Flight Distance Research Articles

Plane Delay Simulator

Flight delays can be costly and inconvenient for both airlines and passengers. Accurately predicting flight delays can help airlines and passengers to plan accordingly and reduce the negative impact of delays. In this project, we propose to use a random forest algorithm to predict flight delays. We pre-process the data by encoding categorical variables and handling missing values. The data includes various flight-related features such as departure time, airline carrier, flight distance, and weather conditions at the origin and destination airports. To forecast flight delays, we next divide the data into different sets and train the model. We evaluate the performance of our model on the testing set using various metrics such as accuracy, precision, recall and F1-score. Our results show that, the random forest algorithm can effectively predict flight delays with an accuracy of over 80%.The most important features for predicting flight delays are found to be departure time, flight distance, and weather conditions. Our model demonstrates the potential of using the random forest algorithm for flight delay prediction, which can help airlines and passengers to plan accordingly and reduce the negative impact of delays.

Frequency scanning interferometry based deformation monitoring system for the alignment of the FCC-ee machine detector interface

In a particle accelerator, two particle beams are accelerated and collided at one or several physics detectors. The machine detector interface (MDI) is the place where the accelerator ring is linked to the physics detector. It is the area where the alignment requirements are the most stringent, and the MDI of the lepton version of the future circular collider (FCC-ee) is no exception. It will implement a complex design and alignment requirement for typical components in the MDI are of the order of 30 μm. Until now, no working solutions have been proposed for the alignment of such MDI. In this contribution, two different systems are studied: the Surveillance d’Ouvrages par Fibre Optique (Structural Monitoring by Optical Fibers, SOFO) and the in-lined multiplexed and distributed frequency scanning interferometry (FSI). Both systems allow individual and simultaneous distance measurements of multiple portions along a fiber, and a new system using the FSI technology is proposed for the alignment monitoring. Using a network of helical shaped fiber allows the measurement of deformations if a sufficient amount of fibers is placed on the cylinder. With a sensor measurement accuracy of 1 μm, 3D coordinates of points at the end of a 4 m long and 0.25 m radius cylinder (FCC-ee MDI dimensions) can be determined at an accuracy under 5 μm. This system will provide a link between the alignment of the final focusing quadrupoles and the rest of the machine.

Preference for partner or servant brand roles depends on consumers’ power distance belief

Anthropomorphism nests in both, persuasion, and marketing communications. This research examines anthropomorphized digital advertising brand message frames as either a servant or a partner. Across five studies, we demonstrate that the relationship between anthropomorphized digital advertising and willingness to pay/purchase intention depends on individual power distance belief. Low power distance belief consumers respond to brand-as-a-partner advertising more favorably while high power distance belief consumers are indifferent across both frames (Studies 1a–c). This conditional positive effect of partner message frame for low power distance belief consumers is mediated by consumers’ righteous anger induced by the message frame (Study 2 & 3). We conclude with contributions to theory, implications for practice, and directions for future inquiries.

Dynamic balance and explosive strength appears to better explain single leg hop test results among young elite female basketball athletes

To analyze the impact of balance, lower-limb explosive strength and anthropometric variables on the result of the hop test in young elite female basketball athletes. Ninety young elite female basketball athletes (13–17 years), without current or recent lower-limb injury, were assessed in the off-season period of July 2021. Single leg hop test, countermovement jump, Y balance test and anthropometric outcomes were assessed. A correlation study and a regression model were performed to investigate the influence of such outcomes and the value of their participation on the hop test results. It was found a low-to-moderate correlation effect size for both countermovement jump (distance and power flight) and Y balance test values (except interlimb outcomes) with the single leg hop test results. Anthropometric outcomes did not show significant correlation (p > 0.05). Regression model revealed that for right hop test, countermovement jump values exhibited an adjusted determination coefficient of 0.408, (β = 0.249, p = 0.013), For left hop test, again the countermovement jump values (β = 0.229, p = 0.025), and left Y balance test values (β = 0.331, p = 0.011) jointly obtained an adjusted determination coefficient of 0.263 significant predictive value for countermovement jump outcomes in both right (β = 0.249, p = 0.013; β = 0.301; p = 0.031) and left leg (β = 0.229, p = 0.025; β = 0.365, p = 0.040), as well as certain Y balance outcomes values. Explosive strength, and dynamic balance although to a lesser extent, appear to be the most relevant physical-functional factors influencing the single leg hop test results among young elite female basketball athletes. These findings may a serve as a basis to implement targeted interventions, such as plyometric and balance training, for an enhancement on functional rehabilitation and reducing the risk of injury related to the hop test results.

Theoretical study of general principle of high-resolution MALDI-linear time-of-flight mass spectrometry in middle to high m/z ranges

This work discusses general principles of high-resolution linear time-of-flight (TOF) mass spectrometers across a wide m/z range. Conventional instrument designs are unable to offer adequate performance across a wide m/z range due to inappropriate calculation. Based on big data analyses conducted using comprehensive flight-time topological calculations, high mass resolving power (Rm) is available when instrument dimensions and extraction parameters satisfy several preconditions. The result indicates that a longer flight distance does not necessarily provide higher Rm. The possibility to achieve high Rm for ions of m/z range 100–100,000 are high when the relative length of extraction and acceleration regions to overall instrument length satisfies specific ratios that distinct from conventional designs. With adequate instrument dimensions, achieving optimal Rm needs to optimize the voltages and extraction delay in the ion source. Simulation shows that a 900 mm-long instrument of ideal design can enhance Rm by more than 250 times (to the order of >100,000) in comparison to the extreme condition of conventional design for ions of m/z 100,000. This general principle can be applied to other TOF instruments of different sizes. The method to finding the ultimate parameters is thoroughly described.

The Influence of Age, Sex and Season on Andean Condor Ranging Behavior during the Immature Stage.

Immature individuals move from their natal area to the area where they settle and reproduce, and this may take several years. This process is essential for long-lived species such as vultures and condors, which spend long periods as immature and move extensively. We studied the movement behavior of 26 GPS-tagged immature Andean condors (Vultur gryphus) from northwestern Patagonia throughout the immature stage, analyzing whether these patterns differed according to age, sex and season. We found that season and age influenced home range size and flight distances, the warm season being when immature condors move most; movement patterns were greater in sub-adults than in juveniles. The age effect was associated with the sex of individuals, with males increasing their home range more than females. Our results provide the first description of how immature Andean condor movement patterns are affected by internal and external factors. This information could be key to understanding condor responses to environmental change and threats at different stages during their immature phase. Until now, condor conservation efforts have not considered the areas used by dispersing individuals. Our results increase our understanding of ranging behavior during the immature stage of this threatened bird, enabling us to improve the conservation policies and management strategies designed to protect them.

Operational Statistics for Rotary Wing Aero Medical Transportation In the United States (2020)

Aero medical transportation (AMT) services provide transportation of patients, medical teams, and organs for the U. S. healthcare system. Categories of AMT operations include scene response (33%), interfacility transfers (54%), delivering specialty care and organs (13%), and repatriation from outside the United States (statistics not recorded). Scene response is conducted primarily using rotary wing aircraft that can land and takeoff from accident scenes and hospital heliports. Data from 12 publicly available databases were combined to identify AMT vehicles and to generate operational statistics including the number of vehicles, ownership, flight distances, flight frequency, geographic distribution, and the types of airports, air traffic control, and navigation systems used. This information can be used for aircraft design, airport and air traffic control infrastructure assessment and funding allocation, industry sector analysis, and strategic planning.

The Impacts and Analysis of Individual and Social Risks of the Stochastic Emission of Benzene from Floating-Roof Tanks Using Response Surface Analysis and MPACT Model.

In the present study, the researchers used an integrated approach composed of response surface analysis (RSM) and MPACT model to predict fatality rates caused by benzene emitted from floating-roof tanks. RSM scenarios were configured in Expert Design (version 7.0) software using the central composite design (CCD) method and five variables of wind speed, relative humidity, atmospheric temperature, failure diameter, and emission height were considered. Continuous Pasquill-Gifford Gaussian model was used to estimate the results of the RSM scenarios. The response values were considered for exposure concentrations above 50ppm (slight damages), 150ppm (moderate damage), and 1000ppm (high damage). The analysis of individual and social risks for each scenario was done using the MPACT model in SAFETI program (version 8.22) by providing two variables of population characteristics and the frequency of tank wall failure. The results showed that atmospheric temperature, wind speed, failure diameter, and emission height have positive effects on the dispersion of the cloud of toxic benzene vapor with a concentration of 1000ppm. Intolerable individual risk distances were estimated to be lower for indoor environments than for outdoor. Maximum distances of intolerable individual risks for the worst-case scenarios were estimated up to 2500m from the emission point, which resulted from exposure to a concentration of 1000-ppm benzene. Results regarding the estimation of social risks showed that over 1600 fatalities should be expected under the worst-case scenarios. The three factors of high temperature, low wind speed, and low emission height play a major role in the occurrence of scenarios with the highest fatalities. High wind speed and high emission height were the most important factors in most scenarios with zero fatalities rate. Generally, the findings of this study show the necessity to provide an emergency response plan in the studied industry in both autumn and winter due to low wind speed. However, the coupling of the developed statistical models based on regional meteorological conditions with the MPACT model can help researchers to design an emergency response plan to deal with leakage incidents in petrochemical industries.

Improving Spatial and Elemental Associations in Analytical Field Ion Microscopy.

Chemically resolved atomic resolution imaging can give fundamental information about material properties. However, even today, a technique capable of such achievement is still only an ambition. Here, we take further steps in developing the analytical field ion microscopy (aFIM), which combines the atomic spatial resolution of field ion microscopy (FIM) with the time-of-flight spectrometry of atom probe tomography (APT). To improve the performance of aFIM that are limited in part by a high level of background, we implement bespoke flight path time-of-flight corrections normalized by the ion flight distances traversed in electrostatic simulations modeled explicitly for an atom probe chamber. We demonstrate effective filtering in the field evaporation events upon spatially and temporally correlated multiples, increasing the mass spectrum's signal-to-background. In an analysis of pure tungsten, mass peaks pertaining to individual W isotopes can be distinguished and identified, with the signal-to-background improving by three orders of magnitude over the raw data. We also use these algorithms for the analysis of a CoTaB amorphous film to demonstrate application of aFIM beyond pure metals and binary alloys. These approaches facilitate elemental identification of the FIM-imaged surface atoms, making analytical FIM more precise and reliable.

Opposing effects of vigilance and foraging on escape behaviour in hooded crows

Abstract Escape represents an important component of animals’ antipredator behaviour entailing both benefits and costs dependent on a moment an animal flees upon predator’s approach. In this study, I examined how the level of vigilance and foraging activity affected escape decision in the urban hooded crow Corvus cornix, predicting that alert distance (AD) and flight initiation distance (FID) should be positively affected by the level of vigilance and negatively affected by foraging activity, whereas buffer distance (BD) should be negatively affected by the level of vigilance and positively affected by foraging activity. Using LMMs it was shown that percent of time crows allocated to vigilance was positively correlated with AD and FID, whereas foraging activity of crows had negative impact on AD and FID. In addition, both AD and FID were positively related to starting distance (SD), while AD was also positively influenced by tree coverage. BD was positively affected by foraging activity and AD. This study demonstrated that more vigilant birds detected predators earlier, which is in accordance with the major function of vigilance. Also, it was shown that foraging crows delayed their escape, once the predator has been detected, as benefits of delayed flight, such as feeding on a profitable food item or within a profitable patch, may outweigh costs, which is consistent with the optimal escape theory.

Drones Do Not Drift between Nests in a Wild Population of Apis cerana.

The modes through which individuals disperse prior to reproduction has important consequences for gene flow in populations. In honey bees (Apis sp.), drones (males) reproduce within a short flight range of their natal nest, leaving and returning each afternoon within a narrow mating window. Drones are assumed to return to their natal nests as they depend on workers to feed them. However, in apiaries, drones are reported to regularly make navigation errors and return to a non-natal nest, where they are accepted and fed by unrelated workers. If such a "drone drift" occurred in wild populations, it could facilitate some further degree of dispersal for males, particularly if drones drift into host nests some distance away from their natal nest. Here, we investigated whether drone drift occurs in an invasive population of the Asian honey bee (Apis cerana). Based on the genotypes of 1462 drones from 19 colonies, we found only a single drone that could be considered a candidate drifter (~0.07%). In three other colonies, drones whose genotypes differed from the inferred queen were best explained by recent queen turnover or worker-laying. We concluded that drone drift in this population is low at best, and A. cerana drones either rarely make navigation errors in wild populations or are not accepted into foreign nests when they do so. We therefore confirm that drone dispersal distance is limited to the distance of daily drone flights from natal nests, a key assumption of both colony density estimates based on sampling of drone congregation areas and population genetic models of gene flow in honey bees.

Regrouping in Dairy Ewes—Effects on Productive Performance and Specific Behavioral Traits

The regrouping of ruminants is a common practice in dairy farms and is targeting at the improvement of milk production efficiency. However, changing the established hierarchy in a group affects both productivity and behavioral attributes. The aim of the present study was therefore to examine the possible effects of regrouping on milk yield, composition and several behavioral indices in dairy ewes. The experimental period was divided into two sub-periods of 20 days each. During the first period, 30 Chios ewes were used, while 15 Chios and 15 Karagouniko ewes were mixed during the second period. Milk yield, composition, oxidative stability, flow rate and number of kick responses during milking were recorded for each ewe. An isolation-flight distance test was also performed on a weekly basis. As indicated, the parameters recorded during the behavioral tests, such as the number of bleats, heart rate and flight distance, and the milk oxidation rate and number of kick responses were significantly increased immediately after regrouping compared to the following days during both sub-periods (p < 0.05). Moreover, milk yield was reduced in the second sub-period by 8.61% (p < 0.05). It can be concluded that regrouping could negatively influence productive and behavioral traits, and the effect was more pronounced when sheep of different breeds were mixed.

Increased grey wolf diurnality in southern Europe under human-restricted conditions.

Wolves have been the archetype of wildlife persecution by humans for centuries all over the world, and still are heavily persecuted in some regions. Facultative diurnal/nocturnal wild mammals are known to become more nocturnal when persecuted. Conversely, little is known regarding the possibility of wolves becoming more diurnal if not persecuted. We took advantage of a 9-year natural experiment of restricted human access to a restored coal mine debris dump to study the daily activity patterns of wolves under conditions of infrequent human presence. Results were compared with a paired control site with frequent human use. Circadian wolf activity was monitored using camera traps (3 years in human-restricted site; 2 years in control). Additionally, data from two GPS-GSM-collared wolves monitored in a second control site were also analyzed. In our control sites, wolves were nearly inactive during daylight hours. In contrast, in the human-restricted site wolves extended their activity toward noon, with a daily activity peak between 10:00 and 12:00, and showed some activity throughout the entire circadian 2-h interval cycle considered. Wolves clearly had higher diurnality in the human-restricted area with 78% greater incidence of capture with remote cameras during the day than in the control site. We suggest that the shift toward increased diurnality was related to the loss of fear of humans. Evidence in support of this hypothesis comes from flight initiation distance (FID) data. Wolves showed relatively short FIDs when faced with a human observer (range 70-183 m) in broad daylight at the human-restricted site, but were so afraid of humans in the control site that we were unable to conduct FID trials there. Based on these results, we suggest that wolves may increase their diurnality in those European countries with currently increasing movement of human populations from rural to urban areas and that do not conduct lethal control of wolves. This would represent a historical landmark for a species that has been persecuted for many centuries. However, such behavioral shifts could bring new human-wolf conflicts that would require new policies.

Flight distance at pasture and stress response during shearing in alpacas

Potential influence of management and handling procedures on alpacas’ behavioral and physiological responses has received little research attention so far and these are the first combined observations of alpacas' behavior with physiological stress assessment in Poland. Human influence on a farm animal can be measured by direct contact in neutral conditions and by an animal’s reactions during husbandry procedures. Quantifying the strength of the flight response toward approaching persons can help assess an individual’s suitability for use in various human–animal contact activities. Shearing is one of the potentially stressful husbandry procedures that can affect alpacas’ behavior and welfare. This study aimed to assess flight distance on the pasture and behavioral and physiological reactions during shearing in 34 alpacas. Two related questions have been raised: (1) do reactions to humans affect reactions to the shearing procedure? and (2) is shearing a stressful practice to alpacas based on both salivary cortisol and stress-related behavior? The flight distance toward humans (familiar and unfamiliar person) was measured. The stress reaction during shearing was assessed by behavioral observation and saliva sampling (to determine cortisol level). The animals that had a short flight distance to a familiar person also had a shorter flight distance to an unfamiliar one (P < 0.001). This study did not show that shorter flight distance to humans was connected with less intensive stress response during shearing. There was a difference (P < 0.001) between salivary cortisol levels before and after shearing, indicating that shearing is stressful for alpacas. It was observed that the later in order the animal was shorn, the fewer attempts to break free through abrupt movements were shown (P < 0.05). It was also noticed that the number of agonistic behaviors reduced as the shearing time increased (P < 0.05). Alpacas can adapt to stressful situations, and the animals most sensitive to stress should be shorn last.

Toxic temperatures: Bee behaviours exhibit divergent pesticide toxicity relationships with warming.

Climate change and agricultural intensification are exposing insect pollinators to temperature extremes and increasing pesticide usage. Yet, we lack good quantification of how temperature modulates the sublethal effects of pesticides on behaviours vital for fitness and pollination performance. Consequently, we are uncertain if warming decreases or increases the severity of different pesticide impacts, and whether separate behaviours vary in the direction of response. Quantifying these interactive effects is vital in forecasting pesticide risk across climate regions and informing pesticide application strategies and pollinator conservation. This multi-stressor study investigated the responses of six functional behaviours of bumblebees when exposed to either a neonicotinoid (imidacloprid) or a sulfoximine (sulfoxaflor) across a standardised low, mid, and high temperature. We found the neonicotinoid had a significant effect on five of the six behaviours, with a greater effect at the lower temperature(s) when measuring responsiveness, the likelihood of movement, walking rate, and food consumption rate. In contrast, the neonicotinoid had a greater impact on flight distance at the higher temperature. Our findings show that different organismal functions can exhibit divergent thermal responses, with some pesticide-affected behaviours showing greater impact as temperatures dropped, and others as temperatures rose. We must therefore account for environmental context when determining pesticide risk. Moreover, we found evidence of synergistic effects, with just a 3°C increase causing a sudden drop in flight performance, despite seeing no effect of pesticide at the two lower temperatures. Our findings highlight the importance of multi-stressor studies to quantify threats to insects, which will help to improve dynamic evaluations of population tipping points and spatiotemporal risks to biodiversity across different climate regions.

Research on Methods of Improving Fuel Efficiency

In recent years, the improvement of aircraft fuel efficiency has been one of the hot topics discussed by scientists. Especially in today's increasingly tense environment of fossil fuels, how to effectively improve the fuel efficiency of aircraft engines is an important scientific problem facing us. The improvement of aircraft fuel efficiency depends not only on high-performance engines, but also on the structural design of the aircraft itself. Therefore, if the aircraft structure can be optimized, it is bound to improve the fuel efficiency of the aircraft and make it have a better flight distance in actual flight. The purpose of this paper is to illustrate ways to reduce emissions while improving fuel efficiency. A small paper airplane experiment is introduced to study the influence of wing area on speed, time, lift, drag and lift drag ratio, so as to further explore the central theme of this paper, including the analysis of many physical models. It also includes many products and ideas that engineers are now designing.

Structured Urban Airspace Capacity Analysis: Four Drone Delivery Cases

A route network-based urban airspace is one of the initial operational concepts of managing the high-density very low-level (VLL) urban airspace for unmanned aircraft system (UAS) traffic management (UTM). For the conceptual urban airspace, it is necessary to perform a quantitative analysis of urban airspace to stakeholders for designing rules and regulations. This study aims to discuss the urban airspace capacity for four different operation types by applying different sequencing algorithms and comparing its results to provide insight and suggestions for different operation cases to assist airspace designers, regulators, and policymakers. Four drone delivery operation types that can be applied in the high-density VLL urban airspace are analysed using the suggested four metrics: total flight time; total flight distance; mission completion time; the number of conflicts. The metrics can be calculated from a flight planning algorithm that we proposed in our previous studies. The algorithm for multiple agents flight planning problems consists of an inner loop algorithm, which calculates each agent’s flight plan, and an outer loop algorithm, which determines the arrival and departure sequences. For each operation type, we apply two different outer loops with the same inner loop to suggest an appropriate sequencing algorithm. Numerical simulation results show tendencies for each type of operation with regard to the outer loop algorithms and the number of agents, and we analyse the results in terms of airspace capacity, which could be utilised for designing structures depending on urban airspace situations and environments. We expect that this study could give some intuition and support to policymakers, urban airspace designers, and regulators.

GA-DCTSP: An Intelligent Active Data Processing Scheme for UAV-Enabled Edge Computing

With the prosperous development of the Internet of Things (IoT), large numbers of IoT devices have been deployed in many scenarios to perceive the data of surroundings. To provide real-time service, devices prefer to transfer the data to servers for faster processing. However, in some special areas with limited communication infrastructure, devices cannot be directly connected to the Internet, so the requirements of data collection and processing are agnostic, which brings a huge challenge for real-time and dynamic data processing. We make the first attempt to tackle this challenge by proposing an Intelligent Active Data Processing Scheme (IADP) in unmanned aerial vehicle (UAV)-enabled edge computing. The main innovations of IADP are as follows: 1) when IoT devices generate or sense data, they can intelligently and proactively spread data or data information to other areas to inform UAV to collect; 2) our scheme combines active data processing with data deadline priority and artificial intelligence (AI)-based UAV trajectory optimization to achieve maximum data processing rate and minimum UAV flight cost. Specifically, genetic algorithm-deadline constraint traveling Salesman problem (GA-DCTSP) algorithm is proposed based on improved GA to achieve it; and 3) an intelligent data processing decision mechanism of optimally determining transmitting to UAV or edge server is proposed to further optimize network performance. Finally, the experimental results show that our proposed IADP increases the data processing rate by 48.77%–232.54% and reduces the UAV flight distance by 63.45%–88.36% compared with the existing schemes.

Robotic automation and unsupervised cluster assisted modeling for solving the forward and reverse design problem of paper airplanes

Although often regarded a childhood toy, the design of paper airplanes is subtly complex. The design space and mapping from geometry to distance flown is highly nonlinear and probabilistic where a single airplane design exhibits a multitude of trajectory forms and flight distances. This makes optimization and understanding of their behavior challenging for humans. By understanding the behavior of paper airplanes and predicting flight behavior, there is a potential to improve the design of aerial vehicles that operate at low Reynolds numbers. By developing a robotic system that can fabricate, test, analyze, and model the flight behavior in an unsupervised fashion, a wide design space can be reliably characterized. We find there are discrete behavioral groups that result in different trajectories: nose dive, glide, and recovery glide. Informed by this characterization we propose a method of using Gaussian mixture models to extract the clusters of the design space that map to these different behaviors. This allows us to solve both the forward and reverse design problem for paper airplanes, and also to perform efficient optimization of the geometry for a given target flight distance.

Data Collection Mechanism for UAV-Assisted Cellular Network Based on PPO

Unmanned aerial vehicles (UAVs) are increasingly gaining in application value in many fields because of their low cost, small size, high mobility and other advantages. In the scenario of traditional cellular networks, UAVs can be used as a kind of aerial mobile base station to collect information of edge users in time. Therefore, UAVs provide a promising communication tool for edge computing. However, due to the limited battery capacity, these may not be able to completely collect all the information. The path planning can ensure that the UAV collects as much data as possible under the limited flight distance, so it is very important to study the path planning of the UAV. In addition, due to the particularity of air-to-ground communication, the flying altitude of the UAV can have a crucial impact on the channel quality between the UAV and the user. As a mature technology, deep reinforcement learning (DRL) is an important algorithm in the field of machine learning which can be deployed in unknown environments. Deep reinforcement learning is applied to the data collection of UAV-assisted cellular networks, so that UAVs can find the best path planning and height joint optimization scheme, which ensures that UAVs can collect more information under the condition of limited energy consumption, save human and material resources as much as possible, and finally achieve higher application value. In this work, we transform the UAV path planning problem into an Markov decision process (MDP) problem. By applying the proximal policy optimization (PPO) algorithm, our proposed algorithm realizes the adaptive path planning of UAV. Simulations are conducted to verify the performance of the proposed scheme compared to the conventional scheme.