasis will be placed on identifying patterns in mental healthcare disparities and comprehending how factors such as race, ethnicity, sex, gender, and incarceration contribute to feelings of loneliness, suicide rates, and dementia. Furthermore, we will also discuss the potential application of this data in developing precise risk assessment tools and targeted prevention and treatment strategies. interventions for late-life mental health issues.