Studies of the fundamental origins of friction have undergone a rapid acceleration in recent years by providing valuable information on the nanoscale mechanisms responsible for the friction at the macroscopic level. Significant efforts have been directed into developing composite nanofluids and nanoparticle additives to unlock new tribological properties unattainable by traditional lub-ricants. The studies are now further evolving by developing methods to achieve active control of the nano- and/or mesoscale friction by application of magnetic and electric fields external to the contact. These methods constitute an area of rapidly growing interest, and they also are illumi-nating how the performance of conventional lubricants could be enhanced through synergistic addition of nanoparticles (NPs). This mini-review highlights 25 publications that collectively re-veal significant progress, as well as important outstanding challenges, to a fundamental under-standing of how the addition of NPs impacts the lubricant performance. The first two sections focus on the use of Quartz Crystal Microbalance (QCM), a technique that spans atomic to mac-roscale length and time scales. Subsequent sections expand to complimentary methods comparing results at the macro and atomic scale for similar materials. These studies highlight the pivotal role of the nanoparticle charge and surface treatment, while also indicating that rolling of nano-particles is ineffective and/or detrimental.

This study explores the application of the Laban/Bartenieff Movement System (® LBMS), particularly its Effort component, to analyze the biomechanical dynamics of the golf swing. Focusing on the initiation of the downswing, this paper investigates how the instantaneous screw axis (ISA) with rotational and linear motions contributes to subsequent movements, such as the hip turn. We propose that the physical forces generated by the golf club, characterized by mass moment inertia, extend beyond the body's boundaries, such as through the hand grip. A skilled golfer’s ability to 'allow' these forces to influence body dynamics without opposing them is analyzed through the lens of LBMS's Free Flow Effort, suggesting an indulgent and expansive use of movement energy.

Due to constraints in launch platform and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems, and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and states deviation at the control-start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning.

There is increasing evidence that myocarditis starts as a patchy process, accordingly, the detection of segmental affection is important for early recognition of the disease and proper initiation of anti-inflammatory treatment. We present our first experience here with using speckle-tracking echocardiography to detect subtle segmental involvement of the left ventricle in two cases with suspected myocarditis. STE consolidated the diagnosis and helped with the early initiation of intravenous immunoglobulins and subsequent control of the disease. STE was also able to show the specific topography of distribution, of each pathogen linked to inflammation.

: In this investigation, the impact of reducing agent concentration on the production of zinc oxide nanoparticles (ZnO NPs) was examined. During the synthesis, an assessment of ionic conductivity was carried out, revealing a significant increase in conductivity prior to the introduction of the reducing agent, followed by a sharp decrease upon its addition. Characterization of the ZnO NPs involved UV-visible spectroscopy, scanning electron microscopy, Fourier infrared spectroscopy, and x-ray diffraction analysis. The outcomes suggest that the characteristics of the ZnO NPs are influenced by the concentration of the reducing agent during the synthesis process. Notably, employing a concentration of 0.5 v/v resulted in the production of nanoparticles with relatively uniform sizes. Conversely, concentrations below 0.5 v/v led to slow formation, while concentrations exceeding 0.5 v/v yielded non-uniform nanoparticles. Furthermore, the ZnO NPs synthesized with a higher concentration of reducing agent exhibited a narrower optical band gap and increased surface energy.

Abstract: Although experimental attempts to measure a single molecule/particle at room temperature or under physiological conditions without immobilization, for example on a surface, or without hydrodynamic flow have so far failed, this failure has given impetus to the underlying theory of Brownian motion towards its stochastic due to diffusion. Quantifying the thermodynamic jitter of molecules/particles inspires many and forms the theoretical basis of single-molecule/single-particle biophysics and biochemistry. For the first time, our simulation results for a live cell (cytoplasm) show that the tracks of individual single molecules are localized in Brownian motion, while there is fanning out in fractal diffusion (anomalous diffusion).

Passivating the grain boundaries is completely very crucial to achieve high power conversion efficiency in halide PSCs.

The intricate interplay between driver cognitive dysfunction, mental workload (MWL), and heart rate variability (HRV) provides a captivating avenue for investigation within the domain of transportation safety studies. This article presents a comprehensive review and examines cognitive hindrance stemming from mental workload and heart rate variability. It scrutinizes the mental workload experienced by drivers by leveraging data gleaned from prior studies that employed heart rate monitoring systems and eye tracking technology, thereby illuminating the correlation between cognitive impairment, mental workload, and physiological indicators such as heart rate and ocular movements. The investigation is grounded in the premise that the mental workload of drivers can be assessed through physiological cues, such as heart rate and eye movements. The study discovered that heart rate variability (HRV) and infrared (IR) measurements played a crucial role in evaluating fatigue and workload for skilled drivers. However, the study overlooked potential factors contributing to cognitive impairment in drivers and could benefit from incorporating alternative indicators of cognitive workload for deeper insights. Furthermore, investigated driving simulators demonstrated that an eco-safe driving Human-Machine Interface (HMI) significantly promoted safe driving behaviors without imposing excessive mental and visual workload on drivers. Recommendations were made for future studies to consider additional indicators of cognitive workload, such as subjective assessments or task performance metrics, for a more comprehensive understanding.

Influenza viruses pose a continuing public health challenge due to their high mutation rate and the need for annual vaccine updates. A recent advancement in nanoparticle-based vaccine technology for developing a universal influenza vaccine. We focused on four key studies investigating the use of lipid nanoparticles (LNPs), nanoparticle immunogens, and multivalent epitope-based nanoparticles. The studies demonstrated promising results. The single-dose mRNA -LNP vaccine targeting five influenza B virus antigens effectively protected mice from a broad range of strain. Additionally, nanoparticle immunogens designed to display multiple influenza virus strains induced broad protective immunity in mice. Furthermore, LNPs enhanced the efficacy of mRNA and protein subunit vaccines by stimulating robust T follicular helper cell and humoral responses. Finally, an intranasal multivalent epitope-based nanoparticle vaccine offered broad protection against diverse influenza viruses. These findings highlight the potential of nanoparticle-based approaches for developing a universal influenza vaccine that offers long-lasting and broad-spectrum protection. Further research is needed to evaluate the safety and efficacy of these novel vaccines in humans.

Background. Transferrin receptor 1 (TfR1), glucose transporter 1 (GLUT1), and CD98hc are candidates for targeted therapy at the blood-brain barrier (BBB). Our objective was to challenge the expression of TfR1, GLUT1, and CD98hc in brain capillaries by the histone deacetylase inhibitor (HDACi) valproic acid (VPA). Methods. Primary mouse brain capillary endothelial cells (BCECs) and brain capillaries isolated from mice injected intraperitoneally with VPA were examined using RT-qPCR and ELISA. Targeting to the BBB was performed by injecting monoclonal anti-TfR1 (Ri7217)-conjugated gold nanoparticles measured using ICP-MS. Results. In BCECs co-cultured with glial cells, Tfrc mRNA expression was significantly higher after 6 h VPA returning to baseline after 24 h. In vivo Glut1 mRNA expression was significantly higher in males, but not females', receiving VPA, whereas Cd98hc mRNA expression was unaffected by VPA. TfR1 increased significantly in vivo after VPA, whereas GLUT1 and CD98hc were unchanged. Uptake of anti-TfR1-conjugated nanoparticles was unaltered by VPA in spite upregulated TfR expression. Conclusions. VPA upregulates TfR1 in brain endothelium in vivo and in vitro. VPA does not increase GLUT1 and CD98hc proteins. The increase in TfR1 does not result in higher anti-TfR1 antibody targetability, suggesting targeting sufficiently occurs with available transferrin receptors without further contribution from accessory VPA-induced TfR1.

This research article describes the creation of a mock-up for a Smart Insole prototype that employs Force Sensitive Resistors (FSRs) and an ADXL345 accelerometer. The mock-up is an early step towards realising the concept and functionality of the planned Smart Insole system. The key factors in the mock-up's design, integration, and testing are highlighted, with a focus on the iterative refining and optimisation process. The mock-up, which was carefully planned and implemented, highlights the practicality and possible applications of Smart Insole technology in healthcare, sports performance measurement, and rehabilitation. The paper outlines the development process and implementation of a "Smart Insole" utilizing Force Sensitive Resistors (FSR) and the ADXL345 accelerometer. The project aims to create an innovative wearable technology solution for monitoring foot biomechanics and enhancing human performance. The Smart Insole prototype integrates FSRs strategically placed on the insole to capture pressure distribution across the foot, along with an ADXL345 accelerometer to track foot orientation and movement. Through a combination of hardware integration, firmware development using Arduino IDE, and visualization using Processing application, the Smart Insole offers real-time monitoring and analysis of gait dynamics, pressure distribution, and foot movement.

Omega-3 polyunsaturated fatty acids (ɷ-3 PUFAs) offer diverse health benefits, such as supporting cardiovascular health, improving cognitive function, promoting joint and musculoskeletal health, and contributing to healthy aging. Despite their advantages, challenges like oxidation susceptibility, low bioavailability, and potential adverse effects at high doses persist. Nanoparticle encapsulation emerges as a promising avenue to address these limitations while preserving stability, enhanced bioavailability, and controlled release. This comprehensive review explores the therapeutic roles of omega-3 fatty acids, critically appraising their shortcomings and delving into modern encapsulation strategies. Furthermore, it explores the potential advantages of Metal-organic framework nanoparticles (MOF NPs) compared to other commonly utilized nanoparticles in improving the therapeutic effectiveness of omega-3 fatty acids within drug delivery systems (DDS). Additionally, it outlines future research directions to fully exploit the therapeutic benefits of these encapsulated omega-3 formulations for cardiovascular disease treatment.

Biological nanoparticles (NPs), such as extracellular vesicles (EVs), exosome-mimetic nanovesicles (EMNVs) and nanoghosts (NGs), are perspective non-viral delivery vehicles for all types of therapeutic cargo. Biological NPs are renowned for their exceptional biocompatibility and safety, alongside their ease of functionalization, but a significant challenge arises when attempting to load therapeutic payloads, such as nucleic acids (NAs). One effective strategy involves fusing biological NPs with liposomes loaded with NAs, resulting in hybrid carriers that offer the benefits of both biological NPs and the capacity for high cargo loads. Despite their unique parameters, one of the major issues of virtually any nanoformulation is the ability to escape degradation in the compartment of endosomes and lysosomes which determines the overall efficiency of nanotherapeutics. In this study, we fabricated all major types of biological and hybrid NPs and studied their response to acidic environment observed in endolysosomal compartment. In this study, we show that EMNVs display increased protonation and swelling relative to EVs and NGs in an acidic environment. Furthermore, the hybrid NPs exhibit an even greater response compared to EMNVs. Short-term incubation of EMNVs in acidic pH corresponding to late endosomes and lysosomes again induces protonation and swelling, whereas hybrid NPs are ruptured, resulting in the decline of their quantities. Our findings demonstrate that in an acidic environment, there is enhanced rupture and release of vesicular cargo observed in hybrid EMNVs that are fused with liposomes compared to EMNVs alone. This was confirmed through PAGE electrophoresis analysis of mCherry protein loaded into nanoparticles. In vitro analysis of NPs colocalization with lysosomes in HepG2 cells demonstrated that EMNVs mostly avoid endolysosomal compartment whereas hybrid NPs escape it over time. To conclude, (1) hybrid biological NPs fused with liposomes appear more efficient in the endolysosomal escape via the mechanism of proton sponge associated with scavenging of protons by NPs, influx of counterions and water, and rupture of endo/lysosomes, but (2) EMNVs are much more efficient than hybrid NPs in actually avoiding endolysosomal compartment in human cells. These results reveal biochemical differences across four major types of biological and hybrid NPs, and indicate that EMNVs are more efficient in escaping or avoiding endolysosomal compartment.

Background: Systemic lupus erythematosus (SLE) is characterized by inflammation and cardiovascular complications. Our study aimed to investigate subclinical and early indicators of systolic myocardial dysfunction in SLE patients using advanced echocardiographic methods and biomarkers. Methods: In this cross-sectional study, we enrolled 102 SLE patients without known cardiac impairment and 51 healthy controls. Demographics, disease characteristics, laboratory results, disease activity (SLEDAI) and organ damage (SDI) indices were recorded. Left ventricular global longitudinal strain (GLS) and myocardial work indices were assessed by utilizing speckle tracking echocardiography. In addition, high sensitivity C-reactive protein (hsCRP), high sensitivity troponin (hsTn) and N-terminal-pro B-type natriuretic peptide (NT-proBNP) levels were measured in blood samples. Results: In comparison to controls, SLE patients had significantly higher GLS (-19.94±2.71%vs-21.15±1.55%, p<0.001) and global wasted work (GWW) (94±71mmHg%vs71±49 mmHg%, p=0.025). Notably, NT-proBNP and hsTn were threefold and twofold higher in SLE group compared to control group, respectively (p<0.001). Within SLE cohort, patients with at least moderate disease activity (SLEDAI≥4) both biomarkers were significantly elevated than those with low disease activity (SLEDAI<4). Conclusion: Advanced echocardiographic parameters combined with specific biomarkers have a promising role in detecting systolic dysfunction at an early phase in SLE patients, potentially enabling timely interventions to mitigate cardiovascular risk.

This paper introduces PatchFusion, an innovative approach for nonrigid tracking and reconstruction of deformable objects using a single RGB-D sensor. Existing methods face challenges in accurately capturing the rapid deformations of soft and flexible objects, thereby limiting their utility in diverse scenarios. Our approach overcomes this challenge by employing a dynamic patch-based framework that adapts to rapid inter-frame motions. Firstly, patch-wise rigid transformation fields for non-overlapping patches are solved via Iterative Closest Point (ICP) by incorporating geometric features as additional similarity constraints, thereby enhancing robustness and accuracy. Secondly, deformation optimization based on a nonrigid solver is applied to refine the coarse transformation fields. In order to enable simultaneous tracking and reconstruction of deformable objects, the patch-based rigid solver is designed to run in parallel with the nonrigid solver, serving as a plug-and-play module requiring minimal modifications for integration while enabling real-time performance. Following a comprehensive evaluation, PatchFusion showcases superior performance in effectively dealing with rapid inter-frame deformations when compared to existing techniques, rendering it a promising solution with broad applicability across domains such as robotics, computer vision, and human-computer interaction.

With the rapid development of tumor immunotherapy, nanoparticle vaccines have attracted much attention as a potential therapeutic strategy. The potential role of the mannose-modified lipid calcium phosphate nanoparticle vaccine in enhancing the anti-tumor immune response was investigated. The aim of this study was to investigate the effect of mannose modification on the immune response of nanoparticles in regulating the tumor microenvironment through systematic review and analysis and to explore its potential clinical application in tumor therapy. Currently, despite the potential advantages of nanoparticle vaccines in immunotherapy, achieving an effective immune response in the tumor microenvironment remains a challenge. Tumor immune escape and overexpression of immunosuppressive factors limit its clinical application. Therefore, this study will explore how to intervene in the immunosuppressive mechanism in the tumor microenvironment through mannose-modified lipid calcium phosphate nanoparticle vaccines so as to improve the immunotherapy effect of tumor patients and provide new ideas and strategies for the field of tumor therapy.

(1) Background: The proportion of fully mechanized harvesting systems in Austria is constantly increasing especially because of the technological development of the machines, which allows them to drive on increasingly steep terrain. This leads to additional challenges and potential hazards for the operators, which may also cause higher stress levels. The purpose of this study is to develop and debate a new set of methodologies for determining time and space resolved psychophysiology data to analyze stressful and non-stressful work situations for harvester and forwarder operators; (2) Methods: we suggest a study protocol to analyze a) tasks performed by the driver, b) environmental factors, like slope gradient, c) the psychophysiological response of experts during these tasks, and d) evaluate the worker´s subjective stress and fatigue before and after a harvest operation. (3) Results: Within this manuscript we present a study protocol based on quantitative and qualitative methods, like time and space resolved psychophysiology, questionnaires, qualitative interviews, as well as video and sensor-based analysis of environmental and machine data. The first results from real measurements of a forwarder driver are presented; (4) Conclusions: This multimodal research protocol serves to explore the relationship between stress, fatigue, and performed tasks. Through our quantitative and qualitative methodology, researchers can improve the health and safety of forest workers at work, improve their productivity and reduce damage to remaining trees.

The right heart catheterisation constitutes the gold standard for pulmonary hypertension (PH) diagnosis. However, echocardiography remains a reliable, non-invasive, inexpensive, convenient, and easily reproducible modality not only for the preliminary screening of PH but also for PH prognosis. The aim of this review is to describe a cluster of echocardiographic parameters for the detection and prognosis of PH and analyse the challenges of echocardiography implementation in patients with suspected or established PH. The most important echocardiographic index is the calculation of pulmonary arterial systolic pressure (PASP) through the tricuspid regurgitation (TR). It has shown high correlation with invasive measurement of pulmonary pressure, but several drawbacks have questioned its accuracy. Besides this, the right ventricular outflow track acceleration time (RVOT-AT) has been proposed for PH diagnosis. A plethora of echocardiographic indices: right atrial area, pericardial effusion, the tricuspid annular plane systolic excursion (TAPSE), the TAPSE/PASP ratio, tricuspid annular systolic velocity (s′) and recently, can reflect the severity and prognosis of PH. Recent advances in echocardiography with 3-dimensional right ventricular (RV) ejection fraction, RV free wall strain and right atrial strain may further assist the prognostication of PH.

The extra precession of Mercury - 42.9 seconds of arc per century - explained by General Relativity (GR), is the result of a secular addition of 5.02 × 10⁻⁷ rad. at the end of every orbit around the Sun. We will analyze, the instantaneous precession and its addition along one orbit, determine the magnitude and oscillations around the mean value, comparing key theoretical proposals. This angular precession, should be the result reaction of Mercury to the gravitoelectric action produced by the geometric curve space-time at each single point of the elliptic orbit. The better we should know about this instantaneous precession, the better we will determine the external action and its quantum core nature, if that is the case. The Doppler tracking of the MESSENGER spacecraft, produces only 1 m error, enough precision to deduce the complete geodesic orbit of Mercury as an open free-fall path, isolated from other planets gravitational interference. The aim of this article is also to encourage JPL, IMCCE. and other scientific teams to do so because, as far as I know, it has not been entirely measured yet, by accurately tracking that motion.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

Abstract: Rationale. Object tracking has significance in many applications ranging from control of unmanned vehicles to autonomous monitoring of specific situations and events, especially when providing safety for patients with certain adverse conditions such as epileptic seizures. Conventional tracking methods face many challenges, such as the need for dedicated attached devices or tags, influence by high image noise, complex object movements, and intensive com-putational requirements. We have developed earlier computationally efficient algorithms for global optical flow reconstruction of group velocities that provide means for convulsive seizure detection and have potential applications in fall and apnea detection. Here, we address the chal-lenge of using the same calculated group velocities for object tracking in parallel. Methods. We propose a novel optical flow-based method for object tracking. It utilizes real-time image se-quences from the camera and directly reconstructs global motion-group parameters of the con-tent. These parameters can steer a rectangular region of interest surrounding the moving object to follow the target. The method successfully applies to multi-spectral data, further improving its effectiveness. Results. Experimental results on simulated tests and complex real-world data demonstrate the method's capabilities. The proposed optical flow reconstruction can provide accurate, robust, and faster results compared to current state-of-the-art approaches.

It has been well established that hypertension is considered as a predominant risk factor for the development of cardiovascular diseases. Despite the link between hypertension and cardiovascular diseases, hypertension may directly affect the cardiac function leading in heart failure, mostly with preserved ejection fraction (HFpEF). There are echocardiographic findings indicating hypertensive heart disease (HHD) defined as altered cardiac morphology (left ventricular concentric hypertrophy, left atrium dilatation) and function (systolic or diastolic dysfunction) in patients with persistent hypertension irrespective of cardiac pathologies to which it contributes, such as coronary artery disease and kidney function impairment. In addition to classical echocardiographic parameters, novel indices, like speckle tracking of the left ventricle and left atrium, 3D volume evaluation, myocardial work in echocardiography may provide more accurate and reproducible diagnostic and prognostic data in patients with hypertension. However, their use is still underappreciated. An early detection and prompt therapy of HHD will greatly improve the prognosis. Hence, in the present review, we shed light on the role of echocardiography in the contemporary diagnostic and prognostic approach of HHD.

This review study, delves into the groundbreaking potential of quantum dots in revolutionizing the field of stem cell tracking for regenerative medicine. Beginning with an introduction that underscores the pivotal role of stem cell tracking in regenerative medicine, this review introduces quantum dots as promising tools for this purpose. It proceeds to explore the fundamental properties of quantum dots, including the quantum confinement effect, size-dependent emission, and exceptional brightness, which render them ideal candidates for stem cell tracking. The historical evolution and recent advancements of quantum dot technology in biomedicine are discussed, emphasizing their growing importance in terms of biocompatibility and safety. Furthermore, various labeling strategies for stem cells using quantum dots are detailed, encompassing surface modification and internalization techniques, with a comparison of their respective advantages and drawbacks. A comprehensive exploration of the wide range of imaging modalities that synergize with quantum dots for stem cell tracking is presented, accompanied by an evaluation of their strengths and limitations. Real-world applications of quantum dot-based stem cell tracking in regenerative medicine, spanning tissue regeneration to disease modeling, are showcased, with illuminating case studies. Current challenges and limitations in quantum dot-based stem cell tracking, including long-term stability and regulatory considerations, are addressed, and innovative directions and emerging trends in quantum dot technology are proposed. Safety considerations and strategies to enhance quantum dot biocompatibility within biological systems are discussed, while ethical and regulatory implications related to their use in stem cell tracking are explored, promoting responsible research and development practices. Finally, the review concludes by summarizing key insights and takeaways, reaffirming the transformative potential of quantum dots in advancing stem cell tracking and the field of regenerative medicine.

Materials based on platinum metals with very good catalytic activity were tested in the reduction of p–nitrophenol (pNP) to p–aminophenol (pAP). The majority of presented catalytic materials are based on the adsorption of p–nitrophenol on the surface of the catalyst simultaneously with molecular hydrogen, coming from sodium borohydride in an aqueous medium, which reduces it. In the present paper, a catalytic material based on osmium dispersed in n–decanol or n–dodecanol is presented, which also works as an emulsion membrane, for the absorption of p–nitrophenol and molecular hydrogen at the n–alcohol aqueous solution interface. The hydrogenation of p–nitrophenol is carried out in a reaction and separation column in which the acid receiving phase emulsion is dispersed in the osmium nanodispersion, in n–alcohols. This emulsion circulates from the base of the column to its upper part in co-current or counter-current with the source phase consisting of p–nitrophenol and sodium borohydride. Experiments show that the circulation of counter-current phases is superior to that in co-current, and the emulsion based on n–decanol is more efficient than the one based on n–dodecanol. The increase in the pH difference between the source and receiving phases leads to the increase in the conversion of p–nitrophenol to p–aminophenol. The efficiency of separation of the reaction product in the receiving phase is lower than the conversion at the same operating time. The apparent catalytic rate constant (kapp) of the new catalytic material based on the emulsion membrane with nanodispersion of osmium nanoparticles (0.1×10−3 for n–dodecanol and 0.9×10−3 for n-decanol) is lower by an order of magnitude compared to those based on adsorption on catalysts from platinum metal group. The advantage of the tested membrane catalytic material is that it extracts p–aminophenol in the acid receiving phase. The paper proposes a mechanism of the studied reduction system.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

This research addresses the formidable challenge of achieving precise trajectory tracking for autonomous vehicle formations in uncertain environments. It introduces an adaptive control system tailored for autonomous vehicles, with a primary focus on ensuring prescribed performance in trajectory tracking within a leader-follower formation paradigm. The system incorporates a guidance law that allows the leader vehicle to dynamically adjust desired yaw angles and speeds for follower vehicles based on the established reference trajectory, enhancing tracking accuracy and responsiveness to environmental changes. To address practical external disturbances, the study utilizes Radial Basis Function Neural Networks (RBFNN) in conjunction with second-order filters for error approximation. This approach is further strengthened by a carefully formulated adaptive law. The innovative integration of a barrier Lyapunov function with the backstepping method significantly enhances the system’s adaptability and robustness, ensuring trajectory tracking performance meets predetermined standards. Simulation results illustrate the control system’s adept handling of various external disturbances, consistently maintaining trajectory tracking errors within predefined limits. This underscores the system’s potential to markedly enhance the operational reliability and efficiency of autonomous vehicle formations in unpredictable environmental conditions.

Cancer, characterized by abnormal cell proliferation driven by genetic mutations, remains a significant health challenge. Tailoring effective therapies depends on factors like tumor location, grade, and stage, alongside patient condition. Leveraging Nano-carrier encapsulated drugs offers a promising avenue, as they accumulate preferentially at tumor sites, enhancing therapeutic efficacy while mitigating side effects. Polymeric Nano-carriers, with their customizable properties, further optimize drug delivery efficiency and specificity. Incorporating active targeting ligands such as antibodies, carbohydrates, peptides, folates, and aptamers-onto polymeric nanoparticle surfaces through techniques like functionalization, adsorption, and conjugation plays a pivotal role in directing therapeutic agents to tumor cells. Consequently, polymeric nanoparticles emerge as the carrier of choice for delivering drugs to various tumor types, including breast, colon, lung, prostate, liver, and spleen tumors.

Electromagnetic actuation can support many fields of technology, such as robotics or biomedical applications. In this context, fully understanding the system behavior and proposing a low-cost package for feedback control is challenging. Modeling the electromagnetic force is particularly tricky because it is a nonlinear function of the actuated object’s position and coil’s current. Measuring in real time the position of the actuated object with the precision required for accurate motion control is also nontrivial. In this study, we propose a novel, cost-effective electromagnetic set-up to achieve position control via visual feedback. We actuate vertically and under different experimental conditions a 10 mm diameter steel ball hanging on a low-stiffness spring, demonstrating good tracking performance (the position error remains within ±0.5 mm with a negligible phase delay in the best scenarios). The experimental results confirm the feasibility of the proposed set-up, which is characterized by minimum complexity and realized with off-the-shelf and cost-effective components. For these reasons, such a contribution helps to understand and apply electromagnetic actuation even further.

This study investigated the accuracy and precision of a commercially available PNT solution that uses DGNSS-SBAS technology. Time and position data were sampled at a frequency of 20Hz during both short and long trajectory of a simulated controlled dry-land slalom, as well as during a real-world on-water slalom exercise. The primary objective was to assess the positional accuracy, availability, integrity, and service continuity of the PNT solution while evaluating its ability to differentiate between trajectories. Additionally, the simulated results were compared with an on-water real-world slalom test to validate the findings. The results of the controlled dry-land slalom test indicate that the PNT solution provided accurate measurements with an overall mean±SD Hrms of 0.20±0.02m. The integrity measures, HDOD and PDOP were found to be ideal to excellent, with values of 0.68±0.03, and 1.36±0.07, respectively. The PNT solution utilised an average of 20±1 satellites from the constellation, resulting in an accuracy of

The objective of this study was to analyze the mental workload using EEG and eye tracking data and classify it using machine learning algorithms. The machine learning model was developed based on the simultaneous recording of eye tracking and EEG measurements during the experimental process. The experiments involved 15 university students, consisting of 7 women and 8 men. Throughout the experiments, the researchers utilized the n-back memory task and the NASA-Task Load Index (TLX) subjective rating scale to assess various levels of mental workload. The findings revealed that as the task difficulty increased, there was an increase in the diameter of both the right and left pupils, the number of fixations, the number and duration of saccades, and the number and duration of blinks. Conversely, variables related to fixation duration decreased. The EEG results indicated that theta power in the prefrontal, frontal, and front central regions increased with task difficulty. Additionally, alpha power increased in the frontal regions but decreased in the temporal, parietal, and occipital regions as the task became more challenging. Furthermore, low beta power significantly decreased in almost all brain regions as the task difficulty increased. In terms of the four-class classification problem, the mental workload level can be predicted with an accuracy rate of 76.59% using 34 selected features. This study has made a significant contribution to the literature by presenting a four-class mental workload estimation model that utilizes different machine learning algorithms.

Cardiotoxicity remains one of the leading causes of morbidity and mortality in childhood cancer survivors. This study aimed to evaluate cardiotoxic side effects of chemotherapeutic regimens in a pediatric population, as revealed by assessment of baseline end-of-treatment and in follow-up after 1 year. A prospective study was conducted on 39 children, enrolled over a period of 5 years (2017-2022), diagnosed with leukemia and receiving chemotherapy regimens. A multimodal echocardiographic evaluation was done (two-dimensional echocardiography and M-mode, tissue doppler imaging (TDI) and 2D-speckle tracking (2DST) before the initiation of the cytostatic treatment, at the end of the treatment and 1 year after the treatment. Ultrasound-derived parameter values were compared between evaluations and correlated with cumulative doses of chemotherapeutic agents used. There were no significant differences in mean values for any of the imagistic parameters analyzed. However, a significant correlation was found between E’value percentage variation and cumulative dose of both anthracyclines and antimetabolics administered (p=0.03). Moreover, a significant linear regression correlation was found between alkylating agent dose and global longitudinal strain (GLS)(p<0.01). Non-invasive cardiovascular imaging parameter values did not differ significantly from baseline in our study, but some of them seem to be dependent upon cumulative dose of cytostatic agents used. Further studies on larger populations and involving a longer follow-up period might provide more insight into cardiotoxicity of chemotherapy regimens.

Nanoencapsulation has emerged as a recent improvement in the delivery of drugs, offering and improving stability and bioavailability, and allowing for the controlled and targeted delivery of substances to specific cells or tissues. However, traditional nanoparticle delivery faces challenges such as short circulation time and immune recognition. To address these issues, cell membrane-coated nanoparticles have been proposed as a promising alternative. The production of cell membrane-coated nanoparticles involves three key stages: cell lysis and membrane fragmentation, membrane isolation, and nanoparticle coating. Typically, cell membranes are fragmented using hypotonic lysis in combination with homogenization or sonication. Subsequent membrane fragments are isolated through multiple centrifugation steps. The coating of nanoparticles can be achieved through extrusion, sonication, or a combination of both methods. This analysis shows the absence of a universally applicable method for nanoparticle coating, as the three stages exhibit notable differences in their procedures. Here we review ongoing developments and approaches to cell membrane-coated nanoparticles that position this technology as a promising alternative for effective targeted drug delivery and many other therapeutic applications.

Nanotechnology has provided an opportunity for unparalleled development of the treatment of various severe diseases. The unique properties of nanoparticles offer a promising strategy in enhancing antitumor immunity by enhancing immunogenicity and presentation of tumor autoantigens for cancer immunotherapy. Polymeric, liposomal, carbon or silica-based nanoparticles are among those with major immunomodulatory roles in various cancer treatments. Cancer vaccines, in particular digestive cancer vaccines have been researched and developed on nanotechnological platforms. Due to their safety, controlled release, targeting of dendritic cells(DCs) and improved antigen uptake, as well as enhanced immunogenicity, nanoparticles have been used as carriers, as adjuvants for increased effect at the tumor level, for their immunomodulating effect, or for targeting tumor microenvironment, increasing tumor immunogenicity and reducing tumor inflamatory response. This review looks at digestive cancer vaccines developed on nanoparticle platforms and the impact nanoparticles have on the effects of these vaccines.

The performance of laser beams in tracking Lissajous scan trajectories is severely limited by beam jitter. To enhance the performance of fast steering mirror (FSM) control in tracking Lissajous scan trajectories, this paper proposed a fractional order active disturbance rejection controller (FOADRC) and verified its effectiveness in improving system scanning tracking accuracy. A dynamic mathematical model of fast steering mirror was studied and the design of parameters for the control mode of the closed-loop system was determined. A reduced order linear active disturbance rejection controller suitable for FSM systems was designed and the corresponding fractional order proportional differentiation (FOPD) controller were determined according to the mathematical model. The use of the designed controller enabled high-performance tracking of high-frequency Lissajous scanning curves (X-axis 500 Hz, Y-axis 350 Hz) and met the need for high-frequency repetitive scanning. The controller has the characteristics of simple implementation and low computational complexity and is suitable for closed-loop control applications in engineering.

The aberrant glycosylation is a hallmark of cancer progression and chemoresistance. It is also an immune therapeutic target for various cancers. Tunicamycin (TM) is one of the potent nucleo-side antibiotics and an inhibitor of aberrant glycosylation in various cancer cells, including breast cancer, gastric cancer, and pancreatic cancer, parallel with inhibition of cancer cell growth and progression of tumors. Thus, TM can be considered a potent antitumor drug in various cancers and may promote chemosensitivity. Mechanistically, TM impedes the role of the UDP-HexNAc enzyme in the biosynthesis of oligosaccharides, specialized macromolecules instrumental in N-linked glycosylation. Further, like chemotherapies such as doxorubicin (DOX), 5'fluorouracil, etoposide, and Cisplatin, TM induces the unfolded protein response (UPR) by blocking aberrant glycosylation. Despite TM's antitumor effectiveness, its lack of cell-type specific cytotoxicity impedes its anticancer efficacy. Thus, various nanoencapsulation techniques and materials have been considered for use in experiments to reduce TM's cytotoxicity and improve efficacy as a targeted therapy. The current review is a profound audit of the benefits and pitfalls of TM in various cancers, focusing on breast, colon, and pancreatic cancers. Additional progressive studies have also discussed the use of TM in immune checkpoints and other unique pathways. Cytotoxicity and other possibly adverse effects of TM are highlighted based on the data from in vitro and in vivo assays. In addition, the recent advances in nano-based drug delivery systems regarding TM have been emphasized. However, the potential of this nucleoside inhibitor re-quires thorough investigation and research to determine its likeliness as a viable chemotherapeutic.

The precise mathematical description of gaze patterns is still an unsettled matter of debate. This can, consequently, affect the analysis of this type of data in its practical applications. In this scope, we show evidence that a Lévy-flight description of eye-gaze trajectories is not only appropriate but its scale invariant properties are remarkably useful to assist in diagnosing children with Attention Deficit and Hyperactivity Disorder (ADHD), alongside with the usual cognitive tests. Using this picture, we find that the distribution of the characteristic exponent of Lévy-flights statistically is different in children with ADHD. Furthermore, we observe that these children deviate from a strategy that is considered optimal for searching processes, in contrast to non-ADHD children. We focus on the case where both eye-tracking data and data from a cognitive test are present and show that the study of gaze patterns in children with ADHD can help in identifying this condition. Since eye-tracking data can be gathered during cognitive tests without needing extra time-consuming specific tasks, we argue that it is in prime position to provide assistance in the arduous task of ADHD diagnosing.

Porcine epidemic diarrhea virus (PEDV) has affected the pork industry worldwide and during outbreaks the mortality of piglets has reached 100%. Lipid nanocarriers are commonly used in the development of immunostimulatory particles due to their biocompatibility and slow-release delivery properties. In this study, we developed a lipid nanoparticle (LNP) complex based on glycyrrhizinic acid (GA) and tested its efficacy as an adjuvant in mice immunized with the recombinant N-terminal domain (NTD) of porcine epidemic diarrhea virus (PEDV) spike (S) protein (rNTD-S). The dispersion stability analysis (Z-potential–27.6 mV) confirmed the size and charge stability of the LNP-GA, demonstrating that the particles were homogeneously dispersed and strongly anionic, that favors nanoparticles binding with the rNTD-S protein, which showed a slightly positive charge (2.11 mV) by in silico analysis. TEM image of LNP-GA revealed nanostructures with a spherical-bilayer lipid vesicle (⁓100 nm). The immunogenicity of the LNP-GA-rNTD-S complex induced an efficient humoral response 14 days after the first immunization (P &lt; 0.05) as well as an influence on the cellular immune response by decreasing serum TNF-α and IL-1β concentrations, which was associated with an anti-inflammatory effect.

Drones are being used more and more frequently and in various ways to attack people and critical infrastructures, which increases their level of danger and makes early detection and risk assessment even more difficult. There is no ultimate drone sensor. Rather, drones can only be effectively detected, if suitable sensor technologies are integrated within a system. Among the best suited sensorics for this purpose are radar and optical sensors, because the advantage of the radar, given by the long detection range, can be well combined with the additional visual-based information gained from a camera in the mid- and short-range, where usually the radar fails detecting micro drones. In this paper, a modular drone detection and assistance system MODEAS is presented, which can be used to automatically detect and track drones within a range up to some kilometers on the sky, but also in complex urban environments, where buildings and vegetation offer a perfect background for camouflage. The system provides an early detection of flying objects as potential drones, when those are not at all or only as small dots visible for the human eye. Main strengths of the system are the robust AI detection to differentiate such an object against clutter (birds, clouds) and its further classification by model and payload recognition, the latter aspect being considered as an indication of dangerousness. Moreover, once a drone is detected, the system follows it automatically, precisely and smoothly with a high-resolution pan-tilt-camera, measuring the distance to the sensor station with a laser rangefinder, compute the geocoordinates and visualize them live on a map. To improve the precision of the detection, a multisensorial fusion of all sensor detections is performed. Furthermore, alarms may be generated when a drone enters a restricted area.

Background: The variability of the obtained results of manual tests assessing the angle of strabismus depends on the experience, skills, and training of the examiner. The authors hope that the new measuring device will provide a more sensitive and repeatable method for detecting small strabismus angles compared to the gold standard – PCT. The purpose of this article is to present an innovative strabismus angle demonstration device, called Strabiscan, to present automated measurements of eye deviation, and to compare the obtained results of these measurements to the traditional manual method. Methods: In patients with the manifest strabismic disease (n = 30) and a group of healthy subjects (n = 30), a detailed history was taken and routine ophthalmologic examinations were performed, including best-corrected distance visual acuity, assessment of refractive error using an autorefractometer after cycloplegia, biomicroscopic evaluation of the anterior segment of the eye, and evaluation of the eye fundus by indirect ophthalmoscopy. Subsequently, each patient and healthy subjects were subjected to a prismatic cover-uncover test using a manual method, and then the presence of strabismus was detected and its angle assessed using demonstration Strabiscan device. Results: In the control group, using the Strabiscan demonstration device, small-angle latent strabismus ≤3DP was diagnosed in 83% of patients, and >3DP in 13%. In contrast, using the prismatic cover-uncover test, latent strabismus ≤3DP was diagnosed in only 13% of patients, and latent strabismus with an angle >3DP in 13% of patients. No statistically significant differences were noted in the measurements of strabismus angles made by the different methods. Conclusions: The Strabiscan demonstration device allows quick and accurate assessment of the strabismus angle. Compared to the prismatic cover-uncover test, it has a higher sensitivity for detecting low-angle latent strabismus. Measurements with the Strabiscan do not require the presence of additional co-assistants for the test.

To address the trajectory tracking issue for quadrotors working under the influence of external disturbances, a control scheme is designed for position and attitude trajectory tracking. Firstly, the quadrotor dynamic model is derived for control design. Secondly, adaptive integral backstepping control (AIBS) is employed in the position loop in which adaptive estimation is used to estimate the upper bounds of disturbances. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) is proposed to follow desired Euler angles. The intro-duction of fast nonsingular terminal sliding mode and integral element is to realize fast convergence and accurate tracking. Dead zone technique is applied to minimize estimation errors. Besides, a saturation function is utilized to eliminate chattering phenomenon. Finally, simulation experiments are conducted under the Simulink environment. The proposed control is verified by comparing it with traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS).

Glioblastoma multiforme (GBM) is a glioma and the most aggressive type of brain tumor with a dismal average survival time, despite the standard of care. One promising alternative therapy is boron neutron capture therapy (BNCT), which is a noninvasive therapy for treating locally invasive malignant tumors, including glioma. BNCT involves boron-10-released radiation directly into tumor cells with minimal damage to healthy tissues. This therapy lacks clinically approved targeted blood-brain-barrier-permeating delivery vehicles for therapeutic drug/ boron-10. Nanoparticles, particularly gold nanoparticles (GNPs), are selective and effective drug-delivery vehicles because of their desirable properties, facile synthesis, and biocompatibility. This review discusses historical and current GNP therapeutic applications as a drug delivery vehicle for treating glioma. Furthermore, GNPs loaded with therapeutic drugs, imaging agents, and GBM-targeting antibodies/ peptides to treat GBM will be discussed. Additionally, the importance of upper and lower limits on therapeutic efficacy will be described and explored followed by highlighting their advantages, limitations, and possible toxicity. Recent research and selected important findings for GNP-mediated pharmaceutics in GBM will also be considered.

Radio techniques are widely used in wildlife tracking. Currently, the most common tracking methods include radio tracking (operating on VHF and UHF frequencies), satellite tracking (e.g., Argos satellite Doppler-based positioning system), and Global Navigation Satellite System (GNSS) tracking. One of the radio tracking systems is the Radio-Frequency Identification (RFID) system, characterized by small dimensions and a long operational period due to energy-efficient features. The advantages of RFID make it possible to apply this technique to track oak acorns in the process of zoochoric dispersal. In our study, we explored the potential applications of RFID systems for monitoring the dispersal of oak acorns. We developed a tracking system based on a semi-passive RFID tag, which we tested under laboratory and quasi-realistic conditions. The obtained results confirm the feasibility of using our system in radio tracking small objects such as oak acorns.

Surfactants are widely used in the synthesis of nanoparticles, as they have a remarkable ability to direct their growth to obtain well-defined shapes and sizes. However, their post-synthesis removal is a challenge, and the methods used often result in morphological changes that defeat the purpose of the initial controlled growth. The cleaning methods could be classified as thermal or non-thermal. In general, the structure of materials can be better preserved by non-thermal treatments. After the removal of surfactants, the highly active surfaces of nanomaterials may undergo structural reconstruction by exposure to a different environment. Thus, ex situ characterization after air exposure may not reflect the effect of the cleaning methods. In situ characterization is required to better understand the impact of various cleaning procedures. Combining X-ray photoelectron spectroscopy, in situ infrared reflection absorption spectroscopy, and environmental transmission electron microscopy measurements with CO probe experiments, we investigated different surfactant-removal methods to produce clean metallic Pt nanoparticles from surfactant-encapsulated ones. Non-thermal plasmas show the best results. It was demonstrated that both UV-ozone treatment and room temperature O2 plasma treatment lead to the formation of Pt oxides on the surface after the removal of the surfactant. These oxides are reduced to metallic Pt during in situ CO probe experiments. On the other hand, when H2 was used for plasma treatment, the Pt0 oxidation state and nanoparticle size distribution were preserved. In addition, H2 plasma treatment can reduce Pt oxides after O2-based treatments, resulting in metallic nanoparticles with clean surfaces. Thermal reduction in hydrogen leads to carbon species emerging onto nanoparticle surfaces after heating and agglomeration of Pt nanoparticles. Particularly, O2-based thermal treatments result in the formation of aggregates consisting of small nanoparticles. These findings provide a better understanding of the various options for surfactant removal from metal nanoparticles and point toward non-thermal plasmas as the best route if the integrity of the nanoparticle needs to be preserved.

The traditional receiver employs scalar tracking loops, resulting in degraded navigation performance in weak signal and high dynamic scenarios. An innovative design of a vector tracking receiver based on nonlinear Kalman filter (KF) tracking loops is proposed in this paper, which combines the strengths of both vector tracking and KF tracking loops. Firstly, a comprehensive description of the vector tracking receiver model is presented, and unscented Kalman filter (UKF) is applied to nonlinear tracking loop. Secondly, to enhance the stability and robustness of the KF tracking loop, we introduce square root filtering and an adaptive mechanism. The tracking loop based on square root UKF (SRUKF) can dynamically adjust its filtering parameters based on signal noise and feedback Doppler error. Finally, the proposed method is implemented on a software-defined receiver (SDR), and the field vehicle experiment demonstrates the superiority of this method over other receivers in complex dynamic environments.

Silica nanoparticles synthesized solely from organosilanes naturally possess a greater number of organic functionalities than silica nanoparticles surface modified with organosilanes. We report the synthesis of organically modified silica (ORMOSIL) nanoparticles with mesoporous and surface rough morphology and with high surface area, made solely from vinyltrimethoxy silane. We chemically modified these vinyl silica nanoparticles using bromination and hydroboration, and demonstrated the high accessibility and reactivity of the vinyl groups with an ~85% conversion of the functional groups for bromination of both particle types, a ~60% conversion of the functional groups for hydroboration of surface rough particles and a 90% conversion of the functional groups for hydroboration of mesoporous particles. We determined that the mesoporous vinyl silica nanopar-ticles, while having a surface area that lies between the non-porous and surface rough vinyl silica nanoparticles, provide the greatest accessibility to the vinyl groups for boronation and allow in-corporating up to 3.1 × 106 B atoms per particle, making the resulting materials attractive for boron neutron capture therapy.

Background: Multiple drug delivery systems obtained by loading nanoparticles (NPs) with different drugs with different physicochemical properties present a promising strategy to achieve synergistic effects between drugs or overcome undesired effects. This study aims to develop a new NP by loading Quercetin (Que) and valproic acid (VPA) onto chitosan. In this context, our study investigated the antioxidant activities of chitosan NPs loaded with single and dual drugs containing Que against oxidative stress. Method: The synthesis of single (Que or VPA) and dual-drug (Que and VPA) loaded chitosan NPs, characterization of the NPs, conducting in vitro antioxidant activity studies, and analysis of the cytotoxicity and antioxidant activity of the NPs in SH-SY5Y cell lines were performed. Result: The NP applications that protected cell viability to the greatest extent against H2O2-induced cell damage were, respectively, 96 µg/ml of Que-loaded chitosan NP (77.30%, 48 h), 2 µg/ml of VPA-loaded chitosan NP (70.06%, 24 h), 96 µg/ml of blank chitosan NP (68.31%, 48 h), and 2 µg/ml of Que and VPA-loaded chitosan NP (66.03%, 24 h). Conclusion: Our study establishes a successful paradigm in developing drug-loaded NPs, with uniform and homogeneous distribution of drugs onto NPs. Chitosan NPs loaded with both single and dual drugs possessing antioxidant activity were successfully developed.

Due to their wide range of uses in modern technology, nanomaterial’s of silver metallic (Ag-NPs) have engaged considerable concern, driving significant research with development efforts. This study focuses on investigating the antimicrobial properties of Ag-NPs, encompassing their production, characterization, and biological aspects. The eco-friendly extracellular biosynthetic method employed in this work utilized extracts from the marine fungus Aspergillus flavus MK4 as reducing agents for nanoparticle synthesis. Analyzing the colloidal Ag-NPs using UV-visible spectroscopy revealed a peak in absorbance at 460 nm, indicating the presence of plasmonic properties. The electrons imaging of internal structure (TEM) elucidated spherical shape of the Ag-NPs by 15 nm size. Testing against bacterial diversities (Gr-ve & Gr+ve) revealed potent antibacterial and antifungal efficacy. Cytotoxicity versus HepG-2 cell line was assessed using the MTT assay, and antioxidant properties were examined through the radical scavenging (DPPH) assay. In wise of their conceivable applications in the fields of antibacterial, anticancer, and wound-healing, the Ag-NPs that were synthesized exhibit promising features. With its powerful ability to synthesize silver nanoparticles (Ag-NP), Aspergillus flavus MK4 Aspergillus flavus MK4 can generate nanoparticles extensively characterized, demonstrating their antibacterial, antioxidant, anticancer, and wound-healing properties.

Moving object detection plays a crucial role in various applications, particularly in traffic surveillance and collision warning systems. However, the high cost of training and slow detection pose significant challenges to the practicality and real-time performance of existing methods. These challenges hinder the practicality and real-time performance of existing methods. The need for a reliable and efficient moving object detection system prompts the search for cost-effective strategies. Enhancing detection speed without sacrificing accuracy is crucial for real-time applications. Overcoming these challenges is essential to advance the field of moving object detection and improve its applicability in various domains. This paper presents a comprehensive review of the literature on moving object detection, proposes novel strategies to overcome the challenges of high training costs and slow detection. The study emphasizes the importance of reliable speed monitoring systems and advancements in control systems to enhance driver assistance on urban highways. Each frame in the dataset undergoes YOLOv6 processing to detect and classify objects, generating bounding box predictions and class probabilities. Optical flow, specifically the Lucas-Kanade method, is then utilized to compute motion vectors between consecutive frames. These motion vectors facilitate object tracking across frames, enabling refined bounding box positions and improving overall object tracking accuracy. The results demonstrate the effectiveness of the proposed technique in reducing training costs, improving detection speed, and maintaining a high level of accuracy when compared to existing methods. The paper concludes by summarizing the findings and highlighting the potential of the proposed strategy for precise and reliable moving object recognition in real-world traffic scenarios

Nano-drugs and nano-delivery systems are rapidly evolving, with new strategies emerging in the current practices. The evolution of these technologies began with modifying the chemical structure, progressing to supramolecular ionic complexes, and culminating in elegant ad hoc delivery systems. Nanoparticles have numerous benefits as a carrier system for delivering therapeutic agents to intra-arterial sites. These benefits include their subcellular size, targeted surfaces, good suspensibility, and uniform dispersity, making them an ideal choice for catheter-based delivery. Despite the advancements made in the field of nano-drugs and nano-delivery systems, there are still some hurdles to overcome in terms of their commercial availability.The current review presents an updated summary of recent advancements in nano-drugs and nano-delivery systems, including their commercial availability. We aim to discuss the present challenges and prospects of commercially available nano-drugs and nano-delivery systems. Here, we provide a precise and informative overview of the current state of these technologies and underscore the potential they hold for future developments. Further, we have categorized commercially available modifications, name, parent company and their main applications in nano-drugs.

Drones have been used in a variety of scenarios such as atmospheric monitoring, fire rescue, agricultural irrigation, etc., in which accurate environmental perception is of crucial importance for both decision-making and control. Among the drone sensors, the RGB camera is indispensable for capturing rich visual information for vehicle navigation but encounters a grand challenge in high-dynamic-range scenes that occur frequently in real applications. Specifically, the recorded frames suffer from under-exposure and over-exposure simultaneously and degenerate the successive vision tasks. To solve the problem, we take object tracking as an example and leverage the superior response of event cameras over a large intensity range to propose an event-assisted object tracking algorithm that can achieve reliable tracking under large intensity variations. Specifically, we propose to pursue feature matching from dense event signals, and based on which to (i) design a UNet-based image enhancement algorithm to balance the RGB intensity with the help of neighboring frames in the time domain, and then (ii) construct a dual-input tracking model to track the moving objects from intensity balanced RGB video and event sequence. The proposed approach is comprehensively validated in both simulation and real experiments.

The agricultural industry places a high priority on crop protection, especially when it comes to protecting cotton crops against pink bollworm infestations. Rapid disease identification is essential for effective crop management at the same time. In order to overcome these difficulties, this study offers a thorough process for utilizing the Robot Operating System (ROS) to deploy an autonomous robot. The robot is intended to identify infestations of pink bollworm in addition to counting and tracking red Disease that impact cotton harvests. Drones are used to check the condition of cotton fields, and the autonomous robot's path planning component is closely related to this process. Large fields are photographed by these drones in multispectral mode, and the robot's course planning technique is done by calculating the Normalized Difference Vegetation Index (NDVI) based on these images. This approach ensures targeted surveillance and intervention, optimizing the use of resources. A customized dataset was created especially for this application to improve the robot's detecting abilities. The dataset was utilized to train a YOLOV8 model, a state-of-the-art object detection architecture. Performance characteristics of the trained model are impressive; it has a mean Average Precision (mAP) of 67.1%, Precision of 67.9%, and Recall of 61.8%. These metrics highlight how well the model works to precisely locate and measure interesting occurrences in the cotton fields. In order to address the particular challenges presented by pink bollworm infestations and crop diseases in the context of cotton cultivation, this research contributes a comprehensive solution for autonomous crop monitoring and protection by seamlessly integrating ROS, drones, NDVI calculations, and a robust detection model.

Green synthesis using plant extracts has emerged as an eco-friendly, clean, and viable strategy alternative to chemical and physical approaches. The leaf, stem, and root extracts of Lannea discolor was utilized as a reducing and stabilizing agent in the synthesis of gold (AuNPs) and copper (CuNPs) nanoparticles. The formation of AuNPs and CuNPs confirmed by their color change, was characterised by UV–Vis Spectroscopy (UV- Vis), Scanning electron microscopy analysis and energy dispersive x-ray (SEM-EDX), Transmission Electron Microscopy (TEM), and Fourier Transform Infrared Spectroscopy (FTIR), coupled with minimum concentration inhibitory (MIC) antibacterial assays. AuNFs, NPs and CuNPs peaked at wavelengths in the ranges of 316, 544 and 564 nm respectively. TEM showed unexpected nanoflowers (30 – 97 nm) in the leaf extracts and spherical NPs (10 -33 nm; 9.3 – 37.5) from stem and root extracts, while spherical CuNPs (20 – 104 nm), were observed from all the extracts. EDX was able to confirm the presence of metal salts and FTIR revealed stable capping agents. AuNPs and NFs from L. discolor extracts showed appreciable antibacterial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae and Bacillus subtilis, when compared to the plant extracts, while none was observed from the CuNPs. These AuNPs and CuNPs are particularly appealing in a variety of applications in the biomedical as well as conductivity manufacturing, due to their shapes and sizes and economical and environmentally friendly production.

Hybrid materials derived adsorbents have showed a great applicable efficiency in various fields including industrial uses and environmental remediation. Herein, the zinc oxide nanoparticles anchored carbon (ZnO-C) is fabricated and utilized for wastewater treatment by adsorption of Zn(II), Cd(II), Co(II) and Mn(II). The surface and structural characteristics are examined by TEM, SEM, XRD, FTIR, EDS and BET surface area. The Kinetics and equilibrium investigations are applied to optimize the adsorptive removal of Zn(II), Cd(II), Co(II) and Mn(II) onto ZnO-C. Results indicated formation of ZnO-C in crystalline spherical granules with nano-size between 29.3 and 48.8 nm. In addition, the spherical granules are gathered to form clusters. The FTIR indicated that the ZnO-C surface is rich with OH groups and ZnO. The adsorption capacity is reported as 212, 209, 200 and 230 mg/L for Zn(II), Cd(II), Co(II) and Mn(II) respectively. The optimum condition for maximum adsorption were pH between 5 and 6, contact time of 180 min and adsorbent dose of 0.1 g/L. The adsorptive removal data modeling for uptake of Zn(II), Cd(II), Co(II) and Mn(II) onto ZnO-C showed agreement with the assumption of pseudo 2nd order kinetic model and Freundlich isotherm suggesting fast adsorption rate and multilayer mechanism. The achieved adsorption capacity using the prepared ZnO-C is more effective compared to ZnO, carbon, Fe3O4 and Fe3O4-C. Real wastewater samples are applied including valley water, industrial wastewater and rain wastewater and evaluated for applicable uptake of Zn(II), Cd(II), Co(II) and Mn(II) using ZnO-C and Fe3O4-C with high efficiency.

Mild Cognitive Impairment (MCI) may progress to severe forms of dementia, so therapy is needed to maintain cognitive abilities. The neural circuitry for oculomotor control is closely linked to that which controls cognitive behavior. In this study, we tested whether training the oculomotor system with gaze-controlled video games could improve cognitive behavior in MCI patients. Patients played a simple game for a month while a control group played the same game using a mouse. Cognitive improvement was assessed using the MoCA screening test and CANTAB. We also measured eye pupil and vergence responses in an oddball paradigm. The results showed an increased score on the MoCA test specifically for the visuospatial domain and on the Rapid Visual Information Processing test of the CANTAB battery. Pupil responses also increased to target stimuli. Patients in the control group did not show significant improvements. This pilot study provides evidence for the potential cognitive benefits of gaze-controlled gaming in MCI patients.

Our previous research provides evidence that vergence eye movements may significantly influence cognitive processing and could serve as a reliable measure of cognitive issues. The rise of consumer-grade eye tracking technology, which uses sophisticated imaging techniques in the visible light spectrum to determine gaze position, is noteworthy. In our study, we explored the feasibility of using webcam-based eye tracking to monitor the vergence eye movements of patients with Mild Cognitive Impairment (MCI) during a visual oddball paradigm. We simultaneously recorded eye positions using a remote infrared-based pupil eye tracker. Both tracking methods demonstrated more pronounced cognitive vergence responses for targets as opposed to distractors. In summary, the use of a consumer-grade webcam to record cognitive vergence shows potential. This method could potentially lay the groundwork for future research aimed at creating an affordable screening tool for mental health care.

Intelligent ship technology is currently an international research hotspot, and model predictive control is widely used in the path-tracking control of intelligent vehicles. To construct an intelligent ship anti-disturbance path-tracking control method, firstly, an environmental disturbance model was constructed with the actual meteorological data of the target sea area. Secondly, the Fossen ship equation of motion is linearized and discretized as the ship motion model. Thirdly, the expression of the prediction equation is derived from the ship motion model. Fourthly, the cost function is constructed by using the polar diameter and polar angle values of the ship. Fifth, the power function in the cost function is replaced with an exponential function to obtain an improved cost function. Sixthly, according to the Lyapunov theory and the MPC terminal constraint theory, the stability of the improved cost function is verified. Seventh, different test paths are set up, the environmental disturbance model is taken as the external disturbance, the ship motion model, the prediction equation, and the improved cost function are used to design the anti-disturbance path-tracking control algorithm according to the model prediction control idea for simulation experiments. Finally, different MATLAB simulation results show that the improved cost function can resist disturbance of the external wave, current, and wind, and effectively track the target path. Therefore, this study provides a reference for improving the navigation safety of ship path-tracking.

High-throughput research on bimetallic nanoparticles brought a vast overview of their characteristics and catalytic activities.¹ However, traditional bimetallic nano-allloy quantification methods serving catalyst preparations are not suitable for the fast and robust data output of high-throughput experiments. Hence, this work designed and validated a more fast, more neat, and reliable quantitative analysis using X-ray fluorescence spectroscopy for bimetallic nanoparticles synthesized by high-throughput setups. The results demonstrated this method to be accurate with high precision. Furthermore, the agreement to qualitative results from an energy-dispersive X-ray spectrometer equiped on a scanning electron microscope provided an option to quantify a bimetallic nano-alloy by just analyzing one of the two composing elements. Thus, this method is proved to be highly compatible with high-throughput experiments.

Abstract: Composite sintered bodies comprising silicon dioxide (SiO2) nanoparticles dispersed in β-tricalcium phosphate (β-TCP) were prepared. The addition of nano-sized colloidal SiO2 to the β-TCP produced well-dispersed secondary phase nanoparticles that promoted densification by suppressing grain growth and increasing volume shrinkage of the sintered bodies. The SiO2 was found not to react with the β-TCP at 1120 °C and the substitution of silicon for phosphorous to produce a solid solution did not occur. This lack of a reaction is ascribed to the absence of avail-able calcium ions to compensate for the increase in charge associated with this substitution. The SiO2 nanoparticles were found to be present near the intersections of grain boundaries in the β-TCP. A β-TCP composite sintered body containing 4.0 wt% SiO2 exhibited a bending strength comparable to that of cortical bone and hence could potentially be used as a bone filling material.

In the field of maneuvering target tracking, the combined observations of azimuth and Doppler may cause weak observation or non-observation in the application of traditional target tracking algorithms. Additionally, traditional target-tracking algorithms require pre-defined multiple mathematical models to accurately capture the complex motion states of targets, while model mismatch and unavoidable measurement noise lead to significant errors in target state prediction. To address those above challenges, in recent years, the target-tracking algorithms based on neural networks, such as recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and Transformer architectures, have been widely used for their unique advantages to achieve accurate predictions. To better model the nonlinear relationship between the observation time series and the target state time series, as well as the contextual relationship among time series points, we present a deep learning algorithm called recursive downsample-convolve-interact neural network (RDCINN) based on convolutional neural network (CNN) that downsamples time series into sub-sequences and extracts multi-resolution features to enable the modeling of complex relationships between time series, which overcomes the shortcomings of traditional target-tracking algorithms in using observation information inefficiently due to weak observation or non-observation. The experimental results show that our algorithm outperforms other existing algorithms in the scenario of strong maneuvering target tracking with the combined observations of azimuth and Doppler.

Plasmonic nanocomposites have the ability to enhance light-matter interaction due to the plasmonic effects leading to promising potential applications. In this paper, we theoretically study the group index of the silver nanoparticle-gold nanoparticle-quantum dot plasmonic hybrid system in the optical region of the electromagnetic spectrum using the density matrix approach. The quantum dot is considered to be a three-level atomic system of a lambda configuration, interacting with strong control and weak probe fields. We find that the plasmonic hybrid system exhibits at near resonance a strong switching between slow and fast light, which can be controlled by the inclination angle of the gold nanoparticle and the size of the metals nanoparticles, in addition to the strength and detuning of the control field. Thus, the silver nanoparticle-gold nanoparticle-quantum dot could potentially be used in optoelectronic devices.

The Ce0.5Y0.35Tb0.15F3 nanoparticles with CeF3 hexagonal structure were synthesized by co-precipitation technique. The average nanoparticle diameter was 14±1 nm. The luminescence decay curves of Ce0.5Y0.35Tb0.15F3 nanoparticles (λem = 541 nm, 5D4 – 7F5 transition of Tb3+) conjugated with Radachlorin by means of polyvinylpyrrolidone coating as well as without Radachlorin were detected. Efficient nonradiative energy transfer from Tb3+ to the Radachlorin was demonstrated. The maximum energy transfer coefficient for nanoparticles conjugated with Radachlorin via polyvinylpyrrolidone and without the coating were 82% and 55%, respectively. The average distance between nanoparticle surface and Radachlorin was R0 =4.5 nm. The best results for X-ray induced cytotoxicity was observed for NP-PVP-Rch sample at the lowest Rch concentration. In particular, after X-ray irradiation the survival A 549 human lung carcinoma cells decreased by ~12%.

A scientific investigation into visual preferences of rural recreation path landscapes is crucial for enhancing visual qualities and visitors' experience. Taking Baofeng, a representative traditional village in Yunlong, as an example, this study analyzed the visual preference of three typical linear recreational paths with different landscape attributes. We used eye-tracking technology to collect eye movement data and conducted a subjective semantic differential evaluation. Our findings manifest a general inclination amongst individuals to favor closer views and paths with clear trajectories and rich elevation changes while walking, despite preference differences on different types of paths. Regarding group diversity, more inclusive design should be made to meet the sensory needs of different groups. Moreover, despite the limited level of correlation between subjective and objective evaluation methods, combining these two approaches remains indispensable. This synthesis advances prior quantitative landscape evaluation with a specific focus on rural path landscapes and upholds the integrity of results by combining objectivity with subjectivity. It also provides relevant design suggestions for further rural renewal and path planning of Baofeng village.

: 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.

Multi-Object Tracking (MOT) is a key technology for Unmanned Aerial Vehicles (UAVs). Traditional tracking-by-detection methods firstly employ an object detector to retrieve targets in each image and then track them based on a matching algorithm. Recently, the popular multi-task learning methods has been dominating this area since they can detect targets and extract Re-Identification (Re-ID) features in a computationally efficient way. However, the detection task and the tracking task have conflicting requirements on image features, leading to the poor performance of the joint learning model compared to separate detection and tracking methods. The problem is more severe when it comes to UAV images due to the presence of irregular motion of large number of small targets. In this paper, we propose a balanced Joint Detection and Re-ID learning (JDR) network to address the MOT problem in UAV vision. To better handle the non-uniform motion of objects in UAV videos, the Set-Member Filter is applied which describes object state as a bounded set. An appearance matching cascade is then proposed based on target state set. Furthermore, a Motion-Mutation module is designed to address the challenges posed by the abrupt motion of UAV. Extensive experiments on the VisDrone-MOT2019 dataset demonstrate that our proposed model, termed as SMFMOT, outperforms state-of-the-arts by a large margin and achieves superior performance on the MOT tasks in UAV videos.

This work focuses on addressing the dynamic positioning and trajectory tracking problem for a 4 degree-of-freedom (DOF) unmanned underwater vehicle (UUV) in the presence of nonlinear dynamics, parametric uncertainties, system constraints, and time-varying external disturbances. To tackle this problem, a disturbance observer-based control (DOBC) scheme is proposed. The scheme is structured around the model predictive control (MPC) method integrated with an extended active observer (EAOB). Compared to the conventional disturbance observer, the EAOB has the unique ability to handle both external disturbances and system/measurement noises simultaneously. The EAOB leverages a combination of sensor measurements and a system dynamic model to estimate disturbances in real-time, which allows continuous estimation and compensation of time-varying disturbances back to the controller. The proposed disturbance observer-based MPC (DOBMPC) is implemented by feeding the estimated disturbances back into the MPC’s prediction model, which forms a robust adaptive controller with a parameter-varying model. The proposed control strategy is validated through simulations in a Gazebo and Robot Operating System (ROS) environment. The results show that it can effectively reject unpredictable disturbances and improve the UUV’s control performance.

In this article, copper(II) oxide and titanium dioxide nanoparticles were added to Group III base oil formulated with 8 wt% Komad 323 dispersant. The nanoparticles were treated with ethyl oleate surface modification. The tribological properties of the homogenized oil samples were tested on a linear oscillating tribometer with continuous monitoring of static friction. Friction absolute integral values were calculated from high data acquisition. The wear was evaluated using a digital optical and confocal microscope. The wear types were characterized with scanning electron microscopy, while the remaining additives were located and quantified with energy-dispersive X-ray spectroscopy. The measurement results show that the CuO nanoparticles did not work well with the Komad 323 dispersant. As a result of their antagonistic effect, in the case of low CuO concentrations (≤0.3 wt%), the friction increased, while in the case of high concentrations (≥0.4%), surface fatigue caused a high wear rate. The cooperation between TiO2 and the dispersant showed synergistic effects. The oxygen-rich boundary layer formed on the worn surface with a titanium content of 0.33-0.39 norm.wt% provides both lower friction and high wear resistance.

Background: We investigated the effect of bioactive glass and zinc oxide nanoparticles on enamel remineralization, as well as their antibacterial effect on cariogenic bacteria. Methods: Fluoride gel (F), bioactive glass microparticles (µB), bioactive glass nanoparticles (nB), zinc oxide nanoparticles (Z), and a mixed suspension of nB and Z (nBZ) were prepared and subjected to the following tests: morphological evaluation by scanning and transmission electron microscopy, measurement of specific surface area, zeta potential measurement, crystal structure analysis by X-ray diffraction, and acid buffering capacity test. Further, we performed a remineralization cycle test of 28 days and a nanoindentation testing was carried out during the immersion period and then the enamel surfaces were examined using scanning electron microscopy. Additionally, the antibacterial effects of the sample suspensions were evaluated by measuring their minimum bactericidal concentrations against various cariogenic bacteria. Results: Our results revealed that nB had a near-circular shape with an amorphous structure, a considerably large specific surface area due to nanoparticulation. Additionally, nB possessed a rapid acid buffering capacity, which was comparable to that of μB. In the remineralization test, faster recovery of mechanical properties was observed on the enamel surface immersed in samples containing bioactive glass nanoparticles (nB and nBZ). After remineralization, demineralized enamel immersed in any of the samples showed a rough and porous surface structure covered with mineralized structures. Furthermore, nBZ exhibited a broad antibacterial spectrum. Conclusions: These results demonstrated that bioactive glass and zinc oxide nanoparticles have superior demineralization-suppressing and remineralization-promoting effects.

In recent years, the use of long-term seismic monitoring systems for the protection of structures is becoming increasingly widespread. This is because more and more awareness is gradually developing regarding the importance of keeping structures under observation so as to prevent any damage scenarios. Within the field of Structural Health Monitoring, data driven techniques allow to process and analyze data collected on site. This paper presents a Mode Tracking procedure to obtain the time-histories of the natural frequencies of a monumental structure. The procedure is applied on the Sanctuary of Vicoforte, an important monumental structure site in Piedmont known for its imposing oval dome and characterized by a permanent structural monitoring system. Through the procedure presented in the paper it has been possible to obtain and observe the time series of the first natural frequencies of the structure considering various aspects, including the temperature variation.

We define a spinor-Minkowski metric for SL(4,C). It is not a trivial generalization of the SL(2,C) metric and it involves the Minkowskian one. We define 4x4 version of the Pauli matrices and eight 4-component associated generalized eigenvectors that can be regarded as undotted covariant spinors. The 4-component spinors can be grouped into four categories. Each category transforms in its own way. The outer products of pairwise combinations of 4-component spinors can be associated with 4-vectors. Including the dotted covariant, undotted and dotted contravariant forms totally we have sixteen pairs of spinors. Eight of them live in the conjugate space which has no countepart in SL(2,C).

The creation of mitochondria-targeted vector systems is a new tool for the treatment of socially significant diseases. Phosphonium groups provide targeted delivery of drugs through biological barriers to organelles. For this purpose, a new class of alkyl(diethylamino)(phenyl) phosphonium iodides (bromides) 1 containing one, two, or three diethylamino groups were obtained by the reaction of alkyl iodides (bromides) with (diethylamino)(phenyl)phosphines under mild conditions and high yields. The structure of compounds 1 was established by NMR and XRD. In vitro a high cytotoxicity against the lines M-Hela, HuTu 80, PC3, DU-145, PANC-1 and MCF-7 was found. Selectivity index are in the range of 0.06-4.0 M (SI 17-277) for the most active compounds. ROS production, mitochondrial localization and the process of cellular apoptosis were investigated. Decorated by 1 of lipid systems (liposomes and solid lipid nanoparticles) improve the cytotoxicity and a decrease in toxicity against normal cell lines. Compounds 1 induce apoptosis proceeding along the mitochondrial pathway. Aminophosphonium salts 1 also exhibit a high selective activity against the Gram-positive bacteria strains S. aureus 209P, B. segeus 8035, including methicillin-resistant strains of S. aureus (MRSA-1, MRSA-2), comparable to the activity of the fluoroquinolone antibiotic norfloxacin. A moderate in vivo toxicity in CD-1 mice was established for the lead compounds.

In recent years, the field of drug delivery has seen a significant shift towards the exploration and utilisation of nanoparticles (NPs) as versatile carriers for therapeutic agents. With its ability to provide exact control over NPs' characteristics, microfluidics has emerged as a potent platform for the efficient and controlled synthesis of NPs. Microfluidic devices designed for precise fluid ma-nipulation at the micro-scale offer a unique platform for tailoring NP properties, enabling en-hanced control over NP properties such as size, morphology and size distribution while ensuring high batch-to-batch reproducibility. Microfluidics can be used to produce liposomes, solid lipid nanoparticles, polymer-based NPs and lipid-polymer hybrid NPs, as well as a variety of inorganic NPs such as silica, metal, metal oxide, quantum dots and carbon-based NPs, offering precise control over composition and surface properties. Its unique precision in tailoring NP properties holds great promise for advancing NP-based drug delivery systems in both clinical and industrial set-tings. Although challenges with large-scale production still remain, microfluidics offers a trans-formative approach to NP synthesis. In this review, starting from the historical development of microfluidic systems, the materials used to create the systems, microfabrication methods and system components will be discussed in order to provide the reader with an overview of micro-fluidic systems. In the following, studies on the fabrication of nanoparticles such as lipid NPs, polymeric NPs and inorganic NPs in microfluidic devices are included.

At this time, nanoparticles used to been considered for various biomedical applications due to their particular properties[1, 2]. It is already known that one of the major advances in the relative application of nanoparticles is the recognition of the steric stabilization which can increase the particle stability in the biological environment and provide the opportunities of the application of nanoparticles in the development of drug delivery systems (DDSs) for achieving drug targeting and controlled drug release. Nano crystalline silver particles (AgNPs) have major applications in biomolecular recognition of highly sensitive, anti-microbial treatment, catalysis and manufacture sensors [3-7]. The NPs for various applications medical like image quality, medicine, tissue, magnetic resonance imaging (MRI) of targeting tissues and cells styles. This is particularly the case of AgNPs significantly encompasses the whole a wide range of industrial and medical applications. In this study, we have been synthesized incorporated omeprazole and omeprazole sulfide drugs with AgNPs and the results was investigated with TEM, FT-IR, DRS and XRD. The particle size has been seen in imaging TEM about 80 nm. Moreover either Omeprazole@AgNPs or omeprazole sulfide@AgNPs are able to excrete bacteria. In this study, the antibacterial properties of drugs with silver nanoparticles also increased.

People often make mistakes, so we try to automate every aspect of our lives. Sports is no exception. While just over a decade ago humans were analyzing games, today this is being done by artificial intelligence. Due to rapid development over the past decade, neural networks are now faster, more accurate, and in some areas even better than their human counterparts. In this paper, we present an algorithm that can detect player statistics during an NBA broadcast. It also helps users better understand the game and the use of augmented reality. The algorithm detects players on the court, tracks their movements, and assigns them to their respective teams. Using homography estimation, we transform the players’ positions from a three-dimensional space in the video to a two-dimensional space on the playing field plane. We define a new algorithm that predicts the players’ actions and their statistics. The results show that the proposed method can effectively identify the players, their respective teams, and their positions. It can also analyze their actions with high accuracy.

The motion of Unmanned Surface Vehicles (USVs) is frequently disturbed by the ocean wind, wave and current. A poorly designed controller will lead to failures and even safety problems during actual navigation. In order to obtain satisfied control performance of the motion for the USVs, a Model Predictive Control (MPC) based on improved Nonlinear Disturbance Observer (NDO) is proposed. Firstly, the USV model is approximately linearized and MPC is designed for the multivariable system with constraints. In order to compensate the influence of disturbances, an improved NDO is designed, with which the calculation time for the MPC saved a lot. Finally, comparison experiments are conducted between the MPC with NDO and the MPC with improved NDO, and the results show that they have similar performance to the USVs. However, the proposed method has less parameter to be tuned and it is much more time-saving compared to the MPC with traditional NDO.

This study examined the eye movement patterns of 317 elementary students across reading conditions (audio-assisted reading (AR) and reading-only (R)) and text types (fiction and non-fiction), and identified eye movement parameters that predict their literal comprehension (LC) and inferential comprehension (IC). Participants, randomly assigned to either reading condition and either text type, answered questions assessing their LC and IC. Average fixation duration (AFD), total fixation duration (TFD), and scanpath length were used as eye movement parameters. There were main effects of age on all parameters and interaction effects between age and reading condition on TFD and scanpath length. Controlling for age, TFD had a positive impact on LC of both text types in the AR, while under the R, it affected negatively on IC of both text types. Longer scanpaths predicted IC of fiction in the AR, LC and IC of non-fiction under the AR, and LC of non-fiction within the R. AFD influenced negatively on IC of fiction in the AR, LC and IC of non-fiction in the AR, and LC of non-fiction under the R. These eye movement patterns and predictors indicate children employ different reading strategies based on reading modality and text type.

Environmental nanoparticles have been shown to exist in most aquatic environments, and environmental nanoparticles in water distribution systems significantly affect water quality. However, little research has been conducted on the environmental nanoparticles in mineral water, which is a special water resource. Nanoparticle tracking analysis (NTA) and high-resolution transmission electron microscopy (HRTEM) were conducted. This study was the first to identify many environmental nanoparticles in natural mineral water in Zibo City, Shandong Province, China. The results of the NTA showed that the concentration of the particles was 5.5 ×106 particles/mL and the peak diameter of the size distribution was 180 nm. The HRTEM showed that the nanoparticles were granular, pinniform, rodlike, and flakey in shape, and some of the nanoparticles existed in aggregation. The energy-dispersive spectrometry results showed that most of the nanoparticles contained O, Mg, Ca, Si, Fe, Ti, and P, and some of them also contained F, V, S, and Mn. When combined with the characteristics of the selected area electron diffraction pattern, the nanoparticles were confirmed to be Ca-bearing nanoparticles, attapulgite nanorods, MnO2 nanosheets, and TiO2 nanoparticles. These results indicate a new form of elements occurring in mineral water. In addition, based on the chemical and physical characteristics of the nanoparticles and mineral water, these environmental nanoparticles in the mineral water are likely to be the weathering byproducts of minerals. These nanoparticles within mineral water provide a good opportunity for understanding the behavior of nanoparticles in varied systems. Moreover, environmental nanoparticle science is important for continuing efforts in water safety, treatment, and remediation.

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles (UAVs) is considered. Adaptive backstepping technology is used to design flight control schemes for quadrotor UAVs. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor UAVs and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during UAV flight under uncertain disturbances. Compared with the existing results, the novelty of this paper is that the proposed formation control scheme does not require the use of the quadrotor model parameters. Finally, a quadrotor UAV swarm system is used to verify the effectiveness of the proposed control scheme.

Emotion recognition and social inference impairments are well-documented post-traumatic brain injury (TBI) yet the mechanisms underpinning these are not fully understood. We examined dynamic emotion recognition, social inference abilities, and eye fixation patterns between adults with and without TBI. Eighteen individuals with TBI and 18 matched non-TBI participants were recruited and underwent all three components of The Assessment of Social Inference Test (TASIT). The TBI group were less accurate in identifying emotions compared to the non-TBI group. Individuals with TBI also scored lower when distinguishing sincere and sarcastic conversations but scored similarly to those without TBI during lie vignettes. Finally, those with TBI also had difficulty understanding the actor’s intentions, feelings, and beliefs compared to participants without TBI. No group differences were found for eye fixation patterns and there were no associations between fixations and behavioural accuracy scores. This conflicts with previous studies and might be related to an important distinction between static and dynamic stimuli. Visual strategies appeared goal- and stimulus-driven, with attention being distributed to the most diagnostic area of the face for each emotion. These findings suggest that low-level visual deficits may not be modulating emotion recognition and social inference disturbances post-TBI.

This study focuses on the recently emerged Internet of Vehicles (IoV) concept to provide an integrated agricultural vehicle/machinery tracking system through two leading low power wide area network (LPWAN) technologies, namely LoRa and NB-IoT. The main aim is to investigate the theoretical coverage limits by considering the urban, suburban, and rural environments. Two vehicle tracking units (VTUs) have been designed for LoRa and NB-IoT connectivity technologies that can be used as reference hardware in coverage analysis. On this basis, the closed-form explicit analytical expressions of the maximum transmission range have been derived using the Hata path loss model. Besides, the computer simulation results have been validated via the maps from XIRIO online radio planning tool. In light of the obtained findings, several evaluations have been made to enhance the LPWAN-based agricultural vehicle tracking feasibility in smart farms.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) is a commonly used technique for analyzing large biomolecules. However, the utilization of organic matrices limits the small-molecule analysis because of the interferences in the low-mass region and reproducibility issues. To overcome these limitations, a surface-assisted laser desorption/ionization (SALDI), which utilizes nanostructured metallic surfaces, has been developed. Herein, a novel approach for SALDI–MS was proposed using nanoengineered gold shell with nanogaps on the silica core (SiO2@Au NGS), which is an emerging material due to its excellent heat-generating capabilities. The gold shell thickness was controlled by adjusting the concentration of gold precursor for the growth of gold nanoparticles. SALDI-MS measurements were performed on a layer formed by drop-casting a mixture of SiO2@Au NGS and analytes. At the optimized process, the gold shell thickness was observed to be 17.2 nm, which showed the highest absorbance. The ion desorption efficiency was confirmed with a survival yield upon fragmentation. Based on the enhanced SALDI capability, SiO2@Au NGS was utilized to detect various small molecules including amino acids, sugars, and flavonoids. The limits of detection, reproducibility, and salt tolerance of SiO2@Au NGS demonstrate its potential as an effective and reliable SALDI material for small-molecule analyses.

Real-time tracking is one of the most challenging problems in computer vision. Most Transformer-based trackers usually require expensive computational and storage power, which leads to the inability of these robust trackers to achieve real-time performance in resource-constrained devices. In this work, we propose a lightweight tracker, AnteaTrack. To localize the target more precisely, we develop a scaling-invariant max-filtering operator employing a sliding window combined with local max-pooling, which filters out the suspected target from the feature and performs an augmented representation while suppressing the background. For a more tight bounding box, we employ Pixel-Shuffle to increase the resolution of the feature map and get a more fine-grained representation of the target. In addition, AnteaTrack can run in real-time at 47 frames per second(FPS) on the CPU. We tested AnteaTrack on 5 datasets, and a large number of experiments have shown that AnteaTrack provides the most efficient solution compared to the same type of CPU real-time trackers. The code will be available at https://github.com/cnchange/AnteaTrack.

This article explores the transformative role of neural networks in the realm of biology, particularly within microscopy image processing and illustrations. Neural networks have revolutionized cell segmentation and analysis, enabling precise delineation of cell boundaries and tracking of cellular behaviours. They excel in detecting subcellular structures, unravelling intricate organelle interactions. In 3D image reconstruction, neural networks navigate volumetric datasets, enhancing our understanding of spatial cellular architecture. These networks enhance disease diagnosis by identifying anomalies and irregularities, potentially revolutionizing early detection and classification. Moreover, neural networks restore and enhance microscopy images, unveiling hidden details. Lastly, they bridge art and science, fostering captivating biological art and enriching science communication. As neural networks evolve, they promise a future of limitless possibilities, weaving together technology, science, and art to illuminate the microscopic realm in unprecedented ways.

Taking advantage of fact that the surface electrons of metallic nanoparticles (NPs) can be effectively released even at a low voltage bias, we demonstrate an improvement in the electrochemical performance of nano-sized Prussian Blue (PB) based secondary batteries by the incorporation of bare Ag or Ni NPs onto the vicinity of the working PB NPs. It is found that the capacity for electrochemical energy storage of the 17-nm-PB-based battery is significantly higher than the capacity of 10-nm-PB-based, 35-nm-PB-based or 46-nm-PB-based batteries. There is a critical PB size for the highest electrochemical energy storage efficiency. The full specific capacity CF of the 17-nm-PB-based battery stabilized to 62 mAh/g after 130 charge-discharge cycles at a working current of IW = 0.03 mA. The addition of 14 mass-percent of Ag NPs in the vicinity of the PB NPs gives rise to a 32% increase in the stabilized CF. A 42% increase in the stabilized CF can be obtained with the addition of 14 mass-percent of Ag NPs on the working electrode of the 35-nm-PB-based battery. An enhancement of CF is also found for electrodes incorporating bare Ni NPs but the effect is smaller.

Polymeric based nanoparticles are garnering significant interest for their potential in drug delivery. Specially, nanopolymers that have been functionalized with molecules, such as proteins or peptides, are a versatile vehicle for drug delivery. Curcumin (Cur) is one of the most commonly studied anticancer compounds and is widely acknowledged as having positive effects on human health. However, its insolubility and low bio-distribution greatly hinder the exploitation of its beneficial traits. In this study, our team created a nano delivery system which utilized a nanopolymer called PCL-PEG (poly(ε-caprolactone)-poly (ethylene glycol)). This system was functionalized with A6 peptide to enable targeted delivery of Cur. The system was designed with advantageous nanoparticles (NPs), including a stable zeta potential (–32.7), small size (54.3), uniform surface morphology, and high hydrophilicity (13.72°). In addition, targeted delivery systems exhibited high encapsulation efficacy (93 ± 0.89 %), and drug loading (16.7 ± 0.9 %), and were characterized by a slow and gradual release profile with a release of approximately 83.13 ± 0.12%. The MTT assay results showed that the formulation known as Cur-NPs-A6 caused a significant increase in cell death in MDA-MB-231 cancer cells (IC50 = 23.31 ± 0.85 µM). The designed delivery system did not cause any harm to the noncancerous MCF-10A cells (normal group). Furthermore, the results of both the RT-qPCR and invasion assays demonstrated that the designed system was able to effectively activate the apoptosis pathway and inhibit cell invasion. Our findings suggest that the use of the designed smart delivery system, which is functionalized with A6 peptide that has a high affinity for CD44 receptor - known to be upregulated in numerous malignant conditions, could be a highly efficient approach to treating cancer.

This paper proposes two max-pooling engines, named the RTB-MAXP engine and the CMB-MAXP engine, with a scalable window size parameter for FPGA-based convolutional neural network (CNN) implementation. The max-pooling operation for the CNN can be decomposed into two stages, i.e., a horizontal axis max-pooling operation and a vertical axis max-pooling operation. These two one-dimensional max-pooling operations are performed by tracking the rank of the values within the window in the RTB-MAXP engine and cascading the maximum operations of the values in CMB-MAXP engine. Both the RBM-MAXP engine and the CMB-MAXP engine were implemented using VHSIC Hardware Description Language (VHDL) and verified by simulations. They have been employed for and tested in our CNN accelerator targeting at the CNN model YOLOv4-CSP-S-Leaky for object detection.

This paper studies the trajectory tracking control of an autonomous underwater vehicle (AUV) based on a stochastic uncertain nonlinear system. We investigate the time-varying gain adaptive control method looking for possible approaches to alleviate the heavy computational burden. Under nonlinear growth, conditions satisfy polynomial growth conditions. These two problems are resolved the fast response time and good path tracking, respectively. Novel adaptive algorithms are developed exploiting the dynamic properties of the AUV motion. By appropriately turning the original controller design problems into parameters choosing problems and then solving them in a functional time-varying observer technical theorem. In order to deal with the station error of system converges to arbitrarily small domains with stochastic uncertain disturbance. A coordinate transformation is proposed for all system states to meet boundedness. We show that the convergence of the AUV trajectory errors can be guaranteed by the proposed contraction constraints in the stability analysis, closed-loop stability is proved, and the system is asymptotically probabilistic in the global scope. They are taking advantage of the guaranteed stability. Extensive simulation studies on the AUV model demonstrate the effectiveness and robustness of the proposed approach. A real-time time-varying gain constructive control strategy is further developed for the Hardware-in-the-loop simulation; the controller design results are imported into the AUV actuator model to verify the effectiveness of the controller design.

In this review, we focus on a small section of the extensive literature that deals with the materials containing pristine defective CNs and those incorporated in the hybrid materials. We will discuss only those topics that focus on structural defects related to the introduction of perturbation into the surface topology of a nanostructure. We focus mainly on the method using microwave (MW) irradiation, which is a powerful tool for synthesizing and modifying carbon-based solid materials. In addition, the simplicity of the technique, economy, and the possibility of conducting the reaction in solvents and solid phase, in the presence of components of different chemical nature, allows use in various combinations. In this review, we will emphasize the advantages of synthesis using MW-assisted heating and indicate the influence of the structure of the obtained materials on their physical and chemical properties. We will also highlight the role of the occurrence of defects in the carbon material and the implication in designing their properties and applications.

Trypanosomes are the extracellular protozoan parasites that cause human African trypanosomiasis disease in humans and nagana disease in animals. The disease is endemic in African countries where tsetse flies which act as a vector for the transmission of disease are present. The animals infected by these parasites become useless or workless and disease can become fatal if not treated. Old drugs used for treatment have many side effects and some are responsible for death in 5% of the patients. The parasite possesses a major surface protein known as variant surface glycoprotein. The immune system of the host develops antibodies against this antigen but due to antigenic variation, parasites evade the immune response. Currently, no vaccine is available that provides complete protection. Only partial protection using certain antigens in murine models was investigated. The tools of molecular biology and immunology have enabled a novel approach to the development of vaccines against trypanosomes. Immunization is the sole method for the control of disease because the eradication of the vector from endemic areas is an impossible task. Genetic vaccines can carry multiple genes encoding different antigens of the same parasite or different parasites. DNA immunization induces the activation of both cellular immune response and humoral immune response along with the generation of memory. This review highlights the importance of DNA vaccines and advances in the development of DNA vaccines against T. brucei.

A class of controlled plants, whose dynamics is governed by a vector system of ordinary differential equations with a partially known right-hand side, is considered. The state variables and their velocities are assumed to be measurable. The aim is to design a controller which minimizes a loss function under certain constraints which arguments is the current state of the controlled plant. The designed control action is admitted to be a function of the current sub-gradient only, which supposed to be measurable on-line. The control design is based on ASG (Average Sub-Gradient method) — version of Integral Sliding Mode (ISM) concept, aimed to minimize on average a given convex (not obligatory strongly convex) cost function of the current state under a set of given constraints. An optimization type algorithm is developed and analyzed using ideas of SDM technique. The main results consist in proving the reachability of the "desired regime" (nonstationary analogue of sliding surface) from the beginning of the process and obtaining an explicit upper bound for the averaged loss function decrement, that is, the averaged in time functional convergence is proven and the rate of such convergence is estimated.

: The radar multi target tracking (MTT) technique requires prior knowledge of a number of parameters about the sensor, the target and backgrounds. The Integrated Track Splitting (ITS) is a fully automatic track-while-scan (TWS) target tracking algorithm capable of extracting and tracking a target in a dense clutter environment using quality false track discrimination (FTD) methodology. The computational complexity in ITS algorithm is limited, compared to other algorithms they use statistical methods to discriminate between false and true tracks, such as multiple hypothesis tracking (MHT), mainly due to the FTD performed. The paper provides an analysis of tracking parameters that allows determining the limit of the possibility of successful target tracking. Extensive experiments have confirmed that the recursive determination of the probability of the existence of a track during tracking can confirm a true track and reject a false track. The clutter density, number of random occurred targets, targets load during the maneuver and the target detection probability were varied. The results of experiments, carried out via Monte Carlo simulations, shown over representative confirmed true tracks (CTT) diagrams, root mean square error position and normalized tracking efficiency parametric diagrams allow the user to select optimal multi-target tracking parameters for different scenarios and clutter densities.

This paper investigates the problem of cooperative standoff tracking using multiple fixed-wing unmanned aerial vehicles (UAVs) with control input constraints. In order to achieve accurate target tracking in the presence of unknown background wind and target motion, a coordinated standoff target tracking algorithm is proposed. The objective of the research is to steer multiple UAVs to fly a circular orbit around a moving target with prescribed intervehicle angular spacing. To achieve this goal, two control laws are proposed, including relative range regulation and space phase separation. On one hand, a heading rate control law based on Lyapunov guidance vector field is proposed. The convergence analysis show that the UAVs can asymptotically converge to a desired circular orbit around the target, regardless of their initial position and heading. Through rigorous theoretical proof, it is concluded that the command signal of the proposed heading rate controller will not violate the boundary constraint on heading rate. On the other hand, a temporal phase is introduced to represent the phase separation and avoid discontinuity of the wrapped space phase angle. On this basis, a speed controller is developed to achieve equal phase separation. The proposed airspeed controller met the requirement of airspeed constraint. In addition, to improve the robustness of the aircraft during target tracking, an estimator is developed to estimate the composition velocity of the unknown wind and target motion. The proposed estimator uses the offset vector between the UAV’s actual flight path and the desired orbit which is defined by Lyapunov guidance vector field to estimate the composition velocity. The stability of the estimator is proved. Simulations are conducted under different scenarios to demonstrate the effectiveness of the proposed cooperative standoff target tracking algorithm. The simulation results of indicate that, the temporal-phase-based speed controller can achieve fast convergence speed and small phase separation error. Additionally, the composition velocity estimator exhibits fast response speed and high estimation accuracy.

The response of plasmonic metal particles to an electromagnetic wave undergoes significant features at the nanoscale level. Different properties of the internal composition of a metal, such as its ionic background and the free electron gas, begin to manifest more prominently. As the dimensions of the nanostructures decrease, the classical local theory gradually becomes inadequate. Therefore, Maxwellʹs equations need to be supplemented with a relationship determining the dynamics of current density which is the essence of nonlocal plasmonic models. In this field of physics, the standard (linearized) hydrodynamic model (HDM) has been widely adopted with great success, serving as the basis for a variety of simulation methods. However, ongoing efforts are also being made to expand and refine it. Recently, the GNOR (general nonlocal optical response) modification of the HDM has been used, with the intention of incorporating the influence of electron gas diffusion. Clearly, from the classical description of fluid dynamics, a close relationship between viscosive damping and diffusion arises. This offers a relevant motivation for introducing the GNOR modification in an alternative manner. The standard HDM and its existing GNOR modification also do not include the influence of interband electron transitions in the conduction band and other phenomena that are part of many refining modifications of the Drude‐Lorentz and other models of metal permittivity. In this article, we present a modified version of GNOR‐HDM that incorporates the viscosive damping of the electron gas and a generalized Drude‐Lorentz term. In the selected simulations, we also introduce Landau damping which corrects the magnitude of the standard damping constant of the electron gas based on the size of the nanoparticle. We have chosen a spherical particle as a suitable object for testing and comparing HD models and their modifications because it allows finding precise analytical solutions for the interaction and, simultaneously, it is a relatively easily fabricable nanostructure in practice. Our contribution also includes our own analytical method for solving the HDM interaction of a plane wave with a spherical particle. This method forms the core of calculations of the characteristic quantities, such as the extinction cross‐sections and the corresponding components of electric fields and current densities.

Dialogue State Tracking is an essential component in multi-domain dialogue systems, aiming to accurately determine the current dialogue state based on the dialogue history. Existing research has addressed the issue of multiple mappings in dialogues by employing slot self-attention as a data-driven approach. However, learning the relationships between slots from a single sample has limitations and introduces noise. In this paper, we propose an External Slot Relation Memory-based Dialogue State Tracking model (ER-DST). By utilizing an external memory storage, we learn the relationships between slots as a dictionary of multi-domain slot relations. Additionally, we employ a small filter to discard slot information irrelevant to the current dialogue state. Experimental results on the MultiWOZ2.0 and MultiWOZ2.1 benchmarks demonstrate significant improvements while reducing the time complexity to O(n).

The present study produced and characterised chitosan, chitosan nanoparticle, chitosan n – benzaldehyde Schiff base, chitosan nanoparticle n – benzaldehyde Schiff base, Fe(III) chitosan n – benzaldehyde Schiff base and Fe(III) chitosan nanoparticle n – benzaldehyde Schiff base for biomedical application as antimicrobial agents. The materials were characterized with Fourier Transform Infrared spectroscopy, X-ray Diffractogram and biologically evaluated using disc diffusion method with three gram-positive bacteria. The FTIR absorption peaks were shifted to a lower wave number than the micro materials from which it was modified. These clearly indicate the linkage between phosphate, ammonium ion, Schiff base and Fe(III) metal. The diffracted peaks of Fe(III) chitosan nanoparticle n – benzaldehyde Schiff base were new peaks at 2θ = 24o and 42o when compare to the peak of Fe(III) chitosan n – benzaldehyde Schiff base of 2θ = 22.5o and 34o. The difference in peak shift were attributed to the ionic bonding of the complexation of Fe(III) with the blending of benzaldehyde to chitosan – Tpp backbone structure. Fe(III) chitosan nanoparticle Schiff base has more antimicrobial activity against same bacteria and fungi tested than Fe(III) chitosan n – benzaldehyde Schiff base, chitosan n – benzaldehyde Schiff base and chitosan. The antimicrobial activities of the synthesised six materials shown that the materials have high activities than the above – mentioned standard drugs.

In this article, copper(II) oxide, titanium dioxide and yttrium(III) oxide nanoparticles were added to Group III type base oil formulated with overbased calcium sulfonate. The nano-sized oxides were treated with ethyl oleate surface modification. The tribological properties of the homogenized oil samples were tested on a linear oscillating tribometer. Friction was continuously monitored during the tribological tests. Surface analysis was performed on the worn samples: the amount of wear was determined using a digital optical and confocal microscope. The type of wear was examined with a scanning electron microscope, while the additives adhered to the surface were examined with energy-dispersive X-ray spectroscopy. From the results of the measurements, it can be concluded that the surface-modified nanoparticles worked well with the overbased calcium sulfonate and significantly reduced both wear and friction. In the present tribology system, the optimal concentration of all three oxide ceramic nanoadditives is 0.4 wt%. By using oxide nanoparticles, friction can be reduced by up to 15% and the wear volume by up to 77%. Overbased calcium sulfonate and oxide ceramic nanoparticles together form a lower friction anti-wear boundary layer on the worn surfaces. It is advisable to further investigate the possibility of formulating nanoparticles into the oil.

In modern security situations, tracking multiple human objects in real-time within challenging urban environments is a critical capability for enhancing situational awareness, minimizing response time, and increasing overall operational effectiveness. Tracking multiple entities enables informed decision-making, risk mitigation, and the safeguarding of civil-military operations to ensure safety and mission success. This paper presents a multi-modal electro-optical/infrared (EO/IR) and radio frequency (RF) fused sensing (MEIRFS) platform for real-time human object detection, recognition, classification, and tracking in challenging environments. By utilizing different sensors in a complementary manner, the robustness of the sensing system is enhanced, enabling reliable detection and recognition results across various situations. Specifically designed Radar tag and thermal tag can be used to discriminate friendly and non-friendly objects. The system incorporates deep learning-based image fusion and human object recognition and tracking (HORT) algorithms to ensure accurate situation assessment. After integrating into an all-terrain robot, multiple ground tests were conducted to verify the consistent HORT in various environments. The MEIRFS sensor system has been designed to meet the Size, Weight, Power, and Cost (SWaP-C) requirements for installation on autonomous ground and aerial vehicles.

Abstract: Embodied pedagogy maintains that teaching and learning abstract concepts can benefit significantly from integrating bodily movements in the process. Here we explored the involvement of eye movements in the process of collective embodied learning of a concept in physics - angular velocity. Embodied learning was accomplished by the subjects forming a line that rotated around a central object, in this case, a bottle. We tracked the gaze resulting from eye and head movements in 12 subjects, who both actively participated in the collective embodied exercise and passively watched it. The tracking data of 7 of these 12 subjects passed our tracking reliability criteria in all trials and are reported here. During active learning, the learners tended to look ahead of the rotating line (by 35.18±14.82 degrees). In contrast, while passively watching others performing the task, the learners tended to look directly at the line. Interestingly, while the learners were performing the collective exercise they were unaware of looking ahead of the rotating line. We discuss possible differences between active and passive embodied learning that might be indicated by the observed differences in gaze control.

Concentrator photovoltaic (CPV) technology offers an alternative to conventional photovoltaic systems, focusing on the concentration of solar radiation through the optics of the system onto smaller and more efficient solar cells. However, the surface on which the solar beam is incident must remain oriented towards the position of the sun, which requires the use of large and heavy external elements known as solar trackers. In addition to their size, these elements must be as accurate as possible to avoid misalignment. To avoid the need of these solar trackers, the concept of tracking-integrated concentrating systems has been developed. This technology has been researched to make CPV systems accessible in places where conventional systems are not viable, such as building roofs or agrivoltaic fields. This review presents a detailed classification of the existing designs in the literature and providing an overview of this type of system. By eliminating the need for external solar trackers, tracking-integrated CPV systems offer a promising solution to increase the adoption of this technology. Therefore, it is expected that these systems will be a viable and effective option for solar power generation.

The rapid development of technology has led to the implementation of data-driven systems whose performance heavily relies on the amount and type of the data itself. In the latest decades, in the fields of bioengineering data management, among others, eye-tracking data has become one of the most interesting and essential components for many medical, psychological, and engineering research applications. However, despite the large usage of eye-tracking data in many studies and applications, a strong gap is still present in the literature regarding real-time data collection and management, which led to strong constraints for the reliability and accuracy of on-time results. To address this gap, this study aims to introduce a system that enables the collection, processing, real-time streaming, and storage of eye-tracking data. The system is developed by using Java programming language, WebSocket protocol, and Representational State Transfer (REST), improving the efficiency in transferring and managing eye-tracking data. Results were computed in two test conditions, i.e., local and online scenarios, within a time window of 100 seconds. The experiments conducted for this study were carried out by comparing the time delay between two different scenarios. Even if preliminary, results showed a significantly improved performance of data management systems in managing real-time data transfer. Overall, this system can significantly benefit the research community by providing real-time data transfer and storing the data, enabling more extensive studies using eye-tracking data.