Flight Method Research Articles

FUNGAL FLORA OF ROSETTE QUILLS IN THE NORTH AMERICAN PORCUPINE (ERETHIZON DORSATUM) IN THE NORTHEASTERN UNITED STATES.

The North American (NA) porcupine (Erethizon dorsatum) is a rodent species with specialized hair structures called quills designed to detach and penetrate into tissues of any human or animal coming into contact with them. The objective of this study was to characterize the fungal flora of the quills in the region of the rosette in wild NA porcupines to further define health risks to NA porcupines and any animal coming into contact with the quills. A total of 17 adult NA porcupines were sampled, and fungal culture was performed. Fungal organisms were cultured from 15 (88.2%) of 17 samples. Thirty-three isolates of 10 different fungal genera were cultured. The most frequently isolated fungi were Lodderomyces elongisporus (n = 7, 41.2%), Candida spp. (n = 3, 17.6%), and Penicillium spp. (n = 2, 11.8%). Eleven (64.7%) individuals grew multiple fungal organisms. In humans and animals quilled by porcupines, fungal culture should be considered in cases of infection, and if isolates resembling Candida spp. are isolated, matrix-assisted laser desorption-ionization time of flight or molecular methods are necessary to rule out L. elongisporus.

Enhancing radioactive environment exploration with bio-inspired swarm robotics: A comparative analysis of Lévy flight and stigmergy methods

Utilizing swarm robotics techniques can significantly enhance the efficiency of exploring and mapping hazardous environments, such as nuclear sites. Instead of relying on a single robot for exploration, employing multiple robots working in coordination allows for fast coverage and more comprehensive data collection. In this study, bio-inspired algorithms, specifically Lévy flight and stigmergy, are utilized to guide the robots' movements. The Lévy flight algorithm mimics the movement patterns observed in animals like sharks and honeybees during their search for food, while stigmergy involves indirect communication between agents through environmental traces. By integrating these algorithms with swarm robotics, the robots effectively explore radioactive environments, gather data, and generate detailed maps of the area. Our research delves into various aspects of exploration, including the influence of the number of deployed robots and their exposure to radiation. Comparative analysis reveals the efficacy of stigmergy as a superior approach for guiding swarm robot movements in radioactive environments. This study underscores the significant potential of employing collective robotics for exploration tasks in nuclear scenarios, highlighting the promising applications of swarm intelligence in enhancing safety and efficiency in hazardous environments.

First identification and genomic features of multidrug-resistant Citrobacter freundii ST669 strain isolated from a domesticated duck in Bangladesh

ObjectivesCitrobacter freundii is a prevalent source of nosocomial infections and a well-known cause of diarrheal diseases. In recent years, it has also become increasingly resistant to various antimicrobials. In this study, we screened and characterized a multidrug-resistant (MDR) C. freundii isolate obtained from a domesticated diseased duck to better understand the genetic features, molecular epidemiology, and underlying factors linked to the antimicrobial resistance genes (ARGs) and virulence factor genes (VFGs) of the isolate. MethodsThe C. freundii BAU_TM8 strain was isolated using culturing, staining, biochemical, polymerase chain reaction, and Matrix-assisted laser desorption/ionization-time of flight methods. The MDR properties of the strain were determined by a disk diffusion test. The genomic sequence of C. freundii BAU_TM8 was performed using the Illumina NextSeq2000 platform. The ARGs, VFGs, and genomic functional characteristics of the C. freundii BAU_TM8 strain were identified using several open-source databases. ResultsThe sequence type of this strain was ST669, and the pathogenicity index of the strain was 0.919. Moreover, the strain had an estimated genome length of 5,797,806 bp, harboring 62 contigs, a G + C content of 54.32 %, and five contig L50s with an N50 value of 443,947 bp. Using phylogenetic analysis, this strain was closely related to two strains isolated from human and environmental samples in the USA and China despite huge geographical distances. The C. freundii BAU_TM8 strain consisted of 40 AGRs encoding resistance to 19 antimicrobial categories, e.g., fluoroquinolones, macrolides, folate pathway antagonists, aminoglycosides, tetracyclines, cephalosporins, and others. According to the phenotypic assay and genome sequence, the sensitivity and specificity of resistance profiles of the strain were 100 % and 20 %, respectively. Moreover, the virulence factor database detected 66 VFGs in this strain. This strain contained 1581 subsystems, having 33 % subsystem coverage and 2275 genes encoding amino acid derivatives, carbohydrate metabolism, protein metabolism, cofactors, vitamins, prosthetic groups, pigments, respiration, motility and chemotaxis, stress response, DNA metabolism, nucleosides and nucleotides, and others. ConclusionsTo the best of our knowledge, this is the first WGS report of C. freundii from a domesticated duck in Bangladesh. The ubiquitous occurrence of ARGs and VFGs in the C. freundii BAU_TM8 strain detected in this study highlights the growing concern about antimicrobial resistance in humans, animals, and environments.

Free Flight Training as a Tool for Psittacine Reintroductions

As habitat loss and other threats accelerate, ecological restoration and reintroduction science are becoming progressively more important. The psittacines are among the most endangered bird groups and are prime candidates for restoration through reintroduction. Unfortunately, post-release survival of captive-raised animals is often quite low because, in part, of high predation rates, low site fidelity, poor flight ability, and low flock cohesion. Current best practices in parrot release hold the birds in captivity for a year or more and include distinct methods to address each of these challenges. Here, we conduct a small-scale, proof-of-concept study using free flight methods and human-socialized trained adult birds to hand raise and release a group of six fledgling Blue-and-yellow Macaws in their historical range in southeastern Brazil. All six released birds showed strong flock cohesion and fidelity to the release site, avoided predation, and survived without supplemental feeding for over one year. One bird was captured by local people but was recovered and rereleased and it has reintegrated into the group and is still alive and doing well. The human-socialized trained adult birds modeled both desirable behaviors (flocking, foraging, reacting to predators) and undesirable behaviors and they were returned to captivity before the conclusion of this study. Our study suggests that free flight training has great potential to help captive-raised young attain a broad array of vital skills needed for survival post-release.

Review on Security Range Perception Methods and Path-Planning Techniques for Substation Mobile Robots

The use of mobile robots in substations improves maintenance efficiency and ensures the personal safety of staff working at substations, which is a trend in the development of technologies. Strong electric and solid magnetic fields around high-voltage equipment in substations may lead to the breakdown and failure of inspection devices. Therefore, safe operation range measurement and coordinated planning are key factors in ensuring the safe operation of substations. This paper first summarizes the current developments that are occurring in the field of fixed and mobile safe operating range sensing methods for substations, such as ultra-wideband technology, the two-way time flight method, and deep learning image processing algorithms. Secondly, this paper introduces path-planning algorithms based on safety range sensing and analyzes the adaptability of global search methods based on a priori information, local planning algorithms, and sensor information in substation scenarios. Finally, in view of the limitations of the existing range awareness and path-planning methods, we investigate the problems that occur in the dynamic changes in equipment safety zones and the frequent switching of operation scenarios in substations. Furthermore, we explore a new type of barrier and its automatic arrangement system to improve the performance of distance control and path planning in substation scenarios.

An improved equilibrium optimization algorithm for feature selection problem in network intrusion detection

In this paper, an enhanced equilibrium optimization (EO) version named Levy-opposition-equilibrium optimization (LOEO) is proposed to select effective features in network intrusion detection systems (IDSs). The opposition-based learning (OBL) approach is applied by this algorithm to improve the diversity of the population. Also, the Levy flight method is utilized to escape local optima. Then, the binary rendition of the algorithm called BLOEO is employed to feature selection in IDSs. One of the main challenges in IDSs is the high-dimensional feature space, with many irrelevant or redundant features. The BLOEO algorithm is designed to intelligently select the most informative subset of features. The empirical findings on NSL-KDD, UNSW-NB15, and CIC-IDS2017 datasets demonstrate the effectiveness of the BLOEO algorithm. This algorithm has an acceptable ability to effectively reduce the number of data features, maintaining a high intrusion detection accuracy of over 95%. Specifically, on the UNSW-NB15 dataset, BLOEO selected only 10.8 features on average, achieving an accuracy of 97.6% and a precision of 100%.

Modelling and Analysis of Vector and Vector Vortex Beams Reflection for Optical Sensing

Light Detection and Ranging (LiDAR) sensors can precisely determine object distances using the pulsed time of flight (TOF) or amplitude-modulated continuous wave (AMCW) TOF methods and velocity using the frequency-modulated continuous wave (FMCW) approach. In this paper, we focus on modelling and analysing the reflection of vector beams (VBs) and vector vortex beams (VVBs) for optical sensing in LiDAR applications. Unlike traditional TOF and FMCW methods, this novel approach uses VBs and VVBs as detection signals to measure the orientation of reflecting surfaces. A key component of this sensing scheme is understanding the relationship between the characteristics of the reflected optical fields and the orientation of the reflecting surface. To this end, we develop a computational model for the reflection of VBs and VVBs. This model allows us to investigate critical aspects of the reflected field, such as intensity distribution, intensity centroid offset, reflectance, and the variation of the intensity range measured along the azimuthal direction. By thoroughly analysing these characteristics, we aim to enhance the functionality of LiDAR sensors in detecting the orientation of reflecting surfaces.

A novel LFSSA-LSTM algorithm for the remaining useful life prediction of lithium-ion batteries in whole life cycle

The accurate prediction of the remaining useful life (RUL) of lithium-ion batteries is essential to improve the safety of battery systems and optimize battery management strategies. Therefore, a new algorithm combining Sparrow search algorithm (SSA) improved by the Levy flight method and long short-term memory neural network (LSTM) is proposed in this paper. By extracting the National Aeronautics and Space Administration (NASA) battery aging datasets, the battery correlated health characteristics are obtained, and the deterioration trend of battery performance is effectively described. The sparrow search algorithm improved by the Levy flight method enhances the ability of the algorithm to jump out of the optimal solution. By using the improved algorithm, the hyper-parameter optimization problem of the long short-term memory network is solved, and the accuracy of the algorithm is improved. Finally, the probability density function is used to predict the remaining useful life of lithium-ion batteries, which effectively prevents the uncertainty caused by a single prediction result. Compared with long short-term memory neural network and the one optimized by a traditional sparrow search algorithm, the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) of the proposed algorithm are kept at 1.77 %, 2.24 %, and 1.25 %, respectively. The results indicate that the algorithm has better accuracy and fitting performance.

Optimization of automated anodizing plant efficiency and process prediction using Random Forest based Levy flight method

The anodizing process is mainly carried out by industrialists to protect aluminium components from corrosion and strengthen their physical and chemical behavior. The goal of this study is to minimize the total cycle time of aluminum anodizing by optimizing pre-treatment procedures and forecasting the anodization process time. The experiments were carried out at the GOLDEN ANODIZER premises, a local aluminum anodizing industry in Coimbatore, India. The relationship between various anodizing pre-treatment parameters such as Nitric bath pH, Caustic pH, alkaline pH, Mean time duration was optimized to reduce time without affecting output qualities like Surface finish (µm), Film thickness (µm), and correction (%). Also, the anodizing pre-treatment process parameters were predicted using a hybrid machine learning method called the Random Forest Levy Flight Algorithm (RF-LFA). The proposed RF-LFA shows 2–3 times better prediction performance than existing RF and deep neural networks.

Metabolic transformation of cyclopiazonic acid in liver microsomes from different species based on UPLC-Q/TOF-MS

To investigate the metabolic transformation of cyclopiazonic acid (CPA) in the liver of different species and to supplement accurate risk assessment information, the metabolism of CPA in liver microsomes from four animals and humans was studied using the ultra–high–performance liquid chromatography–quadrupole/time–of–flight method. The results showed that a total of four metabolites were obtained, and dehydrogenation, hydroxylation, methylation, and glucuronidation were identified as the main metabolic pathways of CPA. Rat liver microsomes exhibited the highest metabolic capacity for CPA, with dehydrogenated (C20H18N2O3) and glucuronic acid-conjugated (C26H28N2O10) metabolites identified in all liver microsomes except chicken, indicating significant species metabolic differences. Moreover, C20H18N2O3 was only detected in the incubation system with cytochromes P450 3A4 (CYP3A4). The hydroxylated (C20H20N2O4) and methylated (C21H22N2O3) metabolites were detected in all incubation systems except for the CYP2C9, with CYP3A4 demonstrating the strongest metabolic capacity. The “cocktail” probe drug method showed that CPA exhibited a moderate inhibitory effect on the CYP3A4 (IC50 value = 8.658 μM), indicating that the substrate had a negative effect on enzyme activity. Our results provide new insights to understand the biotransformation profile of CPA in animals and humans.

A New Method of UAV Swarm Formation Flight Based on AOA Azimuth-Only Passive Positioning

UAV swarm passive positioning technology only requires the reception of electromagnetic signals to achieve the positioning and tracking of radiation sources. It avoids the active positioning strategy that requires active emission of signals and has the advantages of good concealment, long acting distance, and strong anti-interference ability, which has received more and more attention. In this paper, we propose a new UAV swarm formation flight method based on pure azimuth passive positioning. Specifically, we propose a two-circle positioning model, which describes the positional deviation of the receiving UAV using trigonometric functions relative to the target in polar coordinates. Furthermore, we design a two-step adjustment strategy that enables the receiving UAV to reach the target position efficiently. Based on the above design, we constructed an optimized UAV swarm formation scheme. In experiments with UAV numbers of 8 and 20, compared to the representative comparison strategy, the proposed UAV formation scheme reduces the total length of the UAV formation by 34.76% and 55.34%, respectively. It demonstrates the effectiveness of the proposed method in the application of assigning target positions to UAV swarms.

Flight situational assessment based on complex network and MFIM-TOPSIS

In order to objectively and accurately assess the airborne flight posture in the trajectory-based operation (TBO) mode, a flight posture assessment method based on complex network and MFIM-TOPSIS is proposed. Firstly, the precise protection zone of different aircraft types is established by analyzing the risk of lateral collision between aircraft, and the flight conflict network is constructed by using the three-dimensional velocity barrier method, which is close to the TBO air operation environment, based on which six network topology indexes, such as total node degree, average point strength and network density, are selected to build the flight attitude assessment index system. To weaken the influence of the assessment subjectivity, an interaction matrix that can reflect subjective factors-objective factors is proposed. The maximum information coefficient is used to improve the coding of interaction matrix. Finally the flight attitude level status is assessed by using the superiority-disadvantage solution distance method. The simulation analysis and the example analysis of Takasaki Airport show that the evaluation model can accurately assess the air traffic situation and provide auxiliary information for controllers' decision making and command.

The development of the ultrasonic flowmeter sensors for mass flow rate measurement: A comprehensive review

A two-phase flow measuring device whose measurement system does not disturb the flow pattern, real-time measurement, and non-destructive measurement or non-intrusive model is a typical tool for an ideal situation. One measuring instrument that meets these criteria is an ultrasonic flow meter. Ultrasonic sensors can measure the velocity of fluid flow in pipelines. It has the advantage of high accuracy and reproducibility and does not make direct physical contact with the fluid in the pipe. Low fabrication costs and fast response make ultrasonic flowmeters widely used for two-phase flow measurements in both horizontal and vertical orientations. The void fraction or liquid holdup and velocity are the two most essential parameters for flow monitoring. The Time of Flight (ToF) method is mainly used for measurements in several ultrasonic flowmeter methods. In the present manuscript, the introductory section of this review explains the advantages of using the Time of Flight (ToF) method and its basic principles. This review also discusses research on measuring velocity and flow rate, differences in intrusive and non-intrusive measurement methods, parameters that affect ultrasonic measurements, and finally, measuring film thickness using non-intrusive methods.

Visual and machine strength gradings of Scots and red pine structural timber pieces from Türkiye

Scots (Pinus sylvestris L.) and red pine (Pinus brutia Ten.) structural timbers (540 pieces) from Türkiye were first visually graded according to TS 1265 (2012). Then, non-destructive tests were conducted using vibration and time of flight (ToF) methods, followed by destructive tests on a four-point bending test setup according to EN 408 (2012). The vibration method showed a higher correlation than ToF with strength and stiffness. The dynamic modulus of elasticity (MOEd) obtained by the vibration method was 12.3% and 15.4% lower in Scots and red pine, respectively, compared to the ToF method. Mechanical testing determined local MOE was 14% and 15% higher than global MOE for Scots and red pine, respectively. An alternative formula to the existing conversion formula in EN 384 (2018) was derived. The average bending strength of red pine was 7% higher than Scots pine. For visual strength grading, local and global MOE in Scots pine, class 1, 2, and 3 structural timbers were assigned to C35, C27, and C22, respectively. Red pine was assigned to C40, C27, and C24 for local MOE and C35, C24, and C22 for global MOE. In machine strength grading, the grade combination was C40-C30-C22-C16-R for both species. The best results were achieved in settings where vibration method and local MOE were used together. Machine strength grading achieved higher efficiency than visual strength grading.

Dynamic Event-Triggered Prescribed Performance Robust Control for Aggressive Quadrotor Flight

Aggressive flight has become increasingly important for expanding the applications of quadrotors. The typical characteristic of large and rapid changes in commands poses stringent demands on the maneuverability of quadrotors. Ensuring flight stability alone is not enough; dynamic responses must also be selectively constrained, presenting quadcopter flight control with daunting challenges. The prescribed performance control (PPC) method is seen as having the potential to solve this problem by allowing for the constrained control of specified performance, leading to extensive research. However, its practical application still faces challenges, such as the system divergence caused by errors exceeding boundaries due to sudden command mutations. This paper presents a robust dynamic event-triggered PPC (DETPPC) method for an aggressive quadrotor flight. By assessing the direction and proximity of tracking errors approaching constraint boundaries, a dynamic event-triggered compensation mechanism for performance function boundaries is established to mitigate the divergence caused by error surpassing and to preserve preset control over the targeted metrics. Controllers were designed for both the translational and rotational subsystems of the quadrotor, and stability analysis was conducted based on Lyapunov functions. Simulation tests on agile trajectory tracking and abrupt attitude control were carried out, demonstrating the effectiveness of the proposed method.

Energetic and exergetic metrics of a cargo aircraft turboprop propulsion system by using regression method for dynamic flight

Nowadays, the development of aviation in line with sustainability goals is one of the current challenges. Being a source of environmental impact, aero-engines have been the main research and design object for achieving these aims. In this study, thermodynamic analysis involving exergy and sustainability computations is performed at different flight conditions where Mach varies between 0 and 0.7 and altitude changes between 0 and 7.7 km. Based on this analysis, modeling exergy parameters for each component are carried out with multiple regression approach. The exergy efficiency of turboprop engine at dynamic flight conditions varies between 15% and 25.9% whereas it is measured between 76 and 77% for the combustor and between 93 and 99% for gas turbine. Moreover, exergy destruction of the turboprop engine changes between 2.15 MW and 7.55 MW. Exergetic improvement potential rate (IPR) of the combustor resides between 0.4 MW and 1.21 MW throughout flight conditions whereas it is found at orders of 0.1 MW or less for other components. On the other hand, linear and quadratic modelings are performed for several parameters of turboprop engine components including exergy efficiency, exergy destruction and IPR under dynamic flight conditions. The determination coefficient (R2) of the models changes between 0.69 and 0.98 in linear modeling, whereas R2 in quadratic modeling improves to 0.97 and 0.99 ranges. It is thought that component-based modeling by considering different flight conditions could contribute to determining points where component efficiency is the highest.

Comparison of isotype-specific nanobody enrichment with matrix-assisted laser desorption/ionisation-time of flight method with serum immunofixation electrophoresis in detection of paraproteins

Comparison of isotype-specific nanobody enrichment with matrix-assisted laser desorption/ionisation-time of flight method with serum immunofixation electrophoresis in detection of paraproteins

Анализ траекторий легкого лунного буксира с электрореактивной двигательной установкой

The work focuses on developing a lightweight lunar tug with an electric propulsion system for transporting cargo between promising near-Earth and near-lunar stations. The aim is to determine the ranges of transfer trajectory characteristics, considering realistic initial parameters: engine specifications, vehicle mass, launch date, and conditions. The lunar tug's design, solar panel parameters, and engine operating modes are provided. The flight scheme and method for designing transfer trajectories between near-Earth and near-Moon orbits are briefly described. The results of designing trajectories based on launch date, engine mode, and initial mass are presented and discussed.

Difference in Thickness Measurement by Laser Ultrasonic Technique Using Time of Flight Methods

Difference in Thickness Measurement by Laser Ultrasonic Technique Using Time of Flight Methods

Flight Test Fuel Saving Path Based on Green Aviation Perspective

With the continuous progress and development of the aviation industry, fuel consumption and carbon emissions have become important challenges for airlines. Therefore, from the perspective of green aviation, it is of great significance to explore the fuel-saving path of flight tests to reduce the fuel consumption and environmental impact of aviation operations. This path mainly includes optimizing air traffic management, improving aircraft fuel efficiency, strengthening fuel-saving operation training, and improving aviation fuel management. Through these measures, airlines can realize more economical and environmentally friendly flight methods and contribute to the sustainable development of the industry.