Active Tracking Research Articles

Molecular mechanisms of the chemical constituents from anti-inflammatory and antioxidant active fractions of Ganoderma neo-japonicum Imazeki

Ganoderma neo-japonicum Imazeki is a rare medicinal mushroom that has been reported to play a role in scavenging free radicals, protecting the liver, and inhibiting tumor cell activity. In this study, crude extracts were prepared, and 47 triterpenoids were identified by Ultra-high-performance liquid chromatography coupled with triple quadrupole time-of flight mass spectrometry (UHPLC-Triple TOF-MS/MS). Then, the crude extracts were subjected to column chromatography for the first time to obtain six fractions (Fr. (a), (b), (c), (d), (e) and (f)). Antioxidant and anti-inflammatory active tracking assays of all fractions found that Fr. (c) exhibited the strongest bioactivity. Subsequently, the chemical composition of Fr. (c) was clarified, and eight triterpenoids were determined in combination with the standard substances. In addition, this study demonstrated that Fr. (c) reduced the levels of inflammatory cytokines and reactive oxygen species (ROS) in LPS-stimulated RAW264.7 macrophages. Further studies showed that Fr. (c) could down-regulate the expression level of proteins associated of NF-κB signaling pathway, and upregulated Nrf2 and HO-1 protein level. In conclusion, our study showed that Fr. (c) inhibited LPS-mediated inflammatory response and oxidative stress by activating the Nrf2/HO-1 pathway and inactivating the NF-κB pathway. In the future, with the clearing of its composition and activity mechanism, Fr. (c) of G. neo-japonicum are expected to become a functional food for health and longevity.

Silent active device tracking for MR-guided interventional procedures.

To evaluate a silent MR active catheter tracking sequence that allows conducting catheter interventions with low acoustic noise levels. To reduce the acoustic noise associated with MR catheter tracking, we implemented a technique previously used in conventional MRI. The gradient waveforms are modified to reduce the sound pressure level (SPL) and avoid acoustic resonances of the MRI system. The efficacy of the noise reduction was assessed by software-predicted SPL and verified by measurements. Furthermore, the quality of the catheter tracking signal was assessed in a phantom experiment and during interventional cardiovascular MRI sessions targeted at isthmus-related flutter ablation. The maximum measured SPL in the scanner room was 104dB(A) for real-time imaging, and 88dB(A) and 69dB(A) for conventional and silent tracking, respectively. The SPL measured at different positions in the MR suite using silent tracking were 65-69dB(A), and thus within the range of a normal conversation. Equivalent signal quality and tracking accuracy were obtained using the silent variant of the catheter tracking sequence. Our results indicate that silent MR catheter tracking capabilities are identical to conventional catheter tracking. The achieved acoustic noise reduction comes at no penalty in terms of tracking quality or temporal resolution, improves comfort and safety, and can overcome the need for MR-compatible communication equipment and background noise suppression during the actual interventional procedure.

The Influence of Knowledge Management and Islamic Leadership on Organizational Decision Making for Middle School Muslim Youth Development

Islamic youth development and da'wah organizations frequently face constraints in the decision-making process, both those carried out in the secondary level education sector. This is caused by the low effectiveness of the knowledge sharing process carried out between members, the lack of direction and support from the leadership or strategy, and the low quality of information management are the main factors for failure in the knowledge management process in a work program as well as the overall activities of Islamic youth da'wah organizations. The lack of facilities in managing the historical activity track record has hampered the decision-making process in organizational knowledge. Misunderstandings and lack of knowledge also lead to the loss of ghirah (da'wah motivation) and ukhuwah (familial relationships) in Islamic youth da'wah organizations in the education sector. This study aims to prove how knowledge management activities carried out in a structured manner by da'wah organizations, which aim to guide Islamic youth in high school (SMA/K) and junior high school (SMP) can transform information into valuable assets in managing Islamic da'wah operations and decision making that need to be carried out by the organization in the long term based on the determining factors, including managing aspects of knowledge management and Islamic-based leadership character. The methods and data processing carried out in this study used a quantitative-confirmatory approach and used multiple linear regression analysis, through the distribution of questionnaires to members of the XYZ high school Muslim youth development organization in Bandung Regency. The results and conclusions of this study prove that there is a significant positive influence from the application of knowledge management carried out in a structured manner up to 47.1% and Islamic-based leadership abilities up to 41.9%, on the decision-making process of Muslim youth development organizations in secondary schools, as well as Islamic-based education in general.

Longitudinally tracking personal physiomes for precision management of childhood epilepsy.

Our current understanding of human physiology and activities is largely derived from sparse and discrete individual clinical measurements. To achieve precise, proactive, and effective health management of an individual, longitudinal, and dense tracking of personal physiomes and activities is required, which is only feasible by utilizing wearable biosensors. As a pilot study, we implemented a cloud computing infrastructure to integrate wearable sensors, mobile computing, digital signal processing, and machine learning to improve early detection of seizure onsets in children. We recruited 99 children diagnosed with epilepsy and longitudinally tracked them at single-second resolution using a wearable wristband, and prospectively acquired more than one billion data points. This unique dataset offered us an opportunity to quantify physiological dynamics (e.g., heart rate, stress response) across age groups and to identify physiological irregularities upon epilepsy onset. The high-dimensional personal physiome and activity profiles displayed a clustering pattern anchored by patient age groups. These signatory patterns included strong age and sex-specific effects on varying circadian rhythms and stress responses across major childhood developmental stages. For each patient, we further compared the physiological and activity profiles associated with seizure onsets with the personal baseline and developed a machine learning framework to accurately capture these onset moments. The performance of this framework was further replicated in another independent patient cohort. We next referenced our predictions with the electroencephalogram (EEG) signals on selected patients and demonstrated that our approach could detect subtle seizures not recognized by humans and could detect seizures prior to clinical onset. Our work demonstrated the feasibility of a real-time mobile infrastructure in a clinical setting, which has the potential to be valuable in caring for epileptic patients. Extension of such a system has the potential to be leveraged as a health management device or longitudinal phenotyping tool in clinical cohort studies.

Vehicle Stability Analysis under Extreme Operating Conditions Based on LQR Control.

Under extreme working conditions such as high-speed driving on roads with a large road surface unevenness coefficient, turning on a road with a low road surface adhesion coefficient, and emergency acceleration and braking, a vehicle's stability deteriorates sharply and reduces ride comfort. There is extensive existing research on vehicle active suspension control, trajectory tracking, and control methods. However, most of these studies focus on conventional operating conditions, while vehicle stability analysis under extreme operating conditions is much less studied. In order to improve the stability of the whole vehicle under extreme operating conditions, this paper investigates the stability of a vehicle under extreme operating conditions based on linear quadratic regulator (LQR) control. First, a seven degrees of freedom (7-DOF) dynamics model of the whole vehicle is established based on the use of electromagnetic active suspension, and then an LQR controller of the electromagnetic active suspension is designed. A joint simulation platform incorporating MATLAB and CarSim was built, and the CarSim model is verified by real vehicle tests. Finally, the stability of the vehicle under four different ultimate operating conditions was analyzed. The simulation results show that the root mean square (RMS) values of body droop acceleration and pitch angle acceleration are improved by 57.48% and 28.81%, respectively, under high-speed driving conditions on Class C roads. Under the double-shift condition with a low adhesion coefficient, the RMS values of body droop acceleration, pitch acceleration, and roll angle acceleration are improved by 58.25%, 55.41%, and 31.39%, respectively. These results indicate that electromagnetic active suspension can significantly improve vehicle stability and reduce driving risk under extreme working conditions when combined with an LQR controller.

Evaluating Data Stability During Active Head-Eye Tracking: A Comparison of Dynamic Gaze Error between Two Custom-Built Head-Mounted Devices

Evaluating Data Stability During Active Head-Eye Tracking: A Comparison of Dynamic Gaze Error between Two Custom-Built Head-Mounted Devices

Space Noncooperative Object Active Tracking With Deep Reinforcement Learning

Actively tracking an arbitrary space noncooperative object relied on visual sensor remains a challenging problem. In this article, we provide an open-source benchmark for space noncooperative object visual tracking including simulated environment, evaluation toolkit, and a position-based visual servoing (PBVS) baseline algorithm, which can facilitate the research in this topic especially for those methods based on deep reinforcement learning. We also present an end-to-end active visual tracker based on deep Q-learning, named as DRLAVT, which learns approximately optimal policy merely took color or RGBD images as input. To the best of authors knowledge, it is the first intelligent agent used for active visual tracking in aerospace domain. The experiment results show that our DRLAVT achieves an excellent robustness and real-time performance compared with the PBVS baseline, benefitted from the design of complex neural network and efficient reward function. In addition, the multiple targets training adopted in this article effectively guarantees the transferability of DRLAVT by forcing the agent to learn optimal control policy with respect to motion patterns of the target.

Challenges in the execution of public health research: Reflections from Public Health Research Initiative (PHRI) grant management in India.

Well-planned health research is fundamental to the success of any public health system in leading to better population health outcomes. Although the Indian public health system is unique, it lacks strong linkages between research and practice. There is a pressing need to address the gap in the research to reduce the disease burden in the country. Although various efforts are made to enhance public health research, such research is rarely documented as a process. The objective of the present paper is to document issues and challenges in managing public health research grants awarded to the PHRI fellows from 2013-to 2021 under the PHRI project. A mixed-method approach, including qualitative (in-depth) interviews and secondary review, was adopted to collect the challenges in executing PHRI grants (during 2013-2021). The in-depth interviews were conducted among the PHRI execution team, whereas the secondary document review was conducted among the PHRI fellows, and the findings are documented under major themes like administrative, technical, and financial issues and/or challenges. A total of 35 candidates 16 intramural (IM) candidates affiliated with PHFI or IIPH institutes and 19 extramural (EM) candidates affiliated to other academic institutes were selected for the fellowship, The common challenges identified amongst intra & extramural fellows were inability to disseminate the study findings, challenges in communication and getting audited statements, changes in study methods without prior permission, mid study attrition of CO-PIs and high budget utilization. The specific difficulties identified from extramural fellows were change in institute affiliation, lack of support to fund utilization from the parent institute and difficulties in field validation. The present perspective emphasizes that the management and implementation of a research grant is the crucial part of achieving a project's desired outcome. The learnings of PHRI grant execution allows the researchers to understand the issues in terms of methodological rigour and financial guidelines, rigorous tracking of the project activities, and complying with the terms of funding agreement are crucial. The challenges explored in this grant execution recommend developing a structured public health grant management leadership program for researchers and executors.

Mitigation of power oscillations for energy harvesting capability improvement of grid-connected renewable energy systems

The increasing penetration of renewable energy sources in the power system raises several challenges from the power quality and output power fluctuations point of view. However, the output power oscillations and power quality problems caused by the low order harmonic oscillations at the second-order frequency of the utility grid on the dc-link capacitor are emerging as major issues for the efficient operation of power converters. In this manner, a novel method based on modification in the control algorithm to alleviate the output power oscillation and reduce the output current total harmonic distortion is proposed. The proposed control approach seems as a promising solution for the satisfactory grid operation of renewable energy sources regarding not requiring any additional circuit and increment in the capacity of the dc-link capacitor. Moreover, mitigation of oscillations enhances the active power reference tracking capability of the controller that enables the overall efficiency improvement of the system. The performed case studies reveal that the overall efficiency rate of the system is increased by 1.3%. On the other hand, the output current harmonic distortion is decreased below 3% even under low power operating conditions. Also, the complexity level of the control algorithm is quite low for real-time implementation.

Trial-by-trial fluctuations in amygdala activity track motivational enhancement of desirable sensory evidence during perceptual decision-making.

People are biased toward seeing outcomes that they are motivated to see. For example, wanting their favored team to prevail biases sports fans to perceive an ambiguous foul in a manner that is favorable to the team they support. Here, we test the hypothesis that such motivational biases in perceptual decision-making are associated with amygdala activity. We used monetary incentives to experimentally manipulate participants to want to see one percept over another while they performed a categorization task involving ambiguous images. Participants were more likely to categorize an image as the category we motivated them to see, suggesting that wanting to see a particular percept biased their perceptual decisions. Heightened amygdala activity was associated with motivation consistent categorizations and tracked trial-by-trial enhancement of neural activity in sensory cortices encoding the desirable category. Analyses using a drift diffusion model further suggest that trial-by-trial amygdala activity was specifically associated with biases in the accumulation of sensory evidence. In contrast, frontoparietal regions commonly associated with biases in perceptual decision-making were not associated with motivational bias. Altogether, our results suggest that wanting to see an outcome biases perceptual decisions via distinct mechanisms and may depend on dynamic fluctuations in amygdala activity.

Are Some Ways of Expressing Gratitude More Beneficial Than Others? Results From a Randomized Controlled Experiment

Gratitude activities have been shown to increase well-being and other positive outcomes in numerous experiments to date. The current study tested whether self-directed gratitude interventions that vary by type (i.e., social vs. nonsocial) and format (i.e., long-form letters vs. shorter lists) produce differential benefits. To that end, 958 Australian adults were assigned to one of six activities to complete each day for 1 week, including five gratitude activities that varied by type and format and an active control condition (i.e., keeping track of daily activities). Regressed change analyses revealed that, overall, long-form writing exercises (i.e., essays and letters) resulted in greater subjective well-being and other positive outcomes than lists. Indeed, those who were instructed to write social and nonsocial gratitude lists did not differ from controls on any outcomes. However, participants who wrote unconstrained gratitude lists—that is, those who wrote about any topics they wanted—reported greater feelings of gratitude and positive affect than did controls. Finally, relative to the other gratitude conditions, participants who wrote gratitude letters to particular individuals in their lives not only showed stronger feelings of gratitude, elevation, and other positive emotions but also reported feeling more indebted. This study demonstrates that not only does gratitude “work” to boost well-being relative to an active neutral activity, but that some forms of gratitude may be more effective than others. We hope these findings help scholars and practitioners to develop, tailor, implement, and scale future gratitude-based interventions.

Dysbiosis of Gut Microbiota from the Perspective of the Gut-Brain Axis: Role in the Provocation of Neurological Disorders.

The gut-brain axis is a bidirectional communication network connecting the gastrointestinal tract and central nervous system. The axis keeps track of gastrointestinal activities and integrates them to connect gut health to higher cognitive parts of the brain. Disruption in this connection may facilitate various neurological and gastrointestinal problems. Neurodegenerative diseases are characterized by the progressive dysfunction of specific populations of neurons, determining clinical presentation. Misfolded protein aggregates that cause cellular toxicity and that aid in the collapse of cellular proteostasis are a defining characteristic of neurodegenerative proteinopathies. These disorders are not only caused by changes in the neural compartment but also due to other factors of non-neural origin. Mounting data reveal that the majority of gastrointestinal (GI) physiologies and mechanics are governed by the central nervous system (CNS). Furthermore, the gut microbiota plays a critical role in the regulation and physiological function of the brain, although the mechanism involved has not yet been fully interpreted. One of the emerging explanations of the start and progression of many neurodegenerative illnesses is dysbiosis of the gut microbial makeup. The present understanding of the literature surrounding the relationship between intestinal dysbiosis and the emergence of certain neurological diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis, is the main emphasis of this review. The potential entry pathway of the pathogen-associated secretions and toxins into the CNS compartment has been explored in this article at the outset of neuropathology. We have also included the possible mechanism of undelaying the synergistic effect of infections, their metabolites, and other interactions based on the current understanding.

A Trajectory Tracking Approach for Aerial Manipulators Using Nonsingular Global Fast Terminal Sliding Mode and an RBF Neural Network

An unmanned aerial manipulator (UAM) is a novel flying robot consisting of an unmanned aerial vehicle (UAV) and a multi-degree-of-freedom (DoF) robotic arm. It can actively interact with the environment to conduct dangerous or inaccessible tasks for humans. Owing to the underactuated characteristics of UAVs and the coupling generated by the rigid connection with the manipulator, robustness and a high-precision controller are critical for UAMs. In this paper, we propose a nonsingular global fast terminal sliding mode (NGFTSM) controller for UAMs to track the expected trajectory under the influence of disturbances based on a reasonably simplified UAM system dynamics model. To achieve active anti-disturbance and high tracking accuracy in a UAM system, we incorporate an RBF neural network into the controller to estimate lumped disturbances, including internal coupling and external disturbances. The controller and neural network are derived according to Lyapunov theory to ensure the system’s stability. In addition, we propose a set of illustrative metrics to evaluate the performance of the designed controller and compare it with other controllers by simulations. The results show that the proposed controller can effectively enhance the robustness and accuracy of a UAM system with satisfactory convergence. The experimental results also verify the effectiveness of the proposed controller.

A survey of catheter tracking concepts and methodologies.

Catheter tracking has become an integral part of interventional radiology. Over the last decades, researchers have significantly contributed to theoretical and technical catheter tracking solutions. However, most of the published work thus far focuses on a single application or a single tracking technology. This paper provides an exhaustive review of the state-of-the-art for catheter tracking in general by analyzing significant contributions in this field. We first present a historical overview that led to catheter tracking and continue with a survey of leading tracking technologies. These include image-based tracking, active and passive tracking, electromagnetic tracking, fiber optic shape sensing, bioelectric navigation, robotic tracking solutions, and hybrid tracking. As for imaging modalities, the focus is on x-ray based modalities, ultrasound, and magnetic resonance imaging. Finally, we review each tracking technology with respect to the imaging modality and establish the relation between the two and the underlying anatomy of interest.

Proposal for detecting coconut rhinoceros beetle breeding sites using harmonic radar

Coconut rhinoceros beetle (CRB), a major pest of coconut and oil palms, is causing severe economic and environmental damage following recent invasions of several Pacific islands. Population suppression and eradication of this pest requires location and destruction of active and potential breeding sites where all life stages aggregate. Three search tactics for discovering breeding sites have been used with limited success: visual search by humans, search with assistance from detector dogs and search by tracking CRB adults fitted with radio transmitters. Here, we suggest a fourth search tactic: releasing CRB adults fitted with harmonic radar tags to locate breeding sites. Our idea is to find static end points for tags which accumulate at breeding sites, rather than active tracking of individual beetles. We plan to use commercially available hand-held harmonic radar devices. If we are successful, this technique may be useful for locating other insects which aggregate, such as hornets and other social insects.

Portable High-Speed Optical Gaze Controller with Vision Chip

It is important to miniaturize robot systems while maintaining advantages such as high responsiveness and functionality for human-machine interactions and for achieving integration with other robotic systems such as drones. In this research, we focused on the miniaturization of a high-speed visual feedback system, and developed a “portable saccade mirror,” which is a system that can realize active target tracking using 1000 Hz image capturing, processing, and feedback actuation with only 3 ms latency in a handheld device. By using a three-dimensionally-stacked vision chip, the proposed system achieved high speed, low latency, low power consumption and compact size, and therefore, can be considered as a good example of a miniaturized high-speed visual feedback system. In this study, we evaluated the performance of the proposed system in comparison with the conventional optical gaze controller, and demonstrated some applications, such as tracking field scope and panorama target scanning.

Spectral brain signatures of aesthetic natural perception in the α and β frequency bands.

During our everyday lives, visual beauty is often conveyed by sustained and dynamic visual stimulation, such as when we walk through an enchanting forest or watch our pets playing. Here, I devised an MEG experiment that mimics such situations: participants viewed 8 s videos of everyday situations and rated their beauty. Using multivariate analysis, I linked aesthetic ratings to 1) sustained MEG broadband responses and 2) spectral MEG responses in the α and β frequency bands. These effects were not accounted for by a set of high- and low-level visual descriptors of the videos, suggesting that they are genuinely related to aesthetic perception. My findings provide the first characterization of spectral brain signatures linked to aesthetic experiences in the real world.NEW & NOTEWORTHY In the real world, aesthetic experiences arise from complex and dynamic inputs. This study shows that such aesthetic experiences are represented in a spectral neural code: cortical α and β activity track our judgments of the aesthetic appearance of natural videos, providing a new starting point for studying the neural correlates of beauty through rhythmic brain activity.

Multipath Data Fusion With Recursive ML-PDA and Generative ML-PMHT for VLO Targets in Underwater Environment

We discuss and extend two approaches to target detection and motion parameter estimation in a very low observable (VLO) underwater multipath environment. The maximum likelihood probabilistic data association (ML-PDA) algorithm considers all possible path–measurement hypotheses, whereas the maximum likelihood probabilistic multiple hypothesis tracker (ML-PMHT) assumes independence among the returns’ origins leading to a simpler likelihood formulation. In particular, we present a recursive form of the multipath ML-PDA algorithm for improved computational efficiency and a generative multipath ML-PMHT algorithm that accounts for the prior probability distribution of the number of received measurements. By simulation of an active sonar tracking scenario, we show that while the two algorithms perform similarly for few returns, the added fidelity of the ML-PDA outperforms the ML-PMHT in parameter estimation as returns accumulate over multiple scans and dimensions. However, the computational cost of the ML-PDA discourages its use beyond simple scenarios. This cost, coupled with the comparable detection performance of the two algorithms, suggests that the simpler ML-PMHT is the better choice for practical use. We also show how both the ML-PDA and ML-PMHT can be applied to realistic ocean environments using ocean acoustic modeling software. This article is an extension of previous work on comparing the standard versions of the ML-PDA and ML-PMHT algorithms.

Lateral septum modulates cortical state to tune responsivity to threat stimuli

Sudden unexpected environmental changes capture attention and, when perceived as potentially dangerous, evoke defensive behavioral states. Perturbations of the lateral septum (LS) can produce extreme hyperdefensiveness even to innocuous stimuli, but how this structure influences stimulus-evoked defensive responses and threat perception remains unclear. Here, we show that Crhr2-expressing neurons in mouse LS exhibit phasic activation upon detection of threatening but not rewarding stimuli. Threat-stimulus-driven activity predicts the probability but not vigor or type of defensive behavior evoked. Although necessary for and sufficient to potentiate stimulus-triggered defensive responses, LSCrhr2 neurons do not promote specific behaviors. Rather, their stimulation elicits negative valence and physiological arousal. Moreover, LSCrhr2 activity tracks brain state fluctuations and drives cortical activation and rapid awakening in the absence of threat. Together, our findings suggest that LS directs bottom-up modulation of cortical function to evoke preparatory defensive internal states and selectively enhance responsivity to threat-related stimuli.

Social CRM: linking the dots of customer service and customer loyalty during COVID-19 in the hotel industry

PurposeSocial customer relationship management (SCRM) is an evolving strategy gaining prominence in the hotel industry by cultivating new, improved relationships through engaging customers on social media (SM) platforms. Accordingly, this study aims to assess the effect of SCRM on customer service and customer loyalty (CL) in the hotel industry. This study also explores the moderating effect of COVID-19 (EC) on the relationship between (customer engagement [CE] and improved customer service [ICS]) and (CE and trust [TR]).Design/methodology/approachThis study develops and tests the SCRM model using structural equation modelling on a sample size of 214 responses. The questionnaire was administered online to the customers of five preselected global hotel chains. The criteria for selecting the participants were that they must have tweeted from their Twitter handle by using # (hashtag) hotel name to resolve any customer service issues.FindingsResults denote that CE significantly impacts ICS. CE was also found to exert a substantial effect on TR. The moderating EC was also found to be significant, but the effect was weak. Although the customers were extensively impacted by the pandemic and were initially hesitant to visit hotels, SCRM proved to be a powerful tool to gain back customer trust (CT) and develop CL by upsurging the shadows of COVID-19.Practical implicationsThis study suggests that viable enforcement of the SCRM system can assist in real-time monitoring and tracking of customers' activities. This can develop a more profound connection with customers through CE which can boost the co-innovation process.Originality/valueThis study denotes a pioneer attempt to investigate the relationships between SCRM, CE, CT, ICS, CL and COVID-19 in the same framework in a SM context.