Since it was proposed, the Robot Operating System (ROS) has fostered solutions for various problems in robotics in the form of ROS packages. One of these problems is Simultaneous Localization and Mapping (SLAM), a problem solved by computing the robot pose and a map of its environment of operation at the same time. The increasingly availability of robot kits ready to be programmed and also of RGB-D sensors often pose the question of which SLAM package should be used given the application requirements. When the SLAM subsystem must deliver estimates for robot navigation, as is the case of applications involving autonomous navigation, this question is even more relevant. This work introduces an experimental analysis of GMapping and RTAB-Map, two ROS compatible SLAM packages, regarding their SLAM accuracy, quality of produced maps and use of produced maps in navigation tasks. Our analysis aims ground robots equipped with RGB-D sensors for indoor environments and is supported by experiments conducted on datasets from simulation, benchmarks and from our own robot.

The invasion of ship domain stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validated through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of collision risk. Finally, taking the high risk area of merchant and fishing vessels collision in the Minjiang River Estuary as an example, this paper conduct the analysis involves classifying ship collision scenarios, extracting risk data under different collision scenarios, and visually analyzing areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis is verified by accidents occurred in the recent three years.

A more sustainable society and economy also implies a more sustainable behavior in the consumption of financial products. A possible change in focus can come from the demand side, so that more sustainable consumption of financial products have to go hand to hand with financial literacy. However, financial literacy, potential favoring of this sustainable behavior, is far from reaching an international consensus about its definition, object and scope. Two objectives are analyzed; the different interpretations of financial literacy in the academic literature, as well as its evolution and how, in what context and with what other concepts the term is used in social networks. Scientometric techniques and content analysis have been used to carry out a systematic review of literature and also NLP to analyze the comments on Social Networks. Critical moments are identified in the definition of financial literacy. Also ten sentiments are analyzed in social networks in wich positivity, trust, and anticipation predominate. Greater attention to this issue is necessary both from the private initiative and from public policies, so that financial literacy is an effective tool for a more sustainable behavior by consumers. Finally, a new definition is proposed based on our findings.

This study presents the validation process of the Questionnaire on Academic Stress in Secondary Education –QASSE-, designed to assess the wide variety of school sources and situations related to academic stress in adolescence, and their relationship with students’ physical and psychological well-being. Participants were 860 Spanish high school students (52.9% girls) with an average age of 14.62 years (SD = 1.8). Through a cross-validation process, EFA and CFA supported QASSE multifactorial structure with four first-order factors -academic overload, interaction with classmates, family pressure, and future-oriented perspective- and a second-order factor of academic stress, showing a significant and intense relationship with adolescents’ psychological and physical well-being. Results also highlight the effects of the gender*educational level interaction on the students’ stress, with girls showing higher levels of stress in the transition courses between educational phases (sophomore and junior years). The QASSE demonstrates good validity and reliability, showing potential for both research and educational application. The results show the high impact of the QASSE dimensions on psychological and physical well-being in adolescence, highlighting its special usefulness for designing and adjusting educational prevention and intervention actions in this area to the students’ specific characteristics and needs

Type 2 diabetes mellitus (T2DM) accounts for one-sixth of deaths, globally, whereas cancer is the second leading cause of death in the U.S. T2DM is a known risk factor for many cancers. This review examines the link of Reactive oxygen Species (ROS)-altered metabolic and signaling pathways in T2DM to cancer. These reprogrammed metabolic and signaling pathways are activated that contribute to diabetic complications, impact redox balance (Oxidative Stress), and have differential roles in early and late stages of cancer. If the respiratory chain is highly reduced (as under hyperglycemic conditions) or if reduced cofactors accumulate, ROS are greatly elevated. ROS may cause mutations in mitochondrial DNA (mtDNA) that result in further ROS elevation. Amplification of ROS results in activation of PKC, an overarching signaling pathway that activates MAPK with subsequent regulation of several factors that result in pathophysiological manifestations of T2DM and cancer. Upregulation of PKC leads to deregulation of NF-kß that regulates the PKB/P13/Akt pathway that orchestrates cell survival, growth, proliferation, and glucose metabolism manifested in cancer. It also affects Insulin Receptor Substrate (IRS-1), decreasing insulin stimulated glucose transport and glucose uptake, disrupting subsequent cell signaling pathways contributing to the development of T2DM. Dyslipidemia is a hallmark of T2DM and cancer. ROS-induced lipid peroxidation leads to systemic inflammation, producing inflammatory prostaglandins, cytokines and chemokines that result in tumor proliferation, rapid tumor growth, and modulation of immunity. The dual role of ROS in early and late stages of cancer make antioxidant therapy precarious and may be responsible for controversial results. A system that delivers an antioxidant directly to mitochondria may be useful in inhibiting formation of ROS early during the pre-diabetic stage whereas antioxidant therapy must be halted in later stages to retard metastasis.

The increasing emergence of multidrug resistant (MDR) pathogens causes difficult-to-treat infections, with long-term hospitalizations and high incidence of death, thus representing a global public health problem. To manage MDR bacteria bugs, new antimicrobial strategies are necessary, and their introduction in practice is a daily challenge for scientists in the field. An extensively studied approach to treat MDR infections consists in inducing high levels of reactive oxygen species (ROS) by several methods. Although further clinical investigations are mandatory on the possible toxic effects of ROS to mammalian cells, clinical evaluations are extremely promising, and their topical use to treat infected wounds and ulcers, also in presence of biofilm, is already clinically approved. Biochar (BC) is a carbonaceous material obtained by pyrolysis of different vegetable and animal biomass feedstocks, at 200−1000 °C in limited presence of O2. Recently, it has been demonstrated that BC capability of removing organic and inorganic xenobiotics is mainly due to the presence of persistent free radicals (PFRs), which can activate oxygen, H2O2 or persulfate in the presence or not of transition metals by electron transfer thus generating ROS, which in turn degrade pollutants by advanced oxidation processes (AOPs). In this context, the antibacterial effects of BC containing PFRs have been demonstrated by some authors against Escherichia coli and Staphylococcus aureus, thus giving birth to our idea of the possible use of BC-derived PFRs as a novel method capable of inducing ROS generation for antimicrobial oxidative therapy. Here, the general aspects concerning ROS physiological and pathological production and regulation, and the mechanism by which they could exert antimicrobial effects have been reviewed. The methods currently adopted to induce ROS production for antimicrobial oxidative therapy have been discussed. Finally, for the first time, BC-related PFRs have been proposed as a new source of ROS for antimicrobial therapy via AOPs.

Abstract: This study investigates the transition to sustainable shipping industry within the framework of the IMO's 2050 carbon neutrality objective, focusing on socio-technical systems analysis. The research delves into the sustainable paradigm shift towards alternative marine fuels such as LNG, methanol, ammonia, and hydrogen from a socio-technical transition perspective, analyzing the multi-level per-spective challenges and opportunities. Specifically, it scrutinizes the implications of adopting these al-ternative fuels for global shipping, identifying technical uncertainties, financial constraints, and infra-structure needs. Through a comprehensive review of existing literature on ship emissions and alterna-tive fuels, coupled with socio-technical transition theory, the study addresses the multifaceted chal-lenges and opportunities in meeting the IMO's environmental objectives. It emphasizes the necessity of collaborative governance, innovative niche strategies, and a holistic approach to leverage the current window of opportunity in facilitating the maritime industry's transition to sustainable fuel options. Fi-nally, this research enhances our understanding of the intricate interplay between technological, social, industrial, and cultural dynamics in the greening of shipping and offers insights into the strategic adop-tion of environmentally friendly marine fuels for a sustainable future.

Several disruptive attacks against companies in the maritime industry have led experts to consider the increased risk imposed by cyber threats as a major obstacle to undergoing digitization. The industry is heading toward increased automation and connectivity, leading to reduced human involvement in the different navigational functions and increased reliance on sensor data and software for more autonomous modes of operations. To meet the objectives of increased automation under the threat of cyber attacks, the different software modules that are expected to be involved in different navigational functions need to be prepared to detect such attacks utilizing suitable detection techniques. Therefore, we propose a systematic approach for analyzing the navigational NMEA messages carrying the data of the different sensors, their possible anomalies, malicious causes of such anomalies as well as the appropriate detection algorithms. The proposed approach is evaluated through two use cases, traditional Integrated Navigation System (INS) and Autonomous Passenger Ship (APS). The results reflect the utility of specification and frequency-based detection in detecting the identified anomalies with high confidence. Also, the analysis is found to facilitate the communication of threats through indicating the possible impact of the identified anomalies against the navigational operations. Moreover, we have developed a testing environment that facilitates conducting the analysis. The environment includes a developed tool, NMEA−Manipulator that enables the invocation of the identified anomalies through a group of cyber attacks on sensor data. Our work paves the way for future work in the analysis of NMEA anomalies toward the development of an NMEA intrusion detection system.

The morphologically variable moss Trichostomum brachydontium is very common in south and west Europe, particularly under Mediterranean and Atlantic climates. A morphological study was conducted alongside a molecular phylogenetic study based on nr ITS and cp rbcL regions in order to assess if T. brachydontium is an exceptionally polymorphic species as evidenced by the number of described infraspecific taxa from the last century or, alternatively, if it includes more than one species, and if so, to find the valid name for them. Phylogenetic analyses of both nuclear and chloroplast datasets show that there are four well-supported clades. While the ITS based tree is in good agreement with the morphological data, there are a few inconsistencies with reference to the rbcL tree; this may be explained by incomplete lineage sorting or by hybridization. The morphological survey revealed well-defined discriminate differences between the four phylogenetic lineages. The taxonomic conclusions include the recognition of four species: T. brachydontium s.s., T. herzogii (a new name proposed for var. cuspidatum), T. littorale and T. meridionale (a new name proposed for var. densum). Lectotypes are designated for T. brachydontium and T. littorale. Our results underline the ongoing need of integrative studies to examine further the underestimated diversity of the T. brachydontium complex in other regions.

Reductions in water availability and increasing rainfall variability are generating a narrative of growing competition for water in the Mediterranean basin. In this article, we explore the distribution and importance of water resources in the Muga River Basin (Catalonia, Spain) based on key stakeholders’ perceptions. We performed a sociocultural evaluation of the main water ecosystem services in the region through stakeholder interviews and participatory mapping. The basin was generally perceived as a hotspot of ecosystem services, but we detected varying opinions and considerable differences in the perceptions of importance and spatial distribution of water ecosystem services. These discrepancies were linked to the varying levels of stakeholders’ dependence on water. Our findings are important for contributing to correct water planning and management in the river basin, which is a complex water social system marked by conflicts between different stakeholder groups vying for the same resource. This complex situation requires bottom-up strategies to create transparent, participatory decision-making models.

Calculating a minimum-time trajectory requires the solving of a boundary value problem resulting from invocation of necessary conditions of optimality to set up a set of ordinary differential equations to solve the trajectory between the initial position and desired ending position with set constraints on the path between the two. This manuscript expresses the minimum time optimum trajectory between a satellite in a geosynchronous orbit and a target set on earth’s surface utilizing a non-rotating earth centric coordinate system. Expressing motion in coordinates of rotating reference frames necessitates transformation between reference frames, and one such transformation is embodied in the Direction Cosine Matrices (DCM) formed by a sequence of three successive frame rotations. Rotation about the local wing of an aerospace vehicle is almost never the pitch angle, yet modern application of kinematics often assumes such (with accompanying angular error). The same assertion is usually true about the nature of roll and yaw angles. This manuscript evaluates which sequence is the most advantageous for an object starting in space and then travels through the atmosphere to a target on the Earth’s surface. Simulation precision (validated by the quaternion normalization condition) reveals the so-called 132 rotation is the most accurate with an average error of 0.14° and a computational time of 0.013 seconds: resulting in a 97.95% increase in accuracy over the ubiquitous 321 “aerospace” rotation sequence and a 99.84% increase over the so-called 313 “orbital” rotation sequence. Utilizing the proposed optimal trajectory candidate yields a total flight time of 2 hours, 34 minutes and 46 seconds, or an average velocity of 3.85 kilometers per second, while impacting the target with a velocity of 11.54 kilometers per second.

This paper presents ROSGPT, an innovative concept that harnesses the capabilities of large language models (LLMs) to significantly advance human-robot interaction. We develop ROSGPT as a ROS2 package that seamlessly integrates ChatGPT with ROS2-based robotic systems. The core idea is to leverage prompt engineering with LLMs, specifically ChatGPT, utilizing its unique properties such as ability eliciting, chain-of-thought, and instruction tuning. The concept employs ontology development to convert unstructured natural language commands into structured robotic instructions specific to the application context through prompt engineering. We capitalize on LLMs' zero-shots and few-shots learning capabilities by eliciting \textit{structured} robotic commands from \textit{unstructured} human language inputs. To demonstrate the feasibility of this concept, we implemented a proof-of-concept that integrates ChatGPT with ROS2, showcasing the transformation of human language instructions into spatial navigation commands for a ROS2-enabled robot. This versatile concept can be easily adapted to various other robotic missions. ROSGPT serves as a new stride towards Artificial General Intelligence (AGI) and paves the way for the robotics and natural language processing communities to collaborate in creating novel, intuitive human-robot interactions. The open-source implementation of ROSGPT on ROS 2 is available on GitHub.

Indoor navigation systems must deal with absence of GPS signals, since they are only available in outdoor environments. Therefore, indoor systems have to rely upon other techniques for positioning users. Recently various indoor navigation systems have been designed and developed to help visually impaired people. In this paper an overview of some existing indoor navigation systems for visually impaired people are presented and they are compared from different perspectives. The evaluated techniques are ultrasonic systems, RFID-based solutions, computer vision aided navigation systems, ans smartphone-based applications.

Objective: To explore the effect of rural-urban residence on self-reported health status with UK cancer survivors. Design: A cross-sectional postal questionnaire that collected data on demographics, post-code and self-reported health status. Methods: Independent Samples t test was used to detect differences in health status between rural and urban respondents. Pearson’s χ2 was used to control for confounding variables and multivariate analysis was conducted using Stepwise linear regression. Setting: East Midlands of England. Participants: Adult cancer survivors who had undergone primary treatment in the last five years. Participants were excluded if they had recurrence or metastatic spread, started active oncology treatment in the last twelve months and were in receipt of palliative or end of life care. Main Outcome: Residence was measured using the UK ONS RUC2011 Rural-Urban Classifications and Health Status via the UK ONS self-reported health status measure. Results: 227 respondents returned a questionnaire. Forty-five per cent (N=103) were resident in a rural area and fifty-three per cent (N=120) in an urban area. Rural (4.11±0.85) respondents had significantly (p<0.001) higher self-reported health status compared to urban (3.65±0.93) respondents (MD 0.47; 95% CI 0.23, 0.70). Conclusion: Rural respondents had significantly higher self-reported health status compared to their urban counterparts. It is hoped that the results will stimulate further work in this area and that researchers will be encouraged to collect data on rural-urban residency where appropriate.

In order to enhance the accuracy of the relative velocity measurement for the Mars explorer formation flight, we develop a relative velocity measurement method. In this method, the spectrometers at two Mars explorers are adopted to measure the starlight frequency shift and to estimate the velocity with respect to the star. Unfortunately, the instantaneous velocity of star can not be predicted accurately, which results in a large error in the velocity measurement. The difference of these two velocities, which does not include the proper motion of star, is the relative velocity between a pair of Mars explorers at the direction of the star. However, this navigation method can not work alone because of unobservability. To make the navigation system observable and improve the accuracy of both absolute and relative navigation for the Mars explorer formation flight, we combine it with X-ray pulsar navigation and the inter-satellite links, and propose an autonomous integrated navigation method with observability. In this integrated navigation scheme, the extended Kalman filter is adopted to deal with the relative velocity, the inter-satellite links and the pulse time-of-arrival, and estimate the absolute and relative navigation information for the Mars explorer formation flight. The simulation results demonstrate that both absolute and relative navigation accuracy of the proposed method are higher than that of the pulsar navigation, especially the relative one.

Abiotic stress in plants is an increasingly common problem in agriculture, and thus, studies on plant treatments with specific certain compounds that may help to mitigate these effects have increased in recent years Melatonin (MET) application and its role in mitigating the negative effects of abiotic stress in plants have become important in the last few years. MET, a derivative of tryptophan, is an important plant-related response molecule involved in the growth, development, and reproduction of plants, and the induction of different stress factors. In addition, MET plays a protective role against different abiotic stresses such as salinity, high/low temperature, high light, waterlogging, nutrient deficiency and stress combination by regulating both the enzymatic and non-enzymatic antioxidant defense systems. Also, MET interacts with many signaling molecules, among these, reactive oxygen species (ROS) and nitric oxide (NO), and participates in a wide variety of physiological reactions. It is well known that NO produces S-nitrosylation and NO2-Tyr of important antioxidant-related proteins, being this an important mechanism for maintaining the antioxidant capacity of the AsA/GSH cycle under nitro-oxidative conditions, being extensively reviewed here under different abiotic stress conditions. Lastly, in this review, we show the coordination between NO and MET as a long-range signaling molecule, regulating many responses in plants, including plant growth and abiotic stress tolerance. Despite all the knowledge acquired over the years, there is still more to know about how MET and NO act on tolerance to abiotic stresses.

The enantioselective alpha-amination of 1,3-dicarbonyl compounds has been performed using a catalytic system based on deep eutectic solvents (DES) and chiral 2-amino benzimidazole-derived organocatalysts. This procedure avoids the use of toxic volatile organic compounds (VOCs) as a reaction medium, providing access to highly functionalized chiral molecules, which are important intermediates for the natural product synthesis, in a selective and efficient manner. Furthermore, the reaction can be performed on a large scale and recycling the catalytic system is possible for at least five times, leading to a clean, cheap, simple, and scalable procedure that meets most of the criteria required to be a green and sustainable process.

Our starting point is the covariant coordinate transformation equation of a relativistic positioning system in Minkowski space-time, which maps the receiver’s emission coordinates (proper times broadcast by the emitters) to its coordinates in some inertial reference frame. Bancroft’s analytical (closed-form) solution to the basic pseudorange navigation equations with four emitters is recovered and the subjacent elements are geometrically interpreted. The case of four static beacons is analized as a clarifying situation.

Cellular oxidation is responsive to external and internal stimulation and is generated via signal molecules in defense mechanisms through networks of cell proliferation, differentiation, intracellular detoxification, bacterial infection, and immune reactions. Oxidative stress is not necessarily harmful per se; it depends on the balance between oxidation and antioxidation cascades, which are induced according to stimuli and can maintain oxygen homeostasis. The reactive oxygen species (ROS) that are generated during influenza virus (IV) infection have critical effects on both the virus and host cells. In this review, we outline the link between viral infection and ROS production, using IV as an example. We introduce the current state of knowledge on the molecular relationship between cellular oxidation mediated by ROS production and various effects of IV infection. We also summarize the potential anti-IV agents that act by targeting oxidative stress.

TeamIndus’ Lunar Logistics vision includes multiple lunar missions over the coming years to meet requirements of science, commercial and efforts towards building readiness for crewed missions to Mars in the global exploration roadmap. TeamIndus is the only Indian team that participated in the Google Lunar X Prize. The challenge called for privately funded spaceflight teams to be the first to land a robotic spacecraft on the Moon, travel 500 meters, and transmit back high-definition video and images. The first mission is expected to have a net landed payload capacity of 50 kg. The prime objective is to demonstrate autonomous lunar landing, and operations for a Surface Exploration Rover - to collect data in the vicinity of the landing site. The rover is designed to execute the commands given by the operations manager autonomously. The rover software architecture relevant to the navigation and control is described in detail. The functional modes are defined to functionally distinguish the rover drive. Among the various operations performed by the rover are execution of simple drive steps through navigation and control algorithms. The kinematic model of the rover is studied in the hardware locomotion tests performed. The Kalman filter formulation to estimate the sensor bias and to get attitude estimate is discussed. The structural model and the frame definitions are described in a relevant section. A simple heading control algorithm is designed to control the heading direction of the rover according to the operations requirement. The path planning process and visual odometry processes are described. Finally the SIMULINK$^{\textregistered}$ model is tested on the prototype rover and the test experience results are discussed in the last section.

In this paper, feasibility of the initial alignment of the gyro-free inertial navigation system (GF-INS) is investigated. Initial roll and initial pitch are obtained as the conventional INS since centripetal acceleration is very small. Relation between initial heading and accelerometers’ outputs of the gyro-free inertial measurement unit (GF-IMU) is derived. It is determined from the relation whether initial heading can be obtained in 15 GF-IMUs which have been presented in research literatures. The relationship between the accelerometer errors of GF-IMU and the initial heading error is derived. When gyros are additionally attached in one axis or two axes of the body frame, it is investigated that initial heading can be obtained. The initial heading error is also calculated from the accelerometer errors and the gyroscope errors. The results show that the initial heading from only accelerometer outputs of the GF-IMU cannot be used in the GF-INS since the error is too large. It can also be seen from the results that the initial heading can be used in the GF-INS if two gyroscopes are additionally attached to the roll and pitch axes of the body frame.

Unlike aerial or terrestrial navigation, the Global Navigation satellite system (GNSS) is not available underwater. This is a big challenge for underwater navigation. The inertial navigation system (INS) aided by the single-beacon acoustic positioning system (APS) provides one solution, but the long-range case is limited by low SNR conditions. Inspired by passive synthetic aperture detection, we proposed a new tightly coupled navigation algorithm based on spatial synthesis and one-way-travel-time (OWTT) range measurement. We design two estimators: the DOA/Range estimator using the model-based method and the tightly coupled INS/APS navigation estimator. Based on the improved UKF, all information is combined. Simulation is carried out in MATLAB. Compared with range-only tightly coupled INS/APS navigation, synthetic long baseline (SLBL) algorithm and Doppler velocity logger (DVL) aided centralized extended Kalman filter (CEKF) based single beacon INS/OWTT navigation, the proposed method's performance is proven. The main contributions of this work are: 1. Propose a new architecture of underwater integrated navigation; 2. Apply the passive acoustic detecting method in the navigation to improve accuracy. 3. Apply the tightly coupled method to improve availability.

Automatic methods for constructing navigation routes do not fully meet all requirements. The aim of this study was to modify the methodology for generating indoor navigation models based on the Medial Axis Transformation (MAT) algorithm. The simplified method for generating corridor axes relies on the Node-Relation Structure (NRS) methodology. The axis of the modeled structure (corridor) is determined based the points of the middle lines intersecting the structure (polygon). The proposed solution involves a modified approach to the segmentation of corridor space. Traditional approaches rely on algorithms to construct Triangulated Irregular Networks (TINs) by Delaunay triangulation or algorithms for generating Thiessen polygons known as Voronoi diagrams (VDs). In this study, both algorithms were used in the segmentation process. The edges of TINs intersect structures. Selected midpoints on TIN edges, which are located in the central part of the structure, are used to generate VDs. Polygon VDs segment corridor structures. The identifiers or structure nodes are the midpoints on TIN edges rather than the calculated centroids. The generated routes are not zigzag lines, and they approximate natural paths. The main advantage of the proposed solution is its simplicity which can be attributed to the use of standard tools for processing spatial data in a geographic information system.

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

Classically the walk in biped robotics was obtained controlling balance during the whole step, i.e. guaranteeing that the pressure point under the soles always stayed in the polygon of the supporting feet. However, this assumed that the feet were able to transfer torque to the ground during the whole gait cycle. In spite of the fact that the amount of transferrable torque in the feet-ground contact is limited, it is possible only during some phases of the step, and the overall process is energetically inefficient. On the other side, starting from the passive motion of the rimless wheel falling on an inclined surface, and ending to the inverted pendulum with a compass, balance in the whole was proven in spite of dynamical instability inside each step. Along this line results of Foot Placement Estimation (FPE) in 2-D and 3-D showed how energy efficient walk was possible, emulating the human walk with a free fall on the swing foot and energy restitution at the foot collision with the ground for the next step. This model assumes pointy feet, so without torque transfer to the ground. In the realm of FPE, in previous papers the present author adopted the 3-D inverted pendulum in polar coordinates (Spherical Inverted Pendulum - SIP) to introduce omnidirectional walks with arbitrarily changing characteristics. No torque control was used during the step, i.e the pendulum was always in free fall at each step, the only control actions were at the beginning of the next step. These actions are: the change of angular velocities at the start of a new step, with respect to those given after the collision (emulating the torque action in the brief double stance period), to recover for the losses, and the preparation of the position in the frontal and sagittal planes of the swing foot for the next collision. The present paper improves this paradigm, proposing a general model to account for all characteristics of the biped and of the gait, with adding a minimum of dynamical complexity with respect to the SIP. This model allows, not only to walk omnidirectionally on a flat surface, but also to go up and down staircases.

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an Olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot’s search behavior among four strategies: crosswind maneuver, Obstacle-avoid Navigation, Vision-based Navigation, and Olfaction-based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-based navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms Vision-only and Olfaction-only methods, reducing average search time by 54% and 30%, respectively.

By constructing a static map, the library robot can navigate and access documents autonomously, which greatly improves efficiency; however, for libraries where shelves can be moved, map changes do not allow for direct navigation, and also sensors such as radar and camera are relatively expensive, so we propose a low-cost navigation algorithm based on real-time ranging data and map matrices, and designed a mobile archive access robot. In order to obtain real-time distance data, nine near/long range sensors were mounted on the chassis and a composite digital filtering algorithm was designed based on different moving area characteristics; then the access task matrix and map matrix were designed based on the archive access task and the location characteristics of the archive shelf placement, the robot can rely on the range data to update the map matrix during the moving process, complete its own positioning, and use the task matrix The robot can use the task matrix to complete autonomous navigation and access to multiple files. Experiments show that the filtered positioning accuracy can reach 1cm, while the robot can move to the target shelf autonomously, which is more practical and less costly.

The consumption of sweet beverages, including sugar-sweetened beverages (SSB), artificially sweetened beverages (ASB) and fruit juices (FJ) is associated with the risk of different cardiometabolic diseases and probably with some tumors as well. We carried out a systematic review and meta-analysis of observational studies aimed at evaluating the association between sweet beverage intake and different types of cancer risk. Suitable papers published up to June 2020 were searched through PubMed, Web of Science and SCOPUS databases, using relevant keywords. Overall, 64 studies were identified for the systematic review, of which 27 were selected for the meta-analysis. This was performed by analyzing the multivariable-adjusted OR, RR or HR of the highest compared with the lowest sweet beverage intake categories. Random effects showed significant positive association between SSBs intake and breast (RR: 1.14, 95% CI: 1.01 – 1.30) and prostate cancer risk (RR: 1.18, 95% CI: 1.10 – 1.27), also between FJs and prostate cancer risk (RR: 1.03, 95% CI: 1.01 – 1.05). Associations between SSBs and colorectal and pancreatic cancer risk, FJs and breast, colorectal and pancreatic cancer risk, ASBs and pancreatic cancer risk tended to be positive but did not reach the statistically significant threshold. This study supports the recommendation to limit the consumption of SSBs and FJs for cancer prevention and proposes to further investigate the potential harmful role of ASBs intake in cancer risk.

The brain's unique characteristics make it exceptionally susceptible to oxidative stress, which arises from an imbalance between reactive oxygen species (ROS) production, reactive nitrogen species (RNS) production, and antioxidant defense mechanisms. This review explores the factors contributing to the brain vascular tone vulnerability in the presence of oxidative damage, which can be of clinical interest in critically ill patients or presenting acute brain injuries. The brain's high metabolic rate and inefficient electron transport chain in mitochondria lead to significant ROS generation. Moreover, non-replicating neuronal cells and low repair capacity increase susceptibility to oxidative insult. ROS can influence cerebral vascular tone and permeability, with a potential impact on cerebral autoregulation. Different ROS species, including superoxide and hydrogen peroxide, exhibit vasodilatory or vasoconstrictive effects on cerebral blood vessels. Reactive nitrogen species (RNS), particularly NO and peroxynitrite, also exert vasoactive effects. This review further investigates the neuroprotective effects of antioxidants, including superoxide dismutase (SOD), vitamin C, vitamin E, and the glutathione redox system. Various studies suggest that these antioxidants could be used as adjunct therapies to protect the cerebral vascular tone during high oxidative stress conditions. Nevertheless, more extensive research is required to comprehensively grasp the relationship between oxidative stress and cerebrovascular tone, as well as to explore the potential benefits of antioxidants as adjunctive therapies in critical illnesses and acute brain injuries.

The mitochondrial network (MN) is a dynamic structure undergoing constant remodeling in the cell. It is assumed that the violation of MN may be associated with various pathologies, including Parkinson’s disease (PD). Using automatic image analysis and super-resolution microscopy, we have assessed the MN parameters in fibroblasts from patients with established hereditary PD mutations (associated with PINK1, LLRK2, α-synuclein, PINK1 and Parkin simultaneously proteins) under normal conditions and after hydrogen peroxide-induced stress. Fibroblasts with Pink1/Parkin mutation are the most different in morphology from fibroblasts obtained from conditionally healthy donors: MN is larger, contains longer mitochondria and accumulated individual mitochondria. In addition to MN, we evaluated other cellular parameters, such as: cytosolic and mitochondrial ROS production and mitochondrial membrane potential. It has been shown that mitochondria of fibroblasts with mutations in genes encoding PINK1, α-synuclein and Pink/Parkin tends to hyperpolarization and cytosolic ROS overproduction, while mitochondrial ROS production was higher only in fibroblasts with PINK1 and α-synuclein mutation.

When the antioxidants in our immune system cannot neutralize or convert Reactive oxygen species into safe molecules at the rate at which it is produced then this imbalance is termed as “oxidative stress”. It is related with a wide array of diseases that includes cancer, diabetes, cardiovascular diseases, hypertension etc. These ROS species however are utmost essential for the proper functioning of human body which are produced as a consequence of partial oxidation of cellular metabolism performing essential functions such as protein phosphorylation, activation of several transcriptional factors, apoptosis, immunity, and differentiation. The sources by which these are produced can be broadly classified are intrinsic and extrinsic sources. There are variety of natural antioxidant enzymes of human body that combat against this oxidative stress. The extrinsic sources of ROS include the use of natural plants, extracted flavonoids and vitamins. In this review we will briefly explain how the sources of ROS, its essential function in human body, its elevation and associated damage to organs and effect on various diseases, and a hope of finding a way of how this oxidative stress can be exploited for therapeutic potential.

Crotoxin (CTX), the predominant toxin in Crotalus durissus terrificus snake venom (CdtV), has anti-inflammatory and immunomodulatory effects. Despite its inhibitory action on neutrophil migration and phagocytosis, CTX does not directly affect the production of reactive oxygen species (ROS) by the neutrophils. In contrast, it enhances the generation of reactive oxygen and nitrogen intermediates by macrophages. Given the importance of macrophage-neutrophil interactions in innate antimicrobial defense, the aim of this study was to investigate the effect of CTX on neutrophil ROS production and killing activity, either through CTX-treated macrophage co-culture or conditioned medium of CTX-treated macrophages. The results showed an important modulatory action of CTX on the neutrophil function as well as neutrophil-macrophage interactions, as demonstrated by the increased production of hydrogen peroxide, hypochlorous acid, nitric oxide and TNF-α, along with the increased fungicidal activity of neutrophils.

The in vitro production and cryopreservation of mammalian embryos generate reactive oxygen species (ROS) due to conditions of the system that can overcome their antioxidant protection. Resveratrol is an antioxidant used in in vitro systems improving blastocyst rates, but its effect on antioxidant enzymes such as glutathione (GSH) in embryos produced by in vitro fertilization (IVF) after vitrification has not been reported. The objective of this study was to evaluate the effect of resveratrol in the in vitro maturation medium (IVM) of sheep oocytes (Ovis aries) on the levels of ROS and GSH in embryos produced by IVF subjected to vitrification. Resveratrol was added at 0µM, 0.25µM, 0.5µM and 1µM during oocyte in vitro maturation (IVM). Matured oocytes were fertilized with thawed ram sperm. Embryos were cultured in sequential media until blastocysts, then were vitrified for 24 h and after heating they were stained with DCFH-DA (2',7'-dichlorodihydrofluorescein diacetate) to determine the presence of ROS and with Cell Tracker Blue® for the presence of GSH. The quantitative values of ROS and GSH were obtained through the Image J image processor. The results showed that resveratrol increases GSH and decreases ROS production (p<0.05). It is concluded that its use in sheep oocytes during IVM has a beneficial effect on embryos produced by IVF subjected to vitrification, protecting them from oxidative damage by promoting the synthesis of antioxidants.

The growing urgency for sustainable energy solutions necessitates a deeper understanding of the environmental impacts of renewable technologies. This article aims to synthesize and analyze Life Cycle Assessments (LCA) in this domain, providing a comprehensive perspective. We systematically categorize 2,923 articles into four communities: (1) Photovoltaic systems, (2) Wind energy systems, (3) Materials for auxiliary industry of photovoltaic and wind systems, and (4) Solar thermal systems. A comparative analysis is conducted to identify methodological consistencies and disparities across these communities. The findings reveal diverse methodological approaches and a range of environmental impacts, highlighting the complexities in assessing renewable energy systems. The article underscores the significance of material selection in photovoltaic and wind systems, providing a critical overview of the current state of LCA research in renewable energy and stressing the need for standardized methodologies. It also identifies gaps in recent research, offering insights for future studies focused on integrating environmental, economic, and social considerations in renewable energy assessments.As a case study, an LCA was used to evaluate two energy supply methods for a sensor network: one connected to the public grid and another powered by a photovoltaic panel. The off-grid system, while more environmentally friendly by reducing reliance on non-renewable energy sources, posed challenges due to the high environmental impact of battery production and disposal. Integrating environmental assessments provides a robust framework for making informed decisions on sustainable technologies. The findings are critical for projects that balance technological needs with sustainability goals.

Polyurethane (PU) is a polymer widely used by humans whose recycling is highly complex due his chemical structure, being limited to incineration or accumulation in landfills. Biodegradation by enzymes and microorganisms has been studied for decades as an effective method of biological decomposition. In this study, Tenebrio molitor larvae (T. molitor) were fed with polyurethane foams, which gut enzymes and microorganisms were capable of degrading the polymer by 35% in 17 days of treatment, producing a weight loss of 14% in the mealworm. Changes in T. molitor gut bacterial community and diversity were observed, which may be due to colonization of species associated with PU degradation. Physical and structural biodegradation in PU by T. molitor compared to virgin PU, was demonstrated by Fourier Transform InfraRed spectroscopy (FTIR), Thermal Gravimetric Analysis (TGA) and Scanning Electron Microphotography (SEM).

Inflammation is a cause of number of disorders. Many anti-inflammatory drugs are available to cure and prevent inflammation and its related disorders. Some of the drugs are from plant and animal origin. Among animals snake venom is also utilized as treatment option of certain disorders. In the current study the venom of N. oxiana from Northern areas of Pakistan is assayed to determine its anti-inflammatory activity. The Naja oxiana is also called central Asian cobra is endemic to Central Asia. Naja oxiana belong to family Elapidae and it is highly venomous snake. The venom has many enzymatic proteins as well as nonenzymatic proteins that is neurotoxins. The venom is lethal having very high mortality rate and the death may occur due to respiratory failure in 45 minutes to 24 hrs depending upon the nature and amount of venom. As the venom is highly toxic so initially after venom milking its protein estimation was done and toxicity profile and LD50 was determined to find out its therapeutic dose at which anti-inflammatory activity was observed. The toxicity and anti-inflammatory activity was determined on mice model. Inflammation was induced by carrageenan induced peritonitis method. The inflammatory markers ROS, TNF-α and IL-β were determined by ELIZA in peritoneal fluid. The LD50 of crude venom, fraction 1 and fraction 2 was found as 34 µg/kg, 7.4 µg/kg and 416 µg/kg respectively. Anti-inflammatory activity crude venom, fraction 1 and fraction 2 was found at dose 19 µg/kg, 1.8 µg/kg and 267 µg/kg respectively. The levels of inflammatory markers reduced after therapeutic dose administration of venom and its fractions that indicates that it can be utilized as anti-inflammatory agent and so can be effective in various disorders.

: In this paper, we examine potential methods for autonomously tracking and landing multi-rotor unmanned aerial vehicles (UAVs), a complex yet essential problem. Autonomous tracking and landing control technology utilizes visual navigation, relying solely on vision and landmarks to track targets and achieve autonomous landing. This technology improves the UAV's environment perception and autonomous flight capabilities in GPS-free scenarios. In particular, we are researching tracking and landing as a cohesive unit, devising a switching plan for various UAV tracking and landing modes, and creating a flight controller that has an inner and outer loop structure based on relative position estimation. The inner and outer nested markers aid in the independent monitoring and touchdown of UAV. Optimal parameters are determined via optimized experiments on the measurements of the inner and outer markers. An indoor experimental platform for tracking and landing UAV was established. Tracking performance was verified by tracking three trajectories of unmanned ground vehicle (UGV) at varying speeds, and landing accuracy was confirmed through static and dynamic landing experiments. The experimental results show that the proposed scheme has good dynamic tracking and landing performance.

Metal toxicity in soils, along with water runoff, are increasing environmental problems that affect agriculture directly and, in turn, human health. In light of finding a suitable and urgent solution, research on plant treatments with specific compounds that can help mitigate these effects has increased, and thus the exogenous application of melatonin (MET) and its role in alleviating the negative effects of metal toxicity in plants, have become more important in the last few years. MET is an important plant-related response molecule involved in growth, development, and reproduction, and in the induction of different stress-related key factors in plants. It has been shown that MET plays a protective role against the toxic effects induced by different metals (Pb, Cd, Cu, Zn, B, Al, V, Ni, La, As, and Cr) by regulating both the enzymatic and non-enzymatic antioxidant plant defense systems. In addition, MET interacts with many other signaling molecules, such as reactive oxygen species (ROS) and nitric oxide (NO), and participates in a wide variety of physiological reactions. Furthermore, MET treatment enhances osmoregulation and photosynthetic efficiency and increases the concentration of other important antioxidants such as phenolic compounds, flavonoids, polyamines (PAs), and carotenoid compounds. Some recent studies have shown that MET appeared to be involved in the regulation of metal transport in plants, and lastly, various studies have confirmed that MET significantly upregulated stress tolerance-related genes. Despite all the knowledge acquired over the years, there is still more to know about how MET is involved in the metal toxicity tolerance of plants.

Chemotherapy treatment based on Cisplatin (CDDP) is established as the drug of choice for head and neck squamous cell carcinoma (HNSCC). Malignant tumors respond to microenvironment alteration through a dynamic balance of mitochondrial fission and fusion. HNSCC is known to have hypoxic conditions, yet the effects and underlying mechanisms of hypoxia on chemosensitivity and mitochondrial dynamics remain unclear. We found that hypoxia promoted mitochondrial fission and CDDP sensitivity in HNSCC cells. Importantly, Mff was shown to be correlated with chemosensitivity in clinical samples of HNSCC that underwent a hypoxic condition. Hypoxia-inducible factor 1 α-subunit (HIF-1α) dramatically increased Mff transcriptional expression and directly bound to Mff. Hypoxia enhanced the release of reactive oxygen species (ROS) and upregulated the expression of Mff via HIF-1α in HNSCC cells. ROS depletion in HNSCC cells attenuated HIF-1α, Mff expression, and mitochondrial fission. Moreover, a knockdown of Mff suppressed hypoxia-induced mitochondrial fission and decreased CDDP chemosensitivity in vivo and in vitro. Our findings revealed that the hypoxia-induced release of ROS promoted mitochondrial fission and CDDP chemosensitivity via the regulation of HIF-1α/Mff in HNSCC cells, indicating that Mff may serve as a new biomarker to predict neoadjuvant chemosensitivity in HNSCC patients

Autonomous navigation of a mobile robot in dynamic environments presents a significant challenge in the field of robotics. The primary objective for mobile robot navigation is to ensure both smoothness and safety of movement. A path planning is applied to generate a trajectory that allows the robot to move smoothly while avoiding collisions with both stationary and moving obstacles. This study aims to introduce an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based control strategy for a mobile robot navigating in dynamic environments, with a significant focus on ensuring collision-free path planning. The developed control strategy incorporates four ANFIS controllers, each regulating the robot's responsive behaviors. The experimental scene includes a mobile robot moving in an environment with static and dynamic obstacles without colliding with the obstacles. The experimental tests confirm the model's capability to facilitate collision-free motion, employing a path planning algorithm for determining the shortest route to the target destination. Simulations are conducted to show the effectiveness of the proposed algorithm, highlighting the mobile robot's efficiency in navigating without collisions while avoiding both stationary and moving obstacles using the integration of ultrasonic sensors.

Surgical navigation has evolved as a vital tool in maxillofacial surgery, offering precise and patient-specific data. This study explores the clinical applications and accuracy of intraoperative tool tracking in maxillofacial surgery. The research includes 37 patients with various pathologies who underwent surgery assisted by a surgical navigation system using tracked instruments. The study showcases two representative cases: one involving coronoid hyperplasia with mouth opening deficit and another addressing nose-orbital-ethmoidal-frontal ossifying fibroma resection. The results indicate that surgical navigation with tracked instruments provides high precision (<1.5 mm error), reduced surgical time, and less invasive approaches. The study highlights the potential for reproducible outcomes and increased safety, especially in complex cases. Despite some limitations, the synergy between surgical navigation and tracked instruments offers a promising approach in maxillofacial surgery, expanding its applications beyond current practices.

For a mobile robot, navigation in a densely crowded space can be a challenging and sometimes impossible task, especially with traditional techniques. In this paper, we present a framework to train neural controllers for differential drive mobile robots which must safely navigate a crowded environment while trying to reach a target location. To learn the robot’s policy, we train a convolutional neural network using two reinforcement learning algorithms, Deep Q-Networks (DQN) and Asynchronous Advantage Actor Critic (A3C), and develop a training pipeline that allows to scale the process to several compute nodes. We show that the asynchronous training procedure in A3C can be leveraged to quickly train neural controllers and test them on a real robot in a crowded environment.

The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems’ position over the existing spherical constraint.

Studies have shown that aerosols generated from flavored e-cigarettes contain Reactive Oxygen Species (ROS), promoting oxidative stress-induced damage within pulmonary cells. Our lab investigated the ROS content of e-cigarette vapor generated from disposable vape bars, a product exempt from the Federal Drug Enforcement Agency’s (FDA) 2020 flavor ban. Specifically, we analyzed vape bars belonging to multiple flavor categories (Tobacco, Minty Fruit, Fruity, Minty/Menthol, Desserts, and Drinks), manufactured by various vendors and of various nicotine concentrations (0-6.8%). Aerosols from these flavored vape bars were generated by a single puff aerosol generator and individually bubbled through a fluorogenic solution to detect and semi-quantify ROS in H2O2 equivalents generated by the vape bars. We compared and contrasted the ROS levels generated by each flavor as an indirect determinant of oxidative stress potential by these disposable vape bars. Our results showed that ROS concentration (μM) of aerosols produced from the vape bars varied significantly between different flavors and a function of nicotine concentration. Likewise, our results suggest that flavoring chemicals and nicotine concentration play a role in alerting ROS production in e-cigarette aerosols. Our study provides insight into the differential health effects of flavored disposable vape bars and the need for their regulation.

This paper proposes an improvement to a recent Peak-to-Average-Power-Ratio (PAPR) reduction technique for Orthogonal Frequency Division Multiplexing (OFDM), the GreenOFDM. This technique, which is inspired by SeLected Mapping (SLM), generates several waveform candidates using a given number of Inverse Fast Fourier Transforms (IFFT), and selects the one with the lowest PAPR for the transmission of the OFDM symbol. In GreenOFDM, we show that for (U) IFFTs, it provides better PAPR reduction capabilities than SLM-OFDM as it increases the number of waveform candidates from U (available for SLM-OFDM) to U^2/4. In this work, we propose a simple and clever extension of the GreenOFDM that further increases the number of waveform candidates by a factor 4 (from U^2/4 to U^2), or equivalently reduces by a factor of 2 the number of IFFTs for a same PAPR performance. Compared to SLM-OFDM, the improved GreenOFDM technique reduces the complexity by requiring only the square-root of the number of IFFTs for a same PAPR reduction performance.

Cancer cells show an increased glutamine consumption. The glutaminase (GLS) enzyme controls a limiting step in the glutamine catabolism. Breast tumors, especially the triple negative subtype, have a high expression of GLS. Our recent study demonstrated that GLS activity and ammonia production are inhibited by Sirtuin 5 (SIRT5). We have developed MC3138, a selective SIRT5 activator. Treatment with MC3138 mimicked the deacetylation effect mediated by SIRT5 overexpression. Moreover, GLS activity is regulated by inorganic phosphate (Pi). Considering the interconnected role of GLS, SIRT5 and Pi for cancer growth, our hypothesis is that activation of SIRT5 and reduction of Pi could represent a valid anti-tumoral strategy. Treating cells with MC3138 and lanthanum acetate, a Pi chelator, decreased cell viability and clonogenicity. We also observed a modulation of LC3 and ULK1 with MC3138 and lanthanum acetate. Interestingly, inhibition of mitophagy marker BNIP3 was observed only in the presence of MC3138. Such autophagy and mitophagy modulation was accompanied by an increase of cytosolic and mitochondrial reactive oxygen species (ROS). In conclusion, our results show how SIRT5 activation and/or Pi binding can represent a valid strategy to inhibit cell proliferation by reducing glutamine metabolism and mitophagy leading to a deleterious accumulation of ROS.

Some of the barriers preventing Virtual Reality (VR) from being widely adopted are the cost and unfamiliarity of VR systems. Here we propose that in many cases the specialized controllers shipped with most VR head-mounted displays can be replaced by a regular smartphone, cutting the cost of the system, and allowing users to interact in VR using a device they are already familiar with. To achieve this, we developed SmartVR Pointer, an approach that uses smartphones as a replacement for the specialized controllers for two essential operations in VR: selection and navigation by teleporting. In SmartVR Pointer a camera mounted on the head-mounted display (HMD) is tilted downwards so that it points to where the user will naturally be holding their phone in front of them. SmartVR Pointer supports three selection modalities: tracker-based,gaze-based, and combined/hybrid. In the tracker-based SmartVR pointer selection we use image-based tracking to track a QR code displayed on the phone screen and them map the phone’s position to a pointer shown within the field of view of the camera in the Virtual Environment. In the gaze-based selection modality the user places the pointer using their gaze and taps on the phone for selection. The combined technique is a hybrid between head-gaze-based interaction in VR and smartphone-based Augmented Reality. It allows the user to control a VR pointer that behaves like a mouse pointer by moving their smartphone to select objects within the virtual environment, and to interact with the selected objects using the smartphone’s touch screen. The touchscreen is used for selection and dragging. SmartVR Pointer is simple and requires no calibration and no complex hardware assembly or disassembly. We demonstrate successful interactive applications of SmartVR Pointer in a VR environment with a demo where the user navigates in the virtual environment using teleportation points on the floor and then solves a Tetris-style key-and-lock challenge.

Lane detection is a foundational technology for autonomous driving systems. It involves identifying the boundaries of lanes on the road and ensuring the vehicle stays within these boundaries. Accurate lane detection is crucial for safety, navigation and traffic management. This paper presents an artificial intelligent based autonomous road lane detection and navigation system for vehicles. The system can detect and analyze road lanes accurately and efficiently in real-time, with frame rates of up to 17 FPS. By utilizing image processing techniques, the system can identify the location and boundaries of road lanes and obstacles on the road and provide accurate and reliable navigation guidance to the driver. The system is integrated with sensors and actuators to provide comprehensive autonomous navigation. The efficiency of the proposed system is demonstrated using accuracy of lane detection on straight and curve lanes covering frames per second and motor of the speed as parameters for assessment. Results show that the proposed system detects lane as entire lane detection, partial lane detection and no detection status on different settings.

Navigation systems are considered as a fast and efficient source of road information to drivers. However, they can distract drivers with more potential accidents on the road. This study examined the effect of navigation systems on driver distraction and visual search while driving in different driving conditions. An eye-tracking system was used to collect visual search data from twenty young drivers while using a driving simulator. Several factors were investigated, including the driving environment (urban and rural), the illumination level (day and night), and the display of the navigation system (large and small) as well as their interactions. Several measures related to eye movements were used in this experiment, including percentage of total Global Positioning System (GPS) fixation duration, average duration of GPS fixation, GPS fixation frequency, the percentage of total dwell duration for the road ahead, the frequency of dwelling on the mirrors and driver’s right and left side windows, and the percentage of dwellings on the mirrors and driver’s right and left side windows. Statistical analysis of the collected data was performed with repeated measures analysis of variance (ANOVA). The experiment revealed that the small GPS display creates more distraction in terms of average gaze duration and total gaze duration. Moreover, daytime driving conditions increase distraction. Regarding the driver’s visual search, the study showed that the visual search area is wider and more spread out during the day, which leads to better driving performance. This study will compare small and large navigation displays to determine which one is more effective in reducing driver distractions, and contribute to understanding driver distraction and visual search while using the navigation system display.

The magnetic navigation system (MNS) with gradient and uniform saddle coils is one of the effective systems to manipulate various medical magnetic robot due to its compact structure and uniformity of the magnetic field and field gradient. However, it has limited operating time and large inductance effect due to the high current density and numerous turns of coils, respectively. In this paper, we propose an optimization methodology of the MNS considering the current density and inductance of the coils. We introduce objective functions, constraints, and design variables of the MNS. Then, the MNS was designed by an optimization algorithm. The constructed MNS was compared with the conventional MNS, and it could generate 22 % stronger magnetic field or field gradient while the maximum three-dimensional rotating magnetic field was improved by 42 %. We also demonstrated an unclogging performance of a helical robot was improved by 54 % with the constructed MNS.

Maze navigation using one or more robots has become a recurring challenge in scientific literature and real life practice, with fleets having to find faster and better ways to navigate environments such as a travel hub (e.g. airports) or to evacuate a disaster zone. Many methods have been used to solve this issue, including the implementation of a variety of sensors and other signal receiving systems. Most interestingly, camera-based techniques have increasingly become more popular in this kind of applications, given their robustness and scalability. In this paper, we have implemented an end-to-end strategy to address this scenario, allowing a robot to solve a maze in an autonomous way, by using computer vision and path planning. In addition, this robot shares the generated knowledge to another by means of communication protocols, having to adapt its mechanical characteristics to be able to solve the same challenge. The paper presents experimental validation of the four components of this solution, namely camera calibration, maze mapping, path planning and robot communication. Finally, we present the integration and functionality of these methods applied in a pair of NAO robots.

In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.

Inertial navigation system (INS) is a basic component for obtaining a continuous navigation solution in various applications. The INS navigation solution suffers from a growing error over time. In particular, its navigation solution depends mainly on the quality and grade of the inertial measuring unit (IMU) that provides the INS with both accelerations and angular rates. However, low-cost small micro-electro-mechanical systems (MEMS) suffer from tremendous error sources such as bias, scale factor, scale factor instability, and highly non-linear noise. Therefore, MEMS-IMU measurements lead to drifted solutions when used as a control input to the INS. Accordingly, several approaches have been introduced to model and mitigate the errors associated with IMU. In this paper, a machine learning-based adaptive neuro-fuzzy inference system (ML-ANFIS) is proposed to leverage the performance of low-grade IMUs in two phases. The first phase is training 50% of the low-grade IMU measurements with a high-end IMU to generate a suitable error model. The second phase involved testing the developed model on the remaining low-grade IMU measurements. A real road trajectory was conducted to evaluate the performance of the proposed algorithm. The results show the effectiveness of utilizing the proposed ML-ANFIS algorithm in removing errors and improving the INS solution compared to the traditional one. An improvement of 70% in the 2D-positioning and 92% in the 2D-velocity INS solution is attained when the proposed algorithm was applied compared to the traditional INS solution.

Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system's performance when the number of agents increases. To this end, two different mixed reality frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots being the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV those used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real-time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in mixed reality experiences regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

Activity of the Nox1 centered NADPH oxidase complex depends on the activator NoxA1 and the organizer NoxO1. NoxO1 itself is not involved in electron transfer for superoxide formation. Instead, by creating proximity of all components in the right place NoxO1 enables a constitutive formation of reactive oxygen species by that complex. All subunits should form the complex in a 1:1:1 ratio. When analyzing different cell lines in this study, we found an unequal expression of the component on mRNA level with an excess of NoxO1. Even with plasmid-based overexpression of individual components of Nox1 centered NADPH oxidase complex results in different expression of their mRNA, with NoxO1 mRNA being best expressed. Despite an unchanged high level of NoxO1 mRNA over a wide range of transfected plasmid, protein expression is increased with accelerating plasmid concentrations. We thought to analyze the ability of NoxO1 to induce ROS formation, when present in different ratio to Nox1 and NoxA1. To this end, we used Hek293 cells with constitutive expression of Nox1 and NoxA1 transfected with increasing concentrations of NoxO1. Our results suggest that ROS formation by the Nox1 centered NADPH oxidase strongly depends on the level of NoxO1 and a surplus of NoxO1 further increases the activity of the complex.

The oil and gas industry faces increasing pressure to remove people from dangerous offshore environments. Robots present a cost-effective and safe method for inspection, repair and maintenance of topside and marine offshore infrastructure. In this work, we introduce a new immobile multi-sensing robot, the Limpet, which is designed to be low-cost and highly manufacturable, and thus can be deployed in huge collectives for monitoring offshore platforms. The Limpet can be considered an instrument, where in abstract terms, an instrument is a device that transforms a physical variable of interest (measurand) into a form that is suitable for recording (measurement). The Limpet is designed to be part of the ORCA (Offshore Robotics for Certification of Assets) Hub System, which consists of the offshore assets and all the robots (UAVs, drones, mobile legged robots etc.) interacting with them. The Limpet comprises the sensing aspect of the ORCA Hub System. We integrated the Limpet with Robot Operating System (ROS), which allows it to interact with other robots in the ORCA Hub System. In this work, we demonstrate how the Limpet can be used to achieve real-time condition monitoring for offshore structures, by combining remote sensing with signal processing techniques. We show an example of this approach for monitoring offshore wind turbines. We demonstrate the use of four different communication systems (WiFi, serial, LoRa and optical communication) for the condition monitoring process. By processing the sensor data on-board, we reduce the information density of our transmissions, which allows us to substitute short-range high-bandwidth communication systems with low-bandwidth long-range communication systems. We train our classifier offline and transfer its parameters to the Limpet for online classification, where it makes an autonomous decision based on the condition of the monitored structure.

Cobalamin is an essential nutrient required for the normal functioning of cells. Its deficiency can lead to various pathological states. Hydroxocobalamin (HOCbl) and cyanocobalamin (CNCbl) are the forms of vitamin B12 that are most commonly used for supplementation. There is substantial evidence indicating that cobalamins can both suppress and promote oxidative stress; however, the mechanisms underlying these effects are poorly understood. Here, it was shown that the oxidation of thiols catalyzed by HOCbl and CNCbl is accompanied by ROS production and induces, under certain conditions, oxidative stress and cell death. The form of vitamin B12 and the structure of thiol play a decisive role in these processes. It was found that the mechanisms and kinetics of thiol oxidation catalyzed by HOCbl and CNCbl differ substantially. It was discussed how these differences may explain different levels of ROS production and cytotoxicity induced by combinations of thiols with HOCbl and CNCbl. On the whole, the data obtained provide a new insight into the redox processes in which cobalamins are involved and might be helpful in developing new approaches to the treatment of some cobalamin-responsive disorders in which oxidative stress is an important component. In addition, these data may be useful for a better understanding of mechanisms underlying induction of different types of death of cancer cells and in a search for new targets for anticancer therapy.

In this paper we present the exploration of indoor positioning technologies for UAVs, and navigation techniques for path planning and obstacle avoidance. The objective is to perform warehouse inventory tasks using a drone to search for barcodes or markers to identify the objects. For the indoor positioning techniques, we employ Visual-Inertial Odometry (VIO), Ultra-Wideband (UWB), AprilTag fiducial markers, and Simultaneous Localization and Mapping (SLAM). These algorithms encompass global positioning, local positioning, and pre-mapping positioning, comparing the merits and drawbacks of various techniques and trajectories. In UAV navigation, we combine SLAM-based RTAB-Map indoor mapping and navigation path planning of the ROS for indoor environments. This system enables precise drone positioning indoors and utilizes global and local path planners to generate flight paths that avoid dynamic, static, unknown, and known obstacles, demonstrating high practicality and feasibility. To achieve the warehouse inventory inspection, a reinforcement learning approach is proposed to recognize the markers by adjusting the UAV's viewpoint. We address several main problems in inventory management, including efficiently planning paths while ensuring a certain level of detection rate. Two reinforcement learning techniques, AC (Actor-Critic) and PPO (Proximal Policy Optimization), are implemented based on AprilTag identification. Testing is performed in both simulated and real-world environments, and the effectiveness of the proposed method is validated.Code is available at https://github.com/kellen080/Navigation and https://github.com/kellen080/Indoor\_Positioning.

Unmanned Underwater Vehicles (UUVs) are pivotal in ocean exploration, research, and various industrial activities such as marine mining and offshore engineering. However, traditional methods of navigating these vehicles face significant challenges, mainly due to the inefficacy of electromagnetic waves in water, leading to signal loss. To address these limitations, researchers are increasingly turned learning, an artificial intelligence technique capable of learning from data-enhancing underwater navigation, mainly through visual Simultaneous Localization and Mapping (SLAM). This paper explores integrating deep learning methodologies and sensor technologies to revolutionize underwater navigation for UUVs. Proprioceptive sensors, along with exteroceptive sensors, are crucial in accurately measuring and comprehending the underwater environment. Additionally, the paper provides detailed insights into the processes of underwater SLAM, camera-based underwater positioning systems, sonar systems for underwater navigation, and the utilization of Lidar in underwater navigation. Furthermore, it delves into applying deep learning techniques in underwater SLAM, offering a comprehensive understanding of the innovative processes driving advancements in underwater vehicle navigation. By leveraging these advancements, this research aims to improve underwater navigation systems' precision, reliability, and adaptability, thereby unlocking new frontiers in ocean exploration and industrial applications for UUVs.

Unmanned Aerial Systems (UAS) have rapidly gained attraction in recent years as a promising solution to revolutionize numerous applications and meet the growing demand for efficient and timely delivery services due to their highly automated operation framework. Beyond Visual Line of Sight (BVLOS) operations, in particular, offer new means of delivering added-value services through a wide range of applications. This ’plateau of productivity’ holds enormous promise but it is challenging to equip the drone with affordable technologies which support the BVLOS use-case. To close this gap, this work showcases the convergence of the automotive and aviation industries to advance BVLOS aviation for UAS in a practical setting by studying a combination of Commercial Off-The-Shelf (COTS) technologies and systems. A novel risk based approach of investigating the key technological components, architectures, algorithms and protocols is proposed, that facilitate highly reliable and autonomous BVLOS operations, aiming to enhance the alignment between market and operational needs and to better identify integration requirements between the different capabilities to be developed.

The CoDRIVE solution builds on R&amp;D in the development of connected and autonomous vehicles (CAVs). The mainstay of the system is a low-cost GNSS receiver integrated with a MEMS grade IMU powered with CoDRIVE algorithms and high precision data processing software. The solution integrates RFID (radio-frequency identification) localisation information derived from tags installed in the roads around the University of Nottingham. This aids the positioning solution by correcting the long-term drift of inertial navigation technology in the absence of GNSS. The solution is informed of obscuration of GNSS through city models of skyview and elevation masks derived from 360-degree photography. The results show that predictive intelligence of the denial of GNSS and RFID aiding realises significant benefits compared to the inertial only solution. According to the validation, inertial only solutions drift over time, with an overall RMS accuracy over a 300 metres section of GNSS outage of 10 to 20 metres. After deploying the RFID tags on the road, experiments show that the RFID aided algorithm is able to constrain the maximum error to within 3.76 metres, and with 93.9% of points constrained to 2 metres accuracy overall.

A single dose of psilocybin, a psychedelic and serotonin 2A receptor (5-HT2AR) agonist, may be associated with antidepressant effects. The mechanism behind its antidepressive action is unknown but could be linked to increased synaptogenesis and down-regulation of cerebral 5-HT2AR. Here, we investigate if a single psychedelic dose of psilocybin changes synaptic vesicle protein 2A (SV2A) and 5-HT2AR density in the pig brain. Twenty-four awake pigs received either 0.08 mg/kg psilocybin or saline intravenously. Twelve pigs (n=6/intervention) were euthanized one day post-injection, while the remaining twelve pigs were euthanized seven days post-injection (n=6/intervention). We performed autoradiography on hippocampus and prefrontal cortex (PFC) sections with [3H]UCB-J (SV2A), [3H]MDL100907 (5-HT2AR antagonist) and [3H]Cimbi-36 (5-HT2AR agonist). One day post psilocybin injection, we observed 4.4% higher hippocampal SV2A density and lowered hippocampal and PFC 5-HT2AR density (-15.21% to -50.19%). These differences were statistically significant in the hippocampus for all radioligands and in PFC for [3H]Cimbi-36 only. Seven days post-intervention, there was still significantly higher SV2A density in hippocampus (+9.24%) and PFC (+6.1%) whereas there were no longer any differences in 5-HT2AR density. Our findings suggest that psilocybin’s antidepressive actions are linked to increased persistent synaptogenesis and possibly also to an acute decrease in 5-HT2AR density.

Periacetabular osteotomy (PAO) is an effective approach for surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip and limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 which is a state-of-the-art (SOTA) optical see-through head-mounted display (OST-HMD). For AR guidance, we propose an optical marker-based virtual-physical registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS, such that virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns the bone saw with osteotomy planes planned in preoperative images, and then provides surgeons with not only robot assistance but also AR guidance. Comprehensive experiments were conducted to evaluate both virtual-physical registration accuracy and osteotomy accuracy of the developed navigation system. The proposed virtual-physical registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The developed system achieved an average distance deviation of 0.82 ± 0.17 mm and an average angular deviation of 3.77 ± 0.85 . Experimental results demonstrated high virtual-physical registration accuracy. The sub-millimeter distance deviation demonstrated the osteotomy accuracy of the proposed system.

This work presents the development and implementation of a distributed navigation system based on computer vision. The autonomous system consists of a wheeled mobile robot with an integrated colour camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that processes them and calculates the corresponding speeds of the robot using a cascade of trained classifiers. These speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. The classifier cascade should be trained before experimentation with two sets of positive and negative images. The number of images in these sets should be considered to limit the training stage time and avoid overtraining the system.

The purpose of the work is an underwater positioning safety study that used the GNSS-like underwater navigation systems. In the process of research, we used the methods of software modeling of underwater spoofing processes. The spoofing problem consists of three stages: design of spoofers, design of spoofing detection systems, and design of anti-spoofing systems. This article discusses some methods of spoofing detection. We briefly describe the known methods of underwater positioning systems. Unlike GNSS, currently only LNSS (Local Navigation Satellite System) can be considered in this case. Spoofing detection systems with one hydrophone are of great practical importance, as they allow for use of standard hydroacoustic equipment. However, detection of spoofing is not possible in static mode, which is with underwater vehicle at rest. In case of two hydrophones the detection of spoofing in static mode is possible. We discuss the navigation based on the use of an acoustically passive receiver. The receiver “listens” to the buoys and solves the problem of finding its own position using the coordinates of the buoys (such systems are called GNSS-like Underwater Positioning Systems or GNSS-like UPS). Depending on the scale of system service area, GNSS-like UPS-es are divided into global, regional, zonal and local systems. In this article, we take into account only the local class of GNSS-like UPS. The acoustic signal generator transmits a simulation of several buoy signals. If the level of the simulated signal exceeds the signal strength of actual buoys, the UPS receiver will “lock onto” the fake signal and then calculate a false position basing on it. The development of further research should be focused on the creation of hardware and software systems for conducting physical experiments at depths up to 400 m.

This paper presents a system based on pedestrian dead reckoning for localization of networked mobile users, which relies only on sensors embedded in the devices and device- to-device connectivity. The user trajectory is reconstructed by measuring step by step the user displacements. Though step length can be estimated rather accurately, heading evaluation is extremely problematic in indoor environments. Magnetometer is typically used, however measurements are strongly perturbed. To improve the location accuracy, this paper proposes a cooperative system to estimate the direction of motion based on a machine learning approach for perturbation detection and filtering, combined with a consensus algorithm for performance augmentation by cooperative data fusion at multiple device. A first algorithm filters out perturbed magnetometer measurements based on a-priori information on the Earth's magnetic field. A second algorithm aggregates groups of users walking in the same direction, while a third one combines the measurements of the aggregated users in a distributed way to extract a more accurate heading estimate. Extensive indoor experiments show that the heading error is highly reduced by the proposed approach thus leading to noticeable enhancements in localization performance.

This paper develops a methodology to control the navigation of an autonomous ship robot from an initial state to a final. To solve the problem the following approach is used: The ship robot system is modelled as a control system of six ordinary differential equations involving six state variables and three control variables. After having computed the system Hamiltonian, the feasible controls for optimality are derived from the normal equations of optimality as functions of the state and costate variables. Such controls are substituted into the state and the costate equations and give a combined control-free state-costate system of ordinary differential equations which is solved numerically by using a developed Matlab computer program. Associated computational simulations are designed and provided to show the reliability of the approach.

Human colon carcinomas, including HCT116 cells, often exhibit high basal autophagic flux under nutrient deprivation or hypoxic conditions. Mitochondrial ROS (mROS) is known as a “molecular switch”’ for regulating the autophagic pathway, which is critical for directing cancer cell survival or death. In early tumorigenesis, autophagy plays important roles in maintaining cellular homeostasis and contributes to tumor growth. However, the relationships between mROS and the autophagic capacities of HCT116 cells are poorly understood. Ubiquinol cytochrome c reductase binding protein (UQCRB) has been reported as a biomarker of colorectal cancer, but its role in tumor growth has not been clarified. Here, we showed that UQCRB was overexpressed in HCT116 cells compared to CCD18co cells, a normal colon fibroblast cell line. Pharmacological inhibition of UQCRB reduced mROS levels, autophagic flux, and the growth of HCT116 tumors in a xenograft mouse model. We further investigated mutant UQCRB-overexpressing cell lines to identify functional links in UQCRB-mROS-autophagy. Notably, an increasing level of mROS caused by UQCRB overexpression released Ca2+ by activation of lysosomal TRPML1 channels. This activation induced transcription factor EB nuclear translocation and lysosome biogenesis, leading to autophagy flux. Collectively, our study showed that increasing levels of mROS caused by overexpression of UQCRB in human colon carcinoma HCT116 cells could be linked to autophagy for cell survival.

Potato is among one of the most important food crops, yet maintaining plant productivity in this drought-sensitive crop has become a challenge. Competition for scarce water resources and the continued effects of global warming exacerbate current constraints on crop production. While plants’ response to drought in above-ground tissues has been well documented, the regulatory cascades in developing tubers have been largely unexplored. Using the commercial Canadian cultivar ‘Vigor’, plants were subjected to a drought treatment under high-tunnels causing a 4 ℃ increase in canopy temperature when compared to the well-watered control. Tubers were sampled for RNAseq and metabolite analysis. Approximately 2600 genes and 3898 transcripts were differentially expressed by at least four-fold in drought-stressed potato tubers, with 75 % and 69 % being down-regulated respectively. A further 229 small RNAs were implicated in gene regulation during drought. The comparison of protein homologues between Solanum tuberosum L. and Arabidopsis thaliana L. indicates that downregulated genes are associated with phenylpropanoid, carotenoid, and patatin biosynthesis. This suggests that there may be nutritive implications to drought stress occurring during the potato tuber bulking phase in sensitive cultivars.

Unmanned agricultural tractor (UAT) represents the advanced stage of autonomous navigation and serves as a core technology in agricultural production. It reduces the operator’s workload, and improves operational accuracy and efficiency. This article reviews three aspects of key autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages, and shortages of these key technologies on UATs are clarified by analyzing technical principles and the current research status. We conducted summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of key autonomous navigation technologies on UATs, it can be seen that fruitful research progresses have been achieved. The review also summarizes the common problems in current technologies. The application research on sharing and integrating multi-source data for autonomous navigation are relatively weak. There is an urgent need of high-precision, and high-stability sensing equipment. The universality of path planning methods, and the efficiency and precision of path tracking need to be improved. It is necessary to develop high reliability electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

Gravity-aided inertial navigation system (GAINS) is an important development in autonomous underwater vehicle (AUV) navigation. An effective path planning algorithm plays an important role in the performance of navigation in long-term underwater missions. By combining the gravity information obtained at each position with the error information from the INS, the posterior Cram\'er-Rao bound (PCRB) of GAINS is derived in this paper. The PCRB is the estimated lower bound of position variance for navigation along the planned trajectory. And the sum of PCRB is used as the minimum cost from the initial state to the current state in the state space, and the position error prediction variance of inertial navigation system (INS) is used as the minimum estimated cost of the path from the current state to the goal state in the A* algorithm. Thus, a path planning method with optimal navigation accuracy is proposed. According to simulation results, traveling along the path planed by the proposed method can rapidly improve the positioning accuracy while consuming just slightly more distance. Even when measuring noise changes, the planned path can still maintain optimal positioning accuracy, and high positioning accuracy is possible for any trajectory located within a certain range of the planned path.

To keep the global navigation satellite system functional during extreme conditions, it is a trend to employ autonomous navigation technology with inter-satellite link. As in the newly built BeiDou system (BDS-3) equipped with Ka-band inter-satellite links, every individual satellite has the ability of communicating and measuring distances among each other. The system also has less dependence on the ground stations and improved navigation performance. Because of the huge amount of measurement data, centralized data processing algorithm for orbit determination is suggested to be replaced by a distributed one in which each satellite in the constellation is required to finish a partial computation task. In current paper, the balanced extended Kalman filter algorithm for distributed orbit determination is proposed and compared with whole-constellation centralized extended Kalman filter, iterative cascade extended Kalman filter, and increasing measurement covariance extended Kalman filter. The proposed method demands a lower computation power however yields results with a relatively good accuracy.

In this paper, an intelligent blind guide system based on 2D LiDAR and RGB-D camera sensing is proposed, and the system is mounted on the smart cane. The intelligent guide system relies on 2D LiDAR, RGB-D camera, IMU, GPS, Jetson nano B01, STM32 and other hardware. The main advantage of the intelligent guide system proposed by us is that the distance between the smart cane and obstacles can be measured by 2D LiDAR based on Cartographer algorithm, thus achieving Simultaneous localization and mapping (SLAM). At the same time, through the improved yolov5 algorithm, pedestrians, vehicles, pedestrian crosswalks, traffic lights, warning posts, stone piers, tactile paving and other objects in front of the visually impaired can be quickly and effectively identified. Laser SLAM and improved yolov5 obstacle identification tests were carried out inside a teaching building on the campus of Hainan Normal University and on a pedestrian crossing on Longkun South Road in Haikou City, Hainan Province. The results show that the intelligent guide system developed by us can drive the wheels and omnidirectional wheels at the bottom of the smart cane, and give the smart cane a self-leading blind guide function like a "guide dog", which can effectively guide the visually impaired to avoid obstacles and reach the predetermined destination, and can quickly and effectively identify the obstacles on the way out. The laser SLAM speed of this system is 25~31FPS, which can realize the short-distance obstacle avoidance and navigation function both in indoor and outdoor envionments. The improved yolov5 helps to identify 86 types of objects, the recognition rate for pedestrian crosswalks and for vehicles are 84.6% and 71.8%, respectively; the overall recognition rate for 86 types of objects is 61.2%, and the obstacle recognition rate of the intelligent guide system is 25-26FPS.

The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, autonomous robots have been able to achieve relatively high levels of autonomy. In more unstructured environments, however, the realisation of autonomous mobile robots remains challenging due to limitations in the robots’ external environment understanding. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. The classical navigation approach typically includes robot perception, localisation, environmental mapping, path planning and motion control stages. More recent learning-based methods may replace the complete navigation pipeline or selected stages of the classical approach. For effective deployment, autonomous robots need to be able to understand their external environments at a sophisticated level according to their intended applications. Therefore, in addition to robot perception, scene analysis and higher-level scene understanding (e.g., traversable/non-traversable, and rough or smooth terrain) are required for autonomous robot navigation in unstructured outdoor environments. A wide number of alternative approaches have been proposed in recent years to attempt to address these scene understanding requirements. This paper provides a comprehensive review and critical analysis of these methods in the context of their applications to the problems of robot perception and scene understanding in unstructured environments, and the related problems of localisation, environment mapping and path planning. State-of-the-art sensor fusion methods and multimodal scene understanding approaches are also discussed and evaluated within this context. The paper concludes with an in-depth discussion regarding the current state of the autonomous ground robot navigation challenge in unstructured outdoor environments and the most promising future research directions to overcome these challenges.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

In this study, the motion characteristics of soft alginate microrobots were investigated with wireless magnetic fields in complex fluidic environments. Our aim is to explore the various motion modes that arise as a result of shear forces in viscoelastic fluids. Polyacrylamide (PAA), a water-soluble polymer, was characterized to produce a dynamic environment with a non-Newtonian fluid. The robots were fabricated by an extrusion-based microcentrifugal droplet method. We successfully demonstrated the feasibility of both wiggling and tumbling motions using snowman-shaped microbots. It is found that wiggling motion is primarily influenced by the interaction between the viscoelastic fluid environment and the non-uniform magnetization of the microbots. Additionally, it is discovered that modifying the viscoelasticity properties of the fluid can affect the motion behavior of the microbots. Furthermore, we observed that swarms of microbots exhibit non-uniform behavior within complex environments. Our velocity analysis has provided valuable insights into the relationship between applied magnetic fields and motion characteristics, enabling a more realistic understanding of surface locomotion in the context of targeted drug delivery.

Furazolidone (FZD) is a synthetic nitrofuran with the antiprotozoal and antibacterial activity. The proper mechanism of FZD induced toxicity is still unclear. This study aimed to investigate the protective effect of curcumin on FZD induced oxidative stress, DNA injury and apoptosis in human hepatocyte L02 cells. The results showed that curcumin treatment significantly ameliorated FZD induced cytotoxicity, characterized by decreasing the production of reactive oxygen species (ROS) and malondialdehyde, as well as increasing superoxide dismutase, catalase activities and glutathione contents. Moreover, curcumin pretreatment significantly inhibited FZD induced the loss of mitochondrial membrane potential, the activation caspase-9 and -3 and apoptosis. Comet assay showed that curcumin attenuated FZD induced DNA injury in a dose-dependent manner. Correspondingly, curcumin markedly reversed the up-regulation of p53, Bax, caspase-9 and -3 mRNA expressions and the down-regulation of Bcl-2 mRNA (all p<0.05 or 0.01). These results reveal that curcumin protects against FZD induced oxidative stress, DNA injury and cell apoptosis via inhibiting oxidative stress and mitochondrial pathway, which may be attributed to ROS scavenging and anti-oxidative ability of curcumin. Importantly, our study highlights that curcumin may be a potential way to prevent FZD-mediated oxidative DNA injury and apoptosis in human or animals.

Interactions between mobile robots and human operators in common areas require a high safety especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection the crossings of planned trajectories, their uncertainty based on model fluctuations, system noise and sensor noise,play an outstanding role. This paper discusses the calculation of expected areas of interactions du ring human-robot navigation with respect to fuzzy and noisy information. Expected crossing points of possible trajectories are nonlinearily associated with positions and orientations of robot and human. The nonlinear transformation of a noisy system input, such as directions of motion of human and robot, to a system output, the expected area of intersection of their trajectories, is done by two methods: statistical linearization and the sigma-point-transformation. For both approaches fuzzy approximations are presented and the inverse problem is discussed where the input distribution parameters are computed from given output distribution parameters.

In mobile robotics, laser scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due its accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for identification and localization of objects using a 2D LiDARs Our main contribution lies in formally defining laser sensor measurements and their representation, the identification of objects, their main properties and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility on multiple object detection and identification, following strictly its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling and implementation of other applications that use laser scanners as a distance sensor.

Directed movement towards a target requires spatial working memory, including processing of sensory inputs and motivational drive. In a stimulus-driven, operant conditioning paradigm designed to train zebrafish, we present a pulse of light via LED’s and/or sounds via an underwater transducer. A webcam placed below a glass tank records fish swimming behavior. During operant conditioning, a fish must interrupt an infrared beam at one location to obtain a small food reward at the same or different location. A timing-gated interrupt activates robotic-arm and feeder stepper motors via custom software controlling a microprocessor (Arduino). “Ardulink”, a JAVA facility, implements Arduino-computer communication protocols. In this way, full automation of stimulus-conditioned directional swimming is achieved. Precise multi­day scheduling of training, including timing, location and intensity of stimulus parameters, and feeder control is accomplished via a user-friendly interface. Our training paradigm permits tracking of learning by monitoring, turning, location, response times and directional swimming of individual fish. This facilitates comparison of performance within and across a cohort of animals. We demonstrate the ability to train and test zebrafish using visual and auditory stimuli. Current methods used for associative conditioning often involve human intervention, which is labor intensive, stressful to animals, and introduces noise in the data. Our relatively simple yet flexible paradigm requires a simple apparatus and minimal human intervention. Our scheduling and control software and apparatus (NemoTrainer) can be used to screen neurologic drugs and test the effects of CRISPR­-based and optogenetic modification of neural circuits on sensation, locomotion, learning and memory.

Transglutaminase 2 (TG2) is a critical cancer cell survival factor that activates several signaling pathways to foster drug resistance, cancer stem cell survival, metastasis, inflammation, epithelial mesenchymal transition, and angiogenesis. All-trans retinoic acid (ATRA) and chemotherapy have been the standard treatments for acute promyelocytic leukemia (APL), but clinical studies have shown that arsenic trioxide (ATO), alone or in combination with ATRA, can improve outcomes. ATO exerts cytotoxic effects in a variety of ways by inducing oxidative stress, genotoxicity, altered signal transduction, and/or epigenetic modification. In the present study, we showed that ATO increased ROS production and apoptosis ratios in ATRA-differentiated NB4 leukemia cells and that these responses were enhanced when TG2 was deleted. The combined ATRA+ATO treatment also increased the amount of nuclear factor erythroid 2-related factor 2 (NRF2) transcription factor, an adaptive regulator of cellular oxidative stress response, and proteolytic activity of calpain, resulting in TG2 degradation and reduced survival of WT leukemia cells. We further showed that upon ATO treatment, the induced TG2 protein expression was degraded in the MCF-7 epithelial cell line, and primary peripheral blood mononuclear cells, thereby sensitizing these cell types to apoptotic signals.

Tobacco Free Nicotine (TFN) Electronic Nicotine Delivery Systems (ENDS) are yet to be classified as tobacco products; consequently, there is ambiguity over whether Food and Drug Administration (FDA) regulatory authority can be extended to include TFN e-cigarettes. In recent years, a more significant number of e-cigarette companies have been manufacturing TFN-containing e-cigarettes and e-liquids to circumvent FDA regulations. While studies have shown that aerosols generated from tobacco-derived nicotine-containing e-cigarettes contain significant Reactive Oxygen Species (ROS) levels, no comparison studies have been conducted using TFN e-cigarettes. This study uses a single puff aerosol generator to aerosolize TFN and tobacco-derived nicotine-containing vape-products and subsequently involves semi-quantifying ROS generated by these vape products in H2O2 equivalents. We found that the differences between ROS levels generated from TFN and tobacco-derived nicotine-containing vape products vary by flavor. TFN tobacco flavors and fruit flavors are more toxic in terms of ROS generation than menthol/ice and drink/beverage flavored products using TFN. The type of salt nicotine used in vape products, TFN or tobacco-derived nicotine, impacts the level of ROS generated from flavored vape products. Thus, a better understanding of the type of salt nicotine used in e-cigarettes (tobacco-derived or synthetic), has modulating effect on lung oxidative stress.

Autonomous unmanned aerial vehicles (UAVs) require highly reliable navigation information. Generally, navigation systems with the inertial navigation system (INS) and global navigation satellite system (GNSS) have been widely used. However, the GNSS is vulnerable to jamming and spoofing. The terrain referenced navigation (TRN) technique can be used to solve this problem. In this study, to obtain reliable navigation information even if a GNSS is not available or the degree of terrain roughness is not determined, we propose a federated filter based INS/GNSS/TRN integrated navigation system. we also introduce a TRN system that combines batch processing and an auxiliary particle filter to ensure stable flight of UAVs even in a long-term GNSS-denied environment. As an altimeter sensor for the TRN system, we use an interferometric radar altimeter (IRA) to obtain reliable navigation accuracy in high altitude flight. In addition, a parallel computing technique with general-purpose computing on graphics processing units (GPGPU) is applied to process a high resolution terrain database and a nonlinear filter in real time on board. Finally, we verify the performance of the proposed system through software-in-the-loop (SIL) tests and captive flight tests in a GNSS unavailable environment.

In the last five years, European research and innovation programmes have prioritised the development of online catalogues and tools (handbooks, models, etc.) to facilitate the implementation and monitoring of Nature Based Solutions (NBS). However, only a few catalogues and toolkits within European programmes are directly related to mainstreaming of NBS for food production (i.e., edible NBS). Therefore, the main aim of this paper is to present existing NBS tools through the eyes of productive urban landscapes. We reviewed 32 projects related to NBS and 50 tools were identified and characterised. Then, the 6 tools already available, and providing indicators, were further analysed in terms of their format and knowledge domains. Our main conclusion demonstrates that there is a lack of tools capable of supporting users for planning and implementing edible NBS, calculating the food potential of the city and/or of individual edible NBS, including the needed resources for implementation and operation (water, nutrients, energy), and assessing their urban design value, environmental and socio-economic impacts. And when they do exist, there is a resistance to share the models and equations behind the tools to allow other projects to reuse or validate them, fact which is contrary to Open Science principles stood up by many research public agencies.

Inducer of C-Repeat Binding Factor (CBF) expression (ICE), a well-known MYC-type bHLH transcription factor, plays a crucial role in the ICE-CBF-cold regulated (COR) cold signaling pathway. Brassica rapa (B. rapa), an important oilseed and vegetable crop, exhibits strong chilling and freezing tolerance. However, the exact molecular mechanisms by which ICE1 functions in B. rapa remain unclear. Here, 41 ICE1 homologous genes were identified from six widely cultivated Brassica species using a bioinformatics approach. These genes exhibit high conservation but reveal evolutionary complexity between diploid and allotetraploid species. Low-temperature stress induced ICE1 homolog expression, with patterns differing between strong and weak cold-tolerant varieties. Two novel ICE1 paralogs, BrICE1 and BrICE2, were cloned from Longyou 6. They positively regulate cold tolerance in B. rapa via a CBF-dependent pathway, contributing to reactive oxygen species (ROS) scavenfging and osmotic adjustment. Immunoblot analysis revealed that low temperatures induce BrICE1 and BrICE2 degradation via the 26S-proteasome pathway. In summary, ICE1 exhibits complex evolutionary relationships in Brassica species. BrICE1 and BrICE2 positively regulate cold tolerance via the CBF-dependent pathway and ROS scavenging mechanism and are also responsible for balancing the development and cold defense of B. rapa.

When following a prescribed route, we need to decide at each intersection which way to proceed. The present work addressed several factors that might influence the difficulty of this decision making process. Participants repeatedly followed a route through a virtual maze with twelve or eighteen intersections, and with two or three choices per intersection. One group performed task S, which promoted decision making by the serial order strategy since all intersections looked alike. Another group performed task SA, which allowed the use of the serial order and the associative cue strategy since unique visual cues were presented at each intersection. We found that in both tasks, participants were more accurate in making decisions on routes with twelve rather than eighteen intersections, and more accurate by a similar amount on routes with two rather than three choices. Reaction time in task SA was reciprocal to accuracy; reaction time in task S was generally lower and route-independent. Accuracy in task SA was similar for participants who experienced smooth transport across intersections and those who experienced abrupt transport, while accuracy in task S was lower for participants who experienced smooth rather than abrupt transport across intersections. We conclude that the number of intersections and the number of choices were equivalent determinants of route following difficulty. We further conclude that optic flow during turns at intersections interfered with anticipatory decision making in task S; hence natural (smooth) transport across intersections did not enhance route following performance.

Though melatonin is known to improve ultraviolet B (UVB)-induced oxidative damage and inflammatory conditions via blockade of nuclear factor (NF)-κB, interleukin (IL)-6, there is no report on anti-wrinkle effect of melatonin to date. Hence in the present study, anti-wrinkle mechanism of melatonin was elucidated in UVB treated HaCaT keratinocytes and hairless mice. Herein melatonin protected against a radical initiator tert-Butyl hydroperoxide (t-BOOH) induced reactive oxygen species (ROS) production, matrix metalloprotease 1 (MMP-1) and cytotoxicity in HaCaT keratinocytes. Also, melatonin suppressed the expression of sonic hedgehog (SHH) and GLI for hedgehog signaling, p-NF-kB, cyclooxygenase (COX-2), p-ERK for inflammatory responses in UVB treated HaCaT keratinocytes. Furthermore, melatonin protected skin from wrinkle formation, transdermal water loss in hairless mice irradiated by UVB for 8 weeks. Notably, melatonin prevented against epidermal thickness and dermal collagen degradation in UVB irradiated hairless mice by Hematoxylin & Eosin and Masson’s trichrome staining. Taken together, these findings suggest that melatonin reduces wrinkle formation via inhibition of ROS/SHH and inflammatory proteins such as NF-kB/COX-2/ERK/MMP1.

The bionic polarization imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement model of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the measurement accuracy of BPINS are systematically investigated and the Stokes vector-based measurement error model of BPINS is established. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed by using Rayleigh scattering to generate scattered sunlight as a known incident light source. The experimental results show that the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation. This finding can guide the subsequent calibration of BPINS, and the quantitative results provide an important reference for its optimal design.

Objective: To assess the effects of chronic walnut consumption on body weight and adiposity in elderly individuals. Methods: The Walnuts And Healthy Aging study is a dual-center (Barcelona, Spain and Loma Linda University [LLU]), 2-year randomized parallel trial. This report concerns only the LLU cohort. Healthy elders (mean age 69 y, 67% women) were randomly assigned to walnut (n = 183) or control diets (n = 173). Subjects in the walnut group received packaged walnuts (28–56 g/d), equivalent to ≈15% of daily energy requirements, to incorporate into their habitual diet, while those in the control group abstained from walnuts. Adiposity was measured periodically, and data were adjusted for in-trial changes in self-reported physical activity. Results: After 2 years, body weight significantly decreased (P = 0.031), while body fat significantly increased (P = 0.0001). However, no significant differences were observed between the control and walnut groups regarding body weight (−0.6 kg and −0.4 kg, respectively, P = 0.67) or body fat (+0.9% and +1.3%, respectively, P = 0.53). Lean body mass, waist circumference and waist-to-hip ratio remained essentially unchanged. Sensitivity analyses were consistent with the findings of primary analysis. Conclusion: Our findings indicate that walnuts can be incorporated into the daily diet of healthy elders without concern for adverse effects on body weight or body composition.

An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. At first the two key steps, Guided Filtering and improved anti-noise morphology navigation line extraction were addressed in detail. Then the experiments were carried out in order to verify the effectiveness and advancement of the presented algorithm. Finally, the optimal template and it’s application condition were studied for improving the image processing speed. The comparison experiment results show that the YCbCr color space has minimum time consumption of 0.094 s in comparison with HSV, HIS and 2R-G-B color spaces. The Guided Filtering method can effectively distinguish the boundary between the new and old soil than other competing vanilla methods such as Tarel, Multi-scale Retinex, Wavelet-based Retinex and Homomorphic Filtering inspite of having the fastest processing speed of 0.113 s. The extracted soil boundary line of the improved anti-noise morphology algorithm has best precision and speed compared with other operators such as Sobel, Roberts, Prewitt and Log. After comparing different size of image template, the optimal template with the size of 140×260 pixels can meet high precision vision navigation while the course deviation angle is not more than 7.5°. The maximum tractor speed of the optimal template and global template are 51.41 km/h and 27.47 km/h respectively which can meet real-time vision navigation requirement of the smart tractor tillage operation in the field. The experimental vision navigation results demonstrated the feasibility of the autonomous vision navigation for tractor tillage operation in the field using the new and old soil boundary line extracted by the proposed improved anti-noise morphology algorithm which has broad application prospect.

Background and Objectives To compare navigator-gated three-dimensional T1-weighted gradient-echo sequences (NG-3D T1W-GRE) with standard breath-hold T1W-GRE (BH T1W-GRE) for the detection of HCC nodules in patients with chronic viral hepatitis which undergo at magnetic resonance imaging (MRI) using gadoxetic acid. Methods and materials We evaluated 58 patients with hepatic nodules at least 1 cm in diameter detected by ultrasound who underwent liver MRI including NG-3D T1W-GRE sequences and breath hold T1-weighted gradient-echo sequences with different flip angles(FA) at 10-25-40° after contrast administration of gadoxetic acid at magnetic scanner operating at1.5 Tesla. Image quality and relative hepatic and nodular enhancement were evaluated by three blinded reviewers. Results In these patients, image quality of NG-3D T1W-GRE was assessed significantly better than quality of BHT1W- GRE (P < 0.005) and relative enhancement was significantly higher than that of BH- T1W-GRE ( P

Microbial communities play a key role in sustainable agriculture. However, we still need more in-formation, to understand the complex response of the microbial community to long-term organic farming, which aims to reduce synthetic fertilizer and pesticide use in order to produce sustainably and improve soil quality. We have assessed the long-term effect of two organic cropping systems and a conventional system on the microbial soil community structure using high-throughput se-quencing analysis. We analyzed the link between these communities and changes in soil properties and crop yield. Results showed that the crop yield was similar among the three cropping systems. Soil properties, such as total organic carbon, nitrogen, ammonium, magnesium and boron, influ-enced changes in the bacterial community structure. A linear discriminant analysis effect size (LEfSe) showed different bacteria and fungi as key microorganism of each of the three different cropping systems, in addition, our results reflected that fungal community were more sensitive than bacteria to cropping system. This research provides an insight about changes occurred in soils, especially in microbial communities considering the effect of that changes in crop yield which were remained stable among the different cropping systems.

Green products have excellent potential for discovering and producing new medicinal products. In recent years, there is a growing interest towards the green synthesis of metal nanoparticles, particularly from plants sources. This eco-friendly approach was used in the recent research to biosynthesize zinc oxide nanoparticles (ZnO NPs) from Cissus antractica plant. The present study aims to examine the cell cytotoxicity, cell death, and pathways of apoptosis in lung cancer cells (A549) and inflammation properties treated with biosynthesized ZnO NPs. Additionally, synthe-sized ZnO nanoparticles were characterized using UV–vis spectroscopy, X-ray diffraction (XRD), Transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FT-IR), and Energy-dispersive X-ray spectroscopy (EDS). The XRD and TEM analyses exhibited 31 nm as the size of synthesized nanoparticles, the pure crystal form of ZnO NPs, and the shape of the NPs as nearly spherical and hexagonal quartzite. The MTT assay used for cytotoxicity evaluation de-picted the significant toxic effect of CA-ZnONPs against the A549 lung cancer cells at concentra-tions up to 20 µg/mL than non-cancerous cells. Furthermore, we observed an elevated ROS level in cancer cells. These NPs also demonstrated dose-dependent ability to suppress colony for-mation and cell migration, which increases their potential as a lung cancer treatment. Further-more, The NPs formulation's ability to induce apoptosis in cancer cells was further supported by Hoechst and propidium iodide dye. Further, CA ZnO NPs increased the gene expression of BAX, Cyto-c, Caspase 3 and 9, but decreased the expression of Bcl-2, indicating that the nanoformulation triggered mitochondrial-mediated apoptosis. Besides, this study showed that NPs suppressed in-flammatory responses by subsequently decreasing reactive oxygen species (ROS) generation, downregulating the expression of the pro-inflammatory cytokines TNF-α, iNOS, COX-2, IL-6, IL-8, and NO. Moreover, the study's findings imply that Cissus antractica are a potential source with biosynthesize nanoparticles that can might be further investigated for the progress of an-ti-inflammatory and anti-cancer drugs with further study.

In GNSS/IMU integrated navigation systems, factors such as satellite occlusion and non-line-of-sight conditions can lead to degradation of satellite positioning results, Subsequently affecting the overall accuracy of the integrated navigation system. To address this issue and ef-fectively utilize historical pseudorange information from satellites, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. These virtual constraints are con-structed using satellite ‘s position from previous time step, the rate of change of pseudoranges, and ephemeris data. This virtual constraint can serve as an alternative solution for individual satellites in case of signal anomalies, ensuring the integrity and continuity of the graph optimi-zation model. Additionally, this paper conducts an analysis of the graph optimization model constructed using these virtual constraints, comparing it with traditional integrated navigation graph optimization model, and analyzes and reconstructs the marginalization process based on these virtual constraints. The experimental results, compared with tightly coupled Kalman fil-tering and the original graph optimization method on a set of real-world data, demonstrate that the introduction of virtual pseudoranges maintains high positioning accuracy. The RMSE error between it and the original graph optimization remains within 5%, affirming the high feasibility of this approach.

An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. Firstly, the two key steps, Guided Filtering and improved anti-noise morphology navigation line extraction, were addressed in detail. Then the experiments were carried out in order to verify the effectiveness and advancement of the presented algorithm. Finally, the optimal template and its application condition were studied for improving the image processing speed. The comparison experiment results show that the YCbCr color space has minimum time consumption, 0.094 s, compared with HSV, HIS and 2R-G-B color spaces. The Guided Filtering method can enhance the new & old soil boundary effectively than any other methods such as Tarel, Multi-scale Retinex, Wavelet-based Retinex and Homomorphic Filtering, meanwhile, has the fastest processing speed of 0.113 s. The extracted soil boundary line of the improved anti-noise morphology algorithm has best precision and speed compared with other operators such as Sobel, Roberts, Prewitt and Log. After comparing different size of image template, the optimal template with the size of 140×260 pixels can meet high precision vision navigation while the course deviation angle is not more than 7.5°. The maximum tractor speed of the optimal template and global template are 51.41 km/h and 27.47 km/h respectively which can meet real-time vision navigation requirement of the smart tractor tillage operation in the field. The experimental vision navigation results demonstrated the feasibility of the autonomous vision navigation for tractor tillage operation in the field using the new & old soil boundary line extracted by the proposed improved anti-noise morphology algorithm which has broad application prospect.

Hypoxia is the main survival challenge that human beings encounter in high altitudes, it is also the leading cause of Acute Mountain Sickness (AMS). Studies have shown that hypoxia induces a large number of reactive oxygen species (ROS) in AMS patients, and the surge of ROS leads to the reduction of oxygen delivery capacity of erythrocyte, senescence and inflammatory impairment of erythrocyte and vascular endothelial cells to a certain extent. Through depicting a target-pathway network, our study indicates that Compound Danshen Dropping Pills (CDDP), which is one of the best-known traditional Chinese medicine used for the treatment of myocardial ischemic diseases, can improve red blood cell oxygen delivery capacity in AMS patients, alleviate tissue and organ damage, relieve a series of clinical symptoms caused by hypoxia through ROS clearance and related mechanisms. We further elucidate the active ingredients of CDDP targeting ROS related pathway by target-ingredient correspondence analysis. Tanshinone IIA, catechol and some other compounds of CDDP were identified to have certain targeting effect on ROS and ROS dependent pathways. This study provides new understandings of CDDP in clinical application on AMS.

Effect of wireworm-damaged lettuce roots on antioxidative defence system (ascorbate-glutathione cycle, photosynthetic pigments) and movement of insect/slug parasitic nematodes towards determined root exudates was studied in a glasshouse experiment. Lettuce seedlings were grown in a substrate soil in the absence/presence of wireworms (Elateridae). Determination of antioxidants and photosynthetic pigments were analysed. Volatile organic compounds (VOC) emitted from lettuce roots were investigated by GC-MS. Herbivore induced root compounds, namely 2,4-nonadienal, glutathione and ascorbic acid, were selected for a chemotaxis assay with nematodes Steinernema feltiae, S. carpocapsae, Heterorhabditis bacteriophora, P. papillosa, and O. myriophilus. Root pests negatively affected photosynthetic pigment contents even before the appearance of visible symptoms, as protective pigments responded to the presence of reactive oxygene species (ROS). Using lettuce as a model plant, we recognised ascorbate-glutathione system as a redox hub in defense response against wireworms and analysed its role in root-exudate mediated chemotaxis of nematodes. Infected plants also demostrated increased levels of volatile 2,4-nonadienal. Entomopathogenic nematodes (EPNs, S. feltiae, S. carpocapsae, and H. bacteriophora) proved to be more mobile than parasitic nematodes O. myriophilus and P. papillosa towards chemotaxis compounds. Among them 2,4 – nonadienal repelled all tested nematodes. Most exudates that are involved in belowground tritrophic interactions remain unknown but an increasing effort is being made in this field of research. Understanding more of these complex interactions would not only allow a better understanding of the rhizosphere but could also offer ecologically sound alternatives in pest management of agricultural systems.

Exercise produces oxidants from a variety of intracellular sources, including NADPH oxidases (NOX) and mitochondria. Exercise-derived ROS are beneficial, and the amount and location of these ROS are important to avoid muscle damage associated with oxidative stress. We discuss here some of the evidence that involves ROS production associated with skeletal muscle contraction and the potential oxidative stress associated with muscle contraction. We also discuss the potential role of H2O2 produced after NOX activation in the regulation of glucose transport in skeletal muscle. Finally, we propose a model based on evidence for the role of different populations of mitochondria in skeletal muscle in the regulation of ATP production upon exercise. The sub-sarcolemmal population of mitochondria has the enzymatic and metabolic components to establish a high mitochondrial membrane potential when fissioned at rest but lacks the capacity to produce ATP; calcium entry to the mitochondria will further increase the metabolic input. Upon exercise, sub-sarcolemmal mitochondria will fuse to intermyofibrillar mitochondria and will transfer the membrane potential to them. These mitochondria are rich in ATP synthase and will subsequentially produce the ATP needed for muscle contraction in long-term exercise. These events will optimize energy use and minimize mitochondria ROS production.

Obesity and metabolic syndrome involve chronic low-grade inflammation called metabolic inflammation as well as metabolic derangements from increased endotoxin and free fatty acids. It is debated whether the endoplasmic reticulum (ER) stress in monocytic cells can contribute to amplify metabolic inflammation; if so, by which mechanism(s). To test this, metabolic stress was induced in THP-1 monocytic cells by treatments with lipopolysaccharide (LPS), palmitic acid (PA), or oleic acid (OA), in the presence or absence of ER stressor thapsigargin (TG). Gene expression of tumor necrosis factor (TNF)-α and markers of ER/oxidative stress was determined by qRT-PCR, TNF-α protein by ELISA, ROS by DCFH-DA assay, HIF-1α/p38/ERK-1,2/NF-κB phosphorylation by immunoblotting, and insulin sensitivity by glucose-uptake assay. Regarding clinical analyses, adipose TNF-α was assessed by qRT-PCR/IHC and plasma TNF-α/hs-CRP/MDA/OX-LDL by ELISA. We found that the cooperative interaction between metabolic and ER stresses promoted TNF-α, ROS, CHOP, ATF6, SOD2, and NRF2 expression (P≤0.0183),. However, glucose uptake was not impaired. TNF-α amplification was dependent on HIF-1α/p38/NF-κB phosphorylation, while MAPK/NF-κB inhibitors and antioxidants/ROS scavengers attenuated TNF-α production (P≤0.05). Individuals with obesity displayed increased adipose TNF-α gene/protein expression as well as elevated plasma levels of TNF-α, CRP, MDA, and OX-LDL (P≤0.05). Our findings support a cooperative interaction between metabolic and ER stresses, favoring inflammation by triggering TNF-α production via the ROS/CHOP/HIF-1α and MAPK/NF-κB dependent mechanisms. This study also shows the therapeutic potential of ROS scavengers/anti-oxidants in inflammatory conditions involving metabolic/ER stresses.

BOLD-100, a ruthenium-based complex, sodium trans-[tetrachloridobis(1H-indazole)ruthenate(III)] (also known as IT-139, NKP1339 or KP1339), is a novel small molecule drug that demonstrated a manageable safety profile at the maximum tolerated dose and modest antitumor activity in a phase I clinical trial. BOLD-100 has been reported to inhibit the upregulation of the endoplasmic reticulum stress sensing protein GRP78. However, response to BOLD-100 varies in different cancer models and the precise mechanism of action in high-response versus low-response cancer cells remains unclear. In vitro studies have indicated that BOLD-100 induces cytostatic rather than cytotoxic effects as a monotherapy. To understand BOLD-100 mediated signaling mechanism in breast cancer cells, we used estrogen receptor positive (ER+) MCF7 breast cancer cells to obtain gene-metabolite integrated models. Particularly, BOLD-100 significantly reduced expression of genes involved in the DNA repair pathway. BOLD-100 also induced reactive oxygen species (ROS) and phosphorylation of histone H2AX, gH2AX (Ser139), suggesting disruption of proper DNA surveillance. In estrogen receptor negative (ER-) breast cancer cells, combination of BOLD-100 with a PARP inhibitor, olaparib, induced significant inhibition of cell growth and xenografts and increased gH2AX. Thus, BOLD-100 is a novel DNA repair pathway targeting agent and can be used with other chemotherapies in ER- breast cancer.